How Tobacco Smoke Causes 

Disease: The Biology and 

Behavioral Basis for 

Smoking-Attributable Disease

A Report of the Surgeon General

2010

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

Public Health Service

Office of the Surgeon General

Rockville, MD
National Library of Medicine Cataloging in Publication

How tobacco smoke causes disease: the biology and behavioral basis for smoking-attributable 

disease : a report of the Surgeon General. – Rockville, MD : Dept. of Health and Human Services, 

Public Health Service, Office of Surgeon General, 2010.

p. 704

Includes bibliographical references.

1. Tobacco – adverse effects. 2. Smoking – adverse effects. 3. Disease – etiology. 4. Tobacco Use 

Disorder – complications. 5. Tobacco Smoke Pollution – adverse effects. I. United States. 

Public Health Service. Office of the Surgeon General. II. United States. Office on Smoking 

and Health.

QV 137 H847 2010

U.S. Department of Health and Human Services

Centers for Disease Control and Prevention

National Center for Chronic Disease Prevention and Health Promotion

Office on Smoking and Health

This publication is available on the World Wide Web at

http://www.surgeongeneral.gov/library

Suggested Citation

U.S. Department of Health and Human Services. How Tobacco Smoke Causes Disease: The Biology 

and Behavioral Basis for Smoking-Attributable Disease: A Report of the Surgeon General. Atlanta, 

GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, 

National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and 

Health, 2010.

For sale by the Superintendent of Documents, U.S. Government Printing Office, Washington, DC 

20402. ISBN 978-0-16-084078-4

Use of trade names is for identification only and does not constitute endorsement by the 

U.S. Department of Health and Human Services. Any recommendations expressed by 

nongovernmental individuals or organizations do not necessarily represent the views or opinions 

of the U.S. Department of Health and Human Services.
Message from Kathleen Sebelius

Secretary of Health and Human Services

Tobacco use imposes enormous public health and financial costs on this nation—costs that 

are completely avoidable. Until we end tobacco use, more people will become addicted, more people will 

become sick, more families will be devastated by the loss of loved ones, and the nation will continue 

to incur damaging medical and lost productivity costs. Now is the time to fully implement proven and 

effective interventions that reduce tobacco-caused death and disease and to help end this public health 

epidemic once and for all.

Cigarettes are responsible for approximately 443,000 deaths—one in every five deaths—each year 

in the United States. The chronic diseases caused by tobacco use lead the causes of death and disability 

in the United States and unnecessarily strain our health care system. The economic burden of cigarette 

use includes more than $193 billion annually in health care costs and loss of productivity.

We can prevent the staggering toll that tobacco takes on individuals, families, and communities. 

This new Surgeon General’s report focuses on cigarettes and cigarette smoke to provide further 

evidence on how cigarettes cause addiction and premature death. It identifies better approaches to 

helping people stop smoking and brings to light new ideas for how to lower the incidence of smokingcaused disease.

Twenty years of successful state efforts show that the more states invest in tobacco control 

programs, the greater the reductions in smoking, and the longer states maintain such programs, the 

greater and faster the impact. The largest impacts come when we increase tobacco prices, ban smoking 

in public places, offer affordable and accessible cessation treatments and services, and combine media 

campaigns with other initiatives. We have outlined a level of state investment in comprehensive 

tobacco control and prevention efforts that, if implemented, would result in an estimated five million 

fewer smokers over the next five years. Hundreds of thousands of premature deaths caused by tobacco 

use could be prevented, and many fewer of the nations’ children would be deprived by premature 

death of their aunts, uncles, parents, and grandparents. Importantly, in 2009 the U.S. Food and Drug 

Administration received statutory authority to regulate tobacco products. This has the potential to lead 

to even greater progress in reducing morbidity and mortality from tobacco use.

Tobacco prevention and control efforts need to be commensurate with the harm caused by tobacco 

use. Otherwise, tobacco use will remain the largest cause of preventable illness and death in our nation 

for decades to come. When we help Americans quit tobacco use and prevent our youth from ever 

starting, we all benefit. Now is the time for comprehensive public health and regulatory approaches to 

tobacco control. We have the knowledge and tools to largely eliminate tobacco caused disease. If we 

seize this moment, we will make a difference in all of our communities and in the lives of generations 

to come.

i

Foreword

In 1964, the first Surgeon General’s report on the effects of smoking on health was released. In 

the nearly 50 years since, extensive data from thousands of studies have consistently substantiated the 

devastating effects of smoking on the lives of millions of Americans. Yet today in the United States, 

tobacco use remains the single largest preventable cause of death and disease for both men and women. 

Now, this 2010 report of the Surgeon General explains beyond a shadow of a doubt how tobacco smoke 

causes disease, validates earlier findings, and expands and strengthens the science base. Armed with 

this irrefutable data, the time has come to mount a full-scale assault on the tobacco epidemic. 

More than 1,000 people are killed every day by cigarettes, and one-half of all long-term smokers 

are killed by smoking-related diseases. A large proportion of these deaths are from early heart attacks, 

chronic lung diseases, and cancers. For every person who dies from tobacco use, another 20 Americans 

continue to suffer with at least one serious tobacco-related illness. But the harmful effects of smoking do not end with the smoker. Every year, thousands of nonsmokers die from heart disease and lung 

cancer, and hundreds of thousands of children suffer from respiratory infections because of exposure 

to secondhand smoke. There is no risk-free level of exposure to tobacco smoke, and there is no safe 

tobacco product. 

This new Surgeon General’s report describes in detail the ways tobacco smoke damages every 

organ in the body and causes disease and death. We must build on our successes and more effectively 

educate people about the health risks of tobacco use, prevent youth from ever using tobacco products, 

expand access to proven cessation treatments and services, and reduce exposure to secondhand smoke. 

Putting laws and other restrictions in place, including making tobacco products progressively less 

affordable, will ultimately lead to our goal of a healthier America by reducing the devastating effects 

of smoking. 

The Centers for Disease Control and Prevention (CDC), the U.S. Food and Drug Administration 

(FDA), and other federal agencies are diligently working toward this goal by implementing and supporting policies and regulations that strengthen our resolve to end the tobacco epidemic. CDC has 

incorporated the World Health Organization’s MPOWER approach into its actions at the local, state, 

and national levels. MPOWER consists of six key interventions proven to reduce tobacco use that can 

prevent millions of deaths. CDC, along with federal, state, and local partners, is committed to monitoring the tobacco epidemic and prevention policies; protecting people from secondhand smoke where 

they live, work, and play; offering quit assistance to current smokers; warning about the dangers of 

tobacco; enforcing comprehensive restrictions on tobacco advertising, promotion, and sponsorship; 

and raising taxes and prices on tobacco products.

In 2009, the Family Smoking Prevention and Tobacco Control Act was enacted, giving FDA 

explicit regulatory authority over tobacco products to protect and promote the health of the American 

public. Among other things, this historic legislation gave the agency the authority to require companies to reveal all of the ingredients in tobacco products—including the amount of nicotine—and to 

prohibit the sale of tobacco products labeled as “light,” “mild,” or “low.” Further, with this new regulatory mandate, FDA will regulate tobacco advertising and require manufacturers to use more effective 

warning labels, as well as restrict the access of young people to their products. FDA will also assess and 

regulate modified risk products, taking into account the impact their availability and marketing has on 

initiation and cessation of tobacco use.

Reducing the tremendous toll of disease, disability, and death caused by tobacco use in the United 

States is an urgent need and a shared responsibility. All public health agencies need to partner together 

to develop common strategies to combat the dangers of smoking and tobacco use and defeat this 

epidemic for good.
ii

This 2010 Surgeon General’s report represents another important step in the developing recognition, both in this nation and around the world, that tobacco use is devastating to public health. Past 

investments in research and in comprehensive tobacco control programs—combined with the findings 

presented by this new report—provide the foundation, evidence, and impetus to increase the urgency 

of our actions to end the epidemic of tobacco use.

Thomas R. Frieden, M.D., M.P.H. 

 

 

 

 

Margaret A. Hamburg, M.D.

Commissioner of Food and Drugs

U.S. Food and Drug Administration

Director 

Centers for Disease Control and Prevention 

and 

Administrator 

Agency for Toxic Substances and Disease Registry
iii

Preface

from the Surgeon General,

United States Public Health Service

In 1964, the Surgeon General released a landmark report on the dangers of smoking. During the 

intervening 45 years, 29 Surgeon General’s reports have documented the overwhelming and conclusive 

biologic, epidemiologic, behavioral, and pharmacologic evidence that tobacco use is deadly. Our newest 

report, How Tobacco Smoke Causes Disease, is a comprehensive, scientific discussion of how mainstream and secondhand smoke exposures damage the human body. Decades of research have enabled 

scientists to identify the specific mechanisms of smoking-related diseases and to characterize them in 

great detail. Those biologic processes of cigarette smoke and disease are the focus of this report. 

One-third of people who have ever tried smoking become daily smokers. This report investigates how and why smokers become addicted and documents how nicotine compares with heroin and 

cocaine in its hold on users and its effects on the brain. The way tobacco is grown, mixed, and processed 

today has made cigarettes more addictive than ever before. Because of this, the majority of smokers who 

try to quit on their own typically require many attempts. It is imperative that we use this information to 

prevent initiation, make tobacco products less addictive, and provide access to treatments and services 

to help smokers quit successfully. 

This new report also substantiates the evidence that there is no safe level of exposure to cigarette 

smoke. When individuals inhale cigarette smoke, either directly or secondhand, they are inhaling more 

than 7,000 chemicals: hundreds of these are hazardous, and at least 69 are known to cause cancer. The 

chemicals are rapidly absorbed by cells in the body and produce disease-causing cellular changes. This 

report explains those changes and identifies the mechanisms by which the major classes of the chemicals in cigarette smoke contribute to specific disease processes. In addition, the report discusses how 

chemicals in cigarette smoke impair the immune system and cause the kind of cellular damage that 

leads to cancer and other diseases. Insight is provided as to why smokers are far more likely to suffer 

from chronic disease than are nonsmokers.

By learning how tobacco smoke causes disease, we learn more about how chemicals harm cells, 

how genes may make us susceptible, and how tobacco users become addicted to nicotine. The answers 

to these questions will help us to more effectively prevent tobacco addiction and treat tobacco-caused 

disease. Understanding the complexity of genetic, biochemical, and other influences discussed in this 

report offers the promise of reducing the disease burden from tobacco use through earlier detection 

and better treatment; however, even with all of the science presented here, it currently remains true 

that the only proven strategies to reduce the risks of tobacco-caused disease are preventing initiation, 

facilitating cessation, and eliminating exposure to secondhand smoke. 

My priority as Surgeon General is the health of the American people. Although we have made great 

strides in tobacco control, more than 440,000 deaths each year are caused by smoking and exposure to 

secondhand smoke. The cost to the nation is tremendous: a staggering amount is spent on medical care 

and lost productivity. But most importantly there is immeasurable cost in human suffering and loss. 

In 1964, Surgeon General Luther Terry called for “appropriate remedial actions” to address the 

adverse effects of smoking. With this report, the devastating effects of smoking have been characterized in great detail and the need for appropriate remedial action is even more apparent. The harmful 

effects of tobacco smoke do not end with the users of tobacco. There is no safe level of exposure to 

tobacco smoke. Every inhalation of tobacco smoke exposes our children, our families, and our loved 

ones to dangerous chemicals that can damage their bodies and result in life-threatening diseases such 

as cancer and heart disease. And, although not a focus of this report, we know that smokeless tobacco 

causes cancer and has other adverse health effects. The science is now clear that “appropriate remedial 

actions” include protecting everyone in the country from having to breathe secondhand smoke; making all tobacco products progressively less affordable; expanding access to proven cessation treatments 
iv

and services; taking actions at the federal, state, and local levels to counteract the influence of tobacco 

advertising, promotions, and sponsorship; and ensuring that all adults and children clearly understand 

that the result of tobacco use is addiction, suffering, reduced quality of life, and all too often, early 

death. Forty-five years after Surgeon General Terry called on this nation to act, I say, if not now, when? 

The health of our nation depends on it. 

 Regina Benjamin, M.D., M.B.A.

Surgeon General
v

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Acknowledgments

This report was prepared by the U.S. Department of Health 

and Human Services under the general direction of the 

Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, 

Office on Smoking and Health.

Vice Admiral Regina Benjamin, M.D., M.B.A., Surgeon 

General, U.S. Public Health Service, Office of the Assistant 

Secretary for Health, Office of the Surgeon General, Office 

of the Secretary, U.S. Department of Health and Human 

Services, Washington, D.C.

Rear Admiral Boris Lushniak, M.D., M.P.H., Deputy Surgeon General, U.S. Public Health Service, Office of the 

Assistant Secretary for Health, Office of the Surgeon General, Office of the Secretary, U.S. Department of Health 

and Human Services, Washington, D.C.

Rear Admiral Christopher Halliday, D.D.S., M.P.H., Chief 

of Staff, U.S. Public Health Service, Office of the Assistant 

Secretary for Health, Office of the Surgeon General, Office 

of the Secretary, U.S. Department of Health and Human 

Services, Washington, D.C.

Mary Beth Bigley, Dr.P.H., M.S.N., A.N.P., Acting Director of the Office of Science and Communication, Office of 

the Surgeon General, Office of the Assistant Secretary for 

Health, Office of the Secretary, U.S. Department of Health 

and Human Services, Washington, D.C.

Rear Admiral (Retired) Steven K. Galson, M.D., M.P.H., 

former Acting Surgeon General, U.S. Public Health Service, Office of the Surgeon General, Office of the Assistant 

Secretary for Health, Office of the Secretary, U.S. Department of Health and Human Services, Washington, D.C.

Rear Admiral (Retired) Kenneth P. Moritsugu, M.D., 

M.P.H., former Acting Surgeon General, U.S. Public 

Health Service, Office of the Surgeon General, Office of 

Public Health and Science, Office of the Secretary, U.S. 

Department of Health and Human Services, Washington, 

D.C.

Rear Admiral (Retired) Carol A. Romano, Ph.D., R.N., 

F.A.A.N., former Acting Deputy Surgeon General, U.S. 

Public Health Service, Office of the Surgeon General, 

Office of Public Health and Science, Office of the Secretary, U.S. Department of Health and Human Services, 

Washington, D.C.

Rear Admiral (Retired) David Rutstein, M.D., M.P.H., former Acting Deputy Surgeon General, U.S. Public Health 

Service, Office of the Assistant Secretary for Health, Office 

of the Surgeon General, Office of the Secretary, U.S. 

Department of Health and Human Services, Washington, 

D.C.

Rear Admiral (Retired) Robert C. Williams, P.E., D.E.E., 

former Acting Deputy Surgeon General, U.S. Public 

Health Service, Office of the Surgeon General, Office of 

the Assistant Secretary for Health, Office of the Secretary, 

U.S. Department of Health and Human Services, Washington, D.C.

Thomas R. Frieden, M.D., M.P.H., Director, Centers for 

Disease Control and Prevention, Atlanta, Georgia.

Ursula Bauer, Ph.D., Director, National Center for Chronic 

Disease Prevention and Health Promotion, Centers for 

Disease Control and Prevention, Atlanta, Georgia.

Barbara Bowman, Ph.D., Associate Director for Science, 

National Center for Chronic Disease Prevention and 

Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.

Samuel F. Posner, Ph.D., Associate Director for Science 

(Acting), National Center for Chronic Disease Prevention 

and Health Promotion, Centers for Disease Control and 

Prevention, Atlanta, Georgia.

Tim A. McAfee, M.D., M.P.H., Director, Office on Smoking 

and Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control 

and Prevention, Atlanta, Georgia.

Terry F. Pechacek, Ph.D., Associate Director for Science, Office on Smoking and Health, National Center for 

Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.

The editors of the report were

David Sidransky, M.D., Senior Scientific Editor, Professor, 

Otolaryngology-Head & Neck Surgery, Oncology, Pathology, Urology, Cellular and Molecular Medicine, and Director, Head and Neck Cancer Research, The Johns Hopkins 

University School of Medicine, Johns Hopkins Medical 

Institutions, Baltimore, Maryland. 
Surgeon General’s Report

vi

Leslie A. Norman, Managing Editor, Office on Smoking 

and Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control 

and Prevention, Atlanta, Georgia.

Anne McCarthy, Technical Editor, Northrop Grumman 

supporting National Center for Health Marketing, Division of Creative Services, Centers for Disease Control and 

Prevention, Atlanta, Georgia.

Peter L. Taylor, M.B.A., Technical Editor, Senior Editor, 

Palladian Partners, Silver Spring, Maryland.

Contributing editors were

David L. Ashley, Ph.D., Chief, Emergency Response and 

Air Toxicants Branch, Division of Laboratory Sciences,

National Center for Environmental Health, Centers for 

Disease Control and Prevention, Atlanta, Georgia.

Neal L. Benowitz, M.D., Professor of Medicine and Biopharmaceutical Sciences and Chief, Division of Clinical 

Pharmacology and Experimental Therapeutics, University 

of California, San Francisco, California.

Dorothy Hatsukami, Ph.D., Forster Family Professor in 

Cancer Prevention, Professor of Psychiatry, University of 

Minnesota Tobacco Use Research Center, University of 

Minnesota, Minneapolis, Minnesota.

Stephen S. Hecht, Ph.D., Wallin Professor of Cancer Prevention, Masonic Cancer Center, University of Minnesota, 

Minneapolis, Minnesota.

Jack E. Henningfield, Ph.D., Vice President Research and 

Health Policy, Pinney Associates, Bethesda, Maryland; and 

Professor, Adjunct, Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University School of 

Medicine, Baltimore, Maryland.

Patricia Richter, Ph.D., DABT, Toxicologist, Office on 

Smoking and Health, National Center for Chronic Disease 

Prevention and Health Promotion, Centers for Disease 

Control and Prevention, Atlanta, Georgia.

Jonathan M. Samet, M.D., M.S., Professor and Chairman, 

Department of Epidemiology, Bloomberg School of Public 

Health, The Johns Hopkins University, Baltimore, Maryland (1994–2008); and Director, USC Institute for Global 

Health, and Chairman, Department of Preventive Medicine, Keck School of Medicine, University of Southern 

California, Los Angeles, California (2008–present).

Gayle C. Windham, Ph.D., M.S.P.H., Research Scientist 

Supervisor, Chief, Environmental Surveillance Unit, Division of Environmental and Occupational Disease Control, 

California Department of Public Health, Richmond, California. 

Contributing authors were

David L. Ashley, Ph.D., Chief, Emergency Response and 

Air Toxicants Branch, Division of Laboratory Sciences,

National Center for Environmental Health, Centers for 

Disease Control and Prevention, Atlanta, Georgia.

Timothy B. Baker, Ph.D., Professor of Medicine, University 

of Wisconsin School of Medicine and Public Health, Madison, Wisconsin. 

Steve A. Belinsky, Ph.D., Director, Lung Cancer Program, 

Senior Scientist, Lovelace Respiratory Research Institute, 

Albuquerque, New Mexico.

Neal L. Benowitz M.D., Professor of Medicine and Biopharmaceutical Sciences and Chief, Division of Clinical 

Pharmacology and Experimental Therapeutics, University 

of California, San Francisco, California.

Tomoku Betsuyaku, M.D., Ph.D., Associate Professor, First 

Department of Medicine, Hokkaido University School of 

Medicine, Sapporo, Japan. 

Ann M. Bode, Ph.D., Research Professor and Associate 

Director, The Hormel Institute, University of Minnesota, 

Austin, Minnesota.

Anne Burke, M.D., Assistant Professor of Medicine, Gastroenterology Division, University of Pennsylvania School 

of Medicine, Philadelphia, Pennsylvania. 

David M. Burns, M.D., Professor Emeritus, Department of 

Family and Preventive Medicine, School of Medicine, University of California, San Diego, California.

Rebecca Buus, Ph.D., Health Scientist, Maternal and Infant 

Health Branch, Division of Reproductive Health, National 

Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, 

Georgia.

Laurie Chassin, Ph.D., Regents Professor of Psychology, 

Psychology Department, Arizona State University, Tempe, 

Arizona.
vii

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

David Christiani, M.D., M.P.H., Professor, Departments of 

Environmental Health and Epidemiology, Harvard School 

of Public Health, Harvard University, Boston, Massachusetts. 

Pamela I. Clark, M.S.P.H., Ph.D., Research Professor, 

School of Public Health, University of Maryland, College 

Park, Maryland.

John P. Cooke, M.D., Ph.D., Professor of Medicine, Stanford University, Stanford, California. 

Adolfo Correa, M.D., Ph.D., M.P.H., Medical Officer, Division of Birth Defects and Developmental Disabilities, 

National Center on Birth Defects and Developmental 

Disabilities, Centers for Disease Control and Prevention, 

Atlanta, Georgia.

Johannes Czernin, M.D., Professor, Molecular and Medical 

Pharmacology, and Chief, Ahmanson Biological Imaging 

Division, David Geffen School of Medicine, University of 

California, Los Angeles, California. 

Gerald N. DeLorenze, Ph.D., Research Scientist, Division 

of Research, Kaiser Permanente Northern California, Oakland, California. 

David M. DeMarini, Ph.D., Genetic Toxicologist, Integrated 

Systems Toxicology Division, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina.

Delia Dempsey, M.D., M.S., Assistant Professor, Pediatrics, 

Medicine and Clinical Pharmacology, Division of Clinical 

Pharmacology, University of California, San Francisco, 

San Francisco, California.

Phillip A. Dennis, M.D., Ph.D., Senior Investigator, Medical 

Oncology Branch, Center for Cancer Research, National 

Cancer Institute, National Institutes of Health, Bethesda, 

Maryland.

Yan Shirley Ding, Ph.D., Senior Service Fellow, Emergency Response and Air Toxicants Branch, Division of 

Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, 

Atlanta, Georgia.

Mirjana V. Djordjevic, Ph.D., Program Director, Tobacco 

Control Research Branch, Behavioral Research Program, 

Division of Cancer Control and Population Sciences, 

National Cancer Institute, National Institutes of Health, 

Bethesda, Maryland. 

Zigang Dong, M.D., M.S., Dr.P.H., Professor, The Hormel 

Institute, University of Minnesota, Austin, Minnesota.

Björn Eliasson, M.D., Ph.D., Associate Professor, Department of Internal Medicine, Sahlgrenska University Hospital, Göteborg, Sweden.

Lucinda England, M.D., M.S.P.H., Medical Epidemiologist, 

Maternal and Infant Health Branch, Division of Reproductive Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control 

and Prevention, Atlanta, Georgia.

Reginald Fant, Ph.D., Senior Scientist and Director, Pinney Associates, Bethesda, Maryland. 

Garret A. FitzGerald, M.D., Chair, Department of Pharmacology, and Director, Institute for Translational Medicine 

and Therapeutics, University of Pennsylvania School of 

Medicine, Philadelphia, Pennsylvania. 

Mari S. Golub, Ph.D., Staff Toxicologist, Office of Environmental Health Hazard Assessment, California Environmental Protection Agency, Sacramento, California.

Dorothy Hatsukami, Ph.D., Forster Family Professor in 

Cancer Prevention, Professor of Psychiatry, University of 

Minnesota Tobacco Use Research Center, University of 

Minnesota, Minneapolis, Minnesota.

Stephen S. Hecht, Ph.D., Wallin Professor of Cancer Prevention, Masonic Cancer Center, University of Minnesota, 

Minneapolis, Minnesota.

Marc K. Hellerstein, M.D., Ph.D., Professor (DH Calloway 

Chair in Human Nutrition), Department of Nutritional 

Sciences, University of California, Berkeley, California; 

and Professor of Endocrinology, Metabolism and Nutrition, Department of Medicine, University of California, 

San Francisco, California.

Jack E. Henningfield, Ph.D., Vice President Research and 

Health Policy, Pinney Associates, Bethesda, Maryland; and 

Professor, Adjunct, Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University School of 

Medicine, Baltimore, Maryland.

Brian Hitsman, Ph.D., Assistant Professor, Department of 

Preventive Medicine, Northwestern University, Chicago, 

Illinois.
Surgeon General’s Report

viii

James C. Hogg, M.D., Ph.D., Emeritus Professor of 

Pathology and Lab Medicine, iCAPTURE Centre for Cardiovascular and Pulmonary Research, University of British Columbia and St. Paul’s Hospital, Vancouver, British 

Columbia, Canada.

Anne M. Joseph, M.D., M.P.H., Wexler Professor of Medicine, and Director, Applied Clinical Research Program, 

University of Minnesota Medical School, Minneapolis, 

Minnesota.

Caryn Lerman, Ph.D., Mary W. Calkins Professor, Department of Psychiatry and Annenberg Public Policy Center; 

and Director, Tobacco Use Research Center, Scientific 

Director, Abramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania.

William MacNee, Professor, ELEGI Colt Research Labs, 

MRC Centre for Inflammation Research, The Queen’s 

Medical Research Institute, University of Edinburgh, 

Edinburgh, Scotland, United Kingdom.

Athina Markou, Ph.D., Professor, Department of Psychiatry, School of Medicine, University of California, San 

Diego, La Jolla, California.

Robert Merritt, M.A., Branch Chief, Epidemiology and 

Surveillance Branch, Division of Heart Disease and Stroke 

Prevention, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control 

and Prevention, Atlanta, Georgia.

Dennis L. Molfese, Ph.D., Distinguished University Scholar 

and Professor, Birth Defects Center, University of Louisville, Louisville, Kentucky.

Masaaki Moriya, Ph.D., Research Professor, Laboratory of 

Chemical Biology, Department of Pharmacological Sciences, University at Stony Brook, The State University of 

New York, Stony Brook, New York.

Marcus Munafò, M.A., M.Sc., Ph.D., Reader in Biological 

Psychology, Department of Experimental Psychology, University of Bristol, Bristol, United Kingdom. 

Sharon E. Murphy, Ph.D., Professor, Biochemistry, Molecular Biology and BioPhysics, Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota. 

Raymond Niaura, Ph.D., Professor, Department of Psychiatry and Human Behavior, The Warren Alpert 

Medical School of Brown University; and Director, Transdisciplinary Research, Butler Hospital, Providence, Rhode 

Island.

James Pankow, Ph.D., Professor, Department of Chemistry, and Department of Civil and Environmental Engineering, Portland State University, Portland, Oregon. 

Steve Pappas, Ph.D., Research Chemist, Emergency 

Response and Air Toxicants Branch, Division of Laboratory 

Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, Georgia.

Terry F. Pechacek, Ph.D., Associate Director for Science, 

Office on Smoking and Health, National Center for 

Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia.

Kenneth A. Perkins, Ph.D., Professor of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.

Lisa A. Peterson, Ph.D., Professor, Masonic Cancer Center 

and the Division of Environmental Health Sciences, University of Minnesota, Minneapolis, Minnesota.

Gerd P. Pfeifer, Ph.D., Professor and Chair, Division of Biology, Beckman Research Institute, City of Hope National 

Medical Center, Duarte, California. 

Halit Pinar, M.D., Director, Division of Perinatal and Pediatric Pathology, Women and Infants Hospital of Rhode 

Island; and Professor, Department of Pathology and Laboratory Medicine, Brown University Alpert School of Medicine, Providence, Rhode Island.

Gregory Polzin, Ph.D., Research Chemist, Emergency 

Response and Air Toxicants Branch, Division of Laboratory 

Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, Georgia.

Patricia Richter, Ph.D., DABT, Toxicologist, Office on 

Smoking and Health, National Center for Chronic Disease 

Prevention and Health Promotion, Centers for Disease 

Control and Prevention, Atlanta, Georgia.

Nancy Rigotti, M.D., Professor of Medicine, Harvard Medical School; and Director, Tobacco Research and Treatment 

Center, Massachusetts General Hospital, Boston, Massachusetts.
ix

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Wendie A. Robbins, Ph.D., Associate Professor, UCLA 

Schools of Nursing and Public Health, University of California, Los Angeles, California.

Andrew G. Salmon, M.A., D.Phil., Senior Toxicologist, 

Office of Environmental Health Hazard Assessment, California Department of Health Services, Oakland, California.

Jonathan M. Samet, M.D., M.S., Professor and Chairman, 

Department of Epidemiology, Bloomberg School of Public 

Health, The Johns Hopkins University, Baltimore, Maryland (1994–2008); and Director, USC Institute for Global 

Health, and Chairman, Department of Preventive Medicine, Keck School of Medicine, University of Southern 

California, Los Angeles, California (2008–present).

Robert M. Senior, M.D., Professor of Pulmonary Medicine, 

Cell Biology & Physiology, Division of Pulmonary and 

Critical Care, Washington University School of Medicine, 

St. Louis, Missouri. 

Edwin K. Silverman, M.D., Ph.D., Associate Professor of 

Medicine, Harvard Medical School, Harvard University; 

and Associate Physician, Brigham and Women’s Hospital, 

Boston, Massachusetts.

Margaret R. Spitz, M.D., M.P.H., Professor and Chair, 

Department of Epidemiology, The University of Texas, 

M. D. Anderson Cancer Center, Houston, Texas. 

Stephen B. Stanfill, M.S., Chemist, Emergency Response 

and Air Toxicants Branch, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, Georgia.

Prudence Talbot, Ph.D., Professor of Cell Biology, Department of Cell Biology and Neuroscience, University of California, Riverside, California.

Anne Thorndike, M.D., M.P.H., Instructor in Medicine, 

General Medicine Unit, Massachusetts General Hospital, 

Boston, Massachusetts. 

Clifford H. Watson, Ph.D., Lead Research Chemist, Emergency Response and Air Toxicants Branch, National Center for Environmental Health, Centers for Disease Control 

and Prevention, Atlanta, Georgia.

Gayle C. Windham, Ph.D., M.S.P.H., Research Scientist 

Supervisor, Chief, Environmental Surveillance Unit, Division of Environmental and Occupational Disease Control, 

California Department of Public Health, Richmond, California. 

Weija (William) Wu, Ph.D., Senior Service Fellow, Emergency Response and Air Toxicants Branch, Division of 

Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, 

Atlanta, Georgia.

Mitchell Zeller, J.D., Vice President for Policy and Strategic Communications, Pinney Associates, Bethesda, Maryland. 

Reviewers were

Erik M. Augustson, Ph.D., M.P.H., Behavioral Scientist/

Psychologist, Tobacco Control Research Branch, Behavioral Research Program, Division of Cancer Control and 

Population Sciences, National Cancer Institute, National 

Institutes of Health, Bethesda, Maryland.

Cathy L. Backinger, Ph.D., M.P.H., Chief, Tobacco Control 

Research Branch, Behavioral Research Program, Division of Cancer Control and Population Sciences, National 

Cancer Institute, National Institutes of Health, Bethesda, 

Maryland. 

Neal L. Benowitz M.D., Professor of Medicine and Biopharmaceutical Sciences and Chief, Division of Clinical 

Pharmacology and Experimental Therapeutics, University 

of California, San Francisco, California.

Mary Beth Bigley, Dr.P.H., M.S.N., A.N.P., Acting Director of the Office of Science and Communication, Office 

of the Surgeon General, Office of Public Health and Science, Office of the Secretary, U.S. Department of Health 

and Human Services, Washington, D.C.

Michele Bloch, M.D., Ph.D., Medical Officer, Tobacco Control Research Branch, Behavioral Research Program, Division of Cancer Control and Population Sciences, National 

Cancer Institute, National Institutes of Health, Bethesda, 

Maryland.

Naomi Breslau, Ph.D., Professor, Department of Epidemiology, Michigan State University, East Lansing, Michigan.

Klaus D. Brunnemann, M.S., Research Associate, New 

York Medical College, Valhalla, New York. 

David M. Burns, M.D., Professor Emeritus, Department of 

Family and Preventive Medicine, School of Medicine, University of California, San Diego, California.
Surgeon General’s Report

x

Pamela I. Clark, M.S.P.H., Ph.D., Research Professor, 

School of Public Health, University of Maryland, College 

Park, Maryland.

Gregory N. Connolly, D.M.D., M.P.H., Professor, Department of Society, Human Development, and Health, Harvard School of Public Health, Harvard University, Boston, 

Massachusetts.

William A. Corrigall, Ph.D., Professor of Psychiatry, University of Minnesota; and Senior Scientist, Minneapolis 

Medical Research Foundation, Minneapolis, Minnesota.

James D. Crapo, M.D., Professor of Medicine, National 

Jewish Health, Denver, Colorado. 

Michael Criqui, M.D., M.P.H., Professor and Chief, Division of Preventive Medicine, Department of Family and 

Preventive Medicine; and Professor, Department of Medicine, School of Medicine, University of California, San 

Diego, La Jolla, California.

K. Michael Cummings, Ph.D., M.P.H., Senior Research 

Scientist, Chair, Department of Health Behavior, Division 

of Cancer Prevention and Population Sciences, Roswell 

Park Cancer Institute, Buffalo, New York.

Mirjana V. Djordjevic, Ph.D., Program Director, Tobacco 

Control Research Branch, Behavioral Research Program, 

Division of Cancer Control and Population Sciences, 

National Cancer Institute, National Institutes of Health, 

Bethesda, Maryland. 

Erik Dybing, M.D., Ph.D., Division Director and Professor 

(retired), Division of Environmental Health, Norwegian 

Institute of Public Health, Oslo, Norway.

Michael Eriksen, Sc.D., Professor, and Director, Institute 

of Public Health, Georgia State University, Atlanta, Georgia.

Jefferson Fowles, Ph.D., Toxicologist, LyondellBasell 

Industries, Rotterdam, The Netherlands.

Adi F. Gazdar, M.D., Professor, Department of Pathology, 

University of Texas Southwestern Medical Center, Dallas, 

Texas.

Gary A. Giovino, Ph.D., M.S., Professor and Chair, Department of Health Behavior, School of Public Health and 

Health Professions, University at Buffalo, The State University of New York, Buffalo, New York.

Stanton Glantz, Ph.D., Professor of Medicine, Division of 

Cardiology, University of California, San Francisco, California.

Michael R. Guerin, Ph.D., Associate Division Director 

(retired), Oak Ridge National Laboratory, Knoxville, Tennessee. 

Dorothy Hatsukami, Ph.D., Forster Family Professor in 

Cancer Prevention, Professor of Psychiatry, University of 

Minnesota Tobacco Use Research Center, University of 

Minnesota, Minneapolis, Minnesota.

Jack E. Henningfield, Ph.D., Vice President Research and 

Health Policy, Pinney Associates, Bethesda, Maryland; and 

Professor, Adjunct, Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University School of 

Medicine, Baltimore, Maryland.

Allison Chausmer Hoffman, Ph.D., Program Director, 

National Institute on Drug Abuse, National Institutes of 

Health, Bethesda, Maryland. 

John R. Hoidal, M.D., Professor and Chairman of Medicine, School of Medicine, University of Utah Health Sciences Center, Salt Lake City, Utah.

John E. Hokanson, Ph.D., Associate Professor and Chair, 

Department of Epidemiology, Colorado School of Public 

Health, University of Colorado, Denver, Aurora, Colorado.

John Hughes, M.D., Professor, Department of Psychiatry, 

University of Vermont, Burlington, Vermont.

Richard D. Hurt, M.D., Professor of Medicine, Mayo Clinic 

College of Medicine, Rochester, Minnesota. 

Jared B. Jobe, Ph.D., FABMR, Program Director, Clinical 

Applications and Prevention Branch, Division of Prevention and Population Sciences, National Heart, Lung, and 

Blood Institute, National Institutes of Health, Bethesda, 

Maryland.

Rachel Kaufmann, Ph.D., M.P.H., Deputy Associate Director for Science, Office on Smoking and Health, National 

Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, 

Georgia.

Karl T. Kelsey, M.D., M.O.H., Professor, Community 

Health and Pathology and Laboratory Medicine, Director, 

Center for Environmental Health and Technology, Brown 

University, Providence, Rhode Island.
xi

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Juliette Kendrick, M.D., Medical Officer, Division of 

Reproductive Health, National Center for Chronic Disease 

Prevention and Health Promotion, Centers for Disease 

Control and Prevention, Atlanta, Georgia.

Martin Kharrazi, Ph.D., Chief, Program Research and 

Demonstration Section, Genetic Disease Screening Program, California Department of Public Health, Richmond, 

California.

Taline V. Khroyan, Ph.D., Behavioral Pharmacologist, SRI 

International, Center for Health Sciences, Menlo Park, 

California. 

Walther N.M. Klerx, Food and Consumer Product Safety 

Authority, Eindhoven, The Netherlands. 

Philip Lazarus, Ph.D., Professor of Pharmacology, College 

of Medicine, Pennsylvania State University, Milton S. Hershey Medical Center, Hershey, Pennsylvania.

Scott Leischow, Ph.D., Associate Director for Behavioral 

and Social Sciences Research, Arizona Cancer Center, The 

University of Arizona, Tucson, Arizona. 

Christina N. Lessov-Schlaggar, Ph.D., Research Assistant 

Professor, Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri.

Catherine Lorraine, Director, Policy Development and 

Coordination Staff, Food and Drug Administration, Silver 

Spring, Maryland.

Cathy Melvin, Ph.D., M.P.H., Director, Child Health Services Program, Cecil G. Sheps Center for Health Services 

Research, University of North Carolina, Chapel Hill, North 

Carolina. 

John D. Minna, M.D., Director, Hamon Center for Therapeutic Oncology Research, University of Texas Southwestern Medical Center, Dallas, Texas.

Joshua E. Muscat, Ph.D., Professor, Department of Public 

Health Sciences, College of Medicine, Pennsylvania State 

University, Milton S. Hershey Medical Center, Hershey, 

Pennsylvania.

Mark Parascandola, Ph.D., M.P.H., Epidemiologist, 

Tobacco Control Research Branch, Behavioral Research 

Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of 

Health, Bethesda, Maryland.

Wallace Pickworth, Ph.D., Health Research Leader, Battelle Centers for Public Health Research and Evaluation, 

Baltimore, Maryland. 

John M. Pinney, President, Pinney Associates, Bethesda, 

Maryland.

Britt C. Reid, D.D.S., Ph.D., Chief, Modifiable Risk Factors 

Branch, Epidemiology and Genetics Research Program, 

Division of Cancer Control and Population Sciences, 

National Cancer Institute, National Institutes of Health, 

Bethesda, Maryland.

John E. Repine, M.D., Director, Webb-Waring Center, Waring Professor of Medicine and Pediatrics, School of Medicine, University of Colorado, Denver, Colorado.

William Rickert, Ph.D., Chief Executive Officer, Labstat 

International ULC, Kitchener, Ontario, Canada.

David J. Riley, M.D., Professor, Department of Medicine, 

University of Medicine and Dentistry of New Jersey, Robert 

Wood Johnson Medical School, Piscataway, New Jersey. 

Scott Rogers, M.P.H., Public Health Advisor, Epidemiology 

and Genetics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, 

National Institutes of Health, Bethesda, Maryland.

Dale P. Sandler, Ph.D., Chief, Epidemiology Branch, 

National Institute of Environmental Health Sciences, 

National Institutes of Health, Research Triangle Park, 

North Carolina.

David A. Scott, Ph.D., Associate Professor, Oral Health and 

Systemic Disease Research Group, University of Louisville, Louisville, Kentucky.

Harold E. Seifried, Ph.D., DABT, Chemist, Toxicologist, 

Industrial Hygienist (retired), Program Director, Nutritional Sciences Research Group, Division of Cancer Prevention, National Cancer Institute, National Institutes of 

Health, Bethesda, Maryland.

Peter G. Shields, M.D., Professor of Medicine and Oncology, Deputy Director, Lombardi Comprehensive Cancer 

Center, Georgetown University Medical Center, Washington, D.C. 

Saul Shiffman, Ph.D., Research Professor, Psychology and 

Psychiatry, University of Pittsburgh; and Senior Scientific 

Advisor, Pinney Associates, Pittsburgh, Pennsylvania.
Surgeon General’s Report

xii

Donald R. Shopland, Sr., U.S. Public Health Service 

(retired), Ringgold, Georgia. 

Stephen Sidney, M.D., M.P.H., Associate Director for Clinical Research, Division of Research, Kaiser Permanente, 

Oakland, California. 

Gary D. Stoner, Ph.D., Professor Emeritus, Department of 

Internal Medicine, The Ohio State University, Columbus, 

Ohio.

Gary E. Swan, Ph.D., Director, Center for Health Sciences, 

SRI International Fellow, SRI International, Center for 

Health Sciences, Menlo Park, California.

Michael J. Thun, M.D., M.S., Vice President Emeritus, Epidemiology and Surveillance Research, American Cancer 

Society, Atlanta, Georgia. 

Robert B. Wallace, M.D., M.Sc., Irene Ensminger Stecher 

Professor of Epidemiology and Internal Medicine, Department of Epidemiology, University of Iowa College of Public Health, Iowa City, Iowa.

Deborah M. Winn, Ph.D., Deputy Director, Epidemiology 

and Genetics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, 

National Institutes of Health, Bethesda, Maryland.

Other contributors were 

Charlotte Gerczak, M.L.A., Communications Associate, 

Department of Epidemiology, Bloomberg School of Public 

Health, The Johns Hopkins University, Baltimore, Maryland.

Roberta B. Gray, Administrative Supervisor to Dr. Jonathan M. Samet, Department of Epidemiology, Bloomberg 

School of Public Health, The Johns Hopkins University, 

Baltimore, Maryland. 

Marta Gwinn, M.D., M.P.H., Medical Officer, Office of Public Health Genomics, National Center for Chronic Disease 

Prevention and Health Promotion, Centers for Disease 

Control and Prevention, Atlanta, Georgia.

Nancy Leonard, Administrative Coordinator to Dr. Jonathan M. Samet, Department of Epidemiology, Bloomberg 

School of Public Health, The Johns Hopkins University, 

Baltimore, Maryland.

Deborah Williams, Desktop Publishing Specialist to Dr. 

Jonathan M. Samet, Department of Epidemiology, Bloomberg School of Public Health, The Johns Hopkins University, Baltimore, Maryland.
xiii

How Tobacco Smoke Causes Disease: The Biology and 

Behavioral Basis for Smoking-Attributable Disease

Chapter 1. Introduction, Evaluation of Evidence on Mechanisms of Disease Production, and Summary 1

Introduction 3

Evaluation of Evidence on Mechanisms of Disease Production 5

Mechanisms of Action: Necessary, Sufficient, or Neither 7

Description of Evidence on Mechanisms of Disease Production 8

Scientific Basis of the Report 8

Development of the Report 8

Major Conclusions 9

Chapter Conclusions 9

References 12

Chapter 2. The Changing Cigarette 13

Introduction 15

Cigarette Design Changes over the Years 15

New Cigarette Products 17

Low-Nicotine Cigarettes 18

Cigarette-Like Products 18

Evaluation of New Cigarette Products 19

New Oversight of Tobacco Products 20

Summary 20

Conclusions 21

References 22

Chapter 3. Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 27

Introduction 29

Chemistry 30

Biomarkers 51

Summary 77

Conclusions 79

References 80

Chapter 4. Nicotine Addiction: Past and Present 103

Introduction 105

Definition of Nicotine Addiction 105

Tobacco Constituents and Pharmacokinetics 111

Components of Nicotine Addiction 116

Pathophysiology of Nicotine Addiction 124

Genetics 137

Prevalence and Trajectory Toward Nicotine Dependence 156

Epidemiology of Tobacco Use and Nicotine Dependence in Adults 162

Trajectory of Recovery or Relapse 170
xiv

Evidence Summary 180

Conclusions 183

References 184

Chapter 5. Cancer 221

Introduction 225

Carcinogen Exposure, Metabolism, and DNA Adducts 227

DNA Repair and Conversion of Adducts to Mutations 252

Gene Mutations in Tobacco-Induced Cancer 274

Loss of Mechanisms for Growth Control 284

Other Aspects 296

Evidence Summary 302

Conclusions 304

References 305

Chapter 6. Cardiovascular Diseases 351

Introduction 355

Tobacco Use and Cardiovascular Disease 355

Secondhand Tobacco Smoke and Cardiovascular Disease 363

Pathophysiology 363

Hemodynamic Effects 368

Smoking and the Endothelium 370

Thrombogenic Effects 374

Inflammation 382

Smoking and Diabetes 383

Lipid Abnormalities 387

Cardiovascular Biomarkers 391

Smoking Cessation and Cardiovascular Disease 394

Methods to Reduce Exposure 402

Evidence Summary 407

Conclusions 408

References 409

Chapter 7. Pulmonary Diseases 435

Introduction 437

Smoking and Respiratory Defense Mechanisms 450

Oxidative Stress 457

Oxidative Stress in Chronic Obstructive Pulmonary Disease 471

Genetics of Pulmonary Disease and Susceptibility to Tobacco Smoke 475

Pathogenesis of Emphysema 487

Summary 494

Evidence Summary 494

Conclusions 496

Implications 496

References 497

Chapter 8. Reproductive and Developmental Effects 521

Introduction 523
xv

Review of Epidemiologic Literature on Smoking 524

Pathophysiological and Cellular and Molecular Mechanisms of Smoking 555

Implications 606

Evidence Summary 608

Conclusions 612

References 613

Chapter 9. A Vision for the Future 645

The Global Tobacco Epidemic 647

Reducing the Risks from Smoking 651

Ending the Tobacco Epidemic 652

Concluding Remarks 654

Appendix 9.1: Recommendations for Future Research 655

Appendix 9.2: Ending the Tobacco Problem: A Blueprint for the Nation 660

Appendix 9.3: Promoting Healthy Lifestyles: Policy, Program, and Personal Recommendations for 

 Reducing Cancer Risk 664

References 667

List of Abbreviations 671

List of Tables and Figures 675

Definitions and Alternative Nomenclature of Genetic Symbols Used in This Report 679

Index 689

1

Chapter 1

Introduction, Evaluation of Evidence on 

Mechanisms of Disease Production, and Summary

Introduction 3

Evaluation of Evidence on Mechanisms of Disease Production 5

Mechanisms of Action: Necessary, Sufficient, or Neither 7

Description of Evidence on Mechanisms of Disease Production 8

Scientific Basis of the Report 8

Development of the Report 8

Major Conclusions 9

Chapter Conclusions 9

Chapter 2. The Changing Cigarette 9

Chapter 3. Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 9

Chapter 4. Nicotine Addiction: Past and Present 10

Chapter 5. Cancer 10

Chapter 6. Cardiovascular Diseases 10

Chapter 7. Pulmonary Diseases 11

Chapter 8. Reproductive and Developmental Effects 11

References 12

Introduction, Evaluation of Evidence on Mechanisms of Disease Production, and Summary 3

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Introduction

Since the first of the series in 1964, reports of the 

Surgeon General have provided definitive syntheses of the 

evidence on smoking and health. The topics have ranged 

widely, including comprehensive coverage of the health 

effects of active and passive smoking (U.S. Department 

of Health, Education, and Welfare [USDHEW] 1979; U.S. 

Department of Health and Human Services [USDHHS] 

1986, 2004, 2006), the impact of tobacco control policies 

(USDHHS 2000), and addiction (USDHHS 1988). A goal of 

these reports has been to synthesize available evidence for 

reaching conclusions on causality that have public health 

implications. In reaching conclusions on causation, the 

reports have followed a model that originated with the 

1964 report: compilation of all relevant lines of scientific 

evidence, critical assessment of the evidence, evaluation 

of the strength of evidence by using guidelines for evidence evaluation, and a summary conclusion on causation 

(USDHEW 1964; USDHHS 2004). The 2004 Surgeon General’s report provides a review of this approach and gives 

a set of ordered categories for classifying the strength of 

evidence for causality that was used in the 2004 and 2006 

reports on active and involuntary smoking, respectively 

(Table 1.1). The Surgeon General’s reports have established 

a long list of health consequences and diseases caused by 

tobacco use and exposure to tobacco smoke (Figure 1.1).

This report considers the biologic and behavioral 

mechanisms that may underlie the pathogenicity of 

tobacco smoke. Many Surgeon General’s reports have 

considered research findings on mechanisms in assessing 

the biologic plausibility of associations observed in epidemiologic studies. Mechanisms of disease are important 

because they may provide plausibility, which is one of the 

guideline criteria for assessing evidence on causation. The 

1964 report, for example, gave extensive consideration to 

the presence of carcinogens in tobacco smoke and the findings of animal models (USDHEW 1964). This new report, 

however, specifically reviews the evidence on the potential mechanisms by which smoking causes diseases and 

considers whether a mechanism is likely to be operative 

in the production of human disease by tobacco smoke. 

This evidence is important to understand how smoking 

causes disease, to identify those who may be particularly 

susceptible, and to assess the potential risks of tobacco 

products. In addition, this evidence is relevant to achieving the tobacco-related goals and objectives in the Healthy 

People initiative—the nation’s disease prevention and 

health promotion agenda—and to developing the interventions for our nation’s tobacco cessation targets for the 

year 2020 (USDHHS 2009).

In the planning of this report, the diseases and other 

adverse outcomes causally linked to smoking served to 

define the scope of issues considered in each of the chapters. Because sufficient biologic plausibility had been 

established in prior reports for all causal conclusions, the 

evidence on biologic and behavioral mechanisms reviewed 

in this report complements and supports the causal conclusions established earlier. The report is not focused on 

whether the evidence supports the plausibility of a causal 

association of smoking with a particular disease. In fact, 

most of the diseases and other adverse outcomes considered in this report have long been causally linked to 

smoking. This report focuses on the health consequences 

caused by exposure to tobacco smoke and does not 

review the evidence on the mechanisms of how smokeless 

tobacco causes disease.

The determination of whether a particular mechanism figures in the causation of disease by tobacco smoke 

has potential implications for prevention, diagnosis, and 

treatment. A general schema for the causation of disease 

by tobacco smoke is provided in Figure 1.2. The assumption is that disease may be a consequence of one or more 

pathways, each possibly having one or more component 

mechanisms. The figure shows multiple pathways, each 

comprised potentially of multiple mechanisms. Moreover, 

the same mechanism might figure into several different 

pathways. For example, mutations of genes are likely to 

Table 1.1 Four-level hierarchy for classifying the strength of causal inferences from available evidence

Level 1 Evidence is sufficient to infer a causal relationship

Level 2 Evidence is suggestive but not sufficient to infer a causal relationship

Level 3 Evidence is inadequate to infer the presence or absence of a causal relationship (which encompasses 

evidence that is sparse, of poor quality, or conflicting)

Level 4 Evidence is suggestive of no causal relationship

Source: U.S. Department of Health and Human Services 2004, 2006.
Surgeon General’s Report

4 Chapter 1

figure into several different pathways for the causation of 

cancer. As a complex mixture with many different toxic 

components, tobacco smoke is likely to act through multiple pathways in causing disease, and multiple genes may 

be involved. Genes may modulate the activity of these 

pathways, and there may also be connections between the 

pathways. Other environmental factors may act through 

the same pathways as tobacco smoke or through different pathways and, thereby, augment the contribution of 

smoking to disease incidence. For example, the combined 

effects of smoking and radon may contribute to causing 

lung cancer (National Research Council 1998). 

Pathways and mechanisms by which active and passive smoking contribute to causation of cardiovascular 

disease are illustrated in Figure 1.3 (Ambrose and Barua 

2004). This depiction of cigarette components in the “tar 

phase” and “gas phase” shows their action through several 

interacting pathways, indicating a role for genetic as well 

as other factors.

The characterization of mechanisms by which 

smoking causes disease could lead to applications of this 

knowledge to public health by (1) assessing tobacco products for their potential to cause injury through a particular mechanism, (2) developing biomarkers of injury to 

identify smokers at early stages of disease development, 

(3) identifying persons at risk on a genetic basis through 

the operation of a particular mechanism, (4) providing 

a basis for preventive therapies that block or reverse the 

underlying process of injury, and (5) identifying the contribution of smoking to causation of diseases with multiple etiologic factors. Consequently, research continues 

on the mechanisms by which smoking causes disease, 

even though the evidence has long been sufficient to 

infer that active smoking and exposure to secondhand 

smoke cause numerous diseases (USDHHS 2004, 2006). 

In addition, the resulting understanding of mechanisms 

is likely to prove applicable to diseases caused not only by 

Figure 1.1 The health consequences causally linked to smoking and exposure to secondhand smoke

Source: USDHHS 2004, 2006.
Introduction, Evaluation of Evidence on Mechanisms of Disease Production, and Summary 5

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Figure 1.2 General schema for the causation of 

disease by tobacco smoke

Note: M = disease mechanisms; P = disease pathways.

smoking but by other agents that may act through some 

of the same mechanisms. 

This report is written at a time when new research 

methods have facilitated exploration of the mechanisms 

by which smoking causes disease at a depth not previously possible. With the powerful methods of molecular 

and cellular research, disease pathogenesis can now be 

studied at the molecular level, and animal models can be 

developed to explore specific pathways of injury. Consequently, the range of evidence considered in this report is 

broad, coming from clinical studies, animal models, and 

in vitro systems. The coverage extends from research at 

the molecular level to population-level biomarker studies. 

Evaluation of Evidence on 

Mechanisms of Disease Production

Approaches for evaluation and synthesis of evidence 

on mechanisms have not been previously proposed in 

Surgeon General’s reports, although substantial emphasis 

has been placed on biologic mechanisms. The 1964 report 

indicated that three lines of evidence would be reviewed: 

animal experiments, clinical and autopsy studies, and 

population studies. It further commented on the essential 

nature of all three lines of evidence in reaching conclusions on causality. That report and subsequent reports of 

the Surgeon General, however, have given only general 

guidance on assessing biologic plausibility (USDHEW 

1964; USDHHS 2004). The 1964 report used the term 

“coherence of the association” as one of the criteria for 

causality (Table 1.2). In addressing lung cancer, the report 

stated: “A final criterion for the appraisal of causal significance of an association is its coherence with known 

facts in the natural history and biology of the disease” 

(USDHEW 1964, p. 185).

The 1982 report of the Surgeon General noted:

Coherence is clearly established when the actual 

mechanism of disease production is defined. 

Coherence exists, nonetheless, although of a 

lesser magnitude, when there is enough evidence 

to support a plausible mechanism, but not a 

detailed understanding of each step in the chain 

of events by which a given etiologic agent produces disease (USDHHS 1982, p. 20).

The 2004 report discussed coherence, plausibility, 

and analogy together, commenting:

Although the original definitions of these criteria 

were subtly different, in practice they have been 

treated essentially as one idea: that a proposed 

causal relationship not violate known scientific 

principles, and that it be consistent with experimentally demonstrated biologic mechanisms and 

other relevant data, such as ecologic patterns of 

disease.... In addition, if biologic understanding 

can be used to set aside explanations other than 

a causal association, it offers further support for 

causality. Together, these criteria can serve both 

to support a causal claim (by supporting the proposed mechanism) or refute it (by showing that 

the proposed mechanism is unlikely) (USDHHS 

2004, p. 22).

Hill (1965) listed both plausibility and coherence 

among his nine criteria but did not offer a sharp distinction 

between the two. He commented on the linkage of the 

concept of plausibility to the contemporary state of knowledge, and his views of coherence were largely consistent 

with statements in the 1964 Surgeon General’s report. 

Current evidence on mechanisms of disease causation raises issues that could not have been anticipated at 

the time of the 1964 report. With advances in laboratory 

research over the last several decades, researchers are 

challenged to interpret molecular and cellular evidence on 

mechanisms and causation. The need for new approaches 

to interpret such evidence has been recognized in several 

research areas including infectious diseases and cancer. 

Approaches have been proposed by agencies and researchers that assess carcinogens.
Surgeon General’s Report

6 Chapter 1

Figure 1.3 Potential pathways and mechanisms for cardiovascular dysfunction mediated by cigarette smoking 

Source: Ambrose and Barua 2004. Reprinted with permission from Elsevier, © 2004.

Note: The bold boxes and arrows in the flow diagram represent the probable central mechanisms in the complex pathophysiology 

of atherothrombotic disease mediated by cigarette smoking. H2O2 = hydrogen peroxide; METC = mitochondrial electron transport 

chain; NADPH = reduced nicotinamide adenine dinucleotide phosphate; NO = nitric oxide; NOS = nitric oxide synthase; 

O 2 = superoxide anion; ONOO = peroxynitrite. . - -
Introduction, Evaluation of Evidence on Mechanisms of Disease Production, and Summary 7

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

In infectious disease research, the arrival of molecular techniques for studying microbes led to a recognition that extensions of Koch’s postulates were needed 

to accommodate this new type of information (Falkow 

1988; Fredericks and Relman 1996). Falkow (1988) proposed “molecular Koch’s postulates” for considering the 

role of specific microbial genes in pathogenicity. Fredericks and Relman (1996) listed seven criteria for evaluating whether a disease could be attributed to a putatively 

identified pathogen, found by sequence-based methods. 

They emphasized that “coherence and plausibility are 

important” (p. 30). Pagano and colleagues (2004) also 

acknowledged the complexities of causally linking cancer 

to infectious agents. 

Research has broadened and increased the literature 

on mechanisms of carcinogenesis and has contributed to 

a similar rationale for developing approaches to review 

information on mechanisms. Approaches have been 

proposed by the International Agency for Research on 

Cancer (IARC) and the U.S. Environmental Protection 

Agency (EPA). 

In the preamble to its monographs on carcinogenicity, IARC describes its approach for characterizing 

the strength of evidence regarding mechanisms relevant 

to the agent being evaluated (IARC 2006). For animal 

experiments, IARC offers a four-level classification of the 

strength of evidence, which parallels the categories of 

the 2004 Surgeon General’s report: sufficient evidence 

of carcinogenicity, limited evidence of carcinogenicity, 

inadequate evidence of carcinogenicity, and evidence 

suggesting lack of carcinogenicity. The strength of evidence on mechanisms is described with terms such as 

“weak,” “moderate,” or “strong.” The IARC working group 

preparing the monographs is also charged with assessing 

whether the mechanism is operative in humans. Guidance is given for evaluating the role of a mechanism in 

experimental animals. Emphasis is placed on consistency 

across experimental systems and on biologic plausibility 

and coherence. 

EPA covers the identification of a “mode of action” 

in its Guidelines for Carcinogen Risk Assessment (USEPA 

2005). Mode of action refers to the process by which an 

agent causes disease but at a less detailed and specific 

level than is intended by mechanism of action. In these 

guidelines, EPA modified the Hill (1965) criteria, offering its framework for evaluating evidence on mode of 

action. The steps for evaluating a hypothesized mode of 

action include (1) description of the hypothesized mode of 

action, (2) discussion of the experimental support for this 

mode of action, (3) consideration of the possibility of other 

modes of action, and (4) conclusions about the hypothesized mode of action. In regard to evaluating the experimental support, the Guidelines list strength, consistency, 

and specificity of association as considerations. The finding of dose-response is given weight as is proper temporal 

ordering. Finally, the Guidelines call for biologic plausibility and coherence: “It is important that the hypothesized 

mode of action and the events that are part of it be based 

on contemporaneous understanding of the biology of cancer to be accepted” (pp. 2–46). Standard descriptors for 

the strength of evidence are not mentioned. 

Mechanisms of Action: Necessary, 

Sufficient, or Neither

For many of the diseases caused by smoking, multiple mechanisms are likely to be involved. For example, 

study results indicate that general and specific DNA injury 

and repair processes contribute to carcinogenesis. Causal 

agents have been classified as “necessary,” “sufficient,” 

or “neither necessary nor sufficient” (Rothman 1976). A 

necessary cause is requisite for occurrence of the disease; 

Table 1.2 Causal criteria

1964 Report of the Advisory Committee to the U.S. Surgeon General

1. Consistency of the association

2. Strength of the association

3. Specificity of the association

4. Temporal relationship of the association

5. Coherence of the association

Austin Bradford Hill’s criteria

1. Strength

2. Consistency

3. Specificity

4. Temporality

5. Biological gradient

6. Plausibility

7. Coherence

8. Experiment

9. Analogy

Source: U.S. Department of Health, Education, and Welfare 1964; Hill 1965.
Surgeon General’s Report

8 Chapter 1

severe acute respiratory syndrome (SARS), for example, 

cannot occur without infection with the SARS coronavirus. Exposure to a sufficient cause is invariably followed 

by occurrence of the disease. For chronic diseases, many 

causal factors are in the category “neither necessary nor 

sufficient”; cigarette smoking, for example, does not cause 

lung cancer in all smokers, and some cases occur among 

lifetime nonsmokers. 

A similar formulation of “necessary” and “sufficient” might be extended to considering the mechanisms 

of disease production. If there is only one pathway to a 

disease, and a particular mechanism is included in that 

pathway, then the mechanism is required for the development of the disease and would be considered “necessary.” 

A mechanism that is a component of one or more but not 

all pathways would be considered “sufficient.” Application of this type of classification would require a depth 

of understanding of the interplay of mechanisms that has 

not been reached for the pathogenesis of most diseases 

caused by tobacco smoking. Consequently, the chapters of 

this report largely address mechanisms of disease causation one by one without placing them into categories of 

necessary, sufficient, or neither. 

Description of Evidence on 

Mechanisms of Disease Production

Because evidence related to mechanisms of diseases caused by smoking is still evolving, this report uses 

a descriptive approach in reviewing and presenting the 

evidence. The chapters are based on review of the most 

relevant studies at the time they were written. A summary 

is given on the basis of the strength of evidence for each 

mechanism considered. 

As for causal inference in regard to smoking and 

disease, the finding that a particular mechanism plays 

a role in the production of disease by smoking has 

implications. The finding could point to a biomarker indicating that the pathway is active, or it could indicate the 

possibility of new preventive therapies to obviate the particular pathway.

Scientific Basis of the Report

The statements and conclusions throughout this 

report are documented by citation of studies published 

in the scientific literature. For the most part, this report 

cites peer-reviewed journal articles, including reviews that 

integrate findings from numerous studies, and books by 

recognized experts. When a study has been accepted for 

publication but the publication has not yet been issued, 

owing to the delay between acceptance and final publication, the study is referred to as “in press.” This report also 

refers, on occasion, to unpublished research such as a presentation at a professional meeting or a personal communication from the researcher. These personal references 

are to acknowledge experts whose research is in progress. 

Development of the Report

This report of the Surgeon General was prepared by 

the Office on Smoking and Health, National Center for 

Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, USDHHS. Initial 

chapters were written by 64 experts selected because of 

their knowledge of and familiarity with the topics presented here. These contributions are summarized in 

seven chapters evaluated by more than 30 peer reviewers. The entire manuscript was then sent to more than 

20 scientists and other experts, who examined it for scientific integrity. After each review cycle, the drafts were 

revised by the editors on the basis of the reviewers’ comments. Subsequently, the report was reviewed by various 

institutes and agencies within USDHHS. Publication lags, 

even short ones, prevent an up-to-the-minute inclusion 

of all recently published articles and data. Therefore, by 

the time the public reads this report, additional studies or 

data may have been published. 

Throughout this report, genes are represented by 

their abbreviations in italics. In many cases, proteins 

and enzymes related to these genes have the same abbreviation, presented in roman type. Definitions, alternative 

genetic symbols, related proteins and enzymes, and polymorphisms and variant genotypes are listed alphabetically 

by gene abbreviation in the table at the end of this report, 

“Definitions and Alternative Nomenclature of Genetic 

Symbols Used in This Report.” 

On June 22, 2009, President Barack Obama signed 

into law legislation granting authority to the U.S. 

Food and Drug Administration to regulate all tobacco 

products (Family Smoking Prevention and Tobacco 

Control Act 2009 [Public Law 111-31]). Terms used 

in this report reflect terms in the scientific literature 

and may not meet the definitions under the Tobacco 

Control Act.
Introduction, Evaluation of Evidence on Mechanisms of Disease Production, and Summary 9

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Major Conclusions

The scientific evidence supports the following major 

conclusions:

1. The evidence on the mechanisms by which smoking 

causes disease indicates that there is no risk-free level 

of exposure to tobacco smoke. 

2. Inhaling the complex chemical mixture of combustion compounds in tobacco smoke causes adverse 

health outcomes, particularly cancer and cardiovascular and pulmonary diseases, through mechanisms 

that include DNA damage, inflammation, and oxidative stress. 

3. Through multiple defined mechanisms, the risk and 

severity of many adverse health outcomes caused by 

smoking are directly related to the duration and level 

of exposure to tobacco smoke.

4. Sustained use and long-term exposures to tobacco 

smoke are due to the powerfully addicting effects 

of tobacco products, which are mediated by diverse 

actions of nicotine and perhaps other compounds, at 

multiple types of nicotinic receptors in the brain. 

5. Low levels of exposure, including exposures to secondhand tobacco smoke, lead to a rapid and sharp 

increase in endothelial dysfunction and inflammation, which are implicated in acute cardiovascular 

events and thrombosis.

6. There is insufficient evidence that product modification strategies to lower emissions of specific toxicants 

in tobacco smoke reduce risk for the major adverse 

health outcomes.

Chapter Conclusions

Chapter 2. The Changing Cigarette

1. The evidence indicates that changing cigarette 

designs over the last five decades, including filtered, 

low-tar, and “light” variations, have not reduced overall disease risk among smokers and may have hindered prevention and cessation efforts.

2. There is insufficient evidence to determine whether 

novel tobacco products reduce individual and population health risks. 

3. The overall health of the public could be harmed if 

the introduction of novel tobacco products encourages tobacco use among people who would otherwise 

be unlikely to use a tobacco product or delays cessation among persons who would otherwise quit using 

tobacco altogether.

Chapter 3. Chemistry and 

Toxicology of Cigarette Smoke and 

Biomarkers of Exposure and Harm

1. In spite of uncertainties concerning whether particular cigarette smoke constituents are responsible 

for specific adverse health outcomes, there is broad 

scientific agreement that several of the major classes 

of chemicals in the combustion emissions of burned 

tobacco are toxic and carcinogenic.

2. The design characteristics of cigarettes, including 

ventilation features, filters, and paper porosity, have 

a significant influence on the levels of toxic and carcinogenic chemicals in the inhaled smoke.

3. The different types of tobacco lamina (e.g., bright, 

burley, or oriental) that are combined to produce a 

specific tobacco blend have a significant influence on 

the levels of toxic and carcinogenic chemicals in the 

combustion emissions of burned tobacco.

4. There is no available cigarette machine-smoking 

method that can be used to accurately predict doses of 

the chemical constituents of tobacco smoke received 

when using tobacco products.
Surgeon General’s Report

10 Chapter 1

5. Tobacco-specific biomarkers (nicotine and its metabolites and the tobacco-specific nitrosamines) have 

been validated as quantitative measures of exposure 

to tobacco smoke among smokers of cigarettes of 

similar design who do not use other tobacco-containing products.

6. Although biomarkers of potential harm exist for most 

tobacco-related diseases, many are not specific to 

tobacco and levels are also influenced by diet, occupation, or other lifestyle or environmental factors.

Chapter 4. Nicotine Addiction: 

Past and Present

1. Nicotine is the key chemical compound that causes 

and sustains the powerful addicting effects of commercial tobacco products.

2. The powerful addicting effects of commercial tobacco 

products are mediated by diverse actions of nicotine 

at multiple types of nicotinic receptors in the brain.

3. Evidence is suggestive that there may be psychosocial, biologic, and genetic determinants associated 

with different trajectories observed among population subgroups as they move from experimentation to 

heavy smoking.

4. Inherited genetic variation in genes such as CYP2A6 

contributes to the differing patterns of smoking 

behavior and smoking cessation. 

5. Evidence is consistent that individual differences in 

smoking histories and severity of withdrawal symptoms are related to successful recovery from nicotine 

addiction.

Chapter 5. Cancer

1. The doses of cigarette smoke carcinogens resulting 

from inhalation of tobacco smoke are reflected in levels of these carcinogens or their metabolites in the 

urine of smokers. Certain biomarkers are associated 

with exposure to specific cigarette smoke carcinogens, 

such as urinary metabolites of the tobacco-specific 

nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-

1-butanone and hemoglobin adducts of aromatic amines. 

2. The metabolic activation of cigarette smoke carcinogens by cytochrome P-450 enzymes has a direct effect 

on the formation of DNA adducts.

3. There is consistent evidence that a combination of 

polymorphisms in the CYP1A1 and GSTM1 genes 

leads to higher DNA adduct levels in smokers and 

higher relative risks for lung cancer than in those 

smokers without this genetic profile.

4. Carcinogen exposure and resulting DNA damage 

observed in smokers results directly in the numerous 

cytogenetic changes present in lung cancer.

5. Smoking increases the frequency of DNA adducts of 

cigarette smoke carcinogens such as benzo[a]pyrene 

and tobacco-specific nitrosamines in the lung and 

other organs.

6. Exposure to cigarette smoke carcinogens leads to 

DNA damage and subsequent mutations in TP53 and 

KRAS in lung cancer. 

7. There is consistent evidence that smoking leads to the 

presence of promoter methylation of key tumor suppressor genes such as P16 in lung cancer and other 

smoking-caused cancers. 

8. There is consistent evidence that smoke constituents 

such as nicotine and 4-(methylnitrosamino)-1-(3-

pyridyl)-1-butanone can activate signal transduction 

pathways directly through receptor-mediated events, 

allowing the survival of damaged epithelial cells that 

would normally die. 

9. There is consistent evidence for an inherited susceptibility of lung cancer with some less common 

genotypes unrelated to a familial clustering of smoking behaviors. 

10. Smoking cessation remains the only proven strategy 

for reducing the pathogenic processes leading to cancer in that the specific contribution of many tobacco 

carcinogens, alone or in combination, to the development of cancer has not been identified.

Chapter 6. Cardiovascular Diseases 

1. There is a nonlinear dose response between exposure to tobacco smoke and cardiovascular risk, with 

a sharp increase at low levels of exposure (including 

exposures from secondhand smoke or infrequent 

cigarette smoking) and a shallower dose-response 

relationship as the number of cigarettes smoked per 

day increases.

2. Cigarette smoking leads to endothelial injury and 

dysfunction in both coronary and peripheral arteries. There is consistent evidence that oxidizing 

chemicals and nicotine are responsible for endothelial dysfunction.
Introduction, Evaluation of Evidence on Mechanisms of Disease Production, and Summary 11

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

3. Tobacco smoke exposure leads to an increased risk 

of thrombosis, a major factor in the pathogenesis of 

smoking-induced cardiovascular events.

4. Cigarette smoking produces a chronic inflammatory state that contributes to the atherogenic disease 

processes and elevates levels of biomarkers of 

inflammation, known powerful predictors of cardiovascular events.

5. Cigarette smoking produces an atherogenic lipid profile, primarily due to an increase in triglycerides and a 

decrease in high-density lipoprotein cholesterol.

6. Smoking cessation reduces the risk of cardiovascular 

morbidity and mortality for smokers with or without 

coronary heart disease.

7. The use of nicotine or other medications to facilitate 

smoking cessation in people with known cardiovascular disease produces far less risk than the risk of 

continued smoking.

8. The evidence to date does not establish that a reduction of cigarette consumption (that is, smoking fewer 

cigarettes per day) reduces the risks of cardiovascular disease.

9. Cigarette smoking produces insulin resistance and 

chronic inflammation, which can accelerate macrovascular and microvascular complications, including 

nephropathy.

Chapter 7. Pulmonary Diseases

1. Oxidative stress from exposure to tobacco smoke has 

a role in the pathogenetic process leading to chronic 

obstructive pulmonary disease.

2. Protease-antiprotease imbalance has a role in the 

pathogenesis of emphysema.

3. Inherited genetic variation in genes such as SERPINA3 is involved in the pathogenesis of tobaccocaused chronic obstructive pulmonary disease.

4. Smoking cessation remains the only proven strategy 

for reducing the pathogenetic processes leading to 

chronic obstructive pulmonary disease.

Chapter 8. Reproductive and 

Developmental Effects 

1. There is consistent evidence that links smoking in 

men to chromosome changes or DNA damage in 

sperm (germ cells), affecting male fertility, pregnancy 

viability, and anomalies in offspring.

2. There is consistent evidence for association of periconceptional smoking to cleft lip with or without 

cleft palate. 

3. There is consistent evidence that increases in folliclestimulating hormone levels and decreases in estrogen 

and progesterone are associated with cigarette smoking in women, at least in part due to effects of nicotine 

on the endocrine system. 

4. There is consistent evidence that maternal smoking 

leads to transient increases in maternal heart rate and 

blood pressure (primarily diastolic), probably mediated by the release of norepinephrine and epinephrine 

into the circulatory system.

5. There is consistent evidence that links maternal 

smoking to interference in the physiological transformation of spiral arteries and thickening of the villous 

membrane in forming the placenta; placental problems could lead to fetal loss, preterm delivery, or low 

birth weight.

6. There is consistent evidence of the presence of histopathologic changes in the fetus from maternal smoking, particularly in the lung and brain.

7. There is consistent evidence that suggests smoking 

leads to immunosuppressive effects, including dysregulation of the inflammatory response, that may 

lead to miscarriage and preterm delivery. 

8. There is consistent evidence that suggests a role 

for polycyclic aromatic hydrocarbons from tobacco 

smoke in the adverse effects of maternal smoking on a 

variety of reproductive and developmental endpoints.

9. There is consistent evidence that tobacco smoke 

exposure leads to diminished oviductal functioning, 

which could impair fertilization. 

10. There is consistent evidence that links prenatal 

smoke exposure and genetic variations in metabolizing enzymes such as GSTT1 with increased risk of 

adverse pregnancy outcomes such as lowered birth 

weight and reduced gestation.

11. There is consistent evidence that genetic polymorphisms, such as variants in transforming growth factor-alpha, modify the risks of oral clefting in offspring 

related to maternal smoking.

12. There is consistent evidence that carbon monoxide 

leads to birth weight deficits and may play a role in 

neurologic deficits (cognitive and neurobehavioral 

endpoints) in the offspring of smokers.
Surgeon General’s Report

12 Chapter 1

References

Ambrose JA, Barua RS. The pathophysiology of cigarette smoking and cardiovascular disease: an update. 

Journal of the American College of Cardiology 2004;

43(10):1731–7.

Falkow S. Molecular Koch’s postulates applied to microbial pathogenicity. Reviews of Infectious Diseases 1988;

10(Suppl 2):S274–S276.

Fredericks DN, Relman DA. Sequence-based identification of microbial pathogens; a reconsideration of 

Koch’s postulates. Clinical Microbiology Reviews 1996;

9(1):18–33.

Hill AB. The environment and disease: association or causation? Proceedings of the Royal Society of Medicine

1965;58:295–300.

International Agency for Research on Cancer. IARC Monographs on the Evaluation of Carcinogenic Risk to 

Humans: Preamble, 2006; <http://monographs.iarc.fr/

ENG/Preamble/CurrentPreamble.pdf>; accessed: 

December 10, 2008.

National Research Council. Research Priorities for Airborne Particulate Matter. I: Immediate Priorities and a 

Long-Range Research Portfolio. Washington: National 

Academy Press, 1998.

Pagano JS, Blaser M, Buendia M-A, Damania B, Khalili K, 

Raab-Traub N, Roizman B. Infectious agents and cancer: criteria for a causal relation. Seminars in Cancer 

Biology 2004;14(6):453–71.

Rothman KJ. Causes. American Journal of Epidemiology

1976;104(6):587–92.

U.S. Department of Health and Human Services. The 

Health Consequences of Smoking: Cancer. A Report of 

the Surgeon General. Rockville (MD): U.S. Department 

of Health and Human Services, Public Health Service, 

Office on Smoking and Health, 1982. DHHS Publication No. (PHS) 82-50179.

U.S. Department of Health and Human Services. The 

Health Consequences of Involuntary Smoking. A 

Report of the Surgeon General. Rockville (MD): U.S. 

Department of Health and Human Services, Public 

Health Service, Centers for Disease Control, Center 

for Health Promotion and Education, Office on Smoking and Health, 1986. DHHS Publication No. (CDC) 

87-8398.

U.S. Department of Health and Human Services. The 

Health Consequences of Smoking: Nicotine Addiction. 

A Report of the Surgeon General. Atlanta: U.S. Department of Health and Human Services, Public Health 

Service, Centers for Disease Control, National Center 

for Chronic Disease Prevention and Health Promotion, 

Office on Smoking and Health, 1988. DHHS Publication No. (CDC) 88-8406.

U.S. Department of Health and Human Services. Reducing 

Tobacco Use. A Report of the Surgeon General. Atlanta: 

U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National 

Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2000.

U.S. Department of Health and Human Services. The 

Health Consequences of Smoking: A Report of the 

Surgeon General. Atlanta: U.S. Department of Health 

and Human Services, Centers for Disease Control and 

Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and 

Health, 2004.

U.S. Department of Health and Human Services. The 

Health Consequences of Involuntary Exposure to 

Tobacco Smoke: A Report of the Surgeon General.

Atlanta: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, 

Coordinating Center for Health Promotion, National 

Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2006.

U.S. Department of Health and Human Services. Healthy 

People, 2009; <http://www.healthypeople.gov>; 

accessed: September 28, 2009. 

U.S. Department of Health, Education, and Welfare. Smoking and Health: Report of the Advisory Committee to 

the Surgeon General of the Public Health Service.

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and Welfare, Public Health Service, Center for Disease 

Control, 1964. PHS Publication No. 1103.

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Assistant Secretary for Health, Office on Smoking and 

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2005. EPA Publication No. EPA/630/P-013/001F.
13

Chapter 2

The Changing Cigarette

Introduction 15

Cigarette Design Changes over the Years 15

New Cigarette Products 17

Low-Nicotine Cigarettes 18

Cigarette-Like Products 18

Evaluation of New Cigarette Products 19

New Oversight of Tobacco Products 20

Summary 20

Conclusions 21

References 22

The Changing Cigarette 15

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Introduction

growing public awareness of the health hazards of tobacco 

use, primarily through reducing machine-measured tar and 

nicotine content (NCI 1996). However, evidence now demonstrates that these modifications did not reduce the risk 

of cigarette smoking and in addition may have undermined 

efforts to prevent tobacco use and promote cessation 

(NCI 2001). In recent years, a range of new products have 

been introduced and marketed to smokers as an alternative to conventional cigarettes, sometimes accompanied 

by messages, explicit or implied, that they offer reduced 

exposure to toxic substances or risk of disease (Pederson and Nelson 2007). The focus of this chapter is on the 

health consequences of changes in cigarette design over 

time. Coverage of novel cigarette products is not intended 

to be comprehensive or current, because this market is 

rapidly evolving.

Cigarettes are the most common form of tobacco 

used in most of the world (World Health Organization 

[WHO] 2006) and cause 443,000 deaths in the United 

States each year (U.S. Department of Health and Human 

Services [USDHHS] 1986, 1988; National Cancer Institute 

[NCI] 1997; Centers for Disease Control and Prevention 

[CDC] 2008). The primary short- and long-range strategies for reducing deaths associated with tobacco use are 

cessation and prevention, respectively, along with reduction of secondhand smoke exposure (Warner et al. 1998; 

USDHHS 2000; Stratton et al. 2001; WHO 2003a). Another 

concept that has been considered is changing the cigarette itself to make it less toxic. The concept of modifying conventional cigarettes to be potentially less harmful 

is not new. Beginning in the 1950s, the tobacco industry 

embarked on efforts to modify cigarettes in response to 

Cigarette Design Changes over the Years

The history of tobacco product design and marketing has been discussed elsewhere and need not be 

repeated (Reynolds and Shachtman 1989; Goodman 1993, 

2004; Hilts 1996; Kluger 1996; Tate 1999; Brandt 2007). 

However, the tobacco industry’s internal memoranda and 

other documents make it clear that the core concept and 

function of the cigarette has changed little since its invention in the early part of the nineteenth century; namely, 

it is a tobacco-derived product for delivering nicotine 

to the user (University of California at San Francisco 

[UCSF] 2008). 

By the early 1950s, mounting scientific evidence 

began to implicate cigarette smoking in the development of serious respiratory, heart, and neoplastic diseases 

(Royal College of Physicians of London 1962; U.S. Department of Health, Education, and Welfare [USDHEW] 1964). 

This evidence created a new force in cigarette design that 

has remained prominent to this day: to design cigarettes 

that could be marketed as addressing the health concerns 

of both cigarette smokers and health professionals by reducing toxicants (Slade and Henningfield 1998; Stratton 

et al. 2001). Early efforts to reduce toxicants focused on 

efforts to reduce the overall tar (e.g., total particulate matter minus nicotine and water content) and nicotine yields 

of cigarettes.

The first major design change to reduce tar and nicotine yields was the introduction of filters in the 1950s. 

Before 1950, only 0.6 percent of cigarettes were filtered, 

but the increasing lay press coverage of the potential 

dangers of smoking led to an explosion of filter development 

and marketing. By 1960, filtered cigarettes represented 51 

percent of the cigarette market (USDHHS 1989). By 2005, 

they represented 99 percent of the market. Major design 

efforts to reduce machine-measured tar and nicotine 

yields continued throughout the 1960s and 1970s with the 

introduction of “light” and low-tar cigarettes. Efforts to 

further reduce machine-measured tar and nicotine yields 

included the use of porous cigarette paper, reconstituted 

tobacco, filter tip ventilation, and the use of expanded 

tobacco (Hoffmann et al. 1996). 

The initial focus on reduction of tar and nicotine 

yields was supported by early case-control studies suggesting that cancer risks were reduced by increased use of 

filters and decreased machine-measured tar delivery, and 

laboratory studies appeared to confirm this dose-response 

relationship. This research led to the seemingly reasonable 

conclusion that cigarettes with lower machine-measured 

tar and nicotine might pose fewer hazards, assuming that 

smokers did not increase the number of cigarettes they 

smoked per day or otherwise change their smoking behaviors (USDHEW 1967, 1969, 1971, 1974; USDHHS 1981; 

Stratton et al. 2001). Thus, it was widely accepted that 

declining tar and nicotine levels could lead to decreased 

disease risk. The concept that reduced exposure to 
Surgeon General’s Report

16 Chapter 2

toxicants could reduce disease risk was supported 

by previous Surgeon General’s reports (USDHEW 

1969). In 1966, the U.S. Public Health Service recommended “the progressive reduction of the ‘tar’ 

and nicotine content of cigarette smoke” (USDHEW 

1966, p. 2), and the Federal Trade Commission (FTC) 

announced that it would generally permit cigarette companies to make marketing claims about tar and nicotine 

yields as long as those statements were based on a uniform machine-based test method for measuring tar and 

nicotine yields, subsequently known as “the FTC method” 

(Peeler 1996; Pillsbury 1996). 

Efforts to reduce tar and nicotine yields as measured 

on the basis of machine-smoking conditions were successful. The sales-weighted deliveries in U.S. cigarette smoke 

decreased from 38 milligrams (mg) of tar and 2.7 mg of 

nicotine in 1954 to 12 mg of tar and 0.95 mg of nicotine 

in 1993 (Hoffmann et al. 1996). Machine measurements 

of tar have shown little change since then, and machine 

measurements of nicotine delivery have remained at 

approximately 0.9 mg per cigarette since 1981 (Federal 

Register 1995, 1996; Slade et al. 1995; Hurt and Robertson 

1998; Kessler 2001).

Unfortunately, with the accrual and evaluation of 

additional data, the evidence today does not demonstrate 

that efforts to lower machine-measured tar and nicotine 

yields actually decreased the health risks of smoking, primarily because these changes did not reduce smokers’ 

actual exposure to tobacco toxicants (NCI 2001; USDHHS 

2004). Indeed, to the extent that filters and other efforts 

to reduce machine-measured tar and nicotine reduced 

smokers’ health concerns, and thereby delayed quitting 

and/or increased cigarette use, they may have contributed 

to an overall increase in cigarette-caused mortality (Stratton et al. 2001). 

As mentioned above, for example, the first effort to 

change the design of cigarettes was the addition of the filter. In theory, use of filter technologies can remove substantial amounts of a wide variety of toxicants (Browne 

1990; Hoffmann and Hoffmann 1997). In fact, however, 

evidence on the ability of filters to reduce harm is not 

clear (Slade 1993; NCI 2001; Stratton et al. 2001). And, 

some novel filter designs may introduce new toxicants 

such as asbestos (Slade 1993), carbon (Pauly et al. 1997), 

and glass (Pauly et al. 1998). The wide variation in filter 

technology across brands and over time precludes general 

conclusions about whether filters increased or decreased 

exposure of smokers to toxicants. 

Similarly, a variety of design features made it possible for cigarette smokers to compensate, that is, easily 

ingest severalfold higher amounts of tar and nicotine than 

the yields obtained when using the machine-based FTC 

method (Djordjevic et al. 2000; NCI 2001; Stratton et al. 

2001; WHO 2003c). Most important was the introduction 

of ventilation holes in the cigarette filters, which allowed 

smoke to escape during machine testing. In the 1980s, 

researchers discovered that smokers covered these ventilation holes with their fingers, negating the effect of the 

holes in reducing smoke exposure (Kozlowski et al. 1980, 

2002, 2006). Moreover, subsequent research demonstrated 

that the use of ventilation holes produced higher levels of 

free-base nicotine, which led to a more addictive product 

as well as deeper lung inhalation of cooler and less harsh 

smoke (Stratton et al. 2001; Pankow et al. 2003a,b; Watson 

et al. 2004). Driven by nicotine addiction and enabled by 

cigarettes that delivered smoother, cooler smoke diluted 

by ambient air, smokers could easily compensate for 

reduced delivery of nicotine by increasing smoke intake 

per cigarette and per day, thus maintaining high levels of 

disease risk (NCI 2001; Thun and Burns 2001). 

Tobacco industry documents, many of which are 

available at the Legacy Tobacco Documents Library at 

UCSF, clearly demonstrate that at least by the mid-1970s 

the tobacco industry well understood the importance of 

creating health reassurance messages in order to alleviate 

health concerns, and that one important method of doing 

so was through claims of low deliveries of tar. For example, 

a 1977 British American Tobacco marketing report concluded, “All work in this area should be directed towards 

providing consumer reassurance (emphasis in original)

about cigarettes and the smoking habit. This can be provided in different ways, e.g. by claimed low deliveries, by 

the perception of low deliveries and by the perception of 

‘mildness’” (Short 1977, p. 3). At the same time, tobacco 

company documents also clearly demonstrate that the 

industry understood that smokers would not achieve the 

claimed deliveries because of smoker compensation. For 

example, a 1975 Philip Morris memo noted: “In effect, the 

Marlboro 85 smokers in this study did not achieve any 

reduction in smoke intake by smoking a cigarette (Marlboro Lights) normally considered lower in delivery” 

(Goodman 1975, p. 3). 

In contrast to industry awareness, the various ways 

that cigarettes were physically modified and the nature 

and level of compensation in response to design changes 

were not well understood by parties outside of the tobacco 

industry itself. Public health officials had little basis 

to anticipate the degree to which manufacturers could 

design cigarettes to allow smokers to draw more smoke 

and nicotine from cigarettes than was represented by 

machine-measured yields of tar and nicotine (NCI 2001; 

Parascandola 2005).

It was not until the turn of the twenty-first century 

that it became increasingly clear that no relationship 

existed between machine-measured tar and nicotine levels 

and risks for most categories of cigarette-related diseases. 
The Changing Cigarette 17

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

In 1994, an expert committee convened by NCI concluded: 

“The smoking of cigarettes with lower machine-measured

yields has a small effect in reducing the risk of cancer 

caused by smoking, no effect on the risk of cardiovascular 

diseases, and an uncertain effect on the risk of pulmonary 

disease” (NCI 1996, p. vi). Moreover, whereas squamous 

cell carcinomas had been the predominant form of lung 

cancer, by the late twentieth century adenocarcinoma 

of the lung was becoming increasingly common, presumably reflecting deeper inhalation of smoke that was 

facilitated by ventilated filters as well as other factors 

such as changes in agricultural practices, tobacco curing, 

and cigarette manufacturing processes that could lead to 

increased concentrations of tobacco-specific nitrosamines 

(NCI 2001; Stratton et al. 2001) (see Chapter 5, “Cancer”). 

By 2001, NCI concluded that “measurements of tar and 

nicotine yields using the FTC method do not offer smokers meaningful information on the amount of tar and 

nicotine they will receive from a cigarette” (NCI 2001, 

p. 10). The 2001 review also concluded that the evidence 

“...does not indicate a benefit to public health from 

changes in cigarette design and manufacturing over the 

last fifty years” (NCI 2001, p. 10). Today, there is a scientific consensus that changes in cigarette designs from the 

1950s to the 1980s to reduce machine-measured tar yields 

did not result in decreased morbidity and mortality (NCI 

2001; Thun and Burns 2001). In sum, it took decades to 

recognize that changes to reduce machine-measured tar 

and nicotine yields in cigarettes did not have a measurable 

beneficial impact on public health (NCI 2001). In 2008, 

FTC rescinded its 1966 guidance that generally permitted 

statements concerning tar and nicotine yield if they were 

based on the Cambridge filter method (sometimes called 

the FTC method) (FTC 2008).

Other changes during the past 50 years have 

included efforts that potentially have made cigarettes 

more addicting through the use of flavors, chemical 

treatments to alter the smell and appearance of cigarette 

smoke, methods to mask noxious sensory effects, and control of the nicotine dose (see Chapter 4, “Nicotine Addiction: Past and Present”). These approaches included new 

types of filters, tobacco blends, and ingredients; cigarette 

ventilation; control of pH; and efforts to reduce various 

volatile organic compounds in tobacco and smoke. These 

product modifications have the potential to increase the 

risk of addiction by contributing to increased risk of initiating use of the product, increased ease of smoke inhalation, decreased noxiousness of the smoke, and possibly 

increased brain nicotine exposure (WHO 2007; Chapter 4, 

“Nicotine Addiction: Past and Present”). 

New Cigarette Products

Cigarette smoke contains more than 7,000 chemicals, including at least 69 known carcinogens and many 

other toxicants implicated in major diseases (International Agency for Research on Cancer [IARC] 2004; 

Borgerding and Klus 2005; Rodgman and Perfetti 

2009), and because the potency of toxicants and mechanisms of action differ, reducing concentrations of individual toxicants might have only a negligible effect on 

disease risk from smoking (Fowles and Dybing 2003; 

Pankow et al. 2007; Burns et al. 2008). Despite these challenges, Brown & Williamson (acquired by R.J. Reynolds 

in 2004), Vector Tobacco, and Philip Morris have all 

developed cigarettes that purport to deliver lower levels 

of specific toxicants (e.g., carcinogenic nitrosamines) as 

determined by standard machine-smoking methods. This 

reduction in toxicant levels has been accomplished by use 

of new technologies in tobacco curing and/or by adding carbon or other materials to cigarette filters (Hoffmann et al. 

2001; IARC 2004). However, the extent to which exposure 

to toxicants is actually reduced in smokers is not known 

because reduced machine-measured yields of toxicants do 

not necessarily reflect actual human exposure. A smoker 

who switches to a brand with lower machine-measured 

toxicants may smoke these cigarettes in a more intense 

fashion or may consume more cigarettes per day than 

previously. Either change could result in greater human 

exposure to toxicants and no decrease in risk of disease.

For example, Brown & Williamson introduced 

Advance as a new cigarette with the claim that levels of 

tobacco-specific nitrosamines (TSNAs) were 70 percent 

lower than those in leading “light” brands (Star Scientific 

2005). Preliminary laboratory studies of cigarette smokers 

provide mixed evidence for the possibility that use of this 

cigarette substitute would result in reduced exposure to 

tobacco toxicants (Breland et al. 2002, 2003). Omni, manufactured by Vector Tobacco, is a conventional cigarette 

for which the marketers claimed lower levels of carcinogenic polycyclic aromatic hydrocarbons, nitrosamines, 

and catechols (Vector Group 2001). Preliminary studies 

in which Omni is smoked instead of the smokers’ usual 

brand of cigarettes provide little evidence for reduced 

exposure to toxicants (Hatsukami et al. 2004b; Hughes et 

al. 2004). 
Surgeon General’s Report

18 Chapter 2

Low-Nicotine Cigarettes

the addictive threshold. The test market ended in 1991 

when Philip Morris withdrew the product from the market. Quest was a low-nicotine cigarette developed by Vector Tobacco (Rose and Behm 2004; Vector Tobacco 2004). 

Three products were available: (1) a cigarette with 0.6 

mg of nicotine and 10 mg of tar per cigarette, as determined by FTC machine measurements; (2) a cigarette 

with 0.3 mg of nicotine and 10 mg of tar per cigarette; 

and (3) a “nicotine-free” cigarette with no more than 

0.05 mg of nicotine and 10 mg of tar per cigarette (Vector Tobacco 2004). It was unclear how long and how 

often smokers would use the “nicotine-free” version rather 

than versions that contained higher levels of nicotine and 

whether the two versions with nicotine would hinder the 

desire and ability to stop smoking. 

In theory, gradually reducing the content and yield 

of nicotine in cigarettes over a period of many years, 

using design features that make compensation difficult or 

impossible, might lessen smokers’ dependence on nicotine. Low-nicotine cigarettes have also been proposed as 

a method to prevent new smokers (primarily youth) from 

ever establishing nicotine dependence (Benowitz and 

Henningfield 1994; Henningfield et al. 1998; Benowitz 

et al. 2007; Zeller et al. 2009). However, the potential 

role of nicotine analogues in maintaining addiction is 

poorly understood.

A commercial cigarette with very low nicotine 

content was introduced in test markets in 1989 under 

the brand name Next (Butschky et al. 1995). The nicotine content of Next appeared to be lower than the levels 

hypothesized by Benowitz and Henningfield (1994) to be 

Cigarette-Like Products

In 1988, R.J. Reynolds launched a new era of novel 

products with Premier, a nicotine-delivering product 

similar in size and appearance to a conventional cigarette 

but consisting of an aluminum canister that contained 

alumina beads impregnated with glycerin, propylene glycol, and a nicotine-rich tobacco extract (Slade 1993; Slade 

and Henningfield 1998). Heat from a carbon fuel element 

vaporized material adjacent to the alumina beads, and 

these vapors condensed into more proximal segments to 

form the aerosol that was puffed and inhaled by the consumer (Slade and Henningfield 1998). Compared with 

conventional cigarettes, Premier delivered similar doses 

of nicotine, higher levels of carbon monoxide (CO), and 

reduced levels of many other toxicants (WHO 2001). Premier was test marketed in the United States in 1988 but 

was soon withdrawn because of poor sales (Slade and 

Henningfield 1998).

More recently, tobacco companies have developed 

several other novel cigarette-like products that deliver 

nicotine to the consumer (Stratton et al. 2001; Slade 

et al. 2002). Eclipse (R.J. Reynolds) uses a technology 

similar to that developed for Premier (Slade and Henningfield 1998; Slade et al. 2002): the heat source is 

a carbon fuel element, and nicotine and glycerin are 

vaporized from an aluminum-lined chamber filled 

with what the manufacturer described as “highly 

processed tobacco” and mixed with glycerin. Both 

human and machine-testing data indicate that these products provide no clear benefit to users over conventional 

cigarettes. A report commissioned by the Commonwealth 

of Massachusetts Department of Public Health found that 

intensive machine smoking of Eclipse delivered levels of 

key lung and cancer-causing toxicants (e.g., acrolein, CO) 

similar to, or higher than, those from two commercial 

cigarette brands (Labstat 2000). A complication in evaluating the toxicity of Eclipse is that several prototypes were 

test marketed (Slade et al. 2002). It is not clear whether 

changes not disclosed by the manufacturer account for 

the variability across studies (Stapleton et al. 1998; Lee et 

al. 2004; Breland et al. 2006). Nonetheless, it appears that 

volunteers who had been exposed to Eclipse (Shiffman et 

al. 2004; Hughes et al. 2005) or had heard of it believed it 

to be less harmful than conventional cigarettes. Furthermore, concerns have been raised that Eclipse and Premier 

could be modified to deliver other drugs, including illicit 

drugs (Cone and Henningfield 1989; Steckley et al. 2002).

Accord (Philip Morris) consists of a specially 

designed “cigarette” used in combination with an ignition system (Slade and Henningfield 1998). The handheld, 

battery-operated, microchip-controlled product heats 

a cigarette-like tobacco roll when it is puffed (Slade and 

Henningfield 1998). Although actual-use studies of Accord 

have not been performed, preliminary laboratory studies 

with volunteers suggest the possibility that actual human 

exposure to nicotine and toxicants might substantially 

exceed that predicted by Philip Morris’ tests (Buchhalter 

et al. 2001; Breland et al. 2002; Philip Morris USA 2005). 
The Changing Cigarette 19

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Evaluation of New Cigarette Products

6 to 22 percent and average daily consumption by up to 

14 percent among smokers compared with workers subject to minimal or no restrictions (Farrelly et al. 1999; 

NCI 2000; USDHHS 2000; Bonnie et al. 2007). Products 

that enable nicotine consumption in the workplace and 

other places could reverse these potential reductions in 

smoking prevalence through use of one product in the 

workplace and continued smoking outside, that is, dual 

product use (Henningfield et al. 2002; European Commission 2007). Moreover, the dual use of tobacco products is 

likely to result in greater exposure to toxicants than does 

use of either product type alone (Henningfield et al. 2002).

Balancing the risks and benefits of new cigarette 

products is challenging because of the diversity of products, their associated potential risks and benefits on the 

multitude of tobacco-related diseases, and the dearth of 

empirical data on their effects. The 2001 Institute of Medicine (IOM) report (Stratton et al. 2001) and a report from 

the University of Minnesota Transdisciplinary Tobacco Use 

Research Center raised a series of questions about these 

and similar products (Hughes 2000; Stratton et al. 2001; 

Hatsukami and Hecht 2005; Hatsukami et al. 2005). WHO 

developed similar scientific questions, as well as recommendations for research and product testing (WHO 2003d, 

2004a, 2006, 2007). Although all the questions raised by 

these organizations merit consideration, the following 

questions are a critical starting point for evaluating new 

cigarette or cigarette-like products:

	 •	 Does use of the product decrease individual and

population exposure to the harmful substances in 

tobacco smoke?

	 •	 Is this decreased exposure associated with a decrease

in individual and population risk of disease?

	 •	 Are there surrogate indicators of disease risk that

could be measured in a timeframe of sufficient 

duration for product evaluation?

	 •	 What are the public health implications of products

that may reduce exposure to toxicants in tobacco 

smoke? Specifically, do these products increase initiation of tobacco use, decrease cessation, promote 

relapse among those who have quit, or lead to dual 

product use?

The health consequences of new cigarette products 

have not been demonstrated in scientific studies. The 

challenges include a need for development and validation of testing methods for new products (WHO 2004b). 

Extended nonlaboratory studies under natural conditions with a broader range of biomarkers of toxicants are 

required to determine whether novel products result in 

overall reduction of exposure to toxicants, and still longer 

and more extensive studies would be required to determine whether or not the disease risk of the individual or 

population harm are decreased (WHO 2004a, 2007; Hatsukami et al. 2007). For example, products delivering lower 

levels of nitrosamines might theoretically reduce cancer 

risks, but because many of these products still deliver nicotine and CO, cardiovascular risks may remain unchanged 

or may even increase. In addition, if TSNAs are removed, 

other potent carcinogens may sustain overall high levels 

of exposure to carcinogens (Fowles and Dybing 2003). 

There are substantial risks that the marketing of 

novel cigarettes could lead to increased tobacco use in 

current smokers, relapse in former smokers, and initiation in those who never smoked, particularly youth (Henningfield et al. 2003; Hatsukami et al. 2004a, 2005). For 

example, in a survey of 1,000 current cigarette smokers 

and 499 former smokers older than 18 years of age, 91 

percent thought Eclipse was safer than regular cigarettes, 

24 percent believed Eclipse was completely safe, and 

57.4 percent were interested in using the product (Shiffman et al. 2004). Interest was greatest among those who 

were contemplating smoking cessation, and exposure 

to Eclipse’s claims was followed by a reduced interest in 

cessation. Those interested in using Eclipse included 6.2 

percent of all former smokers and 15.2 percent of young 

adults 18 through 25 years of age who had stopped smoking within the past two years. Further extending these 

findings, Hamilton and colleagues (2004) found that 

advertisements for light cigarettes were perceived to imply that their use is healthier than use of regular cigarettes, partly because consumers wrongly believed that 

the advertisements must be approved and endorsed by a 

government agency.

In addition, products designed or marketed to 

be used in places where smoking is not allowed may 

defeat public health efforts to reduce smoking rates. For 

example, studies have found that having a 100-percent 

smoke-free workplace reduced smoking prevalence by 
Surgeon General’s Report

20 Chapter 2

New Oversight of Tobacco Products

2007, or modified after that date) to submit an application 

containing specified manufacturing and ingredient information, as well as studies of the product’s health risks, for 

FDA review. After reviewing the application, the agency 

will issue an order either permitting the product to be 

marketed or denying its marketing according to specified 

bases for its action. New tobacco products determined by 

FDA to be substantially equivalent to products already on 

the market as of February 15, 2007, are not required to 

undergo premarket review.

Section 911 provides that “modified risk tobacco 

products” may only be marketed if FDA determines, 

after reviewing a product application, that the product will 

significantly reduce the risk of tobacco-related disease to 

individual users, and benefit the health of the population 

as a whole, taking into account the impact on both users 

and nonusers of tobacco products. Section 911 recognizes 

so-called special rule products, which also require premarket approval. Such products may be marketed for up 

to five years (subject to renewal) if the agency determines 

that the applicant has met specified criteria, the applicant 

agrees to conduct certain postmarket surveillance and 

studies, and other specified findings regarding the relative 

harm of the product are made. Under this section, FDA 

must issue guidance or regulations on the scientific evidence required for the assessment and ongoing review of 

modified-risk tobacco products in consultation with IOM.

On June 22, 2009, President Barack Obama signed 

into law the Family Smoking Prevention and Tobacco 

Control Act (Public Law 111-31). The Tobacco Control 

Act grants the U.S. Food and Drug Administration (FDA) 

the authority to regulate tobacco products to protect the 

public’s health and recognizes FDA as the primary federal 

regulatory authority with respect to the manufacture, 

marketing, and distribution of tobacco products. Key elements of the act include, among other things, creation 

of a new Center for Tobacco Products, prohibition of the 

sale of cigarettes containing certain characterizing flavors, the requirement that manufacturers and importers 

report to FDA the ingredients and additives in their products, strengthened warning labels with graphic images of 

the adverse effects of cigarette use, and oversight of the 

tobacco industry’s efforts to develop and market potential 

reduced-exposure tobacco products. The Tobacco Control 

Act also requires FDA to reissue the agency’s 1996 regulation aimed at reducing young people’s access to tobacco 

products and curbing the appeal of tobacco to the young. 

Although some provisions of the act went into effect 

shortly after the statute was enacted, such as the ban on 

flavored cigarettes, others will be implemented over time.

Sections 910 and 911 of the Tobacco Control Act 

provide that premarket review of certain tobacco products 

by FDA is required before the products may be marketed. 

Section 910 requires manufacturers of new tobacco products (those not commercially marketed as of February 15, 

Summary

To reduce smoking-attributable death and disease, 

public health efforts since the 1964 Surgeon General’s 

report on smoking and health have focused on reducing the prevalence of tobacco use. Reduced prevalence 

has been achieved through efforts to prevent tobacco use 

and promote cessation; this effort has been termed one of 

the “ten great public health achievements of the twentieth century” (CDC 1999). At the time the adverse effects 

of smoking were being recognized, the tobacco industry 

developed cigarettes with low machine-measured yields 

of tar and nicotine, and public health authorities encouraged consumers to select them (Peeler 1996; Shopland 

2001). Unfortunately, it took public health researchers 

and federal authorities many years to discover what the 

tobacco industry knew much earlier: the health benefits 

of reductions of tar and nicotine intakes were negligible 

at best for persons using these products (Federal Register

1995, 1996; NCI 2001; WHO 2001; U.S. v. Philip Morris No. 

449 F. Supp. 2d 1, 430–75 [D.D.C. 2006]). In 2001, an NCI 

report concluded: “There is no convincing evidence that 

changes in cigarette design between 1950 and the mid 1980s 

have resulted in an important decrease in the disease burden caused by cigarette use either for smokers as a group 

or for the entire population” (NCI 2001, p. 146). Thus, by 

the twenty-first century, it was apparent that five decades 

of evolving cigarette design had not reduced overall disease 

risk among smokers, and new designs were used by the 

tobacco industry as a tool to undermine prevention and 

cessation efforts (NCI 2001; Stratton et al. 2001; WHO 

2001, 2003a,b,c; USDHHS 2004). 
The Changing Cigarette 21

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Similarly, informative and comprehensive scientific 

evaluations do not exist for any of the other new products developed ostensibly to reduce toxicants in cigarette 

smoke. This lack of data limits any conclusions that can be 

drawn about potential health risks or benefits.

The well-documented risks of cigarette design 

changes must be weighed against any potential benefits 

(Stratton et al. 2001). As this chapter makes clear, substantial risks may be associated with new tobacco products: (1) smokers who might have otherwise stopped 

smoking may continue to smoke because of perceived 

reduction in risk with use of new products; (2) former 

smokers may resume smoking because of perceived reduction in risk with use of new products; and (3) nonsmokers, 

particularly youth, may start to use new products because 

of their perceived safety. The theoretical benefit of cigarette design changes is to reduce exposure to toxicants sufficiently to reduce the risk of disease and death. However, 

if these products are used by persons otherwise unlikely 

to use a tobacco product, which would undermine efforts 

to prevent tobacco use, or if the products delay cessation 

among persons who would otherwise stop using tobacco, 

the overall health of the population would be harmed. 

There is little doubt that new tobacco products will 

continue to be developed. Consequently, there is a critical need to conduct independent research on the design, 

composition, and health effects of new cigarette products 

and to put in place a comprehensive surveillance system to understand consumers’ knowledge, attitudes, and 

behaviors regarding these products.

Conclusions

1. The evidence indicates that changing cigarette 

designs over the last five decades, including filtered, 

low-tar, and “light” variations, have not reduced overall disease risk among smokers and may have hindered prevention and cessation efforts.

2. There is insufficient evidence to determine whether 

novel tobacco products reduce individual and population health risks. 

3. The overall health of the public could be harmed if 

the introduction of novel tobacco products encourages tobacco use among people who would otherwise 

be unlikely to use a tobacco product or delays cessation among persons who would otherwise quit using 

tobacco altogether.
Surgeon General’s Report

22 Chapter 2

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27

Chapter 3

Chemistry and Toxicology of Cigarette Smoke

and Biomarkers of Exposure and Harm

Introduction 29

Chemistry 30

Phases of Tobacco Smoke 30

Nicotine and Free Nicotine 31

N-Nitrosamines 34

Polycyclic Aromatic Hydrocarbons 37

Volatile Compounds Including Aldehydes 38

Heavy Metals 40

Aromatic Amines 41

Heterocyclic Amines 43

Effect of Additives on Tobacco Smoke 44

Delivery of Chemical Constituents into Tobacco Smoke 45

Delivery of Chemicals to Smokers 47

Biomarkers 51

General Concepts 51

Biomarkers of Exposure 52

Biomarkers of Biologically Effective Dose 53

Biomarkers of Biologic Events with the Potential to Lead to Harm 54

Genotoxicity 56

Cigarette Smoke Condensate 56

Studies in Humans 57

Cytotoxicity 59

Animal Bioassays 61

Cardiovascular and Cerebrovascular Studies in Animals 67

Respiratory Studies in Animals 69

Reproductive and Developmental Studies in Animals 71

Other Health Effects 74

Summary 77

Conclusions 79

References 80

Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 29

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Introduction

The section on “Biomarkers” offers an overview of 

in vitro and in vivo data on genotoxicity and cytotoxicity and a review of the literature on animal bioassays, in 

addition to general concepts of biomarkers of exposure, 

of biologically effective dose, and of potential harm, as an 

introduction to more detailed descriptions of biomarkers 

in subsequent chapters of this Surgeon General’s report.

Cigarette smoke is a complex mixture of chemical 

compounds that are bound to aerosol particles or are free 

in the gas phase. Chemical compounds in tobacco can be 

distilled into smoke or can react to form other constituents that are then distilled to smoke. Researchers have 

estimated that cigarette smoke has 7,357 chemical compounds from many different classes (Rodgman and Perfetti 

2009). In assessing the nature of tobacco smoke, scientists 

must consider chemical composition, concentrations of 

components, particle size, and particle charge (Dube and 

Green 1982). These characteristics vary with the cigarette 

design and the chemical nature of the product.

Fowles and Dybing (2003) suggested an approach to 

identify the chemical components in tobacco smoke with 

the greatest potential for toxic effects. They considered 

the risk for cancer, cardiovascular disease, and heart disease. Using this approach, these investigators found that 

1,3-butadiene presented by far the most significant cancer 

risk; acrolein and acetaldehyde had the greatest potential 

to be respiratory irritants; and cyanide, arsenic, and the 

cresols were the primary sources of cardiovascular risk. 

Other chemical classes of concern include other metals, N-nitrosamines, and polycyclic aromatic hydrocarbons (PAHs). This evaluation, along with the Hoffmann 

list of biologically active chemicals (Hoffmann and Hoffmann 1998), was used to select the chemicals reviewed in 

this chapter. Other chemical components with potential 

for harm will be identified as analysis of tobacco smoke 

becomes more complete and cigarette design and additives change.

This chapter summarizes the state of knowledge 

about the chemistry and toxicology of cigarette smoke and 

provides data relevant to the evaluations and conclusions 

presented in the disease-specific chapters of this report. 

The literature reviewed in this chapter is limited to manufactured cigarettes and does not include publications on 

handmade (“roll your own”) cigarettes or other products 

that contain nicotine. The next section, “Chemistry,” 

includes a brief description of technologies used by cigarette manufacturers in a limited number of cigarette 

brands marketed as “reduced-exposure” or “lower-yield” 

products. These commercial products have not been met 

with widespread consumer acceptance. The following section, “Biomarkers,” focuses on the manufactured tobaccoburning cigarette consumed by the majority of smokers in 

the United States and elsewhere. 

The section on “Chemistry” describes the chemical components of cigarette smoke and addresses aspects 

of product design that alter the components of cigarette 

smoke and factors affecting delivery of smoke to the 

smoker. In most cases, the data reported for chemical 

levels in mainstream smoke were derived under standard 

smoking conditions described by the U.S. Federal Trade 

Commission (FTC) and the International Organization 

for Standardization (ISO). These standard conditions are 

puff volume of 35 milliliters (mL), two-second puff duration, one-minute puff frequency, and butt length defined 

as either 23 millimeters (mm) for nonfilter cigarettes or 

the length of the filter overwrap paper plus 3 mm. When 

alternative smoking regimens are used, levels of potentially harmful substances in smoke emissions usually 

differ from those measured under standard conditions. 

(For more details, see “Delivery of Chemical Constituents 

into Tobacco Smoke” later in this chapter.) When people 

smoke, they do not use the puff volume and puff frequency 

programmed into smoking machines, and smoking habits vary significantly from person to person and cigarette 

to cigarette. Consequently, actual exposures to and doses 

of components of smoke cannot be derived from values 

obtained with machine smoking. 
Surgeon General’s Report

30 Chapter 3

Chemistry

during puffing (Johnson et al. 1973b; Perfetti et al. 1998). 

Thus, the way the cigarette is smoked (e.g., puff volume 

and time between puffs) can alter the relative levels of 

mainstream and sidestream smoke (Perfetti et al. 1998). 

In addition, the ratio of the levels of chemical components in sidestream smoke to their levels in mainstream 

smoke can be altered by differences among cigarettes 

(Perfetti et al. 1998). These differences are related to the 

tobacco blend or type, the tobacco preparation (e.g., cut 

width, additives, and moisture level), the dimensions of 

the cigarette, the weight of the tobacco rod, the porosity 

of the paper, the presence of a filter, and the type of filter. 

Studies using a machine that simulates human smoking 

have determined that the change in the ratio of sidestream 

to mainstream smoke components after introducing a filter and ventilation primarily resulted from a decrease in 

the amount of mainstream smoke, because the amount 

of sidestream smoke does not change substantially with 

alterations in cigarette design (Perfetti et al. 1998). 

Examination of chemicals with similar properties revealed 

that those with a low boiling point had higher ratios of 

levels in sidestream smoke to levels in mainstream smoke 

and that compounds with a high boiling point had lower 

ratios (Sakuma et al. 1984). Studies indicate that compared 

with mainstream smoke collected under standard FTC/

ISO smoking parameters, sidestream smoke has higher 

levels of PAHs (Grimmer et al. 1987; Evans et al. 1993); 

nitrosamines (Brunnemann et al. 1977a, 1980; Hoffmann 

et al. 1979a; Rühl et al. 1980); aza-arenes (Dong et al. 1978; 

Grimmer et al. 1987); aromatic amines (Patrianakos and 

Hoffmann 1979); carbon monoxide (CO) (Hoffmann et al. 

1979b; Rickert et al. 1984); nicotine (Rickert et al. 1984; 

Pakhale et al. 1997); ammonia (Brunnemann and Hoffmann 1975); pyridine (Johnson et al. 1973b; Brunnemann 

et al. 1978; Sakuma et al. 1984); and the gas phase components 1,3-butadiene, acrolein, isoprene, benzene, and 

toluene (Brunnemann et al. 1990). With increased puffing 

intensity, the toxicant ratios of sidestream to mainstream 

smoke decrease (Borgerding et al. 2000).

The increase in the amount of tobacco burned 

during smoldering compared with tobacco burned during puffing is not the only factor influencing differences 

in the chemical content of sidestream and mainstream 

smoke. The burning conditions that generate sidestream 

and mainstream smoke also differ (Guerin 1987). Temperatures reach 900°C during a puff and fall to about 

400°C between puffs (Guerin 1987). Puffing burns the 

tobacco on the periphery of the cigarette, and tobacco in 

Phases of Tobacco Smoke

Smoke from a burning cigarette is a “concentrated 

aerosol of liquid particles suspended in an atmosphere 

consisting mainly of nitrogen, oxygen, carbon monoxide 

and carbon dioxide” (Guerin 1980, p. 201). Researchers 

have also described cigarette smoke as a “lightly charged, 

highly concentrated matrix of submicron particles contained in a gas with each particle being a multicompositional collection of compounds arising from distillation, 

pyrolysis, and combustion of tobacco” (Dube and Green 

1982, p. 42). Tobacco smoke is a complex and dynamic 

chemical mixture. Researchers have analyzed whole 

smoke or used chemical and physical means to separately examine the gas and particulate portions of tobacco 

smoke. The gas phase is defined as the portion of smoke 

that passes through a glass fiber filter of specified physical parameters, and the particulate phase refers to all 

matter captured by the glass fiber filter (Pillsbury 1969). 

Standard methods for analysis of tobacco smoke separate the two phases by using Cambridge glass fiber filters 

designed to collect aerosol particles of 0.3 micrometers 

(μm) or larger with an efficiency not less than 99 percent 

(Pillsbury 1969). Although these separate phases are an 

artificial construct, they are useful for describing the 

results of analysis of the components of cigarette smoke 

typically obtained by machine smoking. When people 

smoke cigarettes, the continuum of physical characteristics in smoke does not include the differentiation into 

specific fractions. The diameter of cigarette smoke particles constantly changes, and as the particles coalesce 

after their formation, they grow in diameter. However, in 

diluted smoke, loss of a volatile chemical matrix or other 

components may cause particles to shrink and changes in 

the particle size may alter the relative amounts of certain 

chemicals in the gas and particle phases (Guerin 1980). 

Smoke formation occurs when the cigarette is lit 

and a puff is taken or when the cigarette smolders between 

puffs. Mainstream smoke is released from the butt end 

of the burning cigarette during puffing, and sidestream 

smoke emanates from the burning cigarette coal when it 

smolders (Guerin 1980). The air in the immediate vicinity of an active smoker contains a mixture of sidestream 

smoke, exhaled mainstream smoke, and any smoke that 

passes through the porous paper surrounding the tobacco 

(Löfroth 1989). A greater quantity of sidestream smoke 

is generated when the amount of tobacco burned during smoldering increases relative to the amount burned 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 31

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

the core burns between puffs (Johnson 1977; Hoffmann 

et al. 1979a). Thus, mainstream smoke depends on the 

chemical composition of the combustible portion of the 

cigarette near the periphery of the rod, whereas chemicals at higher concentrations in the central portion of 

the rod have higher levels in sidestream smoke than in 

mainstream smoke (Johnson 1977). Sidestream smoke 

is produced during conditions with less available oxygen 

(Guerin et al. 1987) and higher alkalinity and water content than those for mainstream smoke (Brunnemann and 

Hoffmann 1974; Adams et al. 1987; Guerin 1987). Ammonia levels are significantly higher in sidestream smoke, 

resulting in a more alkaline pH (Adams et al. 1987). Thus, 

the composition and levels of chemical species in mainstream smoke differ from those in sidestream smoke. 

Levels of some compounds are higher in mainstream 

smoke than in sidestream smoke, and this difference may 

reflect chemical influences that are more complex than 

just changes in puff frequency. For example, mainstream 

smoke contains considerably more cyanide than sidestream smoke does (Johnson et al. 1973b; Brunnemann 

et al. 1977a; Norman et al. 1983). Sakuma and colleagues 

(1983) measured a series of semivolatile compounds in 

tobacco smoke and found that levels of phenol, cresol, 

xylenols, guiacol, formic acid, and acetic acid were higher 

in sidestream smoke, whereas levels of catechol and 

hydroquinone were higher in mainstream smoke. 

Individual chemical constituents may be found 

in the particulate phase, the gas phase, or both (Guerin 

1980). As cigarette smoke dissipates, chemicals may pass 

between the particulate and gas phases (Löfroth 1989). 

The gas phase contains gases and chemical constituents 

that are sufficiently volatile to remain in the gas phase 

long enough to pass through the Cambridge glass fiber 

filter (Guerin 1980), but as the filter becomes wet during the first puffs, hydrophilic compounds tend to adhere 

to it. The gas phase of cigarette smoke includes nitrogen (N2), oxygen (O2), carbon dioxide (CO2), CO, acetaldehyde, methane, hydrogen cyanide (HCN), nitric acid, 

acetone, acrolein, ammonia, methanol, hydrogen sulfide 

(H2S), hydrocarbons, gas phase nitrosamines, and carbonyl compounds (Borgerding and Klus 2005; Rodgman 

and Perfetti 2009). Constituents in the particulate phase 

include carboxylic acids, phenols, water, humectants, 

nicotine, terpenoids, paraffin waxes, tobacco-specific 

nitrosamines (TSNAs), PAHs, and catechols. Mainstream 

smoke contains only a small amount of nicotine in the 

gas phase (Johnson et al. 1973b; Pakhale et al. 1997), but 

the fraction of nicotine in the gas phase is higher in sidestream smoke because of the higher pH (Johnson et al. 

1973b; Brunnemann and Hoffmann 1974; Adams et al. 

1987; Pakhale et al. 1997). Brunnemann and colleagues 

(1977b) studied both mainstream and sidestream smoke 

and found that the gas phase of mainstream smoke contained more cyanide than did the particulate phase. Johnson and colleagues (1973b), however, showed that in 

sidestream smoke, cyanide is present almost exclusively in 

the particulate phase. Guerin (1980) concluded that both 

formaldehyde and cyanide may be present in both phases, 

and Spincer and Chard (1971) found formaldehyde in both 

the particulate and gas phases. The PAHs in the gas phase 

were only 1 percent of total PAHs, and the PAH distribution between gas and particulate phases varied with the 

boiling point of the PAHs (Grimmer et al. 1987). Because 

physical and chemical changes occur after tobacco smoke 

is drawn from the cigarette, some of the reported differences in PAH levels could result from differences in measurement techniques.

In summary, cigarette smoke is a complex and 

dynamic system. The concentration of smoke and the time 

after it leaves the cigarette can cause changes in particle 

size that may alter the relative amounts of certain chemicals in the gas and particle phases. Also, specific properties of the tobacco, the physical design of the cigarette, 

and the machine-smoking method that is employed to 

generate mainstream smoke for analyes can have a significant impact on the levels of both mainstream and sidestream emissions.

Nicotine and Free Nicotine

The tobacco leaf contains many alkaloid chemicals; 

nicotine is the most abundant. Nicotine content varies, 

among other factors, by the leaf position on the tobacco 

stalk and also by the blend or leaf type used in a given 

cigarette or cigar (Tso 1990; Kozlowski et al. 2001). Plants 

such as tobacco that are characterized by high alkaloid 

content often possess a natural pharmacologic defense 

against microorganisms, insects, and vertebrates. For 

example, nicotine is toxic to many insects and, for many 

years, has been extracted from tobacco for use as a commercial pesticide (Domino 1999). Nicotine is addictive in 

humans because a portion of the nicotine molecule is similar to acetylcholine, an important brain neurotransmitter 

(Brody et al. 2006). 

The alkaloids in tobacco leaf include anatabine, 

anabasine, nornicotine, N-methylanabasine, anabaseine, 

nicotine, nicotine N’-oxide, myosmine, β-nicotyrine, 

cotinine, and 2,3′-bipyridyl (Figure 3.1). In commercial 

tobacco products, nicotine concentrations range from 6 

to 18 milligrams per gram (mg/g) (0.6 to 1.8 percent 

by weight) (International Agency for Research on Cancer [IARC] 2004; Counts et al. 2005). Together, the sum 

of the concentrations of anatabine, anabasine, and nornicotine equals approximately 5 percent of the nicotine 
Surgeon General’s Report

32 Chapter 3

concentration (Jacob et al. 1999). Many minor tobacco 

alkaloids are pharmacologically active in humans in one or 

more ways. Clark and colleagues (1965) observed that some 

of these alkaloids had physiological effects in a variety of 

animal tests. Lefevre (1989) reviewed the evidence and concluded that anabasine and nornicotine had demonstrated 

effects on smooth muscle fiber, blood pressure, and enzyme 

inhibition. The literature on potentially addictive properties of these minor alkaloids is limited. S(-)-nicotine, 

which is present in the tobacco leaf, is structurally similar to forms of several minor alkaloids also found in the 

tobacco leaf, such as S(-)-N-methylanabasine (Figure 3.2). 

Moreover, Dwoskin and colleagues (1995) reported that in 

the rat, anatabine, anabasine, N-methylanabasine, anabaseine, and nornicotine all release dopamine from striatal 

brain tissue. Overall, it is likely that some of the minor 

tobacco alkaloids could (1) be addictive if delivered 

alone at sufficiently high levels and (2) act together with 

nicotine during tobacco use to generate effects that are 

difficult to discern because nicotine levels are so much 

higher. In addition to addictiveness, both nicotine and 

minor secondary amine alkaloids are precursors of carcinogenic TSNAs (IARC 2004, 2007).

The unprotonated nicotine molecule contains two 

nitrogen atoms with basic properties. The unprotonated nicotine molecule can thus add one proton to form 

a monoprotonated species or two protons to form the 

diprotonated species (Figure 3.3) (Brunnemann and Hoffmann 1974). The first proton added to nicotine attaches 

predominantly to the nitrogen on the five-membered 

(pyrrolidine) ring, because that nitrogen is significantly 

more basic than the nitrogen on the six-membered (pyridine) ring. Although protonated nicotine is not volatile, 

unprotonated nicotine is volatile and is able to enter the 

gas phase and readily pass into lipid membranes. Unprotonated nicotine is therefore free of the limitations that 

Figure 3.1 Tobacco alkaloids
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 33

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

come with carrying an ionic charge, and the scientific 

literature and tobacco industry documents frequently 

refer to nicotine in this form as both “free nicotine” and 

“free-base nicotine.” In the tobacco plant and in the dried 

leaf, nicotine largely exists in its ionic forms; otherwise, it 

would be rapidly lost to the surrounding atmosphere.

In water or in the droplets of particulate matter in 

tobacco smoke, the distribution of nicotine among its 

three forms depends on the pH of the solution. Increasing acidity of the solution increases the fraction of protonated molecules; conversely, increasing basicity increases 

the fraction in the unprotonated (free base) form (Figure 

3.3). Because all forms of nicotine are highly soluble in 

water, all of the nicotine entering the respiratory tract 

from one puff of tobacco smoke easily dissolves in lung 

fluids and blood. However, because unprotonated nicotine 

from tobacco smoke particles is volatile, whereas protonated nicotine is not, a higher percentage of unprotonated 

nicotine in a puff results in a higher rate of nicotine deposition in the respiratory tract (Pankow 2001; Henningfield 

et al. 2004). The exact nature and effects of the increased 

rate of deposition depends on the chemical composition 

and the size of particles in the tobacco smoke, as well as 

topographic characteristics of smoking, such as puff size 

and duration and depth of inhalation. Increased rates of 

deposition in the respiratory tract lead to increased rates 

of nicotine delivery to the brain, which intensify the 

addictive properties of a drug (Henningfield et al. 2004). 

The conventional view has been that a sample of particulate matter from tobacco smoke is not usually so 

acidic that the diprotonated form becomes important. In 

water at room temperature, the approximate dividing line 

between dominance by protonated forms or by the unprotonated form is a pH of 8 (González et al. 1980). At higher 

pH, the fraction of unprotonated nicotine (αfb) is greater 

than the fraction of protonated nicotine (Pankow 2001). 

At pH 8, the two fractions are present in equal percentages. At any lower pH, the fraction of protonated nicotine 

is greater. 

Because a typical sample of particulate matter from 

tobacco smoke collected from a cigarette or cigar is mostly 

nonaqueous liquid, it is not possible to take conventional 

pH measurements to determine nicotine distribution 

between the monoprotonated and unprotonated forms 

(Pankow 2001). However, it is possible to measure the 

concentration of unprotonated nicotine in a sample of 

tobacco smoke particulate (cp,u), because that level produces a directly proportional concentration of unprotonated nicotine in the gas phase, which is measurable 

(Pankow et al. 1997, 2003; Watson et al. 2004). Measuring the concentration of nicotine in a sample of tobacco 

smoke in the particulate phase (cp,t) allows calculation of 

the fraction of unprotonated nicotine: αfb = cp,u/cp,t (Pankow et al. 2003). To simplify the discussion of αfb values 

in tobacco smoke, Pankow (2001) introduced the term 

“effective pH” (pHeff), which refers to the pH needed in 

water to obtain the αfb value in a sample of particulate 

matter from smoke. Reported values of αfb for smoke from 

commercial cigarettes at 20oC were 0.006 to 0.36 (Pankow et al. 2003; Watson et al. 2004), which corresponds to 

pHeff values at 20oC in the range of 5.8 to 7.8.

Figure 3.2 Structures of nicotine and minor 

alkaloid S(-)-N-methylanabasine in 

tobacco leaf

Figure 3.3 Three forms of nicotine
Surgeon General’s Report

34 Chapter 3

The fraction αfb for particulate matter in tobacco 

smoke is important because the rapidity with which 

inhaled nicotine from tobacco smoke evaporates from 

the particulate phase and deposits on the linings of the 

respiratory tract is directly proportional to the αfb

value for the smoke (Pankow et al. 2003). According to 

numerous tobacco industry documents, increasing levels 

of unprotonated nicotine in tobacco smoke was known 

to increase smoke “strength,” “impact,” “kick,” and/or 

“harshness” (Backhurst 1965; Dunn 1973; Teague 1974; 

Ingebrethsen and Lyman 1991). Because of similar mechanisms, nicotine replacement therapy delivering gaseous 

nicotine caused throat irritation at delivery levels per puff 

that were similar to those reached by smoking a cigarette 

rated by using the FTC regimen at approximately 1 mg of 

total nicotine delivery; thus, cigarette design is focused on 

a balance between smoke “impact” and irritation. Some 

researchers have suggested that the irritation and harshness of smoke at higher pH makes it harder for smokers to 

inhale this smoke into the lungs (Brunnemann and Hoffmann 1974).

The value of αfb for particulate matter in each puff 

of smoke from one brand of cigarette or cigar strongly 

depends on the overall proportion of acids to bases in the 

puff (Pankow et al. 1997). As already noted, nicotine itself 

is a base. The natural acids in tobacco smoke (e.g., formic 

acid, acetic acid, and propionic acid) can protonate nicotine and tend to reduce αfb from its maximum of 1.0. The 

natural bases (e.g., ammonia) tend to neutralize the acids 

and keep more nicotine in the unprotonated form.

Variability in the acid-base nature of commercially available tobacco leaf is considerable. Flue-cured 

(“bright”) tobacco is typically viewed as producing acidic 

smoke. Air-cured (“burley”) tobacco is typically viewed as 

producing basic smoke. Simple adjustment of the tobacco 

blend can therefore produce a considerable range of acid 

or base content in tobacco smoke. In acidic smoke, αfb can 

be 0.01 or lower (e.g., 1-percent unprotonated nicotine), 

and in basic smoke, the αfb can be relatively high (e.g., 

0.36 [36-percent unprotonated nicotine]) (Pankow et al. 

2003; Watson et al. 2004). 

Tobacco additives that are bases increase αfb values 

in mainstream smoke, and these additives are discussed 

extensively in tobacco industry documents (Henningfield et al. 2004). The documents reveal that a variety of 

basic additives have been considered, including ammonia 

and ammonia precursors. Conversely, some manufacturers also were interested in reducing harshness to a minimum and investigated acidic additives such as levulinic 

acid as “smoothing” agents. In that context, the natural basicity of a specific blend and the harshness of the 

smoke can be reduced by acidic additives such as levulinic 

acid, which tend to reduce αfb (Guess 1980; Stewart and 

Lawrence 1988).

In summary, nicotine in cigarette smoke exists in 

either a protonated or unprotonated form, depending on a 

number of factors, including the presence of natural acids 

and bases, the tobacco blend, tip ventilation, and the use 

of additives. Cigarette design ensures that the smoke has 

enough unprotonated nicotine to rapidly transfer nicotine 

into the body but not so much of it as to be too harsh for 

the smoker to continue to smoke.

N-Nitrosamines

N-nitrosamines are a class of chemical compounds 

containing a nitroso group attached to an amine nitrogen. There are two types of nitrosamines in tobacco 

and tobacco smoke: volatile and nonvolatile, including TSNAs (Hoffmann et al. 1981; Tricker et al. 1991; 

Spiegelhalder and Bartsch 1996; IARC 2007). The 

volatile nitrosamines include N-nitrosodimethylamine, 

N-nitrosoethylmethylamine, N-nitrosodiethylamine, 

N-nitro-sopyrrolidine, and N-nitrosomorpholine. The 

nonvolatile nitrosamines are 4-(N-nitroso-N-methylamino)butyric acid, N-nitrosopipecolic acid, N-nitrososarcosine, 3-(N-nitroso-N-methylamino)propionic acid, 

N-nitrosoproline, and N-nitrosodiethanolamine. The 

nonvolatile TSNAs (Figure 3.4) have been examined 

extensively in tobacco and tobacco smoke. They include 

N’-nitrosonornicotine (NNN), 4-(methylnitrosamino)-

1-(3-pyridyl)-1-butanone (NNK), N’-nitrosoanatabine 

(NATB), and N’-nitrosoanabasine (NAB). The levels of 

nitrosamines in tobacco products are higher than are 

those in other consumer products, such as cooked bacon 

and beer (Hecht and Hoffmann 1988), and smokers are 

exposed to higher levels of TSNAs than of the other nitrosamines (Hoffmann et al. 1981; IARC 2007).

Studies have been conducted to identify precursors 

of nitrosamines and to determine the conditions required 

for their formation in tobacco. The primary intent of this 

research was to identify ways to reduce nitrosamine levels in tobacco and tobacco smoke. Secondary and tertiary 

amines in tobacco, including the alkaloids, react with 

nitrosating agents to form N-nitrosamines (Hecht and 

Hoffmann 1988). Hecht and colleagues (1978) showed 

that both nicotine and nornicotine can react with sodium 

nitrite under controlled conditions to form carcinogenic NNN and NNK, but nicotine is considered more 

important because of its higher level in tobacco products. 

TSNAs are not present at trace levels in freshly harvested 

tobacco, but they are predominantly formed during processing, curing, and storage (Hoffmann et al. 1974, 1981; 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 35

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Chamberlain et al. 1984; Andersen and Kemp 1985; Bhide 

et al. 1987; Djordjevic et al. 1989; Fischer et al. 1989b; 

Fisher 2000a). Aerobic bacteria play a major role in TSNA 

formation in air-cured tobacco (Hecht et al. 1975; Hoffmann et al. 1981; Parsons et al. 1986). In flue-cured 

tobacco, the curing conditions alter levels of nitrosamines 

(Fisher 2000a). Before the late 1960s and early 1970s, 

direct-fire curing in the United States did not produce 

high levels of TSNAs. When propane gas was introduced 

as the combustion source (Fisher 2000a), nitrogen oxides 

from the exhaust gases in tobacco barns reacted with alkaloids in the tobacco plant to form TSNAs. Hoffmann and 

colleagues (Hoffmann et al. 1981; Brunnemann and Hoffmann 1991) also revealed that N-nitrosodiethanolamine is 

formed from the diethanolamine used in the formulation 

of maleic hydrazide, which is applied to regulate suckers 

on tobacco plants.

Volatile nitrosamines are found primarily in the gas 

phase of tobacco smoke, and TSNAs are almost exclusively 

found in the particulate phase (Guerin 1980). Researchers 

suggest that about one-half of the nitrosamines in tobacco 

smoke are transferred unchanged from the tobacco to the 

smoke and that the remainder is formed from pyrosynthesis during smoking (Hoffmann et al. 1977; Adams et al. 

1983). Other researchers have concluded that almost all 

TSNAs are transferred directly from the tobacco (Fischer 

et al. 1990b).

It is difficult to determine whether TSNAs are 

pyrosynthesized or transferred intact, because the most 

important factors in nitrosamine formation such as concentrations of preformed TSNA in tobacco or their precursor, as well as chemical and physical processes during 

smoking, could affect either mechanism. Morie and Sloan 

(1973) reported that the nitrate and amine content in 

tobacco determined the amount of N-nitrosodimethylamine formed in tobacco smoke. This finding has been 

widely duplicated by researchers looking at other nitrosamines (Hecht et al. 1975; Brunnemann et al. 1977a, 1983; 

Hoffmann et al. 1981; Adams et al. 1983, 1984; Fischer et 

al. 1989b; Tricker et al. 1991; Atawodi et al. 1995; Spiegelhalder and Bartsch 1996). Other factors that influence nitrate concentrations in tobacco can also indirectly 

influence nitrosamine concentrations. Because TSNA 

content is strongly influenced by the use of stems that are 

naturally high in TSNAs in the cigarette rod, the increased 

use of stems leads to higher nitrosamines in the smoke 

(Brunnemann et al. 1983). Researchers have also found 

that the use of nitrogen fertilizer can contribute to the 

concentration of nitrosamines in tobacco and ultimately 

in the smoke (Johnson and Rhoades 1972; Tso et al. 1975; 

Brunnemann et al. 1977a; Chamberlain et al. 1984, 1986). 

Other influential factors identified were tobacco growth 

conditions, storage times, storage temperatures (Andersen et al. 1982; Andersen and Kemp 1985), and the stalk 

positions from which the tobacco leaves are harvested 

(Chamberlain et al. 1986).

Another factor contributing to nitrosamine concentrations in tobacco is the type of tobacco used (Johnson 

Figure 3.4 Tobacco-specific nitrosamines
Surgeon General’s Report

36 Chapter 3

and Rhoades 1972; Brunnemann et al. 1983; Fischer et 

al. 1989b,c). Oriental tobaccos are lowest in both nitrates 

and TSNAs (Fischer et al. 1989b), whereas burley tobacco 

contains the highest TSNA concentrations (Fischer et 

al. 1989b,c). The nitrosamine concentrations in bright 

tobacco are between those in oriental and burley and 

depend on the curing practices described earlier (Tso et al. 

1975; Hoffmann et al. 1979a). The TSNA concentrations 

are higher in blended cigarettes than in those made from 

bright tobacco, because burley is included in the blend 

(Fischer et al. 1990a). In most tobaccos, NNN concentrations exceed NNK concentrations (Fischer et al. 1989b), 

but in bright tobacco, NNK concentrations exceed those 

of NNN (Fischer et al. 1989b, 1990a).

The preformed concentration of nitrosamines in 

tobacco leaves and stems is a major determinant of the 

levels in tobacco smoke (Fischer et al. 1990c; Spiegelhalder and Bartsch 1996). However, for cigarettes that have 

the same concentrations of nitrosamines in the tobacco, 

the nitrosamine levels in the smoke were largely determined by the degree of ventilation and the use of cellulose-acetate filter tips in the cigarette. After examining 

machine-generated smoke, by the FTC/ISO method, from 

cigarettes containing the same type of tobacco, whether 

blended or bright only, researchers found that nitrosamine 

levels are correlated with tar delivery, which is primarily 

a function of filter ventilation (Adams et al. 1987; Fischer 

et al. 1990a). However, studies of cigarettes with different 

blends of tobacco have shown that tar is not an accurate 

measure of nitrosamine levels (Fischer et al. 1989c; Spiegelhalder and Bartsch 1996; Counts et al. 2004). Studies 

have also shown that cellulose-acetate filter tips remove 

both volatile nitrosamines and TSNAs (Morie and Sloan 

1973; Brunnemann et al. 1980; Rühl et al. 1980; Hoffmann 

et al. 1981). These findings indicate the importance of 

measuring TSNA levels in smoke, rather than using measured levels of tar or nicotine to predict levels of TSNAs in 

smoke on the basis of an average relationship between tar 

or nicotine and TSNAs. 

Nitrosamine levels measured in the tobacco and the 

smoke from cigarettes that were purchased around the 

world vary widely because of the differences cited above. 

Historically, the ranges of levels of NNN (2 to 12,454 

nanograms [ng] per cigarette), NAB+NATB (109 to 1,033 

ng), and NNK (55 to 10,745 ng) in cigarette tobacco were 

wide (Hoffmann et al. 1974; Fischer et al. 1989b, 1990a,c; 

Tricker et al. 1991; Atawodi et al. 1995; IARC 2004, 2007). 

More recent analyses have given more consistent results 

that depend on the blend of tobacco (NNN + NNK: 87 to 

1,900 ng/g) (Ashley et al. 2003). Levels in mainstream 

tobacco smoke, as reported by the FTC/ISO machinesmoking method, have been reported at an order of magnitude lower than those in tobacco (NNN = 4 to 1,353 ng 

generated per cigarette); NAB+NATB = 10 to 82 ng; and 

NNK = 5 to 1,749 ng (Fischer et al. 1989b, 1990a,c; Tricker 

et al. 1991; Atawodi et al. 1995; Mitacek et al. 1999). 

Using the ISO, Massachusetts (MDPH; 45-mL puff 

volume, 30-second puff interval, 50 percent of ventilation 

holes blocked) and Canadian Intense (CAN; 55-mL puff 

volume, 30-second puff interval, 100 percent of ventilation holes blocked) smoking regimens, Counts and colleagues (2005) reported the levels of TSNAs in mainstream 

smoke from Philip Morris cigarettes sold internationally. 

The investigators found that in mainstream smoke, NNN 

levels were 5.0 to 195.3 ng generated per cigarette for ISO, 

16.3 to 374.2 ng for MDPH, and 20.6 to 410.6 ng for CAN. 

NNK levels were 12.4 to 107.8 ng generated per cigarette 

for ISO, 25.8 to 206.6 ng for MDPH, and 39.1 to 263.0 ng 

for CAN. NATB levels were 8.0 to 160.4 ng generated per 

cigarette for ISO, 31.9 to 295.3 ng for MDPH, and 43.5 to 

345.1 ng for CAN.

The combined levels of NNN and NNK reported by 

Wu and associates (2005) are in good agreement with the 

ranges reported by Counts and colleagues (2005). This 

finding suggests that the more advanced analytical methods used in these later studies yielded more accurate measures for current cigarettes than did previous measures. 

Levels of volatile nitrosamines in mainstream tobacco 

smoke are typically lower than those of the TSNAs 

(dimethylnitrosamine = 0.1 to 97 ng generated per 

cigarette; methylethylnitrosamine = 0.1 to 9.1 ng; and 

N-nitrosopyrrolidine = 1.5 to 64.5 ng) (Brunnemann et al. 

1977a, 1980; Adams et al. 1987). 

Ashley and colleagues (2003) compared TSNA concentrations in tobacco from Marlboro cigarettes with 

those in locally popular, non-U.S. brands of cigarettes in 

13 countries. For most of the countries, TSNA concentrations in the tobacco from Marlboro cigarettes were higher 

than those in tobacco from locally popular brands from 

that country. TSNA concentrations varied widely (20-fold 

overall) between and within brands from the same country and differed significantly from country to country. This 

study confirmed earlier work showing wide variations in 

TSNA levels in tobacco and smoke from products within a 

country and between countries (Hecht et al. 1975; Fischer 

et al. 1990c; Spiegelhalder and Bartsch 1996; Gray et al. 

2000). The basic findings from this study were confirmed 

by work from Wu and colleagues (2005), who examined 

combined levels of NNN and NNK in the mainstream 

smoke from cigarettes from the same 13 countries and 

also found a wide variation in this matrix.

Identification of growing, curing, and blending 

practices that alter nitrosamine levels in tobacco and 

smoke have led researchers to agree that low TSNA levels in smoke can be achieved by using particular varieties 

of tobacco and carefully controlling the factors leading to 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 37

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

formation and transfer of TSNAs from tobacco into smoke 

(Brunnemann et al. 1977a; Hoffmann et al. 1977; Hecht 

et al. 1978; Rühl et al. 1980; Andersen and Kemp 1985; 

Hecht and Hoffmann 1988; Fischer et al. 1990c; Spiegelhalder and Bartsch 1996; Mitacek et al. 1999; Ashley et al. 

2003; Burns et al. 2008). To reduce TSNAs, tobacco curing 

in the United States is undergoing a transition, and nitrosamine levels may change as curing and blending practices change (Counts et al. 2004; O’Connor et al. 2008). 

In summary, nitrosamines are found in tobacco and 

tobacco smoke at high levels compared with other consumer products. The levels of these compounds, which are 

formed during tobacco processing, curing, and storage, 

can be minimized by breeding and selecting tobacco lines 

with lower propensity for TSNA formation, and limiting 

the use of nitrogen fertilizer, the levels of nitrogen oxides 

in the atmosphere during curing, the amount of burley 

tobacco in the blend, and storage times. The impact of different practices is clearly seen by the wide global range of 

TSNA levels in tobacco and smoke. 

Polycyclic Aromatic Hydrocarbons

PAHs are chemical compounds with two or more 

condensed aromatic and other cyclic rings of carbon and 

hydrogen atoms (Douben 2003). Recent studies (Rodgman and Perfetti 2006) have identified at least 539 PAHs in 

tobacco smoke. The U.S. Environmental Protection Agency 

(EPA) has identified 16 priority environmental PAHs on 

the basis of evidence that they cause or may cause cancer: acenaphthylene, acenaphthene, anthracene, benz[a]

anthracene, benzo[a]pyrene (B[a]P), benzo[b]fluoranthene (B[b]F), benzo[k]fluoranthene (B[k]F), benzo[g,h,i]

perylene, chrysene, dibenz[a,h]anthracene, fluoranthene, 

fluorene, indeno[1,2,3-cd]pyrene, naphthalene, phenanthrene, and pyrene (Figure 3.5) (USEPA 1980, 1986). The 

16 PAHs, which have two to six fused rings and molecular weights of 128 to 278, were detected in the particulate 

matter of tobacco smoke (IARC 1986, 2004; Ding et al. 

2006, 2007). PAHs range from highly volatile to relatively 

nonvolatile, and their distribution in the particulate and 

gas phases of tobacco smoke varies with the boiling point 

(Grimmer et al. 1987). However, the gas phase contained 

only an estimated 1 percent of the total PAHs found in 

tobacco smoke. The composition of PAHs in mainstream 

smoke is different from that in sidestream smoke (Grimmer et al. 1987), and the lipophilic characteristics range 

from moderate to high (Douben 2003).

PAHs are formed by incomplete combustion of 

natural organic matter such as wood, petroleum, and 

tobacco and are found throughout the environment 

(Evans et al. 1993; Douben 2003). In the burning cone 

at the tip of the tobacco rod, various pyrolysis reactions 

occur to form methylidyne (CH) radicals that are precursors to the pyrosynthesis of PAHs. Hoffmann and Wynder 

(1967) were the first to show that adding nitrate to tobacco 

reduced B[a]P levels. During smoking, nitrates form O2 and 

nitric oxide (NO), which intercept radicals and reduce 

PAH levels (Johnson et al. 1973a; Hoffmann and Hoffmann 

1997). Other researchers also reported that the presence 

of nitrate in tobacco decreases B[a]P levels in the smoke 

(Torikai et al. 2005). The pyrolytic conditions also favor 

the formation of PAHs from certain isoprenoids such as 

solanesol (IARC 1986), although other findings have disagreed with this assessment (Torikai et al. 2005). B[a]P is 

the most widely known and studied PAH (IARC 2004). 

Differences in tobacco type can affect levels of PAHs 

in the smoke. Flue-cured (bright) or sun-cured (oriental) 

tobaccos have lower nitrate content than does air-cured 

(burley) tobacco. Pyrosynthesis of PAHs generates higher 

PAH levels in smoke from cigarettes made exclusively 

with flue-cured or sun-cured tobaccos than in smoke 

from cigarettes made with burley tobaccos (Hoffmann 

and Hoffmann 1997; Ding et al. 2005). Cigarettes made 

from reconstituted tobacco with cellulose fiber as an 

additive yield significantly reduced PAH levels. Evans 

and colleagues (1993) measured PAHs in mainstream 

and sidestream smoke and found that B[a]P, B[b]F, and 

B[k]F levels are related to tar yields in cigarette smoke 

that result from differences in cigarette ventilation.

Some studies reported the levels of B[a]P alone as a 

surrogate for the total PAH content. Ding and colleagues 

(2005) observed that total PAH levels in mainstream 

smoke from commercial cigarette brands varied from 1 to 

1.6 μg generated per cigarette under FTC machine-smoking conditions. In the same study, individual PAHs ranged 

from less than 10 ng generated per cigarette (B[k]F) to 

approximately 500 ng (naphthalene) (Ding et al. 2005). 

Other researchers reported levels of B[b]F at 10.4 ng, 

B[k]F at 5.1 ng, and B[a]P at 13.4 ng generated per cigarette (Evans et al. 1993). In four of five brands tested, 

B[a]P concentrations in cigarette tar were about 0.5 ng/

mg of tar (Tomkins et al. 1985). Kaiserman and Rickert 

(1992) reported the levels of B[a]P in smoke from 35 

brands of Canadian cigarettes by using the ISO method; 

mean levels were 3.36 to 28.39 ng generated per cigarette. 

Although B[a]P levels were linearly related to declared tar 

values, the tar values and the B[a]P levels did not change 

at the same relative rate. In a study of PAHs in mainstream 

smoke from cigarettes from 14 countries, Ding and colleagues (2006) showed a significant global variation in levels. They also demonstrated an inverse relationship with 

TSNA levels at high PAH and low TSNA levels, possibly as 

a result of differences in nitrate levels.
Surgeon General’s Report

38 Chapter 3

Figure 3.5 Priority environmental polycyclic aromatic hydrocarbons

In summary, PAHs result from the burning of biologic material, so they are present in the smoke from 

any form of burning tobacco. Factors that can affect PAH 

levels in tobacco smoke include the type of tobacco and 

its nitrate content. Because of divergent pyrosynthetic 

mechanisms, factors that increase the nitrate content of 

tobacco decrease PAH levels but may increase TSNA levels 

in cigarette smoke. However, a substantial reduction in 

PAH levels in cigarette smoke will be a challenge as long 

as tobacco smoke is generated from burning tobacco.

Volatile Compounds Including 

Aldehydes

When a cigarette is smoked, chemicals partition 

between the particulate and gas phases on the basis of physical properties including volatility and solubility (Hoffmann and Hoffmann 1997). Complete partitioning of any 

chemical to the gas phase of cigarette smoke is generally 

limited to the gaseous products of combustion, such as the 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 39

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

oxides of nitrogen, carbon, and sulfur, and the extremely 

volatile low-molecular-weight organic compounds. There 

are between 400 and 500 volatile gases and other compounds in the gas phase (Hoffmann and Hoffmann 1997). 

The nearly complete combustion of the cigarette tobacco 

filler generates an effluent stream of gaseous chemicals 

residing almost exclusively in the gas phase portion of 

mainstream cigarette smoke. These chemicals, on the 

basis of weight, account for most of the mainstream 

smoke. In order by prevalence, these chemicals include 

N2, O2, CO2, CO, nitrogen oxides, and the sulfur-containing gaseous compounds.

CO and CO2 result from the combustion of tobacco. 

Other than N2 and O2, CO and CO2 are the most abundant 

compounds in mainstream cigarette smoke, representing nearly 15 percent of the weight of the gas phase. CO2

levels (approximately 50 mg generated per cigarette) are 

more abundant than are CO levels (approximately 20 mg), 

as determined by the FTC machine-smoking method.

Nitrogen oxide gases are formed by the combustion of nitrogen-containing amino acids and proteins in 

the tobacco leaf (Hoffmann and Hoffmann 1997). Mainstream cigarette smoke contains mostly NO with traces of 

nitrogen dioxide (NO2) and nitrous oxide. The formation 

of nitrogen oxides is amplified by combustion with nitrate 

salts, and the amount formed is directly related to the 

nitrate concentration of the tobacco leaf (MacKown et al. 

1999). The mainstream cigarette smoke contains approximately 500 μg of NO generated per cigarette. Although 

fresh smoke contains little NO2, the aging of the smoke 

converts the reactive NO to NO2, which has an estimated 

half-life of 10 minutes (Borland et al. 1985; Rickert et 

al. 1987). These gases react with water and other components in cigarette smoke to form nitrate particles and 

acidic constituents.

Sulfur-containing gases result from the combustion 

of sulfur-containing amino acids and proteins (Horton 

and Guerin 1974). In mainstream cigarette smoke, H2S 

is the most abundant of these gases (approximately 85 μg 

generated per cigarette), and both sulfur dioxide and carbon disulfide are present in smaller quantities (approximately 2 μg). 

In addition to the volatile gases, mainstream cigarette smoke contains a wide range of volatile organic compounds (VOCs) (Counts et al. 2005; Polzin et al. 2007). 

The formation of these VOCs results from the incomplete 

combustion of tobacco during and between puffs. The 

generation of VOCs, as well as the previously mentioned 

volatile gases, is directly related to the tar delivery of the 

cigarette, as evidenced by machine smoking under the 

FTC regimen (Hoffmann and Hoffmann 1997; Polzin et 

al. 2007). Therefore, factors altering the yield of tar (e.g., 

tobacco blend, cigarette filter, filter ventilation, paper 

porosity, and tobacco weight) directly affect the yield of 

VOCs. Under certain machine-smoking conditions, the 

use of charcoal filters (Williamson et al. 1965; Counts et 

al. 2005; Laugesen and Fowles 2006; Polzin et al. 2008), 

variations in the temperature in the burning zone, and 

the presence or absence of O2 can substantially alter the 

levels of VOCs generated in cigarette smoke (Torikai et 

al. 2004). The VOCs in mainstream cigarette smoke, as a 

result of their high biologic activity and levels, are among 

the most hazardous chemicals in cigarette smoke (Fowles 

and Dybing 2003; IARC 2004). In developed countries, the 

combined exposure of smokers to mainstream cigarette 

smoke and nonsmokers to secondhand smoke constitutes 

a significant portion of the population’s total exposure 

to certain VOCs. For example, more than one-half of the 

U.S. population’s exposure to benzene is from cigarette 

smoking (U.S. Department of Health and Human Services 

[USDHHS] 2002). The roughly 500 VOCs in the gas phase 

of mainstream cigarette smoke can be subclassified by 

structure. Among the most significant classes are the aromatic hydrocarbons, carbonyls, aliphatic hydrocarbons, 

and nitriles. Although other classes of volatile compounds 

(e.g., acids and bases) are present, these four classes of 

VOCs have been the most widely studied, because of their 

biologic activity and overall higher levels.

Aromatics are a class of compounds defined by their 

structural similarity to benzene. These compounds result 

from incomplete combustion of the organic matter of the 

cigarette, most notably sugars and cellulose (Chortyk and 

Schlotzhauer 1973). The most abundant aromatic compounds in mainstream smoke generated from full-flavored 

cigarettes with use of the FTC/ISO smoking regimen are 

toluene (approximately 5 to 80 μg generated per cigarette), 

benzene (approximately 4 to 60 μg), total xylenes (approximately 2 to 20 μg), styrene (approximately 0.5 to 10 μg), 

and ethylbenzene (approximately 1 to 8 μg) (Counts et al. 

2005; Polzin et al. 2007).

Carbonyl compounds include the ketones and 

aldehydes. These compounds are studied because of their 

reactivity and levels, which approach 1 mg generated per 

cigarette. The most prevalent aldehydes in mainstream 

smoke from cigarettes, generated using the ISO regimen, 

are acetaldehyde (approximately 30 to 650 μg generated 

per cigarette), acrolein (approximately 2.5 to 60 μg), and 

formaldehyde (approximately 2 to 50 μg) (Counts et al. 

2005). The most prevalent ketones in mainstream cigarette smoke, generated by using the FTC/ISO smoking 

regimen, are acetone (approximately 50 to 550 μg generated per cigarette) and 2-butanone (approximately 10 to 

130 μg) (Counts et al. 2005; Polzin et al. 2007). Spincer 

and Chard (1971) identified formaldehyde in both the 

particulate and gas phases of tobacco smoke and found 

that much of the formaldehyde was associated with total 
Surgeon General’s Report

40 Chapter 3

particulate matter (TPM). These investigators determined 

that formaldehyde delivery was higher in smoke from 

bright tobacco than in that from burley tobacco. 

On the basis of total mass, hydrocarbons represent 

the largest VOC class in mainstream cigarette smoke 

(Hoffmann and Hoffmann 1997). Both saturated hydrocarbons and olefins result from the incomplete combustion 

of cigarette tobacco. The most abundant hydrocarbons in 

cigarette smoke are methane, ethane, and propane, which 

represent nearly 1 percent of the total cigarette effluent. 

Unsaturated hydrocarbons are also present in significant 

quantities in mainstream cigarette smoke, as evidenced by 

using the ISO regimen, but the olefins isoprene (approximately 70 to 480 μg generated per cigarette) and 1,3-butadiene (approximately 6.5 to 55 μg) are the most abundant 

unsaturated hydrocarbons (Counts et al. 2005).

The volatile nitriles, which include compounds such 

as HCN, acetonitrile, and acrylonitrile, are important 

because of their toxic effects. The most abundant nitriles 

in mainstream smoke generated from cigarettes by using 

the ISO regimen are HCN (approximately 3 to 200 μg generated per cigarette), acetonitrile (approximately 100 μg), 

and acrylonitrile (approximately 1 to 12 μg) (Counts et 

al. 2005).

In summary, cigarette smoke is composed primarily 

of gaseous and volatile compounds. Thus, levels of these 

compounds are critical in determining the overall toxicity 

of tobacco smoke. Differences in the design of the cigarette can have a substantial effect on the levels determined 

in smoke, which makes the reproducibility of results challenging, but provides knowledge of possible mechanisms 

to reduce the exposure of smokers.

Heavy Metals

Metals and metalloids are among the many substances contained in tobacco smoke; they are often loosely 

called “heavy metals” without regard to whether they are 

light- or heavy-mass metals or metalloids. Their chemical 

properties span a wide range. These substances are found 

as pure metals or as metals naturally associated or chemically bound to other elements that can significantly alter 

the chemical properties of the metals.

Although metals can be deposited on tobacco 

leaves from particles in the air and some fungicides and 

pesticides containing toxic metals have been sprayed on 

tobacco leaves or soils in the past (Frank et al. 1977), 

most of the metals present in plants are absorbed from 

the soil (Schwartz and Hecking 1991; Cheng 2003; Xiao 

et al. 2004a,b). Soils, therefore, including any amendments to the soil, such as sludge, fertilizers, or irrigation 

with polluted water have been the predominant source 

of metals found in tobacco grown in various geographic 

areas (Bache et al. 1985; Mulchi et al. 1987, 1991, 1992; 

Adamu et al. 1989; Bell et al. 1992; Rickert and Kaiserman 

1994; Stephens et al. 2005). Cadmium and lead content in 

tobacco and smoke have been correlated with the content in the soil in which the tobacco was grown, after 

adjustment for the amendments to the soil (Bache et 

al. 1985; Adamu et al. 1989; Mulchi et al. 1991, 1992; 

Bell et al. 1992; Rickert and Kaiserman 1994; Stephens 

et al. 2005). In addition, Rickert and Kaiserman (1994) 

showed that heavy metals in the air can be important. For 

example, significant changes in the lead concentrations 

in the air between 1974 and 1988 accounted for most of 

the changes in lead levels in tobacco during that period. 

Researchers have associated the mercury content in 

tobacco with environmental factors and soil in geographic 

areas where the tobacco was grown (Rickert and Kaiserman 1994). Mulchi and colleagues (1992) have also 

suggested that consideration of soil pH is important to 

understanding the relationship between metals in the soil 

and metals in the tobacco leaf. Because of differences in 

the soil, air, and metal uptake by the tobacco plant, the 

metal content of tobaccos varies widely.

Most metals and metalloids are not volatile at room 

temperature. Pure metallic mercury is volatile, but only a 

few forms are volatile at temperatures lower than 100oC. 

The temperature of tobacco that burns at the tip of a cigarette may reach 900oC (Baker 1981). A burning cigarette 

tip is hot enough to volatilize many metals into the gas 

phase, but by the time the smoke is inhaled or rises in a 

plume from the cigarette as secondhand smoke, most of 

the metals have condensed and moved into the particulate portion of the smoke aerosol (Baker 1981; Chang et 

al. 2003).

The range of levels of toxic metals found in tobacco 

smoke reflects differences in cigarette manufacturing 

processes, ventilation, additives, concentrations in the 

tobacco, and the efficiency with which the metal transfers 

from the leaf to the smoke. The transfer rate of metals 

from tobacco into smoke also depends on the properties 

of the metal (Krivan et al. 1994). Because tobacco plants 

easily absorb and accumulate cadmium from the soil, 

cadmium is found at relatively high concentrations in 

tobacco leaves. This accumulation, along with the high 

percentage of transfer from the leaves into the smoke 

(Schneider and Krivan 1993), yields high cadmium levels in tobacco smoke (Chiba and Masironi 1992). Kalcher 

and colleagues (1993) developed a model for the behavior 

of metals in mainstream smoke and found that most of 

the cadmium in tobacco smoke is in the particulate phase, 

whereas lead is equally partitioned between the particulate and gas phases. Cadmium levels have been reported 

to range from 10 to 250 ng generated per cigarette in the 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 41

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

particulate phase (Allen and Vickroy 1976; Bache et al. 

1985; Nitsch et al. 1991; Schneider and Krivan 1993; Krivan et al. 1994; Rhoades and White 1997; Csalári and Szántai 2002; Torrence et al. 2002) to a lower level of 1 to 31 

ng in the gas phase (Nitsch et al. 1991). More recent studies of cadmium levels in particulate matter in smoke from 

commercial cigarettes smoked under FTC/ ISO conditions 

reported a range of 1.6 to 101.0 ng generated per cigarette 

(Counts et al. 2005; Pappas et al. 2006). Not surprisingly, 

Counts et al. (2005) also showed that levels of cadmium in 

smoke generated using more intense smoking regimens 

such as MDPH (12.7 to 178.3 ng generated per cigarette) 

and CAN (43.5 to 197.1 ng generated per cigarette) were 

higher than when using FTC/ISO. This increase was also 

seen with other metals tested. These studies also demonstrated that changes in cigarette design, such as introducing filter ventilation, reduces the delivery of metals under 

FTC/ISO smoking conditions. In counterfeit cigarettes, 

levels of cadmium in particulate matter from mainstream 

smoke can be significantly higher, ranging from 40 to 300 

ng generated per cigarette, under FTC smoking conditions (Pappas et al. 2007). 

Lead also transfers well from tobacco to smoke 

(Schneider and Krivan 1993); measurements range 

from 18 to 83 ng generated per cigarette in the particulate phase (Allen and Vickroy 1976; Nitsch et al. 1991; 

Schneider and Krivan 1993; Krivan et al. 1994; Csalári and 

Szántai 2002; Torrence et al. 2002; Baker et al. 2004) and 

from 6 to 149 ng in the gas phase (Nitsch et al. 1991). 

More recent studies of lead levels in particulate matter in 

smoke from commercial cigarettes smoked under FTC/

ISO conditions reported a range of 4 to 39 ng generated 

per cigarette (Counts et al. 2005; Pappas et al. 2006). Studies of cigarettes in the United Kingdom have documented 

concentrations of heavy metals in a number of counterfeit 

cigarette brands that were higher than those in domestic 

products (Stephens et al. 2005). These metals included 

arsenic, cadmium, and lead. In counterfeit cigarettes, 

levels of lead in mainstream cigarette smoke can be significantly higher, ranging up to 330 ng generated per cigarette, under FTC smoking conditions (Pappas et al. 2007). 

Studies have also found similar levels of nickel in both 

phases: particulate levels range from 1.1 to 78.5 ng generated per cigarette (Bache et al. 1985; Nitsch et al. 1991; 

Schneider and Krivan 1993; Torjussen et al. 2003), and 

gas phase levels range from 3 to 57 ng (Nitsch et al. 1991).

Tobacco smoke also contains lower levels of other 

metals. The range of levels found in the particulate phase 

includes cobalt, 0.012 to 48.0 ng generated per cigarette; 

arsenic, 1.5 to 21.0 ng; chromium, 1.1 to 1.7 ng; antimony, 0.10 to 0.13 ng; thallium, 0.6 to 2.4 ng; and mercury, 0.46 to 6.5 ng (Allen and Vickroy 1976; Suzuki et 

al. 1976; Nitsch et al. 1991; Schneider and Krivan 1993; 

Krivan et al. 1994; Rhoades and White 1997; Milnerowicz et al. 2000; Shaikh et al. 2002; Torrence et al. 2002; 

Baker et al. 2004; Pappas et al. 2006). Gas phase levels depend on the volatility of the metals or metal complexes. 

Cobalt levels range from less than 1 to 10 ng generated per 

cigarette, and mercury levels range from 5.0 to 7.4 ng 

generated per cigarette (Nitsch et al. 1991; Chang et al. 

2002). In a limited analysis, Chang and colleagues (2003) 

found arsenic and antimony in the gas phase but did not 

provide quantitative results.

Studies have identified radioactive elements in 

tobacco and tobacco smoke. Lead 210, a product of 

radioactive decay of radon, was found in tobacco (Peres 

and Hiromoto 2002) and is transported at low levels in 

tobacco smoke (Skwarzec et al. 2001). Most of the lead 

in tobacco smoke is the nonradioactive isotopes. Polonium, an element found only in radioactive forms, is also 

a product of radioactive decay of radon. Some researchers have found polonium 210 in tobacco (Skwarzec et al. 

2001; Peres and Hiromoto 2002; Khater 2004), and others 

estimated transfer of 11 to 30 percent of the amount in 

tobacco to tobacco smoke (Ferri and Baratta 1966). The 

presence of a filter and the type of filter used can alter the 

amount of polonium transferred into mainstream smoke; 

some filters remove 33 to 50 percent of the polonium from 

the smoke (Ferri and Baratta 1966). 

In summary, the levels of metals in tobacco smoke 

are primarily a function of their content in the soil in 

which the tobacco is grown, added substances such as fertilizer, and the design of the cigarette. Study findings indicate that (1) growing conditions for tobacco contribute to 

the levels of metals in cigarettes manufactured worldwide 

and (2) some counterfeit cigarettes have higher levels 

of metals than do domestic commercial cigarettes. This 

evidence has proved that tobacco-growing conditions can 

alter the concentrations of metals in cigarette tobacco and 

therefore the levels in the smoke. 

Aromatic Amines

Aromatic amines and their derivatives are used in 

the preparation of dyes, pharmaceuticals, pesticides, and 

plastics (Brougham et al. 1986; Bryant et al. 1994; Centers for Disease Control and Prevention [CDC] 1994) and 

in the rubber industry as antioxidants and accelerators 

(Parmeggiani 1983). Because of their widespread use, 

aromatic amines are prevalent and may be found as contaminants in some color additives, paints, food colors, and 

leather and textile dyes and in the fumes from heating oils 

and fuels. Studies that measured aromatic amines in the 

ambient environment detected their presence and determined concentrations in air, water, and soil (Birner and 
Surgeon General’s Report

42 Chapter 3

Neumann 1988; Del Santo et al. 1991; Ward et al. 1991; 

Skipper et al. 1994; Sabbioni and Beyerbach 1995). Aromatic amines consist of at least one hydrocarbon ring and 

one amine-substituted ring, but these agents have diverse 

chemical structures. Chemically, aromatic amines act as 

bases and most exist as solids at room temperature.

Some scientists have suggested that aromatic 

amines are present in unburned tobacco (Schmeltz and 

Hoffmann 1977) and are also formed as combustion products in the particulate phase of tobacco smoke (Patrianakos and Hoffmann 1979). Investigators determined levels 

of aromatic amines in both mainstream and sidestream 

smoke (Hoffmann et al. 1969; Patrianakos and Hoffmann 

1979; Grimmer et al. 1987; Luceri et al. 1993; Stabbert et 

al. 2003a). The identified compounds include aniline; 1-, 

2-, 3-, 4-toluidine; 2-, 3-, 4-ethylaniline; 2,3-, 2,4-, 2,5-, 

2,6-dimethylaniline; 1-, 2-naphthylamine; 2-, 3-, 4-aminobiphenyl; and 2-methyl-1-naphthylamine. The most 

commonly studied compounds from this class are shown 

in Figure 3.6. Stabbert and colleagues (2003a) found that 

aromatic amines reside primarily in the particulate phase 

of smoke, except for the more volatile amines such as 

o-toluidine; only 3 percent of o-toluidine was found in the 

gas phase. Studies have reported that sidestream smoke 

contains substantially higher levels of aromatic amines 

than does mainstream smoke, but these levels depend on 

the parameters for puffing the cigarette (Patrianakos and 

Hoffmann 1979; Grimmer et al. 1987; Luceri et al. 1993). 

For mainstream smoke, the levels of aromatic amines 

were reported to be 200 to 1,330 ng generated per cigarette (Luceri et al. 1993; Stabbert et al. 2003a), but studies have reported much higher levels in sidestream smoke 

(Luceri et al. 1993). More recently, one study reported 

the following levels of aromatic amines in mainstream 

cigarette smoke (Counts et al. 2005). Using the ISO regimen, these investigators determined that levels were 3 

to 27 ng generated per cigarette for 1-aminonaphthalene; 2 to 17 ng for 2-aminonaphthalene; 0.6 to 4.2 ng for 

3-aminobiphenyl; and 0.5 to 3.3 ng for 4-aminobiphenyl. 

These levels increased on average by approximately 115 

percent when the MDPH smoking regimen was used and 

by approximately 130 percent under the CAN smoking regimen.

Levels of aromatic amines in tobacco smoke are 

influenced by both the chemical constituents in the 

tobacco and the chemical and physical processes of the 

burning cigarette. Levels of aromatic amines in smoke 

from cigarettes made with dark tobacco are higher than 

those in cigarettes made from light tobacco (Luceri et al. 

1993). For typical U.S.-blended cigarettes, there is a linear 

correlation between levels of aromatic amines and tar in 

the smoke (Stabbert et al. 2003a). 

Sources of nitrogen in the tobacco also significantly 

influence levels of aromatic amines in tobacco smoke. 

Nitrate is a primary factor in altering the level of aromatic 

amines in tobacco smoke, and its presence is influenced by 

the use of nitrogen fertilizers (Patrianakos and Hoffmann 

1979; Stabbert et al. 2003a). Protein in tobacco is known 

to be a good source of biologic nitrogen, and studies have 

reported that higher nitrogen content from elevated protein in tobacco increased the yields of 2-naphthylamine 

and 4-aminobiphenyl (Patrianakos and Hoffmann 1979; 

Torikai et al. 2005). Cigarette smoke from bright tobacco 

had lower aromatic amine levels than expected compared 

with the smoke of U.S. blended cigarettes, possibly because 

of the lower nitrogen content in bright tobacco (Stabbert 

et al. 2003a). Combustion temperature is also a factor 

in the generation of aromatic amines in tobacco smoke, 

because lower temperatures yielded lower levels of aromatic amines in smoke (Stabbert et al. 2003b). Other 

investigators have suggested that increased cellulose levels in tobacco can decrease aromatic amines in the smoke 

(Torikai et al. 2005), and in another study, celluloseacetate filters removed a substantial portion of aromatic 

amines from mainstream smoke (Luceri et al. 1993).

In summary, it appears that the nitrogen content in 

tobacco, either from protein levels or use of nitrogen fertilizer, is a primary determinant of aromatic amine levels 

in tobacco smoke. The type of tobacco used in the cigarette filler also alters these levels in tobacco smoke. 

Figure 3.6 Commonly studied aromatic amines in tobacco smoke
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 43

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Heterocyclic Amines

Heterocyclic amines (HCAs) are a class of chemical compounds that contain at least one cyclic ring and 

an amine-substituted ring. HCAs act as basic compounds 

because of the amine functional group. HCAs can occur 

in food stuff, such as grilled meats, poultry, fish, and 

tobacco smoke (Sugimura et al. 1977; Sugimura 1997; 

Skog et al. 1998; Murkovic 2004). HCAs are classified in 

two groups: one is produced by the pyrolysis of amino 

acids and proteins through radical reactions, and the 

other is generated by heating mixtures of creatinine, sugars, and amino acids (Sugimura 1997; Murkovic 2004). 

The first group dominates when the pyrolysis temperature 

is high, whereas the second group is predominant at low 

temperatures commonly used to cook meat (Sugimura 

1997). In tobacco smoke, the primary HCAs are 2-amino9H-pyrido[2,3-b]indole; 2-amino-3-methyl-9H-pyrido[2,

3-b]indole; 3-amino-1,4-dimethyl-5H-pyrido[4,3-b]indole 

(Trp-P-1); 3-amino-1-methyl-5H-pyrido[4,3-b]indole (TrpP-2); 2-amino-3-methylimidazo[4,5-f]quinoline; 2-amino6-methyldipyrido[1,2-a:3’,2’-d]imidazole (Glu-P-1); 

2-aminodipyrido[1,2-a:3’,2’-d]imidazole; and 2-amino1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) (Figure 3.7) (Kataoka et al. 1998).

HCAs are not found in unburned tobacco; they are 

present in tobacco smoke as a result of pyrolysis and are 

found in the particulate phase (Manabe and Wada 1990). 

Figure 3.7 Primary heterocyclic amines in tobacco smoke
Surgeon General’s Report

44 Chapter 3

The chemical composition of amino acids, protein, sugars, and creatine/creatinine in the tobacco filler influences 

the final HCA levels in the smoke. Other components that 

may alter the pyrolysis of amino acids can also change 

HCA levels in smoke. The usual levels of HCAs in tobacco 

smoke were reported to be 0.3 to 260.0 ng generated per 

cigarette (Hoffmann et al. 2001). Manabe and Wada (1990) 

reported levels of 0.29 to 0.31 ng of Trp-P-1 generated per 

cigarette and 0.51 to 0.66 ng for Trp-P-2 in smoke condensate from five types of cigarettes. Manabe and colleagues 

(1991) determined an average level of 16.4 ng generated 

per cigarette for PhIP in tobacco smoke condensate from 

cigarettes purchased in Japan, the United Kingdom, and 

the United States.

In summary, although HCAs are not specific to 

tobacco products, they are found at levels in tobacco 

smoke particulate that must be considered when assessing the harm from the use of burned tobacco. The concentration of nitrogen-containing compounds in tobacco 

influences the levels of HCAs that are found in the smoke, 

and reducing the nitrogen content may be a means of 

reducing HCAs.

Effect of Additives on 

Tobacco Smoke

Chemical additives are introduced into cigarette 

tobacco for a variety of specific purposes, including pH 

adjustment, maintenance of moisture (humectants), amelioration of the harshness of smoke, control of the burn 

rate, and impartation of desirable flavor to the smoke 

(Penn 1997). The taste and flavor of cigarette smoke is 

affected primarily by the tobacco blend and is further 

modified with additives. Specific additives are applied 

to mask the harshness of lower-quality tobacco (World 

Tobacco 2000). Early in the processing of burley and fluecured tobaccos, a solution called “casing” is added to the 

shreds of tobacco lamina. The casing is a slurry containing 

humectants (e.g., glycerol and propylene glycol) and flavor ingredients with low volatility (e.g., cocoa, honey, licorice, and fruit extracts) that lend a pleasant aroma. After 

the tobacco is aged, a top-flavoring solution is added to the 

finished cigarette blend. Top flavoring is generally an alcohol- or rum-based mixture containing volatile compounds 

(e.g., menthol) and other ingredients (e.g., aromatic compounds, essential oils, and extracts) that are added immediately before packaging (Penn 1997; Fisher 1999).

Even though the specific ingredients added to individual cigarette brands are proprietary, a collective list of 

599 additives used in U.S. cigarettes has been published 

on the World Wide Web (Indiana Prevention Resource 

Center 2005). The “599 list” contains individual chemical 

compounds and complex additives, such as essential oils, 

juices, powders, oleoresins, and extracts. Included in the 

list are complex natural extracts and essential oils, such 

as anise, cassia, cedarwood, chocolate, cinnamon, ginger, lavender, licorice, nutmeg, peppermint, valerian, and 

vanilla. The list also includes individual organic chemical compounds, such as 1-menthol, 3-methyl pentanoic acid, anethole, β-caryophyllene, caffeine, ethyl 

acetate, γ-decalactone, isoamyl acetate, methyl cinnamate, 

sucrose, and vanillin. The compounds in the 599 list have 

been approved by the U.S. Food and Drug Administration 

as generally recognized as safe for use in foods (Hoffmann 

and Hoffmann 1997). Virtually any material with this 

approval as a food additive is used in cigarette manufacturing (World Tobacco 2000). However, this use is based on 

the broad assumption that additives designated as safe for 

ingestion are safe to burn and inhale in cigarette smoke. 

Because of the detoxifying action of the liver on blood 

coming directly from the digestive tract and the movement of blood from the lungs into the general circulation 

without first passing through the liver, the toxic effects 

associated with ingesting a compound can differ from the 

toxic effects of breathing it. Studies indicated that eugenol, a compound found in many natural extracts and used 

as an additive in clove cigarettes, had an LD50 200 times 

lower in Fischer rats when administered intratracheally 

compared with gavage (LaVoie et al. 1986). Although this 

did not simulate inhalation, it did raise concern about 

increased toxicity of this compound to the lung. 

Cigarette tobacco is a complex physicochemical 

mixture containing several types of tobacco and numerous additives (Hoffmann and Hoffmann 1997). The flavor compounds in tobacco can be transferred into the 

smoke by distillation, combustion, or pyrolysis (Green et 

al. 1989). Newly emerging flavored “dessert” cigarettes 

marketed under names such as Midnight Berry, Mandarin 

Mint, and Mocha Taboo (Carpenter et al. 2005) may represent new sources of exposure to harmful substances, but 

the qualitative and quantitative differences in smoke from 

these cigarettes have not been described.

One of the most common tobacco additives is menthol, a monoterpene alcohol (Burdock 1995) first used in 

cigarettes in the mid-1920s (Reynolds 1981) and subsequently added to most cigarettes (Eccles 1994). Natural 

sources of menthol include plants in the mint family, 

namely, peppermint (Mentha piperita) and corn mint 

(Mentha arvensis) (Burdock 1995). Flavorants derived 

from natural sources generally contain a mix of compounds, in contrast to flavoring compounds that are 

chemically synthesized. If menthol added to the tobacco 

is derived from natural sources, such as peppermint, 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 45

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

constituents such as pulegone may also be present at low 

concentrations. Submicrogram concentrations of pulegone (0.024 to 0.29 μg/g) were measured in 12 mentholated brands but were not detected in nonmentholated 

brands (Stanfill and Ashley 1999). Menthol can be added 

on the tobacco, the filter, or the foil pack (Wayne and 

Connolly 2004). Menthol levels in smoke have ranged between 0.15 and 0.58 mg generated per cigarette for several brands (Cantrell 1990). Unlike most nonmentholated 

cigarettes, menthol cigarettes usually contain more fluecured and less burley tobacco, along with reconstituted 

tobacco made without added ammonia.

Although they generally are regarded as safe for use 

in foods, certain flavor-related chemicals added to cigarettes and found in cigarette smoke (Stanfill and Ashley 

1999) have known toxic properties. In an analysis of 12 

flavor compounds in tobacco fillers from 68 U.S. cigarette 

brands, concentrations of compounds were 0.0018 to 43.0 

μg/g (Stanfill and Ashley 1999). Also, 62 percent of the 68 

brands contained detectable levels of 1 or more of the 12 

flavor compounds. Piperonal and myristicin were present 

at the highest concentrations. Anethole, myristicin, and 

safrole were found in 20 percent or more of the brands; 

pulegone, piperonal, and methyleugenol were each present in at least 10 percent of the brands. In four brands, 

safrole, myristicin, and elemicin were found together, 

which strongly suggests the presence of flavorings such as 

nutmeg or mace (Myristica fragrans) in the tobacco. Coumarin is a benzopyrone compound found in the tobacco 

of one menthol brand at a concentration of 0.39 μg/g. 

Pulegone, a monoterpene ketone found in peppermint, 

was present only in mentholated brands. Tentative identification of other compounds suggested the use of flavor 

agents such as cinnamon and ginger (Stanfill and Ashley 

1999). In addition to tobacco analysis, mainstream smoke 

particulates from several brands were also analyzed for six 

flavor compounds: eugenol, isoeugenol, methyleugenol, 

myristicin, elemicin, and piperonal (Stanfill and Ashley 

2000). Levels of these compounds in the smoke from eight 

U.S. cigarette brands were 0.0066 to 4.21 μg generated per 

cigarette. The measurements suggested that a portion of 

eugenol and isoeugenol in smoke from some cigarettes 

could be a by-product of the burning tobacco. Also, when 

filter ventilation holes in the cigarette were partially or 

fully blocked, the transfer of these compounds from 

tobacco filler to mainstream smoke particulates increased 

twofold to sevenfold.

In summary, the impact of flavor-related additives 

on the toxicity, carcinogenicity, and addictive properties 

of tobacco products has not been thoroughly studied. In 

addition to the known harmful properties of these compounds, they may potentiate the effects of other known 

smoke constituents or alter the way people smoke 

cigarettes. These additives may also increase the initiation 

and continuation of smoking in the population.

Delivery of Chemical Constituents 

into Tobacco Smoke

Various tobacco types are used in the manufacture 

of cigarettes and other tobacco products. Lamina from 

bright, burley, and oriental tobacco varieties, along with 

reconstituted tobacco sheet, is the main filler component 

used in cigarettes (Hoffmann and Hoffmann 1997). In 

addition to lamina, cigarette filler often contains puffed 

or expanded tobacco, tobacco stems, humectants, and 

various flavor additives (Hoffmann and Hoffmann 1997; 

Abdallah 2003a). One tobacco variety such as bright can 

be used, or several varieties can be mixed together in 

products with specific tobacco blends. Most commercial 

cigarettes are constructed primarily from bright tobacco 

or from a blend of mainly bright, burley, and oriental 

tobaccos, usually referred to as an American blend (Browne 

1990). However, a few small geographic areas outside the 

United States (e.g., France) have regional preferences for 

cigarettes made exclusively from dark, air-cured tobacco 

(Akehurst 1981; Tso et al. 1982). Each type of tobacco has 

unique properties that influence packing density (Artho 

et al. 1963), burn rate (Muramatsu 1981), tar and nicotine delivery (Griest and Guerin 1977), and flavor and 

aroma (Davis 1976; Enzell 1976; Leffingwell 1976). Bright 

tobacco, also known as flue-cured or Virginia tobacco, has 

lower nitrogen content (i.e., less protein) and higher sugar 

content than do the other varieties. Burley and Maryland 

tobaccos are air cured and typically have higher nicotine 

content but reduced sugar content. 

Sakuma and colleagues (1984) measured the smoke 

components in mainstream and sidestream smoke and 

found that nitrogen-containing compounds were abundant in smoke from burley tobacco, whereas the nonnitrogen-containing compounds were more abundant 

in smoke from bright and oriental tobaccos. Oriental 

tobacco is often included in blended varieties because of 

its unique aromatic properties (Browne 1990). Cigarettes 

such as light or ultralight varieties that deliver low yields 

of tar and nicotine by FTC/ISO machine measurement 

often contain puffed or expanded tobacco lamina with 

higher “filling power” (Kertsis and Sun 1984; Lewis 1990; 

Kramer 1991), which lowers the density of the tobacco 

rod, thus lowering the amount of tobacco in each cigarette. Several types of reconstituted tobacco sheet are also 

used to manufacture cigarettes (Abdallah 2003b).

Development of reconstituted tobacco was an 

attempt at 100-percent utilization of tobacco (Abdallah 
Surgeon General’s Report

46 Chapter 3

2003b). Stems, ribs, and scrap lamina are combined with 

various binders and other additives to form a “reconstituted” sheet approximating the physical and chemical 

characteristics of a tobacco leaf (Browne 1990; Blackard 

1997; Abdallah 2003b). A common additive in reconstituted tobacco is diammonium hydrogen phosphate, which 

is used as a pectin release agent that facilitates crosslinkage to form stable sheet material (Hind and Seligman 1967, 1969; Hind 1968). Reconstituted tobacco sheet 

containing this additive selectively adsorbs nicotine from 

surrounding lamina and enriches it in an environment 

abundant in ammonia precursors (Larson at al. 1980). 

The stages of manufacturing a cigarette include 

processing the tobacco lamina and reconstituted tobacco 

materials and slicing them into shreds of a specific cut 

width. Tobacco cut widths vary from approximately 1.5 

mm for a coarse cut to 0.4 mm for a fine cut (Hoffmann 

and Hoffmann 1997). Alternatively, the cut width may 

be expressed in units of cuts per inch, which range from 

approximately 14 to 48. Cigarettes made from fine-cut 

tobacco have faster static burn rates resulting in fewer 

puffs (Resnik et al. 1977). A consequence of using tobacco 

filler with a fine-cut width is that the ratio of filler surface area to void volume increases and may increase the 

efficiency of the tobacco column to filter large aerosol particles (Keith and Derrick 1960). 

The papers used in cigarettes are generally flax or 

linen fiber and may contain additives (Browne 1990). Salts 

often are added to the cigarette paper as optical whiteners to achieve a target static burn rate and to mask the 

appearance of sidestream smoke (Schur and Rickards 

1960; Owens 1978; Durocher 1984). A key physical property of the paper wrapper is its porosity. Papers with high 

porosity facilitate diffusion of gases in and out of the 

tobacco rod (Newsome and Keith 1965; Owen and Reynolds 1967). Volatile smoke constituents such as CO readily diffuse through a porous wrapper, so delivery to the 

smoker is lower than that with less volatile constituents. 

High-porosity papers also permit more O2 to diffuse 

inward, which increases the static burn rate and the airflow through the tobacco column that dilutes the smoke. 

A faster-burning cigarette yields fewer puffs, reducing 

tar and nicotine delivery per cigarette (Durocher 1984). 

Porosity of the paper, filler cut width, filter efficiency, 

and tobacco density all make important contributions to 

reduction of pressure drop in the tobacco rod, which is 

a key index related to acceptance by smokers (Norman 

1999). Smokers prefer a cigarette on which they do not 

have to draw too hard because of changes in pressure drop 

as a result of design. A separate but related parameter, filter pressure drop, is directly related to smoke delivery and 

filter efficiency (Norman 1999). 

In 2006, cigarette lengths generally fell into one 

of four categories in the U.S. market: king-size filter 

cigarettes (79–88 mm; accounting for 62 percent of the 

market); long (94–101 mm; 34 percent of the market); 

ultra long (110–121 mm; 2 percent of the market); and 

regular, nonfilter cigarettes (68–72 mm; 1 percent of the 

market) (FTC 2009). The usual diameter of a conventional cigarette is 7.5 to 8.0 mm (Norman 1999), although 

some “slims” have diameters of 5 to 6 mm. The amount 

of tobacco consumed varies with the circumference of 

the cigarette, and in cigarettes with smaller circumference, delivery of constituents in the smoke to the smoker 

decreases accordingly (Ohlemiller et al. 1993). The greater 

surface of the wrapper in long cigarettes increases the 

opportunity for gaseous diffusion out of the cigarette, 

which can (1) reduce delivery of highly volatile constituents of mainstream smoke to the smoker, but increase 

delivery to the nonsmoker and (2) increase the static burn 

rate as more O2 diffuses inward (Moore and Bock 1968). 

However, long cigarettes generally facilitate delivery of 

higher tar and nicotine levels, because more tobacco mass 

is burned.

Before the 1950s, most cigarettes were about 70 mm 

long and unfiltered (Hoffmann and Hoffmann 1997). The 

addition of a filter tip to a cigarette can greatly reduce 

delivery of many chemical constituents of mainstream 

smoke as determined by the FTC/ISO machine-smoking 

method (Fordyce et al. 1961; Williamson et al. 1965). This 

reduction was attributed to filtering of the smoke particulate and reducing the amount of tobacco in each cigarette. 

Cost savings are also achieved because the filter material 

is less expensive than the tobacco (Browne 1990). Filters 

provide a firm mouthpiece and permit the smoker to avoid 

direct contact with the tobacco. Cigarettes with modern 

cellulose-acetate filter tips gained about 96 percent of 

the market share by the 1970s (Hoffmann and Hoffmann 

1997). In the United States, cellulose-acetate filter tips are 

the most popular and can selectively remove certain constituents of the smoke, including phenols and alkylphenols (Hoffmann and Wynder 1963; Spears 1963; Baggett 

and Morie 1973; Morie et al. 1975). Typically, a bonding 

agent such as triacetin or glycerol triacetate is used to 

facilitate filter manufacturing (Browne 1990). The filtration efficiency is proportional to the length, diameter, 

size, and number of fiber strands and the packing density 

of the cigarette (Keith 1975, 1978; Eaker 1990). Flavoring 

agents or other materials can also be incorporated into the 

filter design. 

Extensive research from the 1960s has examined 

the use of activated charcoal in the cigarette filter to 

efficiently remove volatile compounds (Newsome and 

Keith 1965; Williamson et al. 1965; Keith et al. 1966). The 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 47

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

addition of activated charcoal significantly reduced levels 

of volatile compounds, such as formaldehyde, cyanide, and 

acrolein (Williamson et al. 1965; Spincer and Chard 1971). 

Charcoal filters reduced the delivery of H2S to mainstream 

smoke (Horton and Guerin 1974). Both cellulose-acetate 

and charcoal filters removed some of the volatile pyridines 

(Brunnemann et al. 1978). Coatings with metallic oxides 

were extremely efficient at removing acidic gases (Keith et 

al. 1966). Filter designs can also be tailored to selectively 

pass and not trap certain classes of targeted compounds. 

For instance, inclusion of alkaline materials in the filter 

inhibits filtration of gaseous nicotine (Browne 1990). 

One key technology used to reduce FTC/ISO 

machine-measured tar and nicotine delivery is the inclusion of microscopic ventilation holes in the paper wrapper 

(Harris 1890) or the filter paper. These holes cause the 

mainstream smoke to become diluted with air (Norman 

1974). Filter ventilation holes are usually located in one or 

more rings about 12 mm from the mouth end of the filter 

(Baker and Lewis 1997). The amount of filter ventilation 

ranges from about 10 percent in some full-flavored varieties to 80 percent in brands measured as having very low 

delivery by using the FTC smoking regimen (CDC 1997). 

Filter ventilation also contributes to control of the burn 

rate (Durocher 1984). The tiny perforations can be made 

by mechanical means, electrostatic sparking, or laser 

ablation. Paper permeability can also be used to increase 

air dilution, although as the cigarette is consumed, this 

effect becomes less important. Delivery of lower levels 

of the constituents of mainstream smoke, as measured 

under FTC machine-smoking conditions, occurs when 

smoke drawn through the cigarette rod mixes and is 

diluted with air drawn through filter ventilation holes. 

Under FTC machine-smoking conditions, filter ventilation 

is highly effective in reducing delivery of chemical constituents (Norman 1974). However, the fingers or lips of 

smokers may cover vent holes when they smoke cigarettes 

and reduce the amount of air available for dilution, which 

results in delivery that is higher than expected (Kozlowski 

et al. 1982, 1996). 

Cigarette smoke is formed by (1) the condensation 

of chemicals formed by the combustion of tobacco, (2) 

pyrolysis and pyrosynthesis, and (3) distillation products 

that form an aerosol in the cooler region directly behind 

the burning coal (Browne 1990). During a puff, the coal 

temperature reaches 800°C to 900°C, and the temperature of the aerosol drops rapidly to slightly above room 

temperature as it travels down the tobacco rod (Touey and 

Mumpower 1957; Lendvay and Laszlo 1974). As the smoke 

cools, compounds with lower volatility condense first, and 

many of the very volatile gaseous constituents, such as 

CO, remain in the gas phase. The cooler tobacco rod acts 

as a filter itself, and some portions of the smoke condense 

(Dobrowsky 1960) as the smoke is drawn through the 

tobacco column during a puff.

Torikai and colleagues (2004) examined the influence of the temperature, the pyrolysis environment, and 

the pH of the tobacco leaf on the formation of a wide 

variety of constituents of tobacco smoke. Their findings 

showed that, in general, the yields of the chemical constituents in tobacco smoke that present health concerns 

increased as the temperature increased from 300°C to 

1,000oC, but some compounds (e.g., acrolein and formaldehyde) reached their maximum yield at 500oC and the 

yield remained approximately the same at higher temperatures. The presence of O2 in the pyrolysis atmosphere 

increased the yield of acrolein and other volatile organic 

compounds but lowered the levels of cyanide, phenol, and 

1-aminonaphthalene. The pH of the tobacco had a mixed 

effect on the levels of toxic chemicals in tobacco smoke. 

Levels of B[a]P, cyanide, quinoline, resorcinol, and acrylonitrile increased with a lower pH, and hydroquinone 

and 1-naphthylamine levels increased with higher pH. 

The effects of the pH and pyrolysis atmosphere combine 

to influence the radical reactions that generate many constituents in tobacco smoke.

In summary, design features of the cigarette have a 

major influence on the yield of the constituents in smoke. 

Altering the tobacco blend, filter type and length, cut 

width, paper porosity, ventilation, and chemical additives 

alters the levels of many constituents of smoke. 

Delivery of Chemicals to Smokers

In addition to cigarette design, the major factors 

that influence the delivery of chemicals to smokers are 

characteristics of puffing (puff volume, duration, and frequency), cigarette length smoked, and blocking air dilution holes on the filter tips of ventilated cigarettes (e.g., 

with the mouth or fingers). Testing cigarettes by using 

smoking machines or smokers in a laboratory setting can 

elucidate how certain design factors and smoking characteristics can influence the chemical components in smoke. 

However, the results obtained in a laboratory cannot be 

directly applied to populations of smokers because many 

factors influence the way a person smokes each cigarette.

In a laboratory setting, Fischer and colleagues 

(1989a) investigated the influence of smoking parameters on the delivery of TSNAs in mainstream smoke for 

six cigarette brands. The research included filter-tipped 

cigarettes with very-low-to-medium ISO/FTC yields of 

constituents of smoke and unfiltered cigarettes with high 

and very high ISO smoke yields. The major finding was 

that the puff profile and duration had no remarkable 

influence on TSNA delivery, but puff volume and frequency 
Surgeon General’s Report

48 Chapter 3

significantly increased TSNA yields. The dependency of 

TSNA delivery on the volume of smoke emitted from one 

cigarette (puff volume × number of puffs) was almost linear up to a total volume of approximately 500 mL. TSNA 

yield was equivalent for the same total volume whether 

the total volume was from a change in puff volume or 

puff frequency. Thus, the total volume drawn through a 

cigarette was the main factor responsible for delivery of 

TSNAs in mainstream smoke.

In another study, average levels of tar, nicotine, and 

CO per liter of smoke and per cigarette were determined 

for 10 brands of cigarettes smoked under 27 machinesmoking conditions (Rickert et al. 1986). Yields per cigarette were highly variable across smoking conditions, 

because of differences in the total volume of smoke. The 

results of a simple linear regression analysis indicated that 

up to 95 percent of the variation in tar yield per cigarette 

could be explained by variation in the total volume of 

smoke produced per cigarette. Puffing behavior (topography), especially the interpuff interval and total smoke volume per cigarette, which were influenced by puff volume, 

number of puffs, and length of the cigarette smoked, were 

the primary determinants of blood levels of constituents 

of cigarette smoke (Bridges et al. 1990). 

The influence of machine-smoking parameters on 

levels of chemical constituents measured in smoke is well 

illustrated in the work of Counts and colleagues (2005). 

This research was performed according to the ISO, MDPH, 

and CAN regimens described earlier. The study examined 

levels of 44 chemicals emitted in cigarette smoke. Not surprisingly, the more intense smoking regimens resulted in 

higher levels of constituents in cigarette smoke. However, 

in some cases, the emissions of the constituents did not 

maintain their relative levels as a result of different burning properties of the tobacco under different regimens 

and because of breakthrough in charcoal filters in the 

more intense smoking regimens. Because the intensity of 

smoking changes, the delivery of chemicals to the smoker 

varies and cannot be assessed by using a single smoking regimen.

In studies of 129 female and 128 male smokers 

of contemporary cigarettes, Melikian and colleagues 

(2007a,b) reported data on smoking topography and 

exposure to toxic substances in mainstream smoke of cigarettes that deliver a wide range of nicotine as reported 

by the FTC/ISO method. Exposure was determined by the 

delivered dose and urinary biomarkers. The first study 

focused on whether differences in gender and ethnicity 

affect delivered doses of select toxicants in mainstream 

cigarette smoke, as a result of differences in smoking 

behavior or type of cigarettes smoked (Melikian et al. 

2007b). Smoking topography differed significantly 

between females and males. Compared with men, women 

drew more (13.5 versus 12.0; p = 0.001) but smaller puffs 

(37.6 versus 45.8 mL; p = 0.0001) of shorter duration (1.33 

versus 1.48 seconds; p = 0.002). Women also smoked a 

smaller portion of the cigarettes (36.3-mm butts [40.2 

percent of cigarette length] versus 34.3-mm butts [39.2 

percent of cigarette length]; p = 0.01). Although smoke 

volume per cigarette did not differ between women and 

men (p = 0.06), the daily dose of smoke was significantly 

higher in men (9.3 versus 8.0 liters [L]; p = 0.02), because 

men consume a greater number of cigarettes per day. 

When data were stratified by race, no difference 

was found in puffing characteristics between European 

American and African American female and male smokers, 

except that African American women and men smoked 

equal lengths of the cigarettes (34.5- versus 33.9-mm 

butts; p = 0.93). However, African Americans smoked 

fewer cigarettes, so the daily smoke volume was significantly higher among European American smokers (8.61 

versus 7.45 L for women; 10.6 versus 7.8 L for men). The 

emissions of select toxicants per cigarette, as determined 

by use of machine-smoking regimens that mimicked each 

smoker, were consistently greater among male smokers 

than among the female smokers, and they correlated significantly with delivered smoke volume per cigarette. The 

geometric means of emissions of nicotine from cigarettes 

were 1.92 mg per cigarette for women versus 2.2 mg for 

men (p = 0.005). Cigarettes smoked by women yielded 

139.5 ng of NNK per cigarette compared with 170.3 ng 

for men (p = 0.0007). B[a]P emissions were 18.0 ng per 

cigarette for women and 20.5 ng for men (p = 0.01). Differences between women and men in delivery of toxicants 

in cigarette smoke to the smoker were more profound in 

European Americans than in African Americans. On average, African American men’s smoking behavior produced 

the highest emissions of select toxicants from cigarettes, 

and European American female smokers received the lowest amounts of toxicants.

The second study by Melikian and colleagues (2007a) 

investigated urinary concentrations of biomarkers in relation to levels of select toxicants in mainstream cigarette 

smoke, as determined by using machine-smoking regimens that mimicked the smoking behavior of each smoker. 

In this study of 257 smokers, the researchers determined 

levels of nicotine, NNK, and B[a]P in mainstream smoke 

and concentrations of the respective urinary metabolites: 

cotinine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol 

(NNAL), and 1-hydroxypyrene (1-HOP). The smokers were 

assigned to groups according to the FTC yield of toxic 

substances in the cigarettes they smoked: low yield (0.1 

to 0.8 mg of nicotine generated per cigarette, medium 

yield (0.9 to 1.2 mg), and high yield (>1.3 mg). Concentrations of urinary metabolites, expressed per level of parent compound delivered decreased with increased smoke 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 49

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

emissions. In smokers of low-, medium-, and high-yield 

cigarettes, as measured by FTC methods, the respective 

ratios of cotinine (nanograms per milligram of creatinine) 

to nicotine (milligrams per day) were 89.4, 77.8, and 57.1 

(low versus high; p = 0.06). Ratios of NNAL (picomoles per 

milligram of creatinine) to NNK (nanograms per day) were 

0.81, 0.55, and 0.57 (low versus high; p = 0.05). Ratios of 

1-HOP (picograms per milligram of creatinine) to B[a]P 

(nanograms per day) were 1.55, 1.13, and 0.97 (low versus 

high; p = 0.008). Similarly, for smokers who consumed 

fewer than 20 cigarettes per day, the means of cotinine 

per unit of delivered nicotine were 3.5-fold higher than 

those for smokers of more than 20 cigarettes per day. Likewise, a negative correlation was observed between ratios 

of cotinine to nicotine and delivered doses of nicotine in 

subgroups of smokers who used the identical brand of cigarettes, namely a filter-tipped, vented Marlboro (r = -0.59), 

which is a popular brand among European Americans, and 

Newport (r = -0.37), a menthol-flavored cigarette without 

filter-tip vents that is preferred by African Americans. The 

researchers concluded that the intensity of smoking and 

the mouth levels of smoke constituents significantly affect 

the concentrations of urinary biomarkers of exposure and 

should be taken into account in evaluating human exposure to toxic substances in cigarette smoke.

Regarding the influence of cigarette type on urinary 

biomarkers of exposure to toxic substances in mainstream 

smoke, there is a slight difference in puff volume and 

puff frequency among smokers of low-FTC-yield versus 

medium-FTC-yield cigarettes, as measured under FTC 

conditions (Djordjevic et al. 2000). Smokers of low-FTCyield brands drew somewhat larger puffs (48.6 versus 44.1 

mL) and inhaled more smoke both per cigarette (615 versus 523 mL) and daily (9.5 versus 8.2 L). However, delivered 

doses of NNK and B[a]P were marginally higher among 

smokers of medium-yield cigarettes (NNK: 250.9 versus 

186.5 ng per cigarette; B[a]P: 21.4 versus 17.9 ng). On the 

other hand, Hecht and colleagues (2005) found no differences in urinary biomarkers of exposure to NNK and B[a]P 

among smokers of regular, light, or ultralight cigarettes.

Researchers have also suggested that blocking ventilation holes during smoking can result in increased 

delivery of smoke constituents. For example, when puff 

and inhalation parameters were allowed to vary, participants took significantly more and larger puffs from cigarettes with unblocked ventilation than from those with 

completely blocked ventilation (Zacny et al. 1986; Sweeney et al. 1999). Hoffmann and colleagues (1983) found 

that blocking air-dilution holes in seven brands of commercial filter-tipped cigarettes increased nicotine yields by 

69 percent, tar yields by 51 percent, and CO yields by 147 

percent. Another study examined a cigarette brand with 

tar and nicotine yields of 4.0 and 0.4 mg, respectively, 

under various conditions of machine smoking intended to 

reflect the wide range of smoking behaviors (Rickert et al. 

1983). The researchers studied three levels of five smoking 

parameters (butt length, puff duration, puff interval, puff 

volume, and ventilation occlusion) and the effects on the 

number of puffs and TPM, and they estimated gas phase, 

particulate phase, and total yields of HCN. The HCN and 

TPM yields varied significantly under different smoking 

conditions. Ventilation occlusion had the most pronounced 

effect, accounting for 34 percent of the response variation 

in TPM yields and 42 percent of the response variation in 

total HCN yields.

Comparison of normal lip contact during smoking, 

which partially blocked filter vents, and smoking through 

a cigarette holder, which avoided blocking, showed higher 

nicotine boosts with normal lip contact (Höfer et al. 1991). 

Exposure to other smoke constituents may vary with the 

degree of blocking. Sweeney and colleagues (1999) found 

that blocking the filter vents of cigarettes with ventilation 

levels of at least 66 percent led to significant increases in 

CO exposure. The same manipulation of filter vents in cigarettes with filter ventilation levels of 56 percent or lower 

appeared to have negligible consequences for CO exposure. 

In another report, CO exposure from completely blocked 

filter vents was twice as high as from the unblocked vents 

(8.96 versus 4.32 parts per million [ppm]) (Zacny et al. 

1986). Blocking filter vents also resulted in higher CO 

exposure in a study by Höfer and associates (1991). Blocking filter ventilation holes is not the only element of smoking topography that influences filter efficiency. More rapid 

or intense puffing increases flow rates, which results in 

less effective filtration, because the smoke passes through 

the tobacco column and filter material more quickly with 

less opportunity for adsorption on the filter’s fibers. This 

smoking behavior also reduced the time for highly volatile 

gaseous materials to diffuse outward through the cigarette’s paper wrapper. 

An “elastic” cigarette is one that shows low levels of 

tar and nicotine when it is tested on a smoking machine 

but can potentially yield higher levels of emissions to 

smokers (Kozlowski et al. 2001). When cigarettes are elastic, smokers can extract as much nicotine as they need by 

changing their pattern of puffing on the cigarette. Analysis of tobacco from commercial American blend cigarettes 

purchased in the United States in 1990 revealed that 

the nicotine content did not differ substantially among 

brands that delivered a wide range of FTC-measured yields 

(Kozlowski et al. 1998). This cigarette design allowed 

delivery of virtually any amount of nicotine, depending 

on puffing behavior. Because there are similar amounts 

of other constituents in tobacco (e.g., TSNAs, metals, 

nitrates, and nitrites), regardless of the FTC ranking of the 

cigarette brand, more intense smoking to obtain a desired 
Surgeon General’s Report

50 Chapter 3

dose of nicotine leads to higher exposure to carcinogens. 

Historically, smokers have refused to use brands designed 

to reduce delivery of nicotine. For example, one company 

experimented with a modified cigarette containing denicotinized tobacco and a tar yield of 9.3 mg generated per 

cigarette but a nicotine yield of only 0.08 mg, as determined by using the FTC regimen, but this product was not 

successfully marketed (Rickert 2000).

Not all of the smoke volume delivered in the puff 

is inhaled by the smoker. Some escapes during mouth 

holding before inhalation. The depth of inhalation may be 

important for some smoke constituents but not for others, which is not surprising because of the complexity of 

the physics related to particle size that is involved with 

smoking and respiration. Finally, even very brief breath 

holding at peak inspiration can theoretically contribute to increased diffusion of some smoke constituents 

across alveolar membranes, as the intra-alveolar pressure increases.

There are considerable individual differences in 

inhalation patterns. In one study, inhaled smoke volume 

was measured by tracing the smoke with an isotope of the 

inert gas krypton (Woodman et al. 1986). The percentage 

of inhaled smoke (total inhaled smoke volume per total 

puff volume) averaged between 46 and 85 percent among 

persons in the study. Neither the mean inhaled smoke volume per puff nor the total inhaled smoke volume per cigarette was significantly correlated with any of the indices 

for puffing. 

Evidence on the importance of inhalation patterns 

to total smoke exposure is mixed (Woodman et al. 1986; 

Zacny et al. 1987; Zacny and Stitzer 1996). Variations 

in results may be related to the small number of persons tested and to the difficulties inherent in accurately 

capturing the relationship between puffing indices and 

total inhaled smoke. Methods used include pneumography using a mercury strain gauge, whole-body (head and 

arms out) plethysmography, impedance plethysmography, 

inductive plethysmography, and inert gas radiotracers. 

The method most commonly used in U.S. laboratories 

that study smoking is inductive plethysmography, in 

which chest and abdominal expansions are measured by 

bands applied around the rib cage and the abdomen. Significant practical limitations include difficulties in accurate calibration of the systems and adequate integration of 

chest and abdominal expansions, especially because men 

tend to have greater abdominal expansion than women do. 

Measurement artifacts created by movement during measurement are another limitation. Studies of the accuracy 

of the systems have shown fair results in adults (Zacny et 

al. 1987). Errors in volume measurements were typically 

approximately 100 mL over a large number of respiratory cycles. Unfortunately, the attributes of the systems 

have not been well studied for the puff-by-puff evaluation 

of human smoking behaviors. In addition, the most useful information will come from integrating puff analyses with inhalation parameters on a puff-by-puff basis to 

assess mouth holding and breath holding at peak inhalation. Studies such as those cited above have shown 

that mechanical testing regimens cannot mimic the 

way people smoke cigarettes. These findings suggest the 

importance of expressing the levels of toxic constituents 

as a ratio with nicotine or puff volume in the denominator 

(Rickert et al. 1985; Burns et al. 2008).

The size of particles containing chemical species can 

affect their retention in the lung. Cigarette smoke is an 

aerosol formed as the vapors generated in the pyrolysis 

zone cool and condense. Cigarette design has been shown 

to control particle-size distribution in an aerosol, so particles become easier or more difficult to inhale (Stöber 

1982; Ingebrethsen 1986; McRae 1990; Wayne et al. 2008). 

Burning finer-cut tobacco creates an aerosol with smaller 

particles, which are easier to inhale. Thus, changing the 

filler cut width can change the distribution of particle 

size in the aerosol and the chemistry. Particle size is also 

altered by air dilution. Dilution reduces the aerosol concentration and, thus, the coagulation rate. The particle 

size of the smoke is increased by increasing the coagulation rate or by condensing the moisture produced during 

combustion onto the smoke particles. According to Ishizu 

and colleagues (1987), the timed average particle size 

(equivalent diameter) for major chemical components 

in tobacco smoke was 0.03 to 0.5 μm, and constituents 

with higher boiling points tended toward larger particle 

sizes. Very small particles are more likely to be retained 

in the lungs. The overall equivalent diameter of particles 

of crude tar in tobacco smoke was 0.21 μm. Nicotine was 

usually present in small particles (e.g., 0.08 μm). Particle size influences how fast chemicals are transferred to 

tissue. Particles larger than 0.3 μm are more likely than 

smaller particles to be absorbed in the mouth and throat 

than in the lungs (Wayne et al. 2008).

Accurate measurement of particle size distribution 

in cigarette smoke is important for estimating deposition 

in the lung (Anderson et al. 1989). Most earlier studies 

(1960–1982) reported a median diameter of 0.3 to 0.5 μm, 

including a few ultrafine particles (<0.1 μm). Using the 

electrical aerosol analyzer, Anderson and colleagues (1989) 

reported similar values for median diameter (0.36 to 0.4 

μm) for the particles emitted in smoke from U.S. commercial filter-tipped cigarettes. But, there were also distinctly smaller particles, with a median diameter of 0.096 

to 0.11 μm. This finding indicated the presence of many 

more ultrafine particles in the smoke than was previously 

recognized. It is notable that the low- and ultralow-yield 

filter-tipped cigarettes Merit and Carlton emitted smaller 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 51

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

particles than did the full-flavored Marlboro cigarettes. 

Ultrafine particles are of toxicologic importance because 

their deposition in the respiratory tract was significantly 

higher than that of the 0.3- to 0.5-μm particles. Also, the 

relatively large surface-to-volume ratio of the ultrafine 

particles could facilitate adsorption and delivery of potentially toxic gases to the lung.

An alternative analysis of the impact of particle 

size on deposition in the lung suggested that growth in 

particle size may accelerate deposition in the respiratory 

tract (Martonen and Musante 2000). Because of their 

hygroscopicity, inhaled smoke particles may grow to several times their original diameter. This study suggested 

that mainstream cigarette smoke could behave aerodynamically as a large cloud (e.g., 20 μm in diameter) 

rather than as submicrometer constituent particles. The 

effect of cloud motion on deposition is pronounced. For 

example, an aerosol with a mass median aerodynamic 

diameter of 0.443 μm and a geometric standard deviation 

of 1.44 would have the following deposition fractions: lung, 

0.14; tracheobronchial, 0.03; and pulmonary, 0.11. When 

cloud motion is simulated, the total deposition is concentrated in the tracheobronchial compartment, especially 

in the upper bronchi, and pulmonary deposition is negligible. Cloud motion produces a heterogeneous deposition 

resulting in increased exposure of underlying airway cells 

to toxic and carcinogenic substances. The deposition sites 

correlate with the incidence of cancers in vivo.

Although most of the smoke particles deposit in 

the periphery of the lung, the surface concentrations of 

deposited particles are not significantly greater in the 

periphery than in centrally located airways (Muller et al. 

1990). Concentrations on the surface of the central airway are relatively independent of breathing patterns and 

airway geometry. This finding suggests that the effects of 

deposition of particles from cigarette smoke cannot be 

greatly reduced by changing the pattern of smoke inhalation. Efforts to manipulate particle size in smoke have 

been described in greater detail in a report by Wayne and 

colleagues (2008). Their study draws on internal tobacco 

company documents to assess industry consideration of 

the role of smoke particle size as a potential controlling 

influence over inhalation patterns and exposure of lungs 

to harmful substances. The researchers reported that 

tobacco manufacturers evaluated manipulation of particle 

size to control physical and sensory attributes of tobacco 

products and to reduce health hazards related to exposure 

to tobacco smoke. Examples of design features of tobacco 

products that relate to potential effects on generation 

of particle size and distribution of particles include puff 

flow rate, tobaccos and experimental blends, combustion, circumference, rod length, and ventilation (Wayne et 

al. 2008).

In summary, smoking behavior (puff volume, 

number of puffs per cigarette, and percentage of ventilation holes blocked) has a major impact on the levels of 

toxic, carcinogenic, and addictive compounds delivered 

to the smoker in cigarette smoke. The puffing patterns 

of smokers vary considerably from person to person. To 

completely understand the effect of specific harmful 

chemical constituents on smokers, further research is 

needed to explore how cigarette design and the chemical 

makeup of cigarettes influence use of the product.

Biomarkers

General Concepts

Accurate prediction of health risks from cigarette 

use is complicated by several factors, including the chemical complexity of cigarette smoke, significant variations 

among the dose-response relationships for the many diseases associated with exposure to cigarette smoke, qualitative and quantitative changes in the dose of cigarette 

smoke received by smokers throughout their smoking 

histories, and the long latencies between the initiation 

of exposure and the onset of some diseases, such as various cancers, caused by smoking cigarettes. Prediction is 

also hampered by the ever-changing number and types of 

tobacco products available to consumers, as well as fluctuations in the composition of the products (Stratton et 

al. 2001).

Before the term “biomarker” was coined, biomedical 

researchers used the appearance of unique markers such 

as carcinoembryonic antigens (Burtin et al. 1972) to diagnose and monitor cancer or panels of metabolic or physiological risk factors (e.g., serum cholesterol, maternal 

serum α-fetoprotein, and serum angiotensin-converting 

enzyme) to predict the clinical course of adverse effects on 

health. During the 1980s, the National Research Council 

(NRC) issued a series of reports that covered the conceptual basis for using biomarkers and reviewing biomarkers 
Surgeon General’s Report

52 Chapter 3

related to major organ systems and diseases (Committee 

on Biological Markers of the NRC 1987). In an early comprehensive discussion of biomarkers as risk assessment 

tools, Hattis (1986) described their value in characterizing dose-response relationships, estimating internal dose, 

extrapolating across species, and assessing interindividual variability (DeCaprio 1997). At about the same time, 

Prignot (1987) published a summary of existing chemical markers of tobacco exposure that could be used to 

assess individual exposure to tobacco and exposure to secondhand tobacco smoke as well as to validate successful 

smoking cessation.

In the framework for considering biomarkers proposed by the NRC Committee on Biological Markers 

(1987), a set of still useful definitions was offered. In brief, 

exposure involves contact with the agent of concern. Dose 

refers to the material that enters the body. Internal dose 

refers to the amount of material entering the body, and 

biologically effective dose refers to the amount of the agent 

that reaches the target site(s) within the body. Markers 

of health effects reflect preclinical changes short of those 

reached when clinical disease occurs. Markers of susceptibility are linked to increased risk on exposure. 

The long latency of most diseases caused by cigarette use indicates the need for predictive markers of 

future risk that could identify those people already experiencing preclinical effects of smoking. However, the first 

widely accepted tobacco biomarkers were indicators of 

exposure rather than predictors of disease risk. Breath CO, 

saliva thiocyanate (Jaffe et al. 1981), serum thiocyanate 

(Foulds et al. 1968), and nicotine and nicotine metabolites 

(Watson 1977) were prominent in the early literature for 

assessing exposure to cigarette smoke, and they remain in 

use today.

In comparison with the framework and definitions 

used for exposure and dose generally, a somewhat distinct 

set of terms has been applied to exposure to cigarette 

smoke. The 2001 report, Clearing the Smoke, published 

by the Institute of Medicine defines a biomarker of exposure as a tobacco constituent or metabolite that is measured in a biologic fluid or tissue and has the potential 

to interact with a biologic macromolecule (Stratton et al. 

2001). The definition notes that such biomarkers are also 

considered as measures of internal dose. A biomarker of 

a biologically effective dose is defined as the amount of a 

tobacco constituent or a metabolite that binds to or alters 

a macromolecule. A biomarker of a biologic event with the 

potential to lead to harm is defined as a measurement of 

an effect attributable to exposure, including early biologic 

effects; alterations in morphology, structure, or function; 

and clinical symptoms consistent with harm. In the more 

general formulation, such biomarkers constitute markers 

of health effects. 

Validated biomarkers of tobacco exposure exist, 

and progress has been made in developing biomarkers of 

biologically effective dose. The biologically effective dose 

represents the net effect of metabolic activation and the 

rate of detoxification in a target biologic tissue or bodily 

fluid. Many tobacco-related toxicants and carcinogens 

are biologically inactive until transformed by metabolic 

enzymes such as cytochrome P-450s into reactive intermediates. Reactive metabolic intermediates bind to macromolecules such as DNA and protein and disrupt their 

normal function. Not all binding to, or alteration of, a 

macromolecule leads to an adverse health effect. Consequently, the amount of material bound to a target macromolecule provides only an estimate of the biologically 

effective dose (Stratton et al. 2001). Polymorphisms of the 

metabolic enzymes may modify the balance of activation 

and detoxification and thus the potency and response of a 

biomarker (Norppa 2003).

Biomarkers of biologic events with the potential to 

lead to harm reflect changes in a cell or in cellular macromolecules that result from exposure to tobacco. These 

biomarkers can range from isolated changes with or without effects on function to events that clearly lead to illness or are symptoms of illness (e.g., cough). Measurable 

biomarkers of biologic events with the potential to lead to 

harm are relatively nonspecific (Stratton et al. 2001).

Few specific biomarkers have been validated as 

predictors of disease development (Stratton et al. 2001), 

although some studies indicated that DNA and protein 

adduct levels are associated with cancer risk (Hecht 2003). 

The application of biomarkers in tobacco-related disease is 

described in detail throughout this report and discussed 

briefly here.

Biomarkers of Exposure

There are diverse biomarkers of exposure. The least 

intrusive measurements are of chemicals and metabolic 

products in the breath. Levels of exhaled CO, nitric oxide, 

2,5-dimethylfuran, and volatile organic compounds (e.g., 

benzene and toluene) are higher in the breath of smokers than in the breath of nonsmokers (Gordon et al. 2002; 

IARC 2004). One study showed that volatile compounds 

such as benzene and 1,3-butadiene have a short residence 

time in the body and that their concentrations in breath 

were a function of the number of cigarettes smoked and 

the time between when the smoker takes a puff and when 

the breath sample is collected (Gordon et al. 2002). Saliva 

is another biologic material that is readily accessible and 

inexpensive to collect. Cotinine, a metabolite of nicotine 

(Bernert et al. 2000), and thiocyanate, a metabolite of 

cyanide (Prignot 1987), can be measured in saliva; levels 

of both metabolites can be used to distinguish between 

smokers and nonsmokers. 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 53

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

serum cotinine and blood cadmium levels correlated with 

the number of cigarettes smoked per day (Telišman et 

al. 1997; Caraballo et al. 1998). The correlation between 

acetonitrile concentrations and the number of cigarettes 

smoked per day was shown to be weak (Houeto et al. 1997).

Markers of tobacco smoke exposure that were measured in other biologic tissues include PAH compounds 

in lung tissue, B[a]P and TSNAs in cervical mucus (IARC 

2004), and TSNAs in pancreatic juice (Prokopczyk et al. 

2002). Also, researchers observed that pregnant smokers 

had higher placental levels of cadmium than did pregnant women who did not smoke (Ronco et al. 2005a,b). In 

another study, cadmium was detected in the seminal fluid 

of smokers at higher levels than in that of nonsmokers, 

and the levels correlated with the number of cigarettes 

smoked per day (Telišman et al. 1997).

Biomarkers of Biologically Effective Dose

For cancer, a common assessment of the biologically 

effective dose is measurement of levels of carcinogen-DNA 

adducts. Strong data from animal experiments and some 

human studies indicate relationships among the levels of 

constituents of tobacco smoke, formation of carcinogenDNA adducts, and cancer risk (Stratton et al. 2001). Levels 

of DNA adducts potentially provide the most direct measure of tobacco-induced DNA damage, and many studies 

reported higher levels in the tissues of smokers than in 

those of nonsmokers (Hecht 2003). In one study, most 

cancers causally associated with tobacco smoking showed 

positive evidence of increased adduct levels (Phillips 2005). 

However, human data on adduct formation suggested 

that saturation may occur at high levels of exposure (i.e., 

>20 cigarettes per day), causing the dose-response curve 

to plateau and reducing the proportional relationship 

between exposure and adduct levels (Godschalk et al. 

2003). Little is known about the temporal variability of 

DNA adducts within a target or surrogate tissue. One 

investigator reported that levels of carcinogen-DNA 

adducts are indicators of carcinogenic hazards but not of 

quantifiable risks (Phillips 2005). 

Carcinogen-DNA adducts can be measured in target or surrogate tissues. For example, they were measured in human lung tissue, exfoliated bladder cells, oral 

mucosa, exfoliated oral cells, and cervical cells—all sites 

of tobacco-derived cancers—and in surrogate tissues (e.g., 

carcinogen–peripheral blood lymphocyte DNA adducts) 

(Mancini et al. 1999; Romano et al. 1999; Stratton et al. 

2001). The assumption that levels of DNA adducts in a 

surrogate tissue or cell reflect those in a target tissue has 

principally been supported by studies of animals treated 

with single carcinogens, but results in human biomonitoring studies have been mixed (Phillips 2005). 

Urinary compounds are useful markers of the 

uptake and metabolic processing of constituents of cigarette smoke (IARC 2004). Urinary markers of exposure 

to cigarette smoke are nicotine and nicotine metabolites including cotinine; minor tobacco alkaloids such 

as anatabine and anabasine; 1-HOP; 1- and 2-naphthol; 

hydroxyphenanthrenes and phenanthrene dihydrodiols; 

aromatic amines; heterocyclic amines; N-nitrosoproline; 

and NNAL (Hoffmann and Brunnemann 1983; Jacob et 

al. 1999; Hecht 2002; Murphy et al. 2004), thiocyanate 

(Prignot 1987), acetonitrile (Pinggera et al. 2005), and 

methylhippuric acids (Buratti et al. 1999). Nicotine and 

its metabolites and NNAL are specific to tobacco exposure, 

and compounds such as thiocyanate and 1-HOP reflect 

environmental sources of exposure including diet (Van 

Rooij et al. 1994; Sithisarankul et al. 1997; Hecht et al. 

2004). In one study, levels of total NNAL, total cotinine, 

and 1-HOP increased with the number of cigarettes 

smoked per day (Joseph et al. 2005). The highest rates of 

increase were observed at low levels of cigarette use (1 to 

10 cigarettes per day), and levels in urine plateaued at 25 

to 35 cigarettes per day.

Some urinary metabolites provide information on 

metabolic activation and detoxification, as well as the dose 

(Hecht 2002, 2003). Examples are trans,trans-muconic 

acid and S-phenylmercapturic acid (benzene metabolites), 

NNAL and its glucuronides (metabolites of the TSNA 

NNK) (Melikian et al. 1993, 1994; Hecht 2002, 2003), and 

1-HOP (a pyrene metabolite) (Hecht et al. 2004). Studies 

reported that concentrations of urinary 1-HOP glucuronide (Sithisarankul et al. 1997) and total 1-HOP (free and 

conjugated) (Van Rooij et al. 1994) correlated well with the 

number of cigarettes smoked per day. In one study, there 

appeared to be no significant difference in the urinary 

concentration of 1-HOP glucuronide in smokers of cigarettes containing blond (flue-cured) tobacco versus smokers of black (air-cured) tobacco (Sithisarankul et al. 1997). 

Other studies found that in most smokers, more than 80 

percent of the nicotine dose received was accounted for by 

urine content of nicotine, nicotine glucuronide, cotinine, 

cotinine glucuronide, and trans-3’-hydroxycotinine (Benowitz et al. 1994; Davis and Curvall 1999). Total cotinine 

(free and conjugated) is considered the most reliable urinary marker of nicotine exposure (Murphy et al. 2004).

Examination of the blood of smokers shows elevated 

carboxyhemoglobin, thiocyanate, cadmium, acetonitrile, 

2,5-dimethylfuran, VOCs (e.g., benzene, toluene, and 

styrene), the presence of nicotine and its metabolite cotinine, and NNAL (Ashley et al. 1996; Houeto et al. 1997; 

IARC 2004). In addition, investigators found a positive 

correlation between carboxyhemoglobin and exhaled CO 

for several hours after smoking (Hopkins et al. 1984), and 
Surgeon General’s Report

54 Chapter 3

Additional biomarkers of biologically effective dose 

are (1) protein adducts, in that most carcinogen metabolites that react with DNA also react with proteins, and (2) 

oxidized damage to DNA bases. Protein adducts present 

at higher levels in smokers than in nonsmokers include 

hemoglobin adducts of TSNAs, 3-aminobiphenyl, 4-aminobiphenyl, o-toluidine, p-toluidine, and 2,4-dimethylaniline, as well as adducts from ethylation or methylation 

of the N-terminal valine of hemoglobin (Branner et al. 

1998; Thier et al. 2001; Hecht 2003). The lung tissues 

of smokers have higher levels of acrolein-derived DNA 

lesions, one of which was identified as the mutagenic 

guanine adduct α-hydroxy-2’-deoxyguanosine. This 

lesion blocks DNA replication, potentially leading to G→T 

and G→A base substitution mutations (Yang et al. 2002; 

Zhang et al. 2007; Zaliznyak et al. 2009). The repair products of oxidative DNA lesions are water soluble and are 

generally excreted into urine without further metabolism. Because of extensive and rapid DNA repair, urine 

excretion of the oxidative DNA repair lesions reflects the 

average rate of oxidative DNA damage in all the cells in 

the body (Loft and Poulsen 1998). Levels of 8-hydroxy-2’-

deoxyguanosine (8-OH-dG) (Gackowski et al. 2003) and 

8-nitroguanine (Hsieh et al. 2002), both shown to indicate oxidative DNA damage, were found to be higher in 

the DNA of leukocytes of smokers than in those of nonsmokers. Tobacco smoking was consistently shown to 

increase the urinary excretion rate of 8-OH-dG by 30 to 50 

percent, and levels in urine decreased after smoking cessation (Loft and Poulsen 1998). In addition, both healthy 

smokers and smokers with cancer had urine levels of 

8-hydroxyguanine that were higher than those in healthy 

nonsmokers (Gackowski et al. 2003). The oxidatively 

modified DNA base, 8-hydroxyguanine, is also a marker 

of oxidative stress. There is no epidemiologic evidence 

that high levels of oxidative DNA modification in tissue or 

high levels of oxidatively modified nucleic acid products 

in urine are predictors of cancer development in humans 

(Poulsen 2005).

Many mutagens and carcinogens are metabolically 

activated in vivo to electrophilic forms capable of interaction with cellular macromolecules (van Doorn et al. 

1981). One of the mechanisms used by an organism to 

combat electrophilic attack is conjugation of the reactive 

chemical moiety with reduced glutathione, a nucleophile. 

This reaction causes an increase in more polar thioether 

conjugates, which are excreted from the body in urine and 

bile. Urinary thioether concentrations are used as a nonspecific indicator of exposure to alkylating agents. Cigarette smoking was found to cause a dose-related increase 

in the urinary excretion of thioethers. Chemicals present 

in cigarette smoke and excreted in urine as thioethers 

include benzene, styrene, and vinyl chloride (van Doorn 

et al. 1981; Goldstein and Faletto 1993; Fisher 2000b). 

Increased concentrations of alkyladenines and alkylguanines from the reaction of alkylating agents with DNA 

were also observed in the urine of smokers (Hecht 2002). 

All three types of carcinogen biomarkers (thioethers, 

alkyladenines, and alkylguanines) reflect chemical uptake 

and the balance between activation and detoxification 

(Hecht 2003). 

Biomarkers of Biologic Events with the Potential 

to Lead to Harm

Stratton and colleagues (2001) have reviewed a large 

number of biomarkers of biologic events with the potential to lead to harm. This review and more recent publications are summarized here. On an organ or system level, 

signs and symptoms of potential biologic events with the 

potential to lead to harm include osteoporosis, cough, 

hyperplasia, dysplasia, abnormal serum lipid concentrations, alterations in levels of blood coagulants, periodontal 

disease, and abnormal results for glucose tolerance tests 

(Stratton et al. 2001). On a molecular level, relevant measurements in target tissues of smokers include changes 

in RNA or protein expression, somatic mutations or loss 

of heterozygosity, alterations in promoter methylation, 

and mitochondrial mutations. In surrogate tissues, biomarkers of biologic events with the potential to lead to 

harm among smokers include leukocytosis, HPRT mutations, chromosomal aberrations, and changes in circulating lymphocytes.

Studies have identified biomarkers of biologic 

events with the potential to lead to harm related to cigarette smoking that are addressed in this Surgeon General’s report. For example, a significant association and a 

dose-response relationship were shown for chromosomal 

aberrations induced by B[a]P diol epoxide at locus 3p21.3 

in peripheral blood lymphocytes and for risk of squamous 

cell carcinoma of the head and neck (Zhu et al. 2002). 

Also, study findings suggested the frequency of promoter 

methylation in tumor-suppressor genes (P14, P16, P53) as 

a biomarker for risk of non-small-cell lung cancer among 

current and former smokers and cervical squamous cell 

cancer among smokers (Jarmalaite et al. 2003; Lea et al. 

2004). 

Cigarette smoking is a risk factor for bladder cancer. The increased mutagenicity of smokers’ urine was 

first shown in 1977 by testing the brand XAD/acetoneextractable organics from urine in the Salmonella (Ames 

test) mutagenicity assay (Yamasaki and Ames 1977). Studies using essentially the same methods confirmed this 

observation (DeMarini 2004). Peak mutagenic activity of 

the urine occurs 4 to 5 hours after the start of smoking 

and decreases to pre-smoking levels in approximately 12 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 55

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

to 18 hours (Kado et al. 1985). Findings suggested that the 

mutagens are absorbed rapidly (in 3 to 5 hours).

Urinary mutagenicity generally correlates with the 

number of cigarettes smoked, and the level of urinary 

mutagenicity was found to be similar regardless of the 

tar level of the cigarettes smoked (Tuomisto et al. 1986; 

Kuenemann-Migeot et al. 1996). However, the urine from 

smokers of black tobacco was reported to be twice as 

mutagenic as that from smokers of blond tobacco, which 

correlated with the known increased risk for bladder cancer among smokers of black versus blond tobacco (Malaveille et al. 1989). In addition, smoking-associated urinary 

mutagenicity correlated with external measures of exposure (e.g., daily intake of chemicals from tobacco smoke) 

and with internal measures of exposure (e.g., urinary 

1-pyrenol) (Pavanello et al. 2002). 

Aromatic amines, heterocyclic amines, and PAHs 

appear to be the chemicals responsible for smokingrelated urinary mutagenicity, as detected in the Salmonella assay (IARC 2004). Studies showed that urinary 

mutagenicity correlated with the levels of a 4-aminobiphenyl-DNA adduct in exfoliated urothelial cells from smokers (Talaska et al. 1991). Chemical analyses of urine from 

smokers with exceptionally high urinary mutagenicity 

revealed the presence of the mutagen 2-amino-7-naphthol, a 

metabolite of the bladder carcinogen 2-aminonaphthalene 

(β-naphthylamine) (Connor et al. 1983).

Although studies have described several biomarkers for risk of cardiovascular disease, no biomarker was 

specific to cigarette smoking. These biomarkers include 

changes in blood lipid concentrations, urine thromboxane 

A2 metabolites, blood F2-isoprostanes, vascular cell adhesion molecule-1, reduced platelet survival, atherosclerosis 

or calcium formation, and possibly elevated blood pressure (Stratton et al. 2001; Cavusoglu et al. 2004; Morrow 2005).

Symptoms and signs of biologic events with the 

potential to lead to harm to the respiratory system 

include late-occurring symptoms (cough, chronic phlegm 

production, wheeze, and shortness of breath) and decrements in pulmonary function, such as a notable decline 

in forced expiratory volume in one second (Carrell 1984; 

Ogushi et al. 1991; Stratton et al. 2001). Other biomarkers of biologic events with the potential to lead to harm 

are declines in alveolar neutrophil and macrophage 

counts and declines in neutrophil elastase α1-antiprotease complexes. 

Some of the general markers described here can 

be considered as biomarkers of potential reproductive or 

developmental effects from maternal cigarette smoking 

during pregnancy. Findings in one study indicated that 

increased levels of F2-isoprostane in cord blood may serve 

as a biomarker of oxidative stress (Obwegeser et al. 1999). 

Another study reported biomarkers in cord blood of offspring of women who smoked during pregnancy and in 

maternal blood (İşcan et al. 1997). The markers included 

reduced levels of high-density lipoprotein cholesterol 

(HDLc) and apolipoprotein A-I (APO A-I) and elevated 

ratios of total cholesterol to HDLc, low-density lipoprotein cholesterol (LDLc) to HDLc, and APO B to APO A-I. 

Proteomics allows study of changes to proteins following 

environmental exposures. A recent comparison of up- and 

downregulated proteins in blood cord sera from the offspring of women who smoked during pregnancy with that 

of offspring of nonsmokers suggests that infants exposed 

in utero undergo changes in protein expression similar to those of smoke-exposed adults and animal models 

(Colquhoun et al. 2009). Among the changes were markers of inflammation (α2-macroglobulin), altered lipid 

metabolism (APO A-I), and α-fetoprotein, which is associated with fetal growth retardation (Colquhoun et al. 2009). 

These findings indicate that serum and cord blood lipid 

panels may provide biomarkers of biologic events with the 

potential to lead to harm to fetal metabolism of lipids.

Smoking interferes with absorption of vitamins 

B6, B12, and C and folic acid (Cogswell et al. 2003). 

Study findings indicate that lower plasma concentrations of vitamins (folate and B12) and nitric oxide from 

maternal smoking may result in hyperhomocysteinemia 

in pregnant women, a known risk factor for pregnancyinduced hypertension, abruptio placentae, and intrauterine growth restriction (Obwegeser et al. 1999; Özerol et 

al. 2004; Steegers-Theunissen et al. 2004). Women who 

smoke during pregnancy have an increased risk of delivering a low-birth-weight infant (USDHHS 2004). Decreases 

in birth weight were dose related to the number of cigarettes smoked (Abel 1980). Researchers reported that low 

concentrations of maternal serum folate and vitamin B12 

were associated with higher risk of preterm delivery and 

low birth weight, and low-birth-weight infants had significantly lower concentrations of vitamins A, B2, E, and folate 

(Navarro et al. 1984; Fréry et al. 1992; Scholl et al. 1996). 

In other studies, placental cadmium levels were strongly 

correlated with birth weight in newborns of mothers who 

smoked (Ronco et al. 2005a). Cotinine concentrations in 

maternal serum and urine were also useful in predicting 

birth weight (Stratton et al. 2001).

In summary, several biomarkers provide an accurate 

assessment of exposure to toxic chemicals in cigarette 

smoke. Still to be determined is how accurately they can 

characterize differences in exposure between tobaccoburning cigarettes and the variety of potentially reducedexposure products introduced into the market during the 

last few years. Biomarkers of biologically effective doses 

for mutagenic and carcinogenic chemicals can provide an 

estimate of the interaction between chemicals in smoke 
Surgeon General’s Report

56 Chapter 3

and target biologic tissues or bodily fluids. Genetic polymorphisms of the enzymes involved in the metabolic 

activation of the chemicals may influence the net balance 

of activation and detoxification in a target biologic tissue 

and complicate interpretation of the dose-response relationship between exposure and binding with macromolecular targets. Despite the large number of biomarkers 

of biologic events with the potential to lead to harm, most 

are not specific to exposure to cigarette smoke and require 

additional testing to establish their specificity, sensitivity, 

and reliability when smoking behaviors or product characteristics vary. In addition, not all biomarkers of biologic 

events with the potential to lead to harm may be sufficient 

for determining population-level effects of the product.

Genotoxicity

Cigarette Smoke Condensate

Condensate from cigarette smoke is mutagenic in 

a variety of systems (DeMarini 1983, 2004; IARC 1986, 

2004). Most studies have used condensate generated from 

the smoke of reference cigarettes such as those available 

from the University of Kentucky, Lexington, Kentucky. 

Researchers using the bacterial Salmonella mutagenicity assay reported that the average mutagenicity of 

cigarette smoke condensates prepared from the mainstream smoke from U.S. commercial cigarettes and K1R4F 

reference cigarettes was not significantly different among 

cigarettes representing more than 70 percent of the U.S. 

market (Steele et al. 1995). These findings suggested that 

such reference cigarettes are acceptable standards for 

comparative mutagenicity of condensates from cigarettes 

purchased typically in the United States. The genotoxicity 

of 10 cigarette smoke condensate samples from a diverse 

set of cigarettes (including the K2R4F reference cigarette) 

and produced under different smoking-machine conditions was studied in four short-term assays: the Salmonella mutagenicity assay in frameshift strains TA98 and 

YG1041, the micronucleus and comet assays in L5178YTk 

± 7.3.2C mouse lymphoma cells, and an assay for chromosomal aberrations in CHO-K1 cells (DeMarini et al. 2008). 

All 10 condensate samples were mutagenic in both strains 

of Salmonella and induced micronuclei, and 9 samples 

induced DNA damage or chromosome aberrations. While 

their mutagenic potencies in Salmonella spanned 7-fold 

when expressed as revertants per gram of condensate, they 

spanned 158-fold when expressed as revertants per milligram of nicotine. The range of genotoxic potencies of the 

condensates in the other assays was similar regardless of 

how the data were expressed. The overall conclusion was 

that there was no relation among the genotoxic potencies of the cigarette smoke condensates across the assays 

(DeMarini et al. 2008).

Several lines of evidence indicated that the primary 

sources of mutagenic activity detected in the Salmonella

mutagenicity assay are aromatic amines and heterocyclic 

amine protein pyrolysate products (IARC 1986). Most of 

this activity resides in the basic or base/neutral fraction 

of the condensates, which contains the aromatic and heterocyclic amines. At the molecular level, the mutation 

spectrum of cigarette smoke condensate in the Salmonella 

frameshift strain TA98 was identical to that of the heterocyclic amine Glu-P-1 (DeMarini et al. 1995). The finding 

suggested that this class of compounds is responsible for 

most of the frameshift mutagenic activity of cigarette 

smoke condensate detected in TA98. A frameshift mutation is the insertion into or deletion from DNA of a number of nucleotides that are not three or multiples of three. 

In contrast, most of the mutations induced by cigarette 

smoke condensate in the base-substitution strain TA100 

were shown to be transversions of GC→TA (78 percent), 

which resembled most closely the mutation spectrum of 

B[a]P, the model PAH (DeMarini et al. 1995). The GC→TA 

transversions, a common class of base substitutions found 

in lung tumors of smokers, were also induced by cigarette 

smoke condensate at the HPRT locus in human B-lymphoblastoid MCL-5 cells (Krause et al. 1999).

Study findings indicated that most of the ability of 

cigarette smoke condensate to induce sister chromatid 

exchange (SCE) in mammalian cells may reside in the 

neutral and acidic/neutral fractions, suggesting that this 

activity is attributable to PAHs and acidic compounds, 

such as catechol, hydroquinone, alkylphenols, and benzaldehyde (Jansson et al. 1988). 

Nicotine and its metabolites were not mutagenic in 

Salmonella and did not induce SCEs in mammalian cells 

in culture, and nicotine did not produce mutagenic urine 

in rats (Doolittle et al. 1995). Burning tobacco produced 

mutagenic chemicals, and cigarette smoke condensate 

contained a variety of agents exhibiting a wide range of 

toxic effects. Varying the amounts of 300 to 400 ingredients added to typical commercially blended test cigarettes 

did not alter the inherent mutagenicity or cytotoxicity of 

the resulting condensates or the toxic effects of inhalation 

of the smoke of the resulting cigarettes (Carmines 2002; 

Baker et al. 2004). Many of the pyrolysis products from 

the cigarette ingredients identified as “biologically active” 

were volatile compounds (e.g., benzene, toluene, and styrene) (Baker et al. 2004) and would presumably reside primarily in the gas phase of the cigarette smoke rather than 

in the condensate used in most in vitro assays.
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 57

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

DNA Damage

Many studies have demonstrated that cigarette 

smoke and its condensate can produce DNA strand breaks 

in rodents, in mammalian cells in culture, or in DNA in 

vitro (IARC 2004). Collectively, results of these studies are 

consistent with the demonstrated clastogenicity (chromosome-breaking ability) of cigarette smoke and condensate and cigarette smoke in experimental systems and in 

humans. Several of these studies (IARC 2004) indicated 

that reactive oxygen or nitrogen species may be the primary cause of the breaks in DNA strands.

Cytogenetic Effects in Rodents

Exposure of rodents to cigarette smoke by inhalation has generally produced an increased frequency of 

SCE in the bone marrow (IARC 1986). However, such 

exposure produced some negative studies and one positive 

study of induction of chromosomal aberrations in lung 

cells (DeMarini 2004). Nonetheless, this exposure consistently produced micronuclei in bone marrow, peripheral 

blood erythrocytes, and lung cells (IARC 2004). 

Transplacental Effects in Rodents

Mice born to dams exposed to cigarette smoke by 

inhalation during pregnancy had elevated levels of micronuclei in the liver and peripheral blood (Balansky and 

Blagoeva 1989), and such exposure induced SCEs in the 

liver of fetal mice (Karube et al. 1989). Intraperitoneal 

injection of pregnant Syrian golden hamsters with the 

tobacco carcinogen NNK also induced micronuclei in 

fetal liver (Alaoui-Jamali et al. 1989), and intraperitoneal 

injection of pregnant mice with NNK induced oxidative 

damage, as determined by measurement of concentrations of 8-OH-dG DNA adducts in the fetuses (Sipowicz et 

al. 1997).

Studies in Humans

HPRT Mutations

In general, smoking was shown to increase the frequency of HPRT mutants in peripheral blood lymphocytes 

by approximately 50 percent. However, the increases did 

not reach statistical significance in some studies, probably 

because of the large interindividual variability (DeMarini 

2004). An increase in transversions, in particular GC→TA, 

was noted frequently among smokers (IARC 2004). However, some analyses found no difference in the mutation 

spectrum at HPRT in smokers and nonsmokers (Curry 

et al. 1999). GC→TA transversions are the primary class 

of base substitution induced by PAHs, and an excess of 

this class of mutation in the HPRT mutation spectrum 

for smokers is consistent with exposure to PAHs in cigarette smoke.

Genotoxic Effects in Reproductive Tissues 

and Fluids and in Children of Smokers

Lymphocytes from pregnant women who smoked 

either tobacco cigarettes or marijuana cigarettes had 

elevated frequencies of HPRT mutants, as determined by 

the autoradiographic HPRT assay, and analyses of cord 

blood indicated that lymphocytes from the newborns also 

had elevated frequencies of HPRT mutants (IARC 2004; 

DeMarini and Preston 2005). No differences in frequencies 

of HPRT mutants were observed in T lymphocytes from 

newborns of smokers compared with those from newborns 

of nonsmokers, as determined by the T-cell cloning assay. 

However, the mutation spectra for these two groups of 

newborns differed significantly from those for newborns 

of smokers who had an increase in “illegitimate” genomic 

deletions mediated by V(D)J recombinase. These findings 

suggested alteration in the HPRT mutation spectrum and 

possible increase in the frequency of HPRT mutant cells in 

newborns of mothers who smoked compared with those in 

newborns of mothers who did not smoke. Another study 

reported that in utero exposure to cigarette smoke also 

resulted in increases of translocation frequencies in newborns (Pluth et al. 2000). Other evidence indicated that 

smoking by the mother may lead to DNA strand breaks in 

lymphocytes of newborns (Şardaş et al. 1995). Amniocytes 

from mothers who smoked may show an increase in chromosomal mutations compared with those from nonsmokers (de la Chica et al. 2005); however, researchers raised 

concerns about this study, such as the lack of exposure 

assessment, the small sample size, and the fact that the 

chromosomal aberrations identified were of the chromatid type, which is a type that could have been formed in 

the petri dish during culturing and were not present in 

the amniotic fluid initially (DeMarini and Preston 2005). 

Reviews indicated that the cervical mucus and 

amniotic fluid of smokers were mutagenic and that cervical epithelial cells from smokers had higher frequencies of 

micronuclei compared with those from nonsmokers (IARC 

2004). Findings also suggested that smoking may induce 

chromosomal mutations and DNA damage in sperm or 

ova of smokers. The evidence that smoking induced oxidative damage to sperm DNA was found in elevated concentrations of 8-OH-dG in sperm DNA of smokers compared 

with that of nonsmokers (Shen et al. 1997). In addition, 

seminal fluid from infertile male smokers showed more 

oxidative damage than did that from infertile nonsmokers (Saleh et al. 2002). Consistent with these observations 

was the finding that sperm from smokers had higher concentrations of DNA strand breaks than did sperm from 
Surgeon General’s Report

58 Chapter 3

nonsmokers (Potts et al. 1999). Concentrations of DNA 

adducts in sperm, measured by the 32P-postlabeling assay 

were also higher among current smokers than among lifetime nonsmokers (Horak et al. 2003). Collectively, these 

data from studies of humans are consistent with the 

recent demonstration that exposure to cigarette smoke by 

inhalation resulted in germ-cell mutations in male mice 

(Yauk et al. 2007). 

Cytogenetic Effects

Micronuclei. Many studies have examined the 

influence of smoking on the frequency of micronuclei in 

peripheral lymphocytes; the results were mixed (Bonassi 

et al. 2003). A reanalysis of pooled data from 24 databases 

from the Human MicroNucleus international collaborative project showed that smokers did not have an overall 

increase in micronuclei frequency in lymphocytes. However, a significant increase in micronucleus frequency was 

found in heavy smokers (i.e., those smoking 30 cigarettes 

or more per day) who were not exposed occupationally to 

genotoxic agents. Studies also found elevated micronuclei 

frequencies in the tracheobronchial epithelium of smokers (Lippman et al. 1990).

Sister chromatid exchange. In contrast to frequency of micronuclei, SCE frequencies in peripheral 

lymphocytes are generally higher among smokers than 

among nonsmokers. Numerous studies of SCE frequencies in peripheral lymphocytes showed that cigarette 

smoking induced SCEs, which can then be a confounding 

factor in occupational studies (IARC 2004). The findings 

indicated that of all the cytogenetic endpoints, SCE is the 

most sensitive to the effect of smoking.

Chromosomal aberrations. Studies of large 

populations with use of chromosome banding techniques 

to assess chromosomal aberrations have had mixed 

results. One study reported that the frequency of chromosomal aberration was not increased by smoking (Bender 

et al. 1988), and another reported that smoking caused 

a 10- to 20-percent increase in the frequency (Mutation 

Research 1990). Smaller studies and those using 

molecular cytogenetic techniques also had mixed results; 

in some, smoking increased the frequency of chromosomal aberrations in peripheral lymphocytes, and in others, this finding was not observed (DeMarini 2004). 

Mechanistic considerations include the observation that smokers had lower concentrations of folate in 

red blood cells than did nonsmokers, which may play a 

role in the higher frequency of chromosomal aberrations 

detected in smokers (Chen et al. 1989). Other studies 

found that exposure of peripheral lymphocytes from smokers to mutagens in vitro resulted in a higher frequency 

of chromosomal aberrations than did similar exposure of 

lymphocytes from nonsmokers (IARC 2004). Collectively, 

findings of these studies suggested that cells of smokers, 

especially males, were less able to repair DNA damage 

and that concentrations of DNA repair enzymes, fragile 

sites in chromosomes, and telomeric associations could 

be affected by recent mutagenic exposures such as smoking (DeMarini 2004). These effects of smoking varied 

among individuals, and were influenced by exposures 

other than smoking. 

A large international study showed that an elevated frequency of chromosomal aberrations in lymphocytes predicted cancer risk independently of exposure to 

carcinogens, including cigarette smoke (Bonassi et al. 

2000). However, many studies demonstrated an association between smoking and certain genetic changes that 

are specific predictors of various types of tumors. For 

example, lymphocytes of smokers had a higher frequency 

of fragile sites in chromosomes and metaphases with 

extensive breakage, as well as overexpression of fragile 

sites at chromosomal breakpoints associated with cancer and oncogene sites on chromosomes (Kao-Shan et al. 

1987). Smoking was associated with chromosomal instability in lymphocytes as a biomarker for predisposition to 

oral premalignant lesions (Wu et al. 2002). In addition, 

smoking was associated with mutagen sensitivity of lymphocytes as a predictor of cancer of the upper aerodigestive 

tract. An analysis of normal bronchial epithelium using 

a molecular cytogenetic technique found a significant 

percentage of trisomy 7 in cancer-free tobacco smokers 

(Lechner et al. 1997). Another study reported a significant 

increase in the loss of heterozygosity involving microsatellite DNA at three specific chromosomal sites containing 

putative tumor-suppressor genes in histologically normal 

bronchial epithelium from long-term smokers (Mao et al. 

1997; Wistuba et al. 1997). The frequency of chromosomal 

aberrations was much higher in lung tumors from smokers (48 percent) than in those from nonsmokers (11 percent), suggesting that lung cancer in smokers is a result 

of genetic alterations distinct from those in nonsmokers 

(Sanchez-Cespedes et al. 2001).

Studies also associated alterations in chromosome 

9 in bladder tumors with cigarette smoking, and 

cytogenetic changes and smoking were associated with 

risk for leukemia and other myelodysplastic syndromes 

(IARC 2004).

DNA strand breaks and oxidative damage. 

A review by DeMarini (2004) reported that lymphocytes, 

buccal cells, and urothelial cells of smokers had higher 

frequencies of DNA strand breaks than those in nonsmokers, as measured by the single-cell gel electrophoresis 

(comet) assay, which detects broken DNA that separates 

from whole nuclear DNA when exposed to an electric 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 59

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

current. Oxidative damage measured by concentrations of 

7-hydroxy-8-oxo-2’-deoxyguanosine (8-oxo-dG) (a marker 

of oxidative damage) was elevated in lymphocytes and 

leukocytes, urine, and lung tissue of smokers. In vitro 

studies, including some in human cells, also found that 

cigarette smoke or its components induced DNA or oxidative damage. Collectively, these studies suggested that 

smoking induced oxidative DNA damage.

Mutations in tumors associated with 

smoking. In a review of studies in 2004, IARC noted 

that the TP53 gene was mutated most frequently in lung 

tumors associated with smoking, and the details of this 

observation were reviewed extensively (Pfeifer et al. 2002; 

Pfeifer and Hainaut 2003; IARC 2004). Mutations in the 

TP53 gene were more common in smokers than in nonsmokers, and a direct relationship existed between the frequency of TP53 mutations and the number of cigarettes 

smoked. TP53 mutations were found in preneoplastic 

lesions of the lung, indicating that they were early events 

linked temporally to DNA damage from smoking. 

Among the mutations of the TP53 gene in lung 

tumors of smokers, 30 percent were GC→TA transversions, whereas only 10 percent of the TP53 mutations in 

lung tumors of nonsmokers or in other tumors were of 

this type. The sites at which these mutations occurred in 

the TP53 gene corresponded with the sites of DNA adducts 

remaining after cells were exposed to diol epoxides of PAHs 

and allowed to undergo a period of DNA repair (Smith et 

al. 2000). The mutations in the tumors were targeted at 

methylated CpG sites on chromosomes, and there was 

a bias for most of the mutated guanines of the GC→TA 

mutations to be on the nontranscribed DNA strand in lung 

tumors from smokers, which is attributable to the preferential repair of DNA adducts on the transcribed strand 

(Yoon et al. 2001). 

Mutations in the KRAS gene (codons 12, 13, or 61) 

were shown to occur in approximately 30 percent of lung 

adenocarcinomas of smokers and are primarily GC→TA 

transversions, as seen in the TP53 gene (Gealy et al. 1999). 

As with the TP53 gene, the site at which the majority of 

a particular type of PAH adducts are formed in the KRAS

gene (the first position of codon 12) corresponded with 

the position where a high frequency of GC→TA transversions occur in lung tumors associated with smoking 

(Tretyakova et al. 2002). Similar to TP53 mutations, KRAS

mutations occurred early in carcinogenesis of the lung, 

and 66 percent of the mutations in the KRAS gene in 

smoking-associated lung tumors were GC→TA transversions (Keohavong et al. 2001). 

These observations, along with substantially more 

data, suggest that the TP53 and KRAS mutations in lung 

tumors of smokers are due to the direct DNA damage 

resulting from the carcinogens in cigarette smoke, especially PAHs (Pfeifer and Hainaut 2003). Researchers have 

suggested that other factors, especially selection, may also 

play a role in the observed mutation spectrum in smoking-associated lung tumors (Rodin and Rodin 2005).

Cytotoxicity

Cytotoxicity refers to a specific destructive action 

on cells. The cytotoxicity of cigarette smoke has been 

shown to manifest as several pathological conditions 

including irritation and inflammation, cell proliferation and hyperplasia, oxidative stress and damage, and 

decreased organ function (Andreoli et al. 2003). Studies 

demonstrated the presence of cytotoxic agents in the gas 

and particulate phases of cigarette smoke, and HCN and 

acrolein were identified as specific cytotoxic agents in the 

gas phase (Thayer and Kensler 1964; Battista 1976a). In 

the particulate phase, nonvolatile and semivolatile fractions, especially semivolatile acidic and neutral fractions, 

were found to demonstrate cytotoxic activity (Curvall et 

al. 1984, 1985; Matsukura et al. 1991). 

Study findings indicate that cytotoxicity may play a 

role in several tobacco-related chronic diseases, including 

emphysema, carcinogenesis, and atherosclerosis (Bombick et al. 1998; Andreoli et al. 2003). For example, injury 

to cells of the respiratory system by cigarette smoke is 

thought to be mediated by smoke-induced inflammation 

and damage from free radicals (Churg and Cherukupalli 

1993). Thus, the usefulness of in vitro cytotoxicity tests 

lies in their ability to measure indicators of cellular injury 

that may correlate with or predict inflammation (Stratton 

et al. 2001). 

Many early cytotoxicity studies focused on damage 

to ciliated organisms (paramecium), clam gill epithelium, 

and animal trachea (Wang 1963; Weiss and Weiss 1964; 

Wynder et al. 1965; Dalhamn 1970; Battista 1976a,b; Donnelly et al. 1981a,b; Curvall et al. 1984), as well as cells 

such as adipocytes, macrophages, and human tumor cell 

lines (Thayer and Kensler 1964; Thayer 1976a,b; Drath 

et al. 1981; Curvall et al. 1984, 1985). Ciliatoxicity assays 

measure the time to incapacitation of ciliated cells or the 

time required by ciliated respiratory cells to transport 

inert particles when exposed to cigarette smoke. Impaired 

ciliary function and mucus transport in an intact respiratory system precede metaplasia in bronchial epithelium. 

Assays with isolated or cultured cells typically assess inhibition of metabolic activity or cellular growth in the presence of cigarette smoke or damage to the cell membrane 

(Wynder and Hoffmann 1967).
Surgeon General’s Report

60 Chapter 3

Subsequent research on the cytotoxicity of cigarette 

smoke has frequently used the neutral red incorporation 

assay to evaluate smoke from different types of cigarettes 

or tobaccos (Bombick et al. 1997a,b, 1998; Foy et al. 2004). 

This assay is based on the uptake of neutral red dye into the 

lysosomes of viable cells. Injury to the plasma membrane 

or lysosomal membrane was shown to decrease uptake 

and retention of the dye (Babich and Borenfreund 1987). 

One study demonstrated that flue-cured tobacco produced 

smoke condensate that was significantly more cytotoxic in 

the neutral red incorporation assay than was condensate 

from burley tobacco smoke (Bombick et al. 1998). In addition, no difference was found in the cytotoxicity of smoke 

condensate from reference cigarettes representing commercial ultralow-tar (1R5F), low-tar (1R4F), or unfiltered 

full-flavored (2R1) cigarettes. In contrast, with this assay, 

whole mainstream smoke and the vapor phase of mainstream smoke from a 2R1 cigarette were more cytotoxic 

than those from a 1R4F cigarette, and those from a 1R4F 

cigarette were more cytotoxic than those from a 1R5F 

cigarette (Bombick et al. 1997a). In addition, sidestream 

smoke (whole smoke and vapor phase) was more cytotoxic 

than mainstream smoke, as determined in the neutral red 

incorporation assay. The same laboratory reported that 

neither a low-nitrogen tobacco blend with a celluloseacetate filter (11.6 mg tar in mainstream smoke) nor a 

traditional U.S. tobacco blend with a charcoal filter (10.4 

mg tar in mainstream smoke) reduced the cytotoxicity of 

the condensate of full-flavored, low-tar cigarettes in the 

neutral red incorporation assay (Bombick et al. 1997b). 

In more recent studies, researchers reported that 

heating the tobacco at a low temperature instead of burning it reduced the cytotoxicity of the smoke, as determined by the neutral red incorporation assay (Tewes et al. 

2003). However, the reduction was greater in the particulate phase than in the gas phase (Patskan and Reininghaus 

2003). Less frequently used in vitro assays for cytotoxicity 

include the dye exclusion assay (Hopkin et al. 1981; Hopkin and Evans 1984); the lactate dehydrogenase release 

assay; the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) uptake assay; and the kenacid blue 

binding assay (Putnam et al. 2002). 

Smoking-machine conditions are a determinant of 

the cytotoxicity of cigarette smoke condensate (Foy et al. 

2004; Roemer et al. 2004). Smoke condensates from U.S. 

commercial cigarettes ranging from very low or ultralow tar to full flavor as ranked by the FTC/ISO method, 

and also experimental reference cigarettes ranging from 

ultralow tar to low tar to full flavor, demonstrated a higher 

level of cytotoxicity when produced under smokingmachine conditions that generated higher smoke yields. 

The increase in cytotoxicity was measured in both the particulate and the gas phases expressed on a per cigarette 

basis. The increase in cytotoxicity measured in smoke 

produced under more intense smoking conditions was 

greatest for the particulate phase of the full-flavored commercial cigarettes and least for the ultralight varieties. 

This pattern was not as evident for cytotoxicity induced in 

the gas phase (Roemer et al. 2004).

The cytotoxicity of machine-generated mainstream 

smoke from the 2R1 reference cigarette to cultured mouse 

fibroblast L-929 cells was reduced by increasing the age of 

the smoke and the amounts of charcoal in an acetate filter 

(versus acetate alone) (Sonnenfeld et al. 1985). Investigators showed that cytotoxic effects on lung epithelial cells 

were attributable to oxidants and aldehydes present in 

the volatile phase of the smoke or formed in the cells on 

exposure to the smoke (Hoshino et al. 2001). In one study, 

selective reduction of compounds in the gas phase by an 

activated carbon filter decreased the cytotoxicity of the gas 

phase of the smoke from a commercial cigarette to lung 

epithelial cells (Pouli et al. 2003). (The compounds were 

acetaldehyde, acetone, acetonitrile, acrolein, acrylonitrile, 

benzene, 1,3-butadiene, 2-butanone, 2,5-dimethylfuran, 

ethylbenzene, furan, isobutyraldehyde, isoprene, methacrolein, methanol, 1,3-pentadiene, propionaldehyde, 

propionitrile, toluene, and m-xylene.) However, in other 

research, a decrease in intracellular concentrations of 

reduced glutathione in a human type II–like cultured 

lung cell line (A549) exposed to whole smoke was significantly greater than that produced by smoke filtered 

through a Cambridge filter pad (Ritter et al. 2004). This 

finding suggests that chemicals in the particulate phase 

of cigarette smoke produce an immediate depletion of an 

important cellular antioxidant. The A549 cell line has 

been extensively used to study human lung damage by single chemicals and complex chemical mixtures. This cell 

line may be more useful for studying substances that are 

active in their administered form, rather than for studying 

those that require biotransformation to reactive metabolites, because some cytochrome P-450 isoforms are not 

expressed in A549 cells (Castell et al. 2005). 

Recent mechanistic studies identified apoptosis 

and necrosis as important mechanisms of cytotoxicity 

of cigarette smoke to cultured mammalian lung cells 

(Hoshino et al. 2001; Piperi et al. 2003; Pouli et al. 2003). 

In one study, the viability of alveolar type 2 A549 cells was 

reduced by smoke extract from a commercial cigarette 

in a time- and concentration-dependent manner, as measured by the reduction of MTT (Hoshino et al. 2001). In 

another study, the viability of mouse lung LA-4 cells was 

reduced by the gas phase of commercial cigarette smoke 

in a concentration-dependent manner, as measured by 

lactate dehydrogenase leakage and reduced metabolic 

activity (WST-1 assay) (Piperi et al. 2003). In both studies, apoptosis was seen at low concentrations of smoke 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 61

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

and necrosis was seen at higher concentrations. One of 

the studies found that smoke extract increased intracellular oxidative activity (Hoshino et al. 2001). The other 

study observed a dose-dependent reduction in reduced 

cellular glutathione levels (Piperi et al. 2003). In addition, cells exposed to cigarette smoke showed increased 

protein modification (nitrotyrosine immunoreactivity) 

and activation of mitogen-activated protein kinase pathways. Aoshiba and colleagues (2001) reported that toxic 

effects on isolated alveolar macrophages from the smoke 

of an unfiltered commercial cigarette involved oxidative 

stress, an important mediator of cell death through both 

necrosis and apoptosis. This effect was associated with 

accumulation of BAX protein, mitochondrial dysfunction, 

and release of mitochondrial cytochrome c, but it was 

independent of the TP53 gene, FAS, and caspase activation. Sublethal concentrations of unfiltered extract from 

mainstream smoke from a commercial cigarette produced evidence of senescence in alveolar epithelial cells—

A549 cells and alveolar type 2 cells isolated from normal 

human lungs. The senescence was characterized by doseand time-dependent increases in β-galactosidase activity, 

changes in cell morphology, accumulation of lipofuscin, 

overexpression of the P21CIP1/WAF1/SDI1 protein, and irreversible growth arrest (Tsuji et al. 2004).

Scientists reported that the limitation of past and 

current in vitro tests for cytotoxicity is that the results 

are based on the response of single cell types or isolated 

tissues and do not include the influence of the whole-body 

system on the response (Stratton et al. 2001). However, 

in vitro cytotoxicity assays are useful in determining 

the contribution of different tobacco blends or cigarette 

components (e.g., the filter) to the overall cytotoxicity of 

the smoke and in identifying causative cytotoxic agents 

in smoke and mechanistic pathways. Although in vitro 

assays are not able to replace all conventional animal 

bioassays, they are increasingly seen as alternatives to 

animal testing of drugs and chemicals, in the European 

Union, the United States, and elsewhere (Höfer et al. 2004; 

Interagency Coordinating Committee on the Validation 

of Alternative Methods 2004). Many cellular pathways 

are activated similarly in vitro and in vivo (Devlin et al. 

2005). In 2005, the Canadian government implemented a 

regulation requiring performance of three in vitro tests 

of toxicity (mutagenicity, clastogenicity, and cytotoxicity) on emissions for all cigarettes sold in Canada and that 

the results be reported to the Minister of Health (Canada 

Gazette 2005). Quantitative in vitro dose-response data 

could eliminate the need for use of a large number of 

experimental animals to achieve appropriate statistical 

power in an in vivo study (Parry et al. 2005).

Animal Bioassays

Researchers have tested the carcinogenic ability 

of tar in cigarette smoke in laboratory animals for more 

than nine decades and in animal inhalation studies of 

machine-generated cigarette smoke for more than five 

decades (Wynder and Hoffmann 1967). The first successful 

induction of cancer in a laboratory animal with a tobacco 

product was reported by Wynder and colleagues (1953, 

1957) with the application of cigarette tar to mouse skin. 

They observed a clear dose-response trend between the 

amount of tar applied to the skin of the mice and the percentage of animals bearing skin papilloma and carcinoma 

in the test group. Skin-painting studies typically used 

condensate from cigarette smoke produced under standard FTC or ISO conditions, allowing comparisons among 

studies. More recent studies showed that smoking-machine conditions influence the measures of in vitro mutagenicity and cytotoxicity of smoke condensate, expressed 

on a per cigarette or per milligram of tar basis (Roemer 

et al. 2004; Rickert et al. 2007). However, skin-painting 

studies typically focused on product characteristics such 

as tobacco filler, paper, and additives rather than on smoke 

condensate produced under different smoking-machine 

conditions. One study demonstrated that tobacco blend, 

filter type, and flavoring materials are determinants of the 

composition of mainstream smoke, whereas the amount of 

tobacco in the cigarette, the dimensions of the cigarette, 

and the filter type influence smoke yield (Borgerding 

and Klus 2005). Future skin-painting studies will likely 

use condensates produced by different smoking-machine 

conditions, because some countries have begun to mandate cigarette testing with alternative smoking-machine 

conditions.

The use of experimental animal studies to predict 

cancer risk is more qualitative than quantitative (Stratton 

et al. 2001). Most animals used in laboratory studies with 

smoke are obligate nose breathers. Furthermore, Wynder 

and Hoffman (1967) reported that the respiratory systems 

of laboratory animals differ qualitatively and quantitatively from those of humans in surface area, in the development of mucous membranes, and in having an enhanced 

glandular system that increases the fluid in the nasal 

passages. Despite these limitations, animal studies provide 

information that is not available from in vitro systems 

because animal studies permit the use of an intact host 

system with a full complement of endocrine, hormone, 

and immune effects and hepatic and extrahepatic metabolism (Eaton and Klaassen 2001). Animal studies are often 

used to confirm positive findings or to resolve conflicting results from in vitro assays and to study organ-specific 

effects. Animal studies provide valuable data in terms of 
Surgeon General’s Report

62 Chapter 3

biologic plausibility, mechanisms of action, and causality. 

Animal studies of chronic diseases such as cancer can be 

less expensive than human clinical studies, and they also 

allow the use of invasive procedures (Devlin et al. 2005).

The smoke and smoke condensate animal bioassay 

literature is extensive and was reviewed by IARC in 2004. A 

synopsis follows of similar literature with a focus on studies made available since the publication of that review. 

Dermal Application of Cigarette 

Smoke Condensate

Studies have used mouse skin as the test tissue in 

experiments carried out during the past 35 years, and the 

results from various laboratories have been similar with 

respect to the overall degree of carcinogenic activity of 

cigarette smoke condensate and the major differences in 

activity from cigarettes with different designs. Cigarette 

smoke condensate produces both benign and malignant 

tumors on mouse skin. The induced tumors are usually 

of epidermal origin. The carcinogenic potency of the cigarette smoke condensate depends on the tobacco variety, 

the composition of the cigarette paper, and the presence 

of additives. Subtle differences in smoking techniques, 

storage conditions for cigarette smoke condensate, and 

procedures for animal exposure do not appear to critically 

affect the results (IARC 2004). Researchers also conducted 

a limited number of skin-painting studies in other animal 

species including Syrian golden hamsters (Bernfeld and 

Homburger 1983) and rabbits (Graham et al. 1957).

In early skin-painting experiments with mice, 

researchers examined the tumorigenic activity of smoke 

condensates from reference cigarettes, from cigarettes 

made with different reconstituted tobacco sheets, or from 

mixtures of smoke condensates from reference cigarettes 

and reconstituted tobacco sheets made with 8-percent 

sodium nitrate as a tobacco additive (Dontenwill et al. 

1972). Three preparations were tested: smoke condensate, 

dry smoke condensate without volatile smoke components, 

and condensate from vapor phase smoke. The smoke and 

the dry smoke condensates were equivalent in their ability 

to induce tumors, but the condensate from vapor phase 

smoke was nearly ineffective. The manufacturing process 

used to prepare the reconstituted tobacco sheet was a 

factor in the tumorigenic activity of the smoke condensate. Sodium nitrate reduced the tumorigenic activity of 

smoke condensate when added to the tobacco, to the reference cigarettes, or to the reconstituted tobacco sheet.

Subsequent studies continued to evaluate reference and experimental cigarettes constructed of tobaccoderived materials in dermal tumor promotion studies with 

female SENCAR mice (Meckley et al. 2004a,b). Cigarette 

smoke condensate from 1R4F reference cigarettes, which 

was applied to the skin of mice three times per week for 

29 weeks, produced significant, dose-dependent increases 

in both the number of tumor-bearing animals and in the 

total number of tumors in mice treated first (initiated) 

with the carcinogen 7,12-dimethylbenz[a]anthracene 

(DMBA). The tumors were papillomas and squamous cell 

carcinomas; papillomas were still progressing toward carcinomas at the end of the study. Animals in the high-dose 

group demonstrated treatment-related damage to the 

treated dorsal skin. The damage was described as peeling 

skin, erythema, and sores. The effects on the dorsal skin 

occurred at a lower incidence in the middle-dose group. 

Dose-dependent histologic changes in nonneoplastic skin 

at the treatment site were characterized by increased epidermal thickness (acanthosis) and hyperkeratosis. Significant increases were reported in the ratios of organ 

to body weight for the kidneys, liver, and spleen and in 

organ weight and ratios of organ weight to brain weight 

for the liver and spleen in the mid- and high-dose groups 

compared with those for the control group, which was 

initiated with DMBA but not promoted with condensate. 

Histologic examinations revealed an increase in extramedullary hematopoiesis of the spleen in the high-dose group.

To increase the filling power of tobacco, manufacturers developed processes to impregnate shredded 

tobacco with volatile materials and then rapidly remove 

them to expand the cellular structure of the leaf, thereby 

reducing the density of the tobacco filler. The expanded 

tobacco was shown to have a high burn rate and irritating smoke (Browne 1990). The reduced cigarette weight, 

increased filling power, and increased burn rate reduced 

the number of puffs, which, in turn, reduced delivery of 

tar and nicotine (Abdallah 2003a). Expanded tobacco is 

included in commercial cigarettes, and the amount of 

expanded tobacco as a percentage of the tobacco mass 

increases from approximately 15 percent in full-flavored 

cigarettes to 50 percent in ultralight brands (Theophilus 

et al. 2004). Other scientists reported that concentrations 

of most chemicals measured in the smoke of cigarettes 

with puffed, expanded, or freeze-dried tobacco were significantly reduced compared with those in control cigarettes 

(Hoffmann et al. 2001).

In a study by Theophilus and colleagues (2003b), 

condensates from the smoke of cigarettes constructed with 

100-percent tobacco expanded with dry ice or Freon-11 

(trichlorofluoromethane) produced similar numbers 

of tumor-bearing animals and total tumors in DMBAinitiated mice. Animals in the group treated with a low 

dose of condensate from smoke of tobacco expanded with 

Freon had a significantly longer median time to onset of 

tumors and significantly more total tumors than animals 

in the group treated with a low dose of condensate from 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 63

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

smoke of tobacco expanded with dry ice. No biologically 

significant nonneoplastic changes were observed in internal organs or treated dorsal skin. Smoke from the tobacco 

expanded with dry ice contained significantly higher 

concentrations of CO2, acetone, formaldehyde, catechol, 

nitric oxide, and NATB than did smoke from the Freonexpanded tobacco.

In other research, Theophilus and colleagues 

(2003a) studied smoke from cigarettes constructed with 

100-percent propane-expanded tobacco. They found that 

the smoke had significantly higher concentrations of 

total particulate matter, nicotine, tar, CO, CO2, ammonia, 

catechol, hydroquinone, phenol, p- and m-cresol, nitric 

oxide, NATB, and NNK than did the smoke from Freonexpanded tobacco. No biologically significant nonneoplastic differences in internal organs or treated dorsal skin 

were observed among animals treated with condensate 

from cigarettes containing propane-expanded tobacco 

compared with animals treated with condensate from 

cigarettes containing Freon-expanded tobacco. Smoke 

condensates from cigarettes made with Freon- or propaneexpanded tobacco produced similar numbers of tumorbearing animals and total tumors in DMBA-initiated mice.

In another study, Theophilus and colleagues (2004) 

treated mice with smoke condensate from cigarettes 

constructed with increasing percentages of expanded 

shredded tobacco stems. In general, there was a pattern 

of increasing numbers of tumor-bearing animals and 

total tumors with increasing doses of tar among groups 

of mice treated with low, medium, or high concentrations of expanded shredded tobacco stems. This pattern 

was not present across these groups at a given tar level. 

The control group treated with condensate from cigarettes without expanded shredded tobacco stems showed 

a dose-dependent increase in the percentage of animals 

with tumors and in the total number of tumors compared 

with DMBA-initiated animals in the solvent (vehicle) control group not treated with smoke condensate. Cigarettes 

containing expanded shredded tobacco stems produced 

lower concentrations of some chemicals in mainstream 

smoke than did cigarettes that did not contain expanded 

shredded tobacco stems, but the concentrations were not 

consistently reduced in a dose-dependent manner. 

In vivo and in vitro analyses support the hypothesis 

that short-term measures such as cytotoxicity, cellular 

proliferation (hyperplasia), generation of free radicals, and 

inflammation are involved in tumor promotion produced 

by cigarette smoke condensate (Curtin et al. 2004a). Other 

studies found that in addition to promoting tumors, cigarette smoke condensate and its fractions can act as tumor 

initiators, tumor accelerators, and cocarcinogens when 

applied together with other chemicals such as B[a]P and 

complete carcinogens (Wynder and Hoffmann 1961; Hoffmann and Wynder 1971; Hecht 2005).

The results from studies of dermal application of 

cigarette smoke condensate suggest a tissue-specific 

response to the chemicals in cigarette smoke that undergo 

covalent binding to DNA. Investigators have detected 

adducts in the skin, lung, heart, kidney, liver, and spleen 

of female ICR mice treated topically with cigarette smoke 

condensate from a commercial U.S.-blended unfiltered 

cigarette (Randerath et al. 1986, 1988; Reddy and Randerath 1990). In one study, dermal application of condensate 

from the smoke of 1R4F reference cigarettes three times 

per week for one or four weeks induced DNA adducts in the 

skin and lung tissue of male CD-1 mice (Lee et al. 1992). 

The relative adduct labeling values in skin were highest 

after one week of exposure and did not increase after four 

weeks. DNA adduct levels in the lung increased between 

one week and four weeks of treatment with condensate. 

Skin adducts declined to less than one-half the values of 

the first week by four weeks after cessation of exposure to 

condensate. In contrast, adduct levels in the lung continued to increase during the four weeks after cessation of 

exposure. Adduct levels increased with the total amount 

of tar applied weekly. The dose-response relationship was 

especially evident in lung tissue. In another study, treatments three times per week with similar concentrations 

of condensate from 1R4F cigarettes for 29 weeks resulted 

in an increase in DNA adducts in skin and dose- and timedependent increases in DNA adducts in lung and heart tissues of female SENCAR mice (Brown et al. 1998).

Inhalation Studies with Cigarette Smoke

Historically, animals have not proven to be good 

models for the type of lung tumors induced by cigarette 

smoke in humans. Inhalation exposure to cigarette smoke 

leads to a reduction in the respiratory rate, and nontransgenic animals and animal strains with a low background 

incidence of lung tumors often do not develop an excess 

of lung tumors of any type. Researchers have attempted 

to induce lung cancer by exposure to cigarette smoke in 

several animal species, including rabbits, monkeys, dogs, 

and hamsters and other rodents. Hamsters developed 

laryngeal tumors but not tumors in the lower respiratory 

tract, and dogs developed epidermoid and bronchioloalveolar carcinomas (Coggins 2002; IARC 2004; Witschi 

2005). Rodents tended to develop adenomas arising in the 

periphery of the lung rather than bronchial tumors arising 

centrally (Stratton et al. 2001). A study by Hutt and associates (2005) was the first to describe successful induction 

of lung tumors in mice after a lifetime whole-body exposure to mainstream cigarette smoke. Many animal studies 

used exposure chambers that permit whole-body exposure 
Surgeon General’s Report

64 Chapter 3

to cigarette smoke. Modern nose-only exposure tubes 

that allow body heat to dissipate are regarded by some as 

superior to whole-body exposure chambers because they 

eliminate dosing by nonrespiratory routes and allow the 

test concentration delivered to the animal to be closer to 

the concentration delivered to the system, by avoiding loss 

of the test compound on the walls, loss on the skin and 

fur of the animals, sedimentation and impaction of aerosol particles in the chamber, and chemical reactivity in 

the chamber (Pauluhn 2005). Table 3.1 contains data on 

lung tumor incidence from studies of carcinogenicity in 

rodents that used inhalation exposure to cigarette smoke. 

Mouse. Witschi and colleagues (1997a) demonstrated that mouse lung tumors developed in the 

peripheral lung as areas of hyperplasia that progress to 

adenocarcinomas. In subsequent research, Witschi and 

colleagues (2002) studied male Balb/c and SWR mice 

exposed to a mixture of 89-percent sidestream smoke and 

Table 3.1 Selected chronic carcinogenicity studies in mice and rats with inhalation exposure to cigarette smoke

Study Strain Gender Concentration

Exposure duration/ 

administration route

Lung tumor incidence 

(%)

Mouse               

Witschi et al. 

2002

Balb/c 

and SWR 

Male Average TSP concentration of 122 

mg/m3 from 1R4F reference cigarette 

sidestream/mainstream smoke 

mixture 

6 hours/day, 

5 days/week for 

5 months/whole body

Balb/c: 9/27 (33) 

Controls: 6/30 (20)

SWR: 6/31 (19)

Controls: 1/26 (4)

Witschi et al. 

2004

A/J Male Average TSP concentrations of 

176 mg/m3 (high dose), 

120 mg/m3 (medium dose), 

99 mg/m3 (low dose) from 2R4F 

reference cigarette sidestream/

mainstream smoke mixture

6 hours/day, 

5 days/week for 

5 months/whole body

High: 18/22 (82)a

Medium: 23/25 (92)a

Low: 18/25 (72)a

Controls: 10/25 (40)

Hutt et al. 

2005

B6C3F1 Female Average daily TPM concentration of 

254 ± 27 mg/m3 from a 2R1 reference 

cigarette 

6 hours/day, 

5 days/week for 

30 months/whole body

148/330 (44.8)*

Controls: 31/326 (9.5) 

Rat                

Dalbey et al. 

1980

F-344 Female 10% smoke concentration from 

unfiltered experimental cigarettes 

(NCI code 16)

8 hours/day, 

5 days/week for 126 to 

128 weeks/nose only

 7/80 (9)a,b

Controls: 1/93 (1)

Mauderly et 

al. 2004

F-344 Female, 

male

Low dose (100 mg/m3 [6%]) and 

high dose (250 mg/m3 [14%]) from 

a 1R3 reference cigarette

6 hours/day, 

5 days/week for up to 

30 months/whole body

Female

 Low: 4/175 (2.3)

 High: 4/81 (4.9)a

 Controls: 0/119 (0)

Male

 Low: 1/178 (0.6)

 High: 5/82 (6.1)

 Controls: 3/118 (2.5)

Note: mg/m3 = milligrams per cubic meter; NCI = National Cancer Institute; TPM = total particulate matter; TSP = total suspended 

particulate. 

aSignificantly different (p <0.05) from controls.

bRespiratory tumors consisted of 8 in the lung (5 adenomas, 2 alveologenic carcinomas, 1 squamous carcinoma) and 2 nasal tumors 

(adenocarcinoma and squamous-cell carcinoma).

*p <0.001.
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 65

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

11-percent mainstream smoke from 1R4F reference cigarettes (Witschi et al. 2002). As reported in the previous 

studies (Witschi et al. 1997a,b), the investigators included 

a four-month recovery period to increase the development 

of lung tumors. In both strains, they observed increases 

in lung tumor multiplicities (average number of tumors 

per lung) (0.44 ± 0.13 and 0.35 ± 0.14, respectively) and 

lung tumor incidences (number of tumor-bearing mice 

per total number of treated mice) (33% in treated Balb/c 

mice versus 20% in controls and 19% of treated SWR mice 

versus 4% in controls, respectively) (Table 3.1) after exposure to cigarette smoke. Only the lung tumor multiplicity 

in treated SWR mice was statistically different from that 

in SWR controls exposed to air only. These investigators 

found that strain A/J mice were more susceptible to carcinogen-induced lung tumors than were Balb/c or SWR 

mice (Witschi et al. 2002). The same exposure regimen 

showed that in male strain A/J mice, the lung tumor multiplicity was significantly higher among the exposed mice 

than among the air-only controls, and there was a good 

correlation between exposure (average concentration of 

cigarette smoke multiplied by exposure duration) and 

lung tumor multiplicity (Witschi et al. 2002). Proliferative pulmonary lesions were categorized as focal alveolar 

epithelial hyperplasia, alveolobronchiolar adenomas, and 

alveolobronchiolar adenocarcinomas. Although it was 

possible to achieve a dose-related increase in lung tumor 

multiplicity in A/J mice with this exposure protocol, mice 

exposed to cigarette smoke had fewer adenomas with carcinomatous foci or adenocarcinomas (malignant tumors) 

than did air-only controls (Witschi et al. 2002).

In a later study, Witschi and colleagues (2004) used 

a similar exposure regimen with five months of wholebody exposure to smoke from 2R4F reference cigarettes 

(89-percent sidestream and 11-percent mainstream 

smoke), followed by a four-month recovery period. This 

regimen produced a significant increase in lung tumor 

multiplicity and tumor incidence compared with the 

air-only controls although the response to the high dose 

was slightly less than to the medium dose (Table 3.1) in 

male strain A/J mice. The authors attribute the flat doseresponse curve to the weak lung carcinogenicity of 

cigarette smoke in mice. The tumors were described as 

bronchioloalveolar adenomas.

Curtin and associates (2004b) studied effects of 

subchronic exposure to mainstream smoke from 1R4F 

reference cigarettes in male RasH2 transgenic mice, which 

carry the human C-HA-RAS oncogene, and A/J mice. 

Mice had whole-body exposure for 20 weeks or nose-only 

exposure for 28 weeks. Results indicated that whole-body 

exposure may be more effective than nose-only exposure 

for inducing statistically significant changes in tumor 

multiplicity and tumor incidence. One concentration of 

cigarette smoke was used in the whole-body experiments, 

and three concentrations were used in the nose-only 

experiments. Both exposure regimens included a 16-week 

recovery period. With whole-body exposure, microscopically confirmed tumor incidence and tumor multiplicity 

were significantly greater in the exposed animals than in 

the sham-exposed animals in both mouse strains.

Hutt and colleagues (2005) developed a model 

that achieved a 10-fold increase in hyperplastic lesions, 

a 4.6-fold increase in adenomas and papilloma, a 7.25-

fold increase in adenocarcinomas, and a 5-fold increase 

in metastatic pulmonary adenocarcinomas in mice with 

lifetime whole-body exposure to cigarette smoke compared with lesions in air-only sham controls. The B6C3F1

strain of mice used in this study have low background 

incidence of lung tumors compared with that for A/J mice 

used in other studies. The female mice were exposed to 

mainstream smoke from an unfiltered 2R1 reference cigarette for 30 months. An increase in lung hyperplasia and 

neoplasia was first seen in mice exposed to TPM that died 

spontaneously between 540 and 720 days after the initial 

exposure. At the end of the study, the survival of mice 

exposed to smoke was significantly longer than that of the 

sham-exposed controls possibly because of reduced food 

consumption leading to lower body weight and a lower 

incidence and delayed onset of other types of cancers. 

Animals exposed to TPM also had a statistically significant 

increase in incidence of benign and malignant proliferative lesions in the nasal cavity. In contrast to other studies 

using a mouse model, this study achieved a significantly 

greater incidence of adenocarcinomas in treated animals 

(67 of 330, 20.3 percent) than in sham-exposed controls (9 

of 326, 2.8 percent).

Rat. Female Fischer-344 (F-344) rats received daily 

nose-only exposure to the smoke of experimental cigarettes for 126 to 128 weeks (7 cigarettes per 8-hour day, 

5 days per week) (Dalbey et al. 1980). The mean delivery 

of smoke particulate from 85-mm unfiltered cigarettes 

(National Cancer Institute, code 16) was 18.4 mg per cigarette. The exposure chamber consisted of holding tubes 

attached to the side of a 350-mL chamber containing a 

mixture of cigarette smoke and room air. The two control 

groups consisted of unexposed and sham-exposed controls. Survival in the smoke-exposed rats was similar to 

that of the two control groups combined. Animals in the 

group exposed to smoke had significantly more tumors 

of the respiratory tract than did the combined control 

groups (Table 3.1). Compared with controls, rats exposed 

to cigarette smoke had significantly fewer tumors in the 

hypophysis, hematopoietic and lymphoid system, uterus, 

and ovary. The number of adrenal tumors and oral tumors 
Surgeon General’s Report

66 Chapter 3

in treated animals increased, but the changes did not 

reach statistical significance. Animals exposed to smoke 

also had a significant increase in dermal tumors (subcutaneous sarcomas) near ulcers on the front feet from pushing against the holding tubes during exposure compared 

with animals in the control groups.

In the same study of lifetime exposure, researchers 

observed nonneoplastic tumors throughout the respiratory tract of animals exposed to smoke (Dalbey et al. 1980). 

These lesions included hyperplastic and metaplastic areas 

in the epithelium of the upper airways (nasal turbinates, 

larynx, and trachea) and areas of the lung with focal alveolitis (accumulations of pigmented macrophages, alveolar epithelial hyperplasia, and alveolar fibrosis).Lesions 

in control animals were much smaller and less severe. 

Researchers observed fibrosis and thickening of arterioles 

in the papillary muscle of the heart. No other organ systems showed evidence of smoke-related pathology.

One study also used chronic whole-body exposure 

in an attempt to achieve higher lung doses of cigarette 

smoke in F-344 rats (Mauderly et al. 2004). Low (100 

mg TPM/cubic meter [m3]) and high (250 mg TPM/m3) 

concentrations of mainstream cigarette smoke were used 

for exposures up to 30 months. Cigarette smoke was produced from unfiltered 1R3 reference cigarettes machine 

puffed twice per minute using a 70-mL, two-second puff 

and then diluted with air cleaned by a high-efficiency 

particulate air filter. Exposure to cigarette smoke significantly increased the incidences of nonneoplastic and 

neoplastic, proliferative lung lesions in female rats. Trends 

with exposure for all neoplastic lung lesions were highly 

significant for female rats. No trend with exposure was 

significant for males. Time to first observation of hyperplastic lesions was shortened by exposure among female 

but not male rats. Both benign and malignant neoplasms 

were observed earlier in high-exposure female rats than 

in low-exposure female rats. Hyperplastic responses consisted primarily of focal alveolar epithelial hyperplasia. 

Benign neoplasms were bronchioloalveolar adenomas, 

and malignant neoplasms were bronchioloalveolar carcinomas. Mean absolute weights of lungs in male and female 

rats exposed to high concentrations of smoke were significantly greater than those in animals in the control groups. 

Nonproliferative changes more common in animals in 

high-exposure groups than in low-exposure groups were 

ciliated cuboidal cell metaplasia and squamous metaplasia 

in alveolar ducts. There was no consistent difference by 

sex in development of proliferative nasal lesions, and the 

incidence of nasal cavity neoplasms increased significantly 

in both male and female rats exposed to high concentrations of smoke. Most of the nasal cavity tumors were epithelial in origin, and the benign epithelial tumors were 

adenomas. Histologic changes in the nasal cavity, such 

as squamous metaplasia of transitional and respiratory 

epithelium, mucous cell metaplasia and hyperplasia, and 

inflammatory infiltrates, were more common or more 

severe in the rats exposed to high concentrations of smoke.

Carcinogenicity bioassays should be conducted for 

a major portion of the test animal’s lifetime. Short-term 

(subchronic) exposure studies are primarily performed to 

provide information on target organs of repeated exposure. 

Short-term, nose-only exposures to mainstream smoke 

produced treatment-related histopathologic changes in 

the respiratory tract and in clinical chemistry parameters 

in male and female Sprague-Dawley rats (Coggins et al. 

1989; Ayres et al. 2001; Terpstra et al. 2003). Animals 

exposed to cigarette smoke had significantly more chronic 

active inflammation, epithelial hyperplasia, atrophy of the 

olfactory epithelium, and squamous metaplasia of the nasal passages and larynx. Other histopathologic changes 

included increased counts of intra-alveolar brown-gold 

macrophages and bronchial goblet cells. There was a 

dose-dependent trend toward increased severity of the 

effects with increased exposure. Some of the effects such 

as laryngeal squamous metaplasia were not completely 

reversed during a recovery period. 

A U.S.-tobacco-blend cigarette containing the additive 1-menthol and other conventional processing aids and 

flavoring ingredients was compared with a reference cigarette comprised of a similar tobacco blend in a 13-week 

inhalation study of toxicity in male and female F-344 rats 

(Gaworski et al. 1997). Only one concentration of 1-menthol (5,000 ppm) was used. Three dose levels of cigarette 

smoke were tested for each cigarette. Both cigarette varieties produced similar dose-related histologic changes in 

the respiratory tract and increases in ratios of lung weight 

to body weight. The researchers noted that although 

lesions in the trachea and larynx related to cigarette smoke 

were similar in incidence, the degree of the response 

was slightly more severe in some groups of female rats 

exposed to mentholated cigarette smoke than it was in those 

exposed to nonmentholated cigarette smoke.

Theophilus and colleagues (2003a,b, 2004) performed several 13-week nose-only inhalation studies 

with Sprague-Dawley rats to evaluate the toxic effects 

of expanded materials derived from tobacco (Theophilus 2003a,b, 2004). The exposure regimen consisted of 

one hour of exposure per day, five days per week, for 13 

weeks, followed by a 13-week recovery period. Male and 

female rats were exposed to mainstream smoke from cigarettes constructed of 100-percent tobacco expanded with 

dry ice or Freon-11 (Theophilus et al. 2003b) or tobacco 

expanded with propane or Freon-11 (Theophilus et al. 

2003a). Animals exposed to cigarette smoke demonstrated 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 67

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

chronic active inflammation and epithelial hyperplasia of 

nasal tissues and ventral squamous metaplasia of the larynx that appeared to increase in severity with increasing 

doses. Treated animals also had significantly more nonpigmented macrophages and brown-gold macrophages 

and evidence of chronic active inflammation of the larynx 

than did air-only controls. Most of the histologic changes 

resolved after a 13-week recovery period (Theophilus et 

al. 2003a,b). A separate study was conducted to evaluate the toxic effects of different percentages of expanded 

shredded tobacco stems (Theophilus et al. 2004). Overall, 

exposure to mainstream smoke from cigarettes constructed of 9.25-percent, 18.5-percent, or 25-percent 

expanded shredded stems failed to produce signs of 

increased or decreased toxicity relative to the control 

cigarettes that did not contain expanded shredded stems. 

At the highest dose, animals in all the groups exposed to 

expanded shredded stems had significant increases in the 

severity of nonpigmented macrophages in left and apical 

regions of the lung compared with those in unexposed 

animals. Treatment groups with the medium (18.5 percent) and high (25 percent) content of expanded shredded stems also had a significant increase in the severity 

of nonpigmented macrophages and goblet cells in the 

right diaphragmatic region of the lung at the highest dose 

compared with animals treated with smoke from control 

cigarettes containing zero-percent expanded shredded 

stems. Theophilus and colleagues did not describe the 

composition or tobacco blend in the control cigarettes 

or in the cigarettes made with expanded shredded stems. 

They stated that the tobacco blend and cigarette configuration were comparable between test and control cigarettes and that the main difference was the percentage of 

expanded shredded stems in the test cigarettes.

Cardiovascular and Cerebrovascular 

Studies in Animals

Some animal models show promise for studying 

the development of cardiovascular disease induced by 

cigarette smoke. For example, researchers have proposed 

an elastase-perfusion mouse model for aortic aneurysms 

induced by cigarette smoke (Buckley et al. 2004). Another 

example is the cockerel as a model for arteriosclerosis 

(Penn et al. 1983, 1992, 1996; Penn and Snyder 1988). 

Cockerels are sensitive to the plaque-promoting effects of 

chemicals administered by inhalation or injection. Inhalation of mainstream cigarette smoke or the vapor phase 

smoke component, 1,3-butadiene, was shown to promote 

plaque development in cockerels, but CO or an injection 

of NNK or solubilized concentrated cigarette smoke condensate from an unventilated 2R1 reference cigarette did 

not promote plaque development in cockerels. At high 

doses, intramuscular injections of PAH compounds with 

different carcinogenic potencies also led to arteriosclerotic plaque formation. Sidestream smoke was more effective than mainstream smoke in stimulating aortic plaque 

development in the cockerel model. 

Investigators reported that tissue injury induced 

by oxidative stress, altered serum lipids, increased blood 

pressure, and endothelial damage were other possible 

factors in cardiovascular injury from cigarette smoking 

(Stratton et al. 2001). In another study, inhalation exposure to cigarette smoke produced evidence of oxidative 

stress in the hearts of Balb/c mice (Koul et al. 2003). After 

10 weeks of whole-body exposure for 60 minutes per day 

to the smoke from five commercial filter-tipped cigarettes, 

mice had significantly lower concentrations of glutathione 

and higher concentrations of lipid peroxides, glutathione 

peroxidase, glutathione reductase, and catalase than did 

unexposed mice. Serum triglycerides, total cholesterol, 

LDLc, and the ratio of total cholesterol to HDLc were also 

significantly higher, and HDL and the ratio of HDLc to 

LDLc were significantly lower in the group exposed to 

smoke. Concomitant administration of α-tocopherol prevented some of the smoke-induced changes.

In one study, whole-body exposure to smoke from 

a 2R1 reference cigarette three times per day for 30 days 

resulted in a significant increase in the formation of 

8-oxo-dG, a marker of oxidative damage, in the heart 

tissue of male Sprague-Dawley rats, compared with the 

concentration in unexposed controls (Park et al. 1998). 

Cigarettes were smoked for 15 to 20 minutes to a fixed 

butt length in a 500-mL flask with air pumped into the 

flask. The reduced glutathione content and the oxidative 

state of glutathione in heart tissue were not significantly 

different from those in controls. In another study, wholebody exposure to low concentrations of cigarette smoke 

resulted in impaired oxidative function in cardiac mitochondrial cells; increased intracellular, low-molecularweight iron that can play a role in redox reactions; and 

reduced α-tocopherol during cardiac ischemia and reperfusion in female Sprague-Dawley rats (van Jaarsveld et al. 

1992). These findings suggested a mechanism involving 

oxidant radicals. Twice a day for two months, smoke was 

introduced by inserting a lit cigarette into a hole in the 

exposure chamber and allowing smoke to be drawn into 

the chamber for 5 seconds, followed by room air for 55 

seconds. This procedure was repeated until the cigarette 

extinguished (approximately 10 minutes). Carboxyhemoglobin concentrations in rats exposed to smoke or air were 

not statistically different.

Scientists reported that hepatic uptake of chylomicrons was significantly lower in Sprague-Dawley rats 

with whole-body exposure to the smoke of two unfiltered, 
Surgeon General’s Report

68 Chapter 3

king-size, GPC-brand cigarettes (35 to 40 mL per puff, 

20 puffs per cigarette) than was uptake in sham-exposed 

controls (Pan et al. 1993). Animals were exposed to the 

smoke for 10 minutes, four times per day, for 10 days. 

In addition, more chylomicrons remained in the hearts 

of rats exposed to smoke than in the hearts of controls. 

Hepatic uptake and residence time in heart tissues also 

changed when chylomicrons were administered to unexposed animals that had been previously exposed to smoke. 

Smoke exposure increased the thiobarbituric acid reactive 

substance measurement in chylomicrons, a measure of 

lipid peroxidation. In a subsequent series of experiments, 

whole-body exposure to the smoke of two 2R1 reference 

cigarettes (35 to 40 mL per puff, 20 puffs per cigarette) 

for 10 minutes, six times per day, for 10 days, significantly 

increased postprandial serum triglyceride and chylomicron concentrations, decreased hepatic uptake of chylomicron remnants, and increased plasma postheparin 

lipoprotein lipase activity. Hepatic lipase activity was similar in rats exposed to smoke and controls (Pan et al. 1997). 

In another study, subchronic (14 or 90 days) but not acute 

(1 day) whole-body inhalation exposure to cigarette smoke 

resulted in significantly increased cholesterol, triglyceride, and phospholipid levels in the serum, hearts, aortas, and lungs of male Sprague-Dawley rats (Latha et al. 

1988). Changes in serum lipoproteins included decreases 

in HDLc, triglycerides, and phospholipids and increases 

in LDL and very-low-density lipoprotein cholesterol, triglycerides, and phospholipids. Other alterations in lipid 

metabolism included increased hydroxymethylglutarylCoA reductase activity, decreased lipoprotein lipase 

activity in heart tissue, and increased lipoprotein lipase in 

adipose tissue. 

Research in male hypercholesterolemic ApoE 

*-/*- mice suggested that five weeks of exposure to 

1R4F cigarette smoke led to an increase in oxidized LDL 

immunoglobulin M (IgM) and antiphosphorylcholine 

IgM antibodies and a decrease in oxidized LDL IgG and 

lymphotoxin-β messenger ribonucleic acid (mRNA) 

expression in the spleen (Tani et al. 2004). Both IgM 

changes were associated with an increase in thickness 

of arterial intima. Animals were acclimated to cigarette 

smoke produced by a vacuum pump until smoke from one 

cigarette per day was tolerated. Mice exposed to cigarette 

smoke had significantly higher serum carboxyhemoglobin 

concentrations than those of air-only controls.

Researchers examined the aortic endothelium from 

male Sprague-Dawley rats by scanning and transmission electron microscopy after inhalation exposure to the 

smoke of two medium-tar cigarettes (19 mg of tar and 

1.5 mg of nicotine) (Pittilo et al. 1982, 1990). Smokingmachine conditions were not provided in the description of study methods. Animals were anesthetized before 

exposure. The exposure was repeated 5 days per week during a 25-day period. Compared with sham-exposed controls, the rats exposed to smoke demonstrated marked 

morphologic evidence of endothelial damage that 

included increased blebs, microvillus-like projections, 

plasmalemmal vesicles, and Weibel-Palade bodies that 

store von Willebrand factor protein. No endothelial abnormalities were seen in rats that received nicotine by subcutaneous injections or by continuous subcutaneous pumps. 

These observations suggest that components of cigarette 

smoke other than nicotine are responsible for the endothelial cell changes associated with smoking. Researchers 

reported that male Sprague-Dawley rats with exposure 

to the smoke of five low-nicotine (1 mg) cigarettes for 

20 to 30 minutes per day for four to six weeks had significantly higher mean arterial blood pressure after bilateral occlusion of the common carotid artery than did the 

sham-exposed controls (Bennett and Richardson 1990). 

Additionally, the time required to reach a maximum mean 

arterial blood pressure after occlusion was significantly 

less in the animals exposed to cigarette smoke versus the 

sham-exposed controls. Only one smoke concentration 

was used in this study. Using anesthetized, mechanically 

ventilated rats as an in vivo model, researchers showed 

that cigarette smoke produced a biphasic change in the 

diameter of the cerebral arterioles and an increase in mean 

arterial blood pressure in rats (Iida et al. 1998). An initial 

vasoconstriction was seen in animals breathing the smoke 

but not in animals receiving an intravenous infusion of 

nicotine. These findings led researchers to conclude that 

a smoke constituent other than nicotine was responsible 

for the early vascular change. Thromboxane A2 was proposed as the agent responsible for the vasoconstriction. 

Others have determined that cigarette smoking, but not 

the use of transdermal nicotine or smokeless tobacco, 

increased concentrations of thromboxane A2 (Wennmalm 

et al. 1991; Benowitz et al. 1993).

Cardiovascular changes were observed in several 

studies of short-term and lifetime inhalation cigarette 

smoke exposure in rodents. Investigators studied male 

Wistar rats with whole-body exposure to the smoke of 

an unidentified commercial cigarette for 30 days. They 

observed a significant increase in left ventricular systolic 

diameter and a significant reduction in systolic shortening fraction and ejection fraction compared with those 

in unexposed controls (de Paiva et al. 2003). No change 

in heart rate or heart weight was seen under the exposure conditions of this study. Another study demonstrated a significant increase in heart weight in female, 

but not male, Sprague-Dawley rats with 13 weeks of daily 

nose-only inhalation exposure to the smoke of a customblended experimental cigarette smoked under FTC conditions (Coggins et al. 1989). Other investigators conducted 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 69

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

a 13-week inhalation study of male and female F-344 rats 

exposed to smoke of mentholated or nonmentholated cigarettes. Male rats exposed to medium or high doses and 

female rats exposed to high doses of smoke from mentholated cigarettes, machine smoked under FTC conditions, developed a significant increase in the ratio of heart 

weight to body weight (Gaworski et al. 1997). Male and 

female rats exposed to high doses of smoke from nonmentholated cigarettes also had a significant increase in cardiomegaly (high ratio of heart weight to body weight). The 

difference between treated and control animals was no 

longer significant after a six-week recovery period. Dalbey 

and colleagues (1980) observed fibrosis and thickening of 

arterioles in the heart papillary muscle of female F-344 

rats with daily nose-only inhalation exposure for 126 to 

128 weeks to smoke from unfiltered experimental cigarettes. No smoke-related pathologic changes to the large 

vessels were detected from the one concentration of smoke 

(10 percent) that was used.

Studies using dermal applications of smoke condensate or inhalation exposure to cigarette smoke demonstrated that chemicals in cigarette smoke underwent 

covalent binding to heart tissue DNA in laboratory animals 

(Randerath et al. 1986, 1988; Reddy and Randerath 1990; 

Brown et al. 1998; Gupta et al. 1999). Studies of cigarette 

smokers showed that the heart tissue contained more 

DNA adducts than that from nonsmokers or former smokers (Van Schooten et al. 1998). They also demonstrated a 

linear relationship between DNA adduct levels and daily 

cigarette smoking. Furthermore, higher DNA adduct 

levels were associated with a higher degree of coronary 

artery disease.

Respiratory Studies in Animals

Exposure to chemicals in cigarette smoke affects 

the function of the respiratory system in laboratory animals and humans. Notably, exposure to cigarette smoke 

affected airway mucociliary function (Shephard 1978; 

Wanner 1985; Finch et al. 1995). Another researcher 

demonstrated that exposure resulted in a dose-dependent 

inhibition of lung clearance and increased absorption of 

components of the inhaled smoke through the tracheobronchial airways, especially where particle deposition 

occurred and mucociliary clearance was less efficient, specifically at the ridges within bifurcations and in posterior 

sections of tubular airways (Martonen 1992). Studies have 

shown that the activity of xenobiotic metabolizing (cytochrome P-450) enzymes in human lung tissue is likely 

sufficient to cause in situ activation of pulmonary toxicants (Castell et al. 2005). Species differences in enzyme 

activities have led some to question the use of animal 

data to predict toxic effects in humans from chemicals 

requiring bioactivation to reactive metabolites (Castell et 

al. 2005). Short-term assays to evaluate the components 

of cigarette smoke that impair mucociliary function were 

described in the “Cytotoxicity” section earlier in 

this chapter.

Persistent pulmonary inflammation from repeated 

exposure to cigarette smoke may lead to more severe 

alterations in the structure and function of the lung 

(Stratton et al. 2001). For example, researchers concluded 

that emphysema in cigarette smokers reflects a low-level, 

chronic inflammatory process in the lower respiratory 

tract with an imbalance of protease and antiprotease 

activities leading to the degradation of connective tissue 

(Churg et al. 2002).

Syrian golden hamsters have been used extensively 

to study the pathogenesis of emphysema. They show a pattern of inflammatory airway response and impaired activity of antioxidants (superoxide dismutase and catalase)—a 

pattern similar to that in humans with repeated exposure to cigarette smoke (Hoidal and Niewoehner 1982; 

McCusker and Hoidal 1990). Rat strains were shown 

to be more resistant to the induction of emphysema by 

exposure to cigarette smoke, but susceptibility in mice 

was strain specific (Groneberg and Chung 2004). Research 

on emphysema induced by cigarette smoke in animals has 

not consistently demonstrated progression of the disease 

(March et al. 1999). In a comparative study of B6C3F1

mice and F-344 rats, the mouse strain displayed more 

morphometric changes (parenchymal air-space enlargement, volume density of alveolar air space, and loss of 

alveolar tissue) and significantly more neutrophils within 

inflammatory lesions in the lung. Morphometric differences in the mice at 13 months were greater than those at 

7 months. This finding suggests that in mice, emphysema 

induced by cigarette smoke may be progressive. Animals 

received a whole-body exposure to the smoke of 2R1 reference cigarettes that were machine smoked (two 70-mL 

puffs per minute) and diluted with filtered air to achieve 

a chamber concentration of 250 mg of TPM/m3. The 

exposure duration was six hours per day, five days per week. 

The investigators concluded that the type of inflammatory 

response may be a determining factor for differences in 

susceptibility to emphysema induction by cigarette smoke 

among test species. 

Animal models can readily be used to detect and 

quantitate the pulmonary inflammatory response to 

inhaled compounds or mixtures, and the literature in this 

area was reviewed (Stratton et al. 2001; IARC 2004). An 

analysis of bronchoalveolar lavage (BAL) fluid for cellular 

and biochemical indicators of inflammation allows quantitation of the pulmonary inflammatory response of rodents 

to inhaled cigarette smoke (Churg et al. 2002; Shapiro et 
Surgeon General’s Report

70 Chapter 3

al. 2003). The differential cell count and the functioning of 

cells obtained by the BAL technique can be used to classify 

the type of inflammatory response, and the biochemical 

content of the BAL fluid can be used to detect release of 

various cytokines and alterations in pulmonary surfactant 

(Stratton et al. 2001; Miller et al. 2002).

Response of inflammatory cells, cytokine profiles, 

enlargement of air space, and mechanical properties of 

the lung (elastance) differed among mouse strains after 

exposure to cigarette smoke (Guerassimov et al. 2004). In 

one study, emphysema-resistant (ICR) and emphysemasensitive (C57BL/6) mouse strains showed differences in 

BAL cytokine and chemokine responses following a noseonly inhalation exposure to 2R1 reference cigarette mainstream smoke (two-second, 35-mL puff, once per minute) 

for two hours per day for seven days (Obot et al. 2004). 

Test concentrations were achieved by diluting mainstream 

smoke with fresh, conditioned air. There was a significant 

dose response for chemokines and cytokines (KC, JE, 

MIP-1α, MIP-2, RANTES, interleukin (IL)-17, SDF-1β) 

that recruit or activate neutrophils and other cell types in 

ICR mice, and a significant dose-response change in thymus- and activation-regulated chemokines was noted in 

C57BL/6 mice. Other researchers found that in contrast 

to emphysema-resistant ICR mice, emphysema-sensitive 

mouse strains (DBA/2 and C57BL/6J) showed a decrease in 

BAL antioxidant capacity after acute whole-body exposure 

to smoke (five cigarettes in 20 minutes) from a commercial, Virginia-tobacco-type cigarette (Cavarra et al. 2001). 

The animals that had lifetime exposure to the smoke (three 

cigarettes per day for 90 minutes, five days per week, for 

seven months) had decreased lung elastin content and 

developed emphysema. In a study of male ICR mice 

exposed five days per week for two weeks to mainstream 

smoke from commercial, unfiltered, high-tar cigarettes 

(1-second puff of 20-mL volume at 10-second intervals and 

45 puffs per cigarette), the lungs showed evidence of senescence of alveolar epithelial cells (increased β-galactosidase 

activity, lipofuscin accumulation, and P21CIP1/WAF1/SDI1

protein in type II cells) (Tsuji et al. 2004). The researchers 

proposed that the senescence prohibited lung epithelial 

cells from proliferating and repopulating epithelial cells 

lost to apoptosis during emphysema. 

Bartalesi and associates (2005) also studied wholebody exposure to cigarette smoke from three commercial, 

filter-tipped, Virginia-tobacco cigarettes per day, five days 

per week, for up to 10 months. This exposure produced 

epithelial cell injury, loss of cilia in the airways, and a 

positive reaction for mouse neutrophil elastase. The findings suggested degradation of lung elastin in emphysemasensitive (C57BL/6J and DBA/2) mouse strains. The 

C57 strain of mice is moderately deficient in serum 

α1-proteinase. Overt emphysema in the C57 strain was 

characterized by disseminated foci of severe emphysema 

interspersed by normal parenchyma. In DBA/2 mice, 

the foci of emphysema were scattered in a network of 

uniformly dilated parenchyma. Other differences were 

a greater fibrotic reaction and faster development of 

emphysema in DBA/2 mice (three months versus six 

months in C57 mice), and more extensive goblet cell 

metaplasia and immunohistochemical reaction for IL-4, 

IL-13, and MUC5AC (a secreted mucin) in C57 mice.

Further research with genetically modified mice 

explored the role of α1-antitrypsin (AAT), elastases, and 

tumor necrosis factor-alpha (TNFα) in emphysema induced by cigarette smoke. In one study, mice deficient 

in AAT (C57BL/6J *pa/*pa [pallid]) developed diffuse, 

panlobular emphysema affecting the entire air space, 

and C57 mice with normal concentrations of AAT developed more localized centrilobular emphysema (Takubo 

et al. 2002). Other more evident changes in the pallid 

mice with low concentrations of AAT after daily subchronic exposure (six months) to 2R1 cigarette smoke 

were increased T-cell inflammation in the alveolar wall 

and a reduced ability of the lungs to distend under pressure (compliance). Other investigators studied mice 

deficient in NE*-/*- or MMP-12*-/*-. The animals failed 

to develop air-space enlargement after six months of 

exposure to cigarette smoke from an unfiltered reference 

cigarette (Hautamaki et al. 1997; Shapiro et al. 2003). 

The investigators concluded that neutrophil elastase is 

required for recruitment of neutrophils and macrophages 

and for activation of MMP, which solubilizes extracellular matrix proteins including elastin. Other investigators 

reported that mice deficient in MMP (MMP*-/*-) that had 

a single exposure to the whole smoke of four 2R1 reference 

cigarettes did not show the same early elevations in lavage 

neutrophils, desmosine, or hydroxyproline that are seen 

in mice with normal levels of MMP activity (MMP*+/*+) 

(Churg et al. 2002). In a later study, these investigators 

reported that the absence of TNFα receptors is protective 

against infiltration of inflammatory cells, breakdown of 

lung matrix, and air-space enlargement in mice lacking 

P55 and P75 TNFα receptors (TNFRKO mice) after exposure to whole smoke from four 2R1 reference cigarettes 

five days per week for six months (Churg et al. 2004).

Several studies have shown that subchronic and 

chronic exposure to cigarette smoke produced evidence of 

respiratory tract toxicity that leads to emphysema in rats. 

In one study, the total glutathione, reduced glutathione, 

and protein-bound glutathione content in lung tissue of 

Sprague-Dawley rats with whole-body exposure to smoke 

from 2R1 reference cigarettes for 30 days, three times 

per day, were significantly lower than those in unexposed 

controls (Park et al. 1998). Oxidized glutathione increased 

significantly in rats exposed to smoke. Smoke exposure 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 71

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

also produced a treatment-related increase in 8-oxo-dG 

DNA levels in the lungs. Cigarettes were smoked for 15 to 

20 minutes to a fixed butt length in a 500-mL flask with 

air pumped into the flask.

Researchers found increased lung IL-4 and MMP12 levels and decreased interferon-γ levels in Wistar rats 

after daily whole-body exposure to the smoke of 20 commercial unfiltered cigarettes six hours per day, five days 

per week, for three and one-half months (Xu et al. 2004). 

The changes were accompanied by pathologic evidence 

of emphysema in the form of inflammation, damage 

to airway epithelium and cilia, reduced mean alveolar 

number, air-space enlargement, and changes in pulmonary function.

Chronic nose-only exposure of female SpragueDawley rats to smoke from 2R1 reference cigarettes twice 

per day significantly reduced the disaturated phosphatidylcholine and surfactant protein levels in BAL fluid, but 

not in lung tissues, and significantly increased the albumin content of BAL fluid (Subramaniam et al. 1995). The 

researchers also observed increased surface compressibility and decreased respreading on expansion (respreadability index) of organic extracts of the BAL fluid from treated 

rats compared with those for room controls and shamtreated controls. Total levels of total lung phospholipids 

were not significantly different among the groups.

In selective reviews of the literature, Coggins (1998, 

2002) summarized other nonneoplastic histopathologic 

changes observed in animals exposed to cigarette smoke: 

	 •	 pulmonary fibrosis in C57 mice accompanied by

accumulation of lymphocytes and macrophages in 

the peribronchiolar and perivascular regions; 

	 •	 alveolar fibrosis, alveolitis, and bronchiolitis with

accumulation of macrophages in F-344 rats; 

	 •	 granulomas in alveolar spaces and adjacent interstitial areas of all lobes of the lung in F-344 rats; 

	 •	 perivascular or peribronchiolar accumulation of

lymphoreticular cells, fibrosis and cellular enlargement of peribronchiolar septa, hyperplasia of type II 

cells and septal fibrosis, and air-space enlargement 

in F-344 rats; 

	 •	 pulmonary edema, bronchial pneumonia, pulmonary fibrosis, emphysema, and cor pulmonale in 

beagle dogs that had tracheotomy; and 

	 •	 pleural thickening, alveolar fibrosis, and subpleural

inflammation in beagle dogs without tracheotomy.

Reproductive and Developmental Studies in 

Animals

Fertility and Conception

Animal studies have suggested altered gonadotropin 

release, decreased luteinizing hormone surge, inhibition 

of prolactin release, altered tubal motility, and motility 

and impairment of blastocyst formation and implantation 

as possible mechanisms of fertility impairment among 

smokers (Stratton et al. 2001). In one study, male and 

female Sprague-Dawley rats received nose-only exposure 

to the smoke of 1R4F reference cigarettes (two-second 

puff, one puff per minute, 35-mL puff) for two hours per 

day, seven days per week, for four weeks before and during mating for males, and for two weeks before mating, 

during mating, and through gestation day 20 for females 

(Carmines et al. 2003). The investigators observed a statistically significant decrease in weight of seminal vesicles 

for males exposed to a low concentration or a medium 

concentration of smoke. Weight gains during pregnancy 

and mean uterine weight were significantly reduced in 

the female rats exposed to a high concentration of smoke. 

Fertility and conception endpoints unaffected by exposure 

to smoke were sperm count, motility, and morphology in 

males and corpora lutea, resorptions, implantation sites, 

and mortality in females. In another study, three months 

of whole-body inhalation exposure to mainstream smoke 

for two hours a day from a commercial, filter-tipped, hightar cigarette mechanically smoked with a 50-mL syringe 

did not lead to a reduction in uterine weight or estrous 

cycle but did result in decreased estradiol concentration 

in rat uterine tissue compared with that in uterine tissues of sham-exposed control rats (Berstein et al 1999). 

The proliferation index and proportion of uterine tissue cells in S and G2/M phases were increased at three 

weeks of exposure for two hours per day. By three months, 

the differences in values from those of controls were no 

longer statistically different, but they were significantly 

lower than at three weeks, which the investigators attributed to a decline in the intensity of cell division.

In another study, Wistar rats received whole-body 

exposure to the smoke of a commercial cigarette from 

conception until parturition. Rats were exposed to cigarette smoke six hours per day, five days per week, for 11 

weeks: 6 weeks before mating, 2 weeks during mating, and 

3 weeks during pregnancy (Florek and Marszalek 1999). 

Three concentrations of cigarette smoke were monitored 

by CO concentration, and exposure was assessed by the 

determination of carboxyhemoglobin. Offspring were 

mated to produce two subsequent generations. The 
Surgeon General’s Report

72 Chapter 3

researchers observed an apparent dose-dependent reduction in the mating index, fertility index, and the number of pregnant rats, but no influence on the duration of 

pregnancy. This exposure regimen also resulted in a dosedependent decrease in the mean number of animals rearing pups on the 21st postnatal day (Florek et al. 1999). 

Researchers reported that the transport of preimplantation embryos through the oviduct was retarded in 

golden hamsters with nose-only exposure to mainstream 

or sidestream smoke of unfiltered 2R1 reference cigarettes 

(DiCarlantonio and Talbot 1999). Low, medium, and high 

doses were produced by generating smoke from two, four, 

or six cigarettes. They observed that doses used in the 

study produced serum concentrations of cotinine within 

the range of those in women actively or involuntarily 

exposed to cigarette smoke during pregnancy. Animals 

were exposed to cigarette smoke (one puff per minute, 

35-mL puff) 7 days per week, beginning 14 days before 

mating and continuing through day 3 of pregnancy. In 

females exposed to mainstream smoke, the increased percentage of embryos recovered from the oviducts on day 

three of pregnancy was dose dependent. The difference in 

these percentages for the hamsters in the medium- and 

high-dose groups and the control hamsters, who breathed 

only air, was statistically significant. The number of 

embryos retained in the oviducts of hamsters in all three 

groups exposed to sidestream smoke was significantly different from that for controls, but the researchers did not 

observe a dose-dependent pattern. The contraction rate of 

the oviductal muscle also decreased significantly during a 

single exposure to either mainstream or sidestream smoke 

and did not return to initial values during a 25-minute 

recovery period.

Researchers have evaluated the effects of individual components of cigarette smoke on reproduction 

in hamster oviducts in vitro. Many components act in a 

dose-response manner and inhibit oviduct function at 

concentrations found in cigarette smoke. Talbot and colleagues (1998) showed that cyanide concentrations in 

2R1 cigarette smoke were sufficient to inhibit the ciliary beat frequency and time needed for an oocyte cumulus complex to travel through the oviduct to the ostium 

(oocyte cumulus pickup rate) in golden hamsters. Other 

constituents of cigarette smoke (acrolein, formaldehyde, 

phenol, and acetaldehyde) produced these alterations at 

concentrations that were 3 to 50 times higher than the 

corresponding concentrations in the smoke of an experimental 2R1 reference cigarette that was machine smoked 

under a single set of conditions (two-second puff, one puff 

per minute, 40-mL puff). All chemicals acted in a dosedependent manner, and inhibition of the ciliary beat 

frequency for all except acrolein was at least partially 

reversible. The beat frequency of cilia treated with acrolein continued to decrease after the chemical was flushed 

out of the perfusion chamber. Tested individually, indole, 

5-methylindole, quinoline, isoquinoline, hydroquinone, 

and substituted phenols (compounds present in the mainstream smoke of cigarettes), at picomolar to micromolar 

concentrations, inhibited oviductal functioning (ciliary 

beat frequency, oocyte pickup rate, and the contraction 

rate of infundibular smooth muscle) of golden hamster 

oviduct explants. Substitution of an ethyl or methyl group 

greatly increased the potency of the phenolic derivatives 

over that of the parent compound (Riveles et al. 2005). 

A recent study compared follicle loss and markers of 

apoptosis in the ovaries of mice exposed to mainstream 

cigarette smoke or B[a]P (Tuttle et al. 2009). Female 

mice received a nose-only exposure to mainstream smoke 

for eight weeks at a level equal to a pack-a-day habit in 

humans. Compared with mice exposed only to air, smokeexposed mice had a significant reduction in the number 

of follicles. There was no increase in apoptotic follicles or 

other markers of cell death in response to cigarette smoke 

exposure. In vitro treatment of cultured ovaries with 

B[a]P did not increase apoptosis. The authors concluded 

that smoke exposure selectively reduced follicles in the 

primordial and transitional stages but that the loss was 

not due to apoptosis (Tuttle et al. 2009).

Fetal Effects

Researchers have demonstrated fetotoxicity from 

cigarette smoke exposure by reporting reduced fetal weight 

in rats and mice exposed during gestation. Reduced fetal 

weight is one of the most reproducible treatment-related 

effects. In utero exposure of fetal Sprague-Dawley rats to 

smoke from a king-size, filter-tipped, commercial cigarette on days 1 through 20 of gestation produced a significant reduction in fetal weight (Leichter 1989). For more 

than two hours, the adult female rats were exposed to the 

smoke of 10 lit cigarettes with the burning end of the cigarette placed inside a whole-body-exposure chamber. Litter 

size and placental weights were not different between rats 

exposed to smoke and pair-fed controls given the amount 

of food equal to that consumed by the smoke-exposed 

group. The increase in resorptions of implanted embryos 

in the group exposed to smoke was not significantly different from that in the controls. In a study of mainstream 

smoke from 1R4F cigarettes (two-second puff, one puff 

per minute, 35-mL puff), male Sprague-Dawley rats had 

nose-only exposure for four weeks before and during mating and female rats had nose-only exposure for two weeks 

before mating, during mating, and through gestation 

day 20 (Carmines et al. 2003). Researchers identified a 

significant decrease in mean fetal weight compared with 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 73

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

that of the sham-exposed controls. The number of live and 

dead fetuses was unaffected by smoke exposure. A series 

of experiments with smoke from research cigarettes that 

varied in levels of nicotine, condensate, and CO demonstrated that the weight and length of fetuses from SpragueDawley rats was dependent on the intensity and duration 

of smoke inhalation (Reznik and Marquard 1980). All cigarettes were machine smoked with one set of conditions 

(two-second puff, one puff per minute, 35-mL puff). The 

number of exposures per day, the duration of the exposure 

in days, the number of puffs per cigarette, and the volume 

of air used to dilute the smoke were varied to create different exposure groups. The mean fetal weight and length 

decreased with increasing smoke concentrations, and 

fetuses of rats exposed to cigarette smoke two, three, or 

four times a day had significant reductions in weights and 

lengths compared with the fetuses of rats exposed for one 

period per day. Growth retardation was more extensive 

when smoke exposure occurred during the second half of 

pregnancy, but the reduction was less severe in the fetuses 

of rats exposed during the entire pregnancy. These effects 

could not be attributed to the CO concentration in the 

smoke alone, because the effects were more pronounced 

with exposure to the whole smoke than with exposure to 

the gas phase. The number of resorbed fetuses was not 

influenced by smoke exposure.

In one study, mice with the autosomal recessive 

curly-tail gene received nose-only exposure to the mainstream smoke of a commercial low-tar or high-tar cigarette for 20 minutes, once a day from day zero to day eight 

of pregnancy (Seller et al. 1992). Both cigarette varieties 

were smoked under the same smoking-machine conditions (two-second, 35-mL puff). The scientists observed 

similar levels of increased embryonic loss and retardation in embryonic development. The decrease in the mean 

somite number in the treated animals compared with that 

in the sham-exposed mice was statistically significant. 

Longer exposures (day 0 through day 17 of pregnancy) to 

smoke from the low-tar cigarettes resulted in a fivefold 

increase in intrauterine embryonic deaths, and live 

embryos weighed significantly less than those from the 

sham-treated group. Differences between the groups 

exposed to smoke from the high- or low-tar cigarettes 

were evident when exposure (10 minutes, three times a 

day) was restricted to days six, seven, and eight of pregnancy. The scientists reported that differences between 

the high-tar and low-tar treatment groups disappeared 

when the dose of the smoke from the low-tar cigarettes 

was increased. Weight loss in the treated pregnant mice 

was statistically significant, and weight loss was not dose 

dependent. Findings indicated a dose-response trend in 

the various dosing regimens, and the effect on embryonic 

survival and growth rate from exposure to the smoke of six 

cigarettes was greater than that of two cigarettes.

Curly-tail and C57BL strain mice received nose-only 

exposure on days six, seven, and eight of pregnancy to 

the smoke of a commercial low-tar or high-tar cigarette 

(Bnait and Seller 1995). One set of smoking-machine conditions (two-second puff, one puff per minute, 35-mL puff) 

was used to generate smoke from the low-tar and hightar cigarettes, which was puffed over the noses of the test 

animals in individual chambers. Mice in both treatment 

groups were sacrificed on day nine. The embryos were 

removed, and embryonic cells from the fetal plate, surface ectoderm, pericardium, and heart were examined by 

scanning and transmission electron microscopy. In both 

strains, the morphology of the exterior of the neural cells, 

the surface ectoderm, the pericardium, and the heart were 

the same. Cells from embryos of females in the high-tar 

exposure group showed evidence of depressed metabolic 

activity, suggesting anoxic damage that persisted 20 hours 

after the exposure had ceased. In embryos from the lowtar group, changes were also present but were less marked 

than in embryos of mice in the high-tar group. No change 

occurred in the total cell number or in the number of dead 

cells or alteration in the mitotic index with either type of 

cigarette, but C57BL embryos of mice in the low-tar group 

had a significant reduction in the mitotic index compared 

with embryos of sham-treated controls.

Developmental Effects

Animal studies have suggested that even brief exposures from maternal smoking are detrimental to the very 

early embryo (Bassi et al. 1984; Collins et al. 1985; Lichtenbeld and Vidíc 1989; Moessinger 1989; Seller and Bnait 

1995). Prenatal exposure to cigarette smoke resulted in 

impaired growth and maturation of fetal lung, including reduced lung volume, lower internal surface area, 

fewer and larger alveoli, decreased lung interstitium and 

parenchymal elastic tissue, increased density of parenchymal interstitium, and apparent reduction in synthesis 

of surfactant.

Investigators in one study reported that a single fourhour, whole-body exposure to smoke from filter-tipped or 

unfiltered cigarettes (one puff per minute, 35-mL puff) 

and a single intranasal administration of cigarette smoke 

condensate induced DNA deletions in fetal C57BL/6J mice 

homozygous for the pink-eyed unstable mutation (Jalili 

et al. 1998). The phenotypic expression of the DNA deletions was development of dark spots on the gray fur of 

the offspring. Spotting frequency did not increase with 

an increase in smoke concentration. The investigators 

reported that chemicals in the particulate phase of 

cigarette smoke that are possibly responsible for the 
Surgeon General’s Report

74 Chapter 3

DNA deletions are B[a]P, cadmium, acetamide, aniline, 

o-toluidine, acrylonitrile, and catechol. (For a description 

of transplacental genotoxic effects in rodents, see the section on “Genotoxicity” earlier in this chapter.)

Developmental effects from exposure to cigarette 

smoke were further studied in the curly-tail mouse and 

in the C57BL strain, a strain not predisposed to neural 

tube defects (Seller and Bnait 1995). Mice received noseonly exposure to smoke from commercial low-tar or hightar cigarettes from day 0 through day 17. Six cigarettes 

were smoked during each exposure, using one set of 

smoking-machine conditions (two-second, 35-mL puff). 

Mice in both treatment groups were sacrificed on day 18, 

and the embryos were removed and examined for gross 

congenital malformations. Treated mice (low tar and high 

tar) showed significant reduction in number of ossification centers in seven regions compared with sham-treated 

controls. Changes were consistently more marked in the 

animals exposed to low tar, but the differences were not 

significantly different from those produced by exposure 

to smoke from the high-tar cigarettes. One rib abnormality occurred in the C57BL mice, but no major congenital malformations were observed. In the curly-tail mice, 

a modest increase in the frequency of open spina bifida 

and exencephaly was observed. The researchers proposed 

that although cigarette smoke is not a potent teratogen in 

mice, it may have minor effects in mice that are genetically predisposed to an abnormality.

In a study of pregnancy-related adverse health 

outcomes from exposure to cigarette smoke, fetuses of 

Sprague-Dawley rats were examined for abnormalities of 

the skull, extremities, and other parts of the body (Reznik 

and Marquard 1980). The exposure regimens varied in 

the number of exposures per day, in the period of exposure during gestation, and in smoke concentrations from 

research cigarettes with different yields of nicotine, condensate, and CO. All cigarettes were machine smoked with 

one set of smoking-machine conditions (two-second puff, 

one puff per minute, 35-mL puff). None of the regimens 

produced an increase in malformations. 

A study of developmental toxicity in the fetuses of 

male and female Sprague-Dawley rats exposed to cigarette 

smoke identified an incomplete supraoccipital ossification and unossified sternebrae significantly more often in 

smoke-exposed animals than in sham controls (Carmines 

et al. 2003). The number of skeletal variations was dose 

dependent. Fetal external and visceral variations in treated 

animals and controls were not significantly different. The 

exposure regimen consisted of nose-only inhalation for 

two hours per day, seven days per week, for four weeks 

before and during mating for males, and for two weeks 

before mating, during mating, and through gestation 

day 20 for females. Three concentrations of mainstream 

smoke were generated from 1R4F reference cigarettes 

(two-second puff, one puff per minute, 35-mL puff) by 

diluting the smoke with filtered, conditioned air. No deaths 

among male rats were associated with exposure to smoke. 

Occasional diarrhea, salivation, and red material around 

the eyes and nose were noted among male rats exposed 

to smoke and the sham controls. One female rat died of 

causes unrelated to exposure during the study. Females 

exposed to cigarette smoke also had diarrhea, salivation, 

and red material around eyes and nose. The decrease in 

maternal body weight during gestation days 0 through 

20, mean maternal body weight at termination, and mean 

uterine weight in the group exposed to high smoke concentration (600 mg TPM/m3) were statistically significant 

compared with those in sham-control female rats. 

In another study, two-day-old pups born to SpragueDawley rats with nose-only daily exposure to mainstream 

cigarette smoke from day 2 to day 22 of pregnancy had 

selective reductions in protein kinase C gamma and delta 

isoforms and neuronal nitric oxide synthase within the 

dorsocaudal brainstem, a region relevant to respiratory 

and other autonomic functions (Hasan et al. 2001). One 

concentration of cigarette smoke exposure (1,000 mL = 

10-mL puff × 10 puffs per cigarette × 10 cigarettes per day 

at hourly intervals) was used in this study.

Other Health Effects

Immune System

Habitual use of cigarettes results in repeated contact with thousands of chemicals. Researchers have shown 

that antigens in tobacco and cigarette smoke are capable 

of stimulating an immune response (Becker et al. 1976; 

Romanski and Broda 1977; Lehrer et al. 1978, 1980; Francus et al. 1988). Experimental data suggest that nicotine 

itself can affect the immune system, and at least one 

researcher has identified an allergic reaction to nicotine 

in a person exposed to cigarette smoke (Lee et al. 1998; 

McAllister-Sistilli et al. 1998). In addition to nicotine, other 

immunologically active chemicals are found in cigarette 

smoke, including the common additive menthol (Rappaport and Hoffman 1941; McGowan 1966; Becker et al. 

1976; Johnson et al. 1990; Mudzinski 1993; Li et al. 1997). 

Research into mechanisms underlying allergic sensitization induced by cigarette smoke suggests that exposure to 

cigarette smoke suppresses the normal tolerance to common inhaled allergenic matter (Moerloose et al. 2006). 

Exposure to ovalbumin, an inert antigen, and mainstream 

smoke from five unfiltered 2R4F reference cigarettes produced a significant increase in ovalbumin-specific IgE and 

airway inflammation rich in eosinophils and goblet cells 

in male Balb/c mice. In mice exposed to ovalbumin and 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

cigarette smoke, levels of cytokine IFN-γ and thymus and 

activation-regulated chemokine were significantly higher, 

as were the number of dendritic cells, which are specialized for antigen capture, migration, and T-cell stimulation; 

activated CD4-positive and CD8-positive T lymphocytes; 

and peribronchial infiltrates with eosinophils. Mice 

exposed only to cigarette smoke did not have increased 

serum IgE, increased total numbers of cells in BAL fluid, 

goblet cell hyperplasia in lung tissue, or increased levels of 

cytokines and chemokines in BAL fluid supernatant.

A body of evidence suggests that exposure to cigarette smoke produces changes in cellular and humoral 

immune function in humans and laboratory animals 

(Johnson et al. 1990). The immune and host defense systems are highly conserved across species; thus, organs and 

cells of the immune system in humans, mice, and rats are 

similar (Selgrade et al. 1995). However, the effect of cigarette smoke on the immune system depends on the species, the duration, and the level of exposure. Short-term, 

low-level exposures generally do not affect the immune 

system or may be stimulatory, whereas long-term exposures (six months or more) or high levels of exposure were 

found to be immunosuppressive (Thomas et al. 1974; Holt 

et al. 1978; Gregson and Prentice 1981; Sopori et al. 1985; 

Johnson et al. 1990). Smoking-related changes in the 

peripheral immune system in humans were observed 

(Stratton et al. 2001). These changes included high white 

blood cell counts; high counts of cytotoxic or suppressor T cells; low counts of inducer or helper T cells; slight 

suppression of T-lymphocyte activity; significantly lower 

activity of natural killer cells; low titers of circulating 

immunoglobulin, except for elevated titers of IgE; and 

increased susceptibility to infection. Researchers observed 

similar effects in animals. More recently, researchers 

reported decreased immune response and resistance to 

transplanted tumor cells in mice with prenatal exposure 

to cigarettes (Ng et al. 2006).

Animals exposed to cigarette smoke for extended 

periods were more susceptible to challenges with tumor 

cells and infectious agents than were unexposed animals 

(Johnson et al. 1990). Scientists studied male C57BL/6J 

mice with 26 weeks of exposure to the smoke of a kingsize, filter-tipped cigarette, with seven to eight minutes 

of exposure to the smoke of 30 cigarettes per day on five 

consecutive days per week and subcutaneous inoculation 

with tumor cells (Chalmer et al. 1975). Tumors in the 

mice had a significantly higher mean volume, which is a 

measure of tumor growth rate, than did unexposed controls. This group also had larger and significantly more 

lung metastases. Animals exposed for only 10 weeks had a 

significantly lower mean tumor volume than did control 

mice. In a study of female C57BL/6 mice, toxic effects to 

the cellular immune system induced by cigarette smoke 

resulted in decreased viral neutralization, which was 

reflected in significant decreases in levels of antibody to 

serum adenovirus and a decrease in activated CD4 T cells 

in the lung after adenovirus administration (Robbins et 

al. 2004). The subchronic daily regimen, which consisted 

of exposure to mainstream smoke from 1R1 or 1R3 reference cigarettes, also significantly reduced the number of 

dendritic cells in the lung. Exposure inhibited CD4 T-cell 

expansion and maximal activation and reduced numbers 

of activated CD4 and CD8 T cells in response to adenovirus 

administration. Animals exposed to smoke had percentages of lung macrophages, B cells, and CD4 and CD8 cells 

similar to those of controls without exposure to cigarette 

smoke. CD8 cytotoxic T lymphocytes are major effector 

cells involved in immunologically specific tumor destruction in vivo, and CD4 T cells are essential for controlling 

CD8 T-cell-dependent eradication of tumors (Shiku 2003). 

In another study, tumor cells were injected into 

offspring of female mice exposed to cigarette smoke and 

air-only controls (Ng et al. 2006). Litter size, but not body 

weight of offspring, was significantly reduced by prenatal 

exposure to cigarette smoke. Male offspring injected with 

tumor cells at 5 or 10 weeks of age and female offspring 

injected at 5 weeks had a significant increase in tumor 

incidence compared with that of offspring of mice exposed 

to air only. Tumors grew significantly faster in the male 

offspring with prenatal exposure to cigarette smoke. The 

scientists observed no treatment-related effect on time to 

tumor formation. Activity of cytotoxic T lymphocytes in 

male pups exposed to cigarette smoke was significantly 

reduced, but no effects on natural killer cell activity, 

cytokine levels, histology of lymphoid organs, or subpopulations of immune cells were observed. Scientists studied 

adult mice that were susceptible (A/J strain) or resistant 

(C3H strain) to lung tumors and were exposed to the 

tobacco carcinogen NNK (Razani-Boroujerdi and Sopori 

2007). The findings suggest that differences in immune 

response to chemical carcinogens predicted differences 

in tumor response to the carcinogens. In A/J mice, but 

not in C3H mice, intraperitoneal treatment with NNK 

suppressed anti–sheep red blood cell antibody plaqueforming cells; T-cell proliferation induced by concanavalin 

A; and the rise in intracellular calcium induced by anti–

CD3/CD28 antibody. NNK also stimulated a significantly 

higher expression of cyclooxygenase-2 and of α7 nicotinic 

acetylcholine receptors in the lungs of A/J mice than in 

the lungs of C3H mice. The NNK treatments administered 

in this study resulted in lung tumors in all A/J mice but 

not in C3H mice.

Subchronic (14 weeks) exposure to a 6-percent 

concentration of the smoke of filtered medium-tar 

 ́
Surgeon General’s Report

76 Chapter 3

cigarettes (two-second puff, one puff per minute, 35-mL 

puff) resulted in increased alveolar macrophage activity in 

Wistar rats (Gregson and Prentice 1981). The macrophage 

activity and the increase in levels of macrophage acid 

phosphatase were dose and time dependent. In a study 

of Sprague-Dawley rats, exposures of 21 or more weeks 

to the mainstream smoke of 2R1 reference cigarettes led 

to significant inhibition of antibody production in lymph 

node cells associated with the lung (Sopori et al. 1989). 

Longer exposures of 35 to 39 weeks significantly reduced 

the plaque-forming response of cells in other lymphoid 

tissues. The plaque-forming response of lymph node cells 

associated with the lung to a T-cell-independent antigen 

was markedly reduced compared with the response of cells 

from control rats. Proliferative responses of lymphoid tissue associated with the lung to T-cell mitogens were unaffected by this exposure, by the relative amounts of T and B 

cells in lymph node cells associated with the lung or in the 

spleen, or by macrophage function in the spleen.

In another study of the immunosuppressive effects 

of exposure to cigarette smoke in female F-344 rats, 

chronic, daily whole-body exposures of up to 30 months 

to mainstream smoke from 1R3 reference cigarettes (twosecond puff, two puffs per minute, 70-mL puff) reduced 

proliferation mediated by T-cell antigen and led to constitutive activation of enzymes involved in activation of 

the T-cell antigen receptor, tyrosine phosphorylase, and 

phospholipase C-γ1 (Kalra et al. 2000). At eight months, 

T-cell proliferation in the spleen was significantly reduced 

in response to anti–CD3 antibody, which directly binds 

the T-cell antigen receptor and causes T-cell proliferation in the absence of activation of CD28 on T cells. Other 

treatment-related evidence of altered antigen-mediated 

T-cell signaling were depleted calcium stores sensitive to 

inositol-1,4,5-triphosphate and decreased calcium mobilization in spleen cells after ligation of the T-cell antigen receptor.

Endocrine and Other Effects

Changes in blood glucose were noted in several 

rodent bioassays. Single but not repeated exposure to 

mainstream cigarette smoke produced a significant 

increase in blood glucose levels in anesthetized, mechanically ventilated Sprague-Dawley rats. The smoke was 

inspired through a tracheal cannula (Iida et al. 1998). 

In another study, subchronic nose-only inhalation exposure to the mainstream smoke of mentholated or nonmentholated cigarettes (two-second puff, one puff per 

minute, 35-mL puff) resulted in a significant decrease in 

blood glucose levels in a high-dose group of F-344 rats 

exposed to smoke from menthol cigarettes or nonmenthol cigarettes compared with unexposed control animals 

(Gaworski et al. 1997). Similarly, subchronic nose-only 

exposure to mainstream smoke from 1R4F reference cigarettes (one puff per minute, 35-mL puff) produced a significant decrease in glucose level in a high-dose group of 

male Sprague-Dawley rats and in the two groups of female 

rats with highest doses (Terpstra et al. 2003).

Andersson and colleagues (1985) studied acute, 

nose-only, intermittent exposure to smoke from one, 

two, or four unfiltered 1R1 reference cigarettes. This 

exposure resulted in dose-dependent increases in catecholamine utilization in the dopamine and noradrenaline 

nerve terminal systems in the hypothalamus of SpragueDawley male rats. Luteinizing hormone, prolactin, and 

thyroid-stimulating hormone were significantly lower in 

a dose-dependent manner in treated rats than in controls. 

Corticosterone was significantly increased in rats with the 

highest exposure. Follicle-stimulating hormone, adrenocorticotropic hormone (ACTH), and vasopressin were not 

affected by exposure to cigarette smoke. Treated animals 

received nose-only exposure, but controls were exposed 

only to air. 

In a subsequent study, these investigators reported 

that, in contrast, acute, nose-only continuous exposure of 

male Sprague-Dawley rats to the smoke of one, two, or 

four unfiltered 1R1 reference cigarettes produced smaller 

reductions in catecholamine levels and increases in catecholamine turnover and did not produce an increase in 

dopamine utilization in the median eminence (Andersson 

et al. 1987). The researchers proposed that intermittent 

exposure to cigarette smoke produced stronger euphoric 

and neuroendocrine-related effects than did continuous 

exposure to cigarette smoke. As with male rats, diestrus 

female Sprague-Dawley rats with intermittent 30 minutes 

of nose-only exposure to the smoke of one, two, or four 

unfiltered 1R1 reference cigarettes had decreased catecholamine levels and increased catecholamine utilization 

in hypothalamic and preoptic noradrenaline nerve terminal systems and decreased serum prolactin and luteinizing hormone (Andersson et al. 1985). The effects were 

dose and time dependent. In contrast to findings in male 

rats (Andersson et al. 1985), for female rats, exposure to 

cigarette smoke caused lower dopamine and noradrenaline levels in the median eminence and lower ACTH levels 

(Andersson et al. 1988). Exposure to cigarette smoke did 

not inhibit secretion of the thyroid-stimulating hormone 

in female rats as it did in male rats. Catecholamine levels 

were measured in male Sprague-Dawley rats for 48 hours, 

72 hours, or 7 days after an exposure regimen that consisted of a daily 2-hour exposure to the smoke of two 1R1 

unfiltered reference cigarettes for 10 days (Andersson et 

al. 1989). At 48 hours after exposure, significantly lower 

levels of serum corticosterone and serum prolactin were 

noted and were attributed to maintained activation in 
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 77

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

dopamine utilization. At 72 hours, serum prolactin levels 

were still significantly lower than those in controls. Brain 

regions of increased catecholamine utilization in rats 

exposed to cigarette smoke decreased with time and were 

absent by seven days after exposure. Levels of ACTH were 

not changed relative to those in controls exposed only 

to air. 

Jansson and colleagues (1992) found that age of 

onset of postnatal endocrine changes varied by the duration of exposure to cigarette smoke. Male Sprague-Dawley 

rats were exposed daily to the smoke of two 1R1 reference 

cigarettes, beginning on day 1 after birth and continuing 

for 5, 10, or 20 days. The rats were sacrificed 24 hours 

after the 10- or 20-day exposure. Rat pups had a significant 

increase in serum levels of luteinizing hormone compared 

with levels in control pups exposed only to air. Animals 

sacrificed seven months after the 20-day exposure had a 

significant increase in serum prolactin levels. Pups sacrificed 24 hours after a 20-day exposure had a significant 

increase in catecholamine utilization in the medial palisade zone of the median eminence and a substantial 

reduction in catecholamine utilization in the parvocellular and magnocellular parts of the paraventricular hypothalamic nucleus. Changes in catecholamine utilization 

were not seen in animals sacrificed seven months after the 

20-day exposure to cigarette smoke. Serum corticosterone 

levels and dopamine and norepinephrine utilization in 

the hypothalamus were not significantly different for rats 

exposed to smoke and controls.

Other researchers noted statistically significant 

increases in the weight of the adrenal gland relative to body 

weight in Sprague-Dawley rats after subchronic inhalation exposure to the smoke of 1R4F reference cigarettes 

(one puff per minute, 35-mL puff) (Terpstra et al. 2003). 

Compared with the sham controls, the weight of the left 

adrenal gland increased for males in the two groups with 

the highest doses, whereas females had an increase in 

the weight of the left and right adrenal glands in the two 

groups with the highest doses.

An inverse relationship exists between smoking and 

body weight in humans, and nicotine is believed to be 

the chemical mediator (Chen et al. 2005). Direct nicotine 

administration to humans or animals decreases body 

weight and caloric intake. Scientists designed a study to 

determine the effect of short-term exposure to cigarette 

smoke on appetite control in male Balb/c mice. Inhalation 

exposure to the smoke of three commercial cigarettes a 

day for four days led to a significant decrease in plasma 

concentrations of leptin, a hormone that signals satiety (Chen et al. 2005). Animals exposed to smoke had a 

decrease in mRNA expression of white adipose tissue 

UCP1 (a mitochondrial uncoupling protein involved in energy metabolism) and an increase in mRNA expression of 

brown adipsose tissue UCP3. Food intake and body weight 

were significantly decreased in the animals exposed to 

smoke compared with those in the sham controls, even 

though plasma concentrations of corticosterone were 

unchanged. Concentrations of hypothalamic neuropeptide 

Y, which stimulates feeding behavior, were not affected by 

the acute exposure regimen. Only one concentration of 

smoke was used in this study, and details on smokingmachine conditions were not provided. Other animal 

studies with longer durations of exposure to cigarette 

smoke also documented either weight loss or reduced 

weight gain in treated animals compared with those in 

unexposed controls (Ayres et al. 2001; Carmines et al. 

2003; Witschi et al. 2004).

Summary

This chapter discusses a wide variety of chemicals 

found in cigarette smoke. These chemicals extend across 

a broad spectrum of volatility, lipophilicity, and reactivity, and include compounds that are known or suspected 

to be carcinogenic, toxic, and addictive. Some of these 

compounds also promote the carcinogenicity, toxicity, or 

addictiveness of the other constituents of cigarette 

smoke. Despite uncertainties about which chemical constituents are responsible for specific adverse 

health outcomes, there is broad scientific agreement 

about which chemicals in conventional tobacco-burning cigarettes could be harmful to individuals’ health. 

Less is known about, and research is needed on, the 

potentially harmful chemicals in smoke from new and 

emerging cigarette technologies. Cigarette characteristics 

that influence either nicotine delivery to the smoker or 

smoke constituents that interact with nicotine deserve 

special consideration, because nicotine maintains the 

addiction and thereby leads to ongoing exposures of 

smokers to chemical compounds with known adverse 

health effects.

The levels of the chemical constituents in cigarette 

smoke are influenced by many different factors. The levels of the metals and nitrogen-containing compounds in 

the tobacco are highly influenced by the soil in which it 

is grown and the fertilizers used to promote growth of 
Surgeon General’s Report

78 Chapter 3

the plant. Many of the chemicals of direct concern vary 

with the different types of tobacco (e.g., bright, burley, or oriental) that are combined to produce a specific 

tobacco blend. Within a type of tobacco, the position of 

the leaf on the stalk can also influence the chemical levels in harvested tobacco leaves that will eventually affect 

the levels in smoke. The inclusion of reconstituted and 

expanded tobacco in cigarette fillers can also alter the 

chemistry of cigarette smoke. After the tobacco is harvested, the method of curing and the addition of humectants, sugars, and flavor-related compounds will change 

the chemical composition of the tobacco that goes into 

the cigarette. Different tobacco blends, filters, filter paper, 

additives, and design innovations employed in cigarette 

manufacturing have a profound influence on the levels of 

toxicants transferred from tobacco into the mainstream 

smoke with every single puff.

It is well documented that cigarettes are not smoked 

with the same puffing profile. The differences in smoking patterns, including the number of puffs, the puff volume, and whether the smoker blocks the ventilation holes 

greatly influence the delivery of smoke constituents to the 

smoker. An individual smoker consumes each cigarette 

differently, depending on the time of day, on individual 

stress levels, and on the time since the last nicotine use. 

The smoker will change the number of puffs taken, the 

depth of the puff, and the degree to which ventilation 

holes are blocked, depending on the individual circumstances occurring at that time. In addition, the rate of 

metabolism of the chemicals after they enter the smoker’s 

body, in addition to other enzymatic and genetic effects, 

can influence how long the chemical species of concern 

remains in the smoker’s system. It is broadly understood 

that there is not a single machine-smoking method that 

can be used to project the levels of chemical constituents 

that are found in the human body.

Validated biomarkers of exposure that correlate with 

dose (the number of cigarettes smoked per day) or that 

provide information on metabolic activation and detoxification have been reported in the literature. Additional 

research is needed to determine levels of reduction of 

these chemicals in cigarette smoke that would produce 

measurable decreases in the dose delivered to the smoker. 

Although some biomarkers (nicotine and its metabolites 

and the TSNAs) are specific to tobacco exposure, most 

are not specific to tobacco and are influenced by diet, 

occupation, or other environmental factors. Also, although 

biomarkers typically represent only recent exposures, the 

strongest determinant of risk for many diseases (e.g., lung 

cancer) caused by tobacco use is the duration of smoking (IARC 2004). Carcinogen adducts as biomarkers of 

biologically effective doses are the most direct measure 

of tobacco-induced damage at cancer sites in smokers. 

Surrogate measures such as DNA oxidative repair lesions 

in urine and thioether levels respond in a dose-related 

manner to exposure to cigarette smoke and reflect an 

ongoing state of oxidative stress in the body of a smoker. 

Biomarkers of potential harm exist for all major tobaccorelated diseases. The predictive value of these biomarkers 

is lessened by their nonspecific nature. 

In vitro assays using mammalian or bacterial cellular systems show that cigarette smoke is mutagenic and 

cytotoxic. Genetic damage to the cell and altered metabolic 

activities probably play a role in tobacco-related chronic 

diseases such as cancer and cardiovascular disease. Notably, oxidative DNA damage and markers of oxidative stress 

are represented by increased levels of oxidatively modified DNA bases in urine, white blood cells, and lung tissue and by oxidative damage to sperm DNA and seminal 

fluid; increased oxidation of cell membrane lipids (F2-

isoprostanes) in adult and cord blood; and decreased levels 

of reduced glutathione in lung cells and heart tissue. In 

addition, short-term mutagenicity and cytotoxicity assays 

have led to the identification of several potentially causative chemical agents in cigarette smoke (e.g., aromatic 

amines and heterocyclic amine protein pyrolysate products in the Salmonella mutagenicity assay and HCN and 

acrolein in cytotoxicity assays). Future in vitro research 

on mutagenicity and cytotoxicity will likely involve cigarette smoke produced under smoking-machine conditions 

that more closely mimic human smoking behavior, rather 

than one standard set of conditions such as the FTC or 

ISO methods.

Many smoking-related effects in humans can be 

reproduced in experimental animals. Some of the most 

promising animal models are those for emphysema and 

cardiovascular disease induced by cigarette smoke. In 

contrast, animals have not proven to be good models for 

the type of lung tumors induced by cigarette smoke in 

humans. In the absence of a widely accepted animal model 

for tobacco carcinogenesis, ample data show that cigarette smoke and its condensate are tumorigenic in several 

animal species and are mutagenic in a variety of systems. 

Current animal studies have attempted to demonstrate a 

dose-response relationship by using either the smoke or 

the condensate from one cigarette type diluted to produce several concentrations or the smoke or condensate 

from cigarettes from different yield categories. In either 

instance, researchers have used one set of smokingmachine conditions to produce the cigarette smoke or 

condensate. Standardized smoking-machine conditions 

such as the FTC or ISO methods are useful for comparisons 

between cigarettes but are less relevant to the exposure 

of human smokers. Future studies will likely incorporate 

alternative smoking-machine conditions required by some 

countries or designed to mimic human smoking patterns.
Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm 79

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

In general, an absence of human data requires 

researchers to use the results of experiments with laboratory animals and nonanimal systems to estimate human 

risk. The sum of several decades of laboratory research 

lends experimental support to the epidemiologic observations that cancer, respiratory disease, cardiovascular 

disease, and other adverse health outcomes are causally related to cigarette smoking. Although some topics 

were not a primary focus of this chapter, of note are the 

instances when sidestream smoke, frequently used as a 

surrogate for environmental tobacco smoke or secondhand smoke, proved to be more toxic than mainstream 

smoke, which is inhaled directly by the smoker—for 

example, in the neutral red cytotoxicity assay and in the 

development of aortic plaque in the cockerel. Many chemicals of concern to public health are present in higher concentrations in sidestream smoke, the main contributor to 

secondhand smoke exposure, than in mainstream smoke: 

1,3-butadiene, ammonia, aromatic amines, benzene, 

CO, isoprene, nicotine, nitrosamines, PAHs, pyridine, 

and toluene.

Perhaps the greatest utility of toxicity testing of 

cigarette smoke and condensate comes from the ability to 

explore mechanisms by which tobacco and the constituents of its smoke cause disease, to identify better biomarkers of potential disease risk for use in both clinical and 

population-based studies, and possibly to evaluate the 

relative contribution of cigarette components and design 

features (e.g., additives, tobacco blends, nontobacco components, and filter ventilations) to the inherent toxicity 

and addictiveness of the product.

The uncertainties in understanding all of the factors involved in the delivery and uptake of toxic, carcinogenic, and addictive chemicals in cigarette smoke and 

the mechanisms of toxicity induced by cigarette smoke 

should not impede efforts to lower the concentrations 

of these chemicals in cigarette smoke. There are ways to 

lower the concentrations of toxic constituents in cigarette 

smoke, although additional research is needed to determine the levels of reduction required for achievement of 

measurable and biologically relevant decreases in delivery of these constituents to the smoker. Such approaches 

include controls over tobacco growing and curing; the 

types of tobacco used in the filler, including the use of 

reconstituted tobacco; the use of additives such as menthol; and the design of the cigarette.

Conclusions

1. In spite of uncertainties concerning whether particular cigarette smoke constituents are responsible 

for specific adverse health outcomes, there is broad 

scientific agreement that several of the major classes 

of chemicals in the combustion emissions of burned 

tobacco are toxic and carcinogenic.

2. The design characteristics of cigarettes, including 

ventilation features, filters, and paper porosity, have 

a significant influence on the levels of toxic and carcinogenic chemicals in the inhaled smoke.

3. The different types of tobacco lamina (e.g., bright, 

burley, or oriental) that are combined to produce a 

specific tobacco blend have a significant influence on 

the levels of toxic and carcinogenic chemicals in the 

combustion emissions of burned tobacco.

4. There is no available cigarette machine-smoking 

method that can be used to accurately predict doses of 

the chemical constituents of tobacco smoke received 

when using tobacco products.

5. Tobacco-specific biomarkers (nicotine and its 

metabolites and the tobacco-specific nitrosamines) 

have been validated as quantitative measures of exposure to tobacco smoke among smokers of cigarettes 

of similar design who do not use other tobaccocontaining products.

6. Although biomarkers of potential harm exist for most 

tobacco-related diseases, many are not specific to 

tobacco and levels are also influenced by diet, occupation, or other lifestyle or environmental factors.
Surgeon General’s Report

80 Chapter 3

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103

Chapter 4

Nicotine Addiction: Past and Present

Introduction 105

Definition of Nicotine Addiction 105

Tobacco Constituents and Pharmacokinetics 111

Nicotine and Other Tobacco Constituents 111

Pharmacokinetics 113

Components of Nicotine Addiction 116

Physiological Mechanisms and Indicators: Nicotine Tolerance, Withdrawal, and Reinforcement 116

Chronic Tolerance 116

Withdrawal 117

Reinforcement 118

Learning and Conditioning 120

Nicotine and Secondary Reinforcement 120

Positive Reinforcement and Learning 121

Negative Reinforcement and Learning 122

Environmental Context 122

Summary and Future Directions 124

Pathophysiology of Nicotine Addiction 124

Nicotinic Acetylcholine Receptors 125

Neurosubstrates of Nicotine Reinforcement 125

Dopamine and Nicotinic Acetylcholine Receptors 126

Glutamate 126

γ-Aminobutyric Acid 128

Opioid, Endocannabinoid, and Serotonin Systems 129

Norepinephrine 130

Neurosubstrates of Nicotine Dependence and Withdrawal 131

Nicotine Withdrawal Syndrome in Rodents 131

Neurochemical Correlates of Nicotine Withdrawal 132

Receptors and Behavioral Signs of Nicotine Withdrawal 132

Molecular Mechanisms 133

Clinical Imaging Studies 134

Psychiatric Comorbidity 134

Antidepressant and Antipsychotic Drugs and Nicotine Withdrawal 134

Depression and Nicotine Dependence 135

Schizophrenia and Nicotine Dependence 135

Summary and Future Directions 136

Genetics 137

Heritability of Smoking Behavior 137

Smoking Initiation 137

Smoking Persistence and Nicotine Dependence 138
104

Molecular Genetic Research on Smoking Behavior 138

Linkage Studies 140

Candidate Gene Studies 141

Pharmacogenetic Approaches 145

Nicotine Replacement Therapy 145

Bupropion 154

Varenicline 154

Summary and Future Directions 155

Prevalence and Trajectory Toward Nicotine Dependence 156

Epidemiology of Adolescent Smoking 156

Measuring Nicotine Dependence in Adolescents 156

Prevalence of Symptoms and Diagnoses in Adolescence 157

Trajectories of Smoking from Adolescence to Adulthood 158

Determinants of Nicotine Addiction 160

Summary and Future Directions 161

Epidemiology of Tobacco Use and Nicotine Dependence in Adults 162

Prevalence of Cigarette Smoking and Nicotine Dependence 162

Prevalence by Dose, Duration, and Subpopulations 165

Nicotine Dependence and Psychiatric Comorbidity 167

Summary and Future Directions 169

Trajectory of Recovery or Relapse 170

Relapse: Definitions and Limitations of the Literature 170

Natural History of Relapse 170

Prevalence 170

Rapidity 171

Lapse-Relapse Relationship 171

Risk Factors 171

Person Factors 172

Emergent Processes 174

Situational Instigators 178

Integration Across Relapse Influences 179

Transition from Lapse to Relapse or Recovery 179

Summary and Future Directions 180

Evidence Summary 180

Conclusions 183

References 184
Nicotine Addiction: Past and Present 105

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Introduction

Nicotine addiction is the fundamental reason that 

individuals persist in using tobacco products, and this 

persistent tobacco use contributes to many diseases 

described in this report. The 1988 report, The Health 

Consequences of Smoking: Nicotine Addiction: A Report 

of the Surgeon General (U.S. Department of Health and 

Human Services [USDHHS] 1988, p. 9), describes the pharmacologic basis of tobacco addiction and arrives at three 

major conclusions:

1. Cigarettes and other forms of tobacco are addicting.

2. Nicotine is the drug in tobacco that causes addiction.

3. The pharmacologic and behavioral processes that 

determine tobacco addiction are similar to those 

that determine addiction to drugs such as heroin 

and cocaine.

Tobacco addiction remains a substantial problem in 

the United States and worldwide. Of those individuals who 

have ever tried smoking, about one-third become daily 

smokers (USDHHS 1994, p. 67). Of those smokers who 

try to quit, less than 5 percent are successful at any one 

time (Centers for Disease Control and Prevention [CDC] 

2002, 2004). Although not all smokers become nicotine 

dependent, the prevalence of individuals diagnosed as 

nicotine dependent is higher than that for any other substance abuse disorder (Anthony et al. 1994; CDC 1995b; 

Kandel et al. 1997). Any efforts to reduce tobacco-related 

disease must take into account the addiction potential of 

a tobacco product. 

Since the 1988 Surgeon General’s report was published, significant advances have been made in understanding the physiological effects of nicotine and the basis 

for addiction:

1. identifying specific genotypes and receptor subtypes 

that may contribute to and play an important role in 

nicotine addiction, 

2. observing sensitivities and responses to nicotine in 

adolescents that might make them more susceptible 

to nicotine addiction than adults are and recognizing the different trajectories for the development of 

nicotine dependence, 

3. developing a greater awareness of the important role 

of associative learning in addiction, 

4. recognizing the strong associations between smoking and comorbid psychiatric disorders, and 

5. achieving a better understanding of the relapse and 

recovery processes.

The goals of this chapter are to describe these 

advances and their implications and to discuss future 

directions. 

Definition of Nicotine Addiction

The crux of understanding the pathophysiology of 

tobacco addiction and its measurement relies on the identification of critical characteristics and the definition of 

addiction. This area continues to evolve, and significant 

gaps in research are evident. There is no established 

consensus on criteria for diagnosing nicotine addiction. 

However, researchers have identified several symptoms as 

indicators of addiction. The 1988 Surgeon General’s report 

lists the following general “criteria for drug dependence,” 

including nicotine dependence (USDHHS 1988, p. 7):

Primary Criteria 

•	 Highly controlled or compulsive use

•	 Psychoactive effects

•	 Drug-reinforced behavior

Additional Criteria

•	 Addictive behavior, often involves:

– stereotypic patterns of use

– use despite harmful effects

– relapse following abstinence

– recurrent drug cravings
Surgeon General’s Report

106 Chapter 4

•	 Dependence-producing drugs often produce:

– tolerance

– physical dependence

– pleasant (euphoriant) effects

These criteria are consistent with those for a diagnosis of dependence provided in the Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (DSM-IV) 

(American Psychiatric Association [APA] 2000) and the 

International Classification of Diseases, Tenth Revision

(ICD-10) (Table 4.1) (World Health Organization [WHO] 

1992). The diagnosis of dependence using these diagnostic systems depends on the person experiencing a specific 

number of these symptoms. The relevance of some of 

these symptoms to nicotine addiction may be questionable because the DSM criteria are used across different 

drugs of abuse. For example, one symptom of addiction 

is that a great deal of time is spent in activities necessary 

to obtain the substance or recover from its effect. This 

criterion may not be as relevant to the diagnosis of nicotine addiction compared with other abused substances. 

Another prominent instrument that researchers have 

used to determine the degree or severity of dependence in 

smokers is the Fagerström Tolerance Questionnaire (FTQ) 

(Fagerström 1978; Fagerström and Schneider 1989), and 

a later, modified version, the Fagerström Test for Nicotine 

Dependence (FTND) (Heatherton et al. 1991). The items 

on these scales, which describe the extent of nicotine 

exposure, the impaired control over use, and the urgency 

for use, are listed in Table 4.2. The first item, time to first 

cigarette after waking, is by itself a stronger predictor of 

relapse than is any other self-report measure of dependence (Baker et al. 2007). The 1988 Surgeon General’s 

report describes the general characteristics and criteria 

for drug dependence, DSM-IV and ICD-10 describe the criteria necessary for diagnosis of dependence, and the FTQ 

and FTND can be used to determine the degree of dependence. The core features across these diagnostic methods 

include (1) repeated and compulsive self-administration; 

(2) impaired control over use (e.g., repeated unsuccessful attempts to stop use or continued use despite known 

harmful consequences); (3) high motivation to seek the 

drug, because of cravings, regulation of affect (e.g., smoking to ease a depressed mood, for relaxation, or for stimulation), or other reasons associated with the psychoactive 

effects of the drug; (4) judgment of greater value from 

Table 4.1 Criteria for substance (nicotine) dependence

DSM-IV ICD-10

A maladaptive pattern of substance use, leading to clinically significant 

impairment or distress, as manifested by 3 or more of the following 

criteria, occurring at any time in the same 12-month period

  

•	 Tolerance—need increased amounts of substance to achieve desired

effect, or diminished effect with continued use of same amount

•	 Increased tolerance

•	 Withdrawal symptoms •	 Physical withdrawal at times

•	 Substance often taken in larger amounts or over longer period than

intended

•	 Strong desire to take drug

•	 Persistent desire or unsuccessful efforts to cut down or control

substance use

•	 Difficulty controlling use

•	 Great deal of time spent in activities necessary to obtain substance,

use substance, or recover from its effects

  

•	 Important social, occupational, or recreational activities given up or

reduced because of substance use

•	 Higher priority given to drug use than to other

activities and obligations 

•	 Substance use continued despite knowledge of having persistent

or recurrent physical or psychological problem likely to have been 

caused or exacerbated by substance

•	 Persistent use despite harmful consequences

Source: Adapted from Royal College of Physicians of London 2000 with permission from Royal College of Physicians, © 2000.

Note: DSM-IV = Diagnostic and Statistical Manual of Mental Disorders, 4th ed.; ICD-10 = International Classification of Diseases, 

Tenth Revision.
Nicotine Addiction: Past and Present 107

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Table 4.2 Questions, answers, and scoring for Fagerström Test for Nicotine Dependence and Fagerström 

Tolerance Questionnaire

Questions Answers Points

Fagerström Test for Nicotine Dependencea      

How soon after you wake up do you smoke your first cigarette? Within 5 minutes 3

How soon after you wake up do you smoke your first cigarette? 6–30 minutes 2

How soon after you wake up do you smoke your first cigarette? 31–60 minutes 1

How soon after you wake up do you smoke your first cigarette? After 60 minutes 0

Do you find it difficult to refrain from smoking in places where it is 

forbidden (e.g., in church, at the library, in the cinema, etc.)?

Yes 1

Do you find it difficult to refrain from smoking in places where it is forbidden (e.g., in church, at the library, in the cinema, etc.)? No 0

Which cigarette would you hate most to give up? The first one in the morning 1

Which cigarette would you hate most to give up? All others 0

How many cigarettes/day do you smoke? ≤10 0

How many cigarettes/day do you smoke? 11–20 1

How many cigarettes/day do you smoke? 21–30 2

How many cigarettes/day do you smoke? ≥31 3

Do you smoke more frequently during the first hours after waking up than 

during the rest of the day?

Yes 1

Do you smoke more frequently during the first hours after waking up than during the rest of the day? No 0

Do you smoke if you are so ill that you are in bed most of the day? Yes 1

Do you smoke if you are so ill that you are in bed most of the day? No 0

Fagerström Tolerance Questionnaireb      

How soon after you wake up do you smoke your first cigarette? Within 30 minutes 1

How soon after you wake up do you smoke your first cigarette? After 30 minutes 0

Do you find it difficult to refrain from smoking in places where it is 

forbidden (e.g., in church, at the library, in the cinema, etc.)?

Yes 1

Do you find it difficult to refrain from smoking in places where it is forbidden (e.g., in church, at the library, in the cinema, etc.)? No 0

Which cigarette would you hate to give up? The first one in the morning 1

Which cigarette would you hate to give up? Any other 0

How many cigarettes/day do you smoke? ≤15 0

How many cigarettes/day do you smoke? 16–25 1

How many cigarettes/day do you smoke? ≥26 2

Do you smoke more during the morning than during the rest of the day? Yes 1

Do you smoke more during the morning than during the rest of the day? No 0

Do you smoke if you are so ill that you are in bed most of the day? Yes 1

Do you smoke if you are so ill that you are in bed most of the day? No 0

What is the nicotine level of your usual brand of cigarette? ≤0.9 mg 0

What is the nicotine level of your usual brand of cigarette? 1.0–1.2 mg 1

What is the nicotine level of your usual brand of cigarette? ≥1.3 mg 2

Do you inhale? Never 0

Do you inhale? Sometimes 1

Do you inhale? Always 2

Note: mg = milligrams. aData are from Heatherton et al. 1991.

bData are from Fagerström and Schneider 1989.
Surgeon General’s Report

108 Chapter 4

use of the drug over other reinforcers or activities; and 

(5) manifestation of physical dependence, as evidenced by 

withdrawal or tolerance. 

Despite acknowledgment of these core features, the 

current diagnostic criteria for nicotine addiction have certain limitations. Beginning in 2005, a group of scientists 

have worked to delineate the various issues surrounding 

the measurement of nicotine dependence. The results of 

this work were published in June 2009 (National Cancer 

Institute [NCI] 2009). These issues included the following: 

1. whether nicotine addiction is categorical, dimensional, or emergent (changing over time) and, 

if emergent, whether different aspects of dependence are observed early or late in the process of 

dependence, for example, aspects more related to 

social, sensory, and associational learning versus a 

more physical dimension with a longer duration of 

drug use; 

2. whether nicotine addiction is unidimensional or 

multidimensional and, if multidimensional, whether 

symptoms or dimensions warrant weighting or are 

additive; 

3. whether a threshold of severity or a certain number 

or specific types of symptoms are needed for diagnosis of nicotine addiction; 

4. whether motivations or cognitive processes for 

seeking a drug are important components of the 

addiction;

5. whether multiple profiles, patterns, and pathways of 

addiction exist; and 

6. whether the quantity and frequency of use play a 

critical role in addiction.

Other current measures of nicotine addiction or 

tobacco dependence are shown in Table 4.3 that are 

beginning to consider and address some of the limitations of current definitions of addiction and that consider 

nicotine addiction to be comprised of more than one 

phenotype (expression of a trait on the basis of genetic and 

environmental influences). Developing valid measures 

of the various phenotypes of dependence is critical for 

research that (1) examines how these phenotypes are related 

to the trajectory and cessation of smoking behaviors and 

(2) determines whether these phenotypes are related to 

specific neurobiologic measures of addiction or to specific genes. 

In this chapter, the terms “dependence” and 

“addiction” have been used interchangeably. For some 

disciplines, dependence has been primarily associated 

with physiological manifestations of repeated tobacco use, 

but compulsive drug seeking is typically at the core of 

both the technical term “dependence” and the more general term “addiction.” Furthermore, the terms “nicotine 

dependence” and “tobacco dependence” are used interchangeably. Nicotine is the drug in tobacco that leads to 

compulsive drug seeking or addiction. However, several 

lines of epidemiologic and laboratory evidence presented 

in this chapter indicate that tobacco-delivered nicotine is 

substantially more addictive than are pure nicotine forms. 

Other tobacco constituents, delivery methods, and processes may play a critical supporting role. 

Factors contributing to nicotine or tobacco addiction include the following:

1. the effects of the product itself, including the addictive constituents, their pharmacokinetics and pharmacodynamics, and the design of the product that 

delivers the addictive constituents (see Chapter 3, 

“Chemistry and Toxicology of Cigarette Smoke and 

Biomarkers of Exposure and Harm”); 

2. the response of the host, including genetic susceptibility and physiological response; and 

3. the environmental setting that determines the 

availability of, accessibility to, and norms for use of 

the product. 

Like the 1988 Surgeon General’s report on nicotine 

addiction, this chapter focuses primarily on the effects of 

the product and the response of the host. 
Nicotine Addiction: Past and Present 109

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Table 4.3 Measures of nicotine addiction

Measures Characteristics

Fagerström Tolerance 

Questionnaire (FTQ) 

(Fagerström 1978; 

Fagerström and 

Schneider 1989)

Fagerström Test for 

Nicotine Dependence 

(FTND) (Heatherton et 

al. 1991)

Unidimensional and continuous scale that measures behavioral and physiological aspects of addiction 

(e.g., rate of smoking, morning smoking, and difficulty refraining from smoking) and was developed 

to measure physical dependence. Both FTQ and FTND show limited internal consistency (Pomerleau 

et al. 1990; Etter et al. 1999). FTND is a multidimensional scale (≤2 factors) summarized as single 

score (Haddock et al. 1999; Breteler et al. 2004). Adequate test-retest reliability, particularly with 

FTND (Pomerleau et al. 1994). Modestly correlates with levels of carbon monoxide, nicotine, and 

cotinine; weak predictor of withdrawal symptoms (Hughes and Hatsukami et al. 1986; Shiffman et 

al. 2004a; Etter et al. 2005); and modest or weak predictor of treatment outcome (Pinto et al. 1987; 

Silagy et al. 1994; Haddock et al. 1999; Etter et al. 2003a, 2005; Piper et al. 2006). Moderates efficacy 

of nicotine medications (Shiffman and Paton 1999). Does not have incremental value compared with 

measures of number of cigarettes/day (Razavi et al. 1999; Dale et al. 2001). A single item—time to first

cigarette—is a good predictor of cessation success and reflects a pattern of heavy, uninterrupted, and

automatic smoking (Transdisciplinary Tobacco Use Research Center et al. 2007).

FTQ was modified for adolescents (Prokhorov et al. 1996, 2000). One item was eliminated—brand

of cigarette or number of cigarettes per day—depending on study. Most items were changed to

4-point rating scales. One factor accounted for 41–53% of the variance. Interitem and item-to-total 

score correlations were weak to moderate. Internal consistency was adequate, with good test-retest 

reliability. Modest correlations were observed with amount smoked and between scales for individual 

items (except inhalation item) and cotinine levels.

Stanford Dependence Index is also modified FTQ with only 5 items that are assessed on a 4- to 

6-point scale. This measure was used in adults (Killen et al. 1990) and adolescents (Rojas et al. 1998). 

Adequate test-retest reliability was observed for both populations. In the adolescent population, 

total scores were significantly related to smoking rate, cotinine levels, and self-reported severity of 

withdrawal in past attempts to stop smoking.

Heaviness of Smoking 

Index (Heatherton et al. 

1989) 

Two items from FTQ: time to first cigarette of day and number of cigarettes/day.

Diagnostic and 

Statistical Manual of 

Mental Disorders, 4th ed. 

(DSM-IV) (APA 1994)

Categorical (nicotine dependent and not nicotine dependent) diagnostic resource that measures 

cognitive, behavioral, and physiological aspects of addiction. Criteria are consensus driven rather 

than theory driven and involve pattern of repeated drug use that results in withdrawal, tolerance, 

and compulsive drug taking despite negative consequences. DSM diagnosis is assessed by structured 

and semistructured interviews, such as Diagnostic Interview Schedule (DIS) (Robins et al. 1990) 

or Composite International Diagnostic Interview Substance Abuse Module (Robins et al. 1990). 

DIS results in 2-factor structure (Radzius et al. 2004). Diagnosis of dependence is also made by 

surveys, such as National Comorbidity Survey and National Survey on Drug Use & Health [formerly 

the National Household Survey on Drug Abuse], or by self-reported measures such as Tobacco 

Dependence Screener (TDS) (Kawakami et al. 1999). TDS has a continuous score and acceptable 

internal consistency. DSM-IV diagnoses assessed in epidemiologic surveys are associated with heavier 

smoking and predict persistence in smoking (Breslau et al. 2001). DSM-IV diagnosis is a stronger 

predictor of cessation than FTND, but weaker than number of cigarettes/day (Breslau and Johnson 

2000), and it is poorly correlated with FTND (Moolchan et al. 2002). TDS is associated with number 

of cigarettes/day, carbon monoxide levels, and duration of smoking (Kawakami et al. 1999; Piper 

et al. 2006). Limitation: dichotomous diagnostic classification does not capture dependence that 

varies in degree, assumes unidimensionality, and masks heterogeneity (e.g., diagnosis can be met by 

endorsement of any of several criteria).
Surgeon General’s Report

110 Chapter 4

Table 4.3 Continued

Measures Characteristics

Hooked on Nicotine 

Checklist (DiFranza et al. 

2002a)

Unidimensional, continuous, 10-item measure to stop smoking theoretically derived on the basis 

of theory of loss of autonomy. Items measure inability to stop smoking, difficulty refraining from 

smoking in prohibited places, craving and need for cigarette, and withdrawal and feeling addicted. 

One-factor solution explains 60% of variance. Strong internal reliability, moderate-to-strong testretest reliability of individual items and total score (O’Loughlin et al. 2002), and strong positive 

relationship to maximum frequency of smoking and maximum amount smoked. Weak correlation 

with duration of smoking. Significantly associated (those who endorsed at least 1 item on the scale) 

with failed attempt at smoking cessation, continued smoking until end of follow-up, and progression 

to daily smoking. High rate of symptom endorsement even in persons who ever used tobacco.

Cigarette Dependence 

Scale (CDS) (Etter et al. 

2003a, 2005)

Unidimensional, continuous measure and empirically derived scale (single-factor structure) that 

covers main criteria for DSM-IV and International Statistical Classification of Diseases and Related 

Health Problems, Tenth Revision. Definitions for dependence include compulsion, withdrawal 

symptoms, loss of control, time allocation (the amount of time spent smoking), neglect of other 

activities, and persistence despite harm, but exclude tolerance. This scale has 2 forms, CDS-12 and 

CDS-5, with 12 and 5 items, respectively. Both scales have high test-retest reliability and moderate-tostrong internal consistency. CDS-12 scores were higher in daily smokers than in occasional smokers 

and were associated with strength of urge to smoke on last attempt to stop smoking and saliva 

cotinine levels. Both CDS-12 and CDS-5 scores decreased with reduction in cigarette smoking, but 

neither scale predicted smoking abstinence at follow-up. In a subsequent study, higher CDS-12 scores 

predicted smoking abstinence at 1 month after cessation. Higher baseline CDS-12 scores weakly 

predicted higher withdrawal ratings at follow-up, with the exception of appetite. Performs better than 

FTND on many of these measures.

Wisconsin Inventory of 

Smoking Dependence 

Motives (WISDM) (Piper 

et al. 2006)

Multidimensional, 68 items with 13 theory-based subscales: (1) affiliative attachment (to smoking); 

(2) automaticity (smoking without awareness or intention); (3) behavioral choice/amelioration 

(smoking despite constraints or alternative reinforcers); (4) cognitive enhancement; (5) craving; 

(6) cue exposure/associative process (reflects basic learning process); (7) loss of control; (8) negative 

reinforcement; (9) positive reinforcement; (10) social/environmental goads (potency of social stimuli 

that model or invite smoking); (11) taste/sensory properties; (12) tolerance; and (13) weight control. 

Identifies motivational dependence process that influences dependence criteria. Some subscales are 

highly correlated, indicating overlapping dimensions. All scales except social/environmental goads 

were weakly to strongly correlated with FTND and moderately to strongly correlated with the TDS. 

Total WISDM score was moderately predictive of number of cigarettes/day and carbon monoxide level, 

with variability of strength of prediction for subscales. Total WISDM score did not significantly predict 

relapse, whereas combination of subscales was predictive (e.g., automaticity, behavioral choice/

amelioration, cognitive enhancement, and negative reinforcement).

Nicotine Dependence 

Syndrome Scale (NDSS) 

(Shiffman et al. 2004a; 

Shiffman and Sayette 

2005)

Multidimensional, theoretically derived scale with 5 subscales: drive (craving and withdrawal, 

withdrawal avoidance, and subjective compulsion to smoke), tolerance (reduced sensitivity to effects 

of smoking), continuity (regularity of smoking rate), stereotypy (rigid patterns of tobacco use), and 

priority (preference for smoking over other reinforcers). Continuous factor scores and single total 

score can be obtained. Most of the reliability and validity testing were not conducted on the final 19 

items that comprise this scale. Internal consistency of subscales is moderate to strong. Test-retest 

is modest to strong. In persons who did not stop smoking, NDSS scores modestly correlated with 

number of cigarettes smoked, difficulty in abstaining, and severity of past withdrawal symptoms. In 

treatment-seeking population, scales are modestly predictive of urges during smoking and during 

abstinence, acute withdrawal symptoms (except negative affect), and cessation outcome. Subscales 

show independent predictive usefulness (e.g., differential correlation with indices of dependence). 

NDSS strongly discriminates nonnicotine-dependent smokers who smoke a maximum of 5 cigarettes/

day (chippers) from regular smokers. Scales also discriminated levels of intake and dependence among 

chippers. Relationship between NDSS remained even when controlled for FTQ score.

Note: Description and results on scales are illustrative and not comprehensive.
Nicotine Addiction: Past and Present 111

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Tobacco Constituents and Pharmacokinetics

Nicotine and Other Tobacco 

Constituents

Tobacco products contain more than 4,000 chemicals, some of which could contribute to dependence. However, there is little debate that nicotine is a major tobacco 

component responsible for addiction (USDHHS 1988; 

Stolerman and Jarvis 1995; Royal College of Physicians 

of London 2000; Balfour 2004). Nicotine, 3-(1-methyl2-pyrrolidinyl)pyridine, is a volatile alkaloid (pKa = 8.5) 

with a molecular weight of 162.23. The absorption and 

renal excretion of nicotine are highly dependent on pH. At 

a high (alkaline) pH, nicotine is in the nonionized state, 

which is associated with the ability to more easily pass 

through lipoprotein membranes (Stratton et al. 2001). 

Nicotine can be rapidly absorbed in the lungs through 

cigarette smoking because of the large surface area of the 

alveoli and small airways and the dissolution of nicotine 

in pulmonary fluid, which has a physiological pH that 

facilitates absorption. Similarly, nicotine from oral products that have an alkaline pH can be readily but more 

gradually absorbed through the oral mucosa. In addition, nicotine can be well absorbed in the small intestine, 

because of its more alkaline pH and large surface area. 

However, nicotine is poorly absorbed from the stomach, 

because of its acidic environment resulting in greater ionized nicotine. Unlike when it is swallowed, nicotine’s bioavailability is greater through the lung or through the oral 

mucosa because nicotine reaches systemic circulation 

before passing through the liver (first-pass metabolism). 

Earlier studies that examined a wide range of animal 

species have shown that nicotine alone can lead to selfadministration in preference to an inert control substance

(Henningfield and Goldberg 1983; USDHHS 1988; Swedberg et al. 1990; Rose and Corrigall 1997; Royal College of 

Physicians of London 2000). Humans have also demonstrated a preference for nicotine over a control substance 

in studies examining intravenous administration (Henningfield and Goldberg 1983; Harvey et al. 2004), nasal 

administration (Perkins et al. 1996a), and use of medicinal 

gum (Hughes et al. 1990a). Furthermore, if levels of nicotine in the body are altered, smokers tend to compensate 

or titrate their dose by (1) smoking more if the levels of 

nicotine are reduced or blocked by a nicotinic receptor 

antagonist or (2) smoking less if exogenous nicotine or 

higher levels of nicotine are administered (USDHHS 1988; 

NCI 1996, 2001). Titration of the level of nicotine in the 

body during smoking involves adjusting smoking behaviors by changing the (1) number of puffs on a cigarette, 

(2) duration of the puffs, (3) interpuff intervals, and/or (4) 

number of cigarettes smoked (Griffiths et al. 1982). For example, researchers observed this compensatory smoking 

behavior in smokers who had either switched from cigarettes with a high machine-determined yield of nicotine 

to cigarettes with a low yield (Scherer 1999; NCI 2001) or 

reduced the number of cigarettes smoked (Fagerström 

and Hughes 2002; Hecht et al. 2004). The resulting levels 

of cotinine and other biochemical indicators of exposure 

to tobacco were proportionately lower than expected, considering the reduction in the nicotine yield of the cigarette 

or the number of cigarettes smoked. 

Researchers have observed that ingredients besides 

nicotine in tobacco or tobacco smoke (e.g., nornicotine 

and acetaldehyde) have either synergistic effects with nicotine or reinforcing effects of their own. Several pharmacologically active metabolites of nicotine were observed in 

the central nervous system (CNS) after acute administration of nicotine (Crooks and Dwoskin 1997). Nornicotine 

is both a metabolite of nicotine and a minor tobacco alkaloid. According to a review by Crooks and Dwoskin (1997), 

S(-)-nornicotine evokes concentration-dependent and 

calcium-ion (Ca2+)-dependent increases in endogenous 

release of dopamine from rat striatal slices and from 

mouse striatal synaptosomes. At low nornicotine concentrations, nicotinic receptor antagonists, such as mecamylamine and [3H]-dihydro-β-erythroidine (DHβE), inhibit 

dopamine release evoked by S(-)-nornicotine. At high 

nornicotine doses, this inhibition is not observed, thereby 

indicating that at high doses, nonselective mechanisms 

may be associated with the release of dopamine. In addition, S(-)-nornicotine, R(+)-nornicotine, and nicotine 

appear to activate the neural mechanisms responsible 

for behavioral sensitization. For example, administration of S(-)-nornicotine desensitized nicotine receptors, 

but at a potency 12-fold lower than that of nicotine. 

S(-)-nornicotine also showed cross-desensitization with 

nicotine; that is, receptors desensitized by nicotine were 

also desensitized by S(-)-nornicotine. This result suggests 

the involvement of common subtypes of nicotinic receptors (Dwoskin et al. 2001). 

Researchers have observed similar behavioral effects 

from nicotine and nornicotine. In one study examining 

acute or chronic (repeated) administration of S(-)-nicotine, R(+)-nornicotine, and S(-)-nornicotine on locomotor activity, the effects of both nornicotine enantiomers 

were qualitatively different from that of the S(-)-nicotine enantiomer after acute administration (Dwoskin 

et al. 1999a). Unlike S(-)-nicotine, neither nornicotine 
Surgeon General’s Report

112 Chapter 4

enantiomer produced hyperactivity following acute injection with the doses used in the study. However, long-term 

administration of a nornicotine enantiomer, specifically 

S(-)-nornicotine, showed patterns of effects similar to 

those of nicotine. Furthermore, long-term pretreatment 

with either nornicotine enantiomer produced crosssensitization to the locomotor stimulant effects after a 

nicotine challenge. 

Studies in rats show that (-)-nornicotine substitutes for (-)-nicotine in a drug-discrimination paradigm 

(Goldberg et al. 1989) and partially substitutes for (+)-

amphetamine as a discriminative stimulus, although it 

is less potent than (-)-nicotine (Bardo et al. 1997). In a 

study of self-administration by rats (Bardo et al. 1999), 

S(-)-nicotine and RS(±)-nornicotine produced a number 

of responses on a lever to obtain these drugs that was 

higher than the number on a lever to obtain an inactive or 

saline infusion used as a control. Furthermore, response 

decreased when saline was substituted for nornicotine, 

confirming that the animals were responding for nornicotine. Response increased when nornicotine was again 

available. In another study, pretreatment with (±)-nornicotine produced a dose-dependent decrease in nicotine 

self-administration (Green et al. 2000). 

These results indicate that nornicotine functions 

as a positive reinforcer but has less potency than that of 

nicotine. Researchers have speculated that this reduced 

effect may be attributable to (1) the longer half-life of nornicotine; (2) the use of RS(±)-nornicotine rather than the 

pure S(-)-nornicotine, which is considered more potent in 

evoking dopamine release in the brain; or (3) the reduced 

potency of nornicotine in the release of dopamine (Bardo 

et al. 1999). Because nornicotine is present only as a 

minor metabolite, it is unclear whether it would have any 

significant pharmacologic effect in smokers. 

Less data are available on cotinine, which is a major 

metabolite of nicotine (Benowitz and Jacob 1994). Studies 

suggest that cotinine is available in the CNS and stimulates nicotinic receptors to evoke the release of dopamine 

in a calcium-dependent manner from superfused rat striatal slices but that it is much less potent than nicotine or 

S(-)-nornicotine (Dwoskin et al. 1999b). (In superfusion, 

artificial central spinal fluid is poured over thin slices of 

brain tissue to maintain function and enable in vitro studies.) Other studies indicated that cotinine has a low affinity 

for nicotinic receptors (Abood et al. 1981, 1985) and may 

be associated with increased serotonin (5HT) levels (De 

Clercq and Truhaut 1963; Yamamoto and Domino 1965; 

Essman 1973; Rosencrans and Chance 1977; Fuxe et al. 

1979; Risner et al. 1985; Goldberg et al. 1989; Takada et al. 

1989; Erenmemisoglu and Tekol 1994). Studies in animals 

and humans have shown that cotinine is psychoactive and 

behaviorally active (Hatsukami et al. 1997, 1998a), but 

most studies showed this effect only with high cotinine 

doses. In human clinical studies, cotinine demonstrates 

effects opposite those of nicotine, indicating that cotinine 

may function as a nicotine antagonist (Keenan et al. 1994; 

Hatsukami et al. 1998a,b). 

Acetaldehyde, a constituent in tobacco smoke that 

results from burning sugars and other materials in the 

tobacco leaf, may play a role in increasing the reinforcing effects of nicotine (DeNoble and Mele 1983). In a later 

study, acetaldehyde enhanced the acquisition of nicotine 

self-administration among adolescent rats but not among 

adult rats (Belluzzi et al. 2005). The authors point out 

that adolescence may be a time of particular sensitivity 

to the effects of nicotine. This observation is supported by 

the fact that even a limited exposure to nicotine during 

adolescence may lead to symptoms of dependence (Kandel 

and Chen 2000; DiFranza et al. 2002b). In animals, nicotine treatment during adolescence leads to neurochemical 

changes in the brain that differ from those observed in 

adults (Adriani et al. 2002; Slotkin 2002). Furthermore, 

studies show an increased sensitivity to the rewarding 

effects of nicotine in adolescent compared with adult 

rodents (Adriani et al. 2002; Levin et al. 2003; Belluzzi et 

al. 2004). Further research is needed to understand the 

mechanism(s) by which acetaldehyde enhances the reinforcing effects and other effects of nicotine.

Fowler and colleagues (2003) point out that compared with nonsmokers and former smokers, current 

smokers had lower levels of MAOA, which preferentially 

oxidizes norepinephrine and serotonin, and of MAOB, 

which preferentially oxidizes phenethylamine. Both forms 

of MAO also oxidize dopamine, tyramine, and octopamine. 

Because former smokers showed normal MAO levels, the 

low levels in smokers appear to result from the pharmacologic effects of tobacco use, rather than from an inherent 

characteristic of smokers. Low levels of MAO may contribute to the reinforcing effects of tobacco use, because of 

the resulting higher levels of catecholamines. Nicotine 

does not appear to be responsible for this effect. Rather, 

the responsible constituents appear to be extracts (2,3,6-

dimethyl-benzoquinone and 2-naphthylamine) from fluecured tobacco leaves (Khalil et al. 2000; Hauptmann and 

Shih 2001). Animal studies with rats and mice have also 

shown that cigarette smoke and solutions of cigarette 

smoke (Yu and Boulton 1987; Carr and Basham 1991), as 

well as cigarette tobacco extract (Yu and Boulton 1987), 

inhibit MAO activity in the brain. The MAO inhibition in 

smokers is partial, with reductions at about 30 and 40 

percent for MAOA and MAOB, respectively (Fowler et al. 

2003). The reduction in MAOB levels does not appear to be 

rapidly reversible, as demonstrated by a study that showed 

no difference in MAOB levels when smokers were scanned 

by positron emission tomography (PET) at 10 minutes or 
Nicotine Addiction: Past and Present 113

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

11 hours after smoking a cigarette (Fowler et al. 2000). 

One study found that the intensity of the withdrawal 

symptoms was inversely related to platelet MAO activity (Rose et al. 2001a); that is, smokers with low platelet 

activity at baseline experienced the most severe withdrawal symptoms. 

In summary, nicotine is the most potent constituent associated with the reinforcing effects of tobacco. 

However, researchers have identified other constituents 

in tobacco and tobacco smoke that may be reinforcing or facilitate reinforcing effects of tobacco. Nicotine 

metabolites have also been identified as potential reinforcers or enhancers of the reinforcing effects of nicotine. 

Researchers have observed that in addition to nicotine and 

other constituents of tobacco and tobacco smoke, sensory 

aspects of nicotine and environmental stimuli also have a 

significant role in maintaining smoking behavior (Rose et 

al. 1993; Shahan et al. 1999; Caggiula et al. 2001, 2002b; 

Perkins et al. 2001d) (for details, see “Learning and Conditioning” later in this chapter).

Pharmacokinetics

Nicotine addiction depends on the amount of nicotine delivered and the way in which it is delivered, which 

can either enhance or reduce its potential for abuse: the 

faster the delivery, rate of absorption, and attainment of 

high concentrations of nicotine, the greater is the potential for addiction (Henningfield and Keenan 1993; deWit 

and Zacny 1995; Stitzer and de Wit 1998). 

Nicotine can be readily absorbed in the lung, oral 

mucosa, and nose, and through the skin. Table 4.4 shows 

(1) the bioavailability and amount of nicotine absorbed 

per unit dose of products containing nicotine and (2) the 

time to reach maximum blood concentrations of nicotine 

(Tmax). Figure 4.1 shows the concentrations of nicotine 

in venous blood and the peak concentrations across the 

products containing nicotine. The mean peak concentrations of nicotine are higher with use of tobacco products 

than with use of nicotine replacement products, and cigarette smoking produced both the highest peak concentration and most rapid rate of nicotine absorption. Venous 

concentrations of nicotine from smoking are lower than 

arterial concentrations. Ratios of arterial concentrations 

to venous concentrations ranged from 2.3 to 10 across 

studies (Henningfield et al. 1993; Gourlay and Benowitz 

1997; Rose et al. 1999). What accounts for the variability in arterial to venous nicotine concentration ratios 

observed across studies is unclear but may be a function 

of the study procedures and cigarette brands that were 

tested. In one study, lower-than-expected arterial nicotine 

concentrations were observed. The low concentration was 

attributed to the distribution of nicotine into the lungs 

and the slow release of nicotine into arterial circulation 

(Rose et al. 1999). The greater reinforcing efficacy of 

rapid delivery of nicotine was therefore thought to be due 

to both direct effects on the CNS and to stimulation of 

nicotinic receptors in the lung. These results would also 

suggest that neuronal nicotinic receptors associated with 

reinforcing effects of nicotine may be sensitive to low concentrations of nicotine. Clearly, more studies are needed 

to resolve the issues related to arterial concentrations of 

nicotine and consequent physiological effects. 

Oral use of smokeless tobacco products results in 

high venous concentrations of nicotine equal to those for 

use of cigarettes. Although the Tmax for delivery of nicotine in nasal spray appears to be less (faster) than that for 

Table 4.4 Bioavailability and amount of nicotine absorbed per unit dose and time to maximum venous blood 

concentration of nicotine by product

Product Bioavailability per dose Time to maximum concentration

Cigarette 1–2 mg Within 5 minutes

Nicotine gum (2 mg, 4 mg) 1 mg, 2 mg 30 minutes

Nicotine inhaler 2 mg/cartridge 20–30 minutes

Nicotine nasal spray 0.5 mg 10 minutes

Nicotine patch 15–22 mg (during 16–24 hours) 4–9 hours

Smokeless tobacco 3.6–4.5 mg 20–30 minutes

Source: Data are from Benowitz 1988; Fant et al. 1999a; Fagerström 2000; Medical Economics Company 2000. Table is adapted from 

Stratton et al. 2001 with permission from the National Academies Press, © 2001, National Academy of Sciences.

Note: mg = milligrams.
Surgeon General’s Report

114 Chapter 4

Figure 4.1 Venous blood concentrations of nicotine over time for various nicotine delivery systems

Source: Adapted from Fant et al. 1999b with permission from Elsevier, © 1999.

Note: mg = milligrams; ng/mL = nanograms per milliliter; data table for above data found at 

end of chapter.

smokeless tobacco products, the addiction potential may 

be higher for smokeless tobacco than for nicotine nasal 

spray, because the rate of nicotine absorption for smokeless tobacco is faster. Within 10 minutes after administration of a smokeless tobacco product, a nicotine boost 

of 10 nanograms per milliliter can be achieved (Holm et 

al. 1992) compared with two to three times longer after 

administration of nasal spray. However, the rise of arterial 

concentrations from nicotine nasal spray compared with 

smokeless tobacco is unknown. A further complication 

is that the rate and amount of nicotine absorption vary 

across smokeless tobacco products (Figure 4.2). This variability results from the processing and pH of the smokeless tobacco product. Cigarettes also vary in nicotine 

content. The tobacco plant, the curing process, and the 

additives can determine the pH of the tobacco and tobacco 

smoke (see Chapter 3, “Chemistry and Toxicology of Cigarette Smoke and Biomarkers of Exposure and Harm”). 

Nonetheless, although the pharmacokinetics of 

some smokeless tobacco products may overlap with those 

of medicinal nicotine products, medicinal products tend 

to have a slower rate and a lower amount of nicotine 

absorption than do the most popular brands of conventional smokeless tobacco products (Kotlyar et al. 2007). 

Among the medicinal nicotine products, nicotine nasal 

spray has the fastest rate of nicotine absorption, followed 

by nicotine gum, the nicotine lozenge, and the nicotine patch. 

Together, these results demonstrate that the nicotine pharmacokinetics associated with cigarette smoking 

is likely to lead to high potential for addiction, whereas 

medicinal nicotine products have relatively minimal 

potential for addiction. For example, the extent of liking, 

and therefore the addiction potential for these products, 

are related to the speed of nicotine delivery (Henningfield 

and Keenan 1993). Nicotine delivered through cigarette 

smoking and intravenously shows the greatest dose-related liking for the drug, and nicotine delivered transdermally is associated with the least liking (Henningfield and 

Keenan 1993; Stratton et al. 2001). 

The pharmacokinetic profile of a drug can determine 

the user’s pattern of drug delivery. Cigarette smoking 

results in rapidly rising arterial concentrations of nicotine 

that reach the brain in about 10 to 19 seconds (Benowitz 
Nicotine Addiction: Past and Present 115

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Figure 4.2 Mean plasma nicotine concentrations after administration of each of four smokeless tobacco products 

or mint snuff

Source: Adapted from Fant et al. 1999a with permission from BMJ Publishing Group Ltd., © 1999. 

Note: ng/mL = nanograms per milliliter; data table for above data found at end of chapter.

1990). The peak levels decline quickly as nicotine is taken 

up by peripheral tissues, followed by an elimination of 

nicotine from the body (Benowitz et al. 1988). This profile 

enables the smoker to finely control the nicotine dose to 

obtain the desired effect and enables frequent doses. These 

characteristics facilitate the addiction potential of cigarettes (Benowitz 1999). In contrast, oral nicotine products 

such as smokeless tobacco result in a more gradual rate 

of nicotine absorption and the nicotine levels are more 

sustained, resulting in a reduced ability of the smoker to 

manipulate the nicotine dose and less frequent dosing. 

The nicotine patch is the extreme example of slow absorption and once-a-day dosing, which results in a minimal 

potential for addiction.

Nicotine metabolism may also play a role in the reinforcing effects of nicotine. Researchers have hypothesized 

that the rate of nicotine metabolism should be related to 

smoking behaviors and that faster elimination of nicotine is associated with increased smoking and nicotine 

dependence (Benowitz 1999). Although surprisingly few 

published studies have tested this hypothesis, the research 

evidence has given some support to it (see “Genetics” later 

in this chapter). However, the evidence is modest. The rate 

of nicotine metabolism accounts for less than 16 percent 

of variation in the number of cigarettes smoked per day 

(Benowitz et al. 2003; Johnstone et al. 2006), and there is 

no significant variance in the FTND (Benowitz et al. 2003; 

Johnstone et al. 2006; Kandel et al. 2007) or in scoring 

on the Horn-Russell Scale (Johnstone et al. 2006). Kandel and colleagues (2007) found no significant association 

between the rate of metabolism and the number of cigarettes per day or nicotine dependence as measured by 

the FTND in a sample of young (18 through 26 years of 

age), less dependent, light smokers (average of 12 cigarettes per day). Possible reasons for the apparent disconnect between rate of metabolism and nicotine dependence 

include the following: (1) The questionnaire measures of 

adult nicotine dependence used may not be the most sensitive measures of the rate of metabolism (Benowitz et al. 

2003; Johnstone et al. 2006). (2) The rate of metabolism 

may be related to nicotine dependence only during the 

transition from experimentation to “addicted” smoking 

(Benowitz et al. 2003). (3) The rate of metabolism is not 

an important determinant of smoking behavior in young 

smokers because of a low level of smoking (Kandel et 

al. 2007).

One of the reasons metabolism per se may not be 

directly related to measures of nicotine dependence is 

that the pharmacokinetics of nicotine metabolism are one 

step removed from the pharmacodynamics of nicotine, 

that is, from the impact (1) on neurotransmitters in the 

reward pathway, (2) on central effects, as measured by 

electroencephalography and cerebral blood flow, and (3) 

on peripheral effects such as cardiovascular responses. 

Both central and peripheral effects contribute to subjective reactions to nicotine and the subsequent likelihood 
Surgeon General’s Report

116 Chapter 4

of continued smoking. (For discussion of the pharmacodynamics of nicotine in the brain, see “Pathophysiology of 

Nicotine Addiction” later in this chapter.)

The factors contributing to the high addiction 

potential of tobacco products are undoubtedly multiple 

and have complex interrelationships, making it a challenge to parse their relative contributions. In addition, 

smoking results in rapid delivery of nicotine by cigarette 

smoke and in exposure to chemicals other than nicotine 

that have central and sensory effects, including taste and 

draw resistance, as well as stimuli associated with smoking (Scherer 1999; Caggiula et al. 2002a; Rose 2006). 

Relatively few studies have been conducted outside the 

tobacco industry to determine how features of the cigarette are engineered to increase its addictive potential. 

However, tobacco industry documents suggest that more 

than nicotine dosing and pharmacokinetics are important 

in determining the overall addiction potential of modern 

cigarettes (Slade et al. 1995; Hurt and Robertson 1998; 

Wayne et al. 2004). (For description of design features that 

can enhance nicotine delivery and absorption rate, see 

Chapter 3, “Chemistry and Toxicology of Cigarette Smoke 

and Biomarkers of Exposure and Harm.”) 

Components of Nicotine Addiction

What are the effects of nicotine, and how does 

it cause addiction? The factors that may contribute to 

addictive behaviors include (1) neuroadaptations that 

occur with the persistent use of nicotine (e.g., tolerance), 

(2) withdrawal symptoms experienced when intake of 

the drug is stopped, and (3) the effects of nicotine that 

reinforce dependence. The primary reinforcing effects 

can entail the rewarding (psychoactive or psychostimulant) effects of nicotine (positive reinforcement) and/or 

the alleviation of aversive or negative states or stimuli—

for example, relief from withdrawal symptoms (negative 

reinforcement). Nicotine may also enhance the reinforcing values of other reinforcers or stimuli, which may also 

contribute to its reinforcing effects. 

Strong learning processes also contribute to addictive behaviors. These learning processes include conditioning in which stimuli associated with drug use evoke 

responses that are similar to the effects from the drug or 

similar to withdrawal symptoms or that may modulate 

drug effects. One hypothesis is that incentive sensitization can occur, in which some of the conditioned stimuli 

(CSs) are given priority in the allocation of attention and 

become a strong source of motivation to seek the drug 

(Robinson and Berridge 2001). Incentive sensitization 

consists of neuroadaptations from repeated use of a drug 

that render brain-reward systems hypersensitive (sensitized) to drug-associated stimuli. Also, nicotine’s ability 

to be a secondary reinforcer of CSs to other reinforcers 

strengthens its addictive effects. Nicotine tolerance, withdrawal, and reinforcement in humans are examined in the 

next section, which is followed by a section on learning 

and conditioning in nicotine addiction.

Physiological Mechanisms and 

Indicators: Nicotine Tolerance, 

Withdrawal, and Reinforcement

Chronic Tolerance

Tolerance is a reduced responsiveness to a drug as a 

function of earlier exposure to that drug. This reduction 

in responsiveness is a consequence of drug use (Kalant et 

al. 1971). Therefore, tolerance should be distinguished 

from innate differences in drug responses that may 

relate to an initial risk of dependence, such as responses 

attributable to genetic or other constitutional factors (see 

“Genetics” later in this chapter). Sensitization, the opposite of tolerance, is an enhanced responsiveness to nicotine as a function of earlier exposure to the drug (Kalant 

et al. 1971). Sensitization is not addressed here, because 

it has not been clearly demonstrated in clinical studies. 

However, animal research suggests that sensitization 

occurs in response to locomotor activity and other physical and behavioral effects of exposure to nicotine (Le Foll 

et al. 2003; Samaha et al. 2005).

Tolerance and sensitization can be characterized on 

the basis of the time course of the adaptation involved. 

Acute tolerance develops within minutes after the initial 

exposure of the day (e.g., first few cigarettes) and is generally lost with overnight abstinence from smoking (Perkins 

et al. 1995). Acute tolerance may help to explain patterns 

of smoking during the course of a day (Balfour et al. 2000), 

but researchers think it is less important than chronic 

tolerance for an understanding of dependence (Di Chiara 

2000). Chronic tolerance develops over weeks, months, 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

or years (Kalant et al. 1971). Tolerance can also be distinguished on the basis of mechanisms. Pharmacokinetic 

tolerance is a reduced response to a drug because of an 

increase in drug clearance or metabolism that results in a 

smaller concentration of the drug in the body for a given 

administered dose. This type of tolerance is not discussed 

here, because clinical studies showed no evidence of a 

pharmacokinetic tolerance to nicotine in humans (Benowitz and Jacob 1993). However, innate differences in nicotine metabolism are well known (see “Genetics” later in 

this chapter). Pharmacodynamic tolerance is a reduced 

response to a given concentration of a drug in the body 

that results from changes in tissue sensitivity. The following discussion focuses on the association between chronic 

pharmacodynamic tolerance to nicotine and dependence 

on nicotine. 

Chronic Tolerance to Nicotine

Chronic tolerance to nicotine or to most drugs is difficult to examine in clinical studies for practical and ethical 

reasons. The time required for the onset of chronic tolerance generally precludes longitudinal studies of changes 

in tolerance. Thus, the study of chronic tolerance usually requires cross-sectional comparisons between groups 

that differ in past histories of smoking, which can require 

administering nicotine to nonsmokers. Such comparisons 

may also introduce potential bias due to self-selection of 

drug history and because smoking history may covary with 

many other important differences that affect responses to 

nicotine, such as history of other drug use and psychiatric 

history (Hughes et al. 2000; Richter et al. 2002). 

Despite methodologic limitations, studies have 

clearly shown a chronic tolerance for many self-reported 

responses to nicotine, such as a subjective mood. For 

example, smokers show fewer responses than do nonsmokers to the same amount of nicotine, as evidenced by 

measures of subjective stimulation that may be viewed as 

pleasurable, such as arousal, vigor, and a subjective experience often referred to as “head rush” or “buzz,” as well as 

some experiences that may be viewed as aversive, including tension and nausea (Perkins et al. 2001b). However, 

chronic tolerance is less apparent for many other effects 

of nicotine, including cardiovascular responses (Perkins 

et al. 2001b). Chronic tolerance is virtually absent for 

simple psychomotor effects such as finger-tapping speed 

and Stroop task performance (Perkins et al. 2001b). This 

research is reviewed in detail elsewhere (Perkins 2002).

Association of Nicotine Tolerance with 

Dependence in Adults

Chronic tolerance to some effects of nicotine develops after long-term smoking. However, tolerance appears 

to be a nonsensitive marker for dependence among those 

with any history of extensive smoking (Perkins 2002). Perkins hypothesized that if a close association exists between 

tolerance and the level of dependence, then (1) more 

dependent smokers would show tolerance greater than 

that of less dependent smokers, (2) tolerance to nicotine before smoking cessation would predict the success 

of a subsequent attempt to stop smoking, and (3) tolerance would decrease with a longer duration of abstinence 

after cessation, indicating loss of dependence. However, 

the limited evidence suggests no such links between tolerance and dependence (Perkins 2002). 

First, some research (Shiffman et al. 1992; Perkins 

et al. 2001b) shows little or no difference in tolerance to 

most effects of nicotine between dependent smokers and 

a subset of smokers who do not meet dependence criteria—for example, smokers of up to five cigarettes per day

who do not experience withdrawal symptoms and who 

often go for long periods without smoking (Shiffman et 

al. 1992). Second, the magnitude of tolerance to nicotine before smoking cessation does not predict the severity of withdrawal or the duration of abstinence after an 

attempt to stop smoking, although a measure of nicotine 

reinforcement predicts both (Perkins et al. 2002a). Third, 

longitudinal studies show no change in chronic tolerance 

within one week or one month of smoking cessation and 

no difference in tolerance between former smokers who 

stopped smoking for 1 to 4 years or 6 to 19 years (Perkins 

et al. 2001c).

The conclusion that tolerance among smokers is not 

a good index of dependence warrants additional research 

(Perkins 2002). Most of these studies compared responses 

at low doses of nicotine to avoid aversive effects in groups 

with histories of limited smoking. Even so, tolerance to 

higher doses of nicotine may be associated with indices 

of dependence. Moreover, the acute effects of nicotine 

that explain its reinforcing quality are still not understood fully, so chronic tolerance to responses that were 

not assessed in this earlier research may be tied closely to 

dependence. In addition, chronic tolerance may be more 

critical during the onset of dependence in the adolescent 

years than it is in adults (Kandel and Chen 2000), because 

tolerance to the aversive effects of nicotine must occur for 

adolescents to escalate from one to two cigarettes per day 

to one pack per day (see “Epidemiology of Tobacco Use 

and Nicotine Dependence in Adults” later in this chapter). 

However, chronic tolerance may no longer be important 

after the onset of dependence. 

Withdrawal

In tobacco-dependent smokers, a reliable consequence of abstaining from smoking for more than a few 
Surgeon General’s Report

118 Chapter 4

hours is the onset of distress indicated by self-reported 

behavioral, cognitive, and physiological symptoms and by 

clinical signs (APA 2000; Shiffman et al. 2004b; Hughes 

2007). The subjective symptoms of withdrawal are manifested by affective disturbance, including irritability and 

anger, anxiety, and a depressed mood. The behavioral 

symptoms include restlessness, sleep disturbance, and an 

increased appetite, typically assessed by self-reports. Cognitive disturbances usually center on difficulty concentrating (Shiffman et al. 2004b; Hughes 2007). Researchers 

believe these symptoms—known collectively as withdrawal—are majorfactorsthat impairthe ability to remain

abstinent from smoking (Patten and Martin 1996; see 

“Trajectory of Recovery or Relapse” later in this chapter). 

The management of withdrawal and craving symptoms 

(e.g., the urge to smoke) is a primary treatment strategy to 

maintain smoking cessation. Withdrawal symptoms typically emerge within a few hours after the last cigarette is 

smoked, peak within a few days to one week, and return to 

precessation baseline levels after two to four weeks (Shiffman et al. 2004b). However, individual variability in the 

time course of withdrawal may be substantial and clinically significant (see “Trajectory of Recovery or Relapse” 

later in this chapter).

Individual withdrawal symptoms are often viewed as 

different manifestations of the same underlying process. 

One approach suggests that symptoms should be tightly 

linked in terms of pattern, intensity, time course, relationship to relapse, and neurobiologic factors. Anotherapproach suggests that symptoms should be assessed 

individually instead of by aggregating symptom scores 

into one total score (Shiffman et al. 2004b) (see “Pathophysiology of Nicotine Addiction” and “Trajectory of 

Recovery or Relapse” later in this chapter). 

Unlike nicotine tolerance, the severity of withdrawal 

is more strongly related to some of the indices of nicotine 

dependence (such as cessation). For example, although 

nicotine-dependent and nonnicotine-dependent smokers 

generally do not differ in tolerance to nicotine, nicotinedependent smokers are more likely to experience more 

severe withdrawal during initial abstinence (Shiffman 

1989b). The observation that withdrawal but not tolerance is associated with dependence has also been noted 

for other drugs of abuse, especially alcohol (Schuckit et al. 

1999; Hasin et al. 2000; O’Neill and Sher 2000).

Individual Differences in Withdrawal

Individual differences in the severity and pattern of 

withdrawal are topics of major clinical interest (see “Trajectory of Recovery or Relapse” later in this chapter). A 

history of major depression may exacerbate withdrawal 

after smoking cessation (Pomerleau et al. 2004) and may 

increase the risk of relapse in women but perhaps not in 

men (Hall et al. 1998). The role of a major depressive disorder in relapse has been inconsistent and may be related 

to how depression is defined (see “Trajectory of Recovery 

or Relapse” later in this chapter), and few other characteristics have been associated with differences in withdrawal 

for men and women. For example, even though women 

generally have more difficulty than do men in maintaining abstinence from smoking, the severity of withdrawal 

in men and women does not appear to differ (Benowitz 

and Hatsukami 1998). However, withdrawal severity may 

be moderated by the phase of the menstrual cycle in 

women, with more severe withdrawal and depressed mood 

among women who stop smoking during the luteal phase 

than among those who stop during the follicular phase 

(Allen et al. 1996; Perkins et al. 2000). Other than studies 

of the effects of medication to relieve withdrawal symptoms, few researchers have examined other factors that 

acutely modify withdrawal. 

Reinforcement

In behavioral psychology, a stimulus is considered 

reinforcing if it increases a response or behavior resulting 

in obtaining that stimulus. Thus, a drug is reinforcing if it 

is self-administered more than an inert substance used for 

comparison (e.g., placebo). “Reward,” on the other hand, 

is a less specific term defined as an index of subjective 

hedonic effects of substance use (Everitt and Robbins 

2005), and it is typically assessed after drug intake by 

ratings such as “liking” and “good effects.” Ratings of 

drug reward may help to explain reinforcement, but they 

should be kept distinct from measures of reinforcement, 

which are inherently behavioral. 

After a drug is established to be reinforcing, 

research can then focus on the neurobiologic or behavioral 

underpinnings of the reinforcing effects. (For discussion 

of research on the neurobiology of nicotine reinforcement, see “Pathophysiology of Nicotine Addiction” later in 

this chapter.) Behavioral or subjective effects of nicotine 

that may be reinforcing have not been definitively identified. Methodologic issues complicate the study of what 

makes nicotine either positively or negatively reinforcing. Pleasurable effects indicate positive reinforcement, 

whereas reductions in negative effects, such as relief 

from withdrawal, indicate negative reinforcement. These 

distinctions are important because exploration of positively reinforcing effects may be critical to understanding 

why adolescents begin to smoke cigarettes (i.e., onset of 

addiction) and why persons relapse after an attempt to 

stop smoking. Negatively reinforcing effects may be specific to relief from acute withdrawal and thus relevant 

only to relapse and not to the initiation of smoking or the 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

onset of addiction. Some research in nonsmokers links 

acute self-administration of nicotine with pleasurable 

subjective responses of increased vigor and arousal, suggesting that positive reinforcement occurs with initial 

experience with nicotine (Perkins et al. 2001a). Similar 

research should focus on whether initial nicotine reinforcement is linked to relief from preexisting aversive 

symptoms, such as depressive symptoms. 

Other effects of nicotine may also reinforce its use, 

but their links with self-administration have not been 

clearly established. These effects include modulating 

negative affect (e.g., reducing fatigue, anxiety, or sadness) 

(Kassel et al. 2003), enhancing attention and concentration during cognitively demanding tasks (Heishman et al. 

1994), and perhaps preventing hunger and maintaining a 

lower body weight (Perkins 1993). Evidence suggests that 

these effects are observed largely in abstinent smokers experiencing withdrawal and are thus examples of negative 

rather than positive reinforcement. 

Finally, animal research indicates that nicotine may 

have a secondary reinforcing function, aside from the 

direct (primary) reinforcing effects noted here. These 

studies, conducted mostly by Caggiula, Donny, and colleagues (e.g., Chaudhri et al. 2006), show that nicotine 

can enhance the reinforcing value of other reinforcers 

not associated with nicotine intake. Primary reinforcing 

effects require rapid administration of nicotine and are 

contingent on a response, whereas other reinforcementenhancing effects can occur regardless of the speed of nicotine delivery or the contingency of response. Although 

recent work suggests the occurrence of reinforcementenhancing effects of nicotine (Barr et al. 2008), the clinical research is insufficient to warrant extensive discussion of how this influence promotes nicotine dependence. 

However, this influence may help to explain why smoking appears to acutely increase consumption of other 

reinforcers, such as alcohol (Mitchell et al. 1995), and 

it may facilitate understanding of the difficulties involved 

in smoking cessation. If nicotine has reinforcementenhancing effects, then smoking cessation removes these 

effects, leading to a lessening of reinforcement from many 

other reinforcers and not just the loss of reinforcement 

from smoking. 

Smoking Frequency and Tobacco Addiction

The most common index of reinforcement in 

research on tobacco or nicotine addiction is the number 

of cigarettes smoked per day (smoking frequency). That 

is, drugs that are highly reinforcing will tend to be selfadministered to a greater extent. Typically, the number of 

cigarettes smoked per day is assessed by self-report. Biochemical measures of the amount of smoking exposure 

include blood, salivary, and urinary levels of cotinine, the 

main metabolite of nicotine. Smoking frequency is related 

to a variety of dependence measures including scores on 

scales of nicotine dependence such as the widely used 

FTND (Hughes et al. 2004a). Higher frequency of smoking was found to predict a more severe withdrawal and a 

faster relapse after an attempt to stop smoking (Ockene 

et al. 2000), which are both important clinical indices of 

addiction. Higher frequency of smoking is also associated 

with early lapses after smoking cessation, such as smoking 

on the first day of cessation or within the first two weeks, 

which are each strongly associated with an increased risk 

of relapse (Kenford et al. 1994). Other indices of smoking 

reinforcement or persistence are related to a high level 

of addiction. These indices include a longer duration of 

smoking, young age at smoking initiation, no previous 

attempt to stop smoking, and a shorter duration of abstinence during previous attempts to stop smoking (Ockene 

et al. 2000) (see “Trajectory of Recovery or Relapse” later 

in this chapter).

Acute Measures of Reinforcement

Reinforcement is often assessed in basic research 

studies by analyzing regular, or extent of, smoking behavior over a period of time. This is usually determined by 

the number of cigarettes smoked per day but occasionally 

by microtopographic measures of puffing behaviors, blood 

nicotine levels, or the percentage of carbon monoxide in 

expired air (Lee et al. 2003), a biochemical index of acute 

smoking exposure. Smoking behavior in such short-term 

studies has been sensitive to a variety of manipulations of 

nicotine exposure, demonstrating the reinforcing effects 

of nicotine. For example, the intensity of acute smoking 

behavior increases when the nicotine yield of the cigarette 

is lowered, which is a compensation to maintain nicotine 

intake (Zacny and Stitzer 1988). The increase in plasma 

concentrations of nicotine from smoking is greater after 

pretreatment with mecamylamine, a nicotine receptor antagonist. The increase is probably a result of more 

intense puffing in an attempt to overcome the blockade of 

nicotine receptors (Rose et al. 2001b). Factors have been 

observed to moderate the reinforcing effects of tobacco. 

Some studies have shown increased smoking reinforcement after pretreatment with alcohol (Nil et al. 1984; 

Mitchell et al. 1995) or with stimulant drugs such as 

d-amphetamine (Tidey et al. 2000), methylphenidate 

(Rush et al. 2005), or cocaine (Roll et al. 1997), but not 

with other stimulants such as caffeine (Nil et al. 1984; 

Lane and Rose 1995). The increase in smoking reinforcement from acute pretreatment with drugs may help to 

explain the association between a history of drug use and 

nicotine dependence (Richter et al. 2002).
Surgeon General’s Report

120 Chapter 4

Several other procedures provide sensitive and 

acute measures of smoking or nicotine reinforcement. 

These procedures include performance on a task (operant 

responding) on various schedules of reinforcement for 

puffs on a cigarette and the choice of nicotine or nonnicotine cigarettes. Instances of working for puffs on a cigarette and choosing nicotine over nonnicotine cigarettes 

increase with smoking abstinence (Perkins et al. 1994, 

1996b). The operant response to obtain puffs on a cigarette increases when the required number of responses per 

reinforcer is changed and access to alternative reinforcers 

is reduced, showing regulation of smoking intake (Johnson and Bickel 2003). A slightly different procedure—

responding for puffs on a progressive-ratio schedule by 

gradually increasing the response requirements after 

each earned puff—may also provide a sensitive measure

of the reinforcing value of smoking (Perkins et al. 2002b). 

However, few findings have related this measure to nicotine dependence.

Separation of Nicotine Reinforcement from 

Smoking Reinforcement

Nicotine dependence generally involves the intake 

of nicotine by tobacco use, especially cigarette smoking. 

Therefore, the contribution of the many nonnicotine 

aspects of tobacco associated with smoking cigarettes 

should be distinguished from the influence of nicotine 

per se. The self-administration of cigarette smoke is not 

the same as the self-administration of nicotine. Among 

many differences between nicotine delivery through 

smoking and delivery in other forms, the smoke stimuli 

that typically accompany nicotine from cigarette smoking 

may acquire conditioned reinforcing effects that maintain 

smoking behavior (Caggiula et al. 2001) (see “Learning 

and Conditioning” in the next section). 

Nevertheless, some of the manipulations that alter 

smoking behavior also alter the self-administration of 

novel nicotine formulations. Nicotine alone, isolated from 

tobacco smoke, is reinforcing in humans (Perkins et al. 

1996a; Harvey et al. 2004). The choice of nicotine nasal 

spray instead of a placebo nasal spray increases with smoking abstinence (Perkins et al. 1996b) and subsequently 

predicts a more severe withdrawal and a faster relapse 

during an attempt to stop smoking without medication 

(Perkins et al. 2002a). Blocking the effects of nicotine with 

mecamylamine pretreatment increases the intravenous 

self-administration of nicotine (Rose et al. 2003a). Also, 

under the same conditions of assessment, the amount 

of nicotine spray used voluntarily is correlated with the 

amount of voluntary smoking (Perkins et al. 1997). This 

finding indicates a generalizability between nicotine reinforcement through smoking and reinforcement through 

at least one novel form of nicotine delivery.

Individual Differences in Nicotine 

Reinforcement

Individual differences in nicotine reinforcement 

may provide direction for the study of individual differences in nicotine addiction and in approaches to treating addiction. In some studies, the reinforcing effects 

of nicotine tend to be less in women than in men, but 

the reinforcing effects of nonnicotine stimuli related to 

tobacco smoke (e.g., “cues”) tend to be greater in women 

than in men (Perkins et al. 2001d, 2002b). In light of the 

generally greater difficulty most women have with smoking cessation, this observation suggests that the influence 

of nonnicotine stimuli can be important to the persistence 

of smoking behavior (i.e., dependence) (Caggiula et al. 

2001; Rose 2006). Other characteristics that may be associated with greater reinforcement from smoking or from 

nicotine include comorbid psychiatric disorders (Lasser 

et al. 2000), a history of alcohol dependence (Keenan 

et al. 1990; Hughes et al. 2000), and perhaps other drug 

dependence (Richter et al. 2002), as well as other subgroups 

associated with a high prevalence of smoking and low rates 

of cessation. Similarly, smokers who are not obese may 

find the nicotine in cigarettes more reinforcing than do 

obese smokers (Blendy et al. 2005). 

Learning and Conditioning

Nicotine and Secondary Reinforcement

Perhaps as powerful as the direct effects of smoking and nicotine on neural functioning are the associative 

processes that develop with repeated tobacco use (Caggiula et al. 2002a; Hyman 2005). The classic conditioning 

paradigm provides an important conceptual and theoretical framework for consideration of the powerful associative learning processes that, according to Bevins and 

Palmatier (2004), develop in a specific manner. Smoking 

serves as the unconditioned stimulus (US), and the subjective and physiological effects of smoking and exposure 

to nicotine serve as unconditioned responses. Exteroceptive (environmental) and interoceptive (internal) stimuli 

that occur repeatedly in temporal proximity to smoking 

become CSs. CSs include smoking paraphernalia (e.g., an 

ashtray), sensory aspects of smoking (e.g., cigarette smell 

or taste), and/or situational cues (e.g., smoking in the car 

while driving to work). The acquired response evoked by 

CSs becomes a conditioned response. With longer-term 

smoking, conditioned responses include urges to smoke. 

Repeated pairings of these CSs with cigarette smoking 

result in the CSs alone (before smoking) triggering urges 

to smoke (to want and to seek a cigarette) (Niaura 2000; 

Berridge and Robinson 2003). 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Nicotine as a Conditioned Stimulus

Bevins and Palmatier (2004) have extended the associative learning model of nicotine dependence by hypothesizing that nicotine also has important actions as a CS of 

smoking behavior (the conditioned response) (Figure 4.3). 

The traditional role of nicotine has been limited to serving 

as a US. As a CS, nicotine acquires new or additional affective properties through being paired repeatedly with other 

stimuli such as coffee. In other words, nicotine enhances 

the salience of these and numerous other stimuli, which 

strengthens the associative bond and increases smoking behavior. 

Nicotine as a Modifier of Associative 

Processes

In addition to serving as a CS, nicotine modifies 

associative processes in conditioned and unconditioned 

manners (Bevins and Palmatier 2004). As a conditioned 

modulator (Figure 4.3), the interoceptive cuing of 

nicotine serves as a contextual stimulus that “sets the 

occasion” for an association between a discrete CS in the 

environment and smoking (Bevins and Palmatier 2004). 

The CS-US association is conditioned on the drug state 

(context). Examples include smoking while drinking alcohol to relax and smoking during a break at work to cope 

with distress. As an unconditioned modulator, nicotine 

may enhance the salience of other stimuli that have incentive values to the person (Bevins and Palmatier 2004). For 

example, as depicted in connector “a” (solid line) of Figure 4.3, nicotine enhances the incentive or reward value of 

alcohol, which has its own significant reward value. This 

“incentive amplification” is unconditioned because the 

effects of nicotine do not depend on a contingent association between smoking and the motivational stimulus. 

“Incentive amplification” by nicotine is not limited to 

other drug reinforcers. Nicotine also enhances the reinforcing effects of nondrug reinforcers, such as light stimulus (Palmatier et al. 2007).

Positive Reinforcement and Learning

The positive reinforcing action of nicotine is attributable in large part to its influence on the brain regions 

associated with reward processes (e.g., the mesolimbic 

dopaminergic system) (Balfour 2004). In a review of positive-reinforcement theory as applied to nicotine addiction, 

Glautier (2004) suggests several mechanisms underlying positive-reinforcement processes. Besides exerting a 

direct reinforcing action through its effects on core brainreward centers, nicotine may enhance the reinforcing 

efficacy of smoking-related cues as a result of priming the 

smoker to selectively attend to those stimuli. In addition, 

nicotine acquires indirect reinforcing actions through its 

Figure 4.3 Associative learning processes in nicotine addiction 

Source: Adapted from Bevins and Palmatier 2004 with permission from Sage Publications Inc. Journals, © 2004.

Note: Connections 1, 2, and 3 reflect the role of the unconditioned stimuli (USs), conditioned stimuli (CSs), and occasion setter, 

respectively. Solid lines “a” and “b” refer to nicotine’s ability to amplify incentive salience. Dashed lines (“a*” through “d*”) denote 

potentially interesting feedback functions in which conditioned associations may be strengthened.
Surgeon General’s Report

122 Chapter 4

effect on other behaviors. According to Hogarth and Duka 

(2006), considerable evidence suggests that nicotineconditioned effects are mediated by a smoker’s expectations of the effects of nicotine coupled with an appetitive 

emotional response that reflects the positive value of nicotine to the smoker (e.g., pleasure or relaxation).

Although clearly influential, positive reinforcement 

is not a likely primary motivational influence on persistence in smoking (Baker et al. 2004), except possibly in 

the case of occasional smoking (Shiffman and Paty 2006). 

Unlike expectations of negative reinforcement, such as 

smoking to relieve stress, expectations of positive reinforcement do not predict the likelihood of a relapse after 

smoking cessation. This finding indicates that positivereinforcement processes may have less motivational significance for relapse than do negative-reinforcement 

processes (Wetter et al. 1994). Relapse is less likely to 

occur during positive-affect states than during negativeaffect states (Shiffman et al. 1996c) (see “Trajectory of 

Recovery or Relapse” later in this chapter).

Negative Reinforcement and Learning

Negative reinforcement refers to processes by which 

smoking or nicotine reduces aversive states, such as pain, 

craving, difficulty concentrating, and the negative-affect 

states generally associated with nicotine withdrawal. Nicotine addiction is maintained in part because persons learn 

during the early stages of smoking that tobacco use allows 

them to escape aversive states associated with smoking 

abstinence or because they learn later that it helps them to 

avoid these aversive states (Eissenberg 2004). These states 

include irritability and an anxious or depressed mood. 

With continued use of cigarettes by smokers over time, 

the associative link between tobacco use and the relief 

of withdrawal-associated aversive states is strengthened. 

Tiffany and colleagues (2004) hypothesize that a crucial 

phase in the development of nicotine addiction may be 

the transition from experimental smoking to smoking to 

reduce the experience of negative states. 

Baker and colleagues (2004) extend the conceptualization of this negative-reinforcement model of tobacco 

dependence by focusing on the role of negative affect. 

Within this reformulation of negative reinforcement, negative affect is the core symptom of the nicotine withdrawal 

syndrome that drives a person to smoke to relieve aversive 

states. Traditional negative-reinforcement models have 

emphasized the role of environmental cues, such as interpersonal conflict, but not internal cues, such as physiological symptoms that signal impending withdrawal-related 

states of negative affect. With repeated pairings of nicotine withdrawal and smoking to relieve withdrawal, persons addicted to nicotine may learn over time to detect 

internal cues at a level that is not in the immediate awareness of the smoker, especially cues associated with negative-affect states, regardless of whether they are related to 

withdrawal (Baker et al. 2004). Nicotine operates on both 

aversive withdrawal states and distress associated with 

external stressors, according to Baker and colleagues 

(2004). However, nicotine may be less effective in reducing negative affect associated with distress from external 

stressors. Consistent with this view, cigarette smoking 

has not been found to attenuate experimentally induced 

negative affect in the laboratory setting (Conklin and 

Perkins 2005). Studies of smoking in real-world settings 

have found little or no association between subjective 

negative affect and smoking behavior (Piasecki 2006). 

Baker and colleagues (2004) further hypothesize that 

smokers acquire a “motivational-processing sequence in 

which interoceptive signals of negative affect engage drug 

self-administration response sequences and may induce 

awareness of the desire or urge to use a drug without 

awareness of the affective origins or setting events for the 

desire” (p. 47). 

The finding that negative-reinforcement processes 

may not be consciously accessible (Baker et al. 2004) 

could contribute to the difficulty smokers experience in 

trying to stop smoking. When negative affect or external 

stressors become sufficiently strong, the person becomes 

aware of them, and the negative affect leads to biases in 

information processing. One example is attentional bias 

for negative affect cues that trigger smoking (Baker et al. 

2004). Although it is provocative, Baker and colleagues’ 

model of negative reinforcement should be viewed as provisional and requiring validation. Related individual differences, such as the inability to tolerate distress, may 

influence learning and conditioning processes (Brown et 

al. 2005). Using momentary ecological assessment, Shiffman and Waters (2004) found that rapid increases in 

negative affect exert especially strong influence in precipitating lapses to smoking (see “Trajectory of Recovery or 

Relapse” later in this chapter for a more detailed discussion of smoking relapse). 

Environmental Context

Animal studies confirm the powerful role that environmental stimuli play in nicotine self-administration. 

When environmental stimuli are paired with nicotine selfadministration, the extinguished drug-seeking behavior 

is reinstated (Le Foll and Goldberg 2005). The important 

role of environmental context in nicotine addiction is 

observed in its effect on relapse. (For more description, 

see “Trajectory of Recovery or Relapse” later in this chapter.) Studies of smokers consistently report an association 

among exposure to smoking cues, craving, and positive 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

and negative affective states, which could be construed 

as emotional cues followed by return to smoking after an 

attempt to stop (Shiffman 1982; Marlatt and Gordon 

1985). These studies, however, rely on subjectively recalled 

events that may be prone to several types of memory bias. 

Using methods of ecological momentary assessment in 

an electronic diary, Shiffman and colleagues (1996c) confirmed that lapses in smoking abstinence were strongly 

associated with being in situations in which smoking was 

permitted, cigarettes were available, and other persons 

were smoking.

Clinical studies have used a cue-exposure paradigm 

to explore the association of smoking cues with craving 

and physiological and behavioral responses. These studies 

are premised on the assumption that they yield insights 

into how environmental and internal stimuli play a role in 

provoking smoking and relapse (Niaura et al. 1988; Caggiula et al. 2001; Chiamulera 2005). Stimuli are presented 

in a variety of modes, including photographic and video, 

auditory, in vivo (presence of cigarette paraphernalia or 

smoking by another person), and the use of imagery (e.g., 

request to imagine specific situations). In a meta-analytic 

review, Carter and Tiffany (1999) found that exposure to 

smoking cues increased craving most reliably, followed 

in order by sweat gland activity and heart rate changes. 

Sweating and changes in heart rate probably reflect an 

increased arousal of the sympathetic nervous system. 

Other researchers have noted cue effects on an increase 

in reaction time (Sayette and Hufford 1994), cognitive 

interference on the Stroop test (Munafò et al. 2003), and 

similar paradigms used to assess attentional interference (Mogg and Bradley 2002). Imaging studies of cue 

responses also suggest that neural activity is greatest in 

brain areas involved in emotion and reward, including the 

prefrontal cortex, limbic lobe (anterior cingulate, posterior hippocampus, and right posterior amygdala), medial 

thalamus, and midbrain structures (ventral tegmentum) 

(Due et al. 2002; McClernon and Gilbert 2004; David et 

al. 2005). 

Exposure to smoking cues among smokers also 

decreases the prepulse inhibition of the acoustic startle 

reflex, an effect associated with an increase in dopaminergic activity in the ventral tegmental brain region (Hutchison et al. 1999b). The effects of smoking cues on neural 

responses and craving are also moderated by factors such 

as the perceived availability of cigarettes. After cue exposure, craving increased more when there is an expectation 

of the opportunity to smoke (perceived availability) than 

when there is perceived unavailability (Carter and Tiffany 

1999). Exposure to a cigarette cue under the condition 

of perceived availability is associated with an increase in 

activation of the ventromedial prefrontal cortex and a 

decrease in activation of the dorsolateral prefrontal cortex 

compared with exposure to a neutral cue (Wilson et al. 

2004). This pattern of neural activation with corresponding increases in craving can be seen as setting the stage for 

behaviors that culminate in smoking.

Responses to cues in laboratory experiments are 

associated with responses to smoking cessation treatments. For example, acute increases in heart rate assessed 

among smokers in response to a cue exposure at the end 

of a treatment protocol were related to a later relapse to 

smoking (Niaura et al. 1989). An acute deceleration in 

heart rate assessed when smokers observed a cigarette 

being lit during the cue-exposure procedure also predicted 

relapse. Heart rate deceleration in this context may reflect 

a greater attention paid to the stimulus (e.g., a lit cigarette). Subsequently, Waters and colleagues (2004) found 

that a cue-provoked craving before treatment predicted 

relapse, but only among those who were treated with an 

active nicotine patch instead of a placebo patch, suggesting inconsistent results or uncertainty in the link between 

cue-provoked craving in the laboratory and relapse. 

If cue-provoked responses assessed in the laboratory 

are associated with smoking relapse, then treatments that 

decrease or blunt these responses may increase the likelihood of successful smoking cessation. A review by Conklin 

and Tiffany (2002) suggests that conventional extinctiontype treatments, such as exposure to smoking-related 

cues unaccompanied by the reinforcing effects of nicotine 

or exposure with response-prevention treatments, are 

ineffective in helping persons to stop smoking. This finding may relate to the possibility that stimulus-response 

pairing, if sufficiently strong, cannot be forgotten or 

unlearned (LaBar and LeDoux 2001; Conklin and Tiffany 2002; Niaura 2002). In addition, the large number of 

potential cues likely serves to maintain smoking behavior or the state-dependent learning processes. However, methods such as use of denicotinized cigarettes or 

antagonists (e.g., mecamylamine) show significant effects 

on reducing the rewarding value of smoking cues and 

have the potential to enhance smoking cessation (Rose 

and Behm 2004; Rose 2006). Other cognitive or behavioral methods based in modern learning theory may also 

show more promise in suppressing the stimulus-response 

bond. Pharmacologic treatments show some promise in 

decreasing cue reactivity. Compared with a placebo gum, 

nicotine polacrilex gum diminished the craving response 

to smoking cues more rapidly (Shiffman et al. 2003). In 

a study using the same cue-exposure paradigm, a more 

recent formulation of a rapid-release nicotine gum 

reduced craving more than did conventional nicotine 

polacrilex gum (Niaura et al. 2005). Nicotine polacrilex gum is an effective smoking cessation aid (Silagy et 

al. 2004). Its efficacy may be associated with its ability to 

diminish a cue-provoked craving. 
Surgeon General’s Report

124 Chapter 4

Other rapid-release formulations of nicotine 

replacement therapy (NRT), including gum and nasal 

spray, may similarly help persons to stop smoking, in part 

because these formulations decrease the craving response 

to cues. In contrast, although slower-releasing NRT formulations (e.g., a nicotine patch) appear to lower absolute 

levels of craving, these formulations do not blunt cueprovoked craving (Tiffany et al. 2000; Waters et al. 2004). 

One study has suggested that treatment with bupropion 

blunts cue-provoked craving, but the study did not control for abstinence status (Brody et al. 2004a). Other nonnicotine compounds (e.g., naltrexone and olanzapine) also 

may blunt cue-provoked craving (Hutchison et al. 1999a, 

2004). This finding suggests that the cue-exposure paradigm may be a useful screening tool for testing pharmacologic aids to smoking cessation; however, further studies 

need to be conducted to better understand why some medications affect cue-induced cravings and others do not.

Summary and Future Directions

Long-term exposure to nicotine produces biologic 

adaptations leading to reduced sensitivity to some of the 

effects of nicotine (tolerance) and symptoms of distress 

soon after cessation of drug use (withdrawal). Tolerance of nicotine in adolescent smokers may be related to 

onset of drug dependence, even though tolerance in adult 

smokers does not appear to be related to different indices 

of nicotine addiction. Withdrawal symptoms, especially 

self-reported cravings and negative affect, are related to 

some indices of addiction. A narrower focus on the individual withdrawal symptoms most strongly related to 

relapse, such as negative affect (e.g., depressed mood), 

may increase understanding of the underlying mechanisms associated with the maintenance of nicotine addiction and requires further study. 

Positive reinforcement from nicotine may play 

a more significant role in the initiation of smoking, 

and negative reinforcement, particularly relief from 

withdrawal, is an important contributor to the persistence 

of smoking and relapse. Measures of nicotine’s reinforcing effects, especially the most common measure—selfreported number of cigarettes smoked per day—are consistently related to other indices of addiction, including 

the risk of relapse. However, other objective measures of 

nicotine’s reinforcing effects, especially those reflecting 

persistence in smoking behavior, may provide even stronger markers of addiction for predicting clinical outcomes 

and for testing the efficacy of new treatments or tobacco 

products. Such measures may also be useful as endophenotypes of dependence for future research into the etiology of addiction, including the influence of a person’s 

genetic composition. Therefore, the development of these 

validated markers and measures for nicotine and smoking 

reinforcement is critical for future research examining 

the etiology and treatments for nicotine addiction and for 

tobacco product testing.

Nicotine addiction results not only from the pharmacodynamic effects of nicotine but also from associative 

learning and conditioning. Nicotine serves not only as a 

US, but can also serve as a CS and a modifier of associative 

processes. Motivational influences on persistent smoking are more likely tied to negative reinforcement than to 

positive reinforcement. 

Interoceptive (internal) cues of negative affect have 

been linked to craving and relapse, whereas positive affective states are less likely to lead to relapse. Exteroceptive 

(environmental) cues also play an important role in eliciting craving and relapse. Reactivity to both internal and 

environmental cues may provide another measure of nicotine addiction. Factors such as age, gender, and psychiatric comorbid history are important to consider in future 

research, because they have or may have an important role 

in moderating responses to nicotine (see “Epidemiology of 

Tobacco Use and Nicotine Dependence in Adults” later in 

this chapter). Because of the importance of learning in the 

development and maintenance of nicotine addiction, this 

is an area that requires more extensive research.

Pathophysiology of Nicotine Addiction

Because nicotine is one of the primary constituents 

responsible for tobacco addiction, research to promote 

an understanding of the neurobiology of tobacco addiction focuses on the mechanisms mediating nicotine 

addiction. As noted previously, dependence on nicotine 

is characterized by both the persistence of a drug-taking 

behavior and the emergence of withdrawal symptoms on 

abrupt cessation of nicotine administration (Wikler 1973; 

Levine 1974; Stewart et al. 1984; Ludwig 1986; O’Brien et 

al. 1990; Hughes and Hatsukami 1992; Koob et al. 1993; 

Markou et al. 1993, 1998; APA 1994; Kenny and Markou 

2001). Therefore, both the neurosubstrates (brain structures, pathways, and systems) mediating the reinforcing effects of acute administration of nicotine and those 
Nicotine Addiction: Past and Present 125

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

mediating the nicotine withdrawal syndrome are relevant to drug dependence. The physiological systems that 

develop adaptations to repeated nicotine administration 

and lead to the emergence of withdrawal signs on cessation of nicotine administration are likely to intersect with 

systems that mediate the acute effects of nicotine (Markou 

et al. 1998; Kenny and Markou 2001). That is, drug dependence develops as a neurobiologic adaptation to chronic 

drug exposure. 

Accordingly, this section first reviews the systems 

and pathways mediating the reinforcing effects of nicotine and then discusses the neuroadaptations that occur 

because of chronic nicotine exposure. These neurobiologic adaptations mediate the tolerance to and effects of 

withdrawal from nicotine that are interlinked in most 

theoretical conceptualizations. Researchers have hypothesized that the sensitization to the locomotor-activating 

effects of drugs, including effects observed after repeated 

nicotine administrations, reflect a progressive augmentation in the motivation to self-administer the drug (Robinson and Berridge 1993). (The locomotor-activating effects 

consist of progressively increased locomotor responses to 

repeated drug-challenge injections.) However, no direct 

evidence suggests that sensitization to the locomotoractivating effects of nicotine reflects any aspect of dependence on nicotine. Therefore, sensitization is not covered 

in this section. If sensitization to the reinforcing effects of 

nicotine develops, it will most likely be relevant to early 

phases of tobacco use involving the acquisition of tobacco 

smoking as a continuing behavior. 

The final discussion focuses on the comorbidity 

of nicotine dependence and psychiatric disorders in the 

context of shared substrates that mediate nicotine dependence and depression-like aspects of psychiatric disorders 

(Markou et al. 1998; Markou and Kenny 2002; Paterson 

and Markou 2007).

Nicotinic Acetylcholine Receptors

Nicotine, an alkaloid in concentrations of approximately 1 to 3 percent in tobacco (Browne 1990), is an 

agonist at the nicotinic acetylcholine receptors (nAChRs) 

expressed both in the peripheral nervous system and the 

CNS (Henningfield et al. 1996; Vidal 1996; Holladay et 

al. 1997; Paterson and Norberg 2000). Similar to other 

ligand-gated ion channels, neuronal nAChRs are composed of five membrane-spanning subunits that combine 

to form a functional receptor (Lindstrom et al. 1996; 

Role and Berg 1996; Albuquerque et al. 1997; Lèna and 

Changeux 1998, 1999; Dani 2000; Gotti et al. 2006). Neuronal nAChR subunits are arranged in different combinations to form nAChRs with distinct pharmacologic and 

kinetic properties. The neuronal α subunit exists in nine 

isoforms (α2 through α10), whereas the neuronal β subunit exists in three isoforms (β2, β3, and β4) (Arneric et 

al. 1995; Wonnacott 1997; Elgoyhen et al. 2001). Study 

of oocyte expression systems injected with pairwise combinations of different neuronal α and β subunits indicate 

that these subunits combine with a stoichiometry of 

2α:3β to produce a functional neuronal nicotinic heterooligomeric receptor (Deneris et al. 1991; Conroy and Berg 

1995; Colquhoun and Patrick 1997). In contrast, α7, α8, 

and α9 subunits form homo-oligomeric complexes composed of five α subunits and no β subunits (Chen et al. 

1998). Only the α7 pentamer is expressed in the CNS.

Neuronal nAChRs in rats are divided broadly into 

three classes: (1) those with a high-affinity binding site for 

racemic nicotine—the nAChRs containing α4, of which 

the α4β2 combination is the most abundant (Flores et al. 

1992; Picciotto et al. 1995); (2) those with a high affinity 

for the radioiodine [125I]α-bungarotoxin that correspond 

to the homomeric α7 nAChRs (Clarke 1992); and (3) 

those with a high affinity for neuronal bungarotoxin—the

α3-containing nAChRs (Schulz et al. 1991). The precise 

combinations of nAChR subunits that constitute active 

brain nAChRs in vivo have been primarily inferred from 

their pharmacologic profile (Sershen et al. 1997; Kaiser et 

al. 1998; Luo et al. 1998; Sharples et al. 2000). However, 

advances have identified nAChR subunits expressed by 

individual neurons in specific brain regions (Lèna et al. 

1999; Sheffield et al. 2000).

The predominant role of nAChRs in the brain is 

the modulation of neurotransmitter release, because 

nAChRs are situated primarily on presynaptic terminals 

(Wonnacott 1997). Nevertheless, nAChRs are also found 

at somatodendritic, axonal, and postsynaptic sites (Sargent 1993). As a result of actions at the nAChR sites, 

nicotine stimulates the release of most neurotransmitters 

throughout the brain (Araujo et al. 1988; Toide and Arima 

1989; McGehee and Role 1995; Gray et al. 1996; Role and 

Berg 1996; Wilkie et al. 1996; Albuquerque et al. 1997; 

Alkondon et al. 1997; Kenny et al. 2000; Grady et al. 2001). 

Therefore, as discussed in the next section, various transmitter systems are likely to be involved in the rewarding 

effects of nicotine and in the adaptations that occur in 

response to chronic exposure to nicotine, which give rise 

to dependence and withdrawal responses.

Neurosubstrates of Nicotine 

Reinforcement

The mesocorticolimbic brain system in the midbrain of mammals is composed of interconnected brain 
Surgeon General’s Report

126 Chapter 4

structures. This system has been shown to be critically 

involved in the effects of drugs of abuse (Koob 2008). 

Among the main components of this system are the 

dopaminergic neurons originating in the ventral tegmental area (VTA) and projecting to the nucleus 

accumbens and the frontal cortex. The activity of these 

VTA dopamine neurons is regulated by the release of the 

excitatory neurotransmitter glutamate from neuronal

projections originating from several sites, including the 

nucleus accumbens and the frontal cortex. Other inputs 

that also regulate activity of the mesolimbic system are 

(1) γ-aminobutyric acid (GABA) inhibitory interneurons 

located within the VTA and the nucleus accumbens and (2) 

cholinergic projections from brainstem nuclei to the VTA. 

These cholinergic projections release the endogenous 

neurotransmitter acetylcholine, which acts on excitatory 

nAChRs located on glutamate and GABA neuronal terminals in the VTA (Figure 4.4). Extensive investigations over 

decades have conclusively demonstrated a critical role of 

the mesocorticolimbic system and its connections in several behavioral and affective responses to drugs of abuse. 

Dopamine and Nicotinic Acetylcholine Receptors

As with other drugs of abuse, it has been demonstrated that the mesolimbic dopaminergic system and 

nAChRs within that system are critically involved in the 

reinforcing properties of nicotine (Watkins et al. 2000; 

Picciotto and Corrigall 2002; Balfour 2004). Acute administration of nicotine increased the firing rate of dopaminergic neurons in the VTA (Grenhoff et al. 1986; Pidoplichko 

et al. 1997) and elevated dialysate levels of dopamine in 

the shell of the nucleus accumbens (Imperato et al. 1986; 

Damsma et al. 1989; Mifsud et al. 1989; Benwell and Balfour 1992; Pontieri et al. 1996; Nisell et al. 1997; Carboni 

et al. 2000). These effects of nicotine may occur through 

excitatory actions at nAChRs on the mesolimbic dopaminergic neurons in both the VTA and the nucleus accumbens and at nAChRs located on local neuronal circuitry 

within these brain regions (McGehee and Role 1996; Nisell 

et al. 1997; Teng et al. 1997). The nAChRs in the VTA play a 

more important role than those in the nucleus accumbens 

in the effects of nicotine on the release of dopamine from 

the nucleus accumbens (Nisell et al. 1994a,b, 1997). 

Several findings support the conclusion that nAChRs 

located within the VTA are involved in nicotine reinforcement. Intravenous nicotine self-administration is a procedure that allows the assessment of the reinforcing effects 

of nicotine by measuring the number of infusions a rat 

chooses to receive intravenously through an indwelling 

permanent catheter by pressing a lever during one-hour 

daily sessions in a testing chamber. Each of four factors 

decreased intravenous nicotine self-administration in rats 

(Picciotto and Corrigall 2002). The factors were (1) injections of the competitive nAChR antagonist DHβE into the 

VTA (Williams and Robinson 1984) but not the nucleus 

accumbens (Corrigall et al. 1994), (2) development of 

lesions of the mesolimbic dopaminergic projections from 

the VTA to the nucleus accumbens (Corrigall et al. 1992), 

(3) development of cholinergic lesions of the brainstem 

pedunculopontine tegmental nucleus that project to the 

VTA (Lança et al. 2000), and (4) systemic administration 

of dopamine receptor antagonists (Corrigall and Coen 

1991b). Studies suggest an involvement of the nAChR 

subtypes containing a4β2 in both the nicotine-induced 

release of dopamine and nicotine reinforcement (Picciotto 

et al. 1998; Schilström et al. 1998b; Watkins et al. 1999; 

Grillner and Svensson 2000; Sharples et al. 2000). In addition, mutant mice with hypersensitive α4 nAChRs show a 

50-fold increase in sensitivity to the reinforcing effects of 

nicotine measured by a place-preference procedure (Tapper et al. 2004). A place-preference procedure assesses the 

rewarding effects of a drug by measuring the preference a 

rat exhibits for a compartment previously associated with 

the effects of a drug instead of a compartment associated 

with an injection of saline. The place-preference finding 

by Tapper and colleagues (2004) further indicates a critical role of α4 nAChRs in nicotine reinforcement. The α7 

homomeric receptors may be involved in the reinforcing effects of nicotine. Methyllycaconitine, an antagonist 

with limited selectivity for the α7 nAChR, decreased the 

intravenous nicotine self-administration procedure in 

rats (Markou and Paterson 2001), although another study 

with rats showed no effects of this antagonist on nicotineinduced hyperactivity or nicotine self-administration 

(Grottick et al. 2000). Finally, both the α4β2 and α7 subtypes are implicated in the effects of nicotine on memory (Levin et al. 1999; Bancroft and Levin 2000) and the 

anxiolytic effects of nicotine (Gordon 1999; Cheeta et al. 

2001), which also contribute to persistent tobacco use 

(USDHHS 1988).

Glutamate

Other mechanisms by which nicotine may elevate 

striatal dopamine levels include increases in excitatory 

glutamatergic inputs from the frontal cortex to the 

nucleus accumbens and/or excitatory glutamatergic 

inputs to VTA dopaminergic neurons projecting to the 

striatum. Nicotine increases the release of glutamate by 

agonist actions at excitatory presynaptic nAChRs on glutamatergic terminals in various brain sites, including the 

VTA (Fu et al. 2000; Grillner and Svensson 2000; Mansvelder and McGehee 2000), nucleus accumbens (Reid 

et al. 2000), prefrontal cortex (Gioanni et al. 1999), and 

hippocampus (Gray et al. 1996). In the VTA, nicotine acts 
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Figure 4.4 Neural pathways for γ-aminobutyric acid, glutamate, dopamine, and excitatory neurotransmitters

Source: Markou 2006. Reprinted with permission from Wiley-Blackwell, © 2006.

Note: The circular symbol with the reverse arrow attached to it depicts a neuron. The circle is the cell body, and the reverse arrow is 

the terminal that releases neurotransmitter(s) out of its open site into the synapse at the indicated projection brain site. The minus 

sign (-) indicates inhibitory input of the neurotransmitter, and the plus sign (+) indicates excitatory input of the neurotransmitter. 

Some neurons are interneurons projecting within a particular brain site, and other neurons project from one brain site to another 

distant brain site. GABA = γ-aminobutyric acid; nAChR = nicotinic acetylcholine receptor; mGluR2/3 = metabotropic glutamate 2/3 

receptor; VTA = ventral tegmental area.

at presynaptic α7 nAChRs located on glutamate neurons 

(neurons that release glutamate as the primary neurotransmitter). Activation of these α7 nAChRs on glutamate neurons (Mansvelder and McGehee 2000) increases 

the release of glutamate in the VTA. This activity, in turn, 

stimulates the release of dopamine in the nucleus accumbens (Nisell et al. 1994a,b; Schilström et al. 1998a,b; Fu 

et al. 2000; Mansvelder and McGehee 2000). That is, this 

increased release of glutamate acts at metabotropic and 

ionotropic glutamate receptors located on postsynaptic 

dopamine neurons (neurons that have dopamine as the 

primary neurotransmitter). Activation of these glutamate 

receptors leads to excitation of the dopamine neurons that 

results in increased release of dopamine in terminal brain 

sites where these neurons project, such as the nucleus 

accumbens, the amygdala, and the frontal cortex. 
Surgeon General’s Report

128 Chapter 4

Ionotropic antagonists of N-methyl-d-aspartate 

receptors blocked (prevented) tolerance to the locomotor depressant effects of acute nicotine administration 

(Shoaib and Stolerman 1992; Shoaib et al. 1994) and 

blocked sensitization to the locomotor stimulant effects 

of chronic nicotine administration (Shoaib and Stolerman 1992). Most relevant to addiction is the finding that 

blockade of the postsynaptic metabotropic glutamate 

receptor subtype 5 (mGluR5) with 2-methyl-6-(phenylethynyl)pyridine (MPEP) decreased intravenous nicotine 

self-administration in rats and mice (Paterson et al. 2003) 

and decreased the motivation to self-administer nicotine 

(Paterson and Markou 2005). These effects are likely mediated by decreasing the nicotine-stimulated release of 

dopamine in the mesolimbic system. At doses that blocked 

nicotine self-administration, MPEP had no effect on 

response for food (Paterson et al. 2003). The progressiveratio schedule of reinforcement, which gradually increases 

the response requirements after each earned reward, 

allows the assessment of the motivation for reinforcers, 

such as nicotine or food, by evaluating the maximal number of responses emitted by the rat (i.e., breaking point) to 

receive a single intravenous infusion of nicotine or a single 

food reward. In this schedule, MPEP had a greater effect on 

motivation for nicotine than on motivation for food, even 

when the magnitudes of reinforcer value were equated to 

support equal breaking points for nicotine and food under baseline conditions (Paterson and Markou 2005). This 

selectivity of the MPEP effects for nicotine reinforcement 

versus food reinforcement suggests that MPEP selectively 

blocks the reinforcing effects of nicotine without affecting 

motor performance or food reinforcement. Furthermore, 

evidence suggests a potential role of ionotropic glutamate 

receptors in the effects of nicotine. Animals that selfadministered nicotine chronically exhibited an increase in 

ionotropic glutamate receptor subunits in brain regions, 

such as the VTA and the frontal cortex, that are implicated 

in the reinforcing effects of nicotine (Wang et al. 2007).

γ-Aminobutyric Acid

GABA is the major inhibitory transmitter in the 

brain and is another transmitter system critically involved 

in the reinforcing effects of acute nicotine administration. Several factors inhibit the release of mesolimbic 

dopamine, including inhibitory GABA transmission on 

ascending afferents to dopaminergic VTA neurons from 

the pedunculopontine tegmental nucleus (Walaas and 

Fonnum 1980; Yim and Mogenson 1980), descending 

GABA-ergic inputs from the ventral pallidum and the 

nucleus accumbens, GABA interneurons within the VTA, 

and medium spiny GABA neurons in the nucleus accumbens (Walaas and Fonnum 1979; Heimer and Alheid 1991; 

Churchill et al. 1992; Dewey et al. 1992; Kalivas et al 1992; 

Klitenick et al. 1992; Sugita et al. 1992; Engberg et al. 

1993). As suggested by this neuroanatomy and extensive 

electrophysiological studies, interactions between the 

GABA, dopaminergic, and glutamatergic systems in the 

VTA are complex (Mansvelder and McGehee 2000; Mansvelder et al. 2002). Glutamate afferents to the VTA excite 

dopamine neurons, and GABA-ergic afferents to the VTA 

inhibit dopamine neurons. Excitatory nAChRs are located 

on both glutamate and GABA-ergic neurons. The nAChRs 

on GABA neurons desensitize quickly to chronic administration of nicotine, but the nAChRs on glutamate neurons 

require higher doses of nicotine for desensitization. This 

delicate balance leads to a nicotine-induced increase in 

the release of dopamine in the nucleus accumbens, the 

terminal area of VTA neurons (Schilström et al. 1998b; 

Mansvelder and McGehee 2000). Similar transmitter 

interactions may also occur in other brain sites.

Increased GABA-ergic transmission abolishes 

both the nicotine-induced increases in dopamine in the 

nucleus accumbens and the reinforcing effects of nicotine (Dewey et al. 1999; Brebner et al. 2002). Systemic 

injections of γ-vinyl GABA (vigabatrin) increased GABA 

levels and decreased nicotine self-administration in rats 

(Paterson and Markou 2002). Vigabatrin is an irreversible inhibitor of GABA transaminase, the primary enzyme 

involved in GABA metabolism (Jung et al. 1977; Lippert 

et al. 1977). Systemic injections of vigabatrin also abolished the expression and acquisition of nicotine-induced 

conditioned place preference (Dewey et al. 1998). The 

administration of vigabatrin also lowered nicotineinduced increases in dopamine in the nucleus accumbens in both untreated rats and those receiving long-term 

treatment with nicotine in a dose- and time-dependent 

manner measured by in vivo microdialysis. In addition, 

vigabatrin abolished nicotine-induced increases in striatal dopamine in primates, as determined by PET scan 

(Brebner et al. 2002). 

The use of receptor-selective agonists in animals 

suggests the involvement of GABAB receptors in the 

reinforcing effects of nicotine. Systemic injections or 

microinjections of baclofen or CGP44532 [(3-amino2[S]-hydroxypropyl)-methylphosphinic acid]—twoGABAB

receptor agonists—into the nucleus accumbens shell, the

VTA, or the pedunculopontine tegmental nucleus that 

sends cholinergic, GABA-ergic, and glutamatergic projections to the VTA decreased the reinforcing effects of nicotine (Shoaib et al. 1998; Corrigall et al. 2000, 2001; Fattore 

et al. 2002; Paterson et al. 2004). However, injections 

into the caudate-putamen did not have these effects. The 

decreases in nicotine self-administration persisted even 

after administration of CGP44532 for 14 days, indicating 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

little tolerance to this effect of the GABAB receptor agonist 

with this duration of treatment (Paterson et al. 2005b); 

that is, the reduction in nicotine self-administration 

persisted over time. The issue of tolerance is important 

because long-term administration of drug therapies is 

necessary to achieve smoking cessation. However, in studies of rats, vigabatrin and GABAB receptor agonists also 

decreased response for food, although at doses higher than 

the threshold doses for inducing decreases in nicotine 

self-administration (Paterson and Markou 2002; Paterson 

et al. 2004, 2005b). These effects on response for food may 

reflect nonspecific effects on performance by GABA-ergic 

compounds or specific effects on food intake. The possibility of effects on food intake is intriguing, because weight 

gain associated with abstinence from smoking is often a 

concern for smokers, especially women, who want to stop 

smoking cigarettes.

Thus, increased GABA transmission through the 

activation of GABAB receptors blocks the reinforcing 

effects of nicotine. However, a clinical study shows that 

one dose of baclofen had no effect on either the number 

of cigarettes smoked or the craving for nicotine (Cousins 

et al. 2001). Nevertheless, other clinical studies show that 

long-term administration of baclofen reduced abuse of 

cocaine and alcohol, as well as cue-induced brain activation (Ling et al. 1998; Addolorato et al. 2000, 2002a,b). 

Therefore, long-term treatment with these GABA-ergic 

drugs may first be required to reduce tobacco smoking.

Opioid, Endocannabinoid, and Serotonin Systems

The data on the possible role of opioid systems in 

the rewarding effects of nicotine remain inconclusive. 

Nicotine did not induce a conditioned place preference 

in μ-opioid receptor *NULL-mutant mice, but it did so 

in wild-type animals (Berrendero et al. 2002). Similarly, 

nicotine induced a conditioned place preference in wildtype but not in preproenkephalin *NULL-mutant mice. 

A nicotine-induced elevation in dopamine overflow in 

the nucleus accumbens was absent in *NULL mutants 

(Berrendero et al. 2005). However, systemic or intra-VTA 

administration of the opiate receptor antagonist naltrexone or the opiate receptor agonist d-Ala2,N-Me-Phe4-Glyol-enkephalin, respectively, had limited or no effects on 

nicotine self-administration in rats (Corrigall and Coen 

1991a; Corrigall et al. 2000). 

In humans, acute and short-term nicotine administration leads to the release of β-endorphins, endogenous 

opioid peptides that have reinforcing effects (Davenport 

et al. 1990; Boyadjieva and Sarkar 1997). Furthermore, in 

humans, the acute administration of naltrexone decreased 

the reinforcing value of nicotine in a procedure involving 

choice between puffs on nicotinized versus denicotinized 

cigarettes (i.e., compared with placebo, naltrexone significantly reduced the number of nicotine cigarette choices) 

(Rukstalis et al. 2005). This result is consistent with a previous finding that acute administration of naltrexone significantly decreased the total number of choice cigarettes 

smoked (e.g., subjects were given a choice to smoke four 

cigarettes in a two-hour period of time) (Epstein and King 

2004). However, a randomized, double-blind trial of naltrexone for smoking cessation found only a nonsignificant 

trend toward increased cessation rates, and the effect disappeared at 12 months after cessation (Covey et al. 1999). 

Other clinical trials examining the effects of naltrexone 

versus placebo in smokers who were assigned nicotine 

patches to aid cessation have also observed no significant 

effects of naltrexone on improving treatment outcomes 

(King et al. 2006; O’Malley et al. 2006). Thus, the possible 

involvement of the opiate system in the reinforcing effects 

of nicotine remains at best unclear, and the use of opiate antagonists as treatments for dependence on tobacco 

smoking appears unwarranted. A Cochrane review in 2001

concluded that opioid antagonists failed to significantly 

increase long-term abstinence from smoking on the 

basis that the limited evidence was insufficient to support 

a conclusive finding on whether naltrexone is an aid to 

smoking cessation (David et al. 2006). Although one study 

suggested an effect of gender, women benefited more than 

men from treatment with naltrexone (King et al. 2006).

The evidence is much stronger for the role of 

serotonin in the reinforcing effects of nicotine. Acute 

administration of nicotine elevated extracellular serotonin 

in the nucleus accumbens (Schiffer et al. 2001) and the 

VTA (Singer et al. 2004). Serotonin was also implicated 

in a neurochemical sensitization to nicotine, which some 

researchers hypothesize to be relevant to aspects of nicotine dependence. The administration of the serotonin 

(5HT2) receptor agonist (±)-2,5-dimethoxy-4-iodoamphetamine (Olausson et al. 2001) or the 5HT2C receptor 

agonist (S)-2-(chloro-5-fluoro-indol-1-yl)-1-methylethylamine fumarate (Di Matteo et al. 2004) blocked the increased overflow of serotonin observed after a nicotine 

challenge in nicotine-treated rats. In addition, nicotine 

increased serotonin overflow in cortical areas (Toth et al. 

1992; Ribeiro et al. 1993; Summers and Giacobini 1995; 

Singer et al. 2004) and in the dorsal hippocampus (Singer 

et al. 2004). In contrast, Balfour and Ridley (2000) found a 

decrease in the serotonin overflow after acute administration of nicotine. However, Singer and colleagues (2004) 

used anesthetized rats, and Balfour and Ridley (2000) 

used in vivo microdialysis in conscious rats. In addition, 

administration of nicotine for at least 20 days was associated with decreased serotonin levels in the dorsal hippocampus (Benwell and Balfour 1979; Balfour and Ridley 
Surgeon General’s Report

130 Chapter 4

2000). However, nicotine administration for 14 days was 

associated with increased serotonin levels (Takada et al. 

1995). Nicotine infusion into the ventromedial nuclei 

or the lateral hypothalamic area increased the release of 

serotonin in this area (Yang et al. 1999; Ramos et al. 2004). 

Together, the findings suggest that acute administration 

of nicotine increases serotonin levels but that long-term 

administration leads to decreases in serotonin levels that 

may mediate the affective aspects of nicotine dependence 

and withdrawal (Harrison et al. 2001).

Studies provide conflicting evidence on the role 

of cannabinoid subtype 1 (CB1) receptors in modulating 

the reinforcing effects of nicotine. CB1 knockout mice 

(i.e., mice genetically engineered to lack CB1 receptors) 

self-administered nicotine (Cossu et al. 2001) but did not 

exhibit conditioned place preference to nicotine (Castañe 

et al. 2002). Furthermore, the CB1 receptor antagonist 

rimonabant (SR141716) decreased nicotine seeking and 

self-administration of nicotine induced by the presentation of conditioned cues and also attenuated a nicotineinduced release of dopamine in the nucleus accumbens 

shell (Cohen et al. 2002, 2005; De Vries et al. 2005). Thus, 

the data from experimental studies of rodents on the role 

of the cannabinoid system are inconclusive and so are 

the clinical data (Le Foll and Goldberg 2005). However, 

an analysis of data pooled from three clinical trials of 

rimonabant compared with a placebo showed modest success at the end of treatment (Cinciripini et al. 2006).

Norepinephrine

Data also suggest a role of norepinephrine in the 

effects of nicotine. Acute nicotine administration increases 

extracellular norepinephrine in the nucleus accumbens, 

the hippocampus, and the cortex in rats (Brazell et al. 

1991; Mitchell et al. 1993; Summers and Giacobini 1995; 

Benwell and Balfour 1997; Schiffer et al. 2001). Nicotineevoked hippocampal release of norepinephrine in vivo was 

attenuated by α-bungarotoxin but was unaffected by either 

of the nAChR antagonists mecamylamine or DHβE, implicating α7 nAChRs, rather than α4β2 nAChRs associated 

with the release of norepinephrine in this region of the 

brain (Fu et al. 1999). However, norepinephrine release 

from hippocampal synaptosomes in rats was sensitive to 

mecamylamine, DHβE, and methyllycaconitine suggesting that the release of norepinephrine may not be specific 

to α7 nAChRs (Clarke and Reuben 1996). Additional studies suggest the role of norepinephrine in nicotine’s effects. 

Intravenous self-administration of nicotine increased 

norepinephrine concentrations in the amygdala and the 

hypothalamic paraventricular nucleus (Fu et al. 2001, 

2003). In vitro studies indicated that nicotine increased 

release of norepinephrine in (1) prefrontal cortex slices of 

rats (Rao et al. 2003) and (2) locus coeruleus neurons of 

fetal rats grown in cultures (Gallardo and Leslie 1998). 

Consistent with these neurochemical findings, 

short-term or long-term administration of reboxetine, 

the selective noradrenaline reuptake inhibitor, decreased 

nicotine self-administration in rats (Rauhut et al. 2002). 

However, reboxetine also decreased sucrose-maintained 

response, although to a lesser degree than nicotinemaintained response. Reboxetine acts as a noncompetitive 

nAChR antagonist, in addition to blocking noradrenaline 

reuptake (Miller et al. 2002). Thus, it is not conclusive that 

the effects of reboxetine on nicotine self-administration 

are attributable to its effects on noradrenaline reuptake 

rather than to its actions as an nAChR antagonist. 

Bupropion, a smoking cessation aid, also inhibits 

reuptake of norepinephrine, as well as dopamine (Ferris et 

al. 1983). Administration of bupropion increased extracellular concentrations of dopamine and epinephrine in the 

nucleus accumbens, hypothalamus, and prefrontal cortex 

(Nomikos et al. 1989, 1992; Li et al. 2002). Furthermore, 

electrophysiological studies indicated that bupropion 

decreased the firing rates of dopamine neurons in the 

nucleus accumbens and noradrenergic neurons in the 

locus coeruleus but had no effect on firing of serotonin 

dorsal raphe neurons (neurons located in the dorsal raphe 

firing) (Cooper et al. 1994). 

Despite the demonstrated effects of bupropion on 

neurotransmitter and receptor systems that appear to 

mediate the effects of nicotine, bupropion had inconsistent effects on nicotine self-administration in rats. Some 

studies showed a decrease in nicotine self-administration 

in fixed-ratio schedules of reinforcement but had no effects 

in a progressive-ratio schedule (Glick et al. 2002; Bruijnzeel and Markou 2003). In contrast, another study (Shoaib 

et al. 2003) indicated that repeated daily administration 

of bupropion increased nicotine self-administration in a 

fixed-ratio schedule, but the results were not significant 

(Shoaib et al. 2003). Finally, Rauhut and coworkers (2003) 

showed that low doses of bupropion increased and high 

doses of bupropion decreased nicotine self-administration 

and response for sucrose. 

In summary, these findings suggest a strong 

effect of nicotine on transmission of norepinephrine, but 

bupropion, which inhibits the reuptake of both dopamine 

and norepinephrine, has inconsistent effects on nicotine 

self-administration in rodents. Thus, other properties of 

bupropion, such as relief from withdrawal symptoms, may 

contribute to its efficacy as an aid to smoking cessation. 
Nicotine Addiction: Past and Present 131

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Neurosubstrates of Nicotine 

Dependence and Withdrawal

Nicotine Withdrawal Syndrome in Rodents

Smoking cessation leads to an aversive withdrawal 

syndrome lasting one to four weeks after cessation (Shiffman et al. 2004b). As noted previously, this withdrawal 

syndrome has affective, behavioral, somatic, and cognitive 

components (see “Physiological Mechanisms and Indicators: Nicotine Tolerance, Withdrawal, and Reinforcement” 

earlier in this chapter). The nicotine withdrawal syndrome 

is considered an important motivational factor that contributes to the perpetuation of nicotine dependence and 

continuing behaviors related to tobacco smoking (Markou et al. 1998; Kenny and Markou 2001). Withdrawal 

signs are often opposite to the acute effects of the drug 

(e.g., improved concentration versus poor concentration), 

probably reflecting the finding that the development of 

nicotine dependence leads to changes in brain function to 

counteract the acute effects of nicotine (e.g., increase in 

receptor number). 

One of the first and most widely used measures 

developed to investigate the neurobiology of the nicotine 

withdrawal syndrome and nicotine dependence is the frequency of somatic signs reliably observed in rats, but less 

reliably observed in mice (Malin et al. 1992; Epping-Jordan 

et al. 1998; Hildebrand et al. 1999; Isola et al. 1999; Carboni et al. 2000; Malin 2001; Semenova and Markou 2003; 

Salas et al. 2004). The most prominent somatic signs in 

rats are abdominal constrictions (writhes), gasps, ptosis, 

facial fasciculation, and eyeblinks. These somatic signs are 

both centrally and peripherally mediated (Hildebrand et 

al. 1999; Carboni et al. 2000; Watkins et al. 2000; Malin 

2001; Cryan et al. 2003). 

The somatic components of nicotine withdrawal 

are unpleasant. However, avoidance of the negative 

affect and depression-like components of withdrawal may 

play a more important role in the maintenance of nicotine 

dependence than do the somatic aspects of withdrawal 

(Hughes 1992; Kenny and Markou 2001). In rodents, a 

valid and reliable measure of the affective and motivational aspects of drug withdrawal is the elevation of brainreward thresholds observed after cessation of long-term 

administration of nicotine (Epping-Jordan et al. 1998; 

Harrison et al. 2001; Cryan et al. 2003; Semenova and 

Markou 2003). Elevations of reward thresholds are an 

operational measure of “diminished interest or pleasure” 

in rewarding stimuli (i.e., anhedonia), which is a symptom 

of nicotine withdrawal and a core symptom of depression 

(APA 1994). Similar threshold elevations are observed 

during withdrawal from all major drugs of abuse in rodents 

(Kokkinidis et al. 1980; Markou and Koob 1991; Schulteis et al. 1994, 1995; Paterson et al. 2000; Spielewoy and 

Markou 2003). Several dissociations have been identified 

between the threshold elevations and the somatic signs of 

nicotine withdrawal, and these observations are similar to 

those in clinical studies (see “Physiological Mechanisms 

and Indicators: Nicotine Tolerance, Withdrawal, and Reinforcement” earlier in this chapter). These findings suggest 

that the various aspects of withdrawal are mediated by 

different substrates (Epping-Jordan et al. 1998; Watkins 

et al. 2000; Harrison et al. 2001; Semenova and Markou 

2003). Other rodent models that may be relevant to the 

disruption of behavioral performance in humans involve 

(1) disruptions induced by termination of administration 

of nicotine on behavioral responses maintained by food 

(Carroll et al. 1989); (2) increases in the acoustic startle 

response in rats (Helton et al. 1993); and (3) decreases 

in prepulse inhibition (i.e., decrease in the adaptation 

response to a stronger stimuli after presentation of a prior 

weaker stimuli) in mice (Semenova et al. 2003). 

Important study data indicate that rats with threshold elevations reflecting a reward deficit associated with 

nicotine withdrawal can become conditioned to previously 

neutral environmental stimuli (Kenny and Markou 2005) 

(see “Learning and Conditioning” earlier in this chapter). 

Nicotine-dependent rats were presented with a light and 

tone CS and received injections of the nicotinic receptor antagonist DHβE for four consecutive days before an 

assessment of brain-reward thresholds. This procedure led 

to elevations of brain-reward thresholds in the nicotinedependent rats. When the rats were presented with just the 

light and tone CS on the test day, thresholds were again 

elevated, reflecting a conditioned state of negative affect. 

This type of conditioned affective response may lead to a 

relapse to tobacco smoking to alleviate this conditioned 

state of negative affect. This finding may partly explain the 

relapse observed months or even years after a person last 

smoked a cigarette. 

Subsequent data suggest that the experience of 

nicotine withdrawal in male adolescent rats may differ from that in adult rats. At the time of this review, no 

females have been tested. The evidence for this hypothesis 

is threefold. First, male adolescent rats displayed fewer 

somatic signs of nicotine withdrawal than did adult males. 

Second, although male adolescent rats displayed a conditioned place aversion produced by nicotine withdrawal, 

it was less robust than that seen in adult males. Third, 

adolescent male rats did not display the decreases in 

brain-reward function seen in adult rats experiencing 

withdrawal (O’Dell et al. 2006, 2007).
Surgeon General’s Report

132 Chapter 4

Neurochemical Correlates of Nicotine Withdrawal

Several experimental approaches are used to investigate the neuronal substrates of nicotine dependence and 

withdrawal. In vivo microdialysis studies provide information about the neurochemical changes occurring in 

specific brain sites with nicotine dependence. The precipitation of nicotine withdrawal in nicotine-treated rats, but 

not in controls, with administration of drugs that probe 

various transmitter systems and receptors suggests that 

chronic exposure to nicotine induces adaptations in specific transmitter systems and receptors. The combination 

of the in vivo microdialysis technique with the precipitated nicotine withdrawal technique indicates that the 

circuits mediating the acute effects of nicotine develop 

adaptations with nicotine dependence that lead to the 

withdrawal syndrome (Figure 4.4 depicts the brain structures and their interconnections forming circuits discussed in this chapter). 

During nicotine withdrawal precipitated by systemic 

or intra-VTA administration of the nAChR antagonist 

mecamylamine in nicotine-treated rats, dialysate levels 

of dopamine were decreased in the nucleus accumbens 

(Fung et al. 1996; Hildebrand et al. 1998; Carboni et al. 

2000) and in the central nucleus of the amygdala (Panagis et al. 2000). These mecamylamine injections into the 

VTA also produced, in a dose-dependent manner, most of 

the somatic signs of nicotine withdrawal (Hildebrand et al. 

1999). This finding suggests the involvement of nAChRs in 

the VTA in the expression of the somatic signs of nicotine 

withdrawal. Most important, similar decreases in levels of 

dopamine in the nucleus accumbens were observed in rats 

allowed to self-administer nicotine for 25 days, beginning 

24 to 48 hours after the last session for self-administration 

of nicotine (Rahman et al. 2004). Decreases in dopamine 

levels in the nucleus accumbens are also associated with 

withdrawal from other drugs of abuse, such as ethanol, 

morphine, cocaine, and amphetamine (Rossetti et al. 

1992). In contrast, the increases in dialysate dopamine 

levels observed in the frontal cortex (Hildebrand et al. 

1998; Carboni et al. 2000) were similar to those observed 

during withdrawal from other drugs of abuse (Imperato 

et al. 1986). Thus, it appears that common substrates are 

involved in the mediation of the withdrawal signs associated with different drugs of abuse that involve alterations 

in dopamine transmission in the nucleus accumbens and 

the frontal cortex. 

The smoking cessation aid bupropion, an atypical antidepressant, acts at least partly by inhibiting the 

neuronal uptake of dopamine, which thereby increases 

dopamine transmission (Nomikos et al. 1992). Bupropion reverses both the threshold elevations and the 

somatic signs associated with nicotine withdrawal (Cryan 

et al. 2003) in rats, although its effects on nicotine selfadministration are inconsistent (Glick et al. 2002; Bruijnzeel and Markou 2003; Shoaib et al. 2003). Taken together, 

the above data strongly suggest that a decrease in mesolimbic dopaminergic transmission mediates aspects of 

nicotine withdrawal. 

Another transmitter system that may be involved in 

nicotine dependence and withdrawal is the norepinephrine system. However, to date, the role of this system in 

nicotine dependence has not been investigated as extensively as that of the dopamine system. Acute administration of nicotine elevates extracellular noradrenaline levels 

in the nucleus accumbens (Schiffer et al. 2001), hippocampus (Brazell et al. 1991; Mitchell et al. 1993; Benwell 

and Balfour 1997), cortex (Summers and Giacobini 1995), 

amygdala, and hypothalamic paraventricular nucleus (Fu 

et al. 2001). These findings indicate that nicotine withdrawal may be characterized by a decrease in noradrenergic transmission. This hypothesis is supported by evidence 

for the beneficial effects on smoking cessation of nortriptyline, a norepinephrine reuptake inhibitor (Hughes et al. 

2004b) and the ameliorative effects of the α2-adrenoceptor 

agonist clonidine on nicotine withdrawal in double-blind, 

placebo-controlled studies (Covey and Glassman 1991). 

Other neurotransmitter systems such as serotonin, endocannabinoid, or opioid may also be involved 

in withdrawal, but research on these systems is limited. 

A few studies suggest the involvement of the opioid system. For example, naloxone precipitates somatic signs of 

withdrawal in nicotine-dependent rats (Malin et al. 1993; 

Watkins et al. 1999). Some studies also demonstrate the 

involvement of the serotonin system (see “Antidepressant 

and Antipsychotic Drugs and Nicotine Withdrawal” later 

in this chapter).

Receptors and Behavioral Signs of Nicotine 

Withdrawal

Studies document that administration of a variety 

of nAChR antagonists induces behavioral signs of withdrawal in addition to the neurochemical effects of withdrawal in nicotine-treated rats. Systemic or intra-VTA 

administration of mecamylamine or systemic or intraventricular administration of chlorisondamine induced 

somatic signs and/or elevation of reward threshold in 

nicotine-dependent rats only (Hildebrand et al. 1999; Watkins et al. 2000). Administration of the nAChR antagonist 

DHβE, which is selective for high-affinity nAChRs containing α4 (Harvey and Luetje 1996), induced threshold 

elevations (Epping-Jordan et al. 1998; Bruijnzeel and Markou 2004) but did not induce increases in somatic signs in 

nicotine-dependent rats (Epping-Jordan et al. 1998). This 

finding demonstrates that the threshold elevations are not 
Nicotine Addiction: Past and Present 133

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

due to nonspecific performance effects of the antagonists. 

Together, these results illustrate the involvement of 

nAChRs in the VTA in both the somatic and affective 

aspects of withdrawal. 

In addition, work in knockout mice demonstrates a 

critical role of β4 but not β2 nAChRs in the somatic signs 

of withdrawal (Salas et al. 2004; Jackson et al. 2008). β2 

nAChRs are critical for the reinforcing effects of nicotine (Picciotto and Corrigall 2002) and for the affective 

signs of nicotine withdrawal, as reflected in anxiety-like 

behavior and conditioned place aversion (Jackson et al. 

2008). The α7 homomeric nAChRs may be involved in the 

reinforcing effects of nicotine (Markou and Paterson 

2001) and perhaps only in some somatic aspects but not 

in the affective aspects of nicotine withdrawal (Markou 

and Paterson 2001; Jackson et al. 2008). Specifically, 

administration of the α7 nAChR antagonist methyllycaconitine did not precipitate either the typical 

somatic signs of nicotine withdrawal or the reward deficits 

reflected in threshold elevations in nicotine-dependent 

rats (Markou and Paterson 2001). However, in α7 knockout mice, no hyperalgesia was present during nicotine 

withdrawal, an effect seen in wild-type mice during nicotine withdrawal (Jackson et al. 2008). However, these 

α7 knockout mice showed normal levels of somatic and 

affective signs of nicotine withdrawal. Thus, the role of α7 

nAChRs may be limited to some somatic signs, including 

hyperalgesia, of nicotine withdrawal. Finally, α4 nAChRs 

have been shown to be involved in the reinforcing effects 

of nicotine (Tapper et al. 2004). Their role in nicotine 

withdrawal has not been clearly delineated, but it may 

influence both affective and somatic withdrawal effects 

(Salas et al. 2004; Gonzales et al. 2006; Jorenby et al. 2006; 

Jackson et al. 2008). Overall, the observation that nAChR 

antagonists precipitate the behavioral and neurochemical 

signs of withdrawal in nicotine-dependent rats, but not 

in controls, suggests that chronic exposure to nicotine 

induces a compensatory reduction in endogenous cholinergic tone that leads to the nicotine withdrawal syndrome.

Because glutamate stimulates dopamine release 

(Schilström et al. 1998a; Mansvelder and McGehee 2000), 

decreased glutamate transmission may mediate nicotine withdrawal. Systemic or intra-VTA administration 

of the mGluR subtype 2/3 (mGluR2/3) agonist LY314582 

led to withdrawal-like threshold elevations in nicotinedependent rats but not in control rats (Kenny et al. 2003). 

These mGluR2/3 receptors are found primarily presynaptically (i.e., on the transmitting neuron at the synaptic terminal that extends to the synapse, and the released 

transmitters target the postsynaptic neuron), where they 

inhibit glutamate transmission (Cartmell and Schoepp 

2000; Kenny and Markou 2004). The increased sensitivity 

of nicotine-dependent rats to an agonist at the presynaptic inhibitory mGluR2/3 suggests that nicotine 

dependence is characterized by increased inhibition of glutamate transmission through these receptors, resulting in 

decreases in the release of glutamate when nicotine is no 

longer present to stimulate glutamate release. Consistent 

with this hypothesis, the mGluR2/3 antagonist LY341495 

reversed the threshold elevations observed in rats that 

had spontaneous nicotine withdrawal (Kenny et al. 2003). 

Similarly, activity decreased in postsynaptic α-amino-3-

hydroxy-5-methyl-4-isoxazole proprionic/kainate receptors, although no adaptations in mGluR5 receptors were 

observed in nicotine-dependent rats (Kenny et al. 2003). 

This result was somewhat surprising considering the 

important role found for this receptor in the reinforcing effects of nicotine (Paterson et al. 2003; Paterson and 

Markou 2005). Taken together, all of the above findings 

indicate that decreased glutamate transmission resulting from adaptations in presynaptic and postsynaptic 

receptors may contribute to the affective aspects of nicotine withdrawal. 

These data on the lack of adaptations in mGluR5 

activity highlight the finding that not all systems involved 

in the reinforcing effects of nicotine develop changes with 

long-term exposure to nicotine. This notion is also supported by data demonstrating that there are no changes 

in GABA transmission, GABAB receptor activity, or α7 

nAChR activity in nicotine-dependent rats, despite the 

important role of the GABAB receptor and possibly the α7 

nAChR in the reinforcing effects of nicotine (Markou and 

Paterson 2001; Paterson and Markou 2002; Paterson et al. 

2004, 2005a,b). 

Molecular Mechanisms

Activated nAChRs are permeable to both sodium 

ions and Ca2+, which lead to activation of the neurons 

and thus the release of many transmitters (Wonnacott 

et al. 2005). The widespread brain activation induced by 

acute or long-term administration of nicotine is shown by 

the expression of C-FOS in areas such as the amygdala, 

bed nucleus of the stria terminalis, lateral septum, hypothalamic nuclei, striatum, parts of the cortex, superior 

colliculus, optic tract, interpeduncular nucleus, supramammillary nucleus, periaqueductal gray matter, nucleus 

of the solitary tract, and locus coeruleus (Merlo Pich et 

al. 1999). C-FOS–related antigens are C-FOS proteins 

that heterodimerize with C-JUN proteins to produce complexes of activator protein-1 and transcriptionally regulate 

large numbers of genes related to plasticity (Dobranzki et 

al. 1991; Merlo Pich et al. 1997).
Surgeon General’s Report

134 Chapter 4

Another protein researchers have studied extensively is the cyclic adenosine monophosphate–response 

element binding protein (CREB), because it is part of 

the signaling cascade for several receptors, including 

nAChRs (Nestler 2001). Acute treatment with nicotine 

had no effect on levels of total CREB or phosphorylated 

CREB (p-CREB). However, 18 hours after withdrawal 

from long-term administration of nicotine, total concentrations of CREB and p-CREB decreased in the shell but 

not in the core of the nucleus accumbens (Pluzarev and 

Pandey 2004) and in the medial and basolateral amygdala 

but not in the central amygdala (Pandey et al. 2001). The 

high Ca2+ permeability of nAChRs also leads to the stimulation of additional intracellular messenger systems such 

as calmodulin-dependent protein kinases, including Ca2+

calmodulin-dependent protein kinase II (CaMKII), which 

is the most abundant kinase in the brain (Schulman and 

Hanson 1993). Acute administration of nicotine in mice 

induced increases in CaMKII expression in the spinal cord 

that was involved in the antinociceptive effects of nicotine 

(Damaj 2000).

These are a few examples of the molecular changes 

observed after acute or long-term administration of 

nicotine and on withdrawal from long-term administration. These molecular changes demonstrate that nicotine 

induces changes in molecular mechanisms involved in 

long-term plasticity. Such molecular effects are likely to 

mediate several aspects of dependence on nicotine. 

Clinical Imaging Studies

Clinical imaging studies have confirmed findings 

from basic research in rodents and have provided additional critical information about brain sites and processes 

involved in tobacco addiction in humans that cannot 

readily be investigated in animals (e.g., hedonic responses 

and craving). Some of the effects of nicotine in various 

regions of the brain have also been described elsewhere 

(see “Learning and Conditioning” earlier in this chapter). Similar to other drugs of abuse, nicotine decreases 

global glucose metabolism in the brain, as determined 

by PET with [18F]fluorodeoxyglucose (Stapleton et al. 

2003). Long-term exposure to tobacco smoke also inhibits 

MAOA and MAOB activity (Volkow et al. 1999). Congruent 

with the suggested role of mesolimbic dopamine in the 

rewarding effects of nicotine in rodents, PET studies with 

[11C]raclopride indicate that cigarette smoking increased 

dopamine levels in the striatum of smokers (Brody et 

al. 2004b) and that the hedonic response of the smoker 

to cigarette smoking was proportional to the dopamine 

released in the striatum (Barrett et al. 2004). Other areas 

activated by nicotine or smoking are the prefrontal 

cortex, ventral putamen, anterior cingulated cortex, superior parietal cortex, and thalamus (Kumari et al. 2003; Rose 

et al. 2003b; Brody et al. 2004b; Fallon et al. 2004; Jacobsen et al. 2004; Brody 2006). Smoking-associated images 

during inductions of craving that often lead to smoking 

increased the functional magnetic resonance imaging signal in reward circuits such as the right posterior amygdala, posterior hippocampus, VTA, and medial thalamus 

(Due et al. 2002). As mentioned previously, long-term 

administration of bupropion attenuated cue-induced craving and led to blunted activation of the perigenual and 

ventral anterior cingulate cortex (Brody et al. 2004a). 

Functional magnetic resonance imaging was used 

in an interesting comparison of the effects of nicotine on 

the brains of patients with schizophrenia and the brains 

of control participants. Nicotine-induced activation of 

the anterior cingulate cortex and bilateral thalamus was 

greater in patients with schizophrenia than in control participants during performance of a cognitive task (Jacobsen et al. 2004). This finding suggests that nicotine may 

improve cognitive performance in patients with schizophrenia by enhancing the thalamocortical functional connectivity (Jacobsen et al. 2004) (see “Schizophrenia and 

Nicotine Dependence” later in this chapter). Relevant 

to the high prevalence of smoking among patients with 

depression, smokers showed cortical responses suggesting 

vulnerability to depression in a study that used tryptophan 

depletion to increase the depressed mood in smokers (Pergadia et al. 2004).

Psychiatric Comorbidity

Antidepressant and Antipsychotic Drugs and 

Nicotine Withdrawal

Another experimental approach used to identify systems that mediate nicotine withdrawal and dependence 

is a study of pharmacologic manipulations that reverse 

spontaneous nicotine withdrawal. Inferences can be made 

regarding the underlying abnormality associated with 

withdrawal through the mechanisms associated with the 

pharmacotherapy. On the basis of the phenomenological 

similarities among depression, the depression-like aspects 

of nicotine withdrawal, and the negative symptoms of 

schizophrenia, researchers hypothesize that overlapping 

neurobiologic substrates may mediate these depressive 

symptoms and that antidepressant and atypical antipsychotic treatments would alleviate the depression-like 

aspects of nicotine withdrawal (Markou et al. 1998; 

Markou and Kenny 2002). 

Such common substrates mediating nicotine dependence and psychiatric disorders may explain the high 
Nicotine Addiction: Past and Present 135

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

prevalence of tobacco smoking among psychiatric populations. Compared with the percentage of smokers in the 

general population (20 to 30 percent), a higher percentage 

of mentally ill patients were smokers (26 to 88 percent, 

depending on the mental illness) (Lasser et al. 2000), 

particularly those with schizophrenia, depression, or 

addiction to alcohol or other drugs (Hughes et al. 1986; 

Glassman et al. 1990; Breslau 1995). For illustrative purposes, substrates that mediate depression, schizophrenia, 

and nicotine dependence are described in the following sections.

Depression and Nicotine Dependence

Although the estimates vary across age, population, and criteria for tobacco dependence, most estimates 

suggest that the incidence of major depressive disorder 

among smokers is approximately two to three times that 

among nonsmokers (Hughes et al. 1986; Glassman et al. 

1988, 1990; Kandel et al. 2001; Fergusson et al. 2003). A 

history of major depression increased the risk for progression to daily smoking and nicotine dependence, and a history of daily smoking and nicotine dependence increased 

the risk for major depression (Breslau et al. 1993b, 1998). 

A depressed mood is one of the symptoms of tobacco 

withdrawal syndrome experienced by a significant proportion of persons who attempt to stop smoking (West et al. 

1984; Hughes and Hatsukami 1992; APA 1994). Therefore, 

tobacco smoking may be self-medication for either the 

depression that preceded the drug use or the smokinginduced depression (Pomerleau et al. 1978; Waal-Manning 

and de Hamel 1978; Hughes et al. 1986; Glassman 1993; 

Markou et al. 1998). 

In particular, 5HT and the 5HT1A receptors appear 

to be critically involved in the mode of action of several 

antidepressant drugs used clinically (Markou et al. 1998) 

and may play a role in nicotine withdrawal (Kenny and 

Markou 2001). Systemic administration of 5HT1A receptor agonists, such as 8-hydroxy-2-dipropylaminotetralin 

(8-OH-DPAT), exacerbated the increased startle response 

observed during nicotine withdrawal, whereas 5HT1A 

receptor antagonists (e.g., WAY-100635) alleviated this 

increased response (Rasmussen et al. 1997, 2000). In addition, the responsiveness of dorsal raphe nucleus neurons 

to 8-OH-DPAT increased during nicotine withdrawal (Rasmussen and Czachura 1997). Thus, nicotine withdrawal 

may increase the inhibitory influence of somatodendritic 

5HT1A autoreceptors in the raphe nuclei, and thereby 

decrease the release of serotonin in the forebrain and limbic brain sites (Benwell and Balfour 1979, 1982; Ridley 

and Balfour 1997). This conclusion is supported by the 

observation that a serotonergic antidepressant treatment 

involving the coadministration of the selective serotonin 

reuptake inhibitor fluoxetine and the 5HT1A receptor 

antagonist p-MPPI [4-(2ʹ-methoxy-phenyl)-1-[2ʹ-(n-2ʹʹpyridinyl)-p-iodobenzamido]ethyl-piperazine] rapidly 

reversed the elevation in thresholds of brain-stimulation 

reward observed in rats with nicotine withdrawal, but the 

treatment did not block the somatic signs of withdrawal 

(Harrison et al. 2001). Consistent with this finding, the 

5HT1A receptor partial agonist buspirone has shown limited efficacy in smoking cessation trials and may reduce 

the severity of withdrawal in persons attempting to stop 

smoking (West et al. 1991; Hilleman et al. 1992, 1994; 

Schneider et al. 1996). In conclusion, like depressions not 

induced by drugs, the depression-like aspects of nicotine 

withdrawal may be at least partly mediated by a decrease 

in monoaminergic transmission. 

Consistent with the hypothesis that shared substrates mediate nicotine dependence and depression, 

clinical trials indicate that two of the antidepressant drug 

treatments are efficacious aids for smoking cessation. 

The atypical antidepressant bupropion, which primarily 

inhibits the reuptake of dopamine, was more effective than 

a placebo in clinical trials to achieve smoking cessation 

(Fiore et al. 2008), and bupropion has been approved for 

this use by the U.S. Food and Drug Administration (FDA). 

Preclinical research suggests that bupropion reverses 

both the depression-like and somatic aspects of nicotine 

withdrawal (Cryan et al. 2003), although its effects on the 

rewarding effects of nicotine are inconsistent (Bruijnzeel 

and Markou 2003). In addition, the tricyclic antidepressant nortriptyline, which primarily inhibits the reuptake 

of norepinephrine, is recommended by WHO and the 

U.S. Public Health Service (Fiore et al. 2008) as a smoking cessation aid. In conclusion, similar monoaminergic 

mechanisms appear to be involved in both depression and 

nicotine dependence. 

Schizophrenia and Nicotine Dependence

More than 80 to 90 percent of patients with schizophrenia smoke compared with 20 to 30 percent of the 

general population (Masterson and O’Shea 1984; Goff et 

al. 1992; de Leon et al. 1995; Hughes 1996; Diwan et al. 

1998). Persons with schizophrenia are commonly heavy 

smokers (>1.5 packs of cigarettes per day); smoke high-tar 

cigarettes, which are also high in nicotine content; and 

extract more nicotine from cigarettes than do smokers without schizophrenia (Masterson and O’Shea 1984; 

Hughes et al. 1986; Olincy et al. 1997). 

The mesolimbic dopamine system and its efferent and afferent connections to other brain sites and 

systems, particularly dopamine-glutamate interactions, 

are strongly implicated in both the reinforcing effects of 

nicotine and schizophrenia (Snyder 1976; Carlsson 1977). 
Surgeon General’s Report

136 Chapter 4

Abnormalities in these systems may render patients with 

schizophrenia more susceptible to the rewarding effects 

of nicotine (Chambers et al. 2001). Such patients may 

use nicotine to counteract the cognitive and/or depression-like aspects of schizophrenia that are not effectively 

treated with most antipsychotic drugs (Markou and Kenny 

2002). Nicotine administration through tobacco smoking ameliorated visuospatial cognitive deficits of patients 

with schizophrenia (George et al. 2002) that involve the 

prefrontal cortex (Funahashi and Kubota 1994; GoldmanRakic 1995; Callicott et al. 1998; Kikuchi-Yorioka and 

Sawaguchi 2000; Manoach et al. 2000).

Two forms of sensory-gating deficits (the inability 

to ignore or filter out irrelevant sensory information) 

that patients with schizophrenia exhibit may be influenced by actions on α7 or other nAChRs (Freedman et al. 

1997; Adler et al. 1998). The two deficits are (1) auditory 

P50 gating, a form of sensory blocking, and (2) prepulse 

inhibition of the startle response. Thus, smoking may be 

a form of self-medication to compensate for these gating 

deficits. In support of this hypothesis, one study found 

that acute nicotine treatment reversed disruptions in prepulse inhibition induced in mice by the administration 

of the N-methyl-d-aspartate receptor antagonist phencyclidine, which mimics human psychosis (Spielewoy and 

Markou 2003).

Nicotine administration may be a form of selfmedication for the depression-like negative symptoms of 

schizophrenia. The atypical antipsychotic drug clozapine 

treats the negative symptoms of schizophrenia most effectively and has decreased tobacco smoking in some persons 

without any encouragement to reduce smoking (George 

et al. 1995). In addition, long-term pretreatment with clozapine attenuated the severity of the nicotine withdrawal 

syndrome in rats (Semenova and Markou 2003).

Summary and Future Directions

The VTA region of the brain and the dopamine neurotransmitter are primarily responsible for the positive 

reinforcing aspects of nicotine addiction. An increase in 

dopamine levels is mediated by nicotine directly stimulating nAChRs, primarily α4β2 and α7 homomeric nAChRs 

in the VTA. Nicotine stimulates nAChRs on glutamatergic terminals that release glutamate, an excitatory neurotransmitter, which results in increased dopamine release 

in the nucleus accumbens and the frontal cortex. Nicotine 

also excites nAChRs on GABA-releasing terminals. Thus, 

levels of GABA, an inhibitory neurotransmitter, are also 

increased by nicotine. However, the interplay between 

the quick desensitization of nAChRs on the GABA neuron and the higher doses of nicotine required to desensitize nAChRs on the glutamate neuron results in a greater 

increase in dopamine levels. A critical role may also be 

played by nicotine-induced increases in norepinephrine 

transmission, although the role of this transmitter system in nicotine dependence has not been investigated as 

extensively as that of the dopamine, glutamate, and GABA 

systems. The role of endocannabinoids, serotonin, and 

endogenous opiates in nicotine addiction is less certain. 

The neurophysiology associated with withdrawal 

symptoms may be based on the type of symptoms experienced (e.g., somatic versus affective). The nAChRs appear 

to be involved in both the somatic and affective components of nicotine withdrawal. Animal studies suggest that 

β4 plays an important role in the somatic symptoms of 

withdrawal, whereas β2 seems to play a role in the affective symptoms of withdrawal. The neuronal subunit α7 

may be involved only in some of the somatic (e.g., hyperalgesia) aspects of withdrawal. The role of α4 is unclear, but 

it may influence both affective and somatic withdrawal 

effects. Decreased mesolimbic dopaminergic transmission seems to mediate various aspects of the withdrawal 

syndrome. Noradrenergic and serotonergic systems 

may also play a role in withdrawal. Decreased glutamate 

transmission appears to mediate the affective aspects of 

withdrawal, but GABA transmission does not appear to 

change with withdrawal. Although not discussed in this 

section, some studies also suggest that a dysregulation 

in the hypothalamic-pituitary axis occurs subsequent to 

withdrawal (al’Absi et al. 2004), and this dysregulation 

has been associated with relapse to smoking (al’Absi et al. 

2005). In future research, the involvement of specific neuroreceptors and neurotransmitters relevant to the various 

aspects of addiction needs to be differentiated (see “Physiological Mechanisms and Indicators: Nicotine Tolerance, 

Withdrawal, and Reinforcement” earlier in this chapter).

Finally, understanding the pathophysiology of 

depression and schizophrenia, other psychiatric illnesses, 

and substance abuse disorders, as well as the effects of 

medications used to treat these disorders in smokers, may 

enhance understanding of the pathophysiology of nicotine 

addiction. Because of the high amount of overlap between 

prevalence of nicotine dependence and comorbid psychiatric disorders, the similar monoamines affected by these 

disorders, and the use of similar treatment medications, 

it is possible that common substrates mediate nicotine 

dependence and depression or schizophrenia, as well as 

other psychiatric disorders and can provide insight into 

effective treatments. 
Nicotine Addiction: Past and Present 137

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Genetics

There is strong evidence for a genetic influence on 

smoking behavior. Since the last Surgeon General’s report 

on nicotine addiction (USDHHS 1988), knowledge has 

significantly increased in this area. For example, estimates 

of heritability have been determined for various phenotypes of smoking behavior. Studies of molecular genetic 

association and linkage studies were conducted to identify 

loci that influence these phenotypes. Furthermore, pharmacogenetic studies of smoking cessation were undertaken to increase understanding of interactions between 

genes and treatments. This research offers the possibility 

of interventions for smoking cessation that are tailored to 

individual genotypes. 

Heritability of Smoking Behavior

Smoking behavior and nicotine addiction have generated far less research in behavioral genetics than have 

other addictive behaviors such as alcoholism. This is 

despite evidence from animal studies suggesting that key 

factors—such as the number and distribution of nicotinic

receptors and the development of nicotine tolerance—are

under a strong genetic influence (Stitzel et al. 2000). The 

evidence that does exist from studies of twins, adoption, 

and separated twins, however, has consistently suggested 

a strong genetic component in smoking behavior (Gilbert 

and Gilbert 1995). Behavioral genetics studies enable the 

contribution of genetic influences, environmental influence shared by persons such as twins or biologic relatives 

(shared environmental influences), and environmental 

influences unique to an individual (unique environmental influences) to be distinguished. The heritability coefficient itself reflects the genetic contribution. According 

to this evidence, inherited factors account for 28 to 85 

percent of the observed variation in current smoking 

behavior in the population from which the data were drawn 

(Gilbert and Gilbert 1995). Researchers have suggested that 

the evidence for a genetic influence on smoking behavior 

is stronger than that for a genetic influence on alcoholism (Heath et al. 1995). Moreover, these studies have also 

indicated that these genetic factors relate to two aspects of 

smoking behavior: initiation and persistence.

Smoking Initiation

By comparing concordance rates for being a current 

or former smoker versus a lifetime nonsmoker, researchers can estimate the genetic contribution to smoking initiation. Such comparisons suggest that genetic 

contributions to smoking initiation are substantial. For 

example, one study (Heath et al. 1995) reports heritability 

coefficients for smoking initiation of 0.44 in women and 

0.51 in men in a sample of Swedish adults born between 

1926 and 1958. This study also reports a strong influence 

of shared environmental factors on both smoking initiation and persistence, with little evidence of a role for 

unique environmental influences. Many additional studies have confirmed the heritability of smoking initiation, 

as well as smoking persistence and nicotine dependence 

(True et al. 1997; Kendler et al. 1999). Although the overall 

conclusion is robust, the specific heritability coefficients 

reported by individual studies are highly variable, ranging 

from less than 0.30 to more than 0.80 (Sullivan and Kendler 1999). This finding may be attributable to differences 

in the definitions of smoking initiation across studies. For 

example, current and former smokers are combined into 

a single “ever smoking” category in some studies, but not 

in others, and some studies require a threshold of exposure (e.g., 100 cigarettes smoked) and others do not have 

this requirement. Lack of critical attention to definition of 

phenotype may lead to inconsistencies across studies and 

to misleading conclusions.

The role of shared environmental influences on 

initiation of smoking and persistence in smoking is also 

inconsistent across populations, and some studies report 

minimal shared environmental influences (Heath et al. 

1993). Differences in heritability coefficients by gender 

are generally not reported or are minimal, although one 

study (Hamilton et al. 2006) that tested differences by 

gender in the magnitude of genetic and environmental 

effects in a large cohort of twins indicated significantly 

higher heritability for smoking initiation in males than 

in females but no significant differences for smoking persistence. In that study, heritability for smoking initiation 

was defined as having smoked 100 or more cigarettes over 

their lifetime. In contrast, however, one meta-analysis (Li 

et al. 2003) reported higher heritability for smoking initiation in females than in males and higher heritability for 

smoking persistence in males than in females. Together, 

the evidence supports the importance of both genetic and 

shared environmental factors on smoking initiation. However, the relative importance of these factors is highly variable across populations. For example, one study reports 

different heritability coefficients for smoking behaviors in 

African Americans compared with White Americans (True 

et al. 1997). Nevertheless, evidence from non-Western 

cultures (Niu et al. 2000) suggests that the genetic 

influence on smoking behavior remains an important risk 
Surgeon General’s Report

138 Chapter 4

factor even in populations with much higher prevalence of 

smoking (e.g., in China). Reported heritability coefficients 

may vary with environmental factors such as the prevalence of smoking. For example, some of the highest heritability coefficients for smoking initiation are reported in 

studies on the population of twins during the Vietnam era, 

in which the participants were members of the U.S. Army 

at a time when smoking prevalence in the military was 

very high (True et al. 1997). This natural experiment, in 

which environmental variation in smoking initiation was 

minimized, may account for the high heritability coefficients in this study.

Smoking Persistence and Nicotine Dependence

Understanding smoking initiation is important to 

elucidate the etiology of nicotine addiction. However, 

smoking persistence is responsible for the adverse health 

consequences of smoking. The evidence for a genetic 

influence on smoking persistence (i.e., studies comparing 

current smokers with former smokers) is also strong. Several studies reported heritability coefficients of more than 

0.50 for smoking persistence (Heath and Martin 1993) 

and nicotine dependence (Broms et al. 2007) in both 

men and women, and some studies (Sullivan and Kendler 

1999; Vink et al. 2004) reported heritabilities of more than 

0.70 for nicotine dependence. Studies of multiple indices 

of nicotine dependence (Lessov et al. 2004) indicate that 

salient behavioral indices are similar for women and men, 

with measures such as time to the first cigarette in the 

morning and the number of cigarettes smoked per day 

that may represent the most highly heritable symptoms 

of nicotine dependence for both women and men. Interpreting these results is complicated because genetic factors that influence smoking initiation may also influence 

smoking persistence and subsequent dependence. Some 

data (True et al. 1999) also suggest a common genetic 

vulnerability to nicotine and alcohol dependence in men. 

The balance of evidence suggests that the risk of smoking 

initiation is influenced by both genetic and environmental 

factors (True et al. 1997). However, the risk of smoking 

persistence is more strongly a function of genetic factors 

and some of the genetic influences on smoking behavior 

contribute to a risk for both smoking initiation and persistence (Kendler et al. 1999). Few studies have directly 

assessed the heritability of smoking cessation. However, 

one research study (Xian et al. 2003, 2005) indicated a 

heritability of 0.54 for failed smoking cessation, and another (Broms et al. 2006) suggests that genetic factors are 

related to the number of cigarettes smoked per day and to 

smoking cessation but are largely independent of smoking initiation. Another study (Pergadia et al. 2006) has 

reported genetic influences specific to nicotine withdrawal, which may contribute both to smoking persistence and smoking cessation. However, because evidence 

from studies of twins and of adoption strongly indicates 

a genetic component in other aspects of smoking behavior, smoking cessation may also be strongly influenced by 

genetic factors.

Molecular Genetic Research on 

Smoking Behavior

Consistent evidence for the heritability of smoking behaviors led to molecular genetic studies designed 

to elucidate the specific genetic factors and biologic 

mechanisms involved in nicotine addiction. Two general 

scientific approaches to address this question include 

genetic linkage analysis and candidate gene studies. In 

linkage analysis, genetic variants or markers throughout 

the genome are tested within families (e.g., sibling pairs) 

and examined to identify markers that cosegregate with 

the trait of interest (e.g., nicotine dependence). This is a 

hypothesis-generating approach and does not require a 

priori knowledge about the biologic pathways involved. 

In contrast, studies of candidate genes, which are based 

on associations, use case-control methods to compare 

the prevalence of variants of candidate genes in two 

unrelatedgroups—for example,personswhoaredependent

on nicotine and those who are not dependent on nicotine. 

Although case-control studies have greater statistical 

power and are less costly than linkage analysis, such studies are not designed to identify novel genetic loci. 

Cigarette smoking and nicotine dependence are 

complex traits arising from the interplay of multiple 

genetic and environmental influences. As mentioned previously (see “Definition of Nicotine Addiction” earlier in this 

chapter), definition of phenotype is a critical factor in genetic 

studies. Many genes are likely involved in smoking—for

example, genes that influence the positive rewarding 

effects of nicotine, those that contribute to withdrawal 

symptoms and the negative reinforcing effects of nicotine 

(Pomerleau 1995), and those that determine general susceptibility to addiction (Nestler 2000). Interacting effects 

such as personality and environment are likely to also 

play an important role (Heath et al. 1995). Issues such as 

population heterogeneity (e.g., age, gender, and ethnicity) and bias (false positives results) introduced by ethnic 

admixture in study populations may also have a substantial impact on the outcome of association-based studies 

and may contribute to problems in replicating results 

(Munafò and Flint 2004).
Nicotine Addiction: Past and Present 139

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Table 4.5 Genetic linkage studies of smoking behavior phenotypes
Surgeon General’s Report

140 Chapter 4

Linkage Studies

Representative genetic linkage studies of smoking 

behavior phenotypes up to mid-2005 are shown in Table 

4.5, although several of these report data from the same 

study samples (e.g., Collaborative Studies on the Genetics of Alcoholism and the Framingham Heart Study). 

Despite the success of linkage approaches in unraveling the 

genetic antecedents of disease (Menzel 2002), these initial 

findings about smoking behavior have not been consistent. Potential explanations include lack of refinement in 

phenotype definition and the relatively small sample sizes 

in some studies of smoking behavior. Subsequent studies 

have taken into account the complexity and heterogeneity 

of the nicotine dependence phenotype by using alternate 

measures, such as heavy smoking, severity of withdrawal, 

and history of smoking cessation (Li et al. 2006; Swan et 

al. 2006). These data suggest that different genetic loci 

are linked to different measures and support a multidimensional concept of the nicotine dependence phenotype 

(Swan et al. 2006). 

In addition to linkage studies, investigations using 

an approach of genomewide association can also reveal 

promising novel candidate genes for nicotine dependence (Bierut et al. 2007). With advancements in genotyping technology, phenotype definition, and analytic 

approaches, both case-control studies and linkage analysis 

will likely identify an increasing number of associations 

with novel variants important in nicotine dependence 

(Li 2006). Examples include NTRK2 (Beuten et al. 2007), 

GABARAP (Lou et al. 2007), CHRNA5 (Saccone et al. 

2007), and ANKK1 (Gelernter et al. 2006).

Table 4.5 Continued
Nicotine Addiction: Past and Present 141

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Candidate Gene Studies

A variety of plausible candidate genes have been 

examined for associations with smoking behavior. Most 

of these studies have focused on genetic variations in 

relevant neurotransmitter pathways, nicotine-metabolizing enzymes, or nAChRs. Genetic variants of relevant 

neurotransmitter pathways may have more generalized 

influences on addictive behaviors. Genes for nicotinemetabolizing enzymes and nAChRs may be specific for 

effects on nicotine dependence.

Nicotine Metabolism

To date, more than 20 published studies of candidate 

genes have investigated genes involved in the nicotine 

metabolism pathway (Table 4.6). Most of these studies investigated CYP2A6, for which researchers have identified 

functional genetic variants (Xu et al. 2002). Variants associated with *NULL activity (e.g., *2/*4) or reduced activity 

(*9/*12) are associated with reduced levels of the CYP2A6 

enzyme and slower rates of nicotine metabolism, resulting in higher plasma nicotine levels from a given dose 

of nicotine (Malaiyandi et al. 2006). Thus, persons who 

carry these low activity alleles tend to have a lower risk of 

becoming smokers and, if they smoke, have slower rates 

of nicotine metabolism and tend toward reduced cigarette consumption compared with persons with a wildtype genotype (e.g., *1/*1). Furthermore, evidence from a 

meta-analysis that compared current versus former smokers suggests that the CYP2A6 alleles for reduced activity 

may increase the likelihood of smoking cessation (Munafò 

et al. 2004). However, the results are not consistent within 

or across all studies (Table 4.6). These inconsistencies may 

be attributable to relatively small sample sizes in some 

studies and differences in definition of phenotype and ethnic ancestry and genetic background. 

Some studies investigated other cytochrome genes 

(CYP2D6 and CYP2E1), but evidence for a significant 

and reproducible role of these variants has not emerged, 

perhaps because the role of these enzymes in nicotine 

metabolism is limited.

Neuronal Nicotinic Receptors 

Researchers have examined several genes for nAChR 

subunits to discover associations with smoking status 

(Table 4.7). The genes CHRNA4, CHRNA7, and CHRNB2

code for the α4, α7, and β2 subunits, respectively. However, because the functional relevance of variation in 

these genes is not known, these studies have explored 

associations of single nucleotide polymorphisms (SNPs) 

of unknown functional significance. To date, there is no 

evidence for associations of SNPs in the CHRNB2 gene 

with smoking behavior. However, two studies provide 

evidence for the role of CHRNA4 in nicotine dependence 

(Feng et al. 2004; Li et al. 2005). A small study of smokers with schizophrenia indicated that the CHRNA7 gene 

may be associated with smoking status. The relevance 

of this finding in the general population of smokers is 

unknown. However, studies have reported that these 

nAChR subtypes play a role in reinforcing the effects of 

nicotine and possibly withdrawal (see “Pathophysiology 

of Nicotine Addiction” earlier in this chapter). Moreover, 

because of the history of failure to replicate initial significant findings, these single studies require replication 

before the evidence can be considered to be confirmed. 

Recently, genomewide scans have revealed an association of novel genes, such as NRXN1 and NRXN3, with 

nicotine dependence (Bierut et al. 2007). In addition, 

genomewide association and candidate gene studies have 

identified associations of smoking behavior and nicotine dependence with SNPs in the CHRNA5/CHRNA3/

CHRNB4 gene cluster and in CHRNB3, which code for the 

nicotinic receptor subunits α5, α3, β4 and β3, respectively 

(Saccone et al. 2007; Berrettini et al. 2008; Bierut et al. 

2008; Grucza et al. 2008; Sherva et al. 2008; Stevens et al. 

2008; Thorgeirsson et al. 2008; Weiss et al. 2008; Caporaso 

et al. 2009; Chen et al. 2009).

Dopaminergic and Serotonergic 

Neurotransmitter and Receptor Systems

A large number of candidate gene studies have 

investigated genes involved in the dopamine pathway, 

and most have investigated the gene for the dopamine 

receptor D2 (DRD2) (Table 4.8). Most studies of the DRD2

*TAQ1A polymorphism have reported an association with 

smoking behavior, typically smoking status, but a substantial number have shown no association. Moreover, the 

functional significance of the *TAQ1A polymorphism remains unclear, although there is some reported evidence 

for an association with the density of D2 receptors in the 

brain. One study investigated the functional DRD2-141C

*INS/*DEL polymorphism and reported a significant 

association with smoking status (Yoshida et al. 2001). A 

modest number of studies have investigated other genes 

for dopamine receptors (DRD1, DRD4, and DRD5), DAT, 

and genes involved in dopamine synthesis and metabolism, including tyrosine hydroxylase (an enzyme that converts amino acid l-tyrosine to dihydroxyphenylalanine, a 

precursor of dopamine), DβH (an enzyme that converts 

dopamine to norepinephrine), and COMT (an enzyme that 

degrades dopamine). 
Surgeon General’s Report

142 Chapter 4

Table 4.6 Studies of candidate genes for nicotine metabolism and smoking behavior

Population

Study

(country) Study group Controls

Dominant 

ancestry Gene

Cholerton et al. 1996

(United Kingdom)

100 current smokers 104 lifetime nonsmokers NR CYP2D6

Boustead et al. 1997

(United Kingdom)

100 current smokers None NR CYP2D6

Pianezza et al. 1998

(Canada)

164 nicotine-dependent 

smokers

80 alcohol- and tobaccodependent smokers

184 nonnicotine-dependent and 

former smokers

European CYP2A6

London et al. 1999

(United States)

299 current or former 

smokers

161 lifetime nonsmokers NR CYP2A6

Gu et al. 2000

(United Kingdom)

142 current smokers 501 former smokers

389 lifetime nonsmokers

European CYP2A6

Rao et al. 2000

(Canada)

292 current smokers NA European CYP2A6

Saarikoski et al. 2000

(Finland)

85 current smokers 236 variable smokers

264 lifetime nonsmokers

European CYP2A6

Tiihonen et al. 2000

(Finland)

285 current smokers 680 former smokers or lifetime 

nonsmokers

European CYP2A6

Loriot et al. 2001

(United States)

65 current smokers 142 former smokers European CYP2A6

Schulz et al. 2001

(Germany)

130 current smokers 108 former smokers

109 lifetime nonsmokers

European CYP2A6

Tan et al. 2001

(China)

380 persons who ever 

smoked

246 lifetime nonsmokers East Asian CYP2A6

Zhang et al. 2001

(Japan)

96 current smokers 141 nonsmokers East Asian CYP2A6

Ando et al. 2003

(Japan)

57 current smokers 44 former smokers

139 lifetime nonsmokers

East Asian CYP2A6

Howard et al. 2003

(Canada)

1,512 smokers and 

nonsmokers

NA Multiple 

(stratified)

CYP2E1

Minematsu et al. 2003

(Japan)

92 current smokers 

111 former smokers

123 nonsmokers East Asian CYP2A6

Fujieda et al. 2004

(Japan)

1,705 smokers NA East Asian CYP2A6

Iwahashi et al. 2004

(Japan)

103 smokers

101 nonsmokers

NA East Asian CYP2A6

O’Loughlin et al. 2004

(Canada)

228 adolescents who 

inhaled

NA European CYP2A6
Nicotine Addiction: Past and Present 143

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Study

(country) Polymorphism Primary phenotype Main findings

Cholerton et al. 1996

(United Kingdom)

*3, *4A, *5 Smoking status No association with smoking status

Boustead et al. 1997

(United Kingdom)

*3, *4A, *5 Cigarettes/day

Nicotine dependence

Association with nicotine dependence

Pianezza et al. 1998

(Canada)

*1, *2, *3 Nicotine dependence Association with nicotine dependence (dependent 

vs. nondependent smokers) and amount smoked

London et al. 1999

(United States)

*1, *2, *3 Smoking status

Cigarettes/day

Marginal association with smoking status (lifetime 

nonsmokers vs. current and former smokers)

Gu et al. 2000

(United Kingdom)

*1, *2, *NULL

(allele not stated)

Smoking status

Cigarettes/day

Association with smoking status (former vs. 

current smokers and lifetime nonsmokers)

Rao et al. 2000

(Canada)

*1, *2, *4,

duplication

Cigarettes/day Association with cigarettes/day

Saarikoski et al. 2000

(Finland)

*1, *2, *3, *4B, 

*4C, *5, *10, *16

Smoking status Association with smoking status (heavy vs. 

variable smokers and lifetime nonsmokers)

Tiihonen et al. 2000

(Finland)

*NULL (allele not 

stated)

Smoking status

Cigarettes/day

No association with smoking status or cigarettes/

day

Loriot et al. 2001

(United States)

*1, *2, *4 Cigarettes/day No association with cigarettes/day

Schulz et al. 2001

(Germany)

*1, *2, *3 Smoking status 

Cigarettes/day

No association with smoking status or cigarettes/

day

Tan et al. 2001

(China)

*1, *4 Smoking status 

Pack-yearsa

No association with smoking status or pack-years

Zhang et al. 2001

(Japan)

*1, *DEL Smoking status 

Cigarettes/day

No association with smoking status or cigarettes/

day

Ando et al. 2003

(Japan)

*1A, *1B, *4C Smoking status 

Cigarettes/day

No association with smoking status or cigarettes/

day

Howard et al. 2003

(Canada)

*1C, *1D Nicotine dependence

Cotinine levels/cigarette

Cigarettes/day

Association with nicotine dependence in those of 

East Asian ancestry and cotinine concentrations/

cigarette in those of African ancestry

Minematsu et al. 2003

(Japan)

*1, *3, *DEL Smoking status

Pack-years

Association with pack-years among current and 

former smokers

Fujieda et al. 2004

(Japan)

*1A, *1B, *4, *7, 

*9, *10, *11

Cigarettes/day Association with cigarettes/day

Iwahashi et al. 2004

(Japan)

*1A, *1B, *4C Smoking status Association with smoking status

O’Loughlin et al. 2004

(Canada)

*1, *2, *4, *9, *12 Nicotine dependence

Cigarettes/day

Association with increased risk of acquisition of 

nicotine dependence, but reduced cigarettes/day 

among those who become dependent
Surgeon General’s Report

144 Chapter 4

Table 4.6 Continued

Population

Study

(country) Study group Controls

Dominant 

ancestry Gene

Schoedel et al. 2004

(Canada)

375 current smokers 224 nonsmokers European CYP2A6

Vasconcelos et al. 2005

(Brazil)

144 current smokers

61 former smokers

207 nonsmokers Mixed CYP2A6

Note: NA = not applicable; NR = data not reported. aPack-years = the number of years of smoking multiplied by the number of packs of cigarettes smoked per day.

Table 4.7 Studies of candidate genes for neuronal nicotine receptors and smoking behavior

   Population      

Study

(country) Study group Controls

Dominant 

ancestry Gene

Silverman et al. 2000

(United States)

317 high- and 238 low-nicotine 

dependent smokers

317 nonsmokers European CHRNB2

Lueders et al. 2002

(United States)

184 current smokers 132 former smokers 

427 lifetime nonsmokers

European CHRNB2

De Luca et al. 2004

(Canada)

108 current smokers 

with schizophrenia

69 current nonsmokers 

with schizophrenia

European CHRNA7

Feng et al. 2004

(China) 

577 male smokers from 

206 families

Family-based design East Asian CHRNA4

Li et al. 2005

(United States)

1,568 smokers from 

602 families

Family-based design European and 

African

CHRNA4

CHRNB2

Of the published studies of candidate genes involved 

in the serotonin pathway, eight investigated 5HTT, and 

three investigated TPH, which is involved in serotonin 

synthesis (Table 4.9). All but one study of the functional 

5HTTLPR polymorphism found an association with smoking behavior. Three additional studies investigated the 

MAOA gene, which is involved in metabolism of both 

dopamine and serotonin and in norepinephrine pathways. Two of the three studies reported an association 

with smoking behavior that included both smoking status and cigarette consumption. Other studies of candidate 

genes are summarized in Table 4.10. Research is notably 

lacking on genes involved in glutamatergic and GABAergic mechanisms, despite basic research indicating the 

neurobiologic effects of nicotine on these systems. One 

study (Beuten et al. 2005) reports a significant association 

between a haplotype of SNPs in the GABAB2 gene and nicotine dependence.

In summary, a few candidate genes appear to be 

associated with smoking behavior. Meta-analysis is a 

potentially powerful tool for assessing population-wide 

effects of candidate genes on complex behavioral phenotypes, such as smoking, although such meta-analysis 

requires that the phenotypes examined across studies 

are similar. It may also provide evidence for unrevealed 

diversity, such as heterogeneity in apparently similar 

populations (Munafò and Flint 2004). Despite the large 

number of studies reporting on the association between 

specific candidate genes and smoking behavior, one metaanalysis (Munafò et al. 2004) highlights the lack of depth 

of the research compared with the breadth that exists. 

The conclusion is that the “...evidence for a contribution of specific genes to smoking behavior remains modest” (p. 583). In this analysis, 5HTT and CYP2A6 were the 

only candidate genes for which there was evidence of an 

association with smoking behavior. Studies published 
Nicotine Addiction: Past and Present 145

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Study

(country) Polymorphism Primary phenotype Main findings

Schoedel et al. 2004

(Canada)

*1A, *1B, *2, *4, *5, *6, 

*7, *8, *9, *10, *12

Smoking status 

Cigarettes/day

Association with smoking status and 

cigarettes/day

Vasconcelos et al. 2005 

(Brazil)

*1A, *1B, *2, *4, *9 Smoking status Association with smoking status (current and 

former smokers vs. nonsmokers) among those 

of European and mixed ancestry

Study

(country) Polymorphism Primary phenotype Main findings

Silverman et al. 2000

(United States)

Multiple Smoking status 

Nicotine dependence

No association with smoking status or 

nicotine dependence

Lueders et al. 2002

(United States)

Haplotype Smoking status 

Nicotine dependence

No association with smoking status or 

nicotine dependence

De Luca et al. 2004

(Canada)

D15S1360 Smoking status Association with smoking status (current 

smokers vs. nonsmokers)

Feng et al. 2004

(China) 

Haplotype Nicotine dependence Association with nicotine dependence

Li et al. 2005

(United States)

Haplotype

Haplotype

Nicotine dependence Association of CHRNA4 gene with nicotine 

dependence

No association with CHRNB2 gene

more recently strongly indicate that SNPs in the CHRNA5/

A3/B4 gene cluster are associated with smoking behavior 

and nicotine dependence (Berrettini et al. 2008; Bierut et 

al. 2008; Grucza et al. 2008; Sherva et al. 2008; Stevens 

et al. 2008; Thorgeirsson et al. 2008; Weiss et al. 2008; 

Caporaso et al. 2009; Chen et al. 2009; Saccone et al. 2009). 

Nonetheless, the relatively small effects and evidence for 

substantial heterogeneity between studies suggest that 

extreme care is necessary in the design of case-control 

studies of genetic association.

Pharmacogenetic Approaches

The basic premise of the pharmacogenetic approach 

is that inherited differences in drug metabolism and drug 

targets have important influence on the toxic effects and 

the efficacy of treatment (Evans and Relling 1999; Poolsup 

et al. 2000). Advantages of a pharmacogenetic approach to 

the study of smoking cessation treatments include (1) use 

of more refined phenotypes for genetic analyses, which is 

facilitated by prospective assessment of withdrawal symptoms, side effects of treatment, and measures of the level 

of reward from nicotine; (2) use of various treatment conditions to aid smoking cessation; and (3) use of experimental designs that control the dosing and timing of the 

therapy (Lerman and Niaura 2002; Munafò et al. 2005b; 

Caporaso et al. 2009).

Nicotine Replacement Therapy

To date, two pharmacogenetic trials of NRT have 

been conducted. One placebo-controlled trial using the 

nicotine patch by a large group of general practice physicians in the United Kingdom (Johnstone et al. 2004b; 

Yudkin et al. 2004) focused on variations in the dopamine pathway, including the DβH and DRD2 genes. The 
Surgeon General’s Report

146 Chapter 4

Table 4.8 Studies of candidate genes for dopamine and smoking behavior

   Population      

Study

(country) Study group Controls

Dominant

ancestry Gene

Noble et al. 1994

(United States)

57 current smokers 115 former smokers 

182 lifetime nonsmokers

European DRD2

Comings et al. 1996

(United States)

312 current smokers 714 lifetime nonsmokers European DRD2

Comings et al. 1997

(United States)

371 current smokers 126 lifetime nonsmokers European DRD1

DRD2

Lerman et al. 1997

(United States)

315 current smokers 232 lifetime nonsmokers European TH

Shields et al. 1998

(United States)

283 current smokers 192 lifetime nonsmokers European and 

African

DRD4

Singleton et al. 1998

(United Kingdom)

104 current smokers 117 lifetime nonsmokers NR DRD2

Spitz et al. 1998

(United States)

46 current smokers 67 former smokers 

13 lifetime nonsmokers

European DRD2

Lerman et al. 1999

(United States)

289 current smokers 233 lifetime nonsmokers European and 

African

DRD2

DAT

Sabol et al. 1999

(United States)

283 current smokers 231 former smokers 

593 lifetime nonsmokers

European DAT

Batra et al. 2000

(Germany)

110 nicotine-dependent 

smokers 

60 nonnicotine-dependent or 

light smokers

NR DRD2

Bierut et al. 2000

(United States)

388 habitual smokers

566 nonhabitual smokers

Family-based study European DRD2

Costa-Mallen et al. 2000

(United States)

152 newly diagnosed 

Parkinson’s disease patients

231 with no history of 

Parkinson’s or other 

neurodegenerative disease

European DRD2

Jorm et al. 2000

(Australia)

198 current smokers 211 former smokers 

452 lifetime nonsmokers

European DAT

McKinney et al. 2000

(United Kingdom)

225 current smokers No controls European DβH

MAOA

COMT

Wu et al. 2000

(United States)

73 current smokers 61 former smokers 

88 lifetime nonsmokers

European and 

African

DRD2

Sullivan et al. 2001

(United States)

595 current smokers 338 lifetime nonsmokers European DRD5

Yoshida et al. 2001

(Japan)

77 current smokers 57 former smokers 

198 lifetime nonsmokers

East Asian DRD2

David et al. 2002

(United Kingdom)

266 current smokers 270 former smokers 

265 lifetime nonsmokers

NR COMT
Nicotine Addiction: Past and Present 147

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Study

(country) Polymorphism Primary phenotype Main findings

Noble et al. 1994

(United States)

*TAQ1A Smoking status Association with smoking status (current and former 

smokers vs. lifetime nonsmokers)

Comings et al. 1996

(United States)

*TAQ1A Smoking status Association with smoking status

Comings et al. 1997

(United States)

DDE1

*TAQ1A

Smoking status 

Packs/day

Association of DRD1 and DRD2 genes with smoking status 

and packs/day

Lerman et al. 1997

(United States)

VNTR Smoking status No association with smoking status

Shields et al. 1998

(United States)

VNTR Smoking status 

Cigarettes/day

Association with smoking status in participants of African 

ancestry

Singleton et al. 1998

(United Kingdom)

*TAQ1A Smoking status 

Nicotine dependence

No association with smoking status or nicotine dependence

Spitz et al. 1998

(United States)

*TAQ1A

*TAQ1B

Smoking status 

Age at smoking 

initiation

No association with smoking status

Association of both polymorphisms with age at smoking 

initiation 

Lerman et al. 1999

(United States)

*TAQ1A

VNTR

Smoking status Association of DAT and DRD2 genes with smoking status in 

participants of European ancestry

Sabol et al. 1999

(United States)

VNTR Smoking status Association with smoking status (current vs. former 

smokers)

Batra et al. 2000

(Germany)

FOK1

*TAQ1A

Smoking status Association of FOK1 polymorphism with smoking status 

(nicotine-dependent vs. nonnicotine-dependent or light 

smokers)

Bierut et al. 2000

(United States)

*TAQ1A

*INTRON 2

Smoking status No association with smoking status

Costa-Mallen et al. 

2000

(United States)

*TAQ1A

*TAQ1B

Smoking status No association with smoking status

Jorm et al. 2000

(Australia)

VNTR Smoking status No association with smoking status

McKinney et al. 2000

(United Kingdom)

G1368A

C1460T A1947G

(*VAL/*MET)

Cigarettes/day Association of DβH and MAOA genes with cigarettes/day

Wu et al. 2000

(United States)

*TAQ1A

*TAQ1B

Smoking status 

Cigarettes/day

Association of both polymorphisms with smoking status 

(current vs. former smokers and lifetime nonsmokers) and 

cigarettes/day

Sullivan et al. 2001

(United States)

Haplotype Smoking status 

Nicotine dependence

No association with smoking status

Association with nicotine dependence, although marginal

Yoshida et al. 2001

(Japan)

*TAQ1A

-141C *INS/*DEL

Smoking status Association of TAQ1A polymorphism only with smoking 

status (current vs. former smokers and lifetime 

nonsmokers)

David et al. 2002

(United Kingdom)

A1947G 

(*VAL/*MET)

Smoking status No association with smoking status
Surgeon General’s Report

148 Chapter 4

Table 4.8 Continued

   Population      

Study

(country) Study group Controls

Dominant

ancestry Gene

Hamajima et al. 2002

(Japan)

226 current smokers 133 former smokers 

434 lifetime nonsmokers

East Asian DRD2

Johnstone et al. 2002

(United Kingdom)

1,524 current smokers NA European DβH

MAOA

Qi et al. 2002

(China)

174 current smokers 152 former smokers and 

lifetime nonsmokers

East Asian DRD2

Vandenbergh et al. 2002

(United States)

98 current smokers 153 former smokers 

114 nonsmokers

214 lifetime nonsmokers

European DAT

Ito et al. 2003

(Japan)

147 current smokers 99 former smokers

258 lifetime nonsmokers

East Asian MAOA

MAOB

Lee et al. 2003

(South Korea)

94 current smokers 93 lifetime nonsmokers East Asian DRD2

Anney et al. 2004

(Australia)

51 nicotine-dependent 

smokers

186 nonnicotine-dependent 

smokers

European TH

Audrain-McGovern et al. 

2004a

(United States)

292 adolescents who ever 

smoked

NA European DRD2

DAT

Johnstone et al. 2004b

(United Kingdom)

732 current smokers 243 lifetime nonsmokers European DRD2

Ling et al. 2004

(China)

668 current smokers Family-based study East Asian DAT

Luciano et al. 2004

(Australia)

769 current smokers and 

nonsmokers

Family-based study European DRD4

Olsson et al. 2004

(Australia)

77 nicotine-dependent 

smokers

39 nonnicotine-dependent 

smokers

European TH

Colilla et al. 2005

(United States)

277 female current smokers 505 female former smokers European and 

African

COMT

Costa-Mallen et al. 2005

(United States)

232 persons who ever 

smoked

158 lifetime nonsmokers European DRD2

MAOB

Elovainio et al. 2005

(Finland)

37 current smokers 113 nonsmokers European DRD4

Freire et al. 2006

(Brazil)

220 alcoholic and 

nonalcoholic smokers

112 nonsmokers European DRD2

DβH

Laucht et al. 2005

(Germany)

184 adolescents who ever 

smoked

119 adolescent lifetime 

nonsmokers

European DRD4

Zetteler et al. 2005

(United Kingdom)

141 current smokers NA European DβH

Note: NA = not applicable; NR = data not reported.
Nicotine Addiction: Past and Present 149

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Study

(country) Polymorphism Primary phenotype Main findings

Hamajima et al. 2002

(Japan)

MBO1

*TAQ1A

Smoking status Association of TAQ1A polymorphism only with smoking 

status in men (current vs. former smokers and lifetime 

nonsmokers)

Johnstone et al. 2002

(United Kingdom)

G1368A

C1460T

Cigarettes/day No association with cigarettes/day

Qi et al. 2002

(China)

*TAQ1A

*TAQ1B

Smoking status

Cigarettes/day

Association of *TAQ1A polymorphism only with cigarette 

use

No association with smoking status

Vandenbergh et al. 

2002

(United States)

VNTR Smoking status Association with smoking status (lifetime nonsmokers vs. 

former and current smokers)

Ito et al. 2003

(Japan)

VNTR

A644G

Smoking status

Nicotine dependence

Association of MAOA gene with smoking status among 

women and nicotine dependence among men

Lee et al. 2003

(South Korea)

*TAQ1A Smoking status Association with smoking status

Evidence of heterosis in women

Anney et al. 2004

(Australia)

VNTR Nicotine dependence Association with nicotine dependence

Audrain-McGovern et 

al. 2004a

(United States)

*TAQ1A

VNTR

Smoking status

Smoking 

progression

Association of DRD2 gene with smoking progression in 

those exposed to nicotine

Johnstone et al. 2004b

(United Kingdom)

*TAQ1A Smoking status

Cigarettes/day

No association with smoking status or cigarettes/day

Ling et al. 2004

(China)

*RS27072 Nicotine dependence

Age at smoking 

initiation

No association with nicotine dependence

Association with age at smoking initiation among nicotinedependent smokers only

Luciano et al. 2004

(Australia)

VNTR Smoking status

Cigarettes/day

No association with smoking status or cigarettes/day

Olsson et al. 2004

(Australia)

VNTR Nicotine dependence Association with nicotine dependence

Colilla et al. 2005

(United States)

A1947G 

(*VAL/*MET)

Smoking status Association with smoking status

Costa-Mallen et al. 

2005

(United States)

*TAQ1B

A644G

Smoking status No association with smoking status, although there was 

interactive effect between DRD2 and MAOB genes in men

Elovainio et al. 2005

(Finland)

VNTR Smoking status Association with smoking status

Freire et al. 2006

(Brazil)

*TAQ1A

C1021T

Smoking status Association of DRD2 gene with smoking status

Marginal association of DβH gene with smoking status

Laucht et al. 2005

(Germany)

VNTR Smoking status

Daily smoking

Association with smoking status and daily smoking in men

Zetteler et al. 2005

(United Kingdom)

G1368A Nicotine dependence Association with nicotine dependence
Surgeon General’s Report

150 Chapter 4

Table 4.9 Studies of candidate genes for serotonin and smoking behavior

   Population   

Study

(country) Study group Controls Dominant ancestry Gene

Lerman et al. 1998

(United States)

268 current smokers 230 lifetime nonsmokers European and 

African

5HTT

Ishikawa et al. 1999

(Japan)

202 current smokers 103 former smokers

82 lifetime nonsmokers

East Asian 5HTT

Hu et al. 2000

(United States)

177 current smokers 124 former smokers

458 lifetime nonsmokers

European 5HTT

Lerman et al. 2000

(United States)

185 current smokers None European and 

African

5HTT

McKinney et al. 2000

(United Kingdom)

225 current smokers None European MAOA

Lerman et al. 2001

(United States)

249 current smokers 202 lifetime nonsmokers European TPH

Johnstone et al. 2002

(United Kingdom)

1,524 current smokers None European MAOA

Ito et al. 2003

(Japan)

147 current smokers 99 former smokers

258 lifetime nonsmokers

East Asian MAOA

MAOB

Mizuno et al. 2004

(Japan)

233 current smokers 135 former smokers

667 lifetime nonsmokers

East Asian TPH

Brody et al. 2005

(United States)

110 current smokers 

100 former smokers

275 lifetime nonsmokers European and 

African

5HTT

Gerra et al. 2005

(Italy)

107 adolescents who ever 

smoked

103 adolescent lifetime 

nonsmokers

European 5HTT

Kremer et al. 2005

(Israel)

244 persons who ever 

smoked

486 lifetime nonsmokers Other 5HTT

Munafò et al. 2005a

(United Kingdom)

141 current smokers None European 5HTT

Reuter and Hennig 2005

(Germany)

108 current smokers 144 nonsmokers European TPH
Nicotine Addiction: Past and Present 151

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Study

(country) Polymorphism Primary phenotype Main findings

Lerman et al. 1998

(United States)

LPR Smoking status No association with smoking status

Ishikawa et al. 1999

(Japan)

LPR Smoking status Association with smoking status (current vs. former smokers 

and lifetime nonsmokers)

Hu et al. 2000

(United States)

LPR Smoking status Association with smoking status (current vs. former smokers 

and lifetime nonsmokers) among participants with high levels 

of neuroticism

Lerman et al. 2000

(United States)

LPR Nicotine dependence Association of neuroticism with nicotine dependence among 

those with short allele

McKinney et al. 2000

(United Kingdom)

C1460T Cigarettes/day Association with cigarettes/day

Lerman et al. 2001

(United States)

A779C Smoking status

Nicotine dependence

No association with smoking status or nicotine dependence

Association with age at smoking initiation

Johnstone et al. 2002

(United Kingdom)

C1460T Cigarettes/day No association with cigarettes/day

Ito et al. 2003

(Japan)

VNTR

A644G

Smoking status

Nicotine dependence

Association of MAOA gene with smoking status among women 

and with nicotine dependence among men

Mizuno et al. 2004

(Japan)

C218A Smoking status No association with smoking status

Brody et al. 2005

(United States)

LPR Smoking status

Nicotine dependence

No association with smoking status or nicotine dependence

Gerra et al. 2005

(Italy)

LPR Smoking status Association with smoking status

Kremer et al. 2005

(Israel)

LPR

VNTR

Smoking status

Nicotine dependence

Association with smoking status (persons who ever smoked vs. 

lifetime nonsmokers)

No association with nicotine dependence

Munafò et al. 2005a

(United Kingdom)

LPR Nicotine dependence Association with nicotine dependence

Reuter and Hennig 

2005

(Germany)

A779C Smoking status

Nicotine dependence

Association with nicotine dependence (nonsmokers scored as 

having zero nicotine dependence)
Surgeon General’s Report

152 Chapter 4

Table 4.10 Other studies of candidate genes for smoking behavior

   Population      

Study 

(country) Study group Controls

Dominant 

ancestry Gene

Garciá-Closas et al. 1997

(United States)

315 current smokers None European CYP1A1

GSTM1 *NULL

Comings et al. 2001

(United States)

12 current smokers

326 nicotine-dependent 

smokers 

59 former smokers

120 lifetime nonsmokers

399 nondependent controls

European CCK

Hamajima et al. 2001

(Japan)

126 current smokers 837 nonsmokers East Asian IL-1β

Pitha et al. 2002

(Czech Republic)

75 current and former 

smokers

60 lifetime nonsmokers European CD14

Uno et al. 2002

(Japan)

124 current smokers 131 former smokers

690 lifetime nonsmokers

East Asian IL-1β

Füst et al. 2004

(Hungary)

171 persons who ever 

smoked

140 lifetime nonsmokers European TNF2

C4A

C4B

Smits et al. 2004

(The Netherlands)

20,938 persons, including 

current and former 

smokers and lifetime 

nonsmokers

NA European CYP1A1

GSTM1

GSTT1

GSTP1

NAT2

Beuten et al. 2005

(United States)

990 current smokers

286 nonsmokers

Family-based study European and 

African

GABAB2

Liu et al. 2005

(Japan)

213 current smokers 71 former smokers

55 lifetime nonsmokers

East Asian Various

Ma et al. 2005

(United States)

1,568 current smokers

469 nonsmokers

Family-based study European and 

African

DDC

Takimoto et al. 2005

(Japan)

109 current smokers 162 nonsmokers East Asian CCK

CCKAR

Note: NA = not applicable. aPack-years = the number of years of smoking multiplied by the number of packs of cigarettes smoked per day.

dopamine pathway is widely considered to be central in 

the development of nicotine dependence (see “Pathophysiology of Nicotine Addiction” earlier in this chapter). 

Releasing dopamine after nicotine administration activates postsynaptic dopamine receptors, including the D2 

receptor, whereas DβH is involved in the synthesis of noradrenalin from dopamine (Koob and Le Moal 2001). 

The *TAQ1A (C32806T) allele of the DRD2 gene is 

associated with reduced numbers of dopamine D2 receptors in the corpus striatum (Thompson et al. 1997), 

but the functional significance of this variant remains 

unclear. The *1368A allele of the DβH gene is associated 

with smoking status (McKinney et al. 2000), although this 

polymorphism is not considered functional. The nicotine 

patch was significantly more effective for smoking cessation than was a placebo for carriers of the *A1 allele of 

the DRD2 gene but not among those who were homozygous for the more common *A2 allele (Johnstone et al. 

2004b). The difference in the effects of treatment in the 

genotype groups was significant after the first week of 
Nicotine Addiction: Past and Present 153

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Study 

(country) Polymorphism Primary phenotype Main findings

Garciá-Closas et al. 

1997

(United States)

*MSP1 Pack-yearsa No association with pack-years

Comings et al. 2001

(United States)

C-45T Smoking status

Nicotine 

dependence

Association with smoking status (current vs. former 

smokers vs. lifetime nonsmokers) and nicotine dependence 

(nicotine-dependent smokers vs. nondependent controls)

Hamajima et al. 2001

(Japan)

C-31T Smoking status No association with smoking status

Pitha et al. 2002

(Czech Republic)

C-159T Smoking status Association with smoking status (current and former 

smokers vs. lifetime nonsmokers)

Uno et al. 2002

(Japan)

C-31T Smoking status No association with smoking status

Füst et al. 2004

(Hungary)

Haplotype

Haplotype

Haplotype

Smoking status

Cigarettes/day

Association of TNF2 gene with smoking status (persons 

who ever smoked vs. lifetime nonsmokers)

Smits et al. 2004

(The Netherlands)

*MSP1

*DEL

*DEL

*ILE/*VAL

*4

Smoking status No association with smoking status

Beuten et al. 2005

(United States)

Haplotype Nicotine 

dependence

Association with nicotine dependence

Liu et al. 2005

(Japan)

Various Smoking status Association of OGG1, 5HTT, EPHX1, ESR1, and CYP17A1

genes with smoking status

Ma et al. 2005

(United States)

Haplotype Nicotine 

dependence

Association with nicotine dependence

Takimoto et al. 2005

(Japan)

C-45T

T779C

365 *VAL/*ILE

Smoking status Association of CCK gene with smoking status

treatment but not at the end of 12 weeks of treatment.

The nicotine patch was highly effective among smokers 

with both the DRD2 *A1 allele and the DβH *A allele, but 

it was less effective for smokers with other genotypes. This 

genetic association with treatment response was significant at both 1 and 12 weeks of treatment, which suggests 

that the short-term efficacy of the nicotine patch may be 

modulated by DRD2 and DβH genes. Longer follow-up in 

this analysis supported the association of the DRD2 variant with abstinence from smoking at 6- and 12-month 

follow-ups, although this effect was observed only among 

women and the results for the DβH gene were not 

reported (Yudkin et al. 2004).

The second pharmacogenetic trial of NRT was an 

open-label trial of the nicotine patch versus nicotine 

nasal spray. This trial examined the role of the gene for 

the μ-opioid receptor (OPRM1) (Lerman et al. 2004). 

The opioid receptor is the primary site of action for the 

rewarding effects of the endogenous opioid peptide 

β-endorphin (Zadina et al. 1997), which is released in 
Surgeon General’s Report

154 Chapter 4

response to nicotine (Davenport et al. 1990; Boyadjieva 

and Sarkar 1997). Exon 1 of the human OPRM1 gene 

includes a common A118G (ASN40ASP) missense SNP. 

The *ASP40 variant has been associated with reduced 

messenger RNA (mRNA) and lower protein levels for the 

receptor (Zhang et al. 2005). Smokers carrying the OPRM1

*ASP40 variant were significantly more likely than those 

who were homozygous for the *ASN40 variant to be 

abstinent from smoking at the end of the treatment phase 

(Lerman et al. 2004). The differential treatment response 

among smokers was most pronounced for the nicotine 

patch, modest and nonsignificant for nicotine nasal spray, 

and nonsignificant for a placebo, in the bupropion clinical 

trial described in the next section. A longitudinal analysis in the nicotine patch group revealed a dose-response 

effect of the nicotine patch. The effect of the genotype in 

the *ASP40 group was greatest during the nicotine patch 

treatment of 21 milligrams (mg), but the effect was reduced 

as the treatment was tapered and disappeared after discontinuation. In addition, smokers who carried the *ASP40

variant gained less weight during the treatment period and 

reported greater reductions in symptoms of negative 

mood than did those who were not carriers of the variant. 

These findings suggest that smokers carrying the *ASP40

variant may be candidates for maintenance therapy with 

the 21-mg nicotine patch.

Additional investigations provided evidence for an 

association of the COMT VAL158 MET polymorphism with 

prospective smoking cessation in an NRT open-label trial. 

Female smokers treated with either the nicotine patch or 

nicotine nasal spray who carried the low-activity allele, 

which is associated with a slower degradation of dopamine, were significantly more likely than were those who 

did not carry this allele to stop smoking independent of 

the treatment. These findings are consistent with those 

reported in a retrospective comparison of female current 

versus female former smokers in a case-control study 

(Table 4.8) (Colilla et al. 2005).

Bupropion

The first pharmacogenetic analysis of treatment 

for tobacco dependence was conducted as part of a placebo-controlled clinical trial of bupropion for smoking 

cessation (Lerman et al. 2002) that focused on CYP2B6. 

Smokers who carried the CYP2B6 variant, which, to some 

extent, is associated with slower nicotine metabolism, 

reported greater increases in craving for cigarettes after 

the target date for smoking cessation and had significantly 

higher rates of relapse to smoking than did those without the variant. These effects were modified by a significant interaction among gender, genotype, and treatment, 

which suggests that bupropion attenuated the effects of 

genotype among female smokers.

A second report from this clinical trial (Lerman 

et al. 2006) examined two SNPs that may influence the 

expression of the DRD2 receptor. These SNPs included an 

insertion/deletion variant in the promoter region of the 

DRD2 gene (DRD2 -141C *INS/*DEL). The transcriptional efficiency of the more common *-141C INS C allele 

is greater than that of the variant with the *-141C DEL C

allele (Arinami et al. 1997), and a functional synonymous 

SNP in the DRD2 (C957T) gene decreases mRNA stability and protein synthesis (Duan et al. 2003). At the end of 

the treatment phase, a statistically significant interaction 

between the DRD2 -141C *INS/*DEL genotype and the 

treatment indicated a more favorable response to bupropion among smokers homozygous for the *INS C allele 

than that for smokers carrying a *DEL C allele.

One study investigated whether the *TAQ1A polymorphism in the DRD2 gene is associated with smoking 

cessation outcomes after treatment with a combination of 

bupropion and behavioral counseling in smokers enrolled 

in an open-label randomized trial of effectiveness (Swan et 

al. 2005). Compared with women who were homozygous 

for the *A2 allele, women with at least one *A1 allele were 

significantly more likely to stop taking bupropion because 

of side effects from the medication and at 12 months 

were somewhat more likely to report smoking. However, 

relapse to smoking by 12 months after treatment was not 

statistically significant and constituted only a trend. Significant associations or trends were not observed in men.

In addition, another study reported data on 239 

smokers who were offered bupropion in a group of general 

practice physicians in the United Kingdom (Johnstone 

et al. 2004a). Only 54 of these smokers made an active 

attempt to stop smoking. Allele frequencies for polymorphisms in the DRD2, DAT, DβH, and MAOA genes were 

reported. However, the sample size was insufficient for 

formal analysis of the effects of these polymorphisms on 

smoking cessation.

Varenicline

Varenicline, a partial agonist at the α4β2 nAChR, 

was approved by FDA as a treatment for smoking cessation in 2006 (USFDA 2006). Several large trials provide 

evidence that varenicline was more effective than bupropion or placebo as an aid to smoking cessation (Gonzales et al. 2006; Jorenby et al. 2006; Tonstad et al. 2006). 

Because of the efficacy and relative target selectivity (e.g., 

targeting a specific receptor subtype) of this compound, 

pharmacogenetic studies of varenicline are warranted. 
Nicotine Addiction: Past and Present 155

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Summary and Future Directions

Research on genetic influences on smoking behavior has yielded important insights about the biobehavioral 

basis of nicotine dependence. There is strong and consistent evidence from studies of twins that smoking initiation and nicotine dependence are influenced by heritable 

factors. Support for the role of functional genetic variation in nicotine-metabolizing enzymes (e.g., CYP2A6) and 

genetic variation in nAChR subunit genes (e.g., CHRNA5) 

is largely consistent, although the extent of their contribution to nicotine dependence is unclear. Additional 

but inconsistent evidence supports the roles of genetic 

variants in the dopamine pathways. Although the pharmacogenetic approach to smoking cessation holds early 

promise, larger studies in more diverse populations are 

required (Lerman et al. 2007). Designs for case-control 

studies of genetic association are limited, partly by the 

use of crude measures of smoking behavior phenotypes.

This finding supports the importance of future studies 

to explore associations of candidate genes with endophenotypes, which are intermediate phenotypes of smoking 

behavior. Some phenotypes are biologically more proximal to their genetic antecedents than are complex 

behavioral phenotypes, because biologic proximity affords 

a more homogeneous phenotype and a stronger genetic 

signal. Endophenotypes that may be relevant to nicotine 

dependence encompass acoustic startle response, including prepulse inhibition and affective modulation of the 

acoustic startle (Hutchison et al. 2000); measures of the 

reinforcing value of nicotine in a paradigm of behavioral 

choice (Blendy et al. 2005; Ray et al. 2006); various paradigms of craving related to reactivity to cues (Tiffany et 

al. 2000); measures of attentional bias, such as the modified Stroop task (Munafò et al. 2003) and the dot-probe 

task (Waters et al. 2003a); and patterns of withdrawal after 

smoking cessation (David et al. 2003). The list of candidate 

endophenotypes is growing rapidly, and these may offer 

powerful measures for genetic analysis, although the role 

of these putative endophenotypes remains speculative in 

some cases. 

Also deserving of attention is the study of the interaction between genetic variants, nicotine dependence, 

and disorders comorbid with nicotine dependence (e.g., 

depression and anxiety). Two studies suggest that smoking behaviors and nicotine dependence are influenced 

by an interaction between the 5HTT gene and anxietyrelated traits (Hu et al. 2000; Lerman et al. 2000). In 

one study, however, this association was not replicated 

(Munafò et al. 2005a). A better understanding of genetic 

influences on nicotine dependence in different psychiatric 

populations would be valuable for the development of targeted medications.

Pharmacogenetic investigations of smoking cessation treatments have provided promising initial evidence 

that genetic variations in drug targets, such as the dopamine system or nAChRs, may predict responses to treatments. Only a few such studies have been conducted, and 

these have focused on the two FDA-approved approaches 

for smoking cessation pharmacotherapy: bupropion and 

NRT. Several additional pharmacotherapies have been 

tested for efficacy in smoking cessation (Lerman et al. 

2005). Although the overall effects of alternate pharmacotherapies, such as fluoxetine and naltrexone, have been 

modest, it is possible that subgroups of smokers who 

benefit from such treatments can be identified by genotype. Although pharmacogenetic research on smoking 

cessation treatments is in the early stages, this research 

may ultimately be used to tailor pharmacotherapies to 

smokers most likely to benefit, thereby improving the 

efficacy. Emerging health policy and ethical issues related 

to genetically tailored smoking cessation treatments are 

important to consider (Shields et al. 2004), as are barriers 

to and facilitators of the integration of genetic tests into 

smoking cessation in clinical practice (Shields et al. 2004; 

Munafò et al. 2005b).

Recent studies have begun to provide compelling 

support for association of some common genetic variants 

with smoking behavior and related disease phenotypes, 

such as SNPs within the CHRNA5/A3/B4 gene cluster (Amos et al. 2008; Hung et al. 2008; Liu et al. 2008; 

Thorgeirsson 2009); however, the effect sizes described in 

these studies are very small, and it has been suggested that 

efforts may need to be directed elsewhere if the genetic 

architecture of complex traits is to be fully elucidated 

(Goldstein 2009; Hardy and Singleton 2009; Hirschhorn 

2009). In particular, the hypothesis that common phenotypes, such as nicotine dependence, will be explained by 

common genetic variants has been questioned because 

the effect sizes observed to date suggest an unrealistically 

large number of alleles to explain the known heritability 

of a given phenotype (Goldstein 2009).

A complementary approach may be to seek out 

less common genetic variations that may have a more 

profound effect on phenotypes of interest. For example, 

recent studies have identified a possible role for copy 

number variants and de novo mutations in the etiology 

of psychiatric phenotypes such as schizophrenia (Xu et al. 

2008) and autism (Sebat et al. 2007). Although no studies have yet investigated the role of copy number variants 

in smoking behavior, such studies are likely to emerge in 

the near future. As our understanding of the functional 

biology of genetic variation continues to develop, so too 

will the technologies and methods available to dissect the 

genetic architecture of complex phenotypes such as nicotine dependence.
Surgeon General’s Report

156 Chapter 4

Prevalence and Trajectory Toward Nicotine Dependence

Genes appear to predispose persons to smoking 

initiation and persistence and possibly are related to the 

extent of difficulty a person has in smoking cessation. 

Genetic transmission may include inheritance of polymorphisms of specific genes that affect responses of the 

body and the brain to nicotine. These responses include 

the rate of metabolism of nicotine, receptor sensitivity to 

nicotine and to certain neurotransmitters, and the levels 

of neurotransmitters available at neural synapses. These 

individual differences in response to nicotine are likely to 

affect the trajectory toward the development of nicotine 

dependence. Characterization of differences in trajectories has primarily focused on the adolescent population, 

because most smokers begin smoking cigarettes during 

this period of life. The next section describes the prevalence of adolescent smoking to increase understanding of 

the scope for potential development of dependence, differences in trajectory patterns toward dependence, and 

determinants for developing nicotine addiction. Epidemiologic, laboratory, and clinical studies are described to 

elucidate the emerging science in this area.

Epidemiology of Adolescent 

Smoking

A large body of epidemiologic literature has examined the prevalence of smoking, its initiation in adolescence, and the progression among adolescents from 

experimentation to regular use of cigarettes. This literature includes research on national samples in both 

school-based studies (University of Michigan 2007) and 

household studies (Substance Abuse and Mental Health 

Services Administration 2004). However, compared with 

an extensive amount of literature that examines adolescent smoking, work on adolescent nicotine dependence is 

more recent, so there are fewer empirical studies on early 

antecedents of nicotine addiction than on the antecedents of adolescent smoking (Colby et al. 2000a). Thus, in 

reviewing existing data, it is important to separate cigarette smoking and nicotine addiction as distinct outcomes 

(Hughes 2001). In addition, because most studies have 

focused on adolescent cigarette smoking rather than other 

forms of tobacco use, this review is restricted to studies of 

cigarette smoking.

Subsequent data suggest that approximately one 

in five high school students report “current” smoking, 

defined as any smoking in the past month (CDC 2008b). 

Smoking prevalence increases with age throughout 

adolescence. For example, data from the Monitoring the 

Future study (Johnston et al. 2007) show that current 

smoking is reported by 8.7 percent of 8th graders, 14.5 

percent of 10th graders, and 21.0 percent of 12th graders. In addition to age, the prevalence of adolescent smoking varies with race and ethnicity. The highest rates were 

reported by American Indian and Alaska Natives, followed 

by non-Hispanic Whites, Hispanics, African Americans, 

and Asians (National Institute on Drug Abuse 2003). Few 

characteristics of adolescent smoking differed by gender, 

but adolescents with less-educated parents, lower aspirations for higher education, and rural residence are more 

likely to smoke cigarettes (Johnston et al. 2007). Finally, 

some adolescents smoke at high levels of frequency and 

quantity. For example, daily smoking is reported by 4.0 

percent of 8th graders, 7.6 percent of 10th graders, and 

12.2 percent of 12th graders; and 1.5 percent of 8th graders, 3.3 percent of 10th graders, and 5.9 percent of 12th 

graders smoke one-half pack or more of cigarettes per day 

(Johnston et al. 2007).

Measuring Nicotine Dependence in 

Adolescents

Colby and colleagues (2000b) summarized the literature on methods of measuring adolescent nicotine 

dependence. These researchers note that the two major 

approaches to measurement were formal diagnostic measures, such as interviews based on the DSM-IV criteria (APA 

1994) and brief self-report measures that were most often 

modifications of the FTQ (Fagerström 1978). A brief selfreport measure, Hooked on Nicotine Checklist (HONC), 

has been developed and used in longitudinal studies of the 

early acquisition of nicotine dependence (DiFranza et al. 

2002a; O’Loughlin et al. 2003). This measure defines the 

onset of nicotine dependence as the point of experiencing loss of autonomy over tobacco use (DiFranza et al. 

2002a). Although multiple measures have proved useful 

in predicting aspects of smoking behavior, as previously 

noted in this chapter, there is no gold standard for assessing nicotine dependence, either in adolescents or adults 

(Colby et al. 2000a,b; O’Loughlin et al. 2002).

The complexity of assessing adolescent nicotine 

dependence is evident from the modest correlation found 

between two of the most common methods for measuring dependence—DSM-based diagnoses and FTQ-derived 

self-report measures—and the fact that these measures do not identify the same adolescents as nicotine 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

dependent (Kandel et al. 2005). This finding has also 

been reported for adult smokers (Moolchan et al. 2002). 

Kandel and colleagues (2005) found a low agreement 

between DSM-based and FTQ-derived measures, except 

with high cigarette consumption (≥16 cigarettes per day). 

The DSM-based measure identified a higher prevalence 

of adolescent dependence because smokers met diagnostic criteria at much lower quantities of cigarettes than 

with the FTQ-derived measure (e.g., 60 versus 19 percent 

among those adolescent smokers smoking two to five cigarettes per day). Furthermore, for adolescent smokers who 

smoked a low number of cigarettes per day (e.g., 2.5 cigarettes), increasing depressive symptoms were associated 

with higher risk for DSM-diagnosed dependence (Kandel 

et al. 2005). This association between DSM diagnoses of 

tobacco dependence and depression has also been reported 

in adults (Breslau and Johnson 2000) (see “Epidemiology of Tobacco Use and Nicotine Dependence in Adults” 

later in this chapter). These findings led the investigators 

to believe that the DSM criteria identify a psychological 

component or behavioral symptoms common to both 

dependence and depression, which are not found in the 

FTQ-derived measure. Finally, Kandel and colleagues 

(2005) examined ethnic differences in dependence and 

found that non-Hispanic Whites had higher prevalence 

of dependence than other racial or ethnic groups, but 

this difference was accounted for by higher prevalence of 

smoking among this population. Once adjustment was 

made for differences in prevalence of smoking, differences 

by ethnicity were attenuated or eliminated. Thus, extensiveness of smoking must be considered when measuring 

dependence in youth.

Prevalence of Symptoms and Diagnoses in 

Adolescence

Studies suggest that adolescents report symptoms 

of dependence even at low levels of cigarette consumption (Colby et al. 2000a,b; Hughes 2001; DiFranza et al. 

2002b; Panday et al. 2007). The difference in sensitivity 

to nicotine in adolescents and adults is also reported in 

animal models (Slotkin 2002; Adriani et al. 2003; Torres 

et al. 2008). For example, Levin and colleagues (2003) 

found that when rats were first exposed to nicotine in 

adolescence, they self-administered more nicotine than 

did rats exposed in adulthood. These differences in selfadministration by age at first exposure persisted into 

adulthood. Similarly, Beluzzi and colleagues (2004) found 

that a single nicotine injection during early adolescence 

was sufficient to establish conditioned place preference in 

rats, whereas such injections in late adolescence or adulthood were not sufficient. Thus, paradigms for both selfadministration and conditioned place preference in rats 

suggest that adolescence may be a developmental stage of 

particular vulnerability to the effects of tobacco exposure. 

Furthermore, a study by Torres and colleagues (2008), 

using a conditioned place preference paradigm, showed 

that adolescent rats not only found lower doses more reinforcing but also found higher doses less aversive compared 

with adult rats. If so, adolescents may be particularly vulnerable to developing tobacco dependence. DiFranza and 

colleagues (2002b) concluded that, on average, the onset 

of an initial symptom of tobacco dependence occurred 

when adolescents smoked only two cigarettes once a week. 

Even adolescents who smoked only once or twice in their 

lives reported an average of 1.3 symptoms on the HONC 

(1.0 for males and 1.4 for females) (O’Loughlin et al. 

2003). As a cautionary note, the interpretation of the 

results relies on whether the HONC reflects valid symptoms of dependence.

Kandel and Chen (2000) examined a proxy measure 

of DSM diagnosis of nicotine dependence in data from 

the National Household Survey on Drug Abuse (now the 

National Survey on Drug Use & Health). They reported 

that, compared with adults, adolescents met the criteria 

for dependence at lower levels of cigarette consumption.

Some researchers have suggested that these age differences reflect a greater sensitivity to nicotine among 

adolescents than among adults (Kandel and Chen 2000). 

However, researchers have also noted that these age differences can reflect cohort effects (Breslau et al. 2001; 

Hughes 2001). That is, given the national reductions in 

smoking prevalence are accompanied by greater social 

proscriptions against smoking, smoking among more 

recent (younger) cohorts may represent more “hard core” 

smoking with greater levels of dependence (Breslau et 

al. 2001), although other researchers have questioned 

whether a “hardening of smokers” has actually occurred 

(O’Connor et al. 2006).

Reported prevalence of nicotine dependence among 

current adolescent smokers varies depending on whether 

heavy or light smokers are considered. In one study, 19.4 

percent of adolescents who smoked weekly were considered to be dependent on the basis of an analog measure 

from the ICD criteria (O’Loughlin et al. 2003). Even lessthan-weekly tobacco use may result in progression toward 

nicotine dependence. A later study found that the most 

susceptible youth lose autonomy over tobacco within one 

or two days of first inhaling from a cigarette. The appearance of tobacco withdrawal symptoms and failed attempts 

to stop smoking can precede daily smoking dependence, 

as defined by ICD-10, and typically appears before consumption reaches two cigarettes per day (DiFranza et al. 

2007). One study using data from the National Survey 

on Drug Use & Health reports a 28-percent prevalence 
Surgeon General’s Report

158 Chapter 4

of last-year nicotine dependence (based on symptoms 

approximating DSM-IV dependence criteria) among adolescents aged 12 through 17 years who smoked during 

the last month, which was only slightly lower than the 

prevalence for adults (e.g., 30 to 32 percent among those 

aged 18 through 49 years) (Kandel and Chen 2000). The 

majority of adolescent daily smokers meet criteria for 

nicotine dependence. For example, Kandel and colleagues 

(2005) found that 87 percent of adolescent daily smokers 

met DSM criteria and 63 percent met the modified FTQ 

criteria (score >3). Similarly, O’Loughlin and colleagues 

(2003) found that 65.9 percent of seventh graders who 

smoked daily met ICD criteria.

There has also been interest in whether adolescents 

experience withdrawal symptoms on the discontinuation 

of smoking, either as part of an attempt to stop smoking 

or during periods when they cannot smoke. Colby and colleagues (2000a) summarized six retrospective studies in 

which adolescent smokers recalled their experiences during periods of nonsmoking. Most adolescents reported at 

least one symptom of withdrawal. Craving was the most 

commonly reported symptom upon abstinence. Fernando 

and colleagues (2006) analyzed data from the National 

Youth Tobacco Survey and reported that 63 percent of 

adolescents who smoked five or fewer cigarettes per day 

reported at least one withdrawal symptom. Hanson and 

colleagues (2003) examined the effects of the nicotine 

patch on adolescent-reported withdrawal symptoms. 

Compared with the placebo group, the nicotine patch 

group had lower scores for withdrawal symptoms.

Killen and colleagues (2001) recruited adolescents 

from alternative high schools and from a homeless shelter 

who smoked at least 10 cigarettes per day. There were two 

assessment sessions. Participants were randomly assigned 

to the nicotine patch or the placebo patch for the second 

assessment. The researchers found a decrease in heart rate 

across sessions only for the placebo condition. However, 

they found significant increases in self-reported withdrawal symptoms for both the nicotine patch and the 

placebo patch conditions. The most intense withdrawal 

symptoms were craving and anxiety, which were not relieved by the nicotine patch. Finally, some adolescents who 

believed they had worn a nicotine patch had expectancy 

effects; they reported less craving and frustration and a 

greater ability to concentrate. Together, these results suggest that adolescent smokers experience withdrawal symptoms but that expectancy effects also influence findings. 

Prokhorov and colleagues (2005) suggest caution about 

interpreting nonspecific symptoms such as irritability, 

depression, insomnia, and trouble concentrating, which 

can have multiple causes besides tobacco withdrawal.

Some animal data suggest that adolescents experience a dampened withdrawal response compared with that 

in adults (O’Dell et al. 2004, 2006). O’Dell and colleagues 

(2004) precipitated withdrawal with mecamylamine in 

rats receiving long-term administration of nicotine versus 

saline and found mecamylamine-induced withdrawal in 

adult rats but not in adolescent rats. These findings in animal studies, combined with limited clinical data, indicate 

the need for further studies of differences in withdrawal 

symptoms by age.

Trajectories of Smoking from Adolescence to 

Adulthood

Cigarette smoking shows age-related trends with 

typical initiation of smoking occurring in early adolescence. Retrospective data from the 1999 National Survey 

on Drug Use & Health (Kopstein 2001) suggest that the 

average age at first use of cigarettes is 15.4 years and the 

average age at initiation of daily smoking is 18 years. Data 

from both retrospective and longitudinal studies suggest 

that smoking prevalence or incidence of daily smoking 

in adolescents increases over time, peaks in young adulthood, and then declines (Chen and Kandel 1995; Breslau et al. 2001). However, these data are limited in that 

they describe a single “average” trajectory of age-related 

changes in smoking behavior, which obscures substantial 

heterogeneity among smokers. For example, there is variation in age at smoking initiation (Breslau et al. 1993a; 

Chassin et al. 2000) in the time it takes to progress to daily 

smoking, and in the time to develop dependence symptoms (DiFranza et al. 2002b).

Advances in mixture modeling (Nagin 1999; Muthén 

and Muthén 2000) have enabled longitudinal studies 

to identify multiple age-related trajectories of smoking 

behavior. Some of these studies conducted follow-up on 

participants through adolescence (Colder et al. 2001; 

Audrain-McGovern et al. 2004b; Abroms et al. 2005). Wills 

and colleagues (2004) performed cluster analysis rather 

than mixture modeling. These studies have all identified 

multiple trajectory groups, which typically include a group 

with early-onset (7th grade) regular smoking (smoking 

at least a few times a week); a group with experimental 

smoking (smoking occasionally each year); nonsmokers; 

and a group with intermediate- (regular smoking in 9th 

grade) and late-onset (regular smoking in 10th grade) 

regular smoking. These studies do not assess tobacco 

dependence, and even the late-onset groups were younger 

than age 18 years. Karp and colleagues (2005) studied only 

adolescents who had started to smoke. Most of their participants remained at low levels of smoking, but there was 

heterogeneity in the speed at which the others escalated 

their cigarette use, and youth across all rates of escalation 

were more likely to show symptoms of nicotine dependence than those individuals who maintained low levels 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

of cigarette use. Soldz and Cui (2002) conducted followup on participants through 12th grade. They identified 

the following groups: nonsmokers, experimental smokers, smokers with early or late escalation of smoking, and 

stable continuing smokers. Their findings are noteworthy 

for identifying a group who stopped smoking, which was 

absent in other studies.

Several studies had follow-up from adolescence to 

adulthood. White and colleagues (2002b) recruited 374 

adolescents in New Jersey through random telephone 

sampling. The participants were interviewed five times 

from age 12 years to age 30 or 31 years. The investigators 

identified three trajectory groups: (1) nonsmokers and 

experimental smokers; (2) occasional smokers and smokers whose smoking peaked at 18 years of age and then 

declined; and (3) heavy smokers and regular smokers. Predictor variables distinguished between nonsmoking and 

smoking trajectories but could not predict heavy smoking 

among smokers. Predictor variables were disinhibition 

items from the Zuckerman Sensation Seeking Scale, low 

school grades, and use of other drugs. Chassin and colleagues (2000) recruited 8,556 adolescents in 6th through 

12th grades in a midwestern county school system and 

surveyed them annually in 1980 through 1983. Additional follow-ups were conducted in 1987 and 1993 and 

identified a greater number of groups reflecting smoking 

trajectory. The groups included nonsmokers, experimental smokers, persons with early smoking initiation who 

became stable smokers, persons with late smoking initiation who became stable smokers, and persons who 

stopped smoking. On average, persons with early smoking initiation who became stable smokers were smoking 

daily by 15 years of age and averaged more than one-half 

pack of cigarettes per day by 18 years of age. In contrast, 

persons with late smoking initiation who became stable 

smokers averaged weekly smoking at age 18 years but less 

than one-half pack per day. Thus, the stable group with 

early initiation was also at particular risk for heavy smoking. This group was characterized by (1) a high frequency 

of parental smoking, perhaps reflecting both genetic and 

environmental risk factors; (2) less parental support; 

and (3) greater attitudinal tolerance for deviant behavior 

(“deviance proneness”).

Orlando and colleagues (2004) identified similar 

groups: nonsmokers; triers (never exceeding one or two 

cigarettes per year, increasing slightly in early adolescence, then decreasing to very low levels in young adulthood); late-onset increasers (started at a low smoking rate, 

but increased smoking steadily with the sharpest increase 

occurring between 18 and 23 years); decreasers (smoked 

a few times per month at age 13 years but decreased to 

once or twice a year by age 23 years); and early increasers (started out at low level of smoking at age 12 years 

but rose sharply to weekly smoking by age 14 years with 

continuing increases in smoking). These researchers also 

identified a group of heavy smokers throughout the age 

range of 13 through 23 years. The studies by Chassin and 

associates (2000) and Orlando and colleagues (2004) both 

found that the group with late initiation seemed to be protected in adolescence by family factors, including (across 

the two studies) less familial smoking, more parental support, intact families, and higher levels of parental education. However, Orlando and colleagues (2004) found that 

the trajectory groups of the stable heavy smokers, the 

persons with early initiation who increased cigarette consumption, and those with late initiation who increased 

cigarette consumption all converged to a similar point 

of heavy smoking by 23 years of age. Thus, these studies identify a group of persons with early initiation and 

sharply escalating cigarette consumption who are at high 

risk for heavy smoking. However, late initiation of smoking does not necessarily imply protection against heavy 

smoking. Divergence among these groups may occur at 

ages older than 23 years, which were not represented in 

the study by Orlando and colleagues (2004).

Several studies focused on African Americans. Juon 

and colleagues (2002) conducted follow-up on inner-city 

participants who had low socioeconomic status (SES) and 

divided them into nonsmokers, former smokers, smokers with late initiation (after age 18 years), and smokers 

with early initiation. The group with early initiation was 

more aggressive in childhood, more likely to have lax parental supervision, and had more drug problems. White 

and colleagues (2004) modeled trajectories of the number 

of cigarettes smoked each day. They identified nonsmokers, light smokers, and heavy smokers and found that 

African Americans started smoking later and had lower 

cigarette consumption than did White participants. Similarly, Blitstein and colleagues (2003) found that progression of smoking was more likely to be slow among African 

Americans. Finally, Brook and colleagues (2006) modeled 

trajectories for African American and Puerto Rican adolescents from age 14 to 26 years and identified the following 

groups: nonsmokers, persons whose smoking peaked at 18 

years of age and then declined, smokers with late initiation, and smokers with early initiation. Although there are 

few studies, these findings suggest that the age at smoking 

initiation and the speed of progression in cigarette consumption may differ by ethnicity. This hypothesis should 

be considered in describing smoking trajectories from 

adolescence to adulthood.

Another important consideration is that none of 

these longitudinal studies spanning adolescence and 

adulthood directly assessed nicotine dependence. Therefore, the extent to which predictors of early progression 

to heavy smoking are predictors of nicotine dependence 
Surgeon General’s Report

160 Chapter 4

is unknown. However, Storr and colleagues (2004) performed a latent class analysis of nicotine dependence 

symptoms by using data from the National Survey on Drug 

Use & Health. The findings indicated that early smoking 

initiation leads to a higher probability of experiencing 

nicotine dependence features within two years of smoking 

onset compared with those smokers who initiated smoking after age 20 years. 

Determinants of Nicotine Addiction

Researchers have described the progression of cigarette smoking as a process of multiple stages, including 

precontemplation, contemplation or preparation, initial 

trying, experimental or irregular smoking, and established 

daily smoking (Mayhew et al. 2000). Researchers have also 

suggested that movement across these stages is determined by different factors (Flay et al. 1983). For example, 

social factors such as peer modeling and opportunities to 

experiment may have a greater influence on initial experimentation with smoking, whereas factors such as genetic 

risk, negative affect, and propensity to develop tolerance 

to nicotine have been hypothesized to play a greater role 

in determining movement across later stages of smoking 

(Flay et al. 1983). However, the empirical evidence for 

such stage-specific predictors is weak. Mayhew and colleagues (2000) reviewed this literature and found that few 

studies tested for stage-specific predictors. Rather, most 

studies aggregated data across stages, predicting any progression in smoking or predicting broad categories such 

as “regular” smoking, which ranges from smoking a single cigarette a month to daily heavy smoking. Moreover, 

much of the research on adolescent smoking initiation is 

motivated by an interest in smoking prevention. Therefore, many studies focus on the initiation of smoking or 

experimental smoking. Few studies have examined predictors of nicotine dependence or daily heavy smoking. For 

these reasons, little is known about stage-specific predictors of nicotine dependence.

Some studies have used genetically informed 

designs to examine the extent to which adolescent 

tobacco dependence is related to additive genetic influences, shared environmental influences that make siblings 

more alike, and unshared environmental influences that 

make siblings different (Boomsma et al. 2002). From the 

extensive literature on the genetics of adolescent smoking, several studies are selected for review, because they 

focus on heavy smoking or nicotine dependence in adolescence. McGue and colleagues (2000) report that 44 

percent of the variance in nicotine dependence among 

17-year-old twins was associated with additive genetic 

influence. However, shared environment also played an 

important role, accounting for 37 percent of the variance 

in nicotine dependence. Similarly, a study that focused on 

high frequency of smoking rather than nicotine dependence reports that both additive genetic and shared environmental influences were important (Rende et al. 2005). 

One study reported differences by gender in heritability 

for “problem” tobacco use (Rhee et al. 2003). Heritability 

was a stronger influence, and shared environmental factors were a weaker influence for female than for male adolescents. Thus, studies of behavioral genetics in relation 

to adolescent heavy smoking or nicotine dependence suggest the importance of both genetic and environmental 

influences, although in an adult study population, tobacco 

dependence seems to be more strongly influenced by 

genetics (see “Genetics” earlier in this chapter). 

Researchers have also associated maternal smoking 

during pregnancy with the later development of tobacco 

dependence in offspring. Buka and colleagues (2003) 

examined a sample (aged 17 to 39 years) from the Providence (Rhode Island) cohort of the National Collaborative 

Perinatal Project. They found an elevated risk for tobacco 

dependence when the mother smoked more than one 

pack of cigarettes per day during pregnancy. However, the 

investigators note that these results could also be 

explained by genetic influences. Moreover, because postnatal maternal smoking was not considered, social environmental mechanisms of intergenerational transmission 

of nicotine dependence (e.g., role modeling) could also 

influence findings. For example, Cornelius and colleagues 

(2005) found that the relationship between prenatal exposure and adolescent smoking was not significant after 

adjustment for factors such as the mother’s current smoking and the smoking of friends.

Studies have also associated child and adolescent 

psychopathology with nicotine dependence and heavy 

smoking. Using data from the Yale Longitudinal High-Risk 

Study, Dierker and colleagues (2001) found a significant 

association of nicotine dependence with anxiety disorder, 

affective disorder, conduct disorder, oppositional defiant 

disorder, substance dependence, and parental substance 

dependence. The investigators reported that affective 

disorders and drug use disorders remained unique predictors of nicotine dependence after adjustment for confounding comorbidities. These relationships were found 

only for nicotine dependence and not for distinguishing 

between nonsmoking and experimentation or between 

regular smoking and a combined group of earlier stages 

of smoking progression. Clark and Cornelius (2004) also 

examined adolescents with or without parental substance 

use disorder. They found that substance use disorders 

and daily smoking in parents, as well as conduct disorder, 

oppositional defiant disorder, and attention-deficit/hyperactivity disorder in offspring predicted progression to daily 

smoking. However, these researchers found no significant 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

relationship between anxiety or depressive disorders in 

adolescents and progression to daily smoking.

In a longitudinal study of a large sample of adolescents recruited from high schools, Rohde and colleagues (2004) report a finding similar to that of Clark and 

Cornelius (2004). Externalizing disorders (e.g., attentiondeficit/hyperactivity disorder, disruptive behavior disorders, and alcohol and drug use disorders) are more 

strongly and consistently associated with smoking cigarettes than are internalizing disorders (e.g., mood and 

anxiety disorders). In a multivariate analysis that included 

familial psychopathology, familial smoking, and composite 

variables of internalizing and externalizing disorders, only 

the externalizing disorders predicted both progression to 

daily smoking and to nicotine dependence among daily 

smokers. Thus, these studies show a consistent support 

for externalizing disorders, but less consistent support for 

internalizing disorders, as predictors of frequent smoking 

or nicotine dependence. The inconsistent effects of internalizing disorders may reflect variation in study samples 

and methods and, particularly, differences in the choice 

of which variables are statistically controlled in models of 

multiple predictors. Inconsistent results may also reflect 

the presence of moderating variables. For example, Patton 

and colleagues (1998) found that depression and anxiety 

were significant predictors of transition to daily smoking 

only when there were high levels of peer smoking.

Finally, Lloyd-Richardson and colleagues (2002) 

used data from a cross-sectional study—the National Longitudinal Study of Adolescent Health—to compare adolescents who were at different smoking stages. The smoking 

stages compared were persons who never smoked; experimental smokers, who tried a cigarette but had not smoked 

in the past 30 days and had never smoked daily; intermittent smokers, who reported some smoking but no daily 

smoking in the past 30 days; and regular smokers, who 

smoked daily for the past 30 days. The investigators examined whether predictor variables had different effects at 

different smoking stages. For example, a variable might be 

particularly important at early stages of smoking and thus 

would differentiate persons who never smoked from those 

who experimented with smoking but would not significantly differentiate among the other groups. The results 

showed some stage specificity of predictors. Peer smoking and low level of school connectedness more strongly 

differentiated between regular smokers and persons who 

never smoked, experimental smokers, and intermittent 

smokers than differentiated among persons who never 

smoked, experimental smokers, and intermittent smokers. 

Thus, according to the investigators, peer smoking and 

low school connectedness were more influential in later 

stages of smoking than in early stages. Alcohol use showed 

the opposite pattern and so was thought to be more influential in the early stages of smoking. However, there was 

also evidence that predictors were not stage specific. For 

example, depression, delinquency, parental smoking, and 

family connectedness significantly differentiated among 

all the smoking groups, and thus these variables were not 

found to be stage-specific predictors.

Summary and Future Directions

The literature on adolescent nicotine addiction is 

relatively recent and less extensive than that resulting 

from the years of research that has been conducted on 

adolescent smoking. Some data suggest that compared 

with adults, adolescents display nicotine addiction at lower 

levels of cigarette consumption and so may be particularly 

vulnerable to addiction when exposed to tobacco. To both 

replicate and explain this phenomenon, there is a critical 

need for systematic assessment of how adolescents differ in their experience of different aspects of addiction—

development of tolerance, withdrawal, reinforcing 

effects, associative learning—which makes this population more vulnerable to addiction compared with adults. 

The developing brain may be especially susceptible and 

receptive to acute or repeated doses of nicotine (Adriani 

et al. 2003; Schochet et al. 2005) and potentially other 

tobacco-related constituents and to associative learning processes. 

Multiple trajectories of smoking from adolescence to 

adulthood have been identified, with one subgroup showing early initiation and a steep escalation of smoking associated with familial smoking and lack of parental support 

and with risk for chronic heavy smoking in adulthood. 

Further studies are needed to identify the genetic and 

environmental contributions to such trajectories, as well 

as the endophenotypes underlying the genetic contributions. Epidemiologic studies are particularly useful in 

providing an understanding of the critical environmental influences that may interact with specific genes to 

enhance the risk for developing nicotine dependence. 

Another risk factor for nicotine addiction may be the 

diagnosis or symptoms of externalizing disorders. Previous research has been focused on the common neurosubstrates associated with nicotine addiction and depression 

(see “Psychiatric Comorbidity” earlier in this chapter). 

However, a better understanding of the relationship and 

the neurophysiology that links smoking to externalizing 

disorders is needed. In summary, future research needs to 

focus on the complex interactions among genes, environment, social and neurodevelopmental phases, and their 

influence on the trajectory toward nicotine dependence. 
Surgeon General’s Report

162 Chapter 4

Epidemiology of Tobacco Use and Nicotine Dependence in Adults

Prevalence of Cigarette Smoking 

and Nicotine Dependence

According to one study, the prevalence of current 

smoking among adults (aged ≥18 years), as assessed by the 

National Health Interview Survey, was approximately 19.8 

percent, or 43.4 million U.S. adults (CDC 2008a). According to the survey, 77.8 percent of current smokers smoked 

every day and 22.2 percent smoked on some days. (Current smokers are defined as those who smoked ≥100 times 

during their lifetime and who are smoking every day or on 

some days.) This high prevalence of daily smokers indicates the highly addictive nature of cigarettes. More men 

(22.3 percent) than women (17.4 percent) reported current smoking. For the racial and ethnic groups, the lowest 

prevalence of smoking was among Asians (9.6 percent), 

and the highest prevalence was among American Indians and Alaska Natives (36.4 percent). Across educational 

levels and SES, the highest prevalence of smoking was 

among persons with low levels of education—44.0 percent

of those with a General Educational Development diploma 

and 33.3 percent of those with 9 to 11 years of education, 

versus 6.2 percent of those with graduate degrees—and

persons with the lowest levels of income—28.8 percent

of adults living below the poverty level and 20.3 percent 

of those living at or above the poverty level. The prevalence of smoking was lowest among persons aged 65 years 

or older (10.2 percent) and highest among those aged 18 

through 24 years (23.9 percent).

In adults, the diagnosis of nicotine dependence or 

addiction in population surveys has largely been based on 

DSM 3rd ed. (rev) (DSM-III-R), DSM-IV (APA 1987, 1994, 

2000), and ICD-10 (WHO 1992) diagnostic criteria. The 

adult survey instruments used to make the diagnosis have 

included the National Institute of Mental Health Diagnostic Interview Survey and the Composite International 

Diagnostic Interview-Substance Abuse Module (Colby et 

al. 2000b). Researchers also have used data from other 

population surveys, such as the National Survey on Drug 

Use & Health to assess symptoms of tobacco dependence. That survey includes terms or phrases such as (1) 

“reported daily use of the product for two weeks or longer,” (2) “have tried to cut down on smoking,” (3) “unable 

to cut down or quit or experienced difficulty quitting,” (4) 

“felt a need for more tobacco for the same effect,” (5) “felt 

dependent,” or (6) “felt sick or experienced withdrawal 

symptoms when stopping smoking.” Results have been 

reported on the percentage of smokers who indicated one 

or more of these symptoms of dependence or experienced 

at least one of the withdrawal symptoms, psychoactive 

effects (e.g., “it relaxes or calms me”), or difficulty with 

smoking cessation, as a sign of potential tobacco dependence (CDC 1994, 1995a,b). Researchers have also used 

the presence of a specified number of these symptoms as 

a proxy measure for DSM-IV criteria for nicotine dependence (Kandel et al. 1997). 

The prevalence of nicotine dependence based on 

these measures in population- or community-based 

samples from studies conducted in the United States are 

shown in Table 4.11. The variability in the prevalence of 

nicotine dependence can be mostly attributed to the characteristics of the population surveyed and the diagnostic 

tools used. The lifetime prevalence of DSM-III-R diagnosis of nicotine dependence in the general U.S. population 

ranges from 20 to 24 percent, and past-year prevalence of 

DSM-IV diagnosis of nicotine dependence is 9 to 13 percent. By virtually any measure, the prevalence of lifetime 

nicotine dependence is higher for cigarette smoking than 

for any other category of substance abuse (Anthony et al. 

1994; Giovino et al. 1995). The results from Table 4.11 also 

illustrate that almost one-third of persons who have ever 

tried smoking cigarettes became dependent on nicotine. 

Examination of self-reports of specific symptoms 

by adult daily or dependent smokers (Table 4.12) shows 

that in the majority of studies that assessed these symptoms, the least frequently reported symptoms include 

tolerance, withdrawal, and giving up activities as a result 

of tobacco use. The most frequently reported symptoms 

include efforts to reduce smoking and the inability to 

reduce smoking; feeling dependent; using more cigarettes than intended; and perhaps, continuing to smoke 

cigarettes despite experiencing problems. Therefore, 

the symptoms of nicotine dependence most likely to be 

reported among adults tend to be behavioral or a loss 

of control over smoking, and the least reported items 

appear to be physiological (e.g., symptoms of tolerance 

and withdrawal). In a study by Kandel and Chen (2000), 

a higher proportion of adolescents reported experiencing 

symptoms of tolerance (22.2 percent) and/or physical and 

psychological problems (27.0 percent) resulting from tobacco use, compared with the proportion of adults aged 

18 through 49 years (14.4 and 20.3 percent, respectively) 

and adults aged 50 years or older (9.9 and 11.0 percent, 

respectively). These results may reflect either the cohort 

effect or the effect described previously as higher sensitivity in adolescents than that in adults to the effects 

of nicotine on physiological symptoms of dependence. 
Nicotine Addiction: Past and Present 163

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Table 4.11 Lifetime and current prevalence of nicotine dependence in population studies in the United States

Study Design/sample Diagnostic measure

Prevalence 

(%)

Population 

characteristics

Hughes et al. 

1987

1,006 middle-aged male smokers from 

Multiple Risk Factor Intervention Trial 

screening

1980

DSM-III

FTQ score ≥7

90.0

36.0

Smokers (82% smoked 

≥15 cigarettes/day, 

mean cigarettes/day ± 

standard deviation = 

28.0 ± 12.8)

Breslau et al. 

1991, 1993a

Random sample aged 21–30 years 

Large health maintenance organization

N = 1,007 of 1,200

1989–1990 (follow-up)

NIMH-DIS

DSM-III-Ra

20.0

27.0

51.0

Total sample

Ever smoked

Ever smoked daily for 

1 month

Lifetime prevalence

Anthony et 

al. 1994

Population survey of noninstitutionalized 

persons aged 15–54 years 

National Comorbidity Survey

N = 4,414

1990–1992

CIDI

DSM-III-Rb

24.1

31.9

General population

Ever smokedc

Lifetime prevalence

Centers 

for Disease 

Control and 

Prevention

1995b

NHSDA population survey of 

noninstitutionalized civilians aged ≥12 

years

N = 61,426

1991 and 1992

NHSDA (≥1 indicator of 

dependence)

DSM-IVd

75.2

90.9

Smoked ≥1 time in past 

30 days

Daily smokers 

Smoked daily for ≥2 

consecutive weeks in 

past 12 months

Cottler et al. 

1995

Field trial using random-digit telephone 

dialing methods for general population 

sample

N = 260 daily smokers

1990–1991

CIDI-SAM

DSM-III-Rb

ICD-10

DSM-IVd

71.0

77.0

66.0

Daily smoking for 

1 month

Lifetime prevalence

Kandel et al. 

1997, 2001; 

Kandel and 

Chen 2000

NHSDA population survey of 

noninstitutionalized civilians aged ≥12 

years

N = 87,915: 1991–1993

N = 39,994: 1994–1996

NHSDA 

DSM-IVd

8.6–10.5

28.0

28.5

General population

Used tobacco product in 

past year

Smoked last month

Prevalence in past year

Breslau and 

Johnson 

2000

Random sample aged 21–30 years 

Large health maintenance organization

N = 238 daily smokers

1989–1990 (follow-up)

NIMH-DIS

DSM-III-Ra

FTND score ≥4

66.4

75.0

55.5

57.1

Daily smokers

Daily smokers with 

FTND score ≥4

Daily smokers with 

FTND score <4

Daily smokers

Lifetime prevalence

Breslau et al. 

2001, 2004a

4,414 respondents to National 

Comorbidity Survey, Tobacco 

Supplement

Aged 15–54 years

1990–1992

CIDI

DSM-III-Rb

24.0

48.0

Total population

Daily smokers

Lifetime prevalence
Surgeon General’s Report

164 Chapter 4

Table 4.11 Continued

Study Design/sample Diagnostic measure

Prevalence 

(%)

Population 

characteristics

Grant et al. 

2004

NESARC population survey of 

noninstitutionalized civilians aged ≥18 

years

N = 43,093 

2001–2002

NIAAA Alcohol Use 

Disorder and Associated 

Disabilities Interview 

Schedule 

DSM-IVe

12.8 Total sample

Prevalence in past year

Note: CIDI = World Health Organization’s Composite International Diagnostic Interview; CIDI-SAM = CIDI Substance Abuse Module; 

DSM-III = Diagnostic and Statistical Manual of Mental Disorders, 3rd ed.; DSM-III-R = DSM, 3rd ed. (rev); DSM-IV = DSM, 4th ed.; 

FTND = Fagerström Test for Nicotine Dependence; FTQ = Fagerström Tolerance Questionnaire; ICD-10 = International 

Classification of Diseases, Tenth Revision; NESARC = National Epidemiology Survey on Alcohol and Related Conditions; 

NHSDA = National Survey on Drug Use & Health; NIAAA = National Institute on Alcohol Abuse and Alcoholism; 

NIMH-DIS = National Institute of Mental Health Diagnostic Interview Schedule. aNIMH-DIS included ever smoking daily for ≥1 month plus DSM-III-R criteria for dependence with ≥3 of the following symptoms 

persisting for ≥1 month: greater use than intended; unsuccessful efforts to control use; important activities given up; continued use 

despite social, psychological, or health problems; tolerance; withdrawal symptoms; and use to avoid withdrawal symptoms. Excluded 

2 symptoms listed in the general DSM-III-R criteria for psychoactive substance use disorders: (1) great deal of time spent in activities 

necessary to acquire substance or recover from effects and (2) frequent intoxication or withdrawal symptoms when expected to fulfill 

major role obligations.

bCIDI criteria included daily smoking for ≥1 month plus DSM-III-R criteria for dependence with ≥3 of criteria with symptoms 

persisting for ≥1 month.

cData on persons who ever smoked estimated from synthesis with NHSDA data.

dDSM-IV criteria for dependence with ≥3 of the following symptoms within a 12-month period: tolerance; withdrawal; using larger 

amounts or longer than intended (assessed as needed or if smoker felt dependent on nicotine); unsuccessful efforts to cut down; 

negative social, occupational, and physical consequences; and persistent physical and psychological problems. Excluded spending 

significant amount of time to obtain substance; instead, quantity (smoking ≥2 packs daily in past 30 days) was examined in relation to 

dependence.

eNIAAA used DSM-IV criteria modified as follows: use of nicotine to relieve or avoid withdrawal as operationalized by using the 

following four symptom items: (1) use of nicotine on awakening, (2) use of nicotine after situation in which use was restricted, (3) 

use of nicotine to avoid nicotine withdrawal symptoms, and (4) waking up in middle of the night to use tobacco. “Giving up activities 

in favor of nicotine use” was assessed as (1) giving up or cutting down on important activities, such as associating with friends or 

relatives or attending social activities, because tobacco use was not permitted at activity and (2) giving up or cutting down on activities 

that were of interest or that gave pleasure because tobacco use was not permitted. The “great deal of time spent using tobacco” 

criterion was assessed by single symptom item, chain-smoking. The “using tobacco more than intended” criterion was operationalized 

as having a period when tobacco was used more than intended. Nicotine dependence was assessed for any tobacco product, including 

cigarettes, cigars, pipes, chewing tobacco, and snuff.

However, on the basis of animal studies, withdrawal 

symptoms would be presumed to be fewer in adolescents 

than in adults (O’Dell et al. 2004, 2006), yet more adolescents are endorsing physical problems than do adults. 

As pointed out previously, factors other than withdrawal 

may be associated with higher endorsement of withdrawal 

symptoms among adolescents. Another possibility is that 

questions on physical dependence, particularly on tolerance, are not asked in a manner that is understood by or 

relevant to adult smokers. 

The symptoms most frequently reported by adults 

appear to be less specific to the diagnosis of nicotine 

dependence. For example, Breslau and colleagues (1994) 

observed that (1) 88.6 percent of dependent smokers 

reported the symptom of dependence described as “smoking more than intended” (p. 747) and (2) 93.6 percent 

reported “unsuccessful attempts to quit” (p. 747). However, these items were also reported by a substantial percentage of nondependent smokers (47.9 and 25.2 percent, 

respectively) who smoked daily for a month or more 

during their lifetime but never met criteria for nicotine 

dependence. However, 87 percent of dependent smokers 

as opposed to only 12 percent of nondependent smokers 

reported one or more of the three physiological indicators 

of dependence (tolerance, withdrawal symptoms, and/or 

cigarette use to avoid withdrawal symptoms). 

With regard to the onset of nicotine dependence 

relative to daily smoking, one study of data from the 
Nicotine Addiction: Past and Present 165

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Figure 4.5 Cumulative incidence curves of daily smoking and nicotine dependence in the National Comorbidity 

Survey

Source: Breslau et al. 2001. Reprinted with permission from American Medical Association, © 2001.

Note: Participants included 4,144 daily cigarette smokers and 2,136 smokers who were nicotine dependent.

National Comorbidity Survey showed that the highest 

rates of becoming nicotine dependent, as defined by DSMIII-R, occurred in the first 16 years from the year after 

progression to daily smoking, whereas in the subsequent 

10 years the progression to nicotine dependence declined 

and continued at a slower rate (Figure 4.5) (Breslau et al. 

2001). Thus, nicotine dependence generally followed daily 

smoking, although 5.4 percent of nicotine dependence 

began before or in the same year as progression to daily 

smoking. In most cases, the onset of nicotine dependence 

occurred one or more years after the initiation of daily 

smoking. These results appear somewhat contrary to 

results described in “Prevalence of Symptoms and Diagnoses in Adolescence” earlier in this chapter, which indicates that dependence symptoms may occur even earlier 

in a person’s history of smoking. The discrepancies in 

results may be a function of how nicotine dependence was 

diagnosed or defined, that is, whether one was examining 

symptoms or a diagnosis of dependence or cohort effects.

Prevalence by Dose, Duration, and 

Subpopulations

The results from Table 4.11 also show that the more 

a person smokes, the greater is the likelihood of a diagnosis of nicotine dependence (CDC 1995b). Kandel and 

Chen (2000) observed a linear dose-response relationship 

between the number of cigarettes smoked in the past 

month and the percentage of smokers with nicotine dependence in the last year. This finding was based on 

self-reporting of symptoms approximating DSM-IV criteria for dependence and was confirmed in other studies 

(Kawakami et al. 1998). The percentage of male and female smokers with a diagnosis of dependence rose sharply 

and significantly as the amount of smoking increased 

from less than one cigarette per day, to one to five cigarettes per day, and to one-half pack per day. Thereafter, 

the increase in the percentage of smokers with a diagnosis of dependence tended to rise minimally; however, at 
Surgeon General’s Report

166 Chapter 4

Table 4.12 Prevalence of selected symptoms of nicotine dependence reported in selected studies

numbers higher than one and one-half packs of cigarettes 

per day, females showed a higher prevalence of dependence than did males. The duration of cigarette smoking 

has also been related to the prevalence of nicotine dependence (Kandel and Chen 2000). 

Kandel and Chen (2000) also found that among 

persons who smoked in the last month, the prevalence 

of nicotine dependence in middle-aged adults was similar 

to that in adolescents. After adjustment for the quantity 

of cigarettes smoked, the prevalence of dependence was 

generally higher among adolescents than among adults, 

particularly at lower levels of cigarette consumption. 

Several reasons that may account for this finding (i.e., 

cohort effects) have been discussed previously (see “Prevalence of Cigarette Smoking and Nicotine Dependence” 

earlier in this chapter). The lowest rates of nicotine 

dependence were in adults aged 50 years or older; this 

finding was attributed to lower sensitivity to increased 

quantity of nicotine intake. The investigators also found 

that the prevalence of nicotine dependence was higher 

among females than among males, even after adjustment 

for the number of cigarettes smoked. However, this difference was observed only among persons 18 through 

49 years of age. The prevalence of dependence was also 

higher among Whites than among Blacks, and this difference was particularly evident at the lower levels of cigarette consumption. 

Other studies have found no differences by gender 

in the prevalence of nicotine dependence (Breslau et al. 

1991; Anthony et al. 1994) but have confirmed differences by race when DSM criteria were used to diagnose 

nicotine dependence (Breslau et al. 1994, 2001). However, 

when time to the first cigarette was used as an indicator of 

dependence, more Blacks than Whites reported smoking 
Nicotine Addiction: Past and Present 167

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

within 10 minutes of awakening even though Blacks had 

lower or similar levels of cigarette consumption (Royce et 

al. 1993). In another study, Blacks also reported shorter 

time to the first cigarette than did Whites (Ahijevych and 

Gillespie 1997). Differences in nicotine metabolism and 

blood concentrations of cotinine may contribute to differences in the prevalence of dependence among Blacks 

and Whites (Benowitz et al. 1999). Among smokers who 

ever smoked daily, nonnicotine-dependent Blacks were 

2.5 times more likely to persist in smoking than were 

nondependent Whites (Breslau et al. 2001). These findings suggest a weakness in diagnostic systems categorized 

by differences in ethnic and racial groups, differences in 

sensitivity to nicotine across groups, or differences in 

sociocultural factors (e.g., extent of cigarette promotion 

or smoking restrictions) that contribute to persistence in 

smoking across groups. 

Nicotine Dependence and 

Psychiatric Comorbidity

As described in the previous sections, studies have 

found a strong association between nicotine dependence 

and comorbid disorders that warrants further discussion. It is estimated that nearly one-half of all cigarettes 

sold in the United States (44 percent) are consumed by 

people with mental illnesses or substance abuse disorders. In addition, the prevalence of tobacco use among 

those with either addictions and/or mental illness is 

between 38 to 98 percent, as opposed to 19.8 percent 

for the general population (Schroeder 2009). Breslau 

and colleagues (1991) have conducted several studies. One earlier population-based study in Michigan 

observed that young adults with a diagnosis of nicotine 
Surgeon General’s Report

168 Chapter 4

dependence reported higher prevalence of alcohol and 

drug dependence and major depression and anxiety disorders than did persons who had never experienced nicotine 

dependence (Breslau et al. 1991). The relationships 

between each disorder and nicotine dependence were 

observed even when adjustments were made for confounding comorbidities. These findings are similar to those 

observed for adolescent smokers described earlier (Dierker et al. 2001) (see “Determinants of Nicotine Addiction” 

earlier in this chapter). However, the results were contrary 

to other findings among adolescents (Clark and Cornelius 

2004; Rohde et al. 2004). Other population-based research 

and clinical studies have also pointed to the strong relationship between daily smokers or nicotine-dependent 

smokers (as opposed to lifetime nonsmokers or nondependent smokers) and substance use disorders, anxiety disorders, and depression, with higher prevalence of 

comorbid psychiatric disorders among nicotine-dependent smokers and higher prevalence of nicotine-dependent smokers among persons with comorbid disorders. 

For example, in a U.S. population-based survey, Grant and 

colleagues (2004) observed that the prevalence of alcohol 

use disorders, current mood disorders, or current anxiety disorders among adult respondents with diagnoses of 

nicotine dependence during the past year ranged from 21 

to 23 percent compared with 9 to 11 percent in the general population. Conversely, other studies have shown the 

percentage of persons with nicotine dependence among 

respondents with these comorbid disorders ranging from 

25 to 35 percent and as high as 52 percent among respondents with drug use disorders compared with 12.8 percent 

in the general population (Glassman et al. 1990; Breslau 

et al. 1994, 2004b; Lasser et al. 2000; Degenhardt and Hall 

2001; Kandel et al. 2001; Isensee et al. 2003; Schmitz et al. 

2003; Grant et al. 2004; John et al. 2004).

Furthermore, studies have shown that the more 

severe the nicotine dependence, the more likely was the 

association with comorbid disorders. For example, John 

and colleagues (2004) found that the greater the number 

of nicotine-dependent symptoms or nicotine withdrawal 

symptoms and the higher the total FTND scores, the 

higher the odds ratios for psychiatric disorders. Nonetheless, even nonnicotine-dependent smokers, compared with 

nonsmokers, had significantly higher prevalence of alcohol and drug dependencies, but not of major depression 

or anxiety disorders (Breslau et al. 1991, 1994, 1996). This 

result suggests that smoking may either physiologically 

or perhaps more critically, socially, lower the threshold 

for substance abuse disorders. Conversely, the greater 

the number of psychiatric disorders experienced by the 

individual, the higher the prevalence or odds of smoking, 

particularly daily or heavy smoking (Lasser et al. 2000; 

Breslau et al. 2004b) and of diagnosis of nicotine dependence (Breslau et al. 2004b; John et al. 2004). 

The relationship of major depression or anxiety 

disorders with nicotine dependence is complex and not 

extensively explored. Breslau and colleagues (1993b) 

examined the relationship between depression and nicotine dependence in a prospective investigation of 14 

months. The investigators found that major depressive 

disorder increases the risk of progression to nicotine 

dependence and more severe levels of dependence. These 

results were confirmed in a subsequent analysis of crosssectional data from the National Comorbidity Survey in 

which preexisting major depressive disorders, several 

anxiety disorders (e.g., phobias, generalized anxiety disorders, and posttraumatic stress disorders), and substance 

use disorders had resulted in an increased risk for progression to daily smoking or onset of nicotine dependence 

among daily smokers (Breslau et al. 2004b). Of the anxiety 

disorders assessed, neither preexisting agoraphobia nor 

panic disorder predicted a subsequent progression to daily 

smoking, and panic disorder did not increase the relative 

risk of transition to nicotine dependence. Similar findings 

had also been observed in earlier epidemiologic crosssectional studies of adults (Breslau and Klein 1999) and 

in longitudinal studies with follow-up of adolescents into 

young adulthood (Johnson et al. 2000; Isensee et al. 2003). 

Conversely, Breslau and colleagues (1993b) also 

observed that a history of nicotine dependence increased 

the risk for a subsequent first incident or recurrence of 

major depressive disorder. Daily smoking or nicotine 

dependence increased the risk of a subsequent onset of 

drug use, anxiety disorders, major depression, or dysthymia both in epidemiologic studies (Breslau et al. 1998, 

2004a; Breslau and Klein 1999) and in population-based 

longitudinal studies (Kendler et al. 1993; Isensee et al. 

2003). In a population-based longitudinal cohort study, 

adolescents who smoked one or more packs of cigarettes 

per day had higher odds of the onset of anxiety disorders 

(e.g., generalized anxiety disorders, panic disorder, and 

agoraphobia) in adulthood than did adolescents who 

smoked less than one pack a day (Johnson et al. 2000). 

Analysis of cross-sectional data from the National 

Comorbidity Survey found no differences between nicotinedependent and nondependent daily smokers in the likelihood of a subsequent first onset of a psychiatric disorder 

(Breslau et al. 2004a). Therefore, daily smoking appears to 

be just as important a risk factor as a diagnosis of nicotine 

dependence. This finding may reflect the limitations of the 

criteria for a diagnosis of nicotine dependence.

This bidirectional finding in relation to cigarette 

smoking and some of the mood and substance use disorders can be considered either causal or a reflection of 

an underlying factor that is common to the predisposition to both disorders. For example, psychiatric disorders 

may lead to self-medication with nicotine, which targets 
Nicotine Addiction: Past and Present 169

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

the neurosystems that have mood-altering effects, or 

long-term exposure to nicotine may alter neurobiologic 

substrates, leading to the development of psychiatric 

comorbidities. Another possibility is that psychiatric disorder and nicotine addiction share genetic or environmental vulnerabilities or risk factors. 

Few studies have been directed toward providing 

evidence for whether these factors are responsible for 

the relationships between smoking and psychiatric disorders. Support for self-medication of psychiatric disorders 

would come from three findings that show (1) smokers 

with psychiatric disorders have rates of smoking cessation 

lower than those for smokers who do not have these disorders; (2) remission of disorders is less likely to predict 

progression to daily smoking, because there is no need 

for self-medication, but preexisting active disorders are 

associated with increased risk for smoking and/or nicotine dependence; and (3) prevalence of smoking is higher 

among persons with remission of disorders than among 

those who continue to experience psychiatric symptoms 

because smoking reduced the psychiatric symptoms.

To date, the data show that the impact of psychiatric disorders on smoking cessation is equivocal (see 

“Trajectory of Recovery or Relapse” later in this chapter). 

However, these studies are limited to the disorders of major depression and alcohol abuse or dependence. Major 

depressive disorder is the only psychiatric disorder to 

meet the first two characteristics associating cigarette 

smoking with self-medication (findings 1 and 2) (Romans 

et al. 1993; Breslau et al. 2004a) (see “Trajectory of Recovery or Relapse” later in this chapter). 

If the development of psychiatric disorders were 

caused by the effects of cigarette smoking or nicotine 

exposure, then findings to support this hypothesis would 

show that (1) a longer and higher exposure increases a 

smoker’s odds of developing a psychiatric disorder; (2) 

longer abstinence from smoking leads to reduced risk for 

psychiatric disorder, unless the effects are irreversible; 

and (3) current but not former smoking is associated with 

higher risk for psychiatric disorder. The only disorders 

that appear to meet these characteristics are panic disorders and agoraphobia (Breslau and Klein 1999; Johnson et 

al. 2000; Isensee et al. 2003; Breslau et al. 2004a). 

Support for common factors, hereditary or acquired, 

would be based on findings that show (1) both current and 

former daily smoking increase the risk for psychiatric 

disorders, (2) both active disorders and disorders in 

remission or only disorders in remission predict daily 

smoking or a progression to nicotine dependence, and (3) 

familial or genetic vulnerability is shared across nicotine 

dependence or smoking and psychiatric disorders. The 

greatest support for shared common factors is for substance abuse disorders and smoking. 

Remission of substance abuse disorders has been 

a predictor of daily smoking and progression to nicotine 

dependence (Breslau et al. 2004b). Results of studies on 

families and twins support a shared familial and genetic 

vulnerability across substance use disorders (Bierut et al. 

1998; Merikangas et al. 1998; Tsuang et al. 1998). The data 

on common factors for major depressive disorders and 

smoking are conflicting, showing both support (Breslau et 

al. 1994; Kendler and Gardner 2001; Johnson et al. 2004) 

and lack of support (Dierker et al. 2002; McCaffery et al. 

2003). Researchers have attributed inconsistency in these 

results to differences in levels of cigarette consumption, 

definitions of depression, study methods, and analytic 

approaches (Johnson et al. 2004). The use of antidepressant treatments for both depression and smoking cessation, regardless of a history of depression, would support 

the concept of shared substrates that mediate nicotine 

dependence and depression (see “Pathophysiology of Nicotine Addiction” earlier in this chapter).

As a caveat, the strong relationship between nicotine 

dependence and some psychiatric disorders may be a function of the method used to diagnose nicotine dependence. 

For example, in another study conducted by Breslau and 

Johnson (2000), nicotine dependence, as defined by the 

FTND score, was not related to major depression. These 

researchers attributed the strong relationship between the 

DSM-III-R definition of nicotine dependence and major 

depression to the numerous behavioral symptoms associated with the diagnosis of nicotine dependence.

Summary and Future Directions

The effects of dose, age, race, and gender may be 

related to the prevalence of nicotine dependence. The 

number of cigarettes smoked per day and the duration 

of smoking are positively related to the percentage with 

diagnosis of nicotine dependence. Prevalence of nicotine 

dependence among adolescent smokers may be higher 

than that among adult smokers, particularly for those 

who smoke fewer cigarettes per day. Conflicting study 

results suggest that prevalence of nicotine dependence, 

as defined by DSM criteria, is higher among Whites than 

among Blacks but that prevalence is lower in Whites when 

time to the first cigarette of the day is the criterion for 

dependence. It is unclear whether the prevalence of nicotine dependence differs by gender. These results suggest 

the need for further research to explore reasons for the 

inconsistent findings across subgroups of smokers. A significant association also exists between psychiatric disorders and smoking, but the nature of this association is 

unclear. Depending on the disorder, the relationship may 

be causal; for example, smoking may increase the odds of 
Surgeon General’s Report

170 Chapter 4

panic disorder and major depressive disorder and may lead 

to self-medication with tobacco use. On the other hand, 

this association may result from common underlying factors that involve fundamental psychological or physiological processes, such as intolerance to states of negative 

affect or neurotransmitter dysfunction in a common pathway, which lead to nicotine dependence, substance abuse, 

and possibly depression. To date, understanding the causal 

relationships has relied predominantly on cross-sectional 

data sets. Prospective studies have been limited and have 

examined only a few psychiatric disorders, but this type 

of study is necessary to lend stronger evidence for any 

bidirectional causality or for common underlying causes 

of cigarette smoking and nicotine dependence with specific psychiatric disorders. A clearer understanding of 

these relationships will result in a deeper understanding 

of the pathophysiology of nicotine addiction. Moreover, 

the studies of adults are limited in that the focus has 

been primarily on internalizing rather than externalizing 

disorders. In studies of adolescents, externalizing disorders may play an even greater role than do internalizing 

disorders in the development of nicotine addiction (see 

“Determinants of Nicotine Addiction” earlier in this chapter). Therefore, studies encompassing a broader range of 

diagnoses are warranted. 

Trajectory of Recovery or Relapse

Studying recovery from smoking can provide valuable information on the nature of tobacco addiction and 

the factors affecting it. Every year about 45 percent of daily 

smokers in the United States stop smoking for 24 hours, 

but only 5 percent or less achieve long-lasting abstinence 

(CDC 2002, 2004). Thus, relapse is the principal limiting 

factor in the transition from smoking to nonsmoking status. This finding underscores the need to understand the 

nature of relapse and the factors affecting it.

Relapse: Definitions and 

Limitations of the Literature

Integration of information about relapse is difficult 

because definitions of critical events differ among studies. For instance, it seems useful to distinguish a lapse 

from a relapse. A lapse refers to an occurrence of smoking 

or tobacco use that takes place after an attempt to stop 

smoking but is not part of an ongoing pattern of consistent use (Brandon et al. 1986). Relapse refers to the 

point after an attempt to stop smoking when tobacco use 

becomes ongoing and persistent (Brandon et al. 1986). 

Although standards have been offered for defining 

“relapse” (Hughes et al. 2003), many reported results are 

based on idiosyncratic standards. In addition, there is no 

formally accepted definition of a “lapse.” For instance, 

some studies define a lapse as only the first use of tobacco 

after an attempt to stop smoking, and other studies use 

broader definitions. Because of this diversity, this review 

reports results according to the definitions used by the 

investigators in each study. In addition, some investigators distinguish between relapse and failure of smoking 

cessation, with relapse occurring only after a period of 

abstinence (e.g., after 48 hours) (Hughes et al. 2003). 

Again, few studies make such a distinction. Therefore, to 

render the bulk of the evidence comparable, this review 

uses the concept of return to smoking after a cessation 

attempt as an index of vulnerability to relapse, regardless 

of the duration of abstinence. In general, no distinction is 

made between cessation failure and relapse. Finally, some 

of the reviewed studies predict the likelihood of relapse 

while others predict relapse latency. In this review, either 

prediction is taken to reflect a higher level of vulnerability 

to relapse.

Natural History of Relapse

Prevalence

Two key characteristics of relapse are its high prevalence and its rapidity. Past reviews have consistently 

reported that persons who decide to stop smoking on 

their own and those who receive placebos in clinical trials 

achieve 6- to 12-month abstinence rates of only 3 to 5 percent (Cohen et al. 1989; Hughes et al. 2004c). Thus, within 

one year of an attempt to stop smoking, about 95 percent of persons who try to stop without a pharmacologic 

aid continue to smoke or resume smoking. Reviews of 

efficacious treatments reveal that 20 to 25 percent of those 

who tried to stop smoking succeeded for six months (Fiore 

et al. 2008). This finding means that about 75 percent of 

persons who try to stop smoking by using evidence-based 

treatments return to smoking within six months. The risk 

of relapse, however, does not end 6 to 12 months after 

the attempt at smoking cessation. Findings in studies of 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

long-term outcome suggest that relapse ultimately claims 

30 to 40 percent of smokers who stop smoking for one 

year (Eisinger 1971; Gilpin et al. 1997; Krall et al. 2002). 

For instance, Yudkin and colleagues (2003) found that 

about one-half of the smokers who had stopped smoking 

for one year relapse to smoking within the subsequent 

seven years. However, roughly 50 percent of those who 

have ever smoked eventually become long-term former 

smokers (Husten 2005) because many make repeated 

attempts to stop smoking until they are successful.

Rapidity

Most smokers who ultimately relapse resume smoking early after their attempt to stop. This pattern of early 

lapsing has been reported in persons receiving treatment 

(Kenford et al. 1994), as well as in those who decide on 

their own to stop smoking and in smokers who receive 

placebos (Hughes et al. 2004c). For example, Kenford and 

colleagues (1994) found that 80 to 90 percent of those 

who were smoking at six months after trying to stop had 

resumed smoking in the first two weeks of the attempt 

to stop. Other studies report similarly high rates of early 

lapsing in populations of treated and untreated smokers 

(Garvey et al. 1992; Gulliver et al. 1995; Westman et al. 

1997; Hughes et al. 2004a). Women who stop smoking 

during pregnancy, however, tend not to relapse early in 

the attempt to stop, but rather tend to relapse after delivery, which is often weeks or months after initial cessation 

(Fingerhut et al. 1990; USDHHS 1990; Floyd et al. 1993; 

Stotts et al. 2000; Colman and Joyce 2003). 

Lapse-Relapse Relationship

The odds of an eventual relapse are especially high 

among those who lapse or engage in initially isolated 

smoking episodes after the cessation date. Data suggest 

that lapsing is the single best predictor of an ultimate 

relapse (Brandon et al. 1990; Hughes et al. 1992; Kenford 

et al. 1994; Nides et al. 1995). Moreover, the risk of an 

ultimate relapse appears to increase with the number of 

lapse events (Wileyto et al. 2004). Nevertheless, even multiple lapses do not inevitably lead to a relapse (Nides et 

al. 1995). This finding attests to the wide variation in the 

course of both relapse and successful cessation in a population of smokers attempting to stop smoking.

The pattern of a return to regular smoking varies 

considerably across individuals and typically occurs over 

days and weeks rather than hours. On average, smokers have a second lapse three or four days after the first 

lapse (Shiffman et al. 1996b). Almost one-half of smokers 

have the second lapse within 24 hours of the first lapse 

(Brandon et al. 1990). On average, the latency between the 

first lapse to a relapse is three to five weeks (Brandon et 

al. 1990; Shiffman et al. 1996a,b; Gwaltney et al. 2005a), 

which suggests that there is time after an initial lapse to 

engage in additional treatment to prevent progression to 

full relapse.

Risk Factors

To promote more precise thinking about the time 

courses and interactive and cumulative effects of different 

types of influences on relapse, several reviews recommend 

an organizational framework for categorizing forces that 

influence a relapse (Shiffman et al. 1986; Shiffman 1989a; 

Piasecki et al. 2002). In general, such recommendations 

have proposed three factors as important influences on 

relapse: person factors, emergent processes, and situational instigators. Person factors are stable characteristics 

that preexist the attempt to stop smoking and endure (e.g., 

gender and history of or proneness to depression). Emergent processes are dynamic factors that unfold over time 

and emerge sometime during the postcessation period. 

Such processes tend not to be bound to context. For 

example, although these processes may arise in response 

to an episodic event such as stress, they can persist for 

days or weeks. Withdrawal is an example of a dynamic 

variable that arises gradually in response to falling 

blood concentrations of nicotine (Hughes et al. 1990b; 

Piasecki et al. 2003a). Although situational factors may 

affect withdrawal symptoms (McCarthy et al. 2006), the 

symptoms persist well beyond the situational influences 

and are not wholly explained by them. Situational instigators are factors such as cues, contexts, or events that give 

rise to short-lived (phasic) reactions lasting from seconds 

to hours. Such reactions might comprise affective reactions to a stressor, such as an argument, or to exposure to 

smoking cues, such as seeing someone smoke. 

Thus, this organizational scheme reflects the instigator of the process, such as a contextual cue, as well as 

the time course of vulnerability associated with relapse. 

Such categorization is complex, because the distinction 

among the time courses of influences is somewhat arbitrary and various influences may interact (Piasecki et al. 

2002; Gwaltney et al. 2005b). These influences are not 

mutually exclusive or independent, which adds to the 

complexity of this organizational method. For example, 

person factors may affect situational reactions or emergent patterns of symptoms. The categorization scheme 

described here is only one approach to conceptualizing 

the causes of relapse. This approach has, however, allowed 

researchers to identify factors that consistently predict 

relapse and is consistent with a greater body of research 

and theory showing that person factors, phasic reactions, 

and contexts powerfully affect behavior (Mischel 2004). 
Surgeon General’s Report

172 Chapter 4

Person Factors

Cognitive and Attitudinal Influences

There is evidence that relatively stable attitudinal 

variables affect the vulnerability to relapse of smokers. For 

example, precessation assessments of expectations that 

smoking will alleviate distress (e.g., negative moods and 

stress) predict the subsequent likelihood of a relapse (Wetter et al. 1994; Brandon et al. 1999). In addition, multiple 

studies conclude that baseline measures of confidence 

in the ability to stop smoking can also predict outcomes 

(Condiotte and Lichtenstein 1981; Baer et al. 1986; Shiffman et al. 2000). Other findings indicate that confidence 

before attempts to stop smoking and positive expectations 

may interact to predict risk of relapse to smoking. Smokers with low confidence and high expectations for smoking 

reinforcement are especially likely to relapse (Shadel and 

Mermelstein 1993; Dijkstra and Brosschot 2003). Finally, 

high levels of motivation, based on health concerns (Nides 

et al. 1995; Dijkstra and Brosschot 2003) or other reasons 

(Turner and Mermelstein 2004), may foster cessation and 

protect against relapse. However, motivation tends to be 

less effective than other factors, such as level of tobacco

dependence or self-efficacy, that is, self-confidence in the 

ability to stop smoking cigarettes (Hyland et al. 2004; University of Michigan 2006).

Other cognitive variables are less consistently 

related to lapse and relapse. For instance, expectations 

about the negative effects of smoking (e.g., risk of disease) 

appear to predict the motivation or intention to stop 

smoking but not the likelihood of a relapse (Wetter et al. 

1994; Brandon et al. 1999). Also, one study found that a 

strong commitment to continuing abstinence from smoking was related to reduced rates of relapse, but this finding was obtained in a population that comprised persons 

who abused opiates and alcohol in addition to smokers, 

and this condition made the relevance to smoking per se 

unclear (Hall et al. 1990).

Finally, cognitive dimensions such as expectations 

or motivation are sometimes hard to classify. For example, 

motivational structures and attitudes may affect behavior 

over many years (Etter et al. 2003b; Beltman and Volet 

2007). However, motivational phenomena change over 

time and can be affected by contextual factors (Beltman 

and Volet 2007; McCaul et al. 2007; Sanderson et al. 2008; 

Weiss-Gerlach et al. 2008). Therefore, cognitive and 

motivational factors are discussed both as person factors 

and emergent processes, with the distinction reflecting 

the time course of their emergence.

Other data show that the attentional salience of 

smoking cues also predicts vulnerability to relapse. 

Using the Stroop paradigm, researchers presented 

smoking-related and neutral words to 158 volunteers for a 

smoking cessation program (Waters et al. 2003b). Results 

show that if words related to smoking attracted the attention of smokers, an early relapse was more likely within a 

three-month follow-up interval. In theory, the attentiongrabbing properties of words related to smoking reflect 

the motivational potency of smoking that could then 

account for the greater likelihood of a relapse.

Tobacco Dependence

Measures of tobacco dependence predict the likelihood that a smoker will achieve long-term abstinence 

from tobacco use. For instance, self-report measures of 

dependence tend to predict cessation and relapse (Breslau and Johnson 2000; Piper et al. 2004; Shiffman et 

al. 2004a). However, the various self-report measures 

of dependence often do not show good agreement with 

one another (Breslau and Johnson 2000; Moolchan et al. 

2002). This finding is consistent with emerging evidence 

that nicotine dependence is multifactorial (Hudmon et 

al. 2003; Piper et al. 2004; Shiffman et al. 2004b). More 

recent evidence suggests that some dependence factors 

are more predictive of dependence than are others. In particular, self-report measures of tobacco dependence that 

assess heavy automatic smoking that is not discriminated 

on time or context are most consistently associated with 

heightened risk of relapse (Transdisciplinary Tobacco Use 

Research Center 2007; Piper et al. 2008). This finding is 

consistent with the observation that objective measures 

of a high rate of smoking, such as expired carbon monoxide levels and serum concentrations of cotinine, are often 

related to the likelihood of a relapse (Nørregaard et al. 

1993; Faue et al. 1997; Kenford et al. 2002). Even in 

the best circumstances, however, measures of tobacco

dependence account for only modest amounts of variation in risk of relapse. This finding is consistent with the 

notion that relapse is a function of multiple person factors, emerging processes, and contextual factors. 

In addition to dependence, the sensitivity of a 

smoker to a nicotine reinforcement predicts a shorter 

latency to relapse (Perkins et al. 2002a). In contrast, formal laboratory measures of tolerance to the effects of nicotine do not appear to be significantly related to relapse 

(Perkins et al. 2002a).

Demographic and Lifestyle Variables

Studies have related numerous variables of demographic factors and lifestyle to vulnerability to relapse. For 

example, researchers have related an increased likelihood 

of relapse to younger age (Nides et al. 1995; Ockene et 

al. 2000; Hyland et al. 2004), a low SES or a low level of 

education (Nides et al. 1995; Ockene et al. 2000; Wetter 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

et al. 2005b), being unmarried (Nides et al. 1995; Ockene 

et al. 2000), higher levels of tonic stress, and more stressors or the perception of a higher stress level (Swan et al. 

1988; Wewers 1988; Cohen and Lichtenstein 1990; McKee 

et al. 2003). Of these factors, low SES and low educational 

status appear to be especially strong and consistent predictors of ability to abstain from smoking on a continuing basis (Mullen 2004; Wetter et al. 2005a; Fernández et 

al. 2006; Lee and Kahende 2007; Letourneau et al. 2007). 

In addition, some data from clinical trials and population 

samples indicate that women may be less likely than men 

to maintain abstinence from tobacco use (Hubert et al. 

1987; Bjornson et al. 1995; Community Intervention Trial 

for Smoking Cessation 1995; Wetter et al. 1999; Smith et 

al. 2003; Hyland et al. 2004). However, such relationships 

are not consistently found across different data sets. For 

instance, as noted above, numerous data sets reveal that 

females are more likely to relapse to tobacco use than are 

males. However, a substantial number of studies fail to find 

such a relationship (Gritz et al. 1998; Killen et al. 2002; 

Westmaas and Langsam 2005; Velicer et al. 2007; Walsh 

et al. 2007). Besides the issue of consistency, additional 

topics deserve greater research attention. These topics 

include exploration of how the various person factors 

“work together” to affect the success or failure of smoking cessation. In addition, it is important to determine 

whether the different person factors are associated with 

different sorts of relapse mechanisms or processes; that is, 

regardless of the likelihood of relapse in different smoker 

groups, it is important to determine whether relapse processes “unfold” differently in such groups. 

Research suggests that men and women may differ 

in sensitivity to environmental events. There is evidence, 

for instance, that environmental or conditioned cues 

related to use of nicotine, such as seeing information 

about nicotine dose, seeing others smoking, or receiving 

cues previously paired with nicotine, tend to elicit stronger motivational response to use the drug in women than 

in men (Pomerleau et al. 2005; Perkins et al. 2006; Leventhal et al. 2007; Walsh et al. 2007). These data agree 

with animal research data showing that nicotine-paired 

environmental cues are more effective in eliciting selfadministration of nicotine in female rats than in male rats 

(Chaudhri et al. 2005). Complementary data suggest that 

men are more likely to be responsive to actual nicotine 

dose and other pharmacologic properties than are women 

(Perkins et al. 2006). If men are indeed more sensitive to 

nicotine’s pharmacologic properties than are women, this 

could explain why men who use NRT sometimes achieve 

higher levels of success with smoking cessation than do 

women who use NRT (Wetter et al. 1999; Perkins 2001; 

Cepeda-Benito et al. 2004) and why this finding did not 

hold for use of psychosocial interventions (Velicer et 

al. 2007).

Other studies show additional differences by gender. 

Data from study of a community-based population sample suggest that financial stressors may be more likely to 

inhibit smoking cessation in women than in men and that 

negative health events are more likely to prompt cessation 

in men (McKee et al. 2003). Other research shows that 

male smokers tend to be more reactive to relatively minor 

stressful events (i.e., hassles) than are women (Wetter et 

al. 1999; Delfino et al. 2001; Todd 2004). Although there is 

mounting evidence of differences by gender in reaction to 

nicotine or environmental cues (Perkins et al. 1999), and 

in motivation to use tobacco or nicotine, these differences 

have not been definitively linked with either relapse or differences by gender in relapse. Even less is known about 

the relationship of factors such as low SES or educational 

attainment to likelihood of smoking cessation (Wetter et 

al. 2005a).

One innovative approach to unraveling the complex 

interrelationships among the multiple person factors and 

relapse is to conduct classification or decision-tree analyses. These analyses have been used to determine whether 

categories of person factors (e.g., male versus female) 

comprise smoker subgroups that can be distinguished 

on the basis of their risk profiles for cessation failure. 

One example of this approach generated six subgroups of 

women smokers (Swan et al. 2004). For some subgroups, 

cessation failure appeared to be related to educational 

attainment and the number of previous attempts to stop 

smoking; for others, failure was more strongly related to 

body mass index and family history of depression (Swan et 

al. 2004). In contrast, male smokers comprised subgroups 

more highly distinguished by variables related to nicotine 

dependence, such as FTND score (Heatherton et al. 1991) 

and the number of years of smoking. In addition, male 

subgroups were distinguished on the basis of previous 

NRT and a history of depression. This type of classification 

or decision-tree analysis is useful because it has the potential to reveal factors that are highly predictive of cessation 

outcome in a subgroup of smokers, even if a factor is not 

important over an entire sample (Swan et al. 1997, 1999). 

Further research is needed to assess the replicability of 

such findings. 

Psychiatric and Affective Dimensions

Some researchers have reported that the vulnerability to failure of smoking cessation or relapse to smoking is positively related to a history of depression, alcohol 

intake, a tendency toward negative affect, and an intolerance of psychological distress. As with most other individual differences, these relationships are either small in 
Surgeon General’s Report

174 Chapter 4

magnitude, inconsistent, or both. For example, both studies of population samples and clinical trials indicate that 

a history of depression or depressive symptoms predicts a 

greater likelihood of a relapse or a failure to stop smoking (Anda et al. 1990; Romans et al. 1993; Ferguson et al. 

2003; Smith et al. 2003; Japuntich et al. 2007). However, 

one meta-analysis of data from 15 clinical trials failed to 

find such an effect (Hitsman et al. 2003). Studies in this 

meta-analysis generally excluded participants who were 

currently depressed or taking antidepressant medication. 

One hypothesis is that if depression is correlated 

with vulnerability to relapse, the correlation may be 

attributable to the presence of two specific subpopulations 

of persons who have depression. Hitsman and colleagues 

(2003) observed that several studies have found a relationship between recurrent (multiple episode) depression and 

heightened risk of failure to stop smoking (Glassman et 

al. 1993; Covey et al. 1999; Brown et al. 2001). Haas and 

colleagues (2004) also found that a high rate of failure to 

stop smoking was associated with a history of multiple, 

but not single, episodes of depression. There also is evidence that current depression is more strongly associated 

with relapse than is past depression (Niaura et al. 2001; 

Japuntich et al. 2007; Turner et al. 2008). These results suggest that associations between depression and relapse may 

be attributable to subpopulations with depression, that is, 

those who are either currently depressed or who are prone 

to recurrent depression. These types of depression may be 

linked to risk of relapse because both were associated with 

recurrent or chronic negative mood (Niaura et al. 2001; 

Haas et al. 2004; Japuntich et al. 2007), and negative mood 

has repeatedly been linked with increased likelihood of 

relapse to smoking among persons with depression 

(Kahler et al 2002; Leventhal et al. 2008). However, it is 

possible that the heightened risk of relapse presented by 

current or recurrent depression is caused by other factors, 

such as poor coping skills or low self-efficacy.

There is also mixed evidence as to whether a history 

of alcohol abuse or dependence increases vulnerability to 

relapse to smoking. Some studies show an elevated risk of 

relapse (Hughes 1993; Breslau et al. 1996), but in others 

risk is not elevated (Covey et al. 1993; Hurt et al. 1995). 

Perhaps the best characterization of the evidence is the 

finding that active abuse of or dependence on alcohol constitutes a risk factor for relapse to smoking (Hurt et al. 

1994; Kalman et al. 2001, 2002). However, there may be 

little or no risk if problems with alcohol are in remission 

(Hughes and Callas 2003). Evidence also shows that an 

active consumption of alcohol enhances the risk of relapse 

to smoking (Krall et al. 2002; McKee et al. 2003). Thus, 

the risk of relapse posed by alcohol use is not attributable to alcohol being a marker for a trait-like vulnerability to relapse but rather is attributable to the immediate 

(situational) effects of intoxication. However, there is 

modest evidence that another syndrome of disinhibition, 

attention-deficit/hyperactivity disorder, is associated with 

elevated risk of relapse to smoking (Humfleet et al. 2005).

An additional affective dimension that has been 

studied and may contribute to a heightened risk for 

relapse is the ability of a person to tolerate distress or to 

persist in a distressing task. Hence, several studies have 

associated measures of distress tolerance among smokers with the likelihood of or latency to relapse. In these 

studies, smokers with low vulnerability to relapse showed 

a greater persistence in tasks such as breathholding and 

mental arithmetic than did smokers with high vulnerability to relapse (Hajek et al. 1987; Brown et al. 2002). This 

finding provides evidence that characteristics such as an 

inability or unwillingness to tolerate distress is linked to 

a vulnerability to relapse. An inability to tolerate negative 

affect may be especially related to early relapse to smoking 

(Zvolensky et al. 2004; Brown et al. 2008).

In summary, the person factors that yield the strongest or most consistent prediction of relapse are measures 

of tobacco dependence and cognitive and attitudinal variables such as expectation of smoking reinforcement. In 

addition, measures of low SES and low educational attainment are also fairly consistently related to risk of relapse. 

Other relatively stable person factors are more modestly 

or inconsistently related to smoking relapse. Predictors 

of relapse vary from study to study, probably reflecting 

differences in the populations studied, different mixes 

of predictors included in the studies, and diverse methods and measures of the same target constructs. In addition, much of the variation in vulnerability to relapse is 

no doubt caused by other factors not measured in most 

studies—for example, exposure to episodic events and

reactions to smoking cessation (Shiffman et al. 1996a,c; 

Kenford et al. 2002; Gwaltney et al. 2005a,b; McCarthy et 

al. 2006). Also, other variables may account for apparent 

direct associations between person factors and relapse. 

For instance, persons who drink heavily may be especially 

likely to socialize with other smokers, and an exposure to 

smokers may cause heightened risk of relapse.

Emergent Processes

Emergent processes are reflected in rapid changes 

in symptoms or behaviors that occur within several days 

before a lapse or relapse. Researchers have typically studied emergent processes across two temporal windows: one 

that begins at the time of smoking cessation and therefore captures initial responses to the event and a second 

that starts close in time to a lapse in cessation and captures changes in behaviors or symptoms leading up to 

the event. Both types of analyses provide evidence that 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

emergent processes set the stage for smoking lapses and 

relapses. In general, emergent processes do not depend 

on the sort of treatment or cessation strategy used—for

example, they occur in smokers receiving active or placebo pharmacotherapy.

Tobacco Withdrawal and Affective Symptoms

Perhaps the strongest evidence that emergent processes affect vulnerability to relapse comes from research 

on the tobacco withdrawal syndrome. Until recently, 

major reviews concluded there was little evidence that 

withdrawal symptoms were consistently related to the 

likelihood of a relapse (Hughes et al. 1990b; Patten and 

Martin 1996). However, in the decade ending in 2004, 

research has shed light on the nature of withdrawal, as 

well as its relationship to a relapse (Hughes 2007). First, 

in many smokers, perhaps most of those attempting to 

stop smoking, withdrawal symptoms are persistent and 

often remain elevated for months after an attempt to stop 

smoking (Gilbert et al. 1998, 2002; Piasecki et al. 1998, 

2000). Second, withdrawal results (1) in great heterogeneity of symptoms, both in and across smokers, and (2) in 

volatile changes in affect and craving (see Figure 4.6 for 

craving pattern) (Piasecki et al. 2003a; McCarthy et al. 

2006). Third, withdrawal results in vulnerability to more 

severe symptoms in reaction to environmental events 

than those that occur before smoking cessation (Figure 

4.7) (McCarthy et al. 2006). In addition, research shows 

that some of these symptomatic effects of tobacco withdrawal are associated with an increased vulnerability to 

relapse. In general, smokers are more likely to relapse 

if withdrawal symptoms after smoking cessation are 

severe, increase in severity over time, or are highly variable (Piasecki et al. 1998, 2000, 2003b; McCarthy et al. 

2006). Research also shows that withdrawal symptoms 

indicate vulnerability to relapse, as the result of either 

immediate increases in symptoms in response to abstinence from smoking or emergent changes in symptoms 

that occur across the days preceding a lapse in smoking 

cessation (Figure 4.8) (Piasecki et al. 2003b; McCarthy et 

al. 2006). 

Withdrawal measures tap a variety of symptoms, but 

research suggests that self-reported craving and negative 

affect are the symptoms most predictive of relapse (West 

et al. 1989; Killen et al. 1991; Swan et al. 1996; Killen 

and Fortmann 1997; Piasecki et al. 1998; McCarthy et al. 

Figure 4.6 Individual estimated slopes in craving ratings over three weeks prequit, from just before to just after 

midnight on the quit date, and over three weeks postquit

Source: McCarthy et al. 2006.

Note: The synthesized trajectories are based on multiple daily ratings made in real time with electronic diaries. The heavy black 

line represents the mean trend in craving ratings across all individuals. All other lines represent the slopes or trajectories of craving 

ratings for individual smokers and show how variable withdrawal symptoms can be across smokers across time. 
Surgeon General’s Report

176 Chapter 4

2006). Other elements of the withdrawal syndrome, such 

as sleep disturbances or weight gain, are less consistent 

indices of a vulnerability to relapse (Wetter et al. 1995; 

Borrelli et al. 2001).

One piece of evidence that supports the role of 

withdrawal in precipitating relapse is research showing that withdrawal suppression appears to mediate the 

effects of pharmacologic treatments for smoking cessation 

(McCarthy et al. 2006; Shiffman et al. 2006). Statistical 

tests suggest that nicotine replacement and bupropion 

treatments reduce relapse risk to the extent that they suppress withdrawal symptoms. These studies suggest only 

partial mediation, however, consistent with the notion 

that other factors also influence relapse.

Although it is clear that emergent trends can set the 

stage for lapses and relapses to smoking, much remains to 

be learned about these associations. The time course by 

which emergent symptoms anticipate lapses, for example, 

needs more focused examination, because a gradual emergence of symptoms would permit the delivery of preventive interventions. Several studies show that craving and 

exacerbation of withdrawal symptoms precede lapses by 

several days (Piasecki et al. 2003b; McCarthy et al. 2006; 

Allen et al. 2008). However, as noted earlier in this section, other research shows that lapse-provoking increases 

in negative affect unfold within hours rather than days 

(Figure 4.9) (Shiffman and Waters 2004).

Cognitive and Attitudinal Influences

Emergent cognitive and attitudinal processes may 

also enhance vulnerability to relapse. For instance, one 

study used real-time data recording to show that low 

Figure 4.7 Reactions for the three-week period before the quit date and the three-week period after the quit date

Source: McCarthy et al. 2006.

Note: Data are from 70 smokers making a quit attempt. The y-axis depicts the magnitude of the average standardized coefficient 

derived from multivariate, multilevel models. Episodic event coefficients were estimated separately in the prequit and postquit 

periods. The beta weights shown reflect the degree of symptom change (in overall withdrawal, hunger, craving, and negative affect) 

associated with the presence versus absence of an episodic event. (A) Symptom coefficients associated with smoking in the past 

15 minutes in models of overall withdrawal. (B) Symptom coefficients associated with recent exposure to smoking behavior. 

(C) Symptom coefficients associated with exposure to recent stressful events. (D) Symptom coefficients associated with recent 

strong urges and temptations. Results suggest greater symptomatic reactivity to events after quitting than before quitting.
Nicotine Addiction: Past and Present 177

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

abstinence and self-efficacy estimates, along with high 

expectations of smoking reinforcement, predicted a lapse 

to smoking that occurred on the following day (Gwaltney 

et al. 2005a). These effects were independent of scores 

for these measures on the day of smoking cessation, 

suggesting that the effects reflect emergent processes and 

not trait differences. Other research shows that persons 

who lapse to smoking appear to experience a marked dip 

in motivation during the week leading up to a lapse (Hedeker and Mermelstein 1996). 

Timing and Motivational Significance of 

Emergent Processes 

As previously noted, both symptomatic and attitudinal changes emerge across the period after smoking cessation and predict a relapse. Such changes may occur in the 

first few hours after cessation or in the hours or days just 

before a lapse to smoking (Figures 4.8 and 4.9) (Hedeker 

and Mermelstein 1996; Gwaltney et al. 2005a). Emergent 

symptoms may occur at any time during the postcessation period. However, research shows that symptoms that 

occur early in this period (e.g., in the first 24 hours) may 

Figure 4.8 Withdrawal severity and lapse behavior among smokers who abstained for the first five days of a quit 

attempt

Source: Piasecki et al. 2003b.

Note: Matched abstainers (MAs; n = 152) had never smoked during the follow-up period. Transient lapsers (TLs; n = 124) had lapsed 

but did not immediately resume regular smoking. Protracted lapsers (PLs; n = 28) had immediately returned to regular smoking 

upon lapsing. The figure shows predicted withdrawal severity growth functions for these three groups over several periods: baseline 

(prequit: prior to day 0 in the first panel), the first five days of the quit attempt, the five days preceding and following the lapse dates 

of the lapsers (TL and PL participants); and last five days of the quit attempt (when TL and PL participants were smoking and MA 

participants were abstinent). Each lapsed participant was paired with an MA to produce temporal equivalence across the prelapse and 

postlapse windows. To compare the symptoms of lapsers with those of nonlapsers, the investigators randomly matched each lapser 

with a person who did not lapse, then compared the predicted symptom trajectories of these individuals over the same postquit 

periods of time defined by when a lapse actually occurred.
Surgeon General’s Report

178 Chapter 4

be more tightly linked to outcomes than are later symptoms. For instance, in the Killen and Fortmann (1997) 

research, 2,600 smokers were entered into three studies 

through population-based recruitment. Across all three 

studies, craving ratings gathered early in the attempt to 

stop smoking (e.g., 24 hours postcessation) predicted 

relapses across the first year after cessation. Smokers 

with ratings in the highest quartile for craving were twice 

as likely to relapse as were smokers in the lowest quartile (31 versus 16 percent, respectively, averaged across 

all three studies). This research agrees with a wealth of 

other evidence that appearance of symptoms early in the 

attempt to stop smoking is negatively related to an ability 

to remain abstinent and to avoid a relapse (Killen et al. 

1991; Doherty et al. 1995; McCarthy et al. 2006). 

These data supported a large amount of evidence 

showing that various types of self-reports become markedly more predictive of ultimate outcomes as soon as 

persons have some experience in the attempt to stop 

smoking (Kenford et al. 2002; Gwaltney et al. 2005a). This 

evidence suggests that even though smokers have experience with abstinence from smoking and have memories of 

previous attempts to stop smoking, many are still unprepared for the forces unleashed by abstinence, which ultimately lead to a relapse. 

Situational Instigators

A large body of research shows that lapses and 

relapse are associated with a limited set of contextual or 

situational features. Studies that use remote data collection techniques, in which data are gathered long after 

the lapse or relapse occurred, show that the contexts of 

lapses are characterized by features such as negative 

affect, urges to smoke, alcohol consumption, and cues to 

smoke (O’Connell and Martin 1987; Brandon et al. 1990). 

Figure 4.9 Negative affect in the days and hours preceding the first lapse for smokers who attributed their first 

lapse to a stressor or bad mood (stress trigger) or to some other type of event (other trigger)

Source: Adapted from Shiffman and Waters 2004 with permission.

Note: Stress trigger, n = 29; other trigger, n = 61. These data suggest that increasing negative affect is a risk factor for lapsing for some 

smokers. Error bars show one standard error. 
Nicotine Addiction: Past and Present 179

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Research using real-time data acquisition shows that 

situations in which lapses occur (lapse situations) can be 

distinguished from temptations, that is, instances in 

which smoking did not actually occur, and from random 

occasions on the basis of the negative moods that occur in 

relation to lapses (Shiffman et al. 1996c). Negative moods 

are significantly more likely to co-occur with lapses than 

with temptations without smoking or to occur alone at 

randomly determined times. These negative moods tend 

to be strongly associated with reports of interpersonal 

stress such as arguments.

Shiffman and colleagues (1996c) also found that 

lapse situations can be distinguished from temptation 

situations and random occasions in that lapses are more 

likely to be accompanied by alcohol intake and strong 

urges to smoke that occur later in the day. Considerable 

additional evidence demonstrates that alcohol intake sets 

the stage for lapses (Borland 1990; Brandon et al. 1990). 

Also, both lapses and temptation situations tend to cooccur in the presence of other persons who are smoking. 

Thus, the availability of cigarettes and the modeling of 

smoking are associated with an increased desire to smoke. 

However, such cues do not reliably distinguish between 

the desire to smoke and the occurrence of smoking. 

Finally, the smoker is not a passive party in the progression to relapse. The data show that the execution of a coping response is more characteristic of temptation than of 

lapse occasions, suggesting that coping detoxifies temptation situations (Shiffman et al. 1996c). 

Attesting to the powerful influence of contextual 

factors, recent research shows that smoking policies or 

the numbers of smokers in the person’s environment reliably predict likelihood of relapse or success in cessation 

(Letourneau et al. 2007). For instance, risk of relapse or 

rapidity of relapse is heightened by the number of smokers 

in a person’s social network, whether the person’s partner smokes (Mullen 2004; Letourneau et al. 2007; Macy 

et al. 2007; Solomon et al. 2007), and whether there are 

smoking restrictions at the person’s place of work or at 

home (Gilpin et al. 1999; Lee and Kahende 2007; Macy et 

al. 2007). However, some data suggest that bans in social 

contexts or restaurants may not be related to the success 

of cessation (Albers et al. 2007).

In general, research on situational indicators suggests that temptations to smoke and smoking lapses are 

contingent on internal symptoms of withdrawal (e.g., 

urges to smoke), alcohol use, and environmental signals 

of smoking, including the availability of cigarettes and the 

status of smoking restrictions. These findings are consistent with theories that drug availability and distress both 

constitute potent prods to motivation for drug use (Niaura 

et al. 1988; Skjei and Markou 2003; Baker et al. 2004). 

Integration Across Relapse Influences

Person factors, situational cues, and emergent processes all influence risk of relapse. Moreover, research suggests that relapse risk reflects an interaction among these 

types of influences (Shiffman 1989a; Piasecki et al. 2002). 

For example, the intensity of the urge to smoke during 

temptation events predicts the likelihood of a lapse (Shiffman et al. 1997). However, this relationship depends on 

the level of urges to smoke reported on the day of smoking cessation. Thus, situational ratings are related to trait 

characteristics, such as tobacco dependence or emergent 

trends (e.g., withdrawal) that affect ratings for the urge to 

smoke on the day of smoking cessation. The relationship 

between the type of lapse situation and an emergent negative affect are shown in Figure 4.9. Data also show that 

the intensity of the urge to smoke during temptation episodes grows in the days leading up to a lapse (Shiffman et 

al. 1997). These data provide further evidence for the role 

of emergent processes in affecting situational reactions 

that, in turn, are related to lapse events. Finally, this same 

research shows that the level of the urge to smoke 

reported by persons on awakening predicted the likelihood 

of a lapse later on the same day. For some reason, urges 

to smoke in the morning, as opposed to urges reported at 

other times, tended to provide the most powerful predictions of lapses. In sum, research on the urge to smoke 

shows that the likelihood of a lapse reflects the interaction 

of trait factors, emergent processes, and situational cues.

Other data suggest interactive influences on the 

likelihood of a lapse. For example, Gwaltney and colleagues (2005b) found that persons who have low levels 

of trait-like self-efficacy at baseline show marked declines 

in self-efficacy in situations that produce strong urges or 

negative affect. Hence, trait measures capture a person’s 

vulnerability to succumb to situational challenges. A chief 

goal of future research is to elucidate how various types 

of influences on relapse interact to produce a relapse in a 

particular person at a particular time. 

Transition from Lapse to Relapse 

or Recovery

Exploration of the factors that transform lapses into 

relapses is vital, because initial incidents of tobacco use 

routinely usher in a return to regular smoking (Baer et 

al. 1989; Garvey et al. 1992; Kenford et al. 1994). Study of 

the factors that influence the lapse-relapse progression is 

also important, because it seems that factors affecting this 

progression differ from factors that affect the occurrence 

of the lapse itself. For instance, Wileyto and colleagues 
Surgeon General’s Report

180 Chapter 4

(2005) found that the likelihood of lapse in a smoker was 

relatively unaffected by his or her dependence level (FTND 

score) or symptoms of depression. However, both of these 

factors were associated with greater difficulty in recovering from a lapse—that is, reestablishing abstinence for at

least 24 hours. 

Researchers have found that the probability or the 

latency of a relapse after a lapse can be predicted by nicotine dependence (Shiffman et al. 1996b, 1997) and by features of the lapse situation, such as the failure to make 

a coping response, feelings of hopelessness, and stronger 

urges to smoke during the lapse (Shiffman et al. 1996b). 

In addition, postlapse declines in self-efficacy of abstinence indicate a greater likelihood of or a faster progression to a relapse (Gwaltney et al. 2005b). Thus, it appears 

that individual capitulation in the cessation attempt and 

high levels of nicotine dependence foster the progression 

to a relapse. 

Lapses appear to play a causal role in precipitating a relapse. This finding is indicated by the report that 

smokers randomly assigned to experimental lapse events 

resume smoking more rapidly than do smokers not 

assigned to such lapse experiences (Chornock et al. 1992). 

Summary and Future Directions

The data suggest that factors contributing to a 

relapse are multidimensional and involve many processes 

associated with addiction, including personal traits, past 

experiences with nicotine, associative learning and conditioning, and the manifestation of withdrawal symptoms. 

Development of treatments to prevent lapses (occasional 

smoking) is important, because these events so frequently 

lead to a relapse. In addition, this review suggests that 

treatments should target specific phenomena that may 

motivate lapses and relapses: (1) increases in withdrawal 

symptoms, especially urges to smoke and negative affect 

that occur in the first 48 hours of smoking cessation (Figures 4.6 and 4.8); (2) emergent increases or spikes in negative affect and urges that occur at any point after smoking 

cessation (Figures 4.8 and 4.9); (3) the drop in selfconfidence or the increase in urges engendered by a lapse; 

(4) urges that occur shortly after awakening that may 

or may not reflect conditioned withdrawal effect (Figure 

4.6); (5) a trait-like intolerance of distress; (6) increased 

urges to smoke and withdrawal symptoms prompted by 

smoking-related cues or stressful events (Figure 4.7); and 

(7) alcohol consumption and its effects on cognitive and 

motivational processes. Although relapse has also been 

associated with relatively stable demographic factors such 

as SES and educational status, it is unclear why these 

factors are associated with failure of smoking cessation 

and which treatment strategies could be used to counter 

them. Future research should be focused on further refining types for relapse and recovery, understanding genetic 

and neurobiologic underpinnings, and developing effective treatments for these types. 

Evidence Summary

The 1988 Surgeon General’s Report, The Health 

Consequences of Nicotine Addiction, concluded that 

“nicotine is the drug in tobacco that causes addiction” 

(USDHHS 1988, p. 9). Studies show that animals selfadminister or prefer nicotine over saline and that many 

people smoke to regulate blood concentrations of nicotine. For example, if smokers are given cigarettes with 

lower nicotine yields than their usual brands, they tend 

to smoke more intensely or to cover the filter ventilation 

holes to increase their nicotine intake. The VTA region of 

the brain and the mesocorticolimbic dopamine neurons 

originating in this brain site are primarily responsible for 

the positive reinforcing aspects of nicotine. An increase 

in levels of dopamine is mediated by nicotine directly 

stimulating nAChRs, primarily α7 homomeric and α4β2-

containing nAChRs within the VTA, thus increasing activity of VTA neurons projecting to the nucleus accumbens 

and the frontal cortex. Nicotine stimulates α7 nAChRs on 

glutamatergic terminals that release glutamate, an excitatory neurotransmitter, which results in increased release 

of dopamine in the nucleus accumbens, amygdala, and 

frontal cortex. Nicotine also excites nAChRs on GABAreleasing terminals. Thus, levels of GABA, an inhibitory 

neurotransmitter, are also increased by nicotine. However, 

the interplay between the quick desensitization of nAChRs 

on the GABA neuron and the higher doses of nicotine required to desensitize nAChRs on the glutamate neuron 

result in a greater increase in dopamine levels. 

The neurophysiology associated with withdrawal 

symptoms may be based on the type of symptoms 

experienced (e.g., somatic versus affective). It appears that 

nAChRs differ in their involvement in both the somatic 

and affective components of nicotine withdrawal and 

dependence. As seen in animal studies, β4 nAChRs play an 

important role in the somatic signs of withdrawal, whereas 

β2 nAChRs play an important role in the affective, but not 
Nicotine Addiction: Past and Present 181

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

somatic, aspects of withdrawal. The role of α4 nAChRs is 

unclear, but these receptors may play a role in both the 

affective and somatic withdrawal effects of nicotine addiction. The α7 nAChRs appear to be involved only in some of 

the somatic signs of nicotine withdrawal. 

The amount and speed of nicotine delivery also plays 

a critical role in the potential for abuse of tobacco products. The speed and amount of nicotine delivered to the 

brain depend on the amount of nicotine in the product, 

the alkalinity of the product, and the route of administration. Nicotine, 3-(1-methyl-2-pyrrolidinyl)pyridine, is a 

volatile alkaloid in the tobacco plant, and its absorption 

and renal secretion is highly dependent on pH. Products 

with higher alkalinity are associated with greater amounts 

of nicotine in the nonionized or free base state, which can 

vaporize more easily into the gas phase, can be deposited 

directly on the lung tissues, and crosses cell membranes 

more rapidly than ionized nicotine. Tobacco products 

can contain constituents such as ammonia to increase 

the conversion of nicotine to the nonionized or free base 

state. Physical design features such as filter-tip ventilation also increase the free base fraction of nicotine (see 

Chapter 3, “Chemistry and Toxicology of Cigarette Smoke 

and Biomarkers of Exposure and Harm”). The fastest rate 

of nicotine delivery is through smoking cigarettes. Nicotine, when inhaled, enters the lungs, which present a large 

surface area of small airways and alveoli, undergoes dissolution in pulmonary fluid at a high pH, is transported 

to the heart, and then immediately passes to the brain. 

This rapid and bolus delivery of nicotine through cigarettes leads to greater control over the amount of nicotine 

delivered to the brain and results in higher abuse potential 

than do other tobacco- or nicotine-containing products.

Nicotine in the tobacco product and its kinetic 

profile are not the only factors that might contribute to 

a tobacco product’s potential for addiction. Other constituents may also serve as reinforcers or may enhance 

blood levels of nicotine or its effects. For example, animal 

studies have shown that nornicotine, a secondary tobacco 

alkaloid, functions as a reinforcer, but at less potency than 

nicotine. The effect of nornicotine in humans is unclear. 

Acetaldehyde, another constituent in tobacco smoke, 

which results from burning sugars and other materials in 

the tobacco leaf, may play a role in increasing the reinforcing effects of nicotine. In animal studies, acetaldehyde 

enhanced the acquisition of nicotine self-administration 

among adolescent rats but not adult rats. Extracts from 

flue-cured tobacco that appear to inhibit MAO activity 

in the brain may be another contributory factor to the 

reinforcing effects of cigarettes. Increased MAO inhibition results in increased levels of catecholamines. Current 

smokers have lower levels of MAO than do nonsmokers or 

former smokers. 

Tobacco product design and ingredients contribute to the risk of addiction by reducing noxious effects 

such as the unpleasant taste of nicotine and unpleasant 

sensory effects (see Chapter 2, “The Changing Cigarette”). 

Such designs include ventilation to cool the smoke and 

ingredients such as menthol and chocolate that make 

nicotine inhalation more pleasant. Other nonnicotine factors can also contribute to addiction potential. These factors include the associative learning processes (internal 

and environmental cues linked with nicotine administration) that develop with repeated tobacco use. This associative learning can be as powerful as the direct effects of 

nicotine. For example, presenting smokers with sensory 

aspects of smoking without nicotine has resulted in a 

decrease in craving for cigarettes, a decreased subset of 

withdrawal symptoms, and short-term reinforcing efficacy 

similar to that of cigarettes containing nicotine (see Chapter 3, “Chemistry and Toxicology of Cigarette Smoke and 

Biomarkers of Exposure and Harm”).

Typically, smoking initiation occurs during adolescence. Research shows that adolescent smokers 

report some symptoms of dependence even at low levels 

of cigarette consumption, and animal studies show that 

sensitivity to nicotine in adolescents differs from that 

in adults. For example, results from the paradigms of 

self-administration and conditioned place preference in 

rats demonstrate that adolescence may be at a stage of 

development with higher sensitivity to nicotine exposure 

than that in adults. Using mixture modeling, longitudinal 

studies have identified multiple age-related trajectories 

of smoking behavior. These trajectories typically include 

smokers with early initiation of smoking and steep acceleration of smoking, persons who engage in experimental 

or light smoking, smokers with late initiation and accelerated progression of smoking, persons who stopped smoking, and those who never smoked. The group with early 

initiation and steeply escalating and persistent smoking 

has been associated with familial smoking, which reflects 

genetic and/or environmental risk factors, less parental 

support, and a risk for chronic heavy smoking in adulthood. Ethnic differences have also been observed for the 

age at initiation of smoking and the speed of progression 

in smoking. These studies showed that African Americans 

were more likely to have slower progression of smoking and a lower number of cigarettes smoked than do 

Whites. Studies that have looked at predictors for developing nicotine addiction or heavy smoking suggest the 

importance of both genes and environmental influences. 

Parental smoking, parental substance abuse disorders, 

and externalizing disorders (attention-deficit/hyperactivity, disruptive behavior, and alcohol and drug abuse) have 

been found to be predictive of nicotine dependence and/or 

daily smoking. 
Surgeon General’s Report

182 Chapter 4

Initiation and persistence of smoking and nicotine 

dependence show strong heritability. Most coefficients of 

reported heritability range from less than 0.3 to more than 

0.8 and vary on the basis of the smoking behavior phenotype examined and the social or environmental factors 

such as prevalence of smoking. The balance of evidence 

suggests that the risk of smoking initiation is influenced 

by both genetic and environmental factors, whereas the 

risk of smoking persistence may have a stronger genetic 

component. Although some genetic influences on smoking initiation and persistence are common, there are also 

separate and unique genetic influences for initiation and 

for persistence. Studies also suggest that the ability to stop 

smoking is under a strong genetic influence, and some 

consider this phenotype to be the key behavioral phenotype for nicotine dependence. Molecular genetic studies 

have been conducted to examine the specific genetic factors and biologic mechanisms involved in nicotine addiction. Most of the candidate gene studies have focused on 

genetic variation in nAChRs, relevant neurotransmitter 

pathways, or genes for nicotine-metabolizing enzymes. 

Candidate gene studies are association-based studies 

comparing prevalence of candidate gene variants in two 

unrelated groups—for example, nicotine-dependent versus nondependent persons. Examples of candidate gene 

variants that have been examined include nAChR subunits, such as CHRNA4 and CHRNA5; dopamine receptors 

D2 and D4 (DRD2 and DRD4) and dopamine transporter 

(DAT) genes; tryptophan hydroxylase, which is associated with serotonin biosynthesis; serotonin transporter 

5HTTLPR, which is associated with genes that code for 

serotonin reuptake; MAOA and DβH genes, which affect 

norepinephrine pathways; genes in the endogenous opioid 

pathway (e.g., OPRM1); and genes involved in the metabolism of nicotine (e.g., CYP2A6).

To date, the only candidate genes with consistent 

evidence of an association with smoking behavior or nicotine dependence are CYP2A6 and 5HTT and SNPs in the 

CHRNA5/A3/B4 gene cluster. More research has been conducted on the effects of CYP2A6. Variants of P-450 CYP2A6 

associated with *NULL or reduced activity are associated 

with reduced levels of the CYP2A6 enzyme and slower 

rates of nicotine metabolism, leading to higher plasma 

levels of nicotine for a given dose of nicotine. Persons 

who carry these variants with *NULL or reduced activity 

tend to have lower risk for becoming smokers, reduced 

cigarette consumption, and possibly higher likelihood 

of successful smoking cessation than that for persons 

with wild-type genotypes and higher rates of nicotine 

metabolism. Research in this area will be greatly enhanced 

when there is agreement in the field on phenotypes for 

smoking initiation, trajectory toward nicotine dependence, and nicotine dependence. One area of research that 

has provided promising initial evidence is the pharmacogenetics of treatment to aid in smoking cessation, which 

included examining genetic variations in drug-metabolizing enzymes and variations in drug targets to predict 

responses to treatment. It is important to recognize that 

although genes may play an important role in the various 

aspects of smoking behavior, the risk for smoking exists in 

persons without the gene variants, and it is predominantly 

exposure, rather than the host, that leads to smokingrelated illnesses.

Studying recovery from smoking can provide valuable information on the nature of tobacco addiction and 

the factors that affect it. Relapse to smoking occurs at 

a high rate, and most smokers who ultimately relapse 

resume smoking early after the attempt to stop smoking. 

The risk for relapse is particularly high among those who 

lapse or engage in a single episode of smoking after their 

first day of cessation. The pattern of return to smoking 

varies across individuals. However, on average, a second 

lapse occurs within 24 hours of the first lapse, and lapse 

to relapse occurs three to five weeks after the cessation 

attempt. Several multidimensional factors may be associated with relapse. These factors include the expectations 

that the effects from smoking will be rewarding, confidence in the ability to stop smoking, educational status, 

and degree of tobacco dependence. Situational indicators 

suggest that temptations to smoke and smoking lapse and 

relapse are associated with alcohol use and environmental 

signals such as the sight of others smoking and the availability of cigarettes. 

Evidence supports the relationship of tobacco withdrawal syndrome with vulnerability to relapse. Studies 

show three important findings for many smokers: (1) 

withdrawal symptoms are persistent and often severe for 

several months after an attempt to stop smoking, (2) the 

heterogeneity in withdrawal symptoms is great, and (3) 

features such as the severity, variability, and the course 

of withdrawal symptoms confer increased risk for relapse. 

Craving and negative affect are the withdrawal symptoms 

most predictive of relapse, including urges to smoke 

that are experienced immediately after awakening in the 

morning. Research suggests complex interrelationships 

within and across the different types of influences. Future 

research is needed to elucidate these interactions. 
Nicotine Addiction: Past and Present 183

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Conclusions

1. Nicotine is the key chemical compound that causes 

and sustains the powerful addicting effects of commercial tobacco products.

2. The powerful addicting effects of commercial 

tobacco products are mediated by diverse actions of 

nicotine at multiple types of nicotinic receptors in the 

brain.

3. Evidence is suggestive that there may be psychosocial, biologic, and genetic determinants associated 

with different trajectories observed among population subgroups as they move from experimentation to 

heavy smoking.

4. Inherited genetic variation in genes such as CYP2A6 

contributes to the differing patterns of smoking 

behavior and smoking cessation. 

5. Evidence is consistent that individual differences in 

smoking histories and severity of withdrawal symptoms are related to successful recovery from nicotine 

addiction.
Surgeon General’s Report

184 Chapter 4

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220 Chapter 4

Data table for Figure 4.1 Venous blood concentrations of nicotine over time for various nicotine delivery systems

Time

Cigarette 

(nicotine 

delivery, 

1–2 mg) Oral snuff

Nasal spray 

(nicotine 

delivery 1 mg)

Polacrilex 

(nicotine 

delivery 

4 mg) Nicoderm Nicotrol

-10 2.5 2.5    3.0      

0 3.0 2.0 1.0 2.5 0 1.5

10 15.5 12.0 6.5 6.0      

20 13.0 14.5 5.0 9.0      

30 12.9 14.5 4.5 10.0 3 2.0

40 8.5 14.4 3.0 9.8      

50 7.9 12.5 2.8 9.0      

60 7.4 12.7 2.4 8.5 8 4.2

70 6.9 12.5 2.2 9.0      

80 6.5 12.0 2.1 8.9      

90 6.1 11.8 2.0 8.5 10 5.0

100 6.0 11.4 1.9 7.5      

110 5.7 11.0 1.8 6.5      

120 5.1 10.8 1.7 6.0 12 6.2

Data table for Figure 4.2 Mean plasma nicotine concentrations after administration of each of four smokeless tobacco 

products or mint snuff

Time Copenhagen Skoal Wintergreen

Skoal Long Cut 

Cherry Skoal Bandits Mint “Snuff”

0 6.34 4.22 4.29 6.52 4.88

1 5.65 3.47 4.15 5.15 4.05

2 8.20 3.63 4.31 4.54 4.17

3 9.54 5.18 4.95 4.91 4.54

4 10.77 6.44 4.28 4.71 4.23

6 16.29 8.50 7.26 5.63 3.99

8 15.68 9.89 9.46 6.87 4.10

10 17.54 12.11 9.75 6.65 4.07

15 18.60 14.42 11.51 6.95 4.02

20 21.52 16.77 14.45 8.57 4.03

25 22.33 15.65 15.68 7.96 4.40

30 22.45 17.10 16.16 9.31 3.85

35 23.93 16.64 17.32 8.97 3.66

40 22.43 15.86 16.04 9.07 3.77

45 20.65 14.78 14.99 8.56 3.61

60 17.58 13.20 12.48 7.57 4.00

75 15.48 11.72 11.41 7.08 3.48

90 13.70 10.71 10.61 6.43 3.67
How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Nicotine Addiction: Past and Present 220a

Table 4.5 Genetic linkage studies of smoking behavior phenotypes

Study

(country) Population

Number 

of families

Number 

of 

markers

Primary 

phenotype

Markers of 

significant 

linkage

Chromosome 

number

Bergen et al. 1999

(United States)

Collaborative Study 

on the Genetics of 

Alcoholism

105 extended 296 Ever smoked 

vs. lifetime 

nonsmoking

D1S548 1

Bergen et al. 1999

(United States)

Collaborative Study 

on the Genetics of 

Alcoholism

105 extended 296 Ever smoked 

vs. lifetime 

nonsmoking

D2S379 2

Bergen et al. 1999

(United States)

Collaborative Study 

on the Genetics of 

Alcoholism

105 extended 296 Ever smoked 

vs. lifetime 

nonsmoking

D6S474 6

Bergen et al. 1999

(United States)

Collaborative Study 

on the Genetics of 

Alcoholism

105 extended 296 Ever smoked 

vs. lifetime 

nonsmoking

D9S64 9

Bergen et al. 1999

(United States)

Collaborative Study 

on the Genetics of 

Alcoholism

105 extended 296 Ever smoked 

vs. lifetime 

nonsmoking

D14S302 14

Bergen et al. 1999

(United States)

Collaborative Study 

on the Genetics of 

Alcoholism

105 extended 296 Ever smoked 

vs. lifetime 

nonsmoking

D17S968 17

Bergen et al. 1999

(United States)

Collaborative Study 

on the Genetics of 

Alcoholism

105 extended 296 Ever smoked 

vs. lifetime 

nonsmoking

D18S391 18

Bergen et al. 1999

(United States)

Collaborative Study 

on the Genetics of 

Alcoholism

105 extended 296 Ever smoked 

vs. lifetime 

nonsmoking

D21S120 21

Duggirala et al. 

1999

(United States)

Collaborative Study 

on the Genetics of 

Alcoholism

105 extended 296 Pack-yearsa of 

smoking

D4S244 4

Duggirala et al. 

1999

(United States)

Collaborative Study 

on the Genetics of 

Alcoholism

105 extended 296 Pack-yearsa of 

smoking

D5S1354 5

Duggirala et al. 

1999

(United States)

Collaborative Study 

on the Genetics of 

Alcoholism

105 extended 296 Pack-yearsa of 

smoking

GATA193 17

Straub et al. 1999

(New Zealand and 

United States)

Convenience sample 

(Christchurch, 

New Zealand, and 

Richmond, Virginia)

130 and 91 

nuclear, 

respectively

451 Nicotine 

dependence

D2S1326 2

Straub et al. 1999

(New Zealand and 

United States)

Convenience sample 

(Christchurch, 

New Zealand, and 

Richmond, Virginia)

130 and 91 

nuclear, 

respectively

451 Nicotine 

dependence

D10S2469 10
Surgeon General’s Report

220b Chapter 4

Table 4.5 Continued

Study

(country) Population

Number 

of families

Number 

of 

markers

Primary 

phenotype

Markers of 

significant 

linkage

Chromosome 

number

Goode et al. 2003

(New Zealand and 

United States)

Framingham Heart 

Study

313 extended 401 Cigarettes/day 

(maximum)

ATA4F03 2

Goode et al. 2003

(New Zealand and 

United States)

Framingham Heart 

Study

313 extended 401 Cigarettes/day 

(maximum)

GATA151F03 15

Goode et al. 2003

(New Zealand and 

United States)

Framingham Heart 

Study

313 extended 401 Cigarettes/day 

(maximum)

GATA25A04 17

Goode et al. 2003

(New Zealand and 

United States)

Framingham Heart 

Study

313 extended 401 Cigarettes/day 

(maximum)

GATA47F05 20

Goode et al. 2003

(New Zealand and 

United States)

Framingham Heart 

Study

313 extended 401 Cigarettes/day 

(maximum)

321xd1 20

Li et al. 2003

(United States)

Framingham Heart 

Study

313 extended 401 Cigarettes/day D9S257 9

Li et al. 2003

(United States)

Framingham Heart 

Study

313 extended 401 Cigarettes/day D9S910 9

Li et al. 2003

(United States)

Framingham Heart 

Study

313 extended 401 Cigarettes/day D11S1985 11

Li et al. 2003

(United States)

Framingham Heart 

Study

313 extended 401 Cigarettes/day D11S2371 11

Li et al. 2003

(United States)

Framingham Heart 

Study

313 extended 401 Cigarettes/day ATA78D02 17

Li et al. 2003

(United States)

Framingham Heart 

Study

313 extended 401 Cigarettes/day D17S2196 17

Saccone et al. 2003

(United States)

Framingham Heart 

Study

313 extended 401 Cigarettes/day 

(maximum)

1648xb8 5

Saccone et al. 2003

(United States)

Framingham Heart 

Study

313 extended 401 Cigarettes/day 

(maximum)

ATA59H06 9

Saccone et al. 2003

(United States)

Framingham Heart 

Study

313 extended 401 Cigarettes/day 

(maximum)

GATA6B07 13

Saccone et al. 2003

(United States)

Framingham Heart 

Study

313 extended 401 Cigarettes/day 

(maximum)

Mfd190 14

Saccone et al. 2003

(United States)

Framingham Heart 

Study

313 extended 401 Cigarettes/day 

(maximum)

217xf4 22
How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Nicotine Addiction: Past and Present 220c

Table 4.5 Continued

Study

(country) Population

Number 

of families

Number 

of 

markers

Primary 

phenotype

Markers of 

significant 

linkage

Chromosome 

number

Bierut et al. 2004

(United States)

Collaborative Study 

on the Genetics of 

Alcoholism

97 nuclear 366 Habitual vs. 

nonhabitual 

smoking

D5S815 5

Bierut et al. 2004

(United States)

Collaborative Study 

on the Genetics of 

Alcoholism

97 nuclear 366 Habitual vs. 

nonhabitual 

smoking

D9S1120 9

Bierut et al. 2004

(United States)

Collaborative Study 

on the Genetics of 

Alcoholism

97 nuclear 366 Habitual vs. 

nonhabitual 

smoking

D9A261 9

Bierut et al. 2004

(United States)

Collaborative Study 

on the Genetics of 

Alcoholism

97 nuclear 366 Habitual vs. 

nonhabitual 

smoking

D9S904 9

Bierut et al. 2004

(United States)

Collaborative Study 

on the Genetics of 

Alcoholism

97 nuclear 366 Habitual vs. 

nonhabitual 

smoking

D11S1354 11

Bierut et al. 2004

(United States)

Collaborative Study 

on the Genetics of 

Alcoholism

97 nuclear 366 Habitual vs. 

nonhabitual 

smoking

D21S210 21

Sullivan et al. 2004

(New Zealand and 

United States)

Convenience sample 

(Christchurch, New 

Zealand)

130 nuclear 458 Nicotine 

dependence

D2S1326 2

Sullivan et al. 2004

(New Zealand and 

United States)

Convenience sample 

(Christchurch, New 

Zealand)

130 nuclear 458 Nicotine 

dependence

D10S2469 10

Sullivan et al. 2004

(New Zealand and 

United States)

Convenience sample 

(Christchurch, New 

Zealand)

130 nuclear 458 Nicotine 

dependence

CYP17 10
Surgeon General’s Report

220d Chapter 4

Table 4.5 Continued

Study

(country) Population

Number 

of families

Number 

of 

markers

Primary 

phenotype

Markers of 

significant 

linkage

Chromosome 

number

Vink et al. 2004

(The Netherlands)

Netherlands Twin 

Register

192 nuclear 379 Ever smoked 

vs. lifetime 

nonsmoking

D6S2410 6

Vink et al. 2004

(The Netherlands)

Netherlands Twin 

Register

192 nuclear 379 Ever smoked 

vs. lifetime 

nonsmoking

D6S1053 6

Vink et al. 2004

(The Netherlands)

Netherlands Twin 

Register

192 nuclear 379 Ever smoked 

vs. lifetime 

nonsmoking

Unk283 14

Vink et al. 2004

(The Netherlands)

Netherlands Twin 

Register

192 nuclear 379 Ever smoked 

vs. lifetime 

nonsmoking

D14S617 14

Vink et al. 2004

(The Netherlands)

Netherlands Twin 

Register

192 nuclear 379 Cigarettes/day D3S3050 3

Vink et al. 2004

(The Netherlands)

Netherlands Twin 

Register

192 nuclear 379 Cigarettes/day D3S4545 3

Vink et al. 2004

(The Netherlands)

Netherlands Twin 

Register

192 nuclear 379 Both D10S1412 10

Vink et al. 2004

(The Netherlands)

Netherlands Twin 

Register

192 nuclear 379 Both D10S1430 10

Wang et al. 2005

(United States)

Framingham Heart 

Study

430 nuclear 401 Cigarettes/day ATA4E02 1

Wang et al. 2005

(United States)

Framingham Heart 

Study

430 nuclear 401 Cigarettes/day GATA6G12 3

Wang et al. 2005

(United States)

Framingham Heart 

Study

430 nuclear 401 Cigarettes/day GATA5B02 4

Wang et al. 2005

(United States)

Framingham Heart 

Study

430 nuclear 401 Cigarettes/day GATA24D12 7

Wang et al. 2005

(United States)

Framingham Heart 

Study

430 nuclear 401 Cigarettes/day GATA6B02 8

Wang et al. 2005

(United States)

Framingham Heart 

Study

430 nuclear 401 Cigarettes/day GATA12C06 9

Wang et al. 2005

(United States)

Framingham Heart 

Study

430 nuclear 401 Cigarettes/day GATA48E02 11

Wang et al. 2005

(United States)

Framingham Heart 

Study

430 nuclear 401 Cigarettes/day 290vc9 16

Wang et al. 2005

(United States)

Framingham Heart 

Study

430 nuclear 401 Cigarettes/day GATA185H04 17

Wang et al. 2005

(United States)

Framingham Heart 

Study

430 nuclear 401 Cigarettes/day ATA4E02 20
How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Nicotine Addiction: Past and Present 220e

Table 4.5 Continued

Study

(country) Population

Number 

of families

Number 

of 

markers

Primary 

phenotype

Markers of 

significant 

linkage

Chromosome 

number

Gelernter et al. 

2006

(United States)

Probands identified 

for panic disorder 

(Yale University, 

Connecticut)

12 extended 416 Habitual vs. 

nonhabitual 

smoking

D9S283 9

Gelernter et al. 

2006

(United States)

Probands identified 

for panic disorder 

(Yale University, 

Connecticut)

12 extended 416 Habitual vs. 

nonhabitual 

smoking

D9S1677 9

Gelernter et al. 

2006

(United States)

Probands identified 

for panic disorder 

(Yale University, 

Connecticut)

12 extended 416 Habitual vs. 

nonhabitual 

smoking

D11S4046 11

Note: Dominant ancestry for all studies was European. aPack-years = the number of years of smoking multiplied by the number of packs of cigarettes smoked per day.
220f Chapter 4

Study Population Used daily for ≥2 weeks Tried to cut down Unable to cut down/ unsuccessful attempts to control use (%) Felt need for more/ tolerance (%) Felt dependent (%) Felt sick when stopped/ withdrawal symptoms (%) Greater use than intended (%) Use despite problems (%) Us

relwit(%

Henningfield et al. 1990 NHSDA Used at least once (N = 5,105) 51.1 54.2 11.7 37.9 16.5 Henningfield et 

al. 1990

NHSDA ≥1 pack/day (N = 1,010) 91.2 84.3 23.9 79.2 33.3

Breslau et al. 1994

Random sample Health maintenance organizationAged 21–30 years (N = 1,200)All smokersa (N = 394) 60.4 27.4 30.5 68.8 44.4 26

Breslau et al. 1994

Random sample Health maintenance organizationAged 21–30 years (N = 1,200)Dependentb (N = 202) 93.6 45.5 58.9 88.6 72.3 49

Breslau et al. 1994

Random sample Health maintenance organizationAged 21–30 years (N = 1,200)Nondependentc (N = 194 ) 25.2 8.3 0.3 47.9 15.1 3

Centers for Disease Control and Prevention 1995b

NHSDA 1991–1992Aged ≥12 yearsAll responders (N = 14,688)Daily users in past year (N = 10,343) 78.4 64.4 76.6 14.0 68.9 34.9

Centers for Disease Control and Prevention 1995b

NHSDA 1991–1992Aged ≥12 yearsDaily users in past year (N = 10,343) NA 74.9 79.6 17.5 85.0 37.4

Table 4.12 Prevalence of selected symptoms of nicotine dependence reported in selected studies
Nicotine Addiction: Past and Present 220g

Study Population

Used daily for ≥2 weeks

Tried to cut down

Unable to cut down/unsuccessful attempts to control use (%)

Felt need for more/tolerance (%)

Felt dependent (%)

Felt sick when stopped/withdrawalsymptoms (%)

Greater use than intended (%)

Use despite problems (%)

Use reliwit(%

Kawakami et al. 1999d

Current male smokersVolunteers (N = 58) 64.2 55.2 67.2 84.5 65.5 60.

Kawakami et al. 1999d

Current male smokersSmoking cessation patients (N = 151) 65.5 54.7 73.0 73.0 56.1 63.

Kawakami et al. 1999d

Current male smokersHealth Risk Assessment survey sample (N = 194) 59.3 36.1 58.2 67.5 42.8 49.

Storr et al. 2004 NHSDA

1995–1998Recently initiated 21.7 16.0 17.9 4.7–5.3 

Table 4.12 Continued

Note: NA = data not available; NHSDA = National Survey on Drug Use & Health.aSmoked daily for ≥1 month in their lifetime.bDiagnostic and Statistical Manual of Mental Disorders, 3rd ed. (rev) (DSM-III-R) criteria for nicotine dependence.cHas never met DSM-III-R criteria for nicotine dependence.dConducted in Japan.
221

Chapter 5

Cancer

Introduction 225

Carcinogen Exposure, Metabolism, and DNA Adducts 227

Carcinogens in Cigarette Smoke 227

Biomarkers of Carcinogens in Smokers 230

Urinary Biomarkers 230

Breath and Blood Biomarkers 234

Summary 234

Metabolic Activation and Detoxification of Carcinogens 235

Enzymology of Carcinogen Metabolism 237

Introduction 237

Cytochrome P-450 Enzymes 237

Epoxide Hydrolases 238

Glutathione-S-Transferases 239

Uridine-5’-Diphosphate-Glucuronosyltransferases 240

N-Acetyltransferases 241

DNA Adducts and Biomarkers 242

Introduction 242

Characterized Adducts in the Human Lung 242

Uncharacterized Adducts in Human Lung Tissue 244

Adducts in Other Tissues 244

Protein Adducts as Surrogates for DNA Adducts 245

Summary 245

Molecular Epidemiology of Polymorphisms in Carcinogen-Metabolizing Genes 245

Introduction 245

CYP1A1 Gene 246

CYP2E1 Gene 247

CYP2A13 Gene 247

GSTM1 Gene 248

CYP1A1 and GSTM1 in Combination 248

GSTP1 Gene 249

GSTT1 Gene 249

NAT2 Gene 249

Microsomal Epoxide Hydrolase 250

Genes in the Pathway for Metabolism of Reactive Oxygen Species 251

Summary 251

DNA Repair and Conversion of Adducts to Mutations 252

Repair of DNA Adducts 252

Introduction 252

O6-Alkylguanine–DNA Alkyltransferase 252

Base Excision Repair 253

Nucleotide Excision Repair 254
222

Mismatch Repair 258

Double-Strand Break Repair 259

Molecular Epidemiology of DNA Repair 259

Functional Assays of DNA Damage and Repair to Tobacco Carcinogens 261

8-Oxoguanine DNA Glycosylase Activity Assay 263

Mutagen Sensitivity Assays 263

Comet Assay 263

Polymorphisms in O6-Alkylguanine–DNA Alkyltransferase 264

Polymorphisms in the Pathway for Repair of Base Excision 264

Polymorphisms in the Pathway for Nucleotide Excision Repair 266

Genotype-Phenotype Correlations 267

Polymorphisms in the Pathway for Double-Strand Break Repair 268

Summary 268

Conversion of DNA Adducts to Mutations 268

Molecular Analysis of Conversion to Mutations 269

Translesion Synthesis in Mammalian Cells 269

Factors in Outcome of Translesion Synthesis 271

Conversion of Cigarette-Smoke-Induced DNA Adducts to Mutations 272

Assessment of Genotoxicity of DNA Adducts 273

Gene Mutations in Tobacco-Induced Cancer 274

Chromosome Instability and Loss 274

Lung Cancer 274

Identification of Tumor-Suppressor Genes 274

Tumor-Suppressor Genes Inactivated in Lung Cancer 275

Activation of Oncogenes in Lung Cancer 275

Oncogene Activation, Tumor-Suppressor Gene Inactivation, and Lung Cancer Survival 277

Relationship of TP53 Mutations to Smoking and Carcinogens 278

TP53 Mutations in Smoking-Associated Lung Cancers 278

G→T Transversions in Lung Cancer 279

TP53 Gene Mutations in Other Smoking-Associated Cancers 283

Limitations to the Study of TP53 Mutations and Smoking-Induced Cancer 283

Loss of Mechanisms for Growth Control 284

Signal Transduction 284

Introduction 284

Apoptosis 284

Key Apoptotic Regulators 284

Regulation of Tumor Suppressors and Proapoptotic Proteins 284

Regulation of Antiapoptotic Proteins and Effects 286

Summary 288

Cigarette Smoke and Activation of Cell-Surface Receptors in Cancer 288

Airway Epithelial Cells 288

Activation of Cytoplasmic Kinase by Tobacco Smoke 290

Downstream Targets of Signaling Cascades Mediated by Tobacco Smoke 292

Gene Promoter Hypermethylation in Cancer Induced by Tobacco Smoke 292

Alternative to Mutation 292

Inactivation of the P16 Gene in Lung Cancer 292

Critical Pathways Inactivated in Non-Small-Cell and Small-Cell Lung Cancer 292

Gene Silencing in Lung Cancer 293

Gene Promoter Hypermethylation, Prognosis, and Clinical Risk Factors 293

Other Tobacco-Related Cancers 294
223

Molecular Epidemiology of Cell-Cycle Control and Tobacco-Induced Cancer 294

Introduction 294

CCND1 Gene 294

P21 Protein 295

TP53 Gene 295

P73 Gene 296

Other Aspects 296

Carcinogenic Effects of Whole Mixture and Fractions of Tobacco Smoke 296

Synergistic Interactions in Tobacco Carcinogenesis 297

Alcohol 297

Asbestos 298

Carcinogens as Causes of Specific Cancers 298

Tobacco Carcinogens, Immune System, and Cancer 300

Epidemiology of Family History and Lung Cancer 300

Evidence Summary 302

Conclusions 304

References 305

Cancer 225

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Introduction

The 2004 Surgeon General’s report, The Health 

Consequences of Smoking: A Report of the Surgeon General (U.S. Department of Health and Human Services 

[USDHHS] 2004), concluded that the evidence is sufficient to infer a causal relationship between smoking and 

cancers of the lung, larynx, oral cavity, pharynx, esophagus, pancreas, bladder, kidney, cervix, and stomach, and 

acute myeloid leukemia. In addition, the report found that 

evidence suggests a causal relationship between smoking 

and colorectal and liver cancers. This chapter examines 

the mechanisms by which cigarette smoking induces 

cancer. Literature citations for this section’s discussion 

appear in subsequent sections of this chapter, as appropriate. A schematic overview of the pertinent mechanisms 

discussed in this chapter is presented in Figure 5.1. The 

figure depicts the major established pathways of cancer 

causation by cigarette smoking: (1) the exposure to carcinogens (cancer-causing substances), (2) the formation 

of covalent bonds between the carcinogens and DNA (DNA 

adduct formation), and (3) the resulting accumulation 

of permanent somatic mutations in critical genes (genes 

appear in italics). Somatic mutations lead to clonal outgrowth and, through accumulation of additional mutations, to development of cancer. 

Each puff of each cigarette contains a mixture of 

thousands of compounds, including more than 60 wellestablished carcinogens. The carcinogens in cigarette 

smoke belong to multiple chemical classes, including 

polycyclic aromatic hydrocarbons (PAHs), N-nitrosamines, 

aromatic amines, aldehydes, volatile organic hydrocarbons, and metals. In addition to these well-established carcinogens, others have been less thoroughly investigated. 

These include alkylated PAHs, oxidants, free radicals, and 

ethylating agents. Considerable evidence indicates that 

in human cancers caused by cigarette smoking, PAHs, 

N-nitrosamines, aromatic amines, and certain volatile 

organic agents play a major role. Extensive data in the 

literature demonstrate the uptake of these carcinogens 

by smokers. The data confirm the expected presence of 

metabolites of these substances in the urine of smokers at 

higher levels than those in nonsmokers.

Most carcinogens in cigarette smoke require a 

metabolic activation process, generally catalyzed by cytochrome P-450 enzymes (P-450s), to convert the carcinogens to forms that can covalently bind to DNA and form 

DNA adducts. P-450s 1A1 and 1B1, which are inducible 

by cigarette smoke through interactions with the aryl 

hydrocarbon receptor, are particularly important in the 

metabolic activation of PAHs. The inducibility of these 

P-450s may be a critical aspect of cancer susceptibility in 

smokers. P-450s 1A2, 2A6, 2A13, and 2E1 are also 

important in the activation of cigarette smoke carcinogens. Competing with the activation process is metabolic 

detoxification, which excretes carcinogen metabolites in 

generally harmless forms and is catalyzed by a variety of 

enzymes, including glutathione-S-transferases (GSTs), 

uridine-5’-disphosphate-glucuronosyltransferases (UGTs), 

epoxide hydrolases, and sulfatases. The balance between 

metabolic activation and detoxification of carcinogens 

varies among persons and likely affects cancer susceptibility. Persons with a higher activation and lower detoxification capacity are at the highest risk for smoking-related 

cancers. This finding is supported by considerable evidence from molecular epidemiologic studies of the polymorphisms (variants) in these enzymes.

The metabolic activation of carcinogens results 

in the formation of DNA adducts, which are absolutely 

central to the carcinogenic process. However, some carcinogens can directly form DNA adducts without metabolic activation. Since the mid-1980s, extensive studies 

have examined the presence of DNA adducts in human 

tissues. Studies that used nonspecific methods, such as 

32P-postlabeling and immunoassays, to measure adducts 

concluded that adduct levels in the lung and in other tissues are higher in smokers than in nonsmokers. Some 

epidemiologic data link higher adduct levels with a higher 

probability of developing cancer.

There are ample cellular repair systems that can 

remove DNA adducts and maintain a normal DNA structure. These systems include direct repair of DNA bases by 

alkyltransferases, the excision of DNA damage by base and 

nucleotide excision repair, mismatch repair, and doublestrand break repair. If repair enzymes are overwhelmed 

by DNA damage or for other reasons cannot function 

efficiently, DNA adducts may persist and increase the 

likelihood of developing somatic mutations. Inherited 

polymorphic variants in some DNA repair enzymes are 

also associated with decreased DNA repair activity and a 

potentially higher probability of developing cancer.

Persistent DNA adducts can cause miscoding (e.g., 

insertion of the wrong base) during replication of DNA 

when DNA polymerase enzymes process the adducts 

incorrectly. Considerable specificity exists in the relationship between specific DNA adducts caused by carcinogens 

in cigarette smoke and the types of observed somatic 

mutations; for example, an O6-methylguanine adduct 

causes G→A transitions. These types of mutations are 

frequently observed in the KRAS oncogene in lung 
Surgeon General’s Report

226 Chapter 5

cancer and in the TP53 gene in a variety of cancers 

induced by cigarette smoke. The KRAS and TP53 mutations observed in lung cancer in smokers appear to reflect 

DNA damage caused by metabolically activated PAHs. However, a number of other carcinogens or toxicants, such as 

N-nitrosamines and aldehydes, as well as oxidative damage, are also likely to be involved. Animal studies have 

firmly established the cancer-causing role of mutations in 

these genes.

Gene mutations can cause the loss of normal functions in control of cellular growth, ultimately resulting 

in cellular proliferation and cancer. Studies have strongly 

linked chromosome damage in cells throughout the 

aerodigestive tract to exposure to cigarette smoke. The 

protective process of programmed cell death (apoptosis) 

can counterbalance these mutational events by removing 

cells with DNA damage. The balance between mechanisms 

leading to apoptosis and those suppressing apoptosis has 

a major impact on tumor growth. In addition, researchers have observed numerous cytogenetic changes in 

lung cancer. 

The central track of Figure 5.1 that proceeds through 

genetic damage is clearly established as a major pathway 

by which carcinogens in cigarette smoke can cause cancer. 

However, the top and bottom tracks of Figure 5.1 indicate 

that other pathways also contribute to carcinogenesis. 

Nicotine and tobacco-specific nitrosamines bind to nicotinic receptors and other cellular receptors. This binding 

then leads to the activation of protein kinase B (AKT, also 

known as PKB), protein kinase A (PKA), and other key 

biologic pathways for cytogenetic changes. Cigarette 

smoke activates EGFR and COX-2, both known to be 

important in cell proliferation and transformation. Furthermore, the occurrence of cocarcinogens and tumor 

promoters in cigarette smoke is well established. Although 

these compounds are not carcinogenic, they clearly 

enhance the carcinogenicity of cigarette smoke carcinogens through mechanisms that usually lead to stimulation of cell proliferation. The reversibility of cancer risk 

after smoking cessation supports the role of tumor promoters and other epigenetic factors in tobacco carcinogenesis. However, the specifics of these effects have not 

been fully elucidated. An important epigenetic pathway is 

the enzymatic hypermethylation of promoter regions of 

genes, which can result in gene silencing. If this occurs 

in tumor-suppressor genes, the result can be unregulated 

cellular proliferation.

Figure 5.1 Link between cigarette smoking and cancer through carcinogens in tobacco smoke
Cancer 227

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Carcinogen Exposure, Metabolism, and DNA Adducts

Carcinogens in Cigarette Smoke

Carcinogens in cigarette smoke that were evaluated by the International Agency for Research on Cancer 

(IARC 2004) are listed in Table 5.1. All are carcinogenic 

in laboratory animals, and 15 are rated as carcinogenic in 

humans (group 1 carcinogens). Similar evaluations have 

been published by the USDHHS (2005). The total exposure 

of smokers to these compounds is approximately 1.4 to 2.2 

milligrams (mg) per cigarette (Table 5.1). This estimate 

is based on machine measurements and may underestimate actual exposure. Some of the strongest of these carcinogens are PAHs, N-nitrosamines, and aromatic amines, 

which occur in the lowest amounts, and some of the 

weaker carcinogens, such as acetaldehyde and isoprene, 

occur in the highest amounts. Thus, a simple addition of 

the amounts of carcinogenic agents could be misleading. 

For other carcinogens in cigarette smoke that IARC has 

not evaluated (e.g., broad spectra of PAHs and aromatic 

amines), data on frequency of occurrence, levels, and carcinogenic activities are incomplete (IARC 1986). 

PAHs are incomplete combustion products first 

identified as carcinogenic constituents of coal tar (Phillips 1983). These products occur as mixtures in tar, soot, 

broiled foods, automobile engine exhaust, and other 

materials generated by incomplete combustion (IARC 

1983). Generally, PAHs are carcinogens that act locally. 

Some PAHs, such as benzo[a]pyrene (B[a]P), have powerful carcinogenic activity. Studies have typically evaluated 

PAH carcinogenicity by application to mouse skin, but 

PAHs also induce tumors of the lung, trachea, and mammary gland, depending on the route of administration and 

the animal model used (Dipple et al. 1984). 

Heterocyclic compounds include analogs of PAHs 

containing nitrogen, as well as simpler compounds such 

as furan, which is a liver carcinogen. N-nitrosamines are 

a large class of carcinogens with demonstrated activity in 

at least 30 animal species (Preussmann and Stewart 1984). 

They are potent and systemic carcinogens that affect different tissues depending on their structure. Two of the 

most important N-nitrosamines in cigarette smoke are the 

tobacco-specific 4-(methylnitrosamino)-1-(3-pyridyl)-

1-butanone (NNK) and N’-nitrosonornicotine (NNN) 

(Hecht and Hoffmann 1988). NNK caused lung tumors 

in all species tested, and activity in rats was particularly 

high. Studies using animal models have demonstrated 

that NNK also induces tumors of the pancreas, nasal cavity, and liver. In addition, NNN produces esophageal and 

nasal tumors in rats and respiratory tract tumors in mice 

and hamsters (Hecht 1998). 

Aromatic amines in cigarette smoke are combustion 

products that include the well-known human bladder carcinogens 2-naphthylamine and 4-aminobiphenyl (4-ABP), 

which were first characterized as human carcinogens 

attributable to industrial exposures in the dye industry 

(Luch 2005). Heterocyclic aromatic amines are also combustion products and are best known for their occurrence 

in broiled foods (Sugimura 1995), but they also occur in 

cigarette smoke.

Aldehydes such as formaldehyde and acetaldehyde 

occur widely in the human environment and are endogenous metabolites found in human blood (IARC 1995c, 

1999; Gao et al. 2002). The phenolic compounds catechol and caffeic acid are common dietary constituents. 

High doses of catechol cause glandular stomach tumors 

when administered in the diet. Catechol can also act as a 

cocarcinogen, enhancing the activity of carcinogens such 

as B[a]P (IARC 1999). Dietary caffeic acid caused renal 

cell tumors in female mice (IARC 1993). The volatile 

hydrocarbons include 1,3-butadiene, a powerful multiorgan carcinogen in mice that was shown to have weaker 

activity in rats, and benzene, a known human leukemogen 

(IARC 1982, 1999). 1,3-butadiene and benzene are arguably the two most prevalent potent carcinogens in cigarette smoke, on the basis of toxicologic criteria (Fowles 

and Dybing 2003).

Other carcinogenic organic compounds in cigarette 

smoke include the human carcinogens vinyl chloride in 

low amounts and ethylene oxide in substantial quantities 

(IARC 1979). Ethylene oxide is associated with malignancies of the lymphatic and hematopoietic systems in both 

humans and laboratory animals (IARC 1994). Diverse metals such as the human carcinogen cadmium are also present in cigarette smoke, as is the radioisotope polonium 

210, which is carcinogenic to humans. 

Cigarette smoke also contains oxidants such as 

nitric oxide (about 600 micrograms [μg] per cigarette) 

and related species (Hecht 1999). Free radicals have been 

detected by electron spin resonance and spin trapping 

(Hecht 1999). Researchers postulate that the major species of free radicals are a quinone-hydroquinone complex. 

Other compounds may also be involved in the oxidative 

damage produced by cigarette smoke. In addition, several 

studies demonstrate the presence in cigarette smoke of an 

uncharacterized ethylating agent, which ethylates both 

DNA and hemoglobin (Hb) (Carmella et al. 2002a; Singh 

et al. 2005). 
Surgeon General’s Report

228 Chapter 5

Table 5.1 IARC evaluations of carcinogens in mainstream cigarette smoke

     

IARC evaluations of evidence of 

carcinogenicity in humans   

Carcinogena

Quantity 

(per cigarette) In animals In humans IARC groupb

IARC Monographc

(volume, year)

Polycyclic aromatic hydrocarbons               

Benz[a]anthracene 20–70 ng Sufficient    2A 32, 1983; S7, 1987

Benzo[b]fluoranthene 4–22 ng Sufficient    2B 32, 1983; S7, 1987

Benzo[j]fluoranthene 6–21 ng Sufficient    2B 32, 1983; S7, 1987

Benzo[k]fluoranthene 6–12 ng Sufficient    2B 32, 1983; S7, 1987

Benzo[a]pyrene 8.5–17.6 ng Sufficient Limited 1 32, 1983; S7, 1987; 

92, in press

Dibenz[a,h]anthracene 4 ng Sufficient    2A 32, 1983; S7, 1987

Dibenzo[a,i]pyrene 1.7–3.2 ng Sufficient    2B 32, 1983; S7, 1987

Dibenzo[a,e]pyrene Present Sufficient    2B 32, 1983; S7, 1987

Indeno[1,2,3-cd]pyrene 4–20 ng Sufficient    2B 32, 1983; S7, 1987

5-methylchrysene ND–0.6 ng Sufficient    2B 32, 1983; S7, 1987

Heterocyclic compounds               

Furan 20–40 μg Sufficient    2B 63, 1995a

Dibenz[a,h]acridine ND–0.1 ng Sufficient    2B 32, 1983; S7, 1987

Dibenz[a,j]acridine ND–10 ng Sufficient    2B 32, 1983; S7, 1987

Dibenzo[c,g]carbazole ND–0.7 ng Sufficient    2B 32, 1983; S7, 1987

Benzo[b]furan Present Sufficient    2B 63, 1995a

N-nitrosamines               

N-nitrosodimethylamine 0.1–180 ng Sufficient    2A 17, 1978; S7, 1987

N-nitrosoethylmethylamine ND–13 ng Sufficient    2B 17, 1978; S7, 1987

N-nitrosodiethylamine ND–25 ng Sufficient    2A 17, 1978; S7, 1987

N-nitrosopyrrolidine 1.5–110 ng Sufficient    2B 17, 1978; S7, 1987

N-nitrosopiperidine ND–9 ng Sufficient    2B 17, 1978; S7, 1987

N-nitrosodiethanolamine ND–36 ng Sufficient    2B 17, 1978; 77, 2000

N’-nitrosonornicotine 154–196 ng Sufficient Limited 1 37, 1985; S7, 1987; 

89, in press

4-(methylnitrosamino)-1-(3-pyridyl) 

1-butanone

110–133 ng Sufficient Limited 1 37, 1985; S7, 

1987; 89, in press

Aromatic amines               

2-toluidine 30–200 ng Sufficient Limited 2A S7, 1987; 77, 2000

2,6-dimethylaniline 4–50 ng Sufficient    2B 57, 1993

2-naphthylamine 1–22 ng Sufficient Sufficient 1 4, 1974; S7, 1987

4-aminobiphenyl 2–5 ng Sufficient Sufficient 1 1, 1972; S7, 1987

Heterocyclic aromatic amines                 

2-amino-9H-pyrido[2,3-b]indole 25–260 ng Sufficient    2B 40, 1986; S7, 1987

2-amino-3-methyl-9H-pyrido[2,3-b]indole 2–37 ng Sufficient    2B 40, 1986; S7, 1987

2-amino-3-methylimidazo[4,5-f]quinoline 0.3 ng Sufficient    2A S7, 1987; 56, 1993

3-amino-1,4-dimethyl-5H-pyrido 

[4,3-b]indole

0.3–0.5 ng Sufficient    2B 31, 1983; S7, 1987

3-amino-1-methyl-5H-pyrido[4,3-b]indole 0.8–1.1 ng Sufficient    2B 31, 1983; S7, 1987

2-amino-6-methylpyrido[1,2-a:3’,

2’-d]imidazole

0.37–0.89 ng Sufficient    2B 40, 1986; S7, 1987

2-aminodipyrido[1,2-a:3’,2’-d]imidazole 0.25–0.88 ng Sufficient    2B 40, 1986; S7, 1987

2-amino-1-methyl-6-phenylimidazo

[4,5-b]pyridine

11–23 ng Sufficient    2B 56, 1993
Cancer 229

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Table 5.1 Continued

     

IARC evaluations of evidence of 

carcinogenicity in humans   

Carcinogena

Quantity 

(per cigarette) In animals In humans IARC groupb

IARC Monographc

(volume, year)

Aldehydes               

Formaldehyde 10.3–25 μg Sufficient Sufficient 1 S7, 1987; 62, 1995b

Acetaldehyde 770–864 μg Sufficient 2B S7, 1987; 71, 1999

Phenolic compounds               

Catechol 59–81 μg Sufficient    2B S7, 1987; 71, 1999

Caffeic acid <3 μg Sufficient    2B 56, 1993

Volatile hydrocarbons               

1,3-butadiene 20–40 μg Sufficient Limited 2A S7, 1987; 71, 1999

Isoprene 450–1,000 μg Sufficient    2B 60, 1994; 71, 1999

Benzene 12–50 μg Sufficient Sufficient 1 29, 1982; S7, 1987

Nitrohydrocarbons               

Nitromethane 0.5–0.6 μg Sufficient    2B 77, 2000

2-nitropropane 0.7–1.2 ng Sufficient    2B S7, 1987; 71, 1999

Nitrobenzene 25 μg Sufficient    2B 65, 1996

Miscellaneous organic compounds                 

Acetamide 38–56 μg Sufficient    2B S7, 1987; 71, 1999

Acrylamide Present Sufficient    2A S7, 1987; 60, 1994

Acrylonitrile 3–15 μg Sufficient    2B S7, 1987; 71, 1999

Vinyl chloride 11–15 ng Sufficient Sufficient 1 19, 1979; S7, 1987

1,1-dimethylhydrazine Present Sufficient    2B 4, 1974; 71, 1999

Ethylene oxide 7 μg Sufficient Limited 1 60, 1994; S7, 1987

Propylene oxide 0–100 ng Sufficient    2B 60, 1994; S7, 1987

Urethane 20–38 ng Sufficient    2B 7, 1974; S7, 1987

Metals and inorganic compounds               

Arsenic 40–120 ng Sufficient Sufficient 1 84, 2004

Beryllium 0.5 ng Sufficient Sufficient 1 S7, 1987; 58, 1993

Nickel ND–600 ng Sufficient Sufficient 1 S7, 1987; 49, 1990

Chromium (hexavalent) 4–70 ng Sufficient Sufficient 1 S7, 1987; 49, 1990

Cadmium 41–62 ng Sufficient Sufficient 1 S7, 1987; 58, 1993

Cobalt 0.13–0.20 ng Sufficient    2B 52, 1991

Lead (inorganic) 34–85 ng Sufficient Limited 2A 23, 1980; S7, 1987;

87, in press

Hydrazine 24–43 ng Sufficient    2B S7, 1987; 71, 1999

Radioisotope polonium-210 0.03–1.0 

picocurie

Sufficient    1 78, 2001

Source: Adapted from Hoffmann et al. 2001 and International Agency for Research on Cancer 2004 with permission from American 

Chemical Society, © 2001 and International Agency for Research on Cancer, © 2004.

Note: IARC = International Agency for Research on Cancer; ND = not detected; ng = nanograms; S7 = Supplement 7; 

μg = micrograms. aVirtually all these compounds are known carcinogens in experimental animals, and IARC found sufficient evidence for 

carcinogenicity in animals for all the compounds.

bUsing data on cancer in humans and, in some cases, other data, IARC established classifications for compounds as group 1 

(carcinogenic to humans), group 2A (probably carcinogenic to humans), and group 2B (possibly carcinogenic to humans).

cIf more than two IARC evaluations were performed, only the two most recent monographs are listed.
Surgeon General’s Report

230 Chapter 5

In summary, cigarette smoke contains diverse carcinogens. PAH, N-nitrosamines, aromatic amines, 1,3-

butadiene, benzene, aldehydes, and ethylene oxide are 

probably the most important carcinogens because of their 

carcinogenic potency and levels in cigarette smoke.

Biomarkers of Carcinogens 

in Smokers

Measurements of carcinogens or their metabolites 

in urine, blood, and breath can provide convenient and 

reliable quantitative information on human exposure to 

carcinogens. The information provided by these measurements, which are biomarkers of exposure, is critical to 

objective evaluation of carcinogen doses in smokers.

Urinary Biomarkers

Urinary biomarkers are the most widely applied 

biomarkers of carcinogen exposure in smokers (Hecht 

2002b). Urine is relatively simple to obtain in large quantities, and obtaining study participants’ consent and specimens for testing is almost never a difficulty. Carcinogens 

in cigarette smoke and/or their metabolites are frequently 

present in substantial quantities in urine. Therefore, reliable quantitation is generally feasible. This section provides an overview of some of the urinary biomarkers most 

commonly used to estimate carcinogen doses in smokers. 

The chemical structures of all compounds discussed in 

this section are illustrated in Figure 5.2. 

Polycyclic Aromatic Hydrocarbons

Phenanthrene metabolites. Phenanthrene is the 

simplest PAH with a bay region (the region of a molecule 

between positions 4 and 5), a feature closely associated 

with the carcinogenic activity of PAHs (Figure 5.2). Phenanthrene, however, is inactive as a carcinogen (LaVoie 

and Rice 1988). Concentrations of phenanthrene in mainstream smoke range from 85 to 620 nanograms (ng) 

per cigarette (IARC 1986). Studies have quantified the 

phenanthrene metabolites phenanthrols, phenanthrene 

dihydrodiols, and r-1,t-2,3,c-4-tetrahydroxy-1,2,3,4-tetrahydrophenanthrene (trans, anti-PheT) in human urine 

(Hecht 2002b). Levels of phenanthrols in human urine 

differed between smokers and nonsmokers in some studies but not in others (reviewed in Carmella et al. 2004a). 

There are sources of phenanthrene exposure other than 

cigarette smoke, and all people have phenanthrene 

metabolites in their urine. This finding is well documented 

in environmental and occupational settings with high 

exposures to PAH (Grimmer et al. 1993, 1997; Angerer et 

al. 1997). One metabolite of phenanthrene, trans, antiPheT, results from the diol epoxide metabolic activation 

pathway common to many carcinogenic PAHs. This metabolite is a promising new biomarker for PAH uptake and 

metabolic activation and can be readily quantified by gas 

chromatography (GC)-negative ion chemical ionization–

mass spectrometry (MS) (Hecht et al. 2003). Levels of 

trans, anti-PheT are higher in smokers than in nonsmokers (Hecht et al. 2003).

1-hydroxypyrene. Pyrene is a noncarcinogenic 

component in all PAH mixtures; levels in mainstream 

cigarette smoke were 50 to 270 ng per cigarette (IARC 

1986). The major metabolite of pyrene is 1-hydroxypyrene 

(1-HOP) glucuronide, which can be measured in urine 

(Jongeneelen et al. 1985). To quantify 1-HOP in urine, 

enzymatic hydrolysis is used to release 1-HOP, which is 

then enriched by reverse-phase chromatography and quantified by high-performance liquid chromatography (HPLC) 

with fluorescence detection. Studies have described variations of this method (Carmella et al. 2004b). Hundreds of 

studies of occupational and environmental PAH exposure 

have measured 1-HOP as a surrogate marker for total PAH 

exposure. In reviews of the data on the effects of smoking (Jongeneelen 1994, 2001; Van Rooij et al. 1994; Levin 

1995; Heudorf and Angerer 2001; Hecht 2002b), most of 

the studies noted that 1-HOP levels in the urine of smokers were about twice as high as those in the urine of nonsmokers, although some studies have reported greater 

differences. Levels of 1-HOP may be influenced by genetic 

polymorphisms in carcinogen-metabolizing enzymes 

(Alexandrie et al. 2000; Nerurkar et al. 2000; Nan et al. 

2001; van Delft et al. 2001).

Other metabolites of polycyclic aromatic hydrocarbons. Studies examining urine biomarkers have 

measured phenolic metabolites of naphthalene and a 

variety of PAHs, which show promise as urinary biomarkers of PAH uptake from cigarette smoke (Hecht 2002b; 

Smith et al. 2002a,b; Serdar et al. 2003). Studies have 

quantified B[a]P metabolites in urine, but the levels are 

generally low, limiting their routine application in large 

studies (Hecht 2002b).

Aromatic Amines and Heterocyclic 

Aromatic Amines

Researchers have quantified aromatic amines, but 

not their metabolites, in human urine. In one study, levels 

of 2-toluidine excreted by smokers were 6.3 ± 3.7 (standard deviation [SD]) μg/24 hours and levels excreted by 

nonsmokers were 4.1 ± 3.2 (SD) μg/24 hours. The difference was not significant (El-Bayoumy et al. 1986). Another 

investigation reported urine levels of 2-toluidine that were 

higher in smokers than in nonsmokers (Riffelmann et al. 
Cancer 231

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Note: 1-HOP = 1-hydroxypyrene; DHBMA = dihydroxybutylmercapturic acid; iso-NNAC = 4-(methylnitrosamino)-4-(3-pyridyl)butyric 

acid; MHBMA = monohydroxybutenylmercapturic acid; NAB = N’-nitrosoanabasine; NATB = N’-nitrosoanatabine; 

NNAL = 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol; NNAL-N-Gluc = 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol-N-glucuronide; 

NNAL-O-Gluc = 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol-O-glucuronide; NNN = N’-nitrosonornicotine; NNN-N-Gluc = N’-nitrosonornicotine-N-glucuronide; NPRO = N-nitrosoproline; NSAR = N-nitrososarcosine; NTCA = N-nitrosothiazolidine 4-carboxylic acid; 

S-PMA = S-phenylmercapturic acid; trans, anti-PheT = r-1,t-2,3,c-4-tetrahydroxy-1,2,3,4-tetrahydrophenanthrene; tt-MA = trans,transmuconic acid.

Figure 5.2 Chemical structures of biomarkers of carcinogen exposure
Surgeon General’s Report

232 Chapter 5

1995). There appear to be significant sources of human 

uptake of 2-toluidine in addition to cigarette smoke. 

Although these sources are not fully characterized, diet 

is one likely source. Amounts of 4-ABP excreted by smokers (78.6 ± 85.2 [SD] ng/24 hours) were similar to those 

excreted by nonsmokers (68.1 ± 91.5 ng/24 hours), and 

amounts of 2-naphthylamine excreted by smokers (84.5 

± 102.7 ng/24 hours) were similar to those excreted by 

nonsmokers (120.8 ± 279.2 ng/24 hours) (Grimmer et al. 

2000). In another study, Hb adducts appeared to be better 

biomarkers of exposure to aromatic amines from tobacco 

smoke than were urinary levels of metabolites (Skipper 

and Tannenbaum 1990). 

Researchers have measured urinary biomarkers of 

heterocyclic aromatic amines mainly in studies of dietary 

exposure. Little information is available on the contributions of cigarette smoke to urinary levels of heterocyclic 

aromatic amines (Hecht 2002b).

N-Nitrosamines

4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol and its glucuronides. In rodents and humans, 

4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) 

and its glucuronides are quantitatively significant 

metabolites of NNK (Hecht 1998). Both NNAL and NNK 

are pulmonary carcinogens with particularly strong activity in rats; NNAL also induces pancreatic tumors (Hecht 

1998). Glucuronidation of NNAL at the pyridine nitrogen 

gives NNAL-N-glucuronide, and conjugation at the carbinol oxygen yields NNAL-O-glucuronide. Both NNAL-Nglucuronide and NNAL-O-glucuronide exist as a mixture 

of two diastereomers, and each diastereomer is a mixture 

of E- and Z-rotamers (Upadhyaya et al. 2001). The NNALN-glucuronide and NNAL-O-glucuronide isomers are 

collectively referred to as NNAL glucuronides. (R)-NNALO-glucuronide does not induce tumors in mice (Upadhyaya et al. 1999). The (S) isomer has not been tested, 

but glucuronidation generally deactivates a carcinogenic 

metabolite in any event.

NNAL and NNAL glucuronides can be readily determined in urine by using GC with nitrosamine-selective 

detection (Carmella et al. 1993, 1995; Hecht et al. 1999) 

and by MS methods (Carmella et al. 1993, 1999; Parsons et 

al. 1998; Lackmann et al. 1999; Hecht et al. 2001; Byrd and 

Ogden 2003). Typical levels are about 1 nanomole (nmol) 

of NNAL in 24 hours and 2.2 nmol of NNAL glucuronides 

in 24 hours, with no detection of unchanged NNK. NNAL 

and NNAL glucuronides are absolutely specific to exposure to tobacco and have not been detected in the urine 

of nontobacco users unless they were exposed to secondhand smoke. Because NNAL is not present in cigarette 

smoke, the origin of NNAL and NNAL glucuronides found 

in urine is the metabolism of NNK. Most investigations 

demonstrate a correlation between NNAL plus NNAL glucuronides and cotinine in urine. This finding indicates that 

NNAL and NNAL glucuronides are a biomarker of uptake 

of the lung carcinogen NNK and that cotinine is a biomarker of nicotine uptake. Ratios of NNAL glucuronides 

to NNAL vary at least 10-fold in smokers. This ratio could 

be a potential indicator of cancer risk, because NNAL 

glucuronides are detoxification products, whereas NNAL 

is carcinogenic (Carmella et al. 1995; Richie et al. 1997). 

In human urine, (S)-NNAL-O-glucuronide is the predominant diastereomer of NNAL-O-glucuronide, and the 

level of (S)-NNAL is slightly higher than that of (R)-NNAL 

(Carmella et al. 1999). (S)-NNAL is the more tumorigenic 

enantiomer of NNAL in the A/J mouse lung (Upadhyaya 

et al. 1999). NNAL and NNAL glucuronides are released 

slowly from the human body only after smoking cessation. This finding has been linked to a particularly strong 

retention of (S)-NNAL, possibly at a receptor site (Hecht et 

al. 1999; Zimmerman et al. 2004). Recent studies indicate 

that levels of NNAL plus NNAL-glucuronides are not only 

biomarkers of NNK exposure but also are biomarkers of 

risk for lung cancer in smokers (Church et al. 2009; Yuan 

et al. 2009) 

N’-nitrosonornicotine, N’-nitrosoanatabine, 

N’-nitrosoanabasine, and their pyridine-N-glucuronides. Researchers developed a method to analyze NNN, 

N’-nitrosoanatabine (NATB), N’-nitrosoanabasine (NAB), 

and their pyridine N-glucuronides (e.g., NNN-N-glucuronide) in human urine. NATB and NAB are tobacco-specific 

nitrosamines that like NNN and NNK are formed by the 

nitrosation of tobacco alkaloids (Hecht and Hoffmann 

1988). Studies show that NATB is not carcinogenic but 

that NAB is a weak esophageal carcinogen in rats (Hecht 

1998). Mean levels of total NNN, NATB, and NAB in the 

urine of 14 smokers were 0.18 ± 0.22 SD, 0.19 ± 0.20, and 

0.040 ± 0.039 picomoles/mg of creatinine, respectively. 

These compounds have not been detected in the urine of 

nonsmokers with no exposure to secondhand smoke.

Nitrosamino acids. Researchers have used the 

N-nitrosoproline (NPRO) test to compare endogenous 

nitrosation in smokers and nonsmokers (Bartsch et al. 

1989). The results of clinical studies indicate that the 

frequency of endogenous formation of NPRO is higher 

in smokers than in nonsmokers and that it may be 

enhanced by thiocyanate catalysis (Bartsch et al. 1989; 

Tsuda and Kurashima 1991; Tricker 1997). However, 

some population-based studies document similar levels of 

NPRO in smokers and nonsmokers, because this precursor biomarker for nitrosamine formation is primarily from 

dietary sources (Tricker 1997).
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

The major nitrosamino acids present in human 

urine are N-nitrososarcosine, N-nitrosothiazolidine 

4-carboxylic acid (NTCA), and trans- and cis-isomers of 

N-nitroso-2-methylthiazolidine 4-carboxylic acid (NMTCA) 

(Bartsch et al. 1989; Tsuda and Kurashima 1991). NTCA 

and NMTCA are formed by reactions of formaldehyde or 

acetaldehyde with cysteine, followed by nitrosation. Some 

studies demonstrate increased levels of urinary NTCA 

and NMTCA in smokers (Tsuda and Kurashima 1991). 

Although some studies show a correlation between 

total nitrosamino acids and urinary nicotine plus cotinine 

among smokers (Malaveille et al. 1989), other studies 

show mixed results (Tricker 1997). Collectively, the available data support the concept that nitrosamines can be 

formed endogenously in smokers under some conditions.

Studies suggest that 4-(methylnitrosamino)-4-(3-

pyridyl)butyric acid is a potential monitor of endogenous 

nitrosation of nicotine (Djordjevic et al. 1991). However, 

researchers could not find any evidence for its formation 

after oral administration of nicotine or cotinine to persons 

abstaining from smoking (Tricker et al. 1993).

1,3-butadiene. The major urinary metabolites 

of 1,3-butadiene are monohydroxybutenyl-mercapturic 

acids (MHBMAs) and dihydroxybutyl-mercapturic acid 

(DHBMA). Levels of MHBMA were 86.4 ± 14.0 (SD) μg/24 

hours in smokers and 12.5 ± 1.0 μg/24 hours in nonsmokers—a significant difference (Urban et al. 2003). Corresponding levels of DHBMA were 644 ± 90 (SD) μg/24 

hours in smokers and 459 ± 72 μg/24 hours in nonsmokers, which were not significantly different (Urban et al. 

2003). DHBMA does not appear to be specific to exposure 

to 1,3-butadiene and is probably not a useful biomarker. 

Hb adducts have also proven useful as markers of longterm exposure to 1,3-butadiene. The long half-lives of 

these adducts result in an average measurement that is 

more time weighted than that for some other metabolites 

(e.g., urinary meta-bolites) (Swenberg et al. 2001; Boysen 

et al. 2007). 

Benzene. One path of benzene metabolism proceeds by ring oxidation, ultimately by ring cleavage to 

trans,trans-muconaldehyde, and finally to trans,transmuconic acid (tt-MA), a metabolite widely used as a biomarker of benzene uptake (Scherer et al. 1998). Most 

studies have found significantly elevated levels of tt-MA 

in the urine of smokers (Scherer et al. 1998; Cocco et 

al. 2003; Lee et al. 2005). Levels of tt-MA were 1.4 to 4.8 

times higher in smokers than in nonsmokers, and the 

additional amount of tt-MA excreted by smokers ranged 

from 0.022 to 0.20 mg/gram of creatinine (Scherer et al. 

1998). However, sorbic acid, a food constituent that can be 

transformed metabolically into tt-MA, can contribute to 

urinary levels of tt-MA and thereby decrease its specificity 

as a biomarker for benzene uptake (Scherer et al. 1998; 

Pezzagno et al. 1999). 

S-phenylmercapturic acid (S-PMA) is formed by 

the metabolism of the glutathione conjugate of benzene 

oxide and has the potential to be specific for benzene 

uptake (Stommel et al. 1989; van Sittert et al. 1993; 

Boogaard and van Sittert 1995, 1996; Qu et al. 2000). 

In one study, S-PMA levels were significantly higher in 

smokers (1.71 micromoles [μmol]/mole of creatinine) 

than those in nonsmokers (0.94 μmol/mole of creatinine), 

whereas tt-MA levels were not significantly different 

(Boogaard and van Sittert 1996). Researchers believe that 

S-PMA and tt-MA are the most sensitive biomarkers for 

low levels of exposure to benzene (Qu et al. 2000, 2003). 

Phenol, hydroquinone, catechol, and 1,2,4-trihydroxybenzene are also urinary metabolites of benzene. 

Studies relating urinary levels of these metabolites to 

occupational exposure to benzene have mixed results, 

because background levels of the metabolites are high 

(Inoue et al. 1988, 1989; Ong et al. 1995, 1996; Qu et al. 

2000). Urinary catechol levels did not differ significantly 

between smokers and nonsmokers (Carmella et al. 1982), 

and diet has been shown to be a major source of urinary 

catechol (Carmella et al. 1982).

Products of oxidative damage. The presence of 

free radicals and oxidants in cigarette smoke can lead to 

oxidative DNA damage and the subsequent formation of 

products such as 8-oxodeoxyguanosine, thymine glycol, 

thymidine glycol, and 5-hydroxymethyluracil. Repair of 

these modified DNA constituents ultimately leads to their 

excretion in urine. Researchers have frequently quantified 

8-oxodeoxyguanosine in urine of smokers and nonsmokers (Loft and Poulsen 1998; Prieme et al. 1998; Renner 

et al. 2000). Cigarette smoking usually results in levels of 

8-oxodeoxyguanosine in urine that modestly increase to 

16 to 50 percent higher than those in nonsmokers, but 

studies have also reported negative results (Nia et al. 2001; 

Harman et al. 2003; Mukherjee et al. 2004). Smoking cessation caused a 21-percent decrease in the excretion of 

8-oxodeoxyguanosine (Prieme et al. 1998). Longitudinal 

studies have not shown convincing increases in urinary 

8-oxodeoxyguanosine that were attributable to smoking, 

and a complex pattern of factors may affect background 

levels of this biomarker in urine (Kasai et al. 2001; Pilger 

et al. 2001; Mukherjee et al. 2004). Studies on the effects 

of smoking on urinary levels of 5-hydroxymethyluracil 

or 5-hydroxymethyldeoxyuridine have obtained mixed 

results (Pourcelot et al. 1999; Harman et al. 2003). One 

study showed a correlation between smoking and urinary 

excretion of 3,N4-ethenodeoxycytidine, which may result 

from endogenous lipid peroxidation (Chen et al. 2004a). 

Studies have also detected 1,N6-ethenodeoxyadenosine in 

human urine, but no differences were observed between 

levels in smokers and those in nonsmokers (Hillestrøm 

et al. 2004). 
Surgeon General’s Report

234 Chapter 5

Products of alkylating agents. The reaction of 

alkylating agents with DNA forms alkyladenines, alkylguanines, and other products (Singer and Grunberger 1983). 

Alkylation at the 3-position of deoxyadenosine or at the 

7-position of deoxyguanosine results in products with 

an unstable glycosidic bond. These products are readily 

removed from DNA, either spontaneously or by glycosylases, which results in the urinary excretion of 3-alkyladenines and 7-alkylguanines. Studies have more extensively 

investigated 3-alkyladenines as biomarkers of exposure to 

alkylating agents, because researchers expected the background levels of 3-alkyladenines in urine to be lower than 

those of 7-alkylguanines. However, substantial amounts 

of 3-methyladenine occur in the diet (Prevost et al. 1993; 

Fay et al. 1997). Nevertheless, two controlled studies demonstrated an increase in the urinary excretion of 3-methyladenine among smokers (Kopplin et al. 1995; Prevost 

and Shuker 1996). Another study found lower background 

levels of 3-ethyladenine than those of 3-methyladenine 

(Prevost et al. 1993). Two studies demonstrated convincing increases in urinary levels of 3-ethyladenine in smokers, indicating the presence in cigarette smoke of an 

unidentified ethylating agent (Kopplin et al. 1995; Prevost 

and Shuker 1996). There was no effect from smoking on 

urinary levels of 3-(2-hydroxyethyl)adenine (Prevost and 

Shuker 1996). A population-based study found higher 

levels of both 3-methyladenine and 7-methylguanine in 

smokers than in nonsmokers, and a second study found 

no difference in the 3-methyladenine levels (Shuker et al. 

1991; Stillwell et al. 1991).

Metals. Studies of urinary cadmium have most 

consistently demonstrated differences between smokers and nonsmokers. Large studies in Germany and the 

United States showed increases in urinary cadmium levels with age and smoking (IARC 2004). These results were 

consistent with those of other studies. 

Breath and Blood Biomarkers

Benzene, 1,3-butadiene, and a variety of volatile 

organic compounds including xylenes, styrene, isoprene, 

2,5-dimethylfuran, ethane, and octane were measured in 

expired air; levels were generally higher in smokers than 

in nonsmokers (Gordon et al. 2002; Perbellini et al. 2003; 

IARC 2004). Levels of benzene and 1,3-butadiene in the 

breath of smokers were 360 and 522 μg/cubic meter (m3), 

respectively (Gordon et al. 2002). In another study, mean 

benzene levels ranged from 58.1 to 81.3 μg/m3, depending 

on the cigarette brand (IARC 2004). 

Studies have quantified volatile organic compounds, 

including benzene and styrene, in the blood of smokers; 

levels were generally higher than those in the blood of 

nonsmokers. Benzene levels in blood were significantly 

associated with the number of cigarettes smoked (IARC 

2004). Cadmium levels were also higher in the blood of 

smokers. Measurements of NNAL in blood demonstrated a 

mean level of 42 femtomoles/milliliter of plasma in smokers; NNAL was not detected in nonsmokers (Carmella et 

al. 2005). Cigarette smoke induces oxidative damage as 

determined by elevated blood protein carbonyls (Reznick 

et al. 1992) and blood protein-bound glutathione (Muscat 

et al. 2004). F2-isoprostane levels, which are biomarkers 

of oxidative damage, were higher in the plasma of smokers than in the plasma of nonsmokers and decreased with 

vitamin C treatments (Morrow et al. 1995; Dietrich et al. 

2002). Hb adducts and DNA adducts in white blood cells 

are discussed in the next section.

Summary

Quantitative analysis of carcinogens or their metabolites in urine, breath, and blood provides a convenient and 

reliable method of comparing carcinogen exposure among 

smokers and between smokers and nonsmokers. The most 

extensive measurements have been made in urine. Urinary biomarkers of several major types of carcinogens 

in cigarette smoke are reliable indicators of exposure. 

These biomarkers include trans, anti-PheT and 1-HOP 

for PAH; total NNAL (NNAL plus NNAL glucuronides) for 

NNK; MHBMA for 1,3-butadiene; and tt-MA and S-PMA 

for benzene. The measurements provide good estimates 

of minimum doses of relevant carcinogens in smokers and 

allow comparisons with those in nonsmokers. The total 

carcinogen dose is generally difficult to calculate because 

the extent of conversion of a given carcinogen to the measured metabolite is usually unknown and can vary widely 

among individuals. Nevertheless, the results of these studies are illuminating. They show, for example, that levels 

of metabolites of benzene (about 1,100 nmol/24 hours of 

tt-MA and 8 nmol/24 hours of S-PMA) and 1,3-butadiene 

(about 340 nmol/24 hours of MHBMA) exceed levels of 

other biomarkers (e.g., about 3 nmol/24 hours of NNAL 

plus NNAL glucuronides and 2 nmol/24 hours of 1-HOP). 

These results are consistent with the levels of benzene and 

1,3-butadiene in cigarette smoke, which were higher than 

those of NNK and PAH. 

However, metabolites of benzene and a metabolite 

of 1,3-butadiene (DHBMA) are also found in nonsmokers 

in considerable quantities. Comparisons of smokers and 

nonsmokers demonstrate that total NNAL is the most 

discriminatory carcinogen biomarker because the only 

source of the parent carcinogen NNK is tobacco products. 

Total NNAL is not detected in nonsmokers unless they 

have been exposed to secondhand tobacco smoke. Therefore, this biomarker is particularly useful for comparing carcinogen uptake in smokers who, for example, use 
Cancer 235

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

different tobacco products, because the measurements are 

not confounded by other exposures such as diet, occupation, or the general environment. 

Metabolic Activation and 

Detoxification of Carcinogens

Most of the carcinogens listed in Table 5.1 require 

metabolic activation to become intermediate agents, generally electrophiles, which react with nucleophilic sites in 

DNA to form DNA adducts. All PAHs, heterocyclic compounds, N-nitrosamines, aromatic amines, and heterocyclic aromatic amines in cigarette smoke require metabolic 

activation. Other compounds in Table 5.1 that require 

metabolic activation are 1,3-butadiene, isoprene, benzene, 

nitromethane, 2-nitropropane, nitrobenzene, acrylamide, 

vinyl chloride, and urethane. Detoxification reactions in 

most cases compete with metabolic activation and also 

affect the disposition of compounds that do not require 

metabolic activation, such as ethylene oxide.

An overview of the metabolism of six carcinogens 

in tobacco smoke that are implicated in the formation of DNA adducts identified in human tissues is presented in Figure 5.3. The six carcinogens are B[a]P, NNK, 

N-nitrosodimethylamine (NDMA), NNN, ethylene oxide, 

and 4-ABP. 

The major metabolic activation pathway of B[a]P 

that results in DNA adducts identified in human tissues 

is the conversion to the highly mutagenic B[a]P-7,8-

diol-9,10-epoxides (BPDEs). The formation of BPDE 

occurs in three steps: the metabolism of B[a]P to B[a]

P-7,8-epoxide; hydration of B[a]P-7,8-epoxide to give the 

dihydrodiol B[a]P-7,8-diol; and further epoxidation to 

produce BPDE. One of the four enantiomers is strongly 

carcinogenic and reacts with DNA to form adducts at N2

of deoxyguanosine (BPDE-N2-deoxyguanosine) (Cooper et 

al. 1983; IARC 1983; Thakker et al. 1985). This adduct was 

also observed in animals treated with B[a]P. 

Two other proposed metabolic activation pathways 

of B[a]P exist, but the evidence for their involvement in 

DNA adduct formation in laboratory animals and humans 

is not as strong as that for BPDE. One pathway involves 

the conversion of B[a]P-7,8-diol to the corresponding catechol metabolite catalyzed by dihydrodiol dehydrogenase. 

The catechol can undergo redox cycling to produce a quinone reactive with DNA, and the redox cycling process can 

produce oxidative damage to DNA (Penning et al. 1999; Yu 

et al. 2002). Another metabolic activation process occurs 

when one electron oxidation of B[a]P produces unstable 

depurinating DNA adducts that can lead to apurinic sites 

and miscoding (Casale et al. 2001). A common mechanism 

of metabolic activation for a number of PAHs is the formation of diol epoxides in which the epoxide ring is in the bay 

region of the PAH molecule, similar to that in BPDE (Conney 1982; Thakker et al. 1985; Baird and Ralston 1997). 

Competing with B[a]P metabolic activation processes are 

detoxification pathways leading to (1) phenols through 

direct hydroxylation or rearrangement of initially formed 

epoxides, (2) dihydrodiols through hydration of epoxides 

catalyzed by epoxide hydrolase, and (3) formation of glutathione, glucuronide, and sulfate conjugates. Researchers 

have also observed the formation of quinone metabolites 

from initial hydroxylation at the 6-position, followed by 

further oxidation (Cooper et al. 1983).

Metabolic activation of NDMA occurs by α-hydroxylation and leads to an unstable α-hydroxymethyl metabolite. This compound spontaneously loses formaldehyde 

and forms methanediazohydroxide, the same intermediate agent produced in the α-methylene hydroxylation of 

NNK. Researchers also observed the consequent formation of methyl DNA adducts such as 7-methylguanine, 

O6-methylguanine, and O4-methylthymidine. Denitrosation produces nitrite and methylamine and is a detoxification pathway (Preussmann and Stewart 1984; Hecht and 

Samet 2007). The metabolism of NNK and NDMA forms 

aldehydes, whose roles in carcinogenesis are unclear, but 

studies show that formaldehyde reacts with DNA and protein to form cross-links and other products (Chaw et al. 

1980; Beland et al. 1984; Hecht and Samet 2007). 

α-hydroxylation of NNN adjacent to the pyridine 

ring produces the same intermediate agent formed by 

methyl hydroxylation of NNK, which leads to pyridyloxobutyl (POB)-DNA adducts (Hecht 1998). α-hydroxylation 

distal from the pyridine ring also produces a reactive 

diazohydroxide, but its reactions with DNA have not been 

fully characterized. The acetate esters of the α-hydroxyNNN metabolites are mutagenic (Hecht 1998; Hecht and 

Samet 2007). β-hydroxylation of NNN, a minor pathway, 

and pyridine-N-oxidation are detoxification reactions. 

NNN is also detoxified by denitrosation and oxidation to 

produce norcotinine, and by glucuronidation of the pyridine ring (Hecht 1998; Stepanov and Hecht 2005; Hecht 

and Samet 2007). 

Ethylene oxide reacts directly with DNA to form 

7-(2-hydroxyethyl)guanine and other adducts (IARC 1994; 

Hecht and Samet 2007). Competing detoxification pathways involve glutathione conjugation and excretion of 

mercapturic acids (IARC 1994). 

4-ABP is metabolically activated by N-hydroxylation 

(Kadlubar and Beland 1985; Hecht and Samet 2007). 

Conjugation of the resulting hydroxylamine with acetate 

or other groups, such as sulfate, ultimately produces 

nitrenium ions, which react with DNA and form adducts 
Surgeon General’s Report

236 Chapter 5 Figure 5.3 Metabolism of six carcinogens in tobacco smoke that produce DNA adducts identified in the lungs of smokers

Source: Adapted from Cooper et al. 1983; Preussmann and Stewart 1984; Kadlubar and Beland 1985; International Agency for Research on Cancer 1994; and Hecht 1998, 1999.Note: In 4-ABP scheme, X represents conjugates such as glucuronide or sulfate. 4-ABP = 4-aminobiphenyl; Ac = acetyl; ADP = adenosine diphosphate; B[a]P = benzo[a]pyrene; EH = epoxide hydrolase; Glucs = glucuronides; GSTs = glutathione-S-transferases; NATs = N-acetyltransferases; NDMA = N-nitrosodimethylamine; NIH shift = National Institutes of Health phenomenon of hydroxylation-induced intramolecular migration; NNAL = 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol; NNK = 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone; NNN = N’-nitrosonornicotine; P-450s = cytochrome P-450 enzymes; UGTs = uridine-5’-diphosphate-glucuronosyltransferases.

aCarcinogens in tobacco smoke.
Cancer 237

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

mainly at C-8 of guanine. Other aromatic amines, as well 

as heterocyclic aromatic amines, are predominantly activated metabolically in similar ways. Acetylation of 4-ABP 

can be a detoxification pathway if it is not followed by 

N-hydroxylation. Ring hydroxylation and conjugation of 

the phenols result in detoxification.

Two other important carcinogens from cigarette 

smoke that require metabolic activation are benzene and 

1,3-butadiene. DNA adducts of these compounds have not 

been detected in human samples. However, there is considerable information on their conversion to intermediate 

agents that react with DNA. 

Benzene is metabolized to benzene epoxide, which 

is in equilibrium with its 7-member ring tautomer oxepin 

(Scherer et al. 2001; Hecht and Samet 2007). Researchers 

have observed the reaction of benzene epoxide with DNA 

to produce 7-phenylguanine. Further metabolism of benzene epoxide-oxepin can occur in a variety of ways. One 

way is nonenzymatic rearrangement to phenol, which 

can be further hydroxylated to hydroquinone, catechol, 

and 1,2,4-trihydroxybenzene. These metabolites can then 

be conjugated as glucuronides or sulfates. Hydroquinone 

can be further oxidized to benzoquinone, which can bind 

to DNA, or hydration catalyzed by epoxide hydrolase can 

produce benzene dihydrodiol, which can then be converted to catechol or tt-MA. Another possibility involves 

conjugation with glutathione that ultimately produces 

S-PMA. Other pathways of benzene metabolism result in 

the formation of biphenyl and benzene dioxetane, which 

can also lead to tt-MA (Scherer et al. 2001; Hecht and 

Samet 2007). Studies have detected nitrobenzene, nitrobiphenyl, and nitrophenol isomers in the bone marrow 

of mice treated with benzene; these isomers presumably 

formed from reactions of benzene with endogenously 

generated nitric oxide (Chen et al. 2004b; Hecht and 

Samet 2007). 

1,3-butadiene is metabolically activated by epoxidation to give a monoepoxide that can be further metabolized to a diepoxide and a dihydrodiol epoxide (van Sittert 

et al. 2000; Hecht and Samet 2007), which all form DNA 

adducts. The dihydrodiol epoxide also produces cross-links 

in DNA and may be the most important of these intermediate agents (Park and Tretyakova 2004; Hecht and Samet 

2007). The epoxides can be hydrated to dihydrodiols and 

conjugated by reactions with glutathione. 1,3-butadiene 

metabolism can also lead to epoxidation and formation of N-terminal Hb adducts, providing a longer-term, 

“time-weighted” measurement of exposure (Swenberg et 

al. 2001).

Although details remain to be determined, the 

major pathways of metabolic activation and detoxification 

of some of the principal carcinogens in cigarette smoke 

are well established. Reactive intermediate agents that 

are critical in forming DNA adducts include diol epoxides 

of PAH, diazonium ions generated by α-hydroxylation 

of nitrosamines, nitrenium ions formed from esters of 

N-hydroxylated aromatic amines, and epoxides such as 

ethylene oxide. Glutathione and glucuronide conjugation 

play major roles in the detoxification of carcinogens in 

cigarette smoke. 

Enzymology of Carcinogen 

Metabolism

Introduction

A number of enzyme families are important in 

both the activation and detoxification of carcinogens in 

cigarette smoke, including P-450s, GSTs, UGTs, N-acetyltransferases (NATs), epoxide hydrolases, and sulfotransferases. The importance of each enzyme to the activation 

or detoxification of a particular carcinogen depends on 

characteristics of both the carcinogen (size, polarity, and 

lipophilicity) and the enzyme (structure, tissue distribution, and regulation of expression). The large number of 

carcinogens in cigarette smoke and the wide variety of 

enzymes involved in metabolizing these carcinogens preclude a comprehensive discussion of current understanding of the contribution of each enzyme to every pathway. 

Therefore, the goals of this presentation are to introduce 

the families of enzymes involved and to highlight some 

of the activation and detoxification reactions for specific 

enzymes and carcinogens.

Cytochrome P-450 Enzymes

P-450s, encoded by CYP genes, are microsomal 

enzymes that catalyze the oxidation of myriad chemicals, 

including many of the carcinogens in cigarette smoke. 

Sequencing the human genome has identified 57 CYP

genes, about 15 of which are considered important in 

the metabolism of xenobiotics (Nelson 2003; Guengerich 

2004). Among the P-450s encoded by these genes, a reasonable argument can be made for the role of six (1A1, 

1B1, 1A2, 2A6, 2A13, and 2E1) as important catalysts for 

the metabolic activation of carcinogens in cigarette smoke. 

PAHs are metabolized by P-450s 1A1 and 1B1 (Shimada and 

Fujii-Kuriyama 2004), aromatic amines by P-450 1A2 

(Kim and Guengerich 2005), and N-nitrosamines by 

P-450s 2A6, 2A13, and 2E1 (Yoo et al. 1988; Guengerich 

et al. 1991; Yamazaki et al. 1992; Jalas et al. 2005; Wong 

et al. 2005a). P-450 2E1 also catalyzes the epoxidation of 

benzene and 1,3-butadiene (Guengerich et al. 1991; Bolt 

et al. 2003). 
Surgeon General’s Report

238 Chapter 5

P-450s 1A1 and 1B1 are expressed in a wide range 

of extrahepatic tissues and catalyze both the activation 

and detoxification reactions of PAH metabolism (Shimada 

and Fujii-Kuriyama 2004). In addition, both enzymes are 

inducible by the PAHs in cigarette smoke (Nebert et 

al. 2004). Induction of these two enzymes is generally 

mediated by the aryl hydrocarbon receptor, but differences may exist in the mode of induction for each enzyme. 

Historically, researchers believed that P-450 1A1 was the 

predominant P-450 catalyst for the metabolism of PAHs, 

particularly in the lung. However, the discovery of P-450 

1B1 (Sutter et al. 1994) clarified the equal or more predominant role P-450 1B1 may play in the activation of 

PAHs compared with that of P-450 1A1 (Shimada et al. 

1996). Studies show that P-450 1B1, which is heterologously expressed, activates the proximate carcinogen of 

many PAHs and that in several cases, P-450 1B1 was more 

efficient than P-450 1A1 (Shimada et al. 1996). For example, (+)-B[a]P-7,8-diol was activated to a genotoxic species 

to a greater extent by P-450 1B1 than by P-450 1A1 (Shimada et al. 1996). In addition, the ratio of the maximum 

velocity (Vmax) of an enzyme-catalyzed reaction to the 

concentration of a substrate that leads to half-maximal 

velocity (Km) for the formation of B[a]P-7,8-diol was 3.5-

fold greater for P-450 1B1 than for P-450 1A1 (Shimada 

et al. 1999). (The Vmax to Km ratio measures an enzyme’s 

efficiency.) In contrast, P-450 1A1 was a better catalyst of 

B[a]P 3-hydroxylation, which is a detoxification pathway 

(Shimada et al. 1997). Taken together, these data indicate 

that P-450 1B1 activity, but not P-450 1A1 activity, may 

contribute to individual susceptibility to B[a]P-induced 

carcinogenesis. However, cigarette smoke has many different PAH carcinogens, and either P-450 1B1 or 1A1 

individually or together may be important in their metabolic activation.

As noted previously (see “Cytochrome P-450 

Enzymes” earlier in this chapter), both P-450 1A1 and 1B1 

are inducible by PAHs. Studies have reported that levels 

of messenger RNA (mRNA) and protein of both P-450s 

were higher in the lungs of smokers than in the lungs of 

lifetime nonsmokers (Willey et al. 1997; Kim et al. 2004a; 

Port et al. 2004). The levels of P-450 1A1 and 1B1 proteins 

were correlated in lung microsomes from all participants 

who smoked. However, the absolute amount of P-450 1A1 

in each person was, on average, more than 10-fold greater 

than the amount of P-450 1B1 (Kim et al. 2004a). Despite 

the ability of P-450 1B1 to more efficiently mediate the 

activation of some PAHs, the higher P-450 1A1 levels may 

result in each enzyme contributing similarly to the total 

metabolism of PAHs. An equally important factor in determining the role of these P-450s in the activation of PAHs 

in cigarette smoke is the variability in the induction of 

P-450s across individuals. Researchers do not know 

whether the responsible mechanism is common to both 

P-450s 1A1 and 1B1.

Studies have characterized P-450 1A2 as the best 

catalyst for aromatic amine N-oxidation, which is the first 

step in the activation of these bladder carcinogens (Butler 

et al. 1989; Landi et al. 1999; Kim and Guengerich 2005). 

P-450 1A2 is both constitutively expressed and inducible 

in the liver. The induction of P-450 1A2 is mediated by the 

aryl hydrocarbon receptor, and hepatic levels vary more 

than 60-fold from person to person (Nebert et al. 2004). 

Cigarette smoking induces the levels of this enzyme in the 

liver. Researchers have also reported that P-450s 1A1 and 

1B1 metabolically activate a number of aromatic amines, 

including 4-ABP, and may play a role in extrahepatic 

metabolism (Shimada et al. 1996).

Although hepatic P-450 2A6 catalyzes the metabolic 

activation of NNK (Yamazaki et al. 1992; Jalas et al. 2005), 

P-450 2A6 is not a particularly efficient catalyst. The extrahepatic P-450 2A13 might be a more important catalyst of 

the activation of this carcinogen (Jalas et al. 2005). P-450 

2A13 is expressed in the lung (Su et al. 2000) and catalyzes 

the α-hydroxylation of NNK significantly more efficiently 

than does P-450 2A6. P-450 2A13 is an excellent catalyst 

of NNK α-hydroxylation, with a low Km and a high Vmax. 

P-450 2A13 is the sole catalyst of NNK α-hydroxylation in 

human fetal nasal tissue and is considered equally important in the lung (Wong et al. 2005b). P-450 2E1 has also 

catalyzed the activation of both NNN and NNK (Yamazaki 

et al. 1992). However, the catalytic efficiencies of these 

reactions are poor (Hecht 1998; Jalas et al. 2005). Studies 

have identified P-450 2E1 as the best catalyst of NDMA 

metabolism (Yoo et al. 1988; Guengerich et al. 1991) and 

as an excellent catalyst of the epoxidation and activation of 

benzene and 1,3-butadiene (Guengerich et al. 1991; Bolt 

et al. 2003).

Epoxide Hydrolases

Several carcinogens of tobacco smoke, including 

PAH, 1,3-butadiene, and benzene, are metabolized to 

epoxides. These epoxide metabolites are substrates for 

MEH (also known as EPHX1), an enzyme that catalyzes 

their hydrolysis (Wood et al. 1976; Snyder et al. 1993; 

Krause and Elfarra 1997; Fretland and Omiecinski 2000). 

In mammals, at least five epoxide hydrolases were identified. However, four of these predominantly or exclusively 

catalyze the hydrolysis of endogenous substrates (Fretland 

and Omiecinski 2000). The fifth, MEH, plays a role in both 

the detoxification and activation of xenobiotics. Specifically, MEH is involved in the formation of the reactive diol 

epoxide metabolites of PAHs, and its activity is therefore 

critical to the carcinogenicity of these compounds (Conney 1982). For example, MEH catalyzes the hydrolysis of 
Cancer 239

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

B[a]P-7,8-epoxide to B[a]P-7,8-diol, which is then oxidized to the ultimate carcinogen BPDE (Levin et al. 1976; 

Gautier et al. 1996). The importance of this enzyme to 

PAH carcinogenicity is supported by the observation that 

MEH-null mice are highly resistant to carcinogenesis 

induced by 7,12-dimethylbenz[a]anthracene (Miyata et 

al. 1999).

In contrast to its role in the activation of PAHs, 

MEH detoxifies the epoxides of 1,3-butadiene (Krause 

and Elfarra 1997; Wickliffe et al. 2003). Studies have 

reported that several polymorphisms in MEH result in an 

increased sensitivity to the genotoxic effects of 1,3-butadiene (Abdel-Rahman et al. 2003, 2005). Benzene oxide is 

also a substrate for MEH (Snyder et al. 1993). However, 

male mice deficient in MEH are not susceptible to toxic 

effects induced by benzene (Bauer et al. 2003). The role of 

benzene oxide in carcinogenesis is unclear.

Glutathione-S-Transferases

Another mechanism that may detoxify carcinogenic 

epoxides is conjugation with glutathione. This reaction 

can be catalyzed by cytosolic GSTs (Sheehan et al. 2001; 

Hayes et al. 2005), which are dimeric. Seven classes (alpha, 

mu, pi, sigma, theta, omega, and zeta) exist in mammalian 

species (Sheehan et al. 2001), and at least 16 GST subunits exist in humans. However, only four homodimeric 

enzymes to date have been characterized as catalysts of 

glutathione conjugation of tobacco smoke carcinogens 

(Cheng et al. 1995; Norppa et al. 1995; Wiencke et al. 1995; 

Jernstrom et al. 1996; Sundberg et al. 1998, 2002; Landi 

2000; Verdina et al. 2001; Fustinoni et al. 2002; Sørensen 

et al. 2004a; Hayes et al. 2005). These enzymes are members of four GST classes: alpha (GSTA1-1), mu (GSTM1-1), 

pi (GSTP1-1), and theta (GSTT1-1). The protein levels of 

each GST vary significantly from person to person, as well 

as across tissues within an individual (Rowe et al. 1997; 

Sherratt et al. 1997; Mulder et al. 1999). Researchers have 

identified several polymorphisms in the genes encoding 

these subunits (Hayes et al. 2005). Of particular note with 

regard to cancer risk in smokers are the *NULL alleles 

for GSTM1 and GSTT1, which have decreased detoxification capacity and elevated DNA damage. GSTA1, GSTM1, 

and GSTT1 are expressed in the liver of persons who are 

not homozygous for either null phenotype; little GSTP1 is 

present in the liver (Rowe et al. 1997; Sherratt et al. 1997; 

Mulder et al. 1999). In contrast, the lung expresses higher 

levels of GSTP1 than those expressed by the other three 

subunits (Rowe et al. 1997; Sherratt et al. 1997). 

GSTA1-1, GSTM1-1, and GSTP1-1 each catalyze the 

glutathione conjugation of a number of PAH diol epoxides (Jernstrom et al. 1996; Sundberg et al. 1998, 2002). 

However, the efficiencies and stereoselectivity of each of 

these enzymes vary with the diol epoxide substrate. For 

example, GSTM1-1 is a more efficient catalyst of glutathione conjugation of (+)-anti-BPDE than is either 

GSTA1-1 or GSTP1-1 (Sundberg et al. 1997). The GSTA1-1 

and GSTP1-1 enzymes have overall Kcat/Km values for 

catalytic rate or turnover number that are about 3-fold 

lower than the value for GSTM1-1, but GSTM1-1 is almost 

30-fold better as a catalyst for the conjugation of (-)-antiBPDE (Sundberg et al. 1997). The contribution of each GST 

enzyme to the detoxification of PAH diol epoxides varies with the substrate and across different tissues on the 

basis of their expression levels. In lung tissue from smokers, levels of (+)-anti-BPDE–DNA adducts were dependent on the GSTM1 genotype (Alexandrov et al. 2002). 

Persons with the GSTM1 null genotype had significantly 

higher adduct levels than did those with the GST wild-type 

genotype. These data support the importance of GSTM1-1 

activity in BPDE detoxification in the lung, but they do 

not exclude a role for GSTA1-1 and GSTP1-1 in the detoxification of this or other PAHs.

GSTM1-1 and GSTT1-1 enzymes play a key role in 

the conjugation of two 1,3-butadiene epoxide metabolites: 

3,4-epoxybutene (EB) and diepoxybutane (DEB) (Norppa 

et al. 1995; Wiencke et al. 1995; Thier et al. 1996; Bernardini et al. 1998; Landi 2000; Fustinoni et al. 2002; 

Schlade-Bartusiak et al. 2004). The direct measurement 

of either GSTM1-1 or GSTT1-1 activity with these epoxide 

substrates has not been reported. However, several studies of sister chromatid exchange (SCE) in human lymphocyte cultures from persons with the GSTT1 null genotype 

support the role of GSTT1-1 in the detoxification of DEB 

(Norppa et al. 1995; Wiencke et al. 1995; Bernardini et 

al. 1998; Landi 2000; Schlade-Bartusiak et al. 2004). In 

conflict with these data, one study reports the increased 

mutagenicity of DEB in Salmonella typhimurium TA1535 

expressing GSTT1-1, suggesting that the conjugation of 

this diepoxide is an activation pathway (Thier et al. 1996). 

The role of both GSTM1-1 and GSTT1-1 in the detoxification of EB is supported by a higher induction of SCE by 

EB in lymphocyte cultures from persons with either the 

GSTM1-1 or the GSTT1-1 null genotype (Uusküla et al. 

1995; Bernardini et al. 1998). Although GSTs play a role 

in the metabolism of 1,3-butadiene, it remains unclear 

whether polymorphisms in GSTs modulate the carcinogenic effects of 1,3-butadiene in humans (Fustinoni et 

al. 2002).

One major excreted metabolite of benzene is 

S-PMA, which is formed from the glutathione conjugate of 

benzene oxide (Snyder and Hedli 1996). This glutathione 

conjugate may be generated both enzymatically and nonenzymatically, and it is not clear which pathway predominates. However, a number of studies on benzene exposure 

and toxicity have suggested a role for either GSTM1-1 or 
Surgeon General’s Report

240 Chapter 5

GSTT1-1 in the conjugation of benzene oxide (Hsieh et 

al. 1999; Verdina et al. 2001; Wan et al. 2002; Kim et al. 

2004b). Researchers have not directly measured which 

enzyme is the better catalyst of glutathione conjugation 

of benzene oxide. The in vivo role of GSTT1-1 in benzene 

oxide detoxification is supported by a report that S-PMA 

levels excreted by persons exposed to benzene who carried 

the wild-type GSTT1* allele were higher than those of persons homozygous for the GSTT1* NULL allele (Sørensen 

et al. 2004b). 

Ethylene oxide is also detoxified by glutathione 

conjugation (Brown et al. 1996). Although studies have 

not directly evaluated the role of specific human GSTs, 

evidence supports the role of GSTT1-1 as a catalyst of 

this reaction (Hallier et al. 1993; Fennell et al. 2000). On 

exposure to ethylene oxide, lymphocytes from persons 

with the GSTT1-1* NULL allele had higher levels of SCE 

than did those from persons with the wild-type allele (Hallier et al. 1993). In addition, levels of 2-hydroxyethylvaline 

Hb adducts were higher in smokers than in nonsmokers, because of exposure to ethylene and ethylene oxide 

in cigarette smoke, and were higher in smokers with the 

GSTT1* NULL allele than in those with the wild-type allele 

(Fennell et al. 2000).

Uridine-5’-Diphosphate-Glucuronosyltransferases

Conjugation with glucuronic acid is an important 

metabolic pathway for a number of carcinogens in tobacco 

smoke (Bock 1991; Hecht 2002a; Nagar and Remmel 2006). 

(Conjugation is the addition of a polar moiety to a metabolite to facilitate excretion.) The microsomal enzymes, 

UGTs, catalyze these conjugation reactions. Researchers 

have identified 18 human UGTs that are members of two 

families (UGT1 and UGT2) (Tukey and Strassburg 2000; 

Burchell 2003; Nagar and Remmel 2006). The UGT1A proteins are encoded by a single gene cluster, and expression 

of the nine members of this subfamily occurs through exon 

sharing. Exon 1 is unique for each UGT1A, whereas exon 2 

to exon 5 are shared by all UGT1As (Tukey and Strassburg 

2000). Thus, all UGT1A proteins are identical in the 245 

amino acids of the carboxyl terminus encoded by exon 2 

to exon 5 (Tukey and Strassburg 2000; Finel et al. 2005). 

In contrast, proteins from the UGT2 family are all unique 

gene products (Riedy et al. 2000; Tukey and Strassburg 

2000). The expression of UGTs is tissue specific, and there 

are large differences in expression among tissues (Gregory 

et al. 2000, 2004; Tukey and Strassburg 2000; Wells et al. 

2004). For example, UGTs 1A1, 1A3, 1A4, 1A6, and 1A9 are 

highly expressed in the liver; UGTs 1A7, 1A8, and 1A10 

are mainly expressed in extrahepatic tissues (Tukey and 

Strassburg 2000; Gregory et al. 2004; Wells et al. 2004).

Aromatic amines and their N-hydroxy metabolites 

are glucuronidated to facilitate excretion (Bock 1991; 

Tukey and Strassburg 2000; Zenser et al. 2002). Glucuronidation is a detoxification reaction. Therefore, variations in 

the expression and catalytic efficiency of the enzymes that 

catalyze this reaction may influence the carcinogenicity of 

particular aromatic amines. In general, researchers have 

suggested that members of the UGT1A family contribute 

to the glucuronidation of these carcinogens (Orzechowski 

et al. 1994; Green and Tephly 1998; Tukey and Strassburg 

2000; Zenser et al. 2002). However, UGT2B7 also catalyzes 

their glucuronidation (Zenser et al. 2002). In most cases, 

data support UGT1A9 as the best catalyst. For the tobacco 

smoke carcinogen 4-ABP, the relative catalytic efficiency 

of N-glucuronidation is UGT1A9>UGT1A4>UGT1A7>UGT

2B7>UGT1A6, but the catalytic efficiency of all these proteins is approximately equal to that of UGT1A1 (Zenser et 

al. 2002). 

The phenol and diol metabolites of PAHs are primarily eliminated as glucuronide conjugates. Researchers 

have studied the role of specific UGTs in the metabolism 

of B[a]P (Bock 1991; Guillemette et al. 2000; Fang et al. 

2002; Dellinger et al. 2006). Studies with UGT1A-deficient 

rats have implicated UGT1A enzymes in the detoxification 

of B[a]P (Wells et al. 2004). The glucuronidation of B[a]P7,8-diol and 3-hydroxy-, 7-hydroxy-, and 9-hydroxy-B[a]P 

by heterologously expressed human UGTs has been characterized for a number of UGT1A and UGT2B enzymes 

(Fang et al. 2002; Dellinger et al. 2006). Among the phenols, UGT1A10 was the most efficient UGT1A catalyst of 

glucuronidation. UGTs 2B7, 2B15, and 2B17 all catalyzed 

conjugation of the three B[a]P phenols. However, the Km

of the reaction for UGT2B enzymes was 2- to 250-fold 

higher than that for UGT1A10 (Dellinger et al. 2006). For 

the carcinogenic (-)-B[a]P-7,8-diol, UGT1A10 was a better catalyst of glucuronidation than was UGT1A9, and 

UGT2B7 did not catalyze detectable levels of glucuronidation (Fang et al. 2002), but UGT2B7 did catalyze the glucuronidation of (+)-B[a]P-7,8-diol. 

In smokers, glucuronidation also plays an important role in the excretion of the NNK metabolite NNAL 

(Carmella et al. 2002b; Hecht 2002a). Both O-linked and 

N-linked NNAL glucuronide conjugates are formed (Carmella et al. 2002b). In addition, the direct detoxification of the hydroxymethyl metabolite of NNK occurs by 

glucuronidation in rats (Murphy et al. 1995). However, 

the contribution of this pathway to NNK detoxification 

in smokers has not been identified. In vitro studies with 

fibroblasts both from UGT1A-deficient and control rats 

have confirmed a role for UGT1A enzymes in the protection of these cells from NNK-induced micronuclei formation (Kim and Wells 1996). Human UGT1A9, UGT2B7, 
Cancer 241

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

and UGT2B17 catalyze NNAL-O-glucuronidation, with 

UGT2B17 being the most active, and UGT1A4 catalyzes 

NNAL-N-glucuronidation (Ren et al. 2000; Wiener et al. 

2004b; Lazarus et al. 2005). The rate of NNAL O- and 

N-glucuronidation by human liver microsomes varies significantly among persons; researchers have suggested that 

polymorphisms in UGT2B7 and UGT1A4 contribute to this 

variability (Wiener et al. 2004a).

Glucuronidation may also contribute to the detoxification of benzene (Bock 1991). In hepatocytes from 

rats treated with 3-methylcholanthrene to induce UGTs, 

phenol glucuronidation increases compared with sulfation. Glucuronide conjugates are more stable than the 

corresponding sulfates, and researchers have suggested 

the glucuronidation of phenol as a detoxification pathway 

(Bock 1991). However, to date, the role of glucuronidation 

in benzene-induced carcinogenesis has not been characterized and is poorly understood.

N-Acetyltransferases

NATs are cytosolic enzymes that catalyze the transfer of the acetyl group from acetylcoenzyme A to an 

acceptor molecule (Hein et al. 2000b). This transfer 

occurs through an enzyme intermediate in which cysteine 

68 is acetylated and then deacetylated during the course 

of the reaction. Humans express two unique enzymes, 

NAT1 and NAT2, which catalyze both N- and O-acetylation 

reactions. Researchers have recognized the polymorphic 

nature of NAT2 for more than 40 years and, more recently, 

have identified more than 35 alleles (Hein et al. 2000b; 

Hein 2002). NAT1 is less well studied but is also polymorphic, and more than 25 alleles have been identified 

(Hein 2002; University of Louisville School of Medicine 

2006). Researchers suggest that polymorphisms in both 

NAT1 and NAT2 influence the activation and detoxification of carcinogenic aromatic amines in tobacco smoke 

(Hein 2002).

The N-acetylation of aromatic amines, such as 

4-ABP, is a detoxification reaction (Hein 2002). In contrast, O-acetylation of the N-hydroxy metabolites of 

arylamines generated by P-450 (e.g., N-hydroxy-4-ABP) is 

an activation reaction leading to DNA adduct formation 

(Hein et al. 1993, 1995; Hein 2002). NAT1 and NAT2 both 

catalyze each of these reactions (Hein et al. 1993). However, NAT2 is generally considered the more important 

catalyst of detoxification, and NAT1 is the more important catalyst of activation (Badawi et al. 1995; Hein 2002). 

This assumption is based on differences in the catalytic 

efficiency of the enzymes and their tissue distribution in 

humans as well as on studies with animal models (Hein et 

al. 1993; Hein 2002). 

Studies with recombinant human NAT1 and NAT2

have described differences in the N-acetylation of 4-ABP. 

The apparent affinity of 4-ABP for NAT2 is significantly 

greater than that for NAT1, and ratios of NAT1 activity to 

NAT2 activity and clearance calculations support a greater 

role for NAT2 than for NAT1 in the N-acetylation of arylamines (Hein et al. 1993). The characterization of NAT1 

as the key catalyst of the O-acetylation (i.e., activation) 

of aromatic amines is more speculative and is primarily 

driven by the tissue distribution of NAT1 (see the discussion below). No data in the literature report differences 

between the efficiencies of NAT1- and NAT2-catalyzed 

O-acetylation of aromatic amines. However, more recent 

studies that engineered S. typhimurium strains to overexpress either NAT1 or NAT2 reported that NAT1, but not 

NAT2, catalyzed the genotoxic activation of N-hydroxy4-ABP (Oda 2004). These data provide support for NAT1 

as an important catalyst in the activation of this aromatic amine. 

The organ and tissue distribution of NAT1 and NAT2 

differ markedly (Dupret and Rodrigues-Lima 2005). The 

NAT2 protein is mainly expressed in the gut and liver; the 

NAT1 protein is expressed in the liver and a number of 

other tissues, including the colon and bladder. Researchers believe that aromatic amines in tobacco smoke contribute to smoking-related bladder cancer. Therefore, the 

potential activation of these compounds in the bladder is 

important in understanding the etiology of bladder cancer. Researchers have detected NAT1 activity, but not NAT2 

activity, in samples of bladder tissue from smokers (Badwawi et al. 1995). In addition, DNA adduct levels measured 

by 32P-postlabeling correlated with NAT1 activity. These 

data are thus consistent with a role for NAT1 in the activation of arylamines in tobacco smoke.

Epidemiologic studies that demonstrate a modest 

increase in risk of bladder cancer in persons phenotypically and genotypically identified as having slow acetylation catalyzed by NAT2 further support the role of NAT2 

in the detoxification of aromatic amines (Green et al. 

2000; Hein et al. 2000a; Gu et al. 2005) (see “Molecular 

Epidemiology of Polymorphisms in Carcinogen-Metabolizing Genes” later in this chapter). A number of the NAT2

variant alleles identified in persons with slow acetylation were expressed heterologously and demonstrated a 

decrease in activity for both the N-acetylation of 4-ABP and 

O-acetylation of N-hydroxy-4-ABP, primarily because of 

the instability of the variant enzymes (Hein et al. 1995; 

Zhu et al. 2002). Both activation and detoxification would 

be diminished in persons expressing variant NAT2 activity, 

but NAT1 activity would be maintained. Studies that have 

characterized NAT1 proteins from a number of variants of 

this gene have also reported a decrease in enzyme activity 

(Fretland et al. 2002). 
Surgeon General’s Report

242 Chapter 5

DNA Adducts and Biomarkers

Introduction

Although formation of carcinogen-DNA adducts is 

a well-characterized phenomenon in laboratory animals, 

there were no reports of analyses of DNA adducts in smokers before the mid-1980s. In the past 20 years, a large 

body of literature on DNA adducts in human tissues has 

emerged with the development of sensitive methods such 

as HPLC fluorescence, GC–MS, liquid chromatography 

(LC)–MS, electrochemical detection, 32P-postlabeling, 

and immunoassay. Researchers have applied all of these 

methods to analyze DNA adducts, producing data on these 

biomarkers in molecular epidemiologic studies of cancer susceptibility. Thus, a discussion of DNA adducts in 

human tissues also includes biomarkers of DNA adduct 

formation in smokers. 

Characterized Adducts in the Human Lung

Available data on characterized DNA adducts in 

human lung tissue, the tissue most extensively investigated to date, are summarized in Table 5.2. The small 

number of studies reflects several difficulties in this 

research. First, DNA from human lung tissue is difficult to 

obtain. The amounts of DNA available from routine procedures, such as bronchoscopy, are generally too small for 

analysis of specific DNA adducts. Second, the levels of DNA 

adducts are generally low: between 1 in 10 million and 1 

in 100 million normal DNA bases. Analyzing such small 

amounts of material is challenging. Nevertheless, methods such as those listed previously and in Table 5.2 were 

successfully applied. However, because of the limitations 

noted, the number of participants in most of the studies 

is small.

The major DNA adduct of B[a]P observed in laboratory animals is BPDE-N2-deoxyguanosine. Acid hydrolysis 

of DNA containing this adduct releases B[a]P-7,8,9,10-

tetraol, which can be analyzed by HPLC with fluorescence 

detection (Rojas et al. 1998). Other BPDE-derived DNA 

adducts may be hydrolyzed simultaneously. This assay 

has been applied to lung tissue obtained during surgery 

(Alexandrov et al. 2002; Boysen and Hecht 2003). Compared with nonsmokers, smokers with the GSTM1 null 

genotype displayed higher levels of BPDE-DNA adducts 

in lung tissue, although this finding is based on a small 

number of cases (Rojas et al. 1998, 2004). BPDE-DNA 

adducts were detectable in 40 percent of the smokers with 

whole lung analyses (Boysen and Hecht 2003) and in all 

samples with analyses of bronchial epithelial cells (Rojas 

et al. 2004). When the adduct localization in genes was 

determined by in vitro studies, one target was seen to be 

at mutational hot spots in the P53 tumor-suppressor gene 

and the KRAS oncogene in cells (Tang et al. 1999; Feng et 

al. 2002).

Several studies have quantified 7-methyldeoxyguanosine in human lung tissue. The source of this adduct in 

smokers could be NDMA, NNK, or perhaps other methylating agents. Studies have reported mixed results: some 

show higher adduct levels in smokers than in nonsmokers (Hecht and Tricker 1999; Lewis et al. 2004). One study 

examined O6-methyldeoxyguanosine in human lung tissue but was too small to draw conclusions about the effect 

of smoking (Wilson et al. 1989). 

Three small studies provided evidence for ethyl DNA 

adducts in human lung tissue (Wilson et al. 1989; Blömeke 

et al. 1996; Godschalk et al. 2002). Levels of both O6-ethyldeoxyguanosine and O4-ethylthymidine were higher in 

smokers than in nonsmokers. Although one source of 

these adducts could be N-nitrosodiethylamine, its level in 

cigarette smoke is low. As discussed previously, cigarette 

smoke contains a direct-acting, but chemically uncharacterized, ethylating agent that may be responsible for the 

presence of these adducts (see “Carcinogens in Cigarette 

Smoke” earlier in this chapter).

NNK and NNN are metabolically activated to intermediate agents that pyridyloxobutylate DNA. The resulting POB-DNA adducts can be hydrolyzed with acid to 

yield 4-hydroxy-1-(3-pyridyl)-1-butanone, which can be 

detected by GC–MS. Application of this method demonstrated higher levels of POB-DNA adducts in lung tissue 

of smokers than in that of nonsmokers in a small study 

(Foiles et al. 1991). One study detected 7-(2-hydroxyethyl)

deoxyguanosine in human lung tissue (Zhao et al. 1999), 

and ethylene oxide is the likely source of this adduct. Studies have detected 4-ABP–DNA adducts in human lungs but 

show no clear effect of smoking on adduct levels (Wilson 

et al. 1989; Lin et al. 1994).

Researchers have quantified 1,N6-ethenodeoxyadenosine and 3,N4-ethenodeoxycytidine in human lungs 

by 32P-postlabeling (Godschalk et al. 2002). These adducts 

may result from lipid peroxidation or from metabolic activation of vinyl chloride or ethyl carbamate. No differences 

were reported between smokers and nonsmokers. Studies 

of the oxidative-damage product 8-oxodeoxyguanosine in 

the human lung obtained mixed results regarding a relationship between detection of this product and smoking 

status (Asami et al. 1997; Lee et al. 1999a). 

In summary, data on the quantitation of specific 

DNA adducts in the human lung are limited. However, 

some studies document clear evidence for elevated levels of adducts resulting from exposure to specific carcinogens such as B[a]P, NNK, or NNN. Several methods 

used in these studies—HPLC fluorescence, GC–MS, 

LC–MS, and 32P-postlabeling with modifications for specific 

adducts—have the potential for application to molecular 
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Table 5.2 DNA adducts in human lung tissue
Surgeon General’s Report

244 Chapter 5

epidemiologic studies that relate specific DNA adduct levels to tobacco exposure and cancer risk.

Uncharacterized Adducts in Human Lung Tissue

Studies have extensively applied two main nonspecific methods—32P-postlabeling and immunoassay—to 

analyze DNA adducts in human lung tissue, as well as in 

other tissues. Researchers have discussed the advantages 

and disadvantages of these methods (Kriek et al. 1998; 

Wild and Pisani 1998; Poirier et al. 2000; Phillips 2002). 

Major advantages include high sensitivity for analyzing 

small amounts of DNA, simplicity of analysis, and no need 

for extremely expensive equipment. Disadvantages include 

a lack of chemical specificity, particularly in 32P-postlabeling analyses, and difficulty in quantitation. Studies have 

extensively reviewed the application of these methods to 

tissues obtained from smokers (Phillips 2002; Wiencke 

2002; IARC 2004). 

The output of assays using 32P-postlabeling is 

often a “diagonal radioactive zone” (DRZ), which consists of uncharacterized radioactive components referred 

to in the literature as hydrophobic or aromatic DNA 

adducts. In most cases, little if any evidence supports the 

true chemical characteristics of these adducts. Nevertheless, the intensity of the DRZ is consistently elevated in 

samples from smokers. Immunoassays have used various 

methods of detection, including the fluorescent staining 

of tissue specimens that allows for the location of adducts. 

Cross-reactivity is a common problem of immunoassays. 

For example, antibodies raised against protein conjugates 

of B[a]P–DNA adducts cross-react with adducts generated 

from other PAHs.

Many studies using 32P-postlabeling methods 

examined DNA adduct levels in the peripheral lung, bronchial epithelium, or cells obtained by bronchial lavage of 

smokers. Most of the studies found that adduct levels were 

higher in smokers compared with nonsmokers (Győrffy 

et al. 2004; IARC 2004). Investigations that attempted 

to draw quantitative relationships between the extent 

of smoking and adduct levels had inconsistent results 

(IARC 2004). 

Adducts in Other Tissues

Numerous studies have evaluated DNA adduct 

formation in fetuses and in various tissues and fluids of 

smokers, including samples from the larynx, oral and 

nasal mucosa, bladder, cervix, breast, pancreas, stomach, 

placenta, and cardiovascular system, and samples of sputum, sperm, and blood cells. Researchers have comprehensively reviewed these studies (Phillips 2002; Weincke 

2002; IARC 2004), most of which used 32P-postlabeling 

and immunoassay techniques.

Levels of 7-alkyl-deoxyguanosines determined by 

32P-postlabeling in laryngeal DNA were higher in 

smokers than in nonsmokers (Szyfter et al. 1996), and they 

correlated with the DRZ in these samples. Studies used 

immunoassay also to detect 4-ABP–DNA adducts in laryngeal tissue (Flamini et al. 1998). Other studies examined 

the DRZ by 32P-postlabeling (IARC 2004).

Researchers have detected 1,N2-propanodeoxyguanosine (PdG) adducts derived from acrolein and crotonaldehyde in the DNA of gingival tissue of smokers and 

nonsmokers; adduct levels were higher in smokers (Nath 

et al. 1998). Adducts detected by 32P-postlabeling in oral 

and nasal tissue were also higher in smokers than in nonsmokers. Use of immunoassay techniques revealed that 

levels of BPDE-DNA, 4-ABP–DNA, and malondialdehydeDNA adducts in human oral mucosal cells of smokers were 

higher than those for nonsmokers (IARC 2004).

Using 32P-postlabeling, researchers found 4-ABP–

DNA (C-8 deoxyguanosine) adducts in exfoliated urothelial cells and bladder biopsy samples (IARC 2004). In 

studies using antibodies to 4-ABP–DNA, levels detected 

in biopsy specimens from the bladder of smokers were 

higher than those for nonsmokers (IARC 2004). Studies 

using 32P-postlabeling of bladder DNA from smokers and 

nonsmokers yielded mixed results; some studies showed 

higher adduct levels in smokers (IARC 2004). 

Using GC–MS, Melikian and colleagues (1999) documented that BPDE-DNA adducts were higher in cervical 

epithelial cells of smokers than in those of nonsmokers. An 

immunohistochemical analysis using antibodies to BPDEDNA adduct in human cervical cells also showed higher 

adduct levels in smokers than in nonsmokers (Mancini 

et al. 1999). 32P-postlabeling consistently showed higher 

adduct levels in cervical tissues of smokers than in those 

of nonsmokers (IARC 2004). 

The 32P-postlabeling of DNA from breast tissue 

yields the characteristic DRZ from smokers. Researchers 

also investigated adduct levels by using antibodies against 

BPDE-DNA; results were generally mixed with respect to 

smoking status (IARC 2004). Studies that used 32P-postlabeling to measure adduct levels in pancreatic and stomach tissues reported a correlation with smoking status 

(IARC 2004). 

Some studies indicate the presence of smokingrelated DNA adducts in human placenta, but the overall 

relationship of placental DNA adducts to smoking is weak 

(IARC 2004). Analyses of sperm DNA also reported mixed 

results with respect to smoking status (IARC 2004).

Many studies have examined DNA adducts in blood 

cells (IARC 2004). The common use of blood cells in these 

studies is obviously related to the ease of clinically obtaining these samples. From this viewpoint, blood cell DNA 

is advantageous for biomarker studies. A disadvantage of 
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using blood cells is that adduct levels in blood cells are 

not necessarily directly related to levels of DNA adducts in 

the tissues in which smoking-related cancers occur. The 

collective results of the studies are somewhat inconsistent 

with respect to the effects of smoking on levels of DNA 

adducts. This inconsistency probably results in part from 

competing sources of adduct formation such as diet, occupation, and the general environment. Another factor is the 

lifetime of the blood cells investigated; longer-lived cells 

appear to provide more consistent results with respect to 

smoking (IARC 2004). Studies comparing levels of blood 

cell–DNA adducts in smokers with or without cancer had 

mixed results (IARC 2004). 

A meta-analysis of the relationship of DNA adduct 

levels in smokers to cancer, determined by 32P-postlabeling, used data from case-control studies of lung cancer 

(five studies), oral cancer (one study), and bladder cancer 

(one study). Six studies measured adducts in white blood 

cells, and one study used normal lung tissue. Among current smokers, adduct levels for case patients were significantly higher than those for control participants (Veglia 

et al. 2003).

Protein Adducts as Surrogates for DNA Adducts

Researchers have proposed that levels of carcinogen-Hb adducts and carcinogen-albumin adducts be used 

as surrogates for the measurements of DNA adducts discussed in the preceding section (Osterman-Golkar et al. 

1976; Ehrenberg and Osterman-Golkar 1980). Although 

these proteins are not considered targets for carcinogenesis, all carcinogens that react with DNA are also thought 

to react with protein to some extent. Advantages of Hb 

adducts as surrogates include the ready availability of 

Hb in blood and the long lifetime of the erythrocyte in 

humans (approximately 120 days), which provides an 

opportunity for adducts to accumulate. Other researchers have comprehensively reviewed studies on protein 

adducts in smokers (Phillips 2002; IARC 2004).

The Hb adducts of aromatic amines have emerged 

as highly informative carcinogen biomarkers. Levels of 

these adducts are consistently higher in smokers than in 

nonsmokers, particularly for 3-ABP–Hb and 4-ABP–Hb 

adducts. Adduct levels decrease with smoking cessation and are related to the number of cigarettes smoked 

(Maclure et al. 1990; Skipper and Tannenbaum 1990; 

Castelao et al. 2001). Adducts that form with the amino terminal valine of Hb are also informative. Important examples 

include adducts derived from ethylene oxide, butadiene, 

acrylonitrile, and acrylamide (Bergmark 1997; Fennell 

et al. 2000; Swenberg et al. 2001). Ethylated N-terminal 

valine of Hb is also higher in smokers than in nonsmokers 

(Carmella et al. 2002a). 

Summary

Overwhelming evidence indicates that DNA adduct 

levels are higher in most tissues of smokers than in corresponding tissues of nonsmokers. This observation provides bedrock support for the major pathway of cancer 

induction in smokers that proceeds through DNA adduct 

formation and genetic damage. DNA adducts studied can 

generally be divided into two classes: nonspecific adducts, 

which are detected by 32P-postlabeling and immunoassay, 

and specific adducts, which are detected by structurespecific methods. Studies of nonspecific DNA adducts are 

far more common than studies of specific DNA adducts, 

which are still scarce and are limited mainly to human 

lung tissue. Strong evidence exists for the presence of 

a variety of specific adducts in the human lung, and in 

several cases, adduct levels are higher in smokers than 

in nonsmokers. Measuring levels of Hb adducts by MS 

provides a simple and perhaps more practical approach 

for assessing carcinogen exposure of the cell. In several 

instances, levels of specific adducts are substantially 

higher in smokers than in nonsmokers. Collectively, the 

results of these biomarker studies demonstrate the potential for genetic damage in smokers from the persistence 

of DNA adducts. The propagation of this genetic damage 

during clonal outgrowth is consistent with the accumulation of multiple genetic changes observed in lung cancer progression. 

Molecular Epidemiology of 

Polymorphisms in CarcinogenMetabolizing Genes

Introduction

Genetic polymorphisms may play a role in tobaccorelated neoplasms. Researchers have established cigarette 

smoking as a major cause of lung cancer: more than 85 

percent of lung cancers are attributable to smoking (Ries 

et al. 2004). However, not all smokers develop lung cancer, 

and lung cancer can arise in lifetime nonsmokers. This 

variation in disease has stimulated interest in molecular 

epidemiologic investigations of genetic polymorphisms, 

including carcinogen-metabolizing enzymes that may 

lead to variations in susceptibility to the carcinogens in 

tobacco smoke (Table 5.3). Considerable data exist on 

genetic polymorphisms in cancers other than lung cancer, but the discussion here focuses only on lung cancer 

and bladder cancer, two of the most heavily investigated cancers. 
Surgeon General’s Report

246 Chapter 5

Studies have identified polymorphisms in phase I 

and II enzymes. Phase I enzymes, such as P-450s, generally add an oxygen atom to a carcinogen, and phase II 

enzymes, such as GSTs or UGTs, modify the carcinogen by 

making it highly water soluble for more facile excretion. 

These enzymes are involved in the activation and detoxification of carcinogens and may be associated with a differential ability to process carcinogens. Researchers have 

hypothesized that the accumulation of active carcinogen 

metabolites and hence increased DNA adduct formation 

add to lung cancer risk. Studies of cases with autopsy of 

cancer-free lung tissue indicate that polymorphisms in 

CYP1A1 and GSTM1 genes may be associated with higher 

DNA adduct levels, suggesting that variations in metabolic pathways can play a role in individual response to 

carcinogen exposure (Kato et al. 1995). Numerous studies 

have extended this line of analysis to investigate whether 

this differential ability to metabolize carcinogens leads to 

differential lung cancer risk. Overall, data from the study 

of these polymorphisms have generated inconsistent 

results. These inconsistencies may be explained in part by 

the combination of a small sample size and variable frequencies of the polymorphic alleles within different ethnic 

populations. A summary of some of the specific gene polymorphisms investigated is provided in Table 5.3. A recent 

review summarizes the effects of genetic polymorphisms 

on lung cancer (Schwartz et al. 2007), and specific examples are discussed here.

CYP1A1 Gene

Researchers hypothesize that interindividual variations in the ability to activate carcinogens such as PAH 

through the CYP1A1 gene may lead to differential carcinogenic effects. Studies describe at least two variant polymorphisms in the CYP1A1 gene. The first is a T3801C base 

change in intron 6, which results in a new MSPI restriction site (Kawajiri et al. 1990). (A restriction site is a site in 

the gene that is cleaved by a specific restriction enzyme.) 

The second polymorphism is an A2455G base change in 

exon 7, which results in an Ile to Val amino acid change 

(Hayashi et al. 1991). Although these polymorphisms appear to be linked, study results are inconsistent, and wide 

disparities exist among populations. 

Studies of Japanese and Chinese populations 

associate both of the CYP1A1 variant polymorphisms with 

an increase in lung cancer risk. Nakachi and colleagues 

(1991) were the first to report an association of the *MSPI

polymorphism with lung cancer risk. For patients with 

lung cancer, the frequency of harboring the homozygous 

Table 5.3 Selected gene polymorphisms evaluated by molecular epidemiology investigations for relationship to 

lung cancer through variation in susceptibility to carcinogens in tobacco smoke

Metabolic genes Nucleotide change Amino acid change Enzymatic activity

CYP1A1 T→C (MSPI) NA Increased

CYP1A1 A→G Ile462Val Increased

CYP2E1 T→A (DRAI) NA Increased

CYP2E1 G→C (RSAI) NA Increased

CYP2A13 C→T Arg257Cys Decreased

GSTM1 Deletion NA None

GSTP1 A→G Ile105Val Decreased

GSTT1 Deletion NA None

NAT2 T→C Ile114Thr Decreased

NAT2 C→T Lys161Lys Decreased

NAT2 A→G Lys268Arg Decreased

NAT2 G→A Arg197Gln Decreased

NAT2 C→T Tyr94Tyr Decreased

NAT2 G→A Gly286Glu Decreased

MEH T→C Tyr113His Decreased

MEH A→G His139Arg Increased

Note: NA = not applicable.
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variant genotype was more than two times higher than 

that for control participants. Among patients with squamous cell carcinoma (SCC), the homozygous variant 

genotype was associated with an increased risk of developing lung cancer, especially in those with a lower cumulative dose of cigarette smoke. At low levels of exposure to 

cigarette smoke, the odds ratio (OR) for developing lung 

cancer among persons with the homozygous variant genotype was 7.31 (95 percent confidence interval [CI], 2.13–

25.12). This increased risk was persistent, but of a lesser 

magnitude, at higher levels of exposure to cigarette smoke 

(Nakachi et al. 1991). Okada and colleagues (1994) 

reported similar findings. 

Studies have also associated the ILE462VAL polymorphism of CYP1A1 with lung cancer risk in Japanese 

and Chinese populations. Again, the homozygous variant 

*VAL/*VAL genotype was associated with lung cancer at 

lower cumulative doses of cigarette smoke (Nakachi et al. 

1993; Yang et al. 2004; Ng et al. 2005). One explanation 

posited for this relationship with the dose level in smokers has been that the relevant enzyme is saturated at high 

doses but not at low doses of cigarette smoke (Vineis et 

al. 1997). The effects of genetic variability and differential 

enzymatic activity are more apparent at low doses, when 

saturation has not been reached. 

Results have been inconsistent outside Asian populations. Individual studies often lack statistical power to 

detect an association (Shields and Harris 2000). Also, 

CYP1A1 polymorphisms are common in Asian populations 

(30 percent of the population) (Nakachi et al. 1993), but 

are far less common among Europeans and North Americans (<10 percent of the population) (Warren and Shields 

1997). A study of African Americans and Mexican Americans showed a twofold increase in the risk of lung cancer 

among light smokers with the *MSPI variant genotype 

(Ishibe et al. 1997). However, a Brazilian study showed 

an increase in risk with the *ILE/*VAL polymorphism but 

not with the MSPI polymorphism (Hamada et al. 1995). A 

more recent study suggested that in Latinos, the *MSPI

variant genotype was associated with an overall inverse 

OR of 0.51 (95 percent CI, 0.32–0.81), which reflected the 

inverse interaction with smoking (Wrensch et al. 2005). 

Reports from Finland, Norway, and Sweden show a lack of 

association between either of the CYP1A1 polymorphisms 

and lung cancer risk (Tefre et al. 1991; Hirvonen et al. 

1992; Alexandrie et al. 2004). A meta-analysis provides 

little support for this association (Houlston 2000).

Because of the small sample sizes in these studies, 

Vineis and colleagues (2003) conducted an analysis of 

pooled data from the International Collaborative Study 

on Genetic Susceptibility to Environmental Carcinogens, 

which included raw data from 22 case-control studies 

totaling 2,451 cases and 3,358 controls. This data set thus 

comprised approximately one-half of the case-control 

studies published at that time. Researchers found an 

association in Whites between the CYP1A1 homozygous 

*MSPI variant and lung cancer risk after adjustment 

of values for age and gender (OR = 2.36; 95 percent CI, 

1.16–4.81). The association held for both SCC and adenocarcinomas (Vineis et al. 2003). However, this association 

failed to reach statistical significance among Asians in 

this analysis. Moreover, studies such as the research conducted by Nakachi and colleagues (1991, 1993) discussed 

previously in this section were not included, making the 

Asian data difficult to interpret.

CYP2E1 Gene

The CYP2E1 gene is involved in the metabolic 

activation of NDMA, as well as several other tobacco 

smoke carcinogens. Le Marchand and colleagues (1998) 

performed a population-based, case-control study with 

341 lung cancer cases and 456 controls. These researchers 

found that CYP2E1 polymorphisms were associated with a 

decrease in risk of lung adenocarcinoma. A Chinese study 

(Wang et al. 2003c) confirmed this finding. However, the 

presence of at least one variant CYP1A1 *MSPI allele was 

associated with an increased risk of SCC, both alone (2.4-

fold increase in risk) and in combination with GSTM1 deletion (3.1-fold increase in risk) (Le Marchand et al. 1998). 

These researchers suggest that the associations between 

CYP1A1 and CYP2E1 polymorphisms and subsets of lung 

cancer indicate a specificity of PAHs to induce SCC and of 

nitrosamines to induce adenocarcinomas. 

CYP2A13 Gene

The CYP2A13 gene is expressed primarily in the 

respiratory tract and participates in the metabolic activation of N-nitrosamines such as NNK. Researchers have 

identified a polymorphism in CYP2A13 in which a C→T 

transition leads to an Arg→Cys substitution at position 

257. The variant 257CYS protein, the product of this gene, 

has one-half to one-third the capacity of the 257ARG protein to activate NNK (Su et al. 2000; Zhang et al. 2002). In 

a study of 724 lung cancer patients and 791 control participants, Wang and colleagues (2003a) demonstrated that 

the variant CYP2A13 genotype (*C/*T or *T/*T) was associated with a reduced risk for lung cancer, particularly for 

adenocarcinomas (OR = 0.41; 95 percent CI, 0.23–0.71). 

The reduction in risk did not reach statistical significance 

for SCC or other histologies of lung cancer. The reduced 

risk for adenocarcinomas was apparent only in smokers, 

and in light smokers rather than in heavy smokers (Wang 

et al. 2003a). This finding again indicates that genetic 

polymorphisms may play a greater role when the carcinogen dose is low and does not saturate enzymatic capacity.
Surgeon General’s Report

248 Chapter 5

GSTM1 Gene

Study reports have noted large variations in enzymatic activity for several GSTs. About 50 percent of the 

White population is homozygous for a deletion in the 

GSTM1 gene that leads to null expression (Seidegard et 

al. 1988). The GSTM1 enzyme is important in detoxifying carcinogens, and numerous studies have investigated 

the possible association of the GSTM1 null genotype with 

lung cancer risk. 

Some studies have found an association between 

the GSTM1 null mutation and lung cancer across many 

populations. In a Japanese population, the GSTM1 null 

genotype was positively correlated with SCC of the lung 

but not with adenocarcinomas (Kihara et al. 1993). A similar analysis in a Finnish population also correlated the 

GSTM1 null genotype with SCC (Hirvonen et al. 1993). 

Analyses of Scottish (Zhong et al. 1991), Norwegian 

(Ryberg et al. 1997), and Turkish populations (Pinarbasi et 

al. 2003) had similar findings. A U.S. study also suggested 

that the GSTM1 null genotype was associated with a modest elevation in lung cancer risk, which increased among 

heavy smokers (Nazar-Stewart et al. 2003). However, some 

studies have not shown a significant association between 

the GSTM1 null genotype and lung cancer risk for SCC 

or overall for lung cancer (London et al. 1995; Rebbeck 

1997). A meta-analysis of data from 12 case-control studies comprising 1,593 cases and 2,135 controls showed a 

moderate increase in the risk of lung cancer across all 

histologies with the GSTM1 null genotype (OR = 1.41; 95 

percent CI, 1.23–1.61) (McWilliams et al. 1995). A more 

recent meta-analysis of 43 studies including more than 

18,000 persons showed a smaller but statistically significant OR of 1.17 (95 percent CI, 1.07–1.27) (Benhamou et 

al. 2002). 

Kihara and colleagues (1994) analyzed data on 178 

Japanese patients with lung cancer and 201 healthy control participants and found that the GSTM1 null genotype 

was associated with an overall increase in lung cancer risk 

(OR = 1.87; 95 percent CI, 1.21–2.87). The strongest association was for SCC (OR = 2.13; 95 percent CI, 1.11–4.07). 

With stratification by the amount of smoking, the proportion of GSTM1 null genotype increased progressively in 

the SCC group from 50 percent in light smokers to 72 

percent in heavy smokers (Kihara et al. 1994). One study 

suggested that higher intakes of cruciferous vegetables 

reduced lung cancer risk among persons with the GSTM1 

genotype (highest versus lowest tertile for amount of 

smoking; OR = 0.61; 95 percent CI, 0.39–0.95) but not 

among persons with the GSTM1 null genotype (highest 

versus lowest tertile; OR = 1.15; 95 percent CI, 0.78–1.68) 

(Wang et al. 2004b). However, several other studies have 

shown a greater protective effect in persons with the 

GSTM1 null genotype who consumed cruciferous vegetables (London et al. 2000; Spitz et al. 2000). One hypothesis is that these participants were less able to eliminate 

protective isothiocyanates by conjugation with glutathione. In a case-control study, Cheng and colleagues (1999) 

analyzed data from 162 patients with SCC of the head and 

neck and 315 healthy control participants. They found 

that 53.1 percent of the case patients and 42.9 percent of 

the control participants were null for GSTM1 (p <0.05), 

whereas 32.7 percent of case patients and 17.5 percent of 

control participants were null for GSTT1 (p <0.001).

Thus, the effect of GSTM1 alone may not be dramatic. However, it appears to be magnified by geneenvironment and gene-diet interactions, and the effects 

were significantly greater as exposure to cigarette smoke 

increased. In addition, the high frequency of GSTM1 polymorphisms observed across all ethnicities may contribute 

to the importance of this variant as a risk factor for developing lung cancer (Brennan et al. 2005). 

CYP1A1 and GSTM1 in Combination

Studies of the effect of combined CYP1A1 and GSTM1

variant genotypes hypothesized that increased PAH activation and decreased PAH detoxification in tobacco smokers 

might lead to an increase in lung cancer risk. Numerous 

studies have explored this association. Perhaps the studies with the strongest support for this association come 

from Japan, although they are generally limited by small 

sample sizes. 

Combination of the CYP1A1 variant genotype and 

the GSTM1 null genotype enhanced the risk of smokingrelated lung cancers in a Japanese population. Hayashi 

and colleagues (1992) demonstrated this finding with the 

*ILE/*VAL polymorphism. These investigators found an 

increased frequency of the homozygous *VAL/*VAL genotype combined with the GSTM1 null genotype in lung 

cancer patients compared with control participants (8.5 

percent versus 2.2 percent, respectively). Nakachi and 

colleagues (1991) reported similar results with both the 

*MSPI and *ILE/*VAL polymorphisms and the GSTM1

null genotype. The case-control study found that for light 

smokers, either of the two CYP1A1 susceptible genotypes 

combined synergistically with the deficient GSTM1 genotype to create a high risk for lung cancer (OR = 16; 95 

percent CI, 3.76–68.02 for *MSPI, and OR = 41; 95 percent 

CI, 8.68–193.61 for *ILE/*VAL). Eighty-seven percent 

of the light smokers who developed lung cancer had at 

least one of the three homozygous variant genotypes. The 

investigators suggested that particularly when the cigarette dose is low, CYP1A1 and GSTM1 may be an important determinant of susceptibility to lung cancer (Nakachi 

et al. 1991). 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Kihara and colleagues (1994) also demonstrated a 

synergistic effect. Persons with these variant genotypes 

in both CYP1A1 and GSTM1 had a much higher risk of 

lung cancer than did those with the variant CYP1A1 and 

wild-type GSTM1 (OR = 21.9; 95 percent CI, 4.68–112.7 

versus OR = 3.2; 95 percent CI, 0.37–24.0). Studies in 

Scandinavian populations (Alexandrie et al. 1994; Anttila 

et al. 1994), as well as U.S. populations (García-Closas et 

al. 1997), support an increase in the risk of lung cancer 

with the combination of variant CYP1A1 and GSTM1 genotypes. Using data from the International Collaborative 

Study on Genetic Susceptibility to Environmental Carcinogens database, Vineis and colleagues (2004) found a 

statistically significant effect of the *MSPI variant on lung 

cancer risk in Whites (OR = 2.6; 95 percent CI, 1.2–5.7) 

with evidence for an interaction between the MSPI and 

GSTM1 null genotypes (OR = 2.8; 95 percent CI, 0.9–8.4).

GSTP1 Gene

Studies have reported polymorphisms in the GSTP1

gene family of phase II enzymes with high expression in 

the lung. One GSTP1 polymorphism includes an A→G 

base change that leads to an isoleucine→valine substitution, which results in lower enzymatic activity toward 

1-chloro-2,4-dinitrobenzene (Watson et al. 1998) but 

higher activity toward PAH diol epoxides (Sundberg et al. 

1998). Several studies showed no statistically significant 

association between GSTP1 polymorphisms and lung cancer risk (Harris et al. 1998; Katoh et al. 1999; To-Figueras 

et al. 1999; Nazar-Stewart et al. 2003). However, in the 

study with the largest sample size of 1,042 cases and 1,161 

controls, the GSTP1 homozygous variant genotype was 

associated with a higher lung cancer risk at any level of 

exposure to smoke than was the wild-type genotype (Miller 

et al. 2003). 

The combination of the GSTM1 null genotype and 

the GSTP1 *G/*G genotype may increase lung cancer 

risk (Ryberg et al. 1997; Kihara et al. 1999; Perera et al. 

2002). In a study of 1,694 cases and 1,694 controls, double 

variants in GSTM1 and GSTP1, as well as in GSTP1 and 

TP53, were associated with an increase in lung cancer 

risk among persons aged 55 years or younger (adjusted 

OR [AOR] = 4.03; 95 percent CI, 1.47–11.1 for the M1-

P1 double variant, and AOR = 5.10; 95 percent CI, 1.42–

18.30 for the P1-P53 double variant) (Miller et al. 2002). 

Another study included 350 persons younger than age 50 

years with a diagnosis of lung cancer who were identified 

from the metropolitan Detroit Surveillance, Epidemiology, and End Results program. The study compared these 

patients with 410 control participants matched by age, 

race, and gender. The results indicated that African Americans carrying at least one *G allele at the GSTP1 locus 

were 2.9 times more likely to develop lung cancer than 

were African Americans without a *G allele (95 percent 

CI, 1.29–6.20). African Americans with either one or two 

genotypes that carry risk at the GSTM1 and GSTP1 loci 

were at higher risk of developing lung cancer than were 

African Americans who had fully functional GSTM1 and 

GSTP1 genes (OR = 2.8; 95 percent CI, 1.1–7.2 for GSTM1,

and OR = 4.0; 95 percent CI, 1.3–12.2 for GSTP1). No significant single-gene associations were observed between 

GSTM1, GSTT1, or GSTP1 and early-onset lung cancer in 

Whites (Cote et al. 2005). 

GSTT1 Gene

Previous results have not supported an association 

of the GSTT1 gene with lung cancer risk (To-Figueras et 

al. 1997; Malats et al. 2000; Stücker et al. 2002; RuanoRavina et al. 2003; Wang et al. 2003b). In a study of Chinese living in Hong Kong, the GSTT1 null genotype was 

associated with a higher risk of lung cancer than was the 

functional GSTT1 genotype (AOR = 1.69; 95 percent CI, 

1.12–2.56) only in nonsmokers (Chan-Yeung et al. 2004). 

A study from Denmark also suggested that the GSTT1 null 

genotype is associated with a higher risk of lung cancer 

(Sørensen et al. 2004a). 

NAT2 Gene

Several widely studied polymorphisms for the NAT2

gene are associated with decreased activity or reduced 

stability of the enzyme. Phenotypically, these polymorphisms result in slow or fast acetylation. Study results on 

the association of the NAT2 gene with lung cancer risk 

are conflicting. Most studies report no overall increase 

in risk with the genotype for either slow or fast acetylation (Philip et al. 1988; Martinez et al. 1995; Bouchardy 

et al. 1998; Saarikoski et al. 2000). However, a few studies 

report an increase in risk with the genotype for either slow 

acetylation (Oyama et al. 1997; Seow et al. 1999) or fast 

acetylation (Cascorbi et al. 1996). In the largest study, of 

1,115 lung cancer patients and 1,250 control participants, 

no association between the NAT2 genotype and lung cancer risk was observed. However, the study noted a significant interaction with smoking. Among nonsmokers, the 

genotype for rapid acetylation decreased lung cancer risk 

more than did the genotype for slow acetylation. This 

relationship was reversed among smokers, and persons with 

the genotype for rapid acetylation had a higher risk. The 

authors hypothesized that for nonsmokers, the NAT2 protein may provide a means for N-acetylation, thereby detoxifying aromatic amines and protecting a person against 

cancer. However, cigarette smoke markedly induces CYP 

oxidation and could increase the production of reactive 
Surgeon General’s Report

250 Chapter 5

intermediate agents in smokers. In this setting, NAT2 may 

instead O-acetylate these metabolites and thereby produce 

more reactive metabolites, thus augmenting the cancer 

risk (Zhou et al. 2002b). A study from Denmark confirmed 

the associations of the NAT2 gene with smoking status 

(Sørensen et al. 2005). However, a study from Taiwan 

suggested that the NAT2 genotype for fast acetylation is 

associated with an increased risk of lung cancer among 

women who were lifetime nonsmokers (Chiou et al. 2005). 

The NAT2 protein plays an important role in the bioactivation and detoxification of the aromatic amines associated with bladder cancer induced by cigarette smoke. In 

the phenotypic studies, persons with slow acetylation had 

increased risk of bladder cancer, particularly when they 

had occupational exposure to arylamines or were cigarette 

smokers (Green et al. 2000; Johns and Houlston 2000). In 

the genotype analysis, more than 20 independent studies, 

many with small sample size have assessed the association 

of NAT2 polymorphisms with the risk of bladder cancer. A 

meta-analysis of published case-controlstudies conducted 

in the general population (22 studies, 2,496 cases, and 

3,340 controls) examined the relationship of acetylation 

status (phenotype and genotype) to bladder cancer risk. 

Persons with slow acetylation had a 40-percent increase in 

risk compared with risk for persons with rapid acetylation 

(OR = 1.4; 95 percent CI, 1.2–1.6) (Marcus et al. 2000b). 

However, studies conducted in Asia generated a summary 

OR of 2.1 (95 percent CI, 1.2–3.8), studies in Europe generated a summary OR of 1.4 (95 percent CI, 1.2–1.6), and 

studies in the United States generated a summary OR of 

0.9 (95 percent CI, 0.7–1.3). 

In addition, a case series meta-analysis of data from 

a case series of 16 studies of bladder cancer, conducted in 

the general population and involving 1,999 cases, showed 

a weak interaction between smoking status and NAT2 slow 

acetylation (OR = 1.3; 95 percent CI, 1.0–1.6). The interaction was stronger when analyses were restricted to studies 

conducted in Europe (OR = 1.5; 95 percent CI, 1.1–1.9) 

(Marcus et al. 2000a). In a pooled analysis of data from 

1,530 cases and 731 controls from four case-control studies plus two case series conducted in Whites in European 

countries, a significant association was reported between 

NAT2 slow acetylation and bladder cancer (OR = 1.42; 95 

percent CI, 1.14–1.77) (Vineis et al. 2001). The risk of cancer was elevated in smokers and in persons with occupational exposure to cigarette smoke, and the highest risk 

was for persons with slow acetylation (Vineis et al. 2001).

In a hospital-based, case-control study of 201 men 

in northern Italy and a case-control study with 507 White 

patients with bladder cancer in the United States, findings 

also suggested that the NAT2 genotype for slow acetylation was associated with an increased risk of bladder cancer, especially with the joint effects of cigarette smoking 

and occupational exposure to aromatic amines (Hung et 

al. 2004; Gu et al. 2005). In a case-control study of bladder cancer in females, exclusive use of permanent hair 

dye was associated with a 2.9-fold increased risk of bladder cancer among persons with the NAT2 genotype and 

slow acetylation but not in those with the NAT2 genotype 

and rapid acetylation (Gago-Dominguez et al. 2003). All 

of these results confirmed that the genotype for NAT2

slow acetylation is a risk factor for bladder cancer through 

interaction with smoking or occupational exposure. However, several studies that included populations of Chinese 

(Ma et al. 2004), northern Indians (Mittal et al. 2004), and 

Poles (Jaskula-Sztul et al. 2001) reported no association 

between the NAT2 genotype and bladder cancer risk.

Microsomal Epoxide Hydrolase

Like NAT2, MEH can act as both an activator and a 

detoxifier of carcinogens. As a detoxifier, MEH catalyzes the 

hydrolysis of highly reactive epoxide intermediate agents 

to less reactive dihydrodiols that are excretable. As an 

activator, MEH is involved in further metabolism of PAH 

epoxides. Several identified polymorphisms include a T→C 

base change in exon 3 leading to a tyrosine→histidine 

substitution at residue 113, which is associated with a 

decrease in enzymatic activity, and an A→G base change 

in exon 4, leading to a histidine→arginine substitution 

at residue 139, which leads to an increase in enzymatic 

activity (Hassett et al. 1994). Several reports of studies 

have noted an increased risk of lung cancer among persons 

carrying polymorphisms associated with an increase in 

enzymatic activity. A study of Mexican Americans and African Americans found a greater risk of lung cancer among 

young Mexican Americans with the exon 4 polymorphism, 

but not among those with the exon 3 polymorphism. No 

association was observed among African Americans (Wu 

et al. 2001). The homozygous variant genotype at exon 4 

confers increased enzymatic activity and was again associated with an increase in lung cancer risk in a study in 

Texas (Cajas-Salazar et al. 2003). A study from Austria suggested an association between the exon 3 polymorphism 

of the MEH gene and a significantly decreased risk of lung 

cancer (Gsur et al. 2003). The combination of exon 3 and 

exon 4 polymorphisms that conferred high enzymatic 

activity also significantly increased the risk (Cajas-Salazar 

et al. 2003; Park et al. 2005). In a Chinese population in 

Taiwan, high MEH activity, defined by the corresponding 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

combination of exon 3 and exon 4 polymorphisms, was 

associated with an increased risk for SCC (Lin et al. 2000). 

In a French population, high MEH activity was similarly 

associated with lung cancer risk (Benhamou et al. 1998). 

A study of 974 White patients with lung cancer and 

1,142 control participants found no relationship between 

MEH polymorphisms and lung cancer risk overall. However, evidence of gene-environment interactions was 

observed. Low-activity MEH genotypes were a risk factor 

for lung cancer among nonsmokers (OR = 1.89; 95 percent 

CI, 1.08–3.28) but were protective among heavy smokers 

(OR = 0.65; 95 percent CI, 0.42–1.00) (Zhou et al. 2001b). 

This effect was stronger in SCC than in adenocarcinoma. 

The researchers hypothesized that this difference may be 

explained by the dual actions of MEH. In nonsmokers, 

the presence of low MEH activity may lead to a decreased 

ability to detoxify environmental pollutants, thus increasing lung cancer risk. In smokers, MEH may participate in 

activating the PAHs in cigarette smoke. Therefore, low 

activity is protective for heavy smokers. Similar results 

were reported in a Slovak study (Habalová et al. 2004).

In a meta-analysis of data from seven published 

studies that included 2,078 case patients with lung cancer and 3,081 control participants, investigators found 

no consistent overall association for either the exon 3 or 

exon 4 polymorphisms with lung cancer risk (Lee et al. 

2002c). However, in an analysis of pooled data from eight 

studies (four published and four unpublished at that time) 

with 986 case patients and 1,633 control participants, 

researchers observed a significant decrease in lung cancer 

risk (OR = 0.70; 95 percent CI, 0.51–0.96) for the exon 3 

*HIS/*HIS genotype. The protective effect of the exon 3 

polymorphism seems stronger for adenocarcinomas of the 

lung than for other histologic types. Researchers found no 

overall association between MEH activity and lung cancer 

risk and no consistent modification of the carcinogenic 

effect of smoking according to the MEH polymorphism. 

However, the risk of lung cancer decreased among lifetime 

nonsmokers with high MEH activity and among heavy 

smokers with the exon 3 *HIS/*HIS genotype (Lee et 

al. 2002c).

Genes in the Pathway for Metabolism 

of Reactive Oxygen Species

Studies have identified an alanine→valine substitution at codon 16 of manganese superoxide dismutase 

(SOD), which may be associated with a less efficient 

enzyme transport into mitochondria. The *VAL/*VAL genotype is associated with risk of lung cancer higher than 

that for the wild-type genotype (AOR = 1.67; 95 percent 

CI, 1.27–2.20) (Wang et al. 2001a). Other studies also associate the heterozygous variant genotype with an increased 

risk of lung cancer (AOR = 1.34; 95 percent CI, 1.05–1.70) 

(Wang et al. 2001a, 2004c). Studies have identified a G→A 

polymorphism in the promoter region of myeloperoxidase 

(MPO) that decreases *A allele transcription. A study of 

bronchoalveolar lavage fluid and cells from 106 White 

smokers who had lung cancer showed an association of 

the variant genotypes with reduced MPO activity in the 

fluid and reduced levels of smoking-related DNA adducts 

in bronchoalveolar cells (Van Schooten et al. 2004). The 

association was stronger in persons having two variant 

alleles (homozygous variants) than it was in persons 

having one normal and one variant allele (heterozygous variants).

Findings on lung cancer risk are conflicting. Most 

studies performed since 1999 suggested that the variant 

MPO genotypes are associated with a decreased risk of 

lung cancer (Le Marchand et al. 2000; Dally et al. 2002; 

Feyler et al. 2002; Kantarci et al. 2002; Lu et al. 2002; 

Schabath et al. 2002). In contrast, two studies found no 

association between either the heterozygous or homozygous variant genotypes and lung cancer risk (Xu et al. 

2002; Chevrier et al. 2003). Another study suggested that 

the MPO-G463A polymorphism associated with a novel 

estrogen-receptor-binding site modifies the association 

between the SOD ALA16VAL polymorphism and risk of 

non-small-cell lung cancer (NSCLC) differently by gender. 

For women carrying MPO variant genotypes, the AOR of 

the SOD polymorphism (*VAL/*VAL versus *ALA/*ALA) 

was 3.26 (95 percent CI, 1.55–6.83). No associations were 

found in men or women who carried the MPO *G/*G wildtype genotype (Liu et al. 2004). 

Summary

Studies to date suggest a role for genetic polymorphisms in the risk of lung and bladder cancer in smokers 

and support a possible association between specific genes 

and smoking status. Investigations continue on the role 

of multiple genetic variants that occur simultaneously 

and the interactions between metabolic gene variants and 

other kinds of heritable variations, such as DNA repair, 

cell-cycle control, tumor-suppressor genes, and oncogene activity. 
Surgeon General’s Report

252 Chapter 5

DNA Repair and Conversion of Adducts to Mutations

Repair of DNA Adducts

Introduction

Tobacco products and smoke contain many chemicals that can damage DNA. Multiple repair pathways 

protect a human cell against the mutagenic and carcinogenic activities of these DNA-damaging agents. Pathways 

involved in the repair of tobacco-related DNA damage 

include direct base repair by alkyltransferases, excision of 

DNA damage by base excision repair (BER), or nucleotide 

excision repair (NER), mismatch repair (MMR), and double-strand break repair (DSBR). The inadequate removal 

of DNA damage results in increased rates of mutagenesis 

and, as a consequence, the increased likelihood of a person 

developing cancer.

O6-Alkylguanine–DNA Alkyltransferase

Overview

O6-alkylguanine adducts are repaired by the repair 

protein O6-alkylguanine–DNA alkyltransferase (AGT) in 

a reaction involving transfer of the methyl group from 

the O6 position of guanine to a cysteinyl residue on the 

protein (Pegg 2000). This transfer reaction results in an 

error-proof repair as it regenerates an unmodified guanine residue in DNA. However, the repair protein is inactivated as the alkylated protein undergoes a conformational 

change (Daniels et al. 2000) and is degraded (Srivenugopal et al. 1996; Xu-Welliver and Pegg 2002). As a consequence of this repair mechanism, the constitutive levels 

of AGT determine the initial repair capacity of a cell by 

this mechanism. Overall capacity of the O6-alkylguanine 

repair is determined by the rate of protein synthesis and 

the amount of alkylation at the O6 position of guanine. 

Substrate Specificity

Mammalian AGT specifically repairs O6-alkylguanine adducts, and it repairs the larger O6-alkylguanine 

residues more readily than does the bacterial protein. In 

rodents, AGT repairs O6-methylguanine, O6-butylguanine, 

and O6-[4-oxo-4-(3-pyridyl)butyl]guanine at comparable 

rates, whereas human AGT repairs the bulky adducts more 

slowly (Mijal et al. 2004). This ability of the rodent protein 

to accommodate such large structural differences likely 

results from the additional amino acid residue (Gly166) 

in the binding pocket of the rodent proteins (Loktionova 

and Pegg 2002). Therefore, the steric constraints of an 

active AGT site determine whether it can efficiently repair 

a bulky O6-alkylguanine adduct such as those more commonly resulting from exposure to smoke.

Protecting Against Mutagenicity of Tobacco 

Carcinogens

Tobacco smoke contains a number of alkylating 

agents, such as tobacco-specific nitrosamines, which are 

capable of forming O6-alkylguanine adducts (Wang et al. 

1997; Hecht 1998). AGT protects against the mutagenic 

and carcinogenic properties of alkylating agents.

In vitro studies. Increased expression of AGT protects against the mutagenic effects of O6-alkylguanine 

(Ellison et al. 1989) and alkylating agents (Kaina et al. 

1991; Wu et al. 1992; Ferrezuelo et al. 1998a,b). Consistently, alkylating agents are more toxic and mutagenic 

when coadministered with AGT inactivators such as 

O6-benzylguanine or related compounds (Dolan et al. 

1990, 1991; Bronstein et al. 1992). The mutagenic activity of O6-methylguanine or O6-[4-oxo-4-(3-pyridyl)butyl]guanine is enhanced when cells are pretreated with 

O6-benzylguanine (Pauly et al. 1995, 2002). This finding 

indicated that AGT is important in protecting against 

the mutagenic activity of these adducts derived from 

tobacco constituents.

In vivo studies. AGT is depleted in tissues from 

NNK-treated rats, and AGT levels are depleted in Clara 

cells (Belinsky et al. 1988). NNK also reduces AGT levels 

in the lungs and liver of A/J mice (Peterson et al. 2001). 

Although the liver function recovers to control values 

within 96 hours after exposure, AGT activity remains 

depressed in the lung. Consistently, O6-methylguanine is 

efficiently repaired in the liver of NNK-treated mice, but 

it persists for at least two weeks in lung DNA (Peterson 

and Hecht 1991; Peterson et al. 2001). Notably, levels of 

O6-methylguanine in lung DNA are highly correlated with 

pulmonary tumorigenic activity in A/J mice (Peterson 

and Hecht 1991; Peterson et al. 2001). These observations 

strongly suggest that the inefficient repair of O6-methylguanine, presumably by AGT, is linked to the tumorigenic activity of NNK. This conclusion is supported by the 

observation from another study that high AGT levels protect against NNK-induced lung tumorigenesis and that 

NNK is a less potent lung carcinogen in transgenic mice 

containing the human AGT transgene (Liu et al. 1999).
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Base Excision Repair

Overview

BER is a major pathway for the repair of small DNA 

damage, primarily to alkylated and oxidized DNA bases, as 

well as the repair of apurinic/apyrimidinic (AP) sites and 

single-stranded breaks (Fortini et al. 2003; Fromme et al. 

2004). BER is initiated by a recognition of the damaged 

DNA by specific DNA glycosylases. Studies have characterized 12 human glycosylases (Table 5.4) (Christmann et 

al. 2003; Fortini et al. 2003). Each enzyme has different 

but sometimes overlapping substrate specificities that are 

subgrouped into type I and type II glycosylases, depending 

on their mode of action (Christmann et al. 2003). Type 

I glycosylases catalyze the cleavage of the N-glycosidic 

bond, leaving an AP site. Type II glycosylases remove 

the damaged base in a similar manner. They contain 3’-

endonuclease activity that cleaves the AP site, which generates a single-strand break with a 3’-terminal deoxyribose 

phosphate. Spontaneous hydrolysis of a glycosidic bond 

can also directly generate AP sites. AP sites are substrates 

for DNA AP endonuclease, which cuts the phosphodiester 

Table 5.4 Human DNA glycosylases

Study Glycosylase Specificity Subgroup

Chakravarti et al. 1991 

O’Connor and Laval 1991 

Samson et al. 1991

Alkylpurine DNA glycosylase 

or methylpurine DNA 

glycosylase 

3-methyladenine, 7-methylguanine, 

3-methylguanine, ethenoadenine, 

hypoxanthine

Type I

Hendrich and Bird 1998 

Hendrich et al. 1999

Methyl-CpG binding endonuclease 1 U or T opposite G, preferentially in 

CpG sites

Type I

Slupska et al. 1996, 1999

Fortini et al. 2003

Adenine DNA glycosylase A opposite 8-oxoguanine Type I

Hazra et al. 2002a,b Nei-like DNA glycosylase 1 Formamidopyrimidines, oxidized 

pyrimidines, 8-oxoguanine opposite C, 

G, or T

Type II

Hazra et al. 2002a,b Nei-like DNA glycosylase 2 5-hydroxyuracil, 5-hydroxycytosine Type II

Takao et al. 2002 Nei-like DNA glycosylase 3 Fragmented and oxidized pyrimidines NR

Aspinwall et al. 1997 

Hilbert et al. 1997 

Miyabe et al. 2002 

Fortini et al. 2003

Thymine glycol DNA glycosylase 1 Ring-saturated, oxidized, and 

fragmented pyrimidines

Type II

Bjørås et al. 1997 

Radicella et al. 1997 

Rosenquist et al. 1997 

Fortini et al. 2003

8-oxoguanine DNA glycosylase 1 8-oxoguanine opposite C, T, or G Type II

Hazra et al. 1998 8-oxoguanine DNA glycosylase 2 8-oxoguanine opposite A or G NR

Haushalter et al. 1999 

Nilsen et al. 2001

Mismatch-specific uracil DNA

glycosylase 1

Uracil opposite G Type I

Neddermann and Jiricny 

1993, 1994 

Neddermann et al. 1996

Thymidine DNA glycosylase Uracil, T, or ethenoC opposite G; 

T opposite G, C, or T

Type I

Olsen et al. 1989

Muller and Caradonna 1991 

Fortini et al. 2003

Uracil DNA glycosylase Uracil Type I

Source: Adapted from Christmann et al. 2003 with permission from Elsevier, © 2003. 

Note: NR = data not reported.
Surgeon General’s Report

254 Chapter 5

bond and causes the formation of a strand break with a 

5’-terminal deoxyribose phosphate (Barzilay et al. 1995). 

Once the phosphodiester bond is cleaved, BER can 

proceed through two pathways: short-patch or long-patch 

(Figure 5.4). The balance of the two pathways can depend 

on tissue type (Sancar et al. 2004). In general, short-patch 

BER dominates when BER is initiated by glycosylases. 

Long-patch BER is the preferred pathway when BER is 

initiated with the formation of AP sites through spontaneous hydrolysis or oxidative base loss (Sancar et al. 2004). 

In short-patch BER, DNA polymerase β (polβ) 

inserts a new nucleotide at the lesion site and catalyzes 

the release of 5’-terminal deoxyribose phosphates by 

β-elimination (Matsumoto and Kim 1995; Sobol et al. 

1996; Prasad et al. 1998). This step is followed by ligation 

of the remaining break by the ligase III x-ray repair crosscomplementation group 1 (XRCC1) complex (Kubota et 

al. 1996). 

Long-patch BER occurs in oxidized or reduced AP 

sites, 3’-unsaturated aldehydes, or 3’-phosphates, because 

these modifications are resistant to β-elimination by polβ. 

Therefore, this damage is further processed by long-patch 

repair dependent on the proliferating cell nuclear antigen 

(PCNA) after the insertion of a nucleotide at the lesion 

site by polβ (Christmann et al. 2003; Fortini et al. 2003). 

This mechanism displaces the damaged strand, which is 

followed by DNA synthesis of an oligonucleotide (up to 

10 nucleotides) by pold or pole in concert with PCNA and 

replication factor C (Stucki et al. 1998). The flap endonuclease 1 (FEN1) recognizes and cleaves off the damaged 

oligonucleotide flap structure (Klungland and Lindahl 

1997). Ligase I catalyzes the final ligation step (Prasad et 

al. 1996; Srivastava et al. 1998).

Substrate Specificity

Tobacco smoke is rich in reactive oxygen species 

that can oxidize DNA bases. BER is an important pathway 

for the repair of oxidized DNA bases, such as 8-oxoguanine and oxidized pyrimidines, and for the repair of singlestrand breaks. Tobacco smoke contains N-nitrosamines 

capable of generating small alkylguanine damage that is 

repaired by this pathway. The small chemical alterations 

frequently miscode if they are not repaired by BER. Therefore, this pathway is particularly important in preventing 

mutagenesis.

Protecting Against Mutagenicity and 

Carcinogenicity of Tobacco Carcinogens

Single-gene knockouts of glycosylases in mice 

are well tolerated, with only modest increases in rates 

of spontaneous mutagenesis (Fortini et al. 2003). This 

observation likely results from an overlapping specificity 

of the various glycosylases and repair pathways. However, 

mutagenicity of methyl methanesulfonate (MMS) in lymphocytes from alkylpurine-DNA-N-glycosylase–null mice

was three to four times higher than that in lymphocytes 

from wild-type control mice (Elder et al. 1998). Most of 

the mutations were AT→TA transversions. In addition, 

8-oxoguanine DNA glycosylase 1 (OGG1) knockout mice 

that are aging eventually develop lung cancer (Sakumi 

et al. 2003). However, in another study, knockout of proteins involved in the steps after removal of the base caused 

the knockout mice to die at a very young age (Fortini et 

al. 2003).

Imbalances in the proteins involved in this pathway 

could have negative consequences. Chinese hamster ovary 

cells that overexpress alkylpurine DNA glycosylase are 

more sensitive to both the toxic and mutagenic effects of 

MMS and have higher numbers of mutations at AT base 

pairs than do normal Chinese hamster ovary cells (Calléja et al. 1999). This result suggests that an enhanced 

repair of 3-methyladenine leads to an accumulation of 

unprocessed AP sites that are also mutagenic. Findings 

in another study indicate that imbalances and/or polymorphisms in the proteins involved in BER may cause an 

increase in cancer susceptibility (Fortini et al. 2003).

Nucleotide Excision Repair

Overview

NER repairs a wide class of helix-distorting lesions 

that interfere with base pairing, blocking transcription 

and normal replication (Petit and Sancar 1999; Sancar et 

al. 2004). NER is the primary repair mechanism for bulky 

DNA damage caused by chemicals or ultraviolet (UV) 

radiation or as a result of protein-DNA cross-links (Sancar 

et al. 2004). Two NER pathways exist (Figure 5.5): global 

genomic NER (GGR), which surveys the whole genome 

for DNA damage, and transcription-coupled repair (TCR), 

which primarily repairs damage that interferes with transcription. Both pathways involve recognition of DNA damage and excision of the damaged DNA, followed by the 

synthesis and ligation of new DNA.

Global genomic nucleotide excision repair. 

Researchers think that GGR is largely transcription independent, occurring throughout the genome because no 

gene or strand preference for this repair pathway exists 

(Hanawalt et al. 2003). Proteins involved in this pathway 

are presented in Table 5.5. The initial step involves recognition of DNA damage (Figure 5.5). The complex of repair 

factors in the xeroderma pigmentosum group C (XPC) 

and the homologous recombinational repair group 23B 

(HR23B) can directly recognize some DNA damage (Hey 

et al. 2002). However, in some cases, DNA-binding pro-
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Figure 5.4 Mechanism of base excision repair

Source: Adapted from Christmann et al. 2003 with permission from Elsevier, © 2003.

Note: 5’dRP = 5’-deoxyribose phosphate; AP = apurinic/apyrimidinic; dRPase = DNA deoxyribophosphodiesterase; 

FEN1 = flap endonuclease 1; Lig = ligase; OH = hydroxide; P = phosphate; PCNA = proliferating cell nuclear antigen; 

pol = polymerase; RF-C = replication factor C; XRCC1 = x-ray repair cross-complementation group 1. 
Surgeon General’s Report

256 Chapter 5

Figure 5.5 Mechanism of nucleotide excision repair: (A) global genomic repair; (B) transcription-coupled repair

Source: Adapted from Christmann et al. 2003 with permission from Elsevier, © 2003. 

Note: CSA = Cockayne syndrome complementation group A; CSB = Cockayne syndrome complementation group B; DDB = DNA 

binding protein; ERCC1 = excision repair cross-complementation group 1; HR23B = homologous recombinational repair group 23B; 

mRNA = messenger RNA; PCNA = proliferating cell nuclear antigen; pol = polymerase; RNAPII = RNA polymerase II; RPA = replication protein A; TFIIH = transcription initiation factor IIH; TFIIS = transcription initiation factor IIS; XP = xeroderma pigmentosum 

(groups A–G).
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

tein is required to enhance the DNA distortion before the 

recruitment of XPC-HR23B (Tan and Chu 2002; Hanawalt 

et al. 2003). Repair factors XPA and replication protein 

A are then recruited to the complex to verify that the 

alteration in the DNA structure results from a lesion, as 

opposed to a natural variation in DNA structure (Hanawalt 

et al. 2003). 

The DNA is then unwound at the site of the lesion. 

This step occurs on recruitment of the basal transcription initiation factor IIH (TFIIH) multiprotein complex 

(Christmann et al. 2003). This complex is likely involved 

in a further verification of damage and detection of the 

damaged strand. The helicase subunits of TFIIH, XPB, and 

XPD then unwind the DNA around the lesion. 

Once the DNA has unwound, the lesion is excised 

at defined sites on either side of the damage (Evans et al. 

1997). The 3’-incision is catalyzed by XPG (Habraken et al. 

1994; O’Donovan et al. 1994), and the 5’-incision is catalyzed by the excision repair cross-complementation group 

1 (ERCC1) XPF complex (Sijbers et al. 1996). The resulting DNA gap is filled in by the PCNA-dependent polymerases: pold and pole (Aboussekhra et al. 1995; Araújo et al. 

2000). The final ligation is performed by DNA ligase I and 

associated proteins (Aboussekhra et al. 1995; Mu et al. 

1995; Araújo et al. 2000). Findings from in vivo studies 

suggest that the NER machinery is assembled in a stepwise manner from the individual components at the lesion 

site. After the repair of a DNA lesion, the entire complex is 

believed by researchers to disassemble (Houtsmuller et al. 

1999; Hoeijmakers 2001).

GGR appears to be inducible in humans (Hanawalt 

et al. 2003). The proteins that recognize DNA damage in 

GGR are maintained at low levels under normal physiological conditions. However, as a result of genomic stress, 

the efficiency of GGR is increased through the activation 

of the P53 tumor-suppressor gene (Hanawalt et al. 2003). 

Consequently, the levels of XPC and XPE increase. Repair 

of PAH adducts depends on the presence of the P53 protein (Hanawalt et al. 2003). These adducts are not repaired 

in human fibroblasts that lack a functional P53 protein or 

other gene product (Lloyd and Hanawalt 2000, 2002; Wani 

et al. 2000).

Transcription-coupled repair. TCR occurs when 

DNA damage blocks elongating RNA polymerases (Tornaletti and Hanawalt 1999). The transcription-coupled, 

repair-specific factors belong to two Cockayne syndrome 

Table 5.5 Factors involved in nucleotide excision repair activity in humans

Factor Proteins Factor activity Role in repair

XPA XPA DNA binding Damage recognition

RPA P70 XPA binding Damage recognition

RPA P34 DNA binding NR

RPA P11 NR NR

TFIIH XPB DNA-dependent ATPase Formation of preincision complexes

TFIIH XPD Helicase NR

TFIIH P62 GTP NR

TFIIH P52 NR NR

TFIIH P44 CAK NR

TFIIH CDK7 NR NR

TFIIH CYCH NR NR

TFIIH P34 NR NR

XPC XPC DNA binding Molecular matchmaker

XPC HR23B NR Stabilization of preincision complex 1

XPG XPG NR 3’ incision

XPF XPF NR 5’ incision 

XPF ERCC1 NR NR

Source: Adapted from Petit and Sancar 1999 with permission from Elsevier, © 1999.

Note: ATPase = adenosine triphosphatase; CAK = cyclin-dependent kinase-activating kinase; CDK7 = cyclin-dependent kinase 7; 

CYCH = cytochrome c-type biogenesis protein; ERCC1 = excision repair cross-complementation group 1; GTP = guanosine 

triphosphate; HR23B = homologous recombinational repair group 23; NR = data not reported; RPA = replication protein A; 

TFIIH = transcription initiation factor IIH; XP = xeroderma pigmentosum (groups A–G).
Surgeon General’s Report

258 Chapter 5

complementation groups (A and B) and are involved in 

the displacement of the stalled polymerase (Christmann 

et al. 2003). At this point, TFIIH is recruited to the lesion, 

and the subsequent steps in TCR proceed in a manner 

apparently similar to the steps for GGR. Because of the 

mechanism of DNA damage recognition, TCR is specific 

to a DNA strand. 

Substrate Specificity

The substrate specificity of NER ranges from small 

to large distortions in DNA structure. The bulky DNA 

damage generated by PAHs and aromatic amines in 

tobacco smoke is repaired primarily by NER (Friedberg 

2001). The finding that human NER repairs 8-oxoguanine 

in vitro more efficiently than thymine dimers or thymine 

glycol (Reardon et al. 1997) suggests that this pathway 

may be important for the repair of this mutagenic adduct. 

In addition, human NER repairs O6-methylguanine and 

N6-methyladenine, as well as A:G and G:G mismatches 

(Huang et al. 1994).

Protecting Against Mutagenicity and 

Carcinogenicity of Tobacco Carcinogens

Consistent with the primary role of NER in the 

repair of bulky DNA damage from PAHs and aromatic 

amines, cells deficient in NER are more susceptible to the 

mutagenic and toxic effects of PAHs (Quan et al. 1994, 

1995; Lloyd and Hanawalt 2000, 2002; Wani et al. 2000).

Mismatch Repair

Overview

MMR corrects replication errors (base-base or 

insertion-deletion mismatches) resulting from DNA polymerase errors. This repair pathway is also involved in 

the repair of alkylation DNA damage, such as repair of 

O6-methylguanine (Duckett et al. 1996), cisplatin-derived 

1,2-intrastrand cross-links (Duckett et al. 1996), and 

adducts derived from B[a]P (Wu et al. 1999), 2-aminofluorene, and N-acetyl-2-aminofluorene (Li et al. 1996). This 

pathway can also repair 8-oxoguanine (Colussi et al. 2002).

An overview of MMR is displayed in Figure 5.6. Recognition of DNA damage occurs primarily by the mutSα 

complex (Christmann et al. 2003). This complex is composed of the mutS homologous proteins MSH2 (Fishel 

et al. 1993; Leach et al. 1993) and MSH6 (Palombo et al. 

1995). Once the heterodimer is bound to the mismatch, 

it undergoes an adenosine-triphosphate (ATP)-dependent 

conformational change (Stojic et al. 2004). This complex is involved in determining which strand is the newly 

synthesized DNA (Christmann et al. 2003). A second heterodimer (mutLα) composed of mutL homologs MLH1 

and PMS2 then binds to the mutSα-DNA complex in another ATP-dependent step (Nicolaides et al. 1994; Papadopoulos et al. 1994; Li and Modrich 1995; Stojic et al. 2004). 

Exonuclease I then excises the DNA strand containing the 

mispaired base (Genschel et al. 2002), followed by the 

resynthesis of new DNA by pold (Longley et al. 1997).

MSH2 can also complex with MSH3 to form mutSβ 

(Acharya et al. 1996; Palombo et al. 1996). The substrate 

specificity of this alternate complex is different from that 

of mutSα (Christmann et al. 2003). The mutSα complex 

recognizes base-base mismatches, as well as insertiondeletion mismatches (Umar et al. 1994), whereas mutSβ 

binds only to insertion-deletion mismatches (Palombo et 

al. 1996; Genschel et al. 1998). 

Figure 5.6 Mechanism of mismatch repair

Source: Adapted from Christmann et al. 2003 with permission 

from Elsevier, © 2003.

Note: For two steps dependent on adenosine triphosphatase 

(ATPase), see text. C = cytosine; G = guanine; HMLH1 = human 

mutL homolog 1 protein; HMSH2 = human mutS homolog 2 

protein; HMSH6 = human mutS homolog 6 protein; 

HPMS2 = human postmeiotic segregation increased 2 protein; 

SSB = single-stranded DNA binding protein; T = thymine.
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Protecting Against Mutagenicity and 

Carcinogenicity of Tobacco Carcinogens

Persistent adducts that escape repair by AGT, BER, 

or NER may be processed by MMR. Because MMR occurs 

after DNA replication (Stojic et al. 2004), this is the last 

opportunity for DNA damage repair before cell division. 

Consequently, a defective MMR results in an increase 

in mutagenesis (Schofield and Hsieh 2003). The overall 

effect of a defective MMR is the likelihood that cells with 

persistent DNA damage survive with a miscoded DNA. 

This combination results in a higher cancer risk.

The role of MMR in the toxicity and mutagenicity 

of alkylating agents is well documented for methylating 

agents (Karran 2001; Stojic et al. 2004). Cells lacking 

functional MMR are more resistant to the toxic effects of 

methylating agents (Koi et al. 1994; Risinger et al. 1995; 

Umar et al. 1997; de Wind et al. 1999; Karran 2001; Stojic et al. 2004). However, these cells are sensitive to the 

mutagenic effects of these compounds (Umar et al. 1997; 

Zhu et al. 1998). These effects are linked to the ineffective 

MMR of O6-methylguanine. As a result, a defective MMR is 

associated with increases in mutagenesis and carcinogenesis mediated by O6-methylguanine (Hickman and Samson 1999; Pauly and Moschel 2001). Similar effects were 

reported for ethylating agents (Claij et al. 2003).

Double-Strand Break Repair

Overview

Two pathways exist for DSBRs: homologous recombination and nonhomologous end-joining. Homologous 

recombination occurs during DNA replication in the S 

and G2 phases, whereas nonhomologous end-joining 

occurs during G0 and G1 phases. Homologous recombination uses the sister chromatid as the template for aligning 

the breaks in the proper orientation and is consequently 

error free (Hoeijmakers 2001). However, nonhomologous 

end-joining does not require sequence homology between 

the two breaks to ligate them and is therefore prone to 

errors (Hoeijmakers 2001).

Homologous Recombination

The meiotic recombination 11 (MRE11)-RAD50-

NBS1 protein complex initiates DSBR by catalyzing the 

degradation of the DNA in the 5’ to 3’ direction, generating 

3’ single-stranded DNA (Figure 5.7). This single-stranded 

DNA is protected from degradation by a heptameric ring 

complex of RAD52 proteins (Stasiak et al. 2000). Replication factor A facilitates the assembly of a RAD51 nucleoprotein filament, which consists of RAD51B, RAD51C, and 

RAD51D, as well as XRCC2 and XRCC3 (Christmann et al. 

2003). RAD51 is able to exchange the single strand with 

the same sequence from the sister chromatid DNA. This 

double-stranded copy is then used as a template to correctly repair with DNA synthesis machinery. The resulting 

Holliday structures are subsequently resolved to generate 

the repaired DNA (Constantinou et al. 2001). 

Nonhomologous End-Joining

Nonhomologous end-joining merely links the ends 

of a DSB together in the absence of a template (Figure 

5.8). The break is initially recognized by a heterodimer 

consisting of the proteins KU70 (Reeves and Sthoeger 

1989) and KU80 (Jeggo et al. 1992). This binding protects 

the DNA from digestion and associates it with the protein 

kinase catalytic subunit DNA-PKcs, which is dependent on 

DNA. This complex, in turn, activates XRCC4-ligase IV, 

which connects the broken DNA pieces together once the 

MRE11-RAD50-NBS1 complex has processed the break 

(Maser et al. 1997; Nelms et al. 1998). Researchers think 

that FEN1 and Artemis also play a role in the processing 

of DSBs (Christmann et al. 2003). 

Protecting Against Mutagenicity and 

Carcinogenicity of Tobacco Carcinogens

Scientists think that DSBs trigger large chromosomal aberrations such as chromosomal breaks and 

exchanges (Pfeiffer et al. 2000). Studies link an increase in 

chromosomal aberrations to tobacco exposure (DeMarini 

2004). These aberrations are more common in pulmonary 

lung tumors from smokers than in those from nonsmokers (Sanchez-Cespedes et al. 2001). DSBs are also important in triggering cell death (Rich et al. 2000; Lips and 

Kaina 2001).

Molecular Epidemiology 

of DNA Repair

Studies support the substantial interindividual variations in DNA repair capacity (DRC). Researchers hypothesize that common variants in the genes that regulate 

these protein expressions may modulate repair and influence susceptibility to tobacco carcinogenesis. Two complementary approaches to studying DNA repair as a risk 

factor for tobacco carcinogenesis are applying functional 

assays and genotyping variants in gene pathways for DNA 

repair. Table 5.6 summarizes some relevant genes and 

their variants in pathways involved in repairing tobaccoinduced DNA damage.
Surgeon General’s Report

260 Chapter 5

Figure 5.7 Proposed mechanism of homologous recombination

Source: Adapted from Christmann et al. 2003 with permission from Elsevier, © 2003.

Note: MRE11 = meiotic recombination 11; RAD = S. cerevisiae DNA damage recognition and repair protein; RPA = replication 

protein A; XRCC2/XRCC3 = x-ray repair cross-complementation groups 2 and 3.
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Functional Assays of DNA Damage and 

Repair to Tobacco Carcinogens

Berwick and Vineis (2000) extensively reviewed the 

types of functional assays. The review included assays that 

use a chemical or physical mutagen challenge such as 

mutagen sensitivity, single-cell microgel electrophoresis 

(comet assay), and assays of induced adducts and unscheduled DNA synthesis. The review also included the host-cell 

reactivation (HCR) assay, which measures cellular ability 

to remove adducts from plasmids transfected into lymphocyte cultures in vitro by the expression of damaged 

reporter genes. 

Host-Cell Reactivation Assay

The HCR assay measures the expression level of 

damaged reporter genes, which are involved in reactivation of the host cell. The assay uses undamaged host 

lymphocytes, is fast, and objectively measures intrinsic 

cellular repair (Athas et al. 1991). In the assay, lymphocytes are transfected with a damaged, nonreplicating 

recombinant plasmid harboring a chloramphenicol acetyltransferase (CAT) reporter gene (PCMVCAT). To study 

tobacco-related cancers, the mutagen challenge is B[a]P 

(Gelboin 1980). Experimental conditions produce at least 

one BPDE-DNA adduct per plasmid, completely blocking transcription of the PCMVCAT gene without inducing conformational changes in the DNA. This finding is 

important because conformational change of the plasmid 

could reduce the transfection rate. Because even a single 

unrepaired DNA adduct can effectively block PCMVCAT

transcription (Koch et al. 1993), any measurable PCMVCAT activity reflects the ability of the transfected cells to 

remove BPDE-induced adducts from the plasmids (Athas 

et al. 1991).

Both lymphocytes and skin fibroblasts from patients 

with basal cell carcinoma, but not with XP, were found 

to have lower excision repair rates than those from persons without cancer (Wei et al. 1993). Consequently, the 

repair capacity of lymphocytes may reflect the overall 

repair capacity of a person. Spitz and colleagues (2003) 

showed that case patients with lung cancer had a significantly lower DRC than did control participants and 

that case patients aged 63 years or younger and lifetime 

nonsmokers had a lower DRC than that of matched control participants. DRC appears to be highest among case 

patients and control participants who were current smokers than among those who were former smokers and 

lifetime nonsmokers. Heavy smokers among both case 

patients and control participants tended to have more proficient DRC than did light smokers. This finding indicated 

that cigarette smoking may stimulate DRC in response 

to the DNA damage caused by carcinogens in tobacco. 

Such an adaptation would be consistent with a baseline 

DRC that can be mobilized on an increased demand for 

repair (Eller et al. 1997; Cheng et al. 1998). This adaptation of DRC to smoking, if it exists, appears to be long 

term rather than transient, because the effect was still 

present in former smokers but was not stronger in those 

who had smoked in the 24 hours before the blood sample 

was drawn (Wei et al. 2000). The finding that long-term 

heavy smokers with lung cancer had an efficient DRC may 

also indicate that heavy exposure overwhelms even relatively resistant phenotypes.

Luciferase Host-Cell Reactivation Assay

Researchers have modified the HCR assay by 

replacing CAT with luciferase (LUC). The cell-extraction 

procedure is far more simplified for the LUC assay. A luminometer measures LUC optical density, and the laboratory 

Figure 5.8 Proposed mechanism of nonhomologous 

end-joining

Source: Adapted from Christmann et al. 2003 with permission 

from Elsevier, © 2003.

Note: FEN1 = flap endonuclease 1; MRE11 = meiotic 

recombination 11; PKcs = protein kinase catalytic subunit; 

XRCC4 = x-ray repair cross-complementation group 4.
Surgeon General’s Report

262 Chapter 5

Table 5.6 Select candidate genes and polymorphisms implicated in repair of tobacco-induced DNA damage

Gene Nucleotide position Nucleotide change Amino acid change Allele frequency

Alkyltransferases            

AGT, MGMT       Ile143Val 0.05–0.2

Base excision repair            

MBD4 13390 T/C Ser342Pro 0.05

MBD4 13402 G/A Glu346Lys 0.07

TDG 27090 G/A Gly199Ser 0.09

MUTYH 18556 G/C Gly335His 0.44

OGG1 18069 C/G Ser326Cys 0.25

APEX1 11865 T/G Glu148Asp 0.25

XRCC1 32584 C/T Arg194Trp 0.08

XRCC1 33746 G/A Arg280His 0.05

XRCC1 34432 G/A Arg399Gln 0.31

ADPRT 75787 T/C Val761Ala 0.38

ADPRT 77525 C/T Pro882Leu 0.20

POLD1 24569 G/A Arg19His 0.12

POLD1 27479 A/G His119Arg 0.16

POLD1 27715 A/G Ser173Asn 0.06

Nucleotide excision repair            

XPC 30197 C/T Ala499Val 0.24

XPC 42635 A/C Lys939Gln 0.38

XPD 16232 G/A Asp312Asn 0.40

XPD 28572 A/C Lys751Gln 0.33

XPF 34637 T/C Ser662Pro 0.06

RAD23B 48769 C/T Ala249Val 0.18

CCNH 23563 C/T Val270Ala 0.10

XPG 39583 G/C His1104Asp 0.32

LIG1 29008 A/C Ala170Ala 0.39

LIG1 61130 C/T Asp802Asp 0.21

LIG1 62525 C/G Ala814Ala 0.30

Double-strand break repair            

Homologous recombination            

RAD51 692 (cDNA) G/T Ala143Ser 0.33

XRCC3 26044 T/C Thr241Met 0.22

RAD52 45137 C/A Ser346Ter 0.05

RAD54L 1222 (cDNA) G/C Arg374Ser 0.11

BRCA2 27113 T/G His372Asn 0.23

BRCA2 93268 G/A Ile3412Val 0.05

RAD50 3374 (cDNA) G/T Arg1111Ile 0.25

NBS1 137331 C/G Gln185Glu 0.46

Nonhomologous end-joining            

KU70 336 (cDNA) G/A Glu107Lys 0.06

KU70 454 (cDNA) T/C Val146Ala 0.11

KU70 1825 (cDNA) T/C Leu603Pro 0.10

KU80 1487 (cDNA) C/T Pro485Leu 0.14

LIG4 8 (cDNA) C/T Ala3Val 0.07

LIG4 27 (cDNA) C/T Thr9Ile 0.14

XRCC4 21965 G/T Ala247Ser 0.08

Note: cDNA = complementary DNA.
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

procedures are shorter. The results for the DRC phenotype 

from the independent CAT and LUC assays in parallel are 

highly correlated, with a correlation coefficient of 0.65 

(p <0.0001) (Qiao et al. 2002a). This finding suggests that 

these two assays are comparable. 

8-Oxoguanine DNA Glycosylase Activity Assay

The OGG test is another functional repair assay that 

measures the specific activity of the enzyme 8-oxoguanine 

DNA N-glycosylase in protein extracts prepared from 

peripheral blood mononuclear cells (Paz-Elizur et al. 

2003). The OGG1 enzyme removes 8-oxoguanine from 

DNA and leaves behind an abasic site that is rapidly cleaved 

by the AP lyase of OGG1. OGG activity (in units per μg of 

protein extract) is the amount of fragment cleaved by 1 μg 

of extract in one hour under standard reaction conditions (Paz-Elizur et al. 2003). In a pilot case-control study 

of NSCLC, the mean value of OGG activity in the case 

patients was significantly lower than that in the control 

participants and was independent of tumor histology, 

gender, and smoking status (Paz-Elizur et al. 2003). In 

addition, OGG activity in protein extracts from peripheral 

blood mononuclear cells correlated well with that from 

lung tissue in the same patients (p = 0.003).

Mutagen Sensitivity Assays

Researchers use cytogenetic assays extensively to 

measure human exposure and response to genotoxic 

agents. These assays are based on the unproven hypothesis that the extent of genetic damage in the lymphocytes 

may reflect critical events in carcinogenesis in the affected 

tissues. The assays can only indirectly indicate DRC from 

the cellular damage that remains after mutagenic exposure and recovery and therefore probably reflect nonspecific impairment of the DNA repair machinery (Berwick 

and Vineis 2000).

Hsu and colleagues (1989) developed the in vitro 

mutagen challenge assay to demonstrate interindividual 

differences in susceptibility to carcinogenic agents. This 

assay counts the frequency of bleomycin-induced breaks 

in short-term lymphocyte cultures, as a measure of cancer 

susceptibility. Bleomycin is a clastogenic agent that mimics the effects of radiation by generating free oxygen radicals capable of producing DNA single-strand breaks and 

DSBs after forming a complex with DNA, ferrous ions, and 

oxygen that releases oxygen radicals (Burger et al. 1981). 

Most of the breaks are repaired by BER. Repair is rapid, 

with a half-life of only a few minutes (López-Larraza et 

al. 1990). 

Mutagen sensitivity is an independent risk factor for 

lung cancer that has a dose-response relationship with the 

number of induced chromosomal breaks (Spitz et al. 1995, 

2003; Strom et al. 1995; Wu et al. 1995, 1998a; Zheng et 

al. 2003). The risks associated with mutagen sensitivity, 

stratified by smoking status, are elevated in all smoking 

strata but are highest in current smokers and in the heaviest smokers. For studying tobacco-related cancers, a more 

appropriate mutagen to trigger DNA damage is BPDE; 

BPDE-induced sensitivity is a risk factor for lung cancer 

(Wei et al. 1996; Wu et al. 1998a,b).

Comet Assay

The comet assay (single-cell microgel electrophoresis) is applicable to any cell line or tissue from which a 

single-cell suspension can be obtained (Ross et al. 1995). 

Singh and associates (1988) have described the methods in 

detail. For this assay, a cell culture is mixed with agarose 

gel and attached to a microscope slide. The cells are lysed 

by submerging the slides in freshly prepared lysis buffer 

to remove all cellular proteins. To allow for DNA denaturation, unwinding, and expression of the alkali-labile sites, 

the slides are then placed in an alkali buffer (pH = 12.0). 

To separate the damaged DNA from the intact nuclei, a 

constant electric current is applied, and the slides are neutralized, fixed, and stored in the dark at room temperature 

until ready for analysis. During electrophoresis, damaged DNA migrates from the nucleus toward the anode 

as a result of the constant electric current, which forms 

the typical “comet” cell. A predetermined number of cells 

are manually selected, and comet cells are automatically 

quantified with appropriate imaging software.

Case patients with lung and bladder cancer had 

significantly higher levels of induced DNA damage after exposure to both BPDE and g-radiation, which were 

assessed by the mean “tail moment” in lymphocytes. (The 

tail moment is the product of lymphocyte tail length and 

the fraction of the total DNA in the tail.) Higher levels of 

DNA damage were positively associated with increased 

risk of bladder and lung cancer (Schabath et al. 2003; Wu 

et al. 2005). Schmezer and colleagues (2001) showed that 

case patients with lung cancer were significantly more 

sensitive to bleomycin and had a reduced DRC (68 percent 

in case patients and 81 percent in control participants 

[p <0.001]). Rajee-Behbahani and colleagues (2001) 

reported a similar DRC finding of 67 percent in 160 case 

patients with lung cancer and 79.3 percent in 180 control participants. When the data from the cases and controls were considered together, only 18 percent of the case 

patients were below the median level of sensitivity to bleomycin for all control participants, and 82 percent were in 

the hypersensitive range. 

Mohrenweiser and Jones (1998) have pointed out 

several lines of evidence documenting that differences 

in DRC reflect genetic differences. DRC in lymphocyte 
Surgeon General’s Report

264 Chapter 5

subpopulations from an individual exhibited similar 

repair capacities. Furthermore, intraindividual variations 

in repair capacity among subpopulations of lymphocytes 

are significantly smaller than are interindividual variations (Crompton and Ozsahin 1997). The phenotype of 

reduced repair capacity in the NER pathway is independent of the phenotype for DSBR (Wu et al. 1998a).

Researchers have performed extensive resequencing of DNA repair genes to identify variations that may be 

associated with a reduced function of their encoded proteins rather than an absence of function. Such polymorphisms could explain interindividual differences in DRC 

(Spitz et al. 2001; Qiao et al. 2002b; Wu et al. 2003). 

Although the variant alleles are likely to be associated 

with only a modest cancer risk, because they exist at a 

polymorphic frequency, the attributable risks can become 

substantial. As Berwick and Vineis (2000) noted, studies that compare genetic polymorphisms with results of 

functional assays will likely be the most valuable type of 

investigations to clarify the role of a defect in DRC with 

the development of cancer. 

Polymorphisms in O6-Alkylguanine–DNA 

Alkyltransferase

The ability of a cell to withstand alkyl damage is 

related to the number of AGT molecules in the cell and 

the rate of de novo synthesis of AGT. AGT levels differed 

among persons, and protein levels in the liver, colon, and 

peripheral blood varied 4-, 10-, and 20-fold, respectively 

(Myrnes et al. 1983; Strauss et al. 1989; Povey et al. 2000). 

Environmental and genetic factors, but not age, affect 

expression levels of AGT (Margison et al. 2003). AGT levels are higher in normal lung, colorectal, and placental 

tissues from smokers than in those from nonsmokers, 

although these findings are controversial (Slupphaug et 

al. 1992; Drin et al. 1994; Povey et al. 2000). Exposure 

to AGT inhibitory aldehydes, such as formaldehyde from 

occupational exposure, can deplete AGT activity (Hayes et 

al. 1997). Expression of AGT is higher in NSCLC tumor tissues from smokers than in those from nonsmokers (Mattern et al. 1998). However, small-scale studies examining 

AGT activity in peripheral lymphocytes have not observed 

significant differences between smokers and nonsmokers 

(Vähäkangas et al. 1991; Oesch and Klein 1992; Hall et al. 

1993) or between case patients with cancer and control 

participants (Boffetta et al. 2002). It is not clear how well 

AGT activity in lymphocytes predicts levels in lung tissue.

The AGT gene contains multiple polymorphisms in 

the 5’ upstream region, which comprises the promoter 

and enhancer regions, as well as exon 1 (Egyházi et al. 

2002; Krzesniak et al. 2004). These genetic variations 

may account for some of the interindividual variations in 

expression levels. Eight allelic variants in this region occur 

at a frequency of at least 0.01. One-half of these variants 

have a prevalence of 0.1 to 0.6, and this finding suggests 

a contribution to the variability in AGT expression within 

populations (Krzesniak et al. 2004). The prevalence of the 

best-studied enhancer polymorphism, C1099T, is 0.09 

to 0.12 and is associated with an increase in promoterenhancer activity in the LUC assay (Krzesniak et al. 2004). 

However, heterozygotes for this enhancer polymorphism 

do not appear to be at a markedly lower risk of developing 

lung cancer (OR = 0.82; 95 percent CI, 0.41–1.67) (Krzesniak et al. 2004). None of the other enhancer-promoter 

polymorphisms have been examined for their relationship 

with AGT or cancer risk.

Mutations at or near the cysteine acceptor site can 

affect AGT activity (Crone et al. 1994). Two polymorphisms 

have been identified in this region of the protein: codon 

143 *ILE/*VAL and codon 160 *GLY/*ARG. The variant 

isoform codon 160 *GLY/*ARG has exhibited activity to 

repair bulky alkylated DNA adducts that is significantly 

less than that of the GLY wild-type phenotype (Edara et al. 

1996; Mijal et al. 2004). The estimated prevalence of the 

143 variant is 0.07 in Whites, 0.03 in African Americans 

(Kaur et al. 2000), and as high as 0.24 in Swedish populations (Ma et al. 2003). The codon 160 variant allele is 

likely a mutant, because it was found at a frequency less 

than 0.01 (Kaur et al. 2000). These researchers reported a 

marginally significant increase in the risk of lung cancer 

associated with the codon 143 *ILE/*VAL genotype (OR = 

2.1; 95 percent CI, 1.01–4.7), and no interaction of genotype and smoking dose was seen. More recently, Cohet and 

colleagues (2004) reported an OR of 2.05 (95 percent CI, 

1.03–4.07) for lung cancer among lifetime carriers of the 

codon 143 and 160 variant alleles who were nonsmokers. 

The authors suggested that the strongest risk was associated with exposure to secondhand tobacco smoke.

Polymorphisms in the Pathway 

for Repair of Base Excision

Cross-Complementation 

Group 1 for Excision Repair

The XRCC1 gene encodes a protein that functions 

in BER and involves the excision of the damaged region, 

followed by repair synthesis that uses the opposite strand 

as the template. The XRCC1 protein forms scaffolding 

with DNA ligase III, polβ, and poly (adenosine diphosphate–ribose) polymerase (PARP) to rejoin DNA strand 

breaks and repair gaps left during BER. Of the estimated 

17 variants, 1 is a polymorphism at the XRCC1 28152 site 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

(G→A transition) of codon 399 in exon 10 that results in a 

nonconservative amino acid substitution of arginine 

for glutamine. Goode and colleagues (2002) extensively 

reviewed the conflicting results for lung cancer studies. 

For example, Divine and colleagues (2001) reported a 

more than twofold risk for lung adenocarcinoma associated with the *GLN/*GLN genotype. Zhou and colleagues 

(2003) found an association that was largely restricted to 

nonsmokers and light smokers. Some studies failed to find 

any association between the *GLN/*GLN genotype and 

lung cancer risk (Butkiewicz et al. 2001; Ratnasinghe et 

al. 2001; Popanda et al. 2004; Zhang et al. 2005b). However, Matullo and colleagues (2001a) did find an association for bladder cancer. David-Beabes and London (2001) 

reported a decreased risk of lung cancer for both African 

American and White patients. Other studies also report 

conflicting findings regarding an increased risk associated 

with the exon 10 *ARG/*ARG genotype (Lee et al. 2001; 

Stern et al. 2001).

Another polymorphism at the XRCC1 26304 site 

(C→T transversion) of codon 194 in exon 6 results in a 

nonconservative amino acid substitution of arginine. Most 

studies suggest a reduced risk of cancer associated with 

the 399*ARG variant allele (Goode et al. 2002). Studies 

of lung, bladder, head and neck, and gastric cancers all 

showed inverse associations with the variant allele; some 

studies included evidence of an interaction with smoking 

(Sturgis et al. 1999; David-Beabes and London 2001; Ratnasinghe et al. 2001; Stern et al. 2001). Two studies noted 

no association for esophageal and lung cancers (Butkiewicz et al. 2001; Lee et al. 2001).

A few earlier studies evaluated the functional significance of these polymorphisms. Lunn and colleagues 

(1999) noted that persons with the 399*GLN allele were 

at a significantly higher risk (OR = 2.4) for exhibiting 

detectable aflatoxin B1 adducts and a higher frequency 

of the glycophorin A variant than were carriers of the 

399*ARG/*ARG allele. This study also reported a doseresponse relationship between smoking status and presence of the polymorphism for detecting the adducts and 

the glycophorin A variant (Lunn et al. 1999). However, 

no significant effects were noted for other XRCC1 polymorphisms. Duell and colleagues (2000) found elevated 

SCE frequencies and polyphenol DNA adducts with 

399*GLN/*GLN homozygous genotypes. Abdel-Rahman 

and El-Zein (2000) noted that persons carrying the 

*GLN allele had significantly higher numbers of SCEs in 

response to NNK treatment than did *ARG/*ARG genotype carriers. No differences were detected in persons with 

the codon 194 genotype. 

Matullo and colleagues (2001b) found higher DNA 

adduct levels among lifetime nonsmokers who were 

healthy and were homozygous for the 399*GLN allele 

than among those with the wild-type genotype (15.6 versus 6.78, p = 0.007). Wang and colleagues (2003a) showed 

that persons with the variant 194*TRP allele had fewer 

bleomycin- and BPDE-induced breaks per cell than did 

those with the wild-type genotype. The XRCC1 codon 399 

is within the BRCT domain (amino acids 301 to 402) that 

interacts with PARP and is in many proteins with activity 

involving response to DNA damage and cell-cycle checkpoints. This region also has homology with yeast RAD4

repair-related genes. Because the role of XRCC1 in BER 

brings together DNA polβ, DNA ligase III, and PARP at the 

site of DNA damage, repair activity of the exon 10 variant may be altered. The codon 194 polymorphism is in 

the linker region of the XRCC1 N-terminal domain separating the helix 3 and polβ involved in binding a singlenucleotide gap DNA substrate (Marintchev et al. 1999). 

Therefore, this polymorphism is less likely to cause a significant change in repair function. 

OGG1 Gene

The product of the OGG1 gene catalyzes the excision 

of a modified base, 8-oxoguanine, which may be formed by 

exposure to reactive oxygen species. The reduced ability to 

excise 8-oxoguanine may lead to an accumulation of oxidation-induced mutations. Studies have identified several 

polymorphisms at the OGG1 locus. The most frequently 

studied polymorphism is a common C→G transversion in 

exon 7 that results in an amino acid alteration at codon 

326 (Ser→Cys). The HOGG1 protein encoded by the wildtype 326*SER allele exhibited substantially higher DNA 

repair activity than did the 326*CYS variant in an in vitro 

Escherichia coli complementation activity assay (Kohno 

et al. 1998). 

Researchers have observed fairly consistent 

increased risks of OGG1 polymorphisms (Goode et al. 

2002). The largest study was a U.S.-population-based, 

multiethnic study of lung cancer that identified a significantly increased risk associated with the *CYS/*CYS

genotype (*CYS/*CYS versus *SER/*SER; OR = 2.1; 95 

percent CI, 1.2–3.7) (Le Marchand et al. 2002). A small, 

hospital-based study of lung cancer in Japan supported 

these results (Sugimura et al. 1999). Findings in a third 

study of lung cancer that also suggested an increased risk 

had similar findings for comparison of the two homozygote groups (OR = 2.2; 95 percent CI, 0.4–11.8) (Wikman 

et al. 2000). Analyses of esophageal cancer also showed an 

increased risk associated with the *CYS/*CYS genotype 

(OR = 1.9; 95 percent CI, 1.3–2.6) (Xing et al. 2001). However, overall findings regarding an interaction with smoking were inconsistent.
Surgeon General’s Report

266 Chapter 5

Polymorphisms in the Pathway for 

Nucleotide Excision Repair

Xeroderma Pigmentosum A

XPA is an essential DNA-binding protein in the 

NER pathway that aids in correctly positioning the repair 

machinery around the damaged areas and in maintaining 

contact with core repair factors during the repair process. 

XPA interacts with other proteins, such as replication 

protein A, TFIIH, and XRCC1/XPF (Volker et al. 2001). 

Studies have identified an A→G transversion variant 

in the 5’ noncoding region (Butkiewicz et al. 2000). 

Researchers investigating this polymorphism in lung cancer reported similar results in two studies. Wu and colleagues (2003) reported that the presence of one or two 

copies of the *G allele instead of the *A allele was associated with a reduced lung cancer risk for all ethnic groups. 

Furthermore, control participants with one or two copies 

of the *G allele demonstrated more efficient DRC, as measured by the HCR assay, than did control participants with 

the homozygous A genotype. In a study in Korea, Park and 

colleagues (2002) reported that the *G/*G genotype was 

also associated with a significantly decreased lung cancer 

risk when the combined *A/*A and *A/*G genotype was 

used as the reference group. Butkiewicz and colleagues 

(2004) reported similarly increased risks that had borderline statistical significance for the *A/*A genotype in all 

participants and for SCC and adenocarcinomas. For heavy 

smokers, the risk estimate was 2.52 (95 percent CI, 1.2–

5.4). Popanda and colleagues (2004) reported a nonsignificant risk of 1.53 for the *A/*A genotype compared with the 

*G/*G genotype. Thus, all studies confirm the protective 

effect of the *G/*G genotype and the enhanced risk for the 

*A/*A genotype. 

Xeroderma Pigmentosum C

XPC is the step-limiting factor in NER. Researchers 

have found two single nucleotide polymorphisms (SNPs) 

in the coding region. ALA499VAL is a single *C/*T nucleotide polymorphism that codes for an amino acid substitution (Ala/Val) at codon 499. Another SNP, LYS939GLN, is 

a single *A/*C nucleotide polymorphism that codes for an 

amino acid substitution (Lys/Gln) at codon 939. This variant allele is associated with an increased risk of bladder 

cancer (Sanyal et al. 2004). There is also a bi-allelic poly 

AT insertion/deletion polymorphism (PAT) in intron 9 of 

XPC. The *PAT allele has been associated with risk of head 

and neck cancer (Shen et al. 2001).

Cross-Complementation Group 1 

for Excision Repair 

The XRCC1 gene codes for a 5’ incision subunit of 

the NER complex (Mohrenweiser et al. 1989). The XRCC1 

and XPF proteins form a stable complex in vivo and in 

vitro (de Laat et al. 1999). Although studies have reported 

no defect in the human XRCC1 gene, cells from XRCC1-

deficient mice have an increase in genomic instability and 

a repair-deficient phenotype (Melton et al. 1998). Five 

known polymorphisms of the XRCC1 gene do not cause an 

amino acid change and are validated in the SNP500Cancer Database of the National Cancer Institute. However, researchers think that a polymorphism with A→C 

transversion at nucleotide 8092 in the 3’ untranslated 

region affects mRNA stability (Shen et al. 1998). Studies 

have implicated the XRCC1 polymorphism in the risk of 

adult-onset glioma (Chen et al. 2000) but not in head and 

neck cancer (Sturgis et al. 2002). Zhou and colleagues 

(2005) found no overall effect on lung cancer risk, but 

they did find a lower lung cancer risk in heavy smokers 

and a significantly higher risk in lifetime nonsmokers 

(OR = 2.11; 95 percent CI, 1.03–4.31). 

Xeroderma Pigmentosum 

Complementation Group D

XPD (XRCC2) is one of the seven genetic complementation groups that encode for proteins in the NER 

pathway. The XPD protein has a role in both NER and 

basal transcription. XPD functions as an evolutionary 

conserved ATP-dependent helicase within the multisubunit transcription repair factor complex TFIIH. Of the 

three polymorphisms identified in XPD, two are in exons 

and the third is silent. The G→A transition in exon 10 at 

codon 312 results in an amino acid change (Asp→Asn). 

The transition A→C at codon 751 in exon 23 produces a 

Lys→Gln change. The amino acid substitution Lys751Gln 

in exon 23 does not reside in a known helicase/adenosine triphosphatase domain, but it is an amino acid residue identical in human, mouse, hamster, and fish XPD. 

This finding suggests a functional relevance for such 

a highly evolutionary conserved sequence (Shen et al. 

1998). Goode and colleagues (2002) extensively reviewed 

numerous reports from case-control studies of lung 

cancer that have conflicting results. The largest study 

included 1,092 lung cancer case patients and 1,240 control participants who were spouses or friends (Zhou et al. 

2002a). The overall AOR was 1.47 (95 percent CI, 1.1–2.0) 

for the ASP312ASN polymorphism (*ASN/*ASN versus 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

*ASP/*ASP), but there was no association for the LYS751GLN polymorphism (*GLN/*GLN versus *LYS/*LYS). 

Analyses of the interactions between genes and smoking 

revealed that the adjusted ORs for each of the two polymorphisms decreased significantly as pack-years1 increased. 

The interaction between the ASP312ASN polymorphism 

and smoking status was stronger than that between the 

LYS751GLN polymorphism and smoking. The researchers 

concluded that cumulative cigarette smoking modified 

the association between XPD polymorphisms and lung 

cancer risk. Spitz and colleagues (2001) reported AORs 

for the variant LYS751GLN and ASP312ASN genotypes 

of 1.36 and 1.51, respectively, although neither estimate 

was statistically significant. For persons homozygous for 

the variant genotype at either locus, the AOR was 1.84 (95 

percent CI, 1.11–3.04; p = 0.018 for trend).

A recent review and meta-analysis of nine international case-control studies that included 2,886 lung cancer cases and 3,085 controls for codon 312 (LYS751GLN) 

and 3,374 lung cancer cases and 3,880 controls for codon 

751 (ASP312ASN) did not demonstrate significant associations with either variant genotype (Benhamou and Sarasin 

2005). However, for U.S. studies alone, both variants were 

associated with a significantly increased risk for lung cancer (ORs = 1.43 and 1.25, respectively). Hu and colleagues 

(2004) conducted another meta-analysis. The combined 

case-control studies reported a 21-percent higher risk 

for the 751*C/*C genotype (OR = 1.21; 95 percent CI, 

1.02–1.43) and a 27-percent higher risk for the 

XPD 312*A/*A genotype (OR = 1.27; 95 percent CI, 

1.04–1.56) among cases than among controls. Among 

studies of persons of Asian versus White descent, only 

the studies of Whites found a significantly higher risk for 

the XPD 751*C/*C genotype (OR = 1.23; 95 percent CI, 

1.03–1.47). For the XPD 312*A/*A genotype, the risk 

among Whites compared with other races had borderline statistical significance (OR = 1.22; 95 percent CI, 

0.99–1.49) among cases compared with controls. TFIIH 

transcriptional activity may be tolerant to amino acid 

changes in the XPD protein, and mutations may destroy 

or alter the repair function without affecting transcriptional activity. As Lunn and colleagues (2000) suggested, 

the effects of the *LYS allele may differ in different repair 

pathways, as assessed by different repair assays. The overall effect of conservative mutations in XPD may be subtle, 

because they do not alter XPB and XPD helicase activity, 

and multiple alterations might be needed before any effect 

is noted. 

XPF/ERCC1 Gene Complex

ERCC1 forms a complex with XPF when it makes a 

dual incision at the single-strand to double-strand transition at the 5’ end of the damaged DNA strand (Shen et 

al. 1998). This complex is required to repair interstrand 

cross-links. A T→C transition at codon 662 results in a 

serine→proline substitution. Fan and colleagues (1999) 

reported six SNPs, five in coding regions. Three of the 

SNPs resulted in nonconserved amino acid differences. 

XPG/ERCC5 Gene Complex

This complex shows homology with yeast RAD2 

and carries out incision at the 3’ end of the lesion in 

the DNA strand (Harada et al. 1995; Hyytinen et al. 

1999). Only two of the seven validated SNPs appear 

with significant frequency. In one polymorphism, a 

single nucleotide substitution (G→C) causes an amino 

acid change (His1104Asp) at codon 1104. In the other 

polymorphism, a C→G substitution produces an amino 

acid change from cysteine to serine at codon 529. Sanyal and colleagues (2004) showed that the variant *C/*C

genotype was significantly less frequent in cases of bladder cancer than in controls. Jeon and colleagues (2003) 

reported similar findings for 310 lung cancer cases, in 

which the frequency of the variant genotype was less than 

that for the other two genotypes combined (AOR = 0.54; 

95 percent CI, 0.37–0.80). This protective effect was attenuated in heavy smokers. Jeon and colleagues (2003) 

pointed out that because this SNP is in the C-terminus, it 

might alter binding to other proteins in the incision complex, thereby affecting DRC. 

RAD23B Gene

The RAD23B gene is an evolutionary, well-conserved 

gene with 10 exons. The protein complexes with XPC to 

bind to different types of lesions and recruit the necessary 

factors for NER. Of the six validated SNPs, four are seen 

with considerable frequency. One of the most frequently 

observed polymorphisms is a substitution (C→T) resulting in an amino acid change at codon 249 (Ala249Val). 

Genotype-Phenotype Correlations

Amino acid differences, especially at conserved sites 

in these enzymes, could result in changes in repair proficiency. The next logical step is the challenging task of evaluating the functional relevance of these polymorphisms. A 

variety of factors that modulate the path from genotype to 

1Pack-years = the number of years of smoking multiplied by the number of packs of cigarettes smoked per day.
Surgeon General’s Report

268 Chapter 5

phenotype include protein-protein interaction, posttranslational modification, gene silencing, epigenetic regulation, and environmental factors. Furthermore, proteins 

involved in DNA repair pathways are often multifunctional, resulting in a variety of phenotypes. 

Both of the common genotypes *LYS/*LYS 751 and 

312 *ASP/*ASP XPD were associated with a DRC more 

efficient than that for heterozygotes and with a significantly higher DRC than that for the homozygote mutants 

(Spitz et al. 2001). These results were confirmed in a different study population with a different mutagen challenge: a 

UV exposure of 800 joules per square meter that like BPDE 

invoked NER (Qiao et al. 2002b). Additional validation 

came from a correlative study that used the comet assay to 

assess DNA damage and repair (Schabath et al. 2003). These 

data are consistent with some of the published small-scale 

studies of these types of genotype-phenotype correlations. 

Hou and colleagues (2002) noted a significant increase 

in DNA adduct levels, as measured by 32P-postlabeling, 

with an increased number of variant alleles in exon 10 

(p = 0.02) and exon 23 (p = 0.001). In addition, persons 

with the combined exon 10 *A/*A and exon 23 *C/*C

genotype showed significantly higher levels of adducts 

than those for persons carrying any of the other genotypes (p = 0.02). Lunn and colleagues (2000) reported that 

possessing the common XPD genotype, *LYS/*LYS 751, 

was associated with an increased risk of suboptimal DRC, 

which was reflected in the number of x-ray–induced lymphocyte chromatid aberrations. No association with the 

*ASN312 allele was found.

However, Møller and colleagues (1998) reported no 

relationship between the LYS751GLN polymorphism and 

DRC, as measured by HCR or comet assay in 80 participants, including 20 healthy persons. Another study with a 

small sample of 76 healthy persons found no association 

between either SCE frequencies or the presence of DNA 

adducts by LYS751GLN genotype (Duell et al. 2000). 

For a complex disease such as cancer, multiple 

genes—each with a small effect—probably act independently or interact with other genes to influence the disease phenotype. Although these data suggest that the 

polymorphisms have a functional relevance, biochemical 

and biologic characterizations of the variants are needed 

to validate these findings. 

Polymorphisms in the Pathway for 

Double-Strand Break Repair 

The XRCC3 gene encodes a protein that acts in 

the pathway for DSB/homologous recombination repair 

(DSB/REC repair) and repairs chromosomal damage such 

as breaks, translocations, and deletions. XRCC3 is a protein related to RAD51, which is a critical component of 

DSB/REC. Shen and colleagues (1998) identified a C→T 

substitution in exon 7 at position 18067 of XRCC3, a polymorphism that results in a threonine→methionine amino 

acid substitution at codon 241. David-Beabes and colleagues (2001) found no significant association between 

the XRCC3241 polymorphism and lung cancer. This finding was consistent with a smaller study of NSCLC that 

also found no association after adjustments for age and 

smoking (Butkiewicz et al. 2001). Wang and colleagues 

(2003c) reported an elevated but not statistically significant risk of lung cancer associated with polymorphisms 

of the XRCC3 *T allele in African Americans and Mexican 

Americans, which was evident largely in heavy smokers. 

Other studies have associated this XRCC3 polymorphism 

with an increased risk for melanoma skin cancer (Winsey 

et al. 2000) and bladder carcinoma (Matullo et al. 2001a). 

The THR241MET genetic variant may also contribute to 

increases in DNA adducts and bladder cancer risk (Stern 

et al. 2002). 

Summary

The association between common variants in DNA 

repair genes and the risk for tobacco-induced cancers is 

the focus of considerable interest, but the results to date 

are inconsistent. Complementary functional studies are 

likely to be valuable in addressing these inconsistencies. 

Molecular epidemiologists now have better access to highthroughput genotyping platforms and an enhanced ability 

to focus on analyses based on pathways. Haplotype analyses also increase the power to detect relevant associations. 

In addition, computational algorithms such as PolyPhen 

and Scale-Invariant Feature Transform correlate with risk 

estimates, and new analytic tools are being developed. 

Conversion of DNA Adducts 

to Mutations

DNA replication plays a major role in inducing point 

mutations—substitutions of one base pair for another and 

small mutations due to insertion or deletion of bases. DNA 

adducts per se are not mutations and can be removed by 

various DNA repair mechanisms in cells (Friedberg et al. 

1995). When repair is not completed before a replication 

complex encounters the DNA adducts or other lesions, 

various events are induced, which are sensed by cell-cycle 

checkpoint mechanisms that halt cell-cycle progression 

(Sancar et al. 2004). When the lesion is a strand break, 

replication causes a DSB that is repaired by homologous 

recombination or by the erroneous nonhomologous endjoining mechanism. When the lesion is an interstrand 
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cross-link, the stall of a replication complex triggers the 

unhooking of the cross-link by endonucleolytic incisions on both sides of the cross-link in one strand. When 

the lesion is a modified base or the loss of a base, a DNA 

polymerase often inserts a nucleotide, either correctly or 

incorrectly, opposite the lesion and extends the DNA 

strand beyond the site. The modification of a template nucleotide generally impairs its ability to serve as a template 

in efficiency and fidelity. Therefore, DNA synthesis slows 

down or is blocked at the site of the adducted template. 

Translesion DNA synthesis occurs when a DNA 

polymerase succeeds in DNA synthesis over the modified 

template. The synthesis reaction sometimes results in the 

insertion of an incorrect nucleotide opposite a lesion. This 

insertion leads to base-substitution mutations, the skipping of the lesion nucleotide template, or the realignment 

of a growing primer strand on the template strand at the 

adducted region, which produces frameshift mutations. 

This step results in the introduction of mutations, and 

the subsequent replication of the mutated strand establishes the mutation in the genome. This section describes 

the mechanism of mutation induction by translesion 

DNA synthesis.

Molecular Analysis of Conversion to Mutations

The strategy for studying the conversion of adducts 

to mutations is to incorporate a chemically characterized 

DNA adduct or lesion into a specific sequence (Basu and 

Essigmann 1988). A DNA adduct can be incorporated into 

an oligonucleotide sequence by total chemical synthesis. 

However, a modified oligonucleotide may be prepared by 

direct reaction with a mutagen, followed by HPLC and/or 

gel electrophoresis purification. The modified oligonucleotide is then used as a substrate for in vitro and in vivo 

studies of translesion DNA synthesis, repair, and structure. This experimental approach generally demonstrates 

a clear relationship between cause and effect. The advantage of this approach is the ability to analyze in detail 

events in translesion synthesis such as (1) quantification 

of the effects of blocking DNA synthesis, (2) miscoding frequency, and (3) miscoding specificity. 

In vitro studies of translesion synthesis that use 

purified DNA polymerases complement the in vivo studies. 

As described in the following section, cells have various 

types of DNA polymerases and some of them are responsible 

for translesion synthesis. Therefore, the characterization 

of in vitro translesion synthesis could help to identify the 

polymerase responsible for translesion synthesis in cells. 

In vitro studies can be divided into two phases: insertion 

and extension steps. The insertion step determines which 

nucleotide is most efficiently inserted opposite a lesion by 

a given polymerase. The extension step determines which 

nucleotide terminus is most efficiently extended opposite 

a lesion. These experiments characterize the efficiency 

and fidelity of translesion synthesis by a given polymerase. 

The results of the in vitro experiments may be reflected 

in translesion synthesis in cells if the polymerase is 

involved in the synthesis. The involvement of a candidate 

polymerase is examined by studying translesion synthesis 

in a host cell lacking the polymerase of interest. Finally, 

the involvement is confirmed by a complementation 

experiment in mutant cells that express the exogenous 

gene for the polymerase of interest. Thus, translesion synthesis across a given DNA lesion is studied in detail. One 

limitation of this site-specific experiment is the inability 

to study the effects on chromosomal aberrations. In addition, the results may not apply to other sequence contexts. 

Nevertheless, this approach has provided a tremendous 

amount of information on the mechanism of DNA adduct 

conversion to mutations. 

Translesion Synthesis in Mammalian Cells

DNA polymerases are key players in mutation induction. They introduce mutations during replication and 

determine the types of mutations generated. Great progress has been made in DNA polymerase studies in the last 

several years. Many novel DNA polymerases were discovered in prokaryotes and eukaryotes (Hübscher et al. 2002). 

These DNA polymerases play important roles in various 

aspects of DNA metabolism. The Y family polymerases 

(Ohmori et al. 2001) include eukaryotic polh, polk, and 

polτ, as well as REV1 and E. coli polIV and polV. In addition, polz is a member of the B family. Researchers think 

these Y family polymerases are specialized for translesion 

synthesis (Prakash and Prakash 2002). These discoveries 

have led to the general idea that these polymerases are 

responsible for overcoming the blocking effects of DNA 

adducts and constitute an important mechanism for tolerating unrepaired DNA lesions. 

The role of the polh polymerase is most clearly 

understood. This polymerase is coded by the XPV gene, 

which is defective in persons with XP variant cells (Johnson et al. 1999; Masutani et al. 1999). Although these cells 

possess NER capability, they carry a predisposition to skin 

cancer on exposure to sunlight. The discovery that polh

is able to bypass the cis-syn thymine-thymine dimer efficiently and accurately (Masutani et al. 1999) indicates that 

this polymerase plays a very important role in protection 

from the deleterious effects of unrepaired UV photoproducts. In its absence, the unrepaired lesions are bypassed by 

one or more other polymerases in an error-prone manner 

leading to skin cancer (Gibbs et al. 1998, 2000). X-ray crystallographic studies reveal that Y family polymerases have 

loose catalytic pockets enabling them to accommodate 
Surgeon General’s Report

270 Chapter 5

Table 5.7 Translesion-specialized DNA polymerases (pol) and activities on various DNA lesions

DNA adduct polh polk polz polh + polz poli + polz pold + polz REV1 + polz

cis-syn TT + (a) – (b) – (c)    – (c)      

(6-4) TT – (a) – (b) – (c) + (d) + (c)      

Abasic site + (a) + (b) – (c) + (e) + (c) + (f) + (f)

Acetylaminofluorene 

C8-dG adduct

+ (a) + (b)               

Cisplatin intrastrand 

dG-dG adduct

+ (a) – (b)               

1,N6-

ethenodeoxyadenosine

+ (g) + (g)               

8-oxodeoxyguanosine + (h) + (i)               

(+) BPDE-N2-dG + (j) + (i)               

(–) BPDE-N2-dG    + (i)               

Note: (a) Masutani et al. 2000; (b) Ohashi et al. 2000; (c) Johnson et al. 2000; (d) Johnson et al. 2001b; (e) Yuan et al. 2000; 

(f) Haracska et al. 2001; (g) Levine et al. 2001; (h) Haracska et al. 2000; (i) Zhang et al. 2000a; (j) Zhang et al. 2000b. 

BPDE-N2-dG = trans-anti-benzo[a]pyrene-N2-deoxyguanosine; dG = deoxyguanosine; TT = thymine-thymine dimer.

Figure 5.9 Model of mechanism for mammalian translesion synthesis

Note: Replicative polymerase d encounters DNA lesion (open circle) in template, progression of DNA synthesis is blocked, and d

temporarily disengages. Y family polymerases (h, k, i, and REV1) are recruited to the sites, and 1 or more polymerases catalyze the 

insertion of a nucleotide opposite a lesion and the extension from the newly generated terminus. With some DNA lesions, the Y family 

polymerases can insert a nucleotide (N), but further extension is inhibited. Then, the second translesion polymerase, z, catalyzes the 

extension step. After translesion synthesis, d resumes replication.
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unusual base pairs (Trincao et al. 2001). This structural 

feature could explain the low fidelity of DNA synthesis on 

a normal DNA template. 

In vitro experiments on translesion synthesis using 

purified polymerases reveal that each polymerase catalyzes bypass synthesis across various lesions with a different efficiency and fidelity (Table 5.7). The current model 

of the mechanism for mammalian translesion synthesis 

is illustrated in Figure 5.9. When a replicative DNA polymerase is inhibited by a lesion, translesion synthesis can 

be completed by the action of one polymerase or by the 

cooperation of two polymerases (Prakash and Prakash 

2002). Among these polymerases, polz is unique because it 

has low ability to insert a nucleotide opposite a lesion but 

is efficient at extending from unmatched terminal pairs 

(Johnson et al. 2000). Therefore, researchers think that 

this polymerase plays a role mainly in extending from a 

terminus opposite a lesion where another polymerase has 

inserted a nucleotide and the further extension is blocked. 

Factors in Outcome of Translesion Synthesis

Many studies reveal that the efficiency and fidelity 

of translesion synthesis depend on the host (Moriya et al. 

1994, 1996). Some DNA adducts miscode in one host (human cells) but not in another (E. coli), and the reverse also 

occurs (Moriya et al. 1994; Pandya and Moriya 1996). This 

finding underscores the importance of evaluating translesion events in the appropriate host: human cells. The discrepancy most likely reflects the difference in the activity 

of the translesion polymerases involved.

Sequence context also plays an important role in 

determining the outcome of translesion synthesis. Generally, a DNA adduct in iterated sequences, such as 

monotonous repeats (e.g., GGGGG) and dinucleotide repeats (e.g., GCGCGC), tends to cause frameshift mutations 

because these sequences misalign easily (Benamira et al. 

1992). However, the same adduct induces base-substitution mutations in a different sequence context (Moriya et 

Table 5.8 Mutational specificity of selected DNA adducts derived from tobacco smoke

Study DNA adduct Mutation specificity

Loechler et al. 1984

Dosanjh et al. 1991

Pauly and Moschel 2001

O6-methyldeoxyguanosine G→A

Pauly et al. 2002 O6-[4-oxo-4-(3-pyridyl)butyl]-deoxyguanosine G→A

Dosanjh et al. 1991

Pauly and Moschel 2001

O4-methylthymidine T→C

Wood et al. 1990

Moriya 1993

8-oxodeoxyguanosine G→T

Kanuri et al. 2002

Yang et al. 2002

1,N2-propanodeoxyguanosine from acrolein G→T

Moriya et al. 1994 3,N4-ethenodeoxycytidine C→A, T

Pandya and Moriya 1996 1,N6-ethenodeoxyadenosine A→G, T

Lawrence et al. 1990

Cabral Neto et al. 1994

Gibbs and Lawrence 1995

Apurinic/apyrimidinic sites AP→T, A, G

Moriya et al. 1996

Page et al. 1998

Benzo[a]pyrene-7,8-diol-9,10-epoxide-N2-deoxyguanosine G→T, A, C

Page et al. 1999 Benzo[a]pyrene-7,8-diol-9,10-epoxide-N6-deoxyadenosine A→T

Verghis et al. 1997 4-aminobiphenyl-C8-deoxyguanosine G→C
Surgeon General’s Report

272 Chapter 5

al. 1994). Sequence context influences base-substitution 

events (Moriya et al. 1996; Page et al. 1998) and translesion efficiency (Latham et al. 1993) (see “Benzo[a]

pyrene-7,8-Diol-9,10-Epoxide-N2-Deoxyguanosine stereoisomers” later in this chapter).

Thus, translesion events are determined by the 

interplay between a DNA adduct, its sequence environment, and the DNA polymerase involved. This finding 

underscores the importance of conducting experiments 

with use of a proper sequence context and host. 

Conversion of Cigarette-Smoke-Induced 

DNA Adducts to Mutations

Conversion of DNA adducts induced by cigarette 

smoke to mutations is summarized in Table 5.8. The discussion that follows provides additional details.

O6-Pyridyloxobutyl-Deoxyguanosine

O6-POB-deoxyguanosine is formed by a pyridyloxobutylating metabolite of the tobacco-specific N-nitrosamines NNK and NNN and is removed by AGT. Therefore, 

in the presence of this repair enzyme, the adduct induced 

only a moderate miscoding frequency. The resulting 

mutations were G→A transitions. In the absence of AGT, 

the miscoding frequency markedly increased to more than 

90 percent (Pauly et al. 2002). The results were similar in 

E. coli and human cells. These results indicate that the 

frequency of miscoding for this adduct is high. The DNA 

polymerase involved almost exclusively inserts deoxythymidine monophosphate opposite the adduct, leading to 

G→A transitions. Thus, repair by the alkyltransferase is 

extremely critical to the avoidance of mutation induction 

by this adduct. The biologic characteristics of this adduct 

are similar to those of O6-methyldeoxyguanosine (Pauly 

and Moschel 2001). The DNA polymerase that catalyzes 

the translesion synthesis and the bypass efficiency of this 

synthesis remain to be determined. 

O6-Methyldeoxyguanosine 

and O4-Methylthymidine

The O6-methyldeoxyguanosine and O4-methylthymidine adducts induce mutations by stable pairing 

to thymidine (Dosanjh et al. 1993) and deoxyguanosine 

(Toorchen and Topal 1983), respectively. Accordingly, 

their miscoding potentials are high (Dosanjh et al. 1991; 

Pauly and Moschel 2001) and are similar to those of O6-

POB-deoxyguanosine. MMR acts on base pairs containing 

O6-methyldeoxyguanosine after replication (Branch et al. 

1993) and leads to cell death as a result of a futile MMR. 

Therefore, MMR mutants are more resistant to methylating agents (Branch et al. 1993) and are more prone to 

mutation after exposure to these agents (Pauly and Moschel 2001).

8-Oxodeoxyguanosine

8-oxodeoxyguanosine is a representative adduct 

formed by oxidative damage to DNA, and researchers have 

extensively studied its mutagenic properties and repair 

mechanisms (Grollman and Moriya 1993). The miscoding property of this adduct derives from its propensity to 

assume a syn conformation and to pair easily with deoxyadenosine (anti), which leads to G→T transversions. To 

avoid this mutation induction, cells have developed an 

elaborate postreplication BER mechanism that specifically removes misinserted deoxyadenosine by the action 

of the DNA glycosylase, adenine-DNA-glycosylase (Parker 

and Eshleman 2003). Subsequently, when deoxycytidine 

monophosphat) is inserted opposite the adduct, 8-oxodeoxyguanosine is removed by another BER initiated by 

OGG1, and a G:C pair is restored. 

This adduct is also formed in the nucleotide pool. 

When 8-oxodeoxyguanosine-triphosphate is inserted 

opposite a deoxyadenosine template, the misinsertion 

leads to an A→C transition. To avoid this event, the cellular enzyme MTH1 converts 8-oxodeoxyguanosine triphosphate to 8-oxodeoxyguanosine monophosphate, which is 

no longer a substrate for DNA synthesis. Thus, cells have 

developed several layers of defense mechanisms against 

8-oxodeoxyguanosine. Therefore, the apparent frequency 

of mutation induction by this adduct is low in normal 

cells. However, when MYH is inactivated, the frequency 

of G→T transversions increases drastically (Moriya and 

Grollman 1993; Hashimoto and Moriya, unpublished data) 

and mutations in this gene lead to a high incidence of 

spontaneous human colon cancer (Al-Tassan et al. 2002). 

1,N2-Propanodeoxyguanosine

Various unsaturated α,β-aldehydes, such as acrolein 

and crotonaldehyde, produce the DNA adduct PdG. Acrolein produces two positional isomers: 8-(g-) and 6-(α-) 

xy hydroxyl PdG. When positioned in double-stranded 

DNA, the α adduct is more genotoxic than the g adduct. 

The α adduct has significantly more blocking effects, and 

the g adduct, but not the α adduct, miscodes with G→T 

transversions at a frequency of approximately 10 percent 

(Yang et al. 2002). Most of the miscoding events were 

induced by polh (Yang et al. 2003). Structural studies 

reveal that the exocyclic ring of the g adduct, but not the 

α adduct, opens in a manner similar to that of the malondialdehyde-induced deoxyguanosine adduct (Mao et al. 

1999) when paired to deoxycytidine (de los Santos et al. 

2001). This finding may account for the weaker blocking 

effect and the lack of miscoding, because the ring-opened 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

g adduct pairs nicely to deoxycytidine with the WatsonCrick type of (anti-anti) conformation. When the g

adduct is inserted in single-stranded DNA and replicates 

in mammalian cells, the resulting structure miscodes by 

inducing G→T transversions (Kanuri et al. 2002). In addition, the ring-opened deoxyguanosine adduct forms interstrand G-G cross-links in the sequence 5’CpG (Kozekov et 

al. 2003), which may also contribute to the genotoxicity 

of acrolein.

Exocyclic Etheno Adducts

Although the etheno adduct 1,N6-ethenodeoxyadenosine miscodes efficiently in simian kidney cells, it 

does not miscode in E. coli (Pandya and Moriya 1996). This 

finding emphasizes the importance of the host. The finding is probably attributable to the difference in the fidelity 

of the DNA polymerase involved in translesion synthesis. 

The etheno adduct 3,N4-ethenodeoxycytidine miscodes 

efficiently in both hosts (Moriya et al. 1994).

Apurinic/Apyrimidinic Sites

AP sites are generated by the cleavage of a glycosidic bond between a base and a sugar in DNA for various 

reasons such as (1) the action of a DNA glycosylase and 

(2) modifications to a base that destabilize the glycosidic 

bond. These sites do not convey any coding information. 

Deoxyadenosine is often inserted opposite these sites in 

E. coli (Lawrence et al. 1990), which is known as “the A 

rule” (Strauss 1991). However, this rule does not appear 

to be applicable in mammalian cells: various bases are 

inserted opposite these sites in those cells (Cabral Neto et 

al. 1994; Gibbs and Lawrence 1995).

Benzo[a]pyrene-7,8-Diol-9,10-Epoxide-N2-

Deoxyguanosine Stereoisomers

Studies have extensively characterized the genotoxicity of different stereoisomers of BPDE-N2-deoxyguanosine (Moriya et al. 1996; Fernandes et al. 1998). 

A prominent feature is that both the surrounding DNA 

sequence and the host markedly influence miscoding frequency (Moriya et al. 1996; Fernandes et al. 1998; Page et 

al. 1998) and miscoding specificity (Kozack et al. 2000).

The major adduct, (+)-BPDE-N2-deoxyguanosine, induces 

mainly G→T and G→A transversions in 5’-TGC and 

5’-AGA sequence contexts, respectively, which researchers hypothesize is attributable to differences in adduct 

conformations in different sequence contexts (Kozack et 

al. 2000). The deoxyadenosine adduct (BPDE-N6-deoxyadenosine) also miscodes with A→T transversions (Page 

et al. 1999).

4-Aminobiphenyl-C8-Deoxyguanosine

The adduct 4-ABP-C8-deoxyguanosine barely miscodes in E. coli by inducing G→C transversions (Verghis 

et al. 1997). Because researchers observed G→T, G→A, 

and G→C mutations in an experiment that used a randomly modified single-strand DNA (Verghis et al. 1997), 

the possibilities of the effects from the sequence context 

and the involvement of other deoxyguanosine adducts, 

such as those at N2, remain to be explored. Furthermore, 

it appears that a 4-ABP-deoxyadenosine adduct induces 

A→T transversions (Lasko et al. 1988; Hatcher and Swaminathan 1995). 

Assessment of Genotoxicity of DNA Adducts

Genotoxic properties of a DNA lesion can be characterized by using chemically defined substrates. The 

genotoxicity of a DNA lesion is determined by factors 

such as the efficiency and fidelity of translesion synthesis 

and repair. For point mutations, however, the “genotoxic 

potency” of a DNA adduct can be determined by assessing 

the bypass efficiency and the miscoding potency. According to this formula, a DNA lesion that is easily bypassed 

with a high frequency of miscoding events is defined as 

a highly genotoxic DNA adduct. Furthermore, when the 

genotoxicity of a DNA lesion is assessed, the information 

on its abundance in the genome, which reflects the balance between formation and removal, should also be considered. Therefore, conceptually, the total genotoxicity of 

a DNA adduct could be estimated by determining its genotoxic potency and its abundance in DNA. 

According to these criteria, the genotoxicity of the 

8-oxodeoxyguanosine adduct, which is a unique case, 

would be high because it exists in high levels in genomic 

DNA and is easily bypassed by a DNA polymerase with a 

high miscoding frequency. However, the apparent genotoxicity is low because of the postreplication repair that 

is catalyzed by MYH. Therefore, when the postreplication 

repair is inactivated, this adduct can become a significant 

genotoxic adduct (Al-Tassan et al. 2002).

Data for the genotoxic effects of DNA lesions derived 

from tobacco smoke are scarce, and a systematic study 

is needed. Together with information on the abundance 

of each lesion, the genotoxicity of tobacco-related DNA 

adducts might be ranked by using site-specific modified 

plasmids, introducing them with the use of host cells, and 

subsequently recovering them for sequence analysis. 
Surgeon General’s Report

274 Chapter 5

Gene Mutations in Tobacco-Induced Cancer

Chromosome Instability and Loss

Lung Cancer

The detection of numerous cytogenetic changes 

provided the first link to the molecular pathogenesis of 

lung cancer. Mapping chromosomal sites for rearrangement, breakpoints, and losses revealed both common 

and distinct changes in both SCLC and NSCLC. In SCLC, 

breakpoints are commonly seen in chromosomes 1, 3, 5, 

and 17, although researchers have observed losses of the 

short arm (p) of chromosomes 3 and 17 and of the long 

arm (q) of chromosome 5 (Balsara and Testa 2002). Subsequent studies using comparative genomic hybridization 

showed that deletions on chromosomes 3p, 4q, 5q, 10q, 

13q, and 17p were common in SCLC (Petersen et al. 1997). 

In NSCLC, multiple numeric and structural changes were 

seen across many chromosomes. The most frequent sites 

(60 to 80 percent) for chromosome loss were found on 

chromosomes 3p, 6q, 8p, 9p, 9q, 17p, 18q, 19p, 21q, and 

22q (Balsara and Testa 2002). Some of the most common 

sites for chromosome loss included 3p, 9p, 13q, and 17p. 

These sites were also detected in nonmalignant bronchial epithelium of current and former smokers and were 

absent in lifetime nonsmokers (Mao et al. 1997; Witsuba et 

al. 1997). These findings strongly link tobacco exposure to 

the development of chromosome damage throughout the 

aerodigestive tract.

Identification of Tumor-Suppressor Genes

The commonality for specific regions in the genome 

to lose alleles suggested the presence of tumor-suppressor genes within these loci. The RB gene was the first 

tumor-suppressor gene linked to lung cancer (Harbour et 

al. 1988). A loss of function of this gene through either 

deletion or point mutation occurs in 90 percent of SCLCs, 

whereas few NSCLCs harbor changes in this tumorsuppressor gene (Table 5.9) (Shimizu et al. 1994). The 

most frequently inactivated tumor-suppressor gene in 

lung cancer is TP53. TP53 mutations are found in 70 

percent of SCLCs, 65 percent of SCCs, and 33 percent of 

adenocarcinomas (Greenblatt et al. 1994). (For discussion of specific mutations and their potential relationship to carcinogens in cigarette smoke, see “Relationship 

of TP53 Mutations to Smoking and Carcinogens” later in 

this chapter.)

A frequent deletion within chromosome 3p14 led 

to the identification of the FHIT gene (Zabarovsky et 

al. 2002). The most common fragile site of the human 

genome FRA3B maps in the FHIT gene and may contribute 

to the susceptibility of this locus to gene rearrangement 

induced by carcinogens in cigarette smoke. Researchers 

have observed a loss of the FHIT protein in 50 percent of 

lung cancers, but somatic mutations are uncommon in 

the FHIT gene. The epigenetic inactivation by methylation of the 5’CpG island located in the promoter region 

of FHIT represents another mechanism for inactivating 

this gene in lung cancer (see “Gene Promoter Hypermethylation in Cancer Induced by Tobacco Smoke” later in 

this chapter).

The importance of the inactivation of tumorsuppressor genes FHIT, RB, and TP53 in lung cancer is 

evident from their functions. The binding of hypophosphorylated RB to cyclin-dependent kinase (CDK) 4 or 6 

blocks transit of the RB protein through the G1/S boundary of the cell cycle. Inactivating mutations result in the 

loss of a functional hypophosphorylated protein associated with a shortening of the G1 phase of the cell cycle 

and the enhancement of cell proliferation, a hallmark of 

the cancer cell (Nevins 1992). The TP53 gene is central to 

several critical processes needed to control the response 

of the cell to exogenous stress from exposure to cigarette smoke. This gene functions as a transcription factor 

within several pathways and as a sensor of DNA damage 

(Robles et al. 2002). Thus, the TP53 gene has an important 

role in cell-cycle checkpoints, DNA repair, apoptosis, and 

senescence. A loss of TP53 function is also an early event 

Table 5.9 Frequency of mutation or deletion of 

tumor-suppressor genes in lung cancer

      Frequency (%)

Gene

Chromosomal 

location

Small-cell 

lung cancer

Non-smallcell lung 

cancer

RB 13q14 90 15

TP53 17p13 70 50

CHFR 12q24 ND 6

MYO18B 22q12 ND 13

PTEN 10q23 9 17

LKB1/STK11 19p13 ND 35

Note: ND = not determined.
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

in the genesis of SCC that occurs in bronchial dysplasia 

(Sozzi et al. 1992; Bennett et al. 1993). Studies have also 

detected TP53 mutations in peripheral lung tissue from 

patients with lung cancer, a finding that supports a role 

for this gene in the early development of adenocarcinomas 

(Hussain et al. 2001). The FHIT gene induces apoptosis 

mediated by CASPASE-8 and independent of mitochondrial mediators and inhibits cell growth through interactions with the SRC protein kinase (Pekarsky et al. 2004; 

Roz et al. 2004). A loss of function of the FHIT, RB, and 

TP53, genes leads to the immortalization of bronchial 

epithelial cells, a key step in neoplastic transformation 

(Reddel et al. 1988) (see “Signal Transduction” later in 

this chapter). 

Tumor-Suppressor Genes 

Inactivated in Lung Cancer

The search for tumor-suppressor genes inactivated 

through the two-hit mechanism of the loss of one allele 

and the mutation of the remaining allele has not recently 

identified any genes with a frequency of inactivation 

approaching that seen for the RB and TP53 genes. The 

discussion that follows describes the involvement of several genes and their functions in subsets of lung cancer 

(Table 5.9). The mitotic checkpoint gene CHFR, which 

functions in early prophase to regulate chromosome 

condensation, was mutated in 3 of 53 lung carcinomas (Mariatos et al. 2003). Studies found three somatic 

mutations in the proapoptotic gene CASPASE-8 in 2 of 30 

lung tumors (Hosomi et al. 2003). MYO18B is a candidate 

tumor-suppressor gene at chromosome 22q12. Of 46 primary NSCLCs, 6 contained somatic mutations within this 

gene. Restoring MYO18B function in cell lines inhibited 

anchorage-independent growth, thus supporting its function as a tumor-suppressor gene in lung cancer (Nishioka 

et al. 2002).

The PTEN gene is located on chromosome 10. Its 

gene product is phosphatidylinositol 3’-phosphatase, a 

protein tyrosine phosphatase that uses the phosphoinositide second messenger, phosphatidylinositol 3,4,5-triphosphate (PIP3), as a physiological substrate (Maehama et al. 

2001). Researchers have identified point mutations of the 

PTEN gene in cell lines from 3 of 35 SCLCs and 3 of 18 

NSCLCs; there were two homozygous deletions in primary 

SCLCs (Forgacs et al. 1998). Mutations that impair PTEN

function result in a marked increase in PIP3 levels and in 

the constitutive activation of AKT survival, thus signaling 

pathways that in turn promote hyperplasia and tumor formation. Thus, although it is not common in lung cancer, 

a PTEN mutation or deletion profoundly affects an important signaling pathway in the cell. 

Two additional genes with poorly characterized 

functions and localized to chromosome 3p are altered 

in lung cancer through deletion or mutation. A specific 

ATG→AGG mutation in codon 50 of the ARP gene was 

seen in 8 of 20 lung cancers. In addition, researchers 

observed either exon deletion or intron insertion in the 

DLC1 gene in 11 of 30 NSCLCs (Zabarovsky et al. 2002). 

Frequent deletion involving the short arm of chromosome 

19 occurs in lung adenocarcinomas (Sanchez-Cespedes 

et al. 2001). One gene mapped to this chromosome 

region is STK11, in which germline mutations are causal 

for Peutz-Jeghers syndrome. This syndrome is characterized by a series of anomalies and increased risk for gastrointestinal and extraintestinal malignancies (Giardiello 

et al. 1987). Inactivating mutations and/or deletion of the 

LKB1/STK11 protein were described in about one-third of 

primary adenocarcinomas (Sanchez-Cespedes et al. 2002; 

Ji et al. 2007), and these abnormalities were closely associated with mutation of the KRAS oncogene in the same 

tumors (Ji et al. 2007; Matsumoto et al. 2007). The STK11

gene may function as a growth-inhibiting gene that is 

activated through phosphorylation by the ATM gene, 

which senses DNA damage (Sapkota et al. 2002), and acts 

through pathways dependent or independent of the P53 

protein to suppress invasion and metastasis (Karuman et 

al. 2001; Upadhyay et al. 2006; Ji et al. 2007). In addition 

to inactivating by mutation, epigenetic silencing by promoter hypermethylation has emerged as a major mechanism for inactivating many genes in lung cancer, some of 

which are described here (e.g., MYO18B). (For a detailed 

discussion, see “Gene Promoter Hypermethylation in 

Cancer Induced by Tobacco Smoke” later in this chapter.)

Activation of Oncogenes in Lung Cancer

Oncogenes encode proteins that influence cell 

cycling and promote cancer. They are usually “gain-offunction” mutations of normal genes. Researchers see 

KRAS gene mutations in approximately 30 to 40 percent 

of adenocarcinomas but rarely in SCCs, SCLCs, or lung 

tumors from nonsmokers (Slebos et al. 1990; Westra et 

al. 1996; Ahrendt et al. 2003). Mutations are localized to 

codons 12, 13, and 61. More than 85 percent occur within 

codon 12. Nearly 70 percent of the mutations are G→T 

transversions within codon 12 that change a glycine 

codon (GGT) to valine (GTT) or cysteine (TGT). Mouse 

lung tumors induced by B[a]P and other PAHs show exclusively G→T transversions in codon 12 of the Kras gene. 

These findings support the hypothesis that activation of 

this oncogene in lung tumors results from DNA damage 

leading to base mispairing of these deoxyguanosines. In 

vitro studies have demonstrated that DNA adducts formed 
Surgeon General’s Report

276 Chapter 5

from the metabolism of B[a]P, NNK, and reactive oxygen 

species can all lead to G→T transversions (Table 5.8) (You 

et al. 1989; Belinsky et al. 1992). Thus, the activation of 

carcinogens in tobacco smoke and the pulmonary inflammation that ensues from exposure to particulate matter 

together can lead to activation of the KRAS oncogene. 

Studies detected KRAS gene mutations in 39 percent 

of atypical alveolar hyperplasia, a putative precursor to 

adenocarcinoma (Slebos et al. 1996). A similarity in the 

percentage of precursor lesions and tumors containing 

KRAS mutations supports the importance of this gene in 

tumor progression in a subset of adenocarcinomas. 

The sequence of events leading to activation of the 

RAS signal transduction pathway is well characterized 

(Lechner and Fugaro 2000). When the RAS protein is 

activated through mutations in codon 12, 13, or 61, it 

binds irreversibly to guanosine triphosphate (GTP) in 

the cell, which initiates a cascade of protein activations, 

beginning with v-raf-murine leukemia viral oncogene 1 

(RAF-1), that transmits a signal from the cell membrane 

to the nuclear transcription machinery. Ultimately, these 

signals culminate in the activation of transcription factors 

including MYC, FOS, and JUN, which in turn influence 

many cellular activities such as transcription, translation, 

cytoskeletal organization, and cell-cell interactions. This 

signal remains active until GTPase (guanosine triphosphatase) dephosphorylates GTP to guanosine diphosphate. 

Thus, a RAS oncogene mutation leads to the disruption of 

many cellular pathways and provides a strong oncogenic 

signal for neoplastic transformation (see “Signal Transduction” later in this chapter).

The MYC family of genes (C-MYC, N-MYC, and 

L-MYC) plays a prominent role in the growth of the 

developing and mature adult lung. Extensive studies have 

evaluated the expression and amplification of these genes 

in NSCLC and SCLC (Jänne and Johnson 2000). Most 

lung cancers express one or more of the MYC family of 

genes, whereas gene amplification is seen in a minority 

of primary tumors (Table 5.10). Gene rearrangements 

involving different exons are associated with amplification detected in cell lines but are uncommon in primary 

tumors (Kinzler et al. 1986; Mäkelä et al. 1991; Sekido 

et al. 1992). Mechanisms responsible for the increased 

expression of the MYC genes in the absence of gene amplification are not well understood. Increased expression 

could occur through increased activity in the RAS signaling pathway through either KRAS oncogene mutations or 

effects on the activity of genes in this pathway, such as the 

activity of mitogen-activated protein kinase (MAPK) (Jull 

et al. 2001).

Increased gene expression is common in lung cancer but often is not associated with gene amplification. 

Two genes studied extensively are EGFR and NEU (HER-2/

NEU [ERBB2]). EGFR is the receptor for the epidermal 

Table 5.10 Frequency of gene amplification and increased expression of genes in lung cancer

      Frequency (%)

Gene Tumor histology Amplification Expression

C-MYC Small-cell lung cancer 5 25

N-MYC Small-cell lung cancer 7 3

L-MYC Small-cell lung cancer 12 33

EGFR Small-cell lung cancer 0 0

HER-2/NEU Small-cell lung cancer <1 0–7

C-MYC Non-small-cell lung cancer 8 33

N-MYC Non-small-cell lung cancer 0 ND

L- MYC Non-small-cell lung cancer 3 ND

EGFR Non-small-cell lung cancer 9–25 34–62

HER-2/NEU Non-small-cell lung cancer 2–4 23–58

Note: ND = not determined.
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

growth factor and the HER-2/NEU protein, and the binding of these growth factors to this receptor is associated 

with increased DNA synthesis, cell proliferation, and differentiation. An increased expression of the EGFR gene 

was not seen in SCLCs but occurred in 34 to 62 percent 

of NSCLCs (Hirsch et al. 2003b; Suzuki et al. 2005). In 

addition, an increased expression of this gene was more 

common in SCC than in adenocarcinoma—82 versus 44 

percent (Hirsch et al. 2003b). In contrast, gene amplification was detected in 9 to 25 percent of tumors (Hirsch 

et al. 2003b; Suzuki et al. 2005). Expression of the HER2/NEU gene was seen in 23 to 58 percent of NSCLCs and 

in 0 to 7 percent of SCLCs (Shi et al. 1992; Junker et al. 

2005; Pelosi et al. 2005). Similar to EGFR, HER-2/NEU

was more commonly expressed in SCC than in adenocarcinoma, and gene amplification was rare in all tumors 

(<5 percent).

Observation of EGFR expression in 34 to 62 percent 

of NSCLCs led to the development of small molecule 

inhibitors of the tyrosine kinase domain of the wild-type 

EGFR protein (Fukuoka et al. 2003; Herbst and Bunn 2003; 

Lynch et al. 2004; Amann et al. 2005; Baselga and Arteaga 

2005). The clinical response of approximately 10 percent 

of European patients and 30 percent of patients from 

Japan to treatment with the EGFR inhibitors gefitinib or 

erlotinib led to a search for the mechanism responsible 

(Kris et al. 2003; Pérez-Soler et al. 2004). The outcome of 

these studies was the identification of somatic mutations 

in the tyrosine kinase domain of the EGFR gene in most 

patients who had demonstrated a clinical response to the 

drugs (Lynch et al. 2004; Amann et al. 2005). In addition, 

recent studies suggest that the EGFR copy number and 

KRAS mutation may also be involved in determining a 

response to gefitinib and erlotinib. Subsequent studies 

have sequenced the EGFR gene in thousands of NSCLCs 

from patients in Asia, Europe, and the United States. These 

studies found that most mutations were due to either a 

deletion involving exon 19 or a missense mutation in exon 

21. In addition, mutations were two to three times more 

likely in women than in men and three to five times more 

likely in nonsmokers than in current or former smokers (Johnson and Jänne 2005). Finally, the prevalence of 

mutations was 10 percent in tumors of patients from 

Europe and the United States compared with 30 percent 

in tumors from persons of Asian background residing in 

Japan and Taiwan. 

The BRAF gene encodes a RAS-regulated kinase that 

can mediate cell growth. BRAF mutations were found in 

5 of 179 NSCLCs and are almost exclusively confined to 

adenocarcinomas (Brose et al. 2002; Naoki et al. 2002). 

Although the mutation is relatively uncommon in lung 

cancer, its location in either exon 11 or exon 15 altered the 

phosphorylation of BRAF by AKT (Guan et al. 2000). The 

disruption of AKT-induced BRAF inhibition could contribute to malignant transformation. 

Oncogene Activation, Tumor-Suppressor Gene 

Inactivation, and Lung Cancer Survival

Researchers have studied the prognostic impact of 

commonly altered genes in lung cancer. The effect of an 

activated KRAS oncogene on survival was assessed in 69 

patients, including 48 with stage I adenocarcinoma that 

was completely resected (Slebos et al. 1990). Twelve of 19 

patients with a KRAS mutation died within the followup period (median, 47 months) compared with 22 of 50 

patients with a tumor negative for the KRAS oncogene. 

This significant difference in survival was observed even 

though patients with a KRAS mutation had a less advanced 

disease than those with no mutation. All seven patients 

with stage III disease were negative for mutations. Rosell 

and colleagues (1993) conducted a similar study of largely 

stage I resected adenocarcinomas that again revealed a 

reduced survival rate independent of lymph node status 

for patients whose tumor contained a mutated KRAS

gene. In contrast, a larger study of 127 adenocarcinomas 

found no difference in survival by KRAS mutation status 

(Keohavong et al. 1996). Overall, data are conflicting with 

respect to KRAS mutations as prognostic factors and further research is needed (Aviel-Ronen et al. 2006).

Studies have examined the effect of TP53 gene 

mutations on prognosis in both early- and late-stage lung 

cancers. After four years of follow-up, the hazard ratio for 

106 patients with stage I resected NSCLC with a TP53

mutation was 2.8 for death, compared with patients who 

had a wild-type gene (Ahrendt et al. 2003). Four years 

after surgery, 78 percent of patients with no TP53 mutation and 52 percent with a TP53 mutation were alive. A 

previous study by Tomizawa and colleagues (1999) found 

a similar survival benefit for patients with stage I NSCLC 

and no TP53 mutations, which also confer a poor clinical 

outcome for those with advanced NSCLC. Independent of 

chemotherapy or supportive care, median survival duration for patients with stage III or IV NSCLC with or without a TP53 mutation was 17 versus 39 weeks, respectively 

(Murakami et al. 2000). Recently, a study of 420 patients 

with primary head and neck cancer (Poeta et al. 2007) 

showed that disruptive TP53 mutations in tumor DNA are 

associated with reduced survival after surgical treatment 

of SCC of the head and neck (hazard ratio, 1.7; 95 percent

CI, 1.2–2.4; p = 0.003).

Together, it is apparent that the inactivation of the 

TP53 tumor-suppressor gene and the activation of the 

KRAS oncogene in NSCLCs and other tumors are correlated with exposure to cigarette smoke and contribute 
Surgeon General’s Report

278 Chapter 5

to a phenotype that reduces survival in both early and 

advanced stages of the disease.

Relationship of TP53 Mutations 

to Smoking and Carcinogens

TP53 Mutations in Smoking-Associated 

Lung Cancers

TP53 gene mutations are found in approximately 40 

percent of human lung cancers; TP53 is the most commonly mutated tumor-suppressor gene in lung cancer 

(see “Identification of Tumor-Suppressor Genes” earlier in 

this chapter). These mutations are generally more common in smokers than in nonsmokers (Greenblatt et al. 

1994; Hernandez-Boussard and Hainaut 1998; Pfeifer et 

al. 2002). One study shows that the relative risk of having 

a TP53 mutation in lung cancer was up to 13 times higher 

in lifetime heavy smokers than in lifetime nonsmokers 

(Le Calvez et al. 2005). G→T transversions are commonly 

observed in smoking-associated lung cancers (Greenblatt 

et al. 1994; Hainaut and Hollstein 2000; Hainaut and 

Pfeifer 2001). The frequency of G→T transversions in lung 

cancers from smokers is higher than that for lung cancers 

and most other cancers in nonsmokers (Greenblatt et al. 

1994; Husgafvel-Pursiainen and Kannio 1996; HernandezBoussard and Hainaut 1998; Bennett et al. 1999; Hainaut 

and Pfeifer 2001). Mutational patterns for lung cancers 

from smokers and nonsmokers are shown in Figure 5.10. 

The difference between 28.9 percent G→T transversion 

mutations in “designated smokers” (i.e., smoking status 

Figure 5.10 Patterns of TP53 gene mutations and percentage of G→T transversion mutations in human lung 

cancers

Source: Data are from the R9 version (July 2004) of the International Agency for Research on Cancer TP53 mutation database (IARC 

2006).

Note: Cell lines and metastatic cancers were excluded, as well as cancers with defined exposures other than tobacco (e.g., asbestos, 

radon, mustard gas, and air pollution) (see database Web site for specifications of exposure data). Nonsmokers included a series of 21 

mutations (Le Calvez et al. 2005) not included in the database, in addition to 165 database entries. Data from Gao et al. 1997 were 

excluded (see Hainaut and Pfeifer 2001 for detailed selection criteria). N = total number of mutations. 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

indicated in literature) and 13.4 percent G→T mutations 

in nonsmokers has high statistical significance (p <0.001, 

χ2 test). The frequency of G→T transversions is higher in 

lung cancer tumors than in other tumors, except for liver 

cancers associated with geographic areas with evidence 

of food contamination from aflatoxins (Greenblatt et 

al. 1994). 

In most internal cancers not strongly linked to 

smoking, such as breast, brain, and colorectal, the frequency of G→T mutations is 8 to 10 percent (Figure 

5.10). Nonsmokers have a higher percentage of G→A transitions (42.5 percent) than do smokers (27.9 percent), a 

difference that is also statistically significant. Figure 5.10 

includes categories of both designated smokers and “all 

lung cancer cases minus nonsmokers.” This category 

is based on the knowledge that, overall, 90 percent of 

these lung cancers occur in smokers (Proctor 2001). The 

proportion of G→T transversions, as well as the overall 

mutation pattern for all persons with lung cancers, 

except nonsmokers, is similar to observations of researchers for designated smokers (Figure 5.10). The difference 

in G→T transversions in smokers versus nonsmokers 

may be attributable to bias in the database used, which 

pools data from studies that differ in aims, size, and methods for ascertaining smoking status. However, in a more 

recent study of a series of 21 mutations that was designed 

to address this possibility, TP53 gene mutations were 

found in 27.5 percent of current smokers, 15.8 percent of 

former smokers, and 4.8 percent of lifetime nonsmokers 

(Le Calvez et al. 2005). These observations suggest that 

the difference in G→T transversions in smokers versus 

nonsmokers may be larger than that indicated in the database, perhaps due to the misclassification in the database 

of long-term former smokers as nonsmokers. 

To address the issue of whether the major histologic 

types of lung cancer show differences in TP53 mutational 

patterns, researchers analyzed the IARC TP53 mutation 

database separately for these tumors (Figure 5.11). The frequencies of G→T transversions in the TP53 database were 

31.4 percent in adenocarcinomas, 27.1 percent in SCCs, 

27.5 percent in SCLCs, and 34.7 percent in large-cell carcinomas. Furthermore, the global mutation patterns were 

similar in the two main histologic types: adenocarcinoma 

and SCC. Thus, the different types of lung cancer in smokers all show an excess of G→T transversions compared 

with cancers unrelated to exposure to tobacco smoke. 

TP53 mutations do not occur at random along the 

coding sequence. They are typically clustered at mutation 

“hot spots,” which are within the DNA binding domain 

of the TP53 protein and span codons 120 to 300. Figure 

5.12 shows the concordance of codon distribution of G→T 

transversions (upper panel) along the TP53 gene in lung 

cancer with the distribution of adducts in this gene in 

bronchial epithelial cells treated with BPDE. Hot spots 

of G→T mutations in cancers of the brain, breast, and 

colon differ from those in lung cancers (Pfeifer et al. 2002). 

The codons containing mutation hot spots are important 

because they may allow determination of which carcinogen caused the mutation. However, hot spot codons may 

exist solely as a consequence of phenotypic selection in 

tumors. To address this issue, studies have compared the 

mutational events in different types of cancers at a number of common hot spot codons. The major lung cancer 

mutation hot spots at codons 158, 245, 248, and 273 are 

commonly G→T transversions in lung cancer but are 

generally other mutation types (almost exclusively G→A) 

in other internal tumors not associated with smoking 

(Pfeifer et al. 2002). 

G→T Transversions in Lung Cancer

The major product of the diol epoxide BPDE reaction with DNA is BPDE-N2-deoxyguanosine, which 

induces mainly G→T transversions, depending on the 

sequence context, after a DNA polymerase carries out 

error-prone translesion synthesis past this adduct (Eisenstadt et al. 1982; Chen et al. 1990; Ruggeri et al. 1993; 

Yoon et al. 2001) (see “Conversion of DNA Adducts to 

Mutations” earlier in this chapter). Using the UvrABC 

incision method in combination with a ligation-mediated 

polymerase chain reaction (LMPCR), scientists mapped 

the distribution of BPDE and other PAH diol epoxide 

adducts at the nucleotide level along exons of the TP53

gene in normal human bronchial epithelial cells treated 

with diol epoxide (Denissenko et al. 1996; Smith et al. 

2000). Frequent adduct formation occurred at guanine positions in codons 156, 157, 158, 245, 248, and 

273. These positions of preferential formation of PAH 

adducts are major mutational hot spots in human lung 

cancers (Figure 5.12). The only exception is codon 156, 

where G→T substitution commonly results in a phenotypically silent mutation and is therefore not selected during tumorigenesis. 

Researchers analyzed the distribution of BPDE-N2-

deoxyguanosine within TP53 exons by using stable isotope 

labeling LC-electrospray ionization tandem MS (Tretyakova et al. 2002; Matter et al. 2004). In this approach, 

specific guanine nucleobases within TP53 gene sequences 

were labeled with 15N so the BPDE adducts originating 

from these positions could be distinguished from the 

lesions formed at other sites. Researchers observed an 

excellent agreement with the data from the UvrABCLMPCR method (Denissenko et al. 1996). All four diastereomers of BPDE-N2-deoxyguanosine were formed 

preferentially at the frequently mutated TP53 codons 157, 

158, 245, 248, and 273. The contributions of individual 
Surgeon General’s Report

280 Chapter 5

diastereomers to the total adducts at a given site varied 

but were highest (70.8 to 92.9 percent) for (+)-transBPDE-N2-deoxyguanosine (Matter et al. 2004). 

A mechanistic basis for the selectivity of formation of diol epoxide–DNA adducts in the TP53 gene is the 

enhancement of adduct formation by 5-methylcytosine 

bases present at CpG dinucleotide sequences (Denissenko 

et al. 1997; Chen et al. 1998; Weisenberger and Romano 

1999; Tretyakova et al. 2002; Matter et al. 2004). All CpG 

sequences in TP53 coding exon 5 through exon 9 were 

completely methylated in all of the tissues examined, 

including the lung (Tornaletti and Pfeifer 1995). In the 

TP53 gene of lung cancers, the five major G→T mutational hot spots at codons 157, 158, 245, 248, and 273 

(Figure 5.12) consisted of methylated CpGs (Yoon et al. 

2001). Methylation at CpG sites may increase the binding 

of planar carcinogenic compounds at the intercalation step 

through the hydrophobic effect of the methyl group that 

can stabilize intercalated adduct conformations (Zhang 

et al. 2005a). However, the precise mechanism by which 

cytosine methylation at CpG sites enhances carcinogen 

binding and mutagenesis still needs to be determined. In 

contrast, the presence of 5’-neighboring 5-methylcytosine 

inhibited formation of guanine adducts by NNK metabolites (Rajesh et al. 2005). 

Studies show that the preferential formation of 

BPDE adducts at methylated CpG sites is reflected in 

the strongly enhanced mutagenesis at CpG sequences 

after cells were treated with BPDE. This finding was demonstrated with three different mutated reporter genes, 

Figure 5.11 Patterns of TP53 gene mutations and percentage of G→T transversion mutations in different histologic 

types of lung cancer

Source: Data are from the R9 version (July 2004) of the International Agency for Research on Cancer TP53 mutation database (IARC 

2006).

Note: Cancers were classified according to International Classification of Diseases, Tenth Revision (ICD-10), World Health Organization 1994. The data set excluded lung cancers from nonsmokers. Cell lines and cancers metastatic to the lung were excluded, as well 

as all cancers with defined exposures other than tobacco (e.g., asbestos, radon, mustard gas, and air pollution). ADC = adenocarcinoma (ICD C34-8140/3); LCC = large-cell carcinoma (ICD C34-8012/3); N = total number of mutations; SCC = squamous cell carcinoma 

(ICD C34-8070/3); SCLC = small-cell lung carcinoma (ICD C34-8041/3).
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including two chromosomal genes with methylated CpG 

sequences (Yoon et al. 2001).

Methylated CpG sites are preferentially modified 

by several carcinogens, including aromatic amines and 

aflatoxins (Chen et al. 1998). However, the exact range of 

compounds that target methylated CpGs is not known. 

In one study, researchers did not observe a preferential 

mutagenesis at methylated CpGs by the aromatic amine 

4-ABP (Besaratinia et al. 2002). G→T transversions 

resulting from 8-oxodeoxyguanosine are not specifically targeted to methylated CpG sequences (Lee et al. 

2002a). A more recent study demonstrated that the DNA 

adduction profile of acrolein in the P53 gene was similar 

to that of BPDE and other PAH diol epoxides, indicating 

that this α,β-unsaturated aldehyde reacts at methylated 

CpG sites and, because of its high concentration in cigarette smoke compared with that of PAHs, could contribute to the TP53 mutations observed in lung tumors from 

smokers (Feng et al. 2006).

Hussain and colleagues (2001) have shown that 

exposing bronchial epithelial cells to BPDE produces G→T 

transversions in the TP53 gene at lung cancer hot spot 

codons 157, 248, and 249. Nontumorous lung tissues from 

smokers with lung cancer carried a high TP53 mutational 

Figure 5.12 Concordance between codon distribution of G→T transversions along TP53 gene in lung cancers (top) 

and distribution of adducts of benzo[a]pyrene-7,8-diol-9,10-epoxide (BPDE)–DNA adducts in bronchial 

epithelial cells (bottom)

G→T Transversions

2

4

6

8

10

245 157

158

248

273

249

0.4

0.6

0.8

1.0

BPDE Adducts

156

157

158

245

248 273

 

0.2

% of all mutations Relative adduct frequency

Source: Adduct data were quantitated from Denissenko et al. 1996 and Smith et al. 2000. 

Note: Distribution of G→T mutations is shown along the TP53 coding sequence, and “hot spot” codons for major mutations are indicated. Mutation data from the International Agency for Research on Cancer TP53 mutation database were used. Cell lines and cancers 

metastatic to the lung were excluded, as well as all cancers with defined exposures other than tobacco (e.g., asbestos, radon, mustard 

gas, and air pollution). Length of bars indicates relative adduct frequency at major hot spots for adducts. For adducts of BPDE, the 

strongest binding site has a value of 1. Sites with values less than 0.2 are not shown. Numbers correspond to TP53 codon numbers.
Surgeon General’s Report

282 Chapter 5

Figure 5.13 Patterns of TP53 gene mutations and percentage of G→T transversions in smoking-associated cancers 

other than lung cancer

Source: Data are from R9 version (July 2004) of International Agency for Research on Cancer TP53 mutation database 

(IARC 2006). 

Note: Oral cancers include cancers of oropharynx, hypopharynx, gum, palate, floor of mouth, and tongue. Cases with defined 

exposures other than tobacco (e.g., asbestos, radon, mustard gas, and air pollution) were excluded. ADC = adenocarcinoma; 

N = total number of mutations; SCC = squamous cell carcinoma.
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load at these codons, even when another TP53 mutation 

was present in the tumor itself. DeMarini and colleagues 

(2001) studied TP53 and KRAS mutations in lung tumors 

from Chinese women who were nonsmokers and whose 

tumors were associated with exposure to smoky coal 

containing high levels of PAHs and probably other compounds such as acrolein. The tumors showed a high percentage of mutations that were G→T transversions in 

the KRAS oncogene (86 percent) or the TP53 gene (76 

percent). In the TP53 gene, the mutations clustered at 

the CpG-rich codons 153 through 158 and at codons 249 

and 273. 

The site specificity of mutagenesis by PAH diol epoxides implies that targeted adduct formation, in addition to 

phenotypic selection, is responsible for shaping the TP53

mutational spectrum in lung tumors. According to the 

IARC TP53 mutation database, more than 80 percent of 

G→T transversions in lung cancers are targeted to guanines on the nontranscribed DNA strand. This observation 

suggests that a preferential repair of DNA lesions occurs 

on the transcribed strand. DNA repair experiments analyzing BPDE adducts in the TP53 gene showed that the 

nontranscribed strand is repaired more slowly than is the 

transcribed strand (Denissenko et al. 1998). These findings support the proposal that both the initial DNA adduct 

levels and a bias in repair of DNA strands may contribute 

to the mutational spectrum of the human TP53 gene in 

lung cancer. 

TP53 Gene Mutations in Other 

Smoking-Associated Cancers

Of four cancer types analyzed, only SCC of the larynx showed a strong similarity with lung cancers. Prevalence of G→T transversions was high (25.9 percent), and 

many occurred at PAH-target codons 157 and 245. A gradient in the upper respiratory tract reflects the prevalence 

of TP53 G→T transversions in cancers of smokers. This 

prevalence ranges from low in the oral cavity, to intermediate in the larynx, and high in various histologic types of 

lung cancers. The gradient may reflect the existence of an 

underlying, parallel gradient in the extent of exposure of 

respiratory tract cells to carcinogens in tobacco smoke. 

In oral cancers, studies show that the TP53 mutation load 

is proportional to the extent of smoking, with an almost 

fourfold increase in the prevalence of mutations among 

heavy smokers compared with nonsmokers (Brennan et 

al. 1995). In one study of oral and esophageal SCC, however, the frequency of G→T transversions is only slightly 

higher (16.5 and 19.6 percent, respectively) than those in 

cancers not strongly related to exposure to tobacco smoke 

(e.g., breast, colorectal, and brain cancers). The patterns 

of mutations in both oral and esophageal SCC are similar, 

perhaps reflecting the importance of common risk factors, 

such as the combined use of tobacco and alcohol, infections by human papilloma virus (Gillison and Shah 2003), 

and various lifestyle behaviors such as tobacco chewing 

or consuming scalding hot beverages, as well as similar 

histology in oral and esophageal tissues. In contrast, the 

mutation pattern is different in esophageal adenocarcinomas, with a high prevalence of G→T transversions at CpG 

sites (Figure 5.13) and a type of mutation that could be 

associated with the overproduction of reactive nitrogen 

species due to inflammation (Ambs et al. 1999). 

For bladder cancer, the mutation pattern shows an 

unusually high prevalence of G→A transitions at non-CpG 

sites. These mutations are not distributed at random, and 

bladder-specific mutation hot spots can be seen at codons 

280 and 285, according to the IARC TP53 database. Both 

codons occur within the same primary sequence context 

(5’AGAG), which raises the possibility that this sequence 

may be a preferential target site for a carcinogen involved 

in bladder carcinogenesis. However, aromatic amines, 

a potent class of bladder carcinogens in tobacco smoke, 

produce mainly G→T mutations (Besaratinia et al. 2002). 

Limitations to the Study of TP53 Mutations 

and Smoking-Induced Cancer

Although the study of mutations in the TP53 gene 

provides potentially useful leads for understanding mechanisms of tobacco carcinogenesis, this approach also has 

limitations. As already mentioned, various carcinogenDNA adducts can produce G→T transversions and even 

similar spectra of mutations. In addition, most of this 

research is not population based, and the studies may 

be biased with respect to the stage of lung cancer represented. Finally, lack of a mutation in the TP53 gene does 

not necessarily mean that the tumor is not related to 

smoking, because other uncharacterized changes could 

have occurred.
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284 Chapter 5

Loss of Mechanisms for Growth Control

Signal Transduction

Introduction

Normally, cell signaling is very tightly regulated and 

begins with the transduction of the signal through a membrane receptor. The signal is conveyed through a series of 

intracellular proteins, and the result is the regulation of 

cellular processes including proliferation and apoptosis. 

In lung cancer cells, the processes governing these events 

are frequently deregulated by DNA-damaging mutations 

induced by cigarette smoke or other alterations in the 

molecules of numerous signaling pathways. The balance 

between mechanisms leading to apoptosis (proapoptotic) 

and those suppressing apoptosis (antiapoptotic) or suppressing increased proliferation will have a major impact 

on lung tumor growth. Identifying and targeting signaling 

pathways that lead to therapeutic resistance could help to 

neutralize a patient’s resistance to standard therapies. 

Apoptosis

Apoptosis was first described in 1972 (Kerr et al. 

1972). The term “apoptosis” is from the Greek word for 

“falling off.” Apoptosis is a natural process that consists of 

a well-orchestrated cascade of distinct biologic and histologic events (Kerr et al. 1972). These events are critical for 

eliminating injured or genomically unstable cells while 

minimizing damage to surrounding normal cells (Martin 

2002). The induction of apoptosis prevents the malignant 

growth of cancer cells (Rich et al. 2000). The deregulation 

of the mechanisms governing apoptosis is a distinctive 

characteristic of most cancer cells (Hanahan and Weinberg 2000).

Apoptosis is characterized by morphologic features 

including membrane blebbing, cell shrinking, and chromosomal condensation. Apoptosis is generally believed 

to occur through two “effector” mechanisms: extrinsic 

(death receptor mediated) and intrinsic (mitochondrial 

mediated) (Hengartner 2000). The extrinsic pathway is 

regulated by binding a “death receptor molecule” to the 

cancer cell’s membrane receptor (i.e., death receptor). 

The intrinsic pathway is mediated by rendering the mitochondrial membrane permeable, a phenomenon directly 

influenced by the ratio of the interaction of proapoptotic 

and antiapoptotic proteins. In general, researchers believe 

that the inactivation of apoptosis through the intrinsic 

pathway is the primary mechanism through which DNAdamaging agents from tobacco smoke act to enhance 

the survival of lung cancer cells, which is the focus of 

this section. 

Key Apoptotic Regulators

One or more pathways may lead to apoptosis. Stress 

signals stimulate a pathway that activates proteins to 

respond to DNA damage. These proteins subsequently 

phosphorylate, activate, and stabilize the P53 protein. The 

activated P53 protein drives the transcription of genes 

associated with cell-cycle arrest, DNA repair, and apoptosis. These genes include the BCL-2 family of proteins, 

which consists of both proapoptotic and antiapoptotic 

members. The BCL-2 family of proteins interacts with the 

outer mitochondrial membrane to regulate the release of 

cytochrome c, which results in the activation of aspartyl 

and cysteine proteases (caspases) (Igney and Krammer 

2002). The caspases are crucial executioners of apoptosis 

(Meier et al. 2000; Reed 2000). Once stimulated, the caspases activate endonucleases that subsequently cleave the 

DNA of the targeted cell into nucleosome-sized fragments, 

which is a common characteristic of apoptosis. 

A multitude of signaling molecules mediate the 

mechanisms that govern apoptosis. An imbalance in proapoptotic and antiapoptotic signaling events contributes 

to the development and progression of lung cancer. The 

mechanisms for the deregulation of apoptosis can be 

categorized into (1) the decrease of signaling associated 

directly with the induction of apoptosis and (2) the 

increase of signaling leading to the suppression of apoptosis. This decrease may include mutations induced by 

cigarette smoke or other smoke-related mechanisms that 

activate oncogenes or inactivate tumor-suppressor proteins or other proapoptotic proteins. The increase may 

include mutations induced by cigarette smoke, certain 

kinases, other antiapoptotic proteins or transcription 

factors, or overexpression or constitutive activation of 

growth factors. The end result of this deregulation usually 

includes a profound resistance to apoptosis. 

Regulation of Tumor Suppressors and 

Proapoptotic Proteins

Decrease of important proapoptotic proteins of the 

BCL-2 family and tumor suppressors such as the P53 and 

RB proteins is a characteristic in many types of cancers, 

including lung cancer. This decrease provides lung cancer 

cells with a strong ability to resist apoptosis, which leads 

to a distinct advantage for cell survival (Figure 5.14).
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BCL-2 Family Proteins

In normal cells, stresses initiate apoptosis through 

the mitochrondrial or intrinsic pathway, and the BCL-2 

family proteins are important mediators of the apoptotic 

response. These proteins are characterized by the presence of one to four conserved BCL-2 homology (BH) 

domains. The BCL-2 family can be divided into antiapoptotic members: BCL-2, BCL-XL, and myeloid cell leukemia-1. The proapoptotic BCL-2 proteins are subdivided 

into two groups: the multidomain BAX subfamily (BAK, 

BAX, and BOK) and the BH3-only proteins (BAD, BID, 

and BIM) (Korsmeyer 1995; Hale et al. 1996; Adams and 

Cory 1998; Huang and Strasser 2000; Cory et al. 2003). 

The BCL-2 family of proteins appears to directly influence the permeability of the mitochondrial membrane to 

regulate apoptosis. 

The interaction of BAX with the mitochrondrial 

membrane causes the release of cytochrome c into the 

cytosol, where it binds to apoptotic-releasing factor 1. 

The binding of cytochrome c and apoptotic-releasing factor 1 results in the activation of cysteine-aspartic acid 

protease-9 (CASPASE-9), which is required to form the 

“apoptosome” complex that initiates apoptosis. The apoptotic response is critically dependent on the ratio of the 

expression of proapoptotic and antiapoptotic BCL-2 members (Zha et al. 1997; Korsmeyer 1999; Kroemer 1999; 

Reed 1999; Huang and Strasser 2000; Lutz 2000; Cheng 

et al. 2001; Ruvolo et al. 2001). A lack of BAX (Zhang et al. 

2000a; Schmitt and Lowe 2002) or an increase of BCL-2 

or BCL-XL (Schott et al. 1995; Walczak et al. 2000; Chipuk 

et al. 2001) suppresses apoptosis, whereas a decrease of 

BCL-XL or BCL-2 enhances apoptosis (Hayward et al. 

2003). Dimers containing BAX and BCL-2 inactivate BAX 

and therefore inhibit apoptosis. In addition, phosphorylation of the BAD protein results in its inactivation, because 

only the nonphosphorylated form of BAD can antagonize 

the antiapoptotic BCL-2 or BCL-XL at the mitochondrial 

membrane (Hermeking 2003). 

Nicotine suppresses the death of lung cancer cells 

by phosphorylation mediated by the extracellular signalregulated kinase (ERK) of BCL-2 (Heusch and Maneckjee 

1998; Mai et al. 2003). Conversely, NNK inactivates BAD 

through β-adrenergic receptors and protein kinase C 

(PKC), which promotes survival of NSCLC cells (Lahn et 

al. 2004; Jin et al. 2005). Nicotine also stimulates cell survival through the phosphorylation and inhibition of BAD 

activated by β-adrenergic-receptor–mediated AKT-, PKA-, 

and/or ERK-dependent pathways (Jin et al. 2004a). These 

studies show that BCL-2 family members are critical effectors of signaling pathways that promote cancer cell survival in response to components of cigarette smoke—in 

these cases, through direct receptor binding rather than 

DNA damage.

P53 Protein

The P53 pathway is clearly involved in cellular life 

or death. The P53 tumor-suppressor protein can induce 

the expression of BAX and additional proapoptotic members of the BCL-2 family (Miyashita and Reed 1995; Yin et 

al. 1997; Oda et al. 2000a,b; Nakano and Vousden 2001). 

In addition to having direct effects on BCL-2 family proteins, the P53 protein also increases activity of the APAF1 

gene (Robles et al. 2001), which as indicated earlier, is 

a member of the apoptosome complex and is critical for 

the activation of CASPASE-9 to initiate apoptosis (Soengas et al. 1999) (see “BCL-2 Family Proteins” earlier in 

this chapter). Although it is primarily a nuclear protein, 

P53 may function outside the nucleus by translocating 

to the mitochondria, where it interacts directly with antiapoptotic proteins such as BCL-2 and BCL-XL to induce 

apoptosis (Mihara et al. 2003). The aberrant inactivation 

of P53 leads to a deregulation of cell-cycle control and a 

suppression of many crucial proapoptotic pathways (Ford 

Figure 5.14 Tobacco-associated suppression of 

proapoptotic proteins and tumorsuppressor proteins

Note: Tobacco-associated suppression of proapoptotic proteins 

and tumor-suppressor proteins increases cell proliferation and 

resistance to apoptosis. Two major signaling pathways that are 

downregulated by DNA-damaging tobacco agents are the TP53 

protein and the proapoptotic family of BCL-2 proteins. 

APAF1 = apoptotic-releasing factor 1; BAX = BCL-2 associated 

X protein; CASPASE-9 = cysteine-aspartic acid protease-9.
Surgeon General’s Report

286 Chapter 5

and Hanawalt 1995; Wang et al. 1995a,b; Offer et al. 1999; 

Vogelstein et al. 2000; Zhou et al. 2001a). The loss of P53 

function markedly decreases the sensitivity of lung cancer 

cells to apoptosis induced by exposure to tobacco smoke 

or other stresses (Lowe et al. 1994).

Retinoblastoma Protein

Inactivation of the RB protein results in the release 

and activation of the transcription factor E2F (Flemington 

et al. 1993; Helin et al. 1993). Some E2F family members 

induce expression of the genes important in apoptosis, 

such as the P14ARF gene (DeGregori et al. 1997; Bates et 

al. 1998). The P14ARF protein is a negative regulator of 

murine double minute 2 (MDM2), a P53 binding protein. 

The inhibition of MDM2 leads to elevated P53 levels and 

apoptosis. The E2F protein can also activate proapoptotic 

BCL-2 family members and caspases (Nahle et al. 2002; 

Hershko and Ginsberg 2004). 

Regulation of Antiapoptotic Proteins and Effects

Studies document that many genes and signaling 

proteins are overexpressed or display gain-of-function 

mutations in lung cancers. These include the EGFR 

gene, signal transduction and activator of transcription, 

PKC, RAS/MAPK, phosphatidylinositol-3 kinase (PI-3K)/

AKT, PTEN, nuclear factor-kappa B (NF-kB), and COX 

(Figure 5.15). 

Figure 5.15 Protein-signaling pathways deregulated in lung cancer

Note: Many protein-signaling pathways deregulated in lung cancer represent a dense interactive network with a range of 

potential survival-enhancing effects. Tobacco- or cigarette smoke-associated activation of antiapoptotic proteins provides lung cancer 

cells with a distinct growth advantage. Major protein survival-signaling pathways activated by tobacco carcinogens are illustrated. 

KRAS and P53 are boxed to emphasize that KRAS and TP53 are the most commonly mutated genes. Mutationally activated KRAS is 

locked in its active form, resistant to the inactivating effects of GTPase-activating proteins, and cannot hydrolyze guanosine triphosphate to guanosine diphosphate. Similarly, mutated P53 cannot carry out many of its normal protective functions with respect to cell 

cycle control and apoptosis. AKT = protein kinase B; AP-1 = activator protein-1; BAD = BCL-associated death protein; BAX = BCL-2 

associated X protein; CASPASE-9 = cysteine-aspartic acid protease-9; ERK = extracellular signal-regulated kinase; IkKa = I kappa-B 

kinase alpha; MDM2 = murine double minute 2 protein; MEK = mitogen-activated protein kinase kinase; NF-kB = nuclear factorkappa beta; PI-3K = phosphatidylinositol 3-kinase; PKC = protein kinase C signaling pathway; PTEN = phosphatase and tensin 

homolog; RAF = v-raf murine leukemia viral oncogene; RSK2 = P90 ribosomal protein S6 kinase; STAT3 = signal transducer and 

activator of transcription 3. 
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Epidermal Growth Factor Receptor

Exposure of oral cells to cigarette smoke caused 

an increase in EGFR tyrosine kinase activity (Moraitis et 

al. 2005). Signaling through EGFR can lead to survival 

signals that suppress dependent (downstream) apoptotic 

pathways or stimulate cell proliferation. Some evidence 

suggests that EGFR signaling can influence the levels and 

activities of antiapoptotic BCL-2 family members (Kari et 

al. 2003). The EGFR gene is overexpressed and thus constitutively activated in lung cancer cells (Sridhar et al. 

2003) and bronchial preneoplastic lesions (Rusch et al. 

1995; Kurie et al. 1996; Piyathilake et al. 2002). In addition, a truncated form of the EGFR protein (EGFRvIII) is 

constitutively active in NSCLC cells (Okamoto et al. 2003). 

The expression of this mutant form of EGFR is associated with an increase in cell transformation and with the 

constitutive activation of important downstream signaling pathways for survival, including the PI-3K/AKT pathway (Antonyak et al. 1998; Moscatello et al. 1998; Tang et 

al. 2000). 

RAS/Mitogen-Activated Protein Kinase

Activation of the RAS pathway sends a strong antiapoptotic signal, and the constitutive activation of RAS 

can transform normal cells. Oncogenic RAS protein has a 

primary role in the development of lung cancer (Johnson 

et al. 2001a). RAS activates several pathways, including 

RAF/mitogen-activated protein kinase kinase (MEK)/ERK, 

PKC, PI-3K/AKT, and NF-kB (Kauffmann-Zeh et al. 1997; 

Kennedy et al. 1997; Peeper et al. 1997; Baldwin 2001). 

These pathways are commonly deregulated by RAS in lung 

cancers (Adjei 2001a,b). RAF/MEK/ERK pathway activation can lead to changes in downstream gene expression 

through the activation of activator protein-1 (AP-1). AP-1 

is a well-characterized transcription factor composed of 

homodimers and/or heterodimers of the JUN and FOS

gene families (Angel and Karin 1991). AP-1 regulates the 

transcription of various genes. Many stimuli, including 

tumor promoters, mediate AP-1 binding to the DNA of 

genes that govern cellular processes such as inflammation, proliferation, and apoptosis (Angel and Karin 1991). 

Phosphatidylinositol-3 Kinase, 

Phosphatidylinositol 3’-Phosphatase, 

and Protein Kinase B

PI-3K consists of a family of heterodimeric complexes, each composed of a p110 catalytic subunit and 

a regulatory subunit that exists primarily as a p85 form 

(Tolias et al. 1995; Vanhaesebroeck et al. 1997; Wymann 

and Pirola 1998). This family of proteins is involved in 

the regulation of proliferation, viability, adhesion, and 

motility migration in numerous cell types (Carpenter and 

Cantley 1996; Khwaja 1999; Rameh and Cantley 1999; 

Blume-Jensen and Hunter 2001; Roymans and Slegers 

2001). Cell survival and oncogenic transformation require 

PI-3K activation (Datta et al. 1999; Stambolic et al. 1999). 

PI-3K–dependent kinases include 3-phosphoinositide–

dependent protein kinase-1 (PDK1) and AKT (PKB). The 

PI-3K pathway can also be activated by the EGFR protein 

and by an activated RAS protein (Rodriguez-Viciana et 

al. 1997). One of the first steps in PI-3K signaling is the 

activation of PDK1, which phosphorylates and activates 

AKT (Coffer et al. 1998; Belham et al. 1999). AKT phosphorylates and inactivates several proapoptotic proteins, 

including BAD and CASPASE-9. Other targets of AKT 

important in the regulation of apoptosis include glycogensynthase-kinase-3 (Pap and Cooper 1998), the Forkhead 

transcription factor FKHRL1 (Brunet et al. 1999), and the 

mammalian target of rapamycin/p70S6 kinase (McCormick 2004). Furthermore, AKT inactivates P53 by phosphorylating MDM2, which increases the ability of MDM2 

to bind to and promote P53 degradation (Ogawara et al. 

2002). AKT also suppresses apoptosis by activating NF-kB 

through AKT phosphorylation of I kappa-B kinase alpha 

(Ozes et al. 1999; Romashkova and Makarov 1999).

Most NSCLC cells display an increase in PI-3K 

activity that results in highly active AKT and other downstream mediators (Moore et al. 1998; Brognard et al. 

2001). AKT is important in the survival of lung cancer 

cells and is constitutively activated in most NSCLC cell 

lines to promote the survival of NSCLC cells under stressful conditions (Brognard et al. 2001). Studies have also 

found AKT expression in SCLC tumor samples (Lee et al. 

2002b; Mukohara et al. 2003), SCLC cell lines (Moore et 

al. 1998), SCLC tumors (Blackhall et al. 2003), mouse 

tumors induced by tobacco carcinogens (West et al. 2003), 

and human bronchial dysplastic lesions (Tsao et al. 2003). 

(For additional details on AKT activation by components 

of cigarette smoke through receptor interactions, see 

“Activation of Cytoplasmic Kinase by Tobacco Smoke” 

later in this chapter.)

Nuclear Factor-Kappa B

NF-kB is a rapidly induced transcription factor 

responsive to stress that functions to intensify the transcription of a variety of genes, including those encoding 

cytokines, growth factors, and acute response proteins 

(Baldwin 1996). Nicotinic activation of nicotinic acetylcholine receptors (nAChRs) stimulates NF-kB activity downstream of ERK and AKT, which promotes tumor growth 

and angiogenesis through the vascular endothelial growth 

factor (VEGF) in vivo (Heeschen et al. 2001, 2002). Moreover, NF-kB activation by exposure to cigarette smoke in 
Surgeon General’s Report

288 Chapter 5

lung cancer cells induces the expression of COX-2 (Anto 

et al. 2002; Shishodia and Aggarwal 2004). Recent results 

suggest that nicotine, but not NNK, activates NF-kB–

dependent survival of lung cancer cells in addition to their 

proliferation. These studies illustrate that the activation 

of NF-kB by nicotine or by cigarette smoke in its entirety 

through receptor binding can promote tumorigenesis in 

the lung through many mechanisms, including increased 

levels of VEGF and COX-2.

Cyclooxygenase

COX-1 and COX-2 were shown to catalyze synthesis of prostaglandins from arachidonic acid. Researchers observed that COX-1 was constitutively expressed in 

most tissues, whereas COX-2 was inducible and found at 

elevated levels in various cancers (Koki et al. 2002; Dannenberg and Subbaramaiah 2003; Dubinett et al. 2003). In 

lung cancers, researchers have found COX-2 expression at 

most stages of tumor progression (Hida et al. 1998; Huang 

et al. 1998; Wolff et al. 1998; Hosomi et al. 2000; Anderson et al. 2002; Fang et al. 2003). Others reported high 

levels of COX-2 in NSCLC and premalignant lesions, but 

COX-2 expression is less consistent in SCLC (Wolff et al. 

1998; Hosomi et al. 2000). Studies show that NNK induces 

a high expression of COX-2 in rats (El-Bayoumy et al. 

1999). Levels of COX-2 mRNA are about four times higher 

in the oral mucosa of smokers than in that of lifetime nonsmokers (Moraitis et al. 2005). Researchers believe that 

at least one role of COX-2 in cancer is associated with 

cell resistance to apoptosis and an increase in metastatic 

potential (Gupta and Dubois 2001). The supporting evidence shows that COX-2 overexpression coincides with an 

increased BCL-2 expression (Tsujii and DuBois 1995) and an 

increased stabilization of the antiapoptotic protein survivin (Li et al. 1998a; Krysan et al. 2004). Lung cancer 

cells that were induced to express COX-2 demonstrated 

an increase in survival time (Lin et al. 2001b), and COX-2 

inhibitors stimulated apoptosis in lung carcinoma cells 

(Hida et al. 2000; Yao et al. 2000; Chang and Weng 2001). 

Summary

Apoptosis is commonly suppressed in lung cancer, 

which correlates with increases in cancer cell survival 

and proliferation. Deregulation of the many pathways for 

growth control (Figure 5.15) in lung cancer is attributable 

partly to interactions of carcinogens in cigarette smoke 

with the KRAS oncogene, the P53 tumor-suppressor 

gene, and other genes. These pathways represent a dense 

interactive network with a range of potential effects on 

cell survival. Mechanisms associated with cigarette smoke 

that increase resistance to apoptosis include activation of 

antiapoptotic proteins and/or suppression of proapoptotic 

and tumor-suppressor proteins. 

Cigarette Smoke and Activation of 

Cell-Surface Receptors in Cancer

Airway Epithelial Cells

Nicotinic Acetylcholine Receptors

Neuronal nAChRs are large membrane-associated 

proteins that are the first line of contact between cells and 

components of cigarette smoke such as nicotine and NNK. 

These proteins were originally described as receptors for 

acetylcholine (ACh). Their function in the brain has been 

studied in detail because of their ability to mediate the 

addictive effects of nicotine. Each receptor is made up of 

five subunits arranged in a barrel-like structure, creating 

a pore that allows calcium to enter the cell in response 

to ligand binding. Nine alpha subunits (α2 through α10) 

and three beta subunits (β2 through β4) combine with 

each other to form heteropentamers (combinations of α2 

through α6 with β2 through β4) or homopentamers (α7 

through α10). Each nAChR consists of 5 subunits, and 

researchers have identified at least 12 subunits; thus, 

many functional nAChRs exist. Different ligands, including nicotine, NNK, and ACh, have varying affinities for 

different nAChRs. Despite this complexity, the primary 

receptors that mediate the addictive effects of nicotine 

are α4β2 nAChRs, whereas α7 nAChRs are high-affinity 

receptors for NNK (Lindstrom 1997, 2003). Moreover, the 

discovery that mutations in the α4 nAChR subunit lower 

the threshold for addiction raises the possibility that 

genetic variations in these receptors could increase susceptibility to nicotine dependence and exposure to carcinogens through smoking (Tapper et al. 2004). 

Although nAChRs were originally thought to be limited to neuronal cells, studies have identified functional 

nAChRs in tissues outside the nervous system. This finding raises the possibility that these receptors may mediate 

some of the systemic effects of smoking. In lung tissues, 

researchers have discovered nAChRs in human bronchial 

epithelial cells, vascular endothelial cells, pulmonary neuroendocrine cells, neuroepithelial bodies, NSCLC cells, 

and SCLC cells (Tarroni et al. 1992; Maneckjee and Minna 

1994; Macklin et al. 1998; Maus et al. 1998; Schuller and 

Orloff 1998; Wang et al. 2001b; Fu et al. 2003; Schuller et 

al. 2003; Song et al. 2003a,b; Tsurutani et al. 2005). 

The stimulation of nAChRs by components of cigarette smoke has biologic effects on cells that are important 

for the initiation, progression, and maintenance of cancer. 
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The activation of nAChRs in lung epithelial cells by nicotine or NNK promotes the survival and proliferation of 

human mesothelioma and lung cancer cells (Maneckjee 

and Minna 1994; Schuller and Orloff 1998; West et al. 

2002; Schuller et al. 2003; Trombino et al. 2004; Tsurutani 

et al. 2005). In normal cells, nicotine can stimulate properties consistent with cell transformation and the early 

stages of cancer formation, such as increased cell proliferation, decreased cellular dependence on the extracellular matrix for survival, and decreased contact inhibition, 

which is the natural process of arresting cell growth when 

two or more cells come in contact with each other (West 

et al. 2003). Furthermore, nicotine stimulation of endothelial nAChRs promotes angiogenesis, another property 

of cancer (Heeschen et al. 2001, 2002; Zhu et al. 2003). 

Thus, the induced activation of nAChRs in lung tissues 

by components of cigarette smoke can promote processes 

required for development of cancer.

In addition to stimulating nAChRs directly, components of cigarette smoke can indirectly stimulate nAChRs 

by promoting the growth of tobacco-related cancers that 

express and secrete ACh, the endogenous ligand for these 

receptors. SCLC and NSCLC cells synthesize, transport, 

and release ACh in vitro, which stimulates proliferation of 

cancer cells through the autocrine activation of nAChRs 

(Song et al. 2003a; Proskocil et al. 2004). This finding 

suggests that there are many mechanisms for activation 

of nAChRs in lung cancer and further emphasizes the 

importance of these receptors in the biology of tobaccorelated cancer.

ß-Adrenergic Receptors

The β-adrenergic receptors are neuronal receptors that may play a role in mediating effects of cigarette 

smoke related to signal transduction. NNK is structurally similar to epinephrine, the endogenous ligand for 

the β-adrenergic receptor, suggesting that in addition to 

binding nAChRs, NNK may bind to these receptors. Once 

bound to β-adrenergic receptors, NNK can stimulate the 

release of arachidonic acid (Schuller et al. 1999; Weddle 

et al. 2001). The enzyme COX-2 converts arachidonic acid 

to prostaglandin E2, which mediates inflammation and 

promotes cell survival and proliferation in cancer. This 

finding is important because cell lines from human lung 

cancer overexpress the β-adrenergic receptor (Schuller et 

al. 2001), and several studies suggest that the presence or 

expression of arachidonic acid is a risk factor for pulmonary adenocarcinomas (Alavanja et al. 1993, 2001). Thus, 

these studies indicate that the β-adrenergic receptor may 

be an important mediator of signal transduction pathways 

associated with exposure to cigarette smoke.

Other Receptors

The ERBB family is another group of EGFRs that 

indirectly mediate signal transduction associated with cigarette smoke. The four types of ERBB receptors are EGFR 

(HER-1), HER-2, HER-3, and HER-4. These receptors act 

in pairs to stimulate downstream signaling pathways that 

mediate the survival and proliferation of both normal 

cells and cancer cells. Ligands that bind to ERBB family 

members include the epidermal growth factor TGFα and 

amphiregulin. In addition, receptors can be activated in 

the absence of a ligand through overexpression of the 

receptors themselves. Both of these mechanisms play 

a role in activation of these receptors mediated by cigarette smoke. 

The hypothesis that ERBB receptors mediate the 

effects of cigarette smoke on airway epithelial cells 

emerged from correlative clinical data and mechanisms 

defined in vitro. Clinical data include many reports of 

EGFR and HER-2 overexpression in lung cancer (Hendler and Ozanne 1984; Cerny et al. 1986; Veale et al. 1987; 

Hirsch et al. 2003a; Tan et al. 2003). In addition, some 

studies have shown that EGFR overexpression and activation in human lung cancers correlate with shorter survival times, suggesting that they play an important role in 

development of cancer (Kern et al. 1990; Kanematsu et al. 

2003; Selvaggi et al. 2004). 

Clinical data also support the hypothesis that ERBB 

expression and activation change with exposure to cigarette smoke or its components. Studies have demonstrated the overexpression of EGFR and ERBB3 in the 

bronchial epithelium of smokers (Yoneda 1994; O’Donnell 

et al. 2004). Results of mechanistic in vitro studies, such 

as the demonstration that NNK-induced transformation 

of lung epithelial cells is associated with an increase in 

EGFR expression, support these observations (Lonardo 

et al. 2002). Moreover, exposure to nicotine alone can 

increase the expression of EGFR in cervical cancer cell 

lines (Mathur et al. 2000). Studies also demonstrate that 

exposure to tobacco smoke increases the activity of EGFR, 

and metabolites of B[a]P induce activation of EGFR and 

downstream signaling pathways that promote proliferation (Burdick et al. 2003; Moraitis et al. 2005). These studies support the idea that components of cigarette smoke 

modulate the expression and activation of the ERBB family of receptors. 

In addition to increasing the expression of ERBB 

family members, components of tobacco smoke stimulate cells to produce ligands that activate the receptors. In 

clinical specimens, studies have described the coexpression of EGFR and its ligand TGFα in human NSCLC. In 

one study, both EGFR and TGFα were expressed in 38 
Surgeon General’s Report

290 Chapter 5

percent of the cases of NSCLC examined (Rusch et al. 

1993). In a second study, 72 percent of SCCs and 34 

percent of adenocarcinomas expressed both EGFR and 

TGFα (Hsieh et al. 2000). This finding may be clinically 

important because a retrospective analysis showed that the 

coexpression of EGFR and TGFα is an indicator of a 

poor prognosis (Tateishi et al. 1990). These studies suggest that the stimulation of ERBB ligands induced by 

cigarette smoke may be an important mechanism of signal transduction.

Consistent with the clinical data, in vitro studies 

show that condensate from cigarette smoke stimulates 

the release of amphiregulin and TGFα from the cell membrane, which leads to the autocrine activation of EGFR 

and cell proliferation (Richter et al. 2002; Lemjabbar et al. 

2003; Moraitis et al. 2005). Several studies demonstrate 

that cigarette smoke condensate activates matrix metalloproteinases (MMPs), which are enzymes on the extracellular surface of cells that cleave these ligands from the 

extracellular matrix. Support for these in vitro observations comes from the demonstration that MMP activity is 

higher in lung tissues from smokers than in those from 

nonsmokers (Kang et al. 2003; Kangavari et al. 2004). 

In addition to stimulating downstream kinases, 

EGFR activation by cigarette smoke may provide a mechanistic link to the increased inflammation characteristic 

of smokers by increasing COX-2 activity (see “Activation 

of Cytoplasmic Kinase by Tobacco Smoke” later in this 

chapter). In vitro data suggest that autocrine activation 

of EGFR, by the expression of the TGFα and AREG genes 

induced by tobacco smoke, stimulates COX-2 expression 

(Moraitis et al. 2005). Cigarette smoke also increases 

COX-2 expression by lung fibroblasts in vitro, and B[a]P 

increases COX-2 expression by oral epithelial cells (Kelley 

et al. 1997; Martey et al. 2004). Thus, many in vitro studies demonstrate that EGFR activation by components of 

cigarette smoke can contribute to inflammation through 

the increased expression and activation of COX-2.

Clinical data support the validity of these in vitro 

observations. For example, studies document increased 

levels of COX-2 in the oral mucosa of smokers (Moraitis 

et al. 2005) and in urothelial tissues from smokers with 

bladder cancer (Badawi et al. 2002). Moreover, COX-2 is 

expressed only in neoplastic epithelial cells, not in normal bronchial epithelial cells (Hastürk et al. 2002). COX-2 

overexpression in lung cancer is associated with tumor 

angiogenesis and survival and proliferation of tumor cells 

(Riedl et al. 2004) and with a poor prognosis in NSCLC 

(Achiwa et al. 1999; Yuan et al. 2005). Thus, the stimulation of EGFR that leads to COX-2 activity by exposure 

to cigarette smoke is another mechanism mediated by a 

growth factor receptor to promote cell survival and proliferation in carcinogenesis. 

Activation of Cytoplasmic Kinase 

by Tobacco Smoke

Activation of cell-surface receptors by components 

of tobacco smoke stimulates downstream kinases that 

mediate cancer cell survival, proliferation, and resistance 

to chemotherapy. The best-described kinases activated 

by smoking are AKT, ERK, PKC, and PKA. All of these 

kinases can be activated by cigarette smoke components 

through nAChRs, but ERBB family members also mediate 

AKT and ERK activation by cigarette smoke components. 

In addition, β-adrenergic receptor activation by cigarette 

smoke components can activate PKA and PKC. Thus, 

these proteins can be activated by tobacco smoke components through multiple receptor-mediated mechanisms, 

suggesting that the proteins are important mediators of 

smoking-induced signal transduction. 

Protein Kinase B

The serine/threonine kinase AKT may be the critical 

effector of signaling induced by cigarette smoke, because 

AKT is stimulated in response to the activation of nAChRs, 

β-adrenergic receptors, and the ERBB family of receptors. 

Moreover, AKT controls many cellular processes that 

promote cell survival, proliferation, and the resistance of 

cancer cells to chemotherapy. Clinical data also suggest 

that AKT activation indicates a poor prognosis in many 

tobacco-related cancers. Thus, activation of this kinase 

by components of tobacco smoke can affect many cellular 

processes important for the initiation, growth, and progression of tumors. 

AKT might be important for the initiation as well as 

the maintenance of tobacco-related cancers. Nicotine and 

NNK cause rapid AKT activation through different nAChRs 

(West et al. 2003; Tsurutani et al. 2005). B[a]P metabolites activate AKT in breast epithelial cells, although the 

cellular receptor responsible for the effect has not been 

identified (Burdick et al. 2003). Furthermore, nicotineinduced AKT activation in normal human bronchial cells 

or in small airway epithelial cells promotes cell survival, 

proliferation, and anchorage-independent growth, all 

of which are properties of transformed cells (West et al. 

2003). These studies are important because they suggest 

that AKT activation by tobacco smoke components may 

precede the formation of DNA mutations that cause cancer. Thus, AKT activation could serve as a biochemical 

gatekeeper for lung carcinogenesis by promoting the survival of cells that would normally die from DNA damage.

In addition to promoting AKT-dependent growth 

and survival of normal epithelial cells, tobacco smoke 

components have similar effects on cells throughout the 

phenotypic spectrum of transformation. In a mouse model 

of NNK-induced lung tumorigenesis, an increase in AKT 
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activation was associated with an increase in the progression of NNK-induced lung lesions (West et al. 2004b). In 

human lung cancer cells, nicotine or NNK activated the 

AKT pathway and stimulated AKT-dependent proliferation through nAChRs (Tsurutani et al. 2005). Moreover, 

these researchers showed that nicotinic activation of AKT 

increased survival of lung cancer cells after treatment with 

chemotherapeutic agents or radiation (Tsurutani et al. 

2005). The fact that tobacco smoke components activate 

AKT and promote the survival of cancer cells is important, 

and it is supported by the finding that cancer patients who 

continue to smoke during chemotherapy have a worse 

prognosis than those who stop smoking (Johnston-Early 

et al. 1980; Browman et al. 1993; Videtic et al. 2003). 

Clinical data and preclinical models support the 

hypothesis that AKT activation is an early event in carcinogenesis. AKT is activated in preneoplastic lung lesions 

induced by exposure to NNK (West et al. 2004a) and in dysplastic lung lesions from smokers (Massion et al. 2004). In 

addition, AKT activation is associated with poor survival 

in patients with tobacco-related cancers, including lung 

cancer and pancreatic cancer (David et al. 2004; Hirami 

et al. 2004; Yamamoto et al. 2004; Tsurutani et al. 2005). 

Together, these clinical studies support the idea that AKT 

plays an important role in the formation and maintenance 

of tobacco-related cancers.

Extracellular Signal-Regulated Kinases

In addition to AKT, ERK may play an important role 

in smoking-related cancers because it can be activated 

in response to components of tobacco smoke through 

both nAChR and ERBB receptors. In normal cells, ERK 

is activated in response to many extracellular signals and 

stimulates cell proliferation. In SCLC and pulmonary neuroendocrine cells, NNK-induced activation of nAChR leads 

to the activation of RAF-1 and its downstream effector ERK 

(Jull et al. 2001; Schuller et al. 2003). In addition, B[a]P 

metabolites activate ERK (Burdick et al. 2003), and nicotine activates ERK and promotes cell survival (Heusch and 

Maneckjee 1998). Thus, like AKT, ERK can be activated as 

an acute response to tobacco smoke components. Because 

ERK and AKT can promote cell survival and proliferation, 

early activation of both kinases may contribute to the initiation, promotion, and progression of cancer. 

Researchers have also described ERK activation 

in tobacco-related cancers, thus validating the mechanisms defined in vitro. ERK activation is associated with 

poor survival in SCLC, which occurs almost exclusively 

in smokers (Blackhall et al. 2003). The overexpression of 

C-MYC, an oncogene activated by ERK, has been described 

in lung cancer and promotes proliferation as well as 

resistance to cell death (Zajac-Kaye 2001). Thus, tobacco 

smoke components stimulate ERK, which promotes cell 

proliferation and contributes to the poor prognosis of 

lung cancer patients with this biochemical alteration.

Protein Kinase C

The PKC kinases also mediate cellular responses 

to exposure to tobacco smoke. Several isoforms of PKC 

can promote cell survival, most notably PKCα. Nicotine- and NNK-induced activation of PKCα through the 

β-adrenergic receptor promotes the survival of lung 

cancer cells (Schuller et al. 2003). In addition, nicotinic 

activation of nAChRs activates PKC in human bronchial 

epithelial cells, as well as in lung cancer cells (Maneckjee and Minna 1994; Carlisle et al. 2004). In SCLC, NNKinduced activation of nAChRs causes PKC activation 

associated with cell proliferation (Jull et al. 2001). 

Another PKC isoform, PKCd, seems to act atypically in 

NSCLC cells. Activation of PKCd in NSCLC promotes cell 

survival and resistance to chemotherapeutic agents (Clark 

et al. 2003), and nicotine can prevent chemotherapy from 

inhibiting PKC (Heusch and Maneckjee 1998). Like AKT, 

nicotinic activation of PKC has ramifications for smokers by contributing to chemotherapeutic resistance. This 

finding is consistent with the finding that patients with 

lung cancer who continue to smoke during chemotherapy 

have a worse prognosis than those who stop smoking. 

A clinical study also demonstrates the importance 

of PKC in tobacco-related cancers. Lahn and colleagues 

(2004) found that PKCα is overexpressed in a subset of 

NSCLC. Collectively, the results suggest that the activation of prosurvival PKC isoforms by cigarette smoke is an 

important mechanism of cell proliferation mediated by 

nAChRs and β-adrenergic receptors in carcinogenesis. 

Protein Kinase A

Another cytoplasmic kinase activated by components of tobacco smoke is PKA. Under normal physiological conditions, PKA is stimulated through the 

production of cyclic adenosine monophosphate by activated 

G protein–coupled receptors. Nicotinic activation of PKA 

occurs through both nAChRs and β-adrenergic receptors 

(Dajas-Bailador et al. 2002; Jin et al. 2004a). The primary 

effect of nAChR-mediated PKA activation was an increase 

in cell proliferation. Nicotinic activation of PKA through 

β-adrenergic receptors, however, promoted cell survival. 

Although the data on PKA are limited, they suggest that 

PKA might be an important mediator of signal transduction, mediating cell survival and proliferation in response 

to activation by nAChRs and β-adrenergic receptors.
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292 Chapter 5

Downstream Targets of Signaling Cascades 

Mediated by Tobacco Smoke

Activation of cell-surface receptors induced by components of tobacco smoke and the subsequent activation 

of cytoplasmic kinases stimulate other proteins that dictate cellular responses, such as cell survival and proliferation. Although activated kinases have many downstream 

targets, the two most studied are the transcription factor NF-kB and proteins in the BCL-2 family. Activation 

of these proteins by tobacco smoke components through 

signaling cascades promotes processes involved in initiation, progression, and maintenance of cancers (see “Signal Transduction” earlier in this chapter).

Gene Promoter Hypermethylation 

in Cancer Induced by Tobacco 

Smoke

Alternative to Mutation

Gene promoter hypermethylation is an epigenetic 

change of a gene involving extensive methylation at the 5’ 

position of C in CpG islands within the promoter region

and often extending into exon 1 of regulatory genes (Jones 

and Baylin 2002; Herman and Baylin 2003). “Epigenetic” 

refers to alteration in gene expression resulting from 

changes other than DNA sequence. The end result of this 

process can be loss of gene transcription and therefore the 

silencing of gene function. 

Inactivation of the P16 Gene in Lung Cancer

One region on chromosome 9p contains the 

CDKN2A (P16) tumor-suppressor gene (Kamb et al. 1994; 

Merlo et al. 1994). Mutations within the P16 coding 

sequence are uncommon in lung cancer (Kamb et al. 

1994). In contrast, this gene is inactivated by hypermethylation at prevalences up to 60 percent and 70 percent in 

adenocarcinomas and SCC of the lung, respectively (Merlo 

et al. 1995; Belinsky et al. 1998; Kim et al. 2001; ZöchbaurMüller et al. 2001; Divine et al. 2005). This discovery of 

inactivation of a tumor-suppressor gene by hypermethylation in lung cancer and identification of such inactivation of the P16 gene launched an area of research to 

uncover other genes inactivated by this mechanism. The 

targeting of P16 for inactivation is likely attributable to 

the critical function of this gene in the cell, which is to 

inhibit CDKs that bind cyclin D1 and phosphorylate the 

RB gene product (Lukas et al. 1995; Weinberg 1995). 

This regulation is lost if either the P16 or the RB gene is 

inactivated. The reciprocal relationship between RB 

alterations in SCLC and P16 alterations in NSCLC supports the premise that dysfunction within the RB pathway 

is a major target in research on the genesis of lung cancer 

(Swafford et al. 1997).

Critical Pathways Inactivated in Non-Small-Cell 

and Small-Cell Lung Cancer

More than 50 genes are inactivated by gene promoter hypermethylation in lung cancer, and new genes 

are still being identified through genomewide screening 

approaches (Suzuki et al. 2002; Palmisano et al. 2003). 

The pathways and genes involved are summarized in 

Table 5.11. 

Of particular importance is the DNA repair gene 

AGT, which protects cells from the carcinogenic effects 

of alkylating agents by removing adducts from the O6

position of deoxyguanosine (see “Repair of DNA Adducts” 

earlier in this chapter). Failure to repair this DNA adduct 

could lead to mutations in genes such as KRAS and TP53. 

AGT is inactivated by gene promoter methylation in 24 to 

48 percent of adenocarcinomas (Esteller et al. 1999; Zöchbaur-Müller et al. 2001; Pulling et al. 2003). SCLC studies 

conducted for methylation of this gene are limited. Studies have reported an association between AGT promoter 

hypermethylation and a G→A transition mutation at CpG 

sites within the TP53 gene in NSCLC (Wolf et al. 2001). 

In contrast, no association was found between AGT gene 

methylation and a transition mutation in codon 12 of the 

KRAS gene from adenocarcinomas (Pulling et al. 2003). 

The RAS superfamily of GTP-binding proteins 

plays an important role in signal transduction pathways 

that control cell proliferation, differentiation, and death 

(Campbell et al. 1998; Downward 2001) (see “Activation 

of Oncogenes in Lung Cancer” earlier in this chapter). 

Researchers identified a new family of genes that encode 

RAS-binding proteins. One of these genes, RASSF1A, is 

located at chromosome 3p21 and inactivated in 30 percent of NSCLCs and in 100 percent of SCLCs (Dammann 

et al. 2000; Burbee et al. 2001). Attempts to determine 

the function of this gene are continuing (Agathanggelou 

et al. 2003). RASSF1A protein forms a heterodimer with 

NORE1A, which allows it to bind with the proapoptotic 

protein MST1 (Khokhlatchev et al. 2002). Binding RAS 

to this complex may mediate RAS-dependent apoptosis. NORE1A is also silenced by methylation in NSCLC 

but not in SCLC (Hesson et al. 2003). Therefore, silencing either RASSF1A or NORE1A could effectively block 

apoptosis mediated by RAS activation. Two other RASSF 
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family members appear to be involved in lung cancer 

development. Studies show that RASSF2 binds directly to 

the KRAS gene in a GTP-dependent manner and appears 

to promote both cell-cycle arrest and apoptosis through 

this interaction (Vos et al. 2003). The expression of this 

gene is markedly reduced in some lung cancer cell lines, 

thus suggesting silencing by gene promoter hypermethylation. There is support for this mechanism of inactivation 

in studies on colon cancer that document hypermethylation of this gene in 70 percent of tumors (Hesson et al. 

2005). A third member of this gene family, RASSF4, shares 

25 percent homology with RASSF1A and 40 percent with 

RASSF2 and is methylated in approximately 20 percent of 

NSCLCs and SCLCs (Eckfeld et al. 2004). Thus, the loss 

of function among members of the RASSF gene family is 

important to the development of lung cancer.

Gene Silencing in Lung Cancer

The most extensively studied gene with respect to 

timing of methylation in NSCLC is P16. Examination of 

biopsy specimens from premalignant lesions obtained 

from people without SCLC or from different airways or 

at different bronchial generations revealed a progressive 

increase in the prevalence of P16 methylation as the disease developed. The frequency of P16 methylation was 

17 percent in basal cell hyperplasia, and the frequency 

increased incrementally over the histologic stages to 60 

percent in SCCs (Belinsky et al. 1998). Further studies 

examined bronchial epithelial cells obtained by bronchoscopy from cancer-free smokers and found that inactivation of the P16 gene is likely one of the earliest events in 

lung cancer (Belinsky et al. 2002). Researchers detected 

P16 methylation in specimens from 25 of 137 biopsy procedures (18 percent) classified as histologically normal, 

metaplasia, or mild dysplasia. In contrast, no P16 methylation was found in biopsy specimens obtained from lifetime nonsmokers. Researchers used an animal model to 

determine the timing of P16 methylation in adenocarcinomas. In rats, 94 percent of adenocarcinomas induced 

by NNK were hypermethylated at the P16 promoter; this 

change was frequently detected in precursor lesions to the 

tumors: adenomas and hyperplastic lesions (Belinsky et 

al. 1998).

Inactivation of the AGT gene appears to be a later 

event in lung cancer than is the inactivation of P16. Only 

3 of 40 biopsy specimens (8 percent) from heavy smokers 

with histologies including normal, hyperplasia, metaplasia, and dysplasia showed methylation of the AGT gene 

(Pulling et al. 2003). In addition, the prevalence of AGT

methylation increased between stage I adenocarcinoma 

and stages II to IV. Finally, of the 137 bronchial biopsy 

specimens studied, 3 percent of the DAPK gene and none 

of the RASSF1A genes showed methylation, which suggests that the silencing of these genes likely occurs after 

P16 inactivation in SCC (Pulling et al. 2003). In contrast, the inactivation of DAPK by methylation in alveolar 

hyperplasias in a murine model of lung adenocarcinomas 

suggests a role for this gene in the early development of 

adenocarcinomas (Pulling et al. 2004). 

Gene Promoter Hypermethylation, Prognosis, 

and Clinical Risk Factors

Numerous studies have evaluated relationships 

between gene promoter methylation and established clinical risk factors such as smoking dose and tumor stage. 

In addition, researchers have examined in detail the effect 

of gene-specific methylation on the survival of patients 

Table 5.11 Pathways altered through gene silencing 

by promoter methylation

      Methylation prevalence (%)

Pathway Gene

Non-smallcell lung 

cancer

Small-cell 

lung cancer

Cell cycle P16 26–70 0

Cell cycle PAX5a 64–74 ND

Cell cycle PAX5ß 52–61 ND

Cell cycle CHFR 10–19 ND

DNA repair AGT 27–47 0–19

Apoptosis DAPK 24–48 33

Apoptosis CASPASE-8 0 35–52

Apoptosis FAS ND 40

Apoptosis TRAIL-R1 ND 40

Apoptosis FHIT 38–45 ND

RAS 

signaling

RASSF1A 30 100

RAS signaling RASSF4 20 20

RAS signaling NORE1A 24 0

Invasion E-CADHERIN 16–19 ND

Invasion H-CADHERIN 43 ND

Invasion TIMP3 19–24 ND

Invasion LAMA3 27–58 65

Invasion LAMB3 20–32 77

Invasion LAMC2 13–32 58

Invasion MYO18B 31 45

Source: Belinsky 2004. Reprinted with permission from 

Macmillan Publishers Ltd., © 2004.

Note: ND = not determined.
Surgeon General’s Report

294 Chapter 5

with a diagnosis of early-stage lung cancer. Results from 

investigations of the most commonly studied genes in 

lung cancer are highlighted here.

P16 methylation was significantly associated with 

pack-years of smoking and with an independent risk factor 

that predicts a shorter survival for patients who had resection of a stage I adenocarcinoma (Kim et al. 2001). Several 

other studies also support P16 methylation as a prognostic 

factor for survival of patients who had resection of a stage 

I adenocarcinoma (Suzuki et al. 2002; Wang et al. 2004a). 

In contrast, RASSF1A methylation in stage III NSCLC was 

a stronger predictor of poor survival than was P16 methylation (Wang et al. 2004a). These two genes may differ 

in that the silencing of P16 is an early event involved in 

initiation of tumorigenesis, whereas RASSF1A methylation is a later event more likely involved in progression 

of tumorigenesis. Thus, the methylation of RASSF1A may 

lead to a more aggressive tumor phenotype. This hypothesis is supported by the more frequent involvement of 

RASSF1A methylation in tumors with a vascular invasion, 

pleural involvement, and a poorly differentiated histology (Tomizawa et al. 2002). Persons who started smoking 

before 19 years of age were 4.2 times more likely to have 

methylation of the RASSF1A gene than were those who 

started smoking after 19 years of age (Kim et al. 2003). 

This research also suggests that for patients with stage I 

or stage II NSCLC at diagnosis, methylation of this gene is 

associated with a poorer prognosis (Kim et al. 2003).

Other Tobacco-Related Cancers

In addition to the studies on lung cancer described 

here, other studies have shown association of cigarette 

smoking with gene promoter hypermethylation in other 

tobacco-related cancers, such as the head and neck and 

bladder. Aberrant promoter methylation is common in 

head and neck cancer and has been detected by using 

saliva samples (Rosas et al. 2001). Promoter methylation 

of the P16, DAPK, E-CADHERIN, and RASSF1A genes was 

associated with smoking and commonly found in head 

and neck cancer (Hasegawa et al. 2002). P16 promoter 

hypermethylation and the loss of P16 protein expression 

were detected in head and neck SCC; loss of expression 

correlated significantly with a history of alcohol consumption or tobacco use (Ai et al. 2003). The prevalence 

of P15 methylation in the healthy epithelium of patients 

with head and neck SCC who had long-term smoking 

and drinking behaviors was significantly higher than that 

in nonsmokers (Wong et al. 2003). Another study suggested that P15 gene methylation could be induced by 

chronic smoking and drinking and could play a role in 

the early stages of head and neck SCC (Chang et al. 2004). 

Cigarette smoking was also associated with an increased 

risk of promoter methylation of the P16 gene in bladder 

cancer (Marsit et al. 2006).

Molecular Epidemiology of 

Cell-Cycle Control and TobaccoInduced Cancer

Introduction

Cell-cycle checkpoints delay cell-cycle progression, 

thereby affording adequate time for DNA repair to occur. 

Such checkpoint signaling also activates pathways leading to apoptosis if the damage cannot be repaired. The 

introduction of new techniques of profiling gene expression has enabled researchers to comprehensively evaluate 

activity of proteins in regulating the cell cycle (Singhal 

et al. 2003). A hallmark of the neoplastic cell is the ability to disrupt the tightly regulated cell-cycle control and 

enable the cell to bypass checkpoints, especially at the 

G1/S and G2/M boundaries (Hanahan and Weinberg 2000). 

Persons with defects in cell-cycle checkpoints (acquired or 

inherited) could therefore exhibit chromosome damage, 

genomic instability, and increased susceptibility to 

tobacco carcinogenesis. 

In vitro studies show an association between exposure to tobacco carcinogens and the disruption of cellcycle control (Khan et al. 1999). Furthermore, Jin and 

colleagues (2004b) provide data showing that NNK promotes cell survival and proliferation through phosphorylation of the proteins BCL-2 and C-MYC. Studies implicate 

tobacco carcinogens in genetic alterations in the P16-RB 

and P14ARF-P53 pathways, mainly through the formation of DNA adducts. Variations in cell-cycle checkpoints 

might also be attributed to functional polymorphisms 

in cell-cycle control genes. The SNP500Cancer Database 

reports that 27 genes related to the cell cycle are polymorphic, and these include genes that control checkpoints for 

both the G1/S and G2 phases of the cell cycle. However, 

only a few genes, including CCND1, TP53, P21, and P73, 

have been studied in tobacco-related cancers.

CCND1 Gene

The CCND1 gene, together with CDK4, P16, and 

the tumor-suppressor gene RB, comprise a linked system 

governing the passage of the cell through the cell cycle 

(Betticher et al. 1997). A common finding in a variety of 

cancers is the amplification or overexpression of CCND1, 

which contributes to tumor initiation, progression, 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

and outcome, such as death. A G→A polymorphism at 

codon 242 in the conserved splice donor region of exon 

4 increases alternate splicing (Betticher et al. 1995). 

The alternate transcript appears to encode for a proteinmissing sequence involved in protein turnover, and therefore, the encoded protein may have a longer half-life. This 

extended half-life, in turn, would facilitate passage of damaged cells through the checkpoint for the G1/S phase and 

promote proliferation rather than apoptosis. Researchers 

have studied the association between the CCND1 genotype 

and cancer risk in several tobacco-related cancers. Qiuling and colleagues (2003) reported that the CCND1 *A/*A

genotype was associated with a significantly increased 

risk of lung cancer (OR = 1.87; 95 percent CI, 1.01–3.45) 

compared with that for the *G/*G genotype. The risk was 

even higher in young persons and men. A similar finding 

was reported in cancer of the head and neck (Zheng et 

al. 2001). These investigators demonstrated that carriers 

of the *A/*A genotype, on average, had diagnoses of cancer 3.5 years earlier than did carriers of the*G/*G genotype. Wang and colleagues (2002) reported that the *A/*A

genotype was associated with a significantly higher risk 

of transitional cell carcinoma of the bladder than that for 

the *A/*G plus *G/*G genotypes (OR = 1.76; 95 percent 

CI, 1.09–2.84). However, neither Cortessis and colleagues 

(2003) nor Yu and colleagues (2003) reported significant 

associations with either bladder cancer or esophageal SCC, 

respectively. Spitz and colleagues (2005) demonstrated an 

increased risk for lung cancer associated with this polymorphism. The risk estimate was 1.35 (95 percent CI, 

1.05–1.73) for the *A/*A and *A/*G genotypes compared 

with the *G/*G genotypes.

P21 Protein

Cell-cycle inhibitor protein P21 (WAF1/CIP1) acts as 

a checkpoint regulator for the G1/S and G2/M phases. Marwick and colleagues (2002) showed a significant increase 

in P21 mRNA expression in alveolar epithelial cells after 

exposure to condensate from cigarette smoke and concluded that oxidative stress induced by cigarette smoke 

modulates the expression of P21. 

Three studies of lung cancer have examined the 

association of cancer risk with a polymorphism of P21 at 

codon 31 (SER31ARG), but the findings were inconsistent. 

Själander and colleagues (1996) reported an increased frequency of the variant allele (*ARG) among patients with 

lung cancer (p <0.004). Two other studies failed to replicate this finding (Shih et al. 2000; Su et al. 2003). However, Chen and colleagues (2002) reported that the variant 

allele (*ARG) was associated with increased risk of bladder cancer.

TP53 Gene

Studies have reported 14 polymorphisms in the 

TP53 gene, 3 of which have been widely studied: a G→C 

polymorphism at codon 72 (proline/arginine), a 16bp 

insertion in intron 3, and a G→A transition in intron 6. 

Polymorphisms in codons 21, 36, and 213 are silent. The 

polymorphism in codon 47 involves a rare allele with a frequency less than 5 percent. The codon 72 polymorphism 

on exon 4 produces variant proteins with an arginine 

(CGC) or proline (CCC) at the site. Thomas and colleagues 

(1999) reported differences between the two variants in 

their ability to interact with basic elements of the transcriptional machinery and to induce apoptosis. Weston 

and colleagues (1992) reported an increased frequency 

of the proline allele in lung adenocarcinoma, which was 

consistent with findings in a Japanese study of lung cancer 

(Kawajiri et al. 1993). Jin and colleagues (1995) reported 

significantly higher risks for the *PRO/*PRO genotype 

among patients with lung cancer who were younger than 

55 years of age and among patients reporting fewer than 

30 pack-years of smoking. In a study of NSCLC, Nelson 

and coworkers (2005) found that mutation on the *PRO

allele was associated with a significantly worse outcome 

than that for patients with no mutation or with mutation 

on the *ARG allele.

Mutations in intron sequences may initiate aberrant 

pre-mRNA splicing that results in a defective protein (Hillebrandt et al. 1997) or that may influence mutations in 

the coding region. Either result would increase the likelihood of a deleterious phenotype (Malkinson and You 1994). 

Biroš and colleagues (2001) reported a higher percentage 

of the intron 6 variant allele in patients with lung cancer 

than in control participants. However, Birgander and colleagues (1995) found no association of the allele with lung 

cancer. Several studies estimated the pairwise haplotype 

frequencies for the polymorphisms in exon 4 and introns 

3 and 6. The researchers proposed that the P53 haplotypes 

were associated with a higher risk for lung cancer (Birgander et al. 1995; Biroš et al. 2001). In one study of 635 pairs 

of lung cancer patients and control participants, variant 

alleles of TP53 exon 4, introns 3 and 6, and their variant 

haplotypes were associated with an increased risk of lung 

cancer (Wu et al. 2002). In a meta-analysis of TP53 polymorphisms and lung cancer risk that included data from 

16 case-control studies, Matakidou and colleagues (2003) 

concluded that persons with the P53 exon 4 *PRO/*PRO

genotype had a 1.18-fold increase in lung cancer risk 

(OR = 1.18; 95 percent CI, 0.99–1.41). Other researchers 

have observed a similar association with polymorphisms 

of P53 introns 3 and 6. However, evidence of these associations has not been consistent (Wang et al. 1999; Mabrouk 

et al. 2003). 
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296 Chapter 5

P73 Gene

The P73 gene activates the promoters of several 

genes that are responsive to the TP53 gene and participate 

in cell-cycle control, DNA repair, and apoptosis and inhibit 

cell growth in a P53-like manner by inducing apoptosis or 

cell-cycle arrest in the G1 phase (Nomoto et al. 1998; Cai 

et al. 2000). Loss of heterozygosity at the P73 locus is relatively common. Studies have identified an estimated 17 

polymorphisms. Two common SNPs at positions 4 (G→A) 

and 14 (C→T) in the uncoding region of exon 2 of the 

P73 gene are in complete linkage disequilibrium and may 

affect P73 function by altering the efficiency of translation 

initiation (Kaghad et al. 1997).

Studies have reported the role of the P73

G4C14→A4T14 polymorphism in the risk of smokingrelated cancer (Ryan et al. 2001; Hamajima et al. 2002; 

Hiraki et al. 2003; Huang et al. 2003). In NSCLC, the most 

significant effect observed was among male smokers 

(OR = 1.87; 95 percent CI, 1.25–2.80) with SCLC, suggesting that this P73 polymorphism may have an impact on 

the repair of tobacco-associated DNA damage. A study of 

1,054 patients with lung cancer and 1,139 control participants found a dose-response relationship between the frequency of heterozygous or homozygous variant alleles and 

risk of lung cancer (trend test, p <0.001). ORs were 1.32 

(95 percent CI, 1.10–1.59) for the frequency of heterozygous alleles and 1.54 (95 percent CI, 1.05–2.26) for the 

frequency of homozygous alleles (Li et al. 2004b). The risk 

of lung cancer was more pronounced in persons younger 

than 50 years of age, men, light smokers, and patients with 

SCLC. The variant genotypes were also associated with an 

increased risk for SCCs of the head and neck that was statistically significant (OR = 1.33) and an even higher risk 

among current smokers (OR = 1.77) (Li et al. 2004a). 

Other Aspects

Carcinogenic Effects of Whole 

Mixture and Fractions of 

Tobacco Smoke

Researchers have conducted inhalation studies of 

cigarette smoke in hamsters, rats, mice, rabbits, dogs, and 

nonhuman primates. The model systems used in these 

studies had various problems, including the inability of 

any study to accurately duplicate human smoking behaviors. Nevertheless, comprehensive reviews of these studies 

have found a large amount of useful information (IARC 

1986, 2004; Coggins 1998; Witschi 2000). Researchers 

observed the most consistent results on cancer induction 

in Syrian golden hamsters; whole cigarette smoke and its 

particulate phase induced malignant tumors and other 

lesions in the larynx. Tumors were not induced by the gas 

phase of cigarette smoke. 

Findings of studies that induced malignant tumors 

by inhalation of cigarette smoke and its particulate phase 

are consistent with those in the substantial amount of 

literature demonstrating that condensate from cigarette 

smoke, which lacks volatile constituents of the gas phase, 

causes benign and malignant tumors when applied to 

mouse skin and rabbit ears or instilled in rat lungs by 

intrapulmonary administration (Hoffmann et al. 1978; 

IARC 1986, 2004). Collectively, these results clearly show 

that major carcinogenic fractions of cigarette smoke 

reside in the particulate phase.

Extensive fractionation studies were conducted 

with cigarette smoke condensate (Hoffmann et al. 1978). 

Bioassays of the resulting fractions applied to the skin of 

mice demonstrated that the neutral portion of the condensate has carcinogenic activity and the acidic portion 

has tumor-promoting and cocarcinogenic activity. The 

recombined neutral and acidic portions accounted for 

about 80 percent of the carcinogenic activity of the condensate. Subfractionation of the neutral portion revealed 

that certain PAHs were the major tumor initiators in this 

fraction. However, these PAHs alone, in the levels at which 

they occur, were insufficient to induce tumors. Moreover, 

when these PAHs were added to the condensate, the tumor 

yield was higher than with the condensate alone. These 

results indicate that the combination of PAHs acting as 

tumor initiators, together with cocarcinogens in the condensate, accounted for the tumorigenicity of the condensate on mouse skin. Researchers identified catechol and 

alkyl catechols as major cocarcinogens in the condensate, 

and the weakly acidic portion of the condensate demonstrated tumor-promoting activity (Van Duuren and Goldschmidt 1976; Hecht et al. 1981). Other cocarcinogens in 

cigarette smoke include undecane, pyrene, fluoranthene, 

and B[a]P (Van Duuren and Goldschmidt 1976). The 

identity of tumor promoters in cigarette smoke is largely 

unknown, although simple phenols may contribute 

weakly (Hecht et al. 1975). Researchers have also observed 

tumor-promoting activity of cigarette smoke in inhalation 

experiments with hamsters (IARC 1986). PAH-enriched 
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fractions of cigarette smoke condensate instilled in the rat 

lung also resulted in tumor formation (IARC 1986).

These results clearly demonstrate the carcinogenic, 

tumor-promoting, and cocarcinogenic activity of the particulate phase of cigarette smoke. However, some data 

indicate that constituents of the gas phase also contribute 

to tumor induction. Early studies in Snell’s mice demonstrated an increase in pulmonary adenocarcinomas in 

animals exposed to the gas phase alone (IARC 2004). In an 

exposure model using 89 percent sidestream smoke and 11 

percent mainstream smoke, increased multiplicity of lung 

adenomas was consistently observed in A/J mice exposed 

to the smoke for five months, followed by a four-month 

resting period. Tumor response in this model was clearly 

attributable to the gas phase, because filtration had no 

effect on multiplicity of lung adenomas (Witschi 2000; 

IARC 2004). The results of these studies indicate that a 

volatile carcinogen in cigarette smoke—possibly 1,3-butadiene—produced a tumorigenic response in the A/J 

mouse lung.

Two other studies not included in the reviews previously cited here demonstrate convincingly that cigarette 

smoke administered to rats or mice by whole-body exposure for extended periods induces benign and malignant 

tumors of the respiratory tract (Mauderly et al. 2004; 

Hutt et al. 2005). When male and female F-344 rats were 

exposed to smoke from 1R3 research cigarettes or to clean 

air for six hours per day, five days per week for up to 30 

months, the exposure significantly increased the incidence of nonneoplastic and neoplastic proliferative lung 

lesions in females. The combined incidence of bronchoalveolar adenomas and carcinomas was 14 percent in the 

high-exposure group (250 mg of particulates per m3 of 

air), 6 percent in the low-exposure group (100 mg/m3), 

and none in the controls. Mutations in codon 12 of the 

KRAS gene occurred in 4 of 23 tumors. Both males and 

females had significant increases in neoplasia of the nasal 

cavity (Mauderly et al. 2004). Female B6C3F1 mice were 

exposed to smoke for 6 hours per day, 5 days per week, 

for 925 days (250 mg/m3) or were sham exposed. The 

incidence of lung adenoma (28 percent) and lung adenocarcinoma (20 percent) in the mice exposed to smoke 

were significant (Hutt et al. 2005). 

Synergistic Interactions in 

Tobacco Carcinogenesis

Alcohol

There is persuasive epidemiologic evidence that 

alcohol consumption and smoking synergistically increase 

the risk for cancers of the oral cavity, pharynx, larynx, and 

esophagus (IARC 2004). No single mechanism clearly 

explains these observations, but several have been proposed and there is reasonable support for some. The most 

consistent body of evidence relates to the effects of alcohol 

on the distribution of carcinogenic nitrosamines. Swann 

and colleagues (1984) demonstrated that alcohol could 

inhibit the hepatic metabolism and clearance of NDMA, 

a carcinogen in tobacco smoke. This inhibition occurs 

because ethanol competitively inhibits hepatic cytochrome P-450 2E1, the main hepatic enzyme responsible 

for metabolism of NDMA. Consequently, more NDMA 

reaches extrahepatic tissues where it can be metabolically 

activated and has the potential to cause cancer. Anderson and coworkers (1992, 1996) demonstrated that coadministration of ethanol and NDMA to A/J mice resulted 

in an incidence of lung tumors higher than that in mice 

treated with NDMA alone and that this increase was a consequence of inhibition of hepatic metabolism and not of 

tumor promotion. Furthermore, administration of ethanol to patas monkeys before they received NDMA resulted 

in a 14.6-fold increase in O6-methylguanine in esophageal 

DNA and other extrahepatic tissues (Anderson et al. 1996). 

Another potential mechanism also involves the 

effects of ethanol on P-450 2E1, but as an inducer of this 

enzyme. Chronic ethanol consumption is known to induce 

production of hepatic P-450 2E1, and researchers hypothesized that this induction could lead to increased metabolic 

activation of carcinogens in tobacco smoke (McCoy et al. 

1979). Some N-nitrosamines in tobacco smoke—NDMA, 

N-nitrosodiethylamine, and N-nitrosopyrrolidine—are all 

substrates for P-450 2E1. McCoy and colleagues (1981) 

demonstrated that chronic ethanol consumption in hamsters increased the metabolism of N-nitrosopyrrolidine 

in hepatic and target tissue (e.g., trachea), as well as the 

carcinogenicity of this nitrosamine, which increases the 

occurrence of tumors in the nasal cavity and trachea. The 

carcinogenicity of N-nitrosodiethylamine in the rat esophagus was also increased by simultaneous administration 

of ethanol (Gibel 1967). Overall, however, the effects of 

ethanol consumption on N-nitrosamine carcinogenesis have been mixed, and they appear to depend on the 

N-nitrosamine studied and the protocol used. For example, long-term ethanol consumption had no effect on the 

carcinogenicity of NNN in the hamster and only modest or 

no effect in the rat (McCoy et al. 1981; Trushin et al. 1984). 

Other mechanisms for the enhancing effect of 

alcohol consumption on tobacco carcinogenesis have been 

discussed (Pöschl and Seitz 2004). Persons who abuse 

alcohol generally have nutritional deficiencies, which 

could exacerbate the effects of smoking. They commonly 

have folate deficiency that could contribute to an inhibition of transmethylation, which is important in gene regulation. Zinc deficiency is known to result in enhanced 
Surgeon General’s Report

298 Chapter 5

carcinogenesis in the rat esophagus (Fong et al. 2001). 

Reduced serum and hepatic levels of vitamin A in persons 

with long-term alcohol abuse may affect carcinogenesis. 

Alcohol could also act as a solvent, increasing absorption 

of tobacco carcinogens (Squier et al. 1986).

Asbestos

Smoking and exposure to asbestos interact synergistically to increase the risk for lung cancer (IARC 2004). 

The mechanism for this synergy is unknown. Researchers have investigated a number of possibilities, however, 

and these have been summarized (Nelson and Kelsey 

2002). It has been proposed that asbestos fibers serve as a 

vehicle to deliver tobacco carcinogens to the cell nucleus. 

Surfactant phospholipids may help to solubilize carcinogenic PAH, increasing their concentrations in the lung 

epithelium. Studies have also demonstrated that asbestos 

fibers can induce chromosomal aberrations and extensive 

deletions, potentially adding to the DNA damage produced 

by carcinogens in tobacco smoke. Furthermore, asbestos 

may cause oxidative damage that could be related to inflammation and cell death related to pulmonary fibrosis 

associated with exposure to asbestos. It seems likely that 

asbestos fibers could cause proliferation that may increase 

the probability of mutations attributable to DNA damage 

by tobacco smoke carcinogens.

Carcinogens as Causes of 

Specific Cancers

Data from carcinogenicity studies, product analyses, 

and findings from studies using biochemistry and molecular biology support a significant role for certain carcinogens in tobacco-induced cancer (Table 5.12). 

Considerable evidence favors PAHs and NNK as 

major factors in development of lung cancer. PAHs are 

strong carcinogens acting locally; thus, fractions of 

tobacco smoke enriched in these compounds are carcinogenic (Hoffmann et al. 1978; Deutsch-Wenzel et al. 1983; 

IARC 1983) (see “Carcinogens in Cigarette Smoke” earlier in this chapter). Researchers have detected PAH-DNA 

adducts in human lungs, and the spectrum of mutations 

in the TP53 gene isolated from lung tumors was similar to 

the pattern of DNA damage produced in vitro by PAH diol 

epoxide metabolites and in cell cultures by B[a]P (Pfeifer 

et al. 2002; Phillips 2002; Boysen and Hecht 2003; Liu et 

al. 2005) (see “DNA Adducts and Biomarkers” earlier in 

this chapter).

NNK is a strong systemic carcinogen in lungs of 

rodents that induces lung tumors independent of the 

route of administration (Hecht 1998). NNK was found to 

be particularly potent in the rat. Significant incidence of 

lung tumors was induced by total doses as low as 6 mg/

kilogram (kg) of body weight or by 1.8 mg/kg as part of 

a dose-response trend. These doses are comparable to an 

estimated NNK dose of 1.1 mg/kg in persons who have 

smoked for 40 years (Hecht 1998). DNA adducts derived 

from NNK or from the related tobacco-specific nitrosamine, NNN, are present in lung tissue from smokers, 

and metabolites of NNK are found in the urine of smokers (Hecht 2002b). Epidemiologic data indicate that a 

systemic carcinogen causes lung cancer in cigar smokers 

who do not inhale the smoke; this finding is consistent 

with the tumorigenic properties of NNK (Boffetta et al. 

1999; Shapiro et al. 2000). 

The changing histology of lung cancer is also consistent with the role of NNK: adenocarcinoma has now 

overtaken SCC as the most common lung cancer type. 

This nitrosamine in tobacco smoke produces primarily 

adenocarcinomas in rodents. However, this outcome has 

also been attributed to differing inhalation patterns of 

current cigarette smokers (Travis et al. 1995; Hecht 1998). 

As nitrate concentrations in tobacco increased from 1959 

to 1997, NNK concentrations in mainstream smoke 

increased and those of B[a]P decreased. Researchers 

attributed these changes to tobacco blends with higher 

levels of air-cured tobacco, the use of reconstituted 

tobacco, and other factors (Hoffmann et al. 2001). Other 

compounds that could be involved in lung cancer include 

1,3-butadiene, isoprene, ethylene oxide, ethyl carbamate, 

aldehydes, benzene, metals, and oxidants, but the collective evidence for each of these substances is not as strong 

as the evidence for PAHs and NNK (Hecht 1999). 

The particulate phase of cigarette smoke causes 

tumors of the larynx in hamsters, which could be attributed to PAHs (IARC 1986). TP53 gene mutations identified 

in tumors of the human larynx support a role for PAHs 

in the development of this cancer (Pfeifer et al. 2002). 

N-nitrosamines, as well as acetaldehyde and formaldehyde, induce nasal tumors in rodents and are likely candidates for causing nasal tumors associated with smoking 

(Preussmann and Stewart 1984; IARC 1995c, 1999). On 

the basis of animal studies, PAH, NNK, and NNN are the 

most likely causes of oral cancer in smokers (Hoffmann 

and Hecht 1990). N-nitrosamines are the most effective 

esophageal carcinogens known. NNN causes tumors of 

the esophagus in rats and is the most prevalent N-nitrosamine carcinogen in cigarette smoke (Hecht and Hoffmann 

1989; Lijinsky 1992). 

NNK and several other N-nitrosamines and furan 

in cigarette smoke are effective hepatocarcinogens in rats 

(Preussmann and Stewart 1984; IARC 1995b). NNK and 

its major metabolite NNAL are the only known pancreatic 

carcinogens in tobacco products. Biochemical data from 
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Table 5.12 Carcinogens and tobacco-induced cancers

Study Cancer type Likely carcinogen involvementa

Hoffmann and Hecht 1990

Hecht et al. 1994

Törnqvist and Ehrenberg 1994

Hecht 1999

Hoffmann et al. 2001

Pfeifer et al. 2002

Lung PAHs, NNK (major), 1,3-butadiene, isoprene, ethylene oxide, 

ethyl carbamate, aldehydes, benzene, metals

IARC 1986

Hoffmann et al. 2001

Pfeifer et al. 2002

Larynx PAHs

Preussmann and Stewart 1984

IARC 1995c, 1999

Hecht 1998

Nasal NNK, NNN, other nitrosamines, aldehydes

Hecht et al. 1986

Hoffmann et al. 1987, 1995, 2001

Hecht and Hoffmann 1988, 1989

Hoffmann and Hecht 1990

Hecht 1998

Vainio and Weiderpass 2003

Oral cavity PAHs, NNK, NNN

Hecht and Hoffmann 1989

Lijinsky 1992

Hecht 1998

Hoffmann et al. 2001

Esophagus NNN, other nitrosamines

Preussmann and Stewart 1984

IARC 1995a

Hecht 1998

Liver NNK, other nitrosamines, furan

Rivenson et al. 1988

Hecht 1998

Hoffmann et al. 2001

Prokopczyk et al. 2002

Pancreas NNK, NNAL

Melikian et al. 1999

Prokopczyk et al. 2001

Phillips 2002

Cervix PAHs, NNK

IARC 1974

Hoffmann and Hecht 1990

Skipper and Tannenbaum 1990

Skipper et al. 1994

Landi et al. 1996

Probst-Hensch et al. 2000

Hoffmann et al. 2001

Bladder 4-aminobiphenyl, other aromatic amines

IARC 1982 Leukemia Benzene

Source: Adapted from Hecht 2003 with permission.

Note: IARC = International Agency for Research on Cancer; NNAL = 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol; 

NNK = 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone; NNN = N’-nitrosonornicotine; PAHs = polycyclic aromatic hydrocarbons. aBased on carcinogenicity studies in laboratory animals, biochemical evidence from human tissues and fluids, and epidemiologic data 

when available.
Surgeon General’s Report

300 Chapter 5

studies of human tissue provide some support for the 

role of these carcinogens in smoking-related pancreatic 

cancer, although the studies did not detect DNA adducts 

(Rivenson et al. 1988; Prokopczyk et al. 2002, 2005). Biochemical studies demonstrate that both NNK and PAHs 

can reach the cervix in humans and are metabolically 

activated in these tissues (Melikian et al. 1999; Prokopczyk et al. 2001). Researchers have detected DNA adducts 

derived from B[a]P and other hydrophobic compounds in 

cervical tissue from smokers (Melikian et al. 1999; Phillips 

2002). Therefore, in combination with the human papilloma virus, these compounds may contribute to development of cervical cancer in smokers (IARC 1995a). 4-ABP 

and 2-naphthylamine are known human bladder carcinogens, and considerable data from human studies support 

the role of aromatic amines as the major cause of bladder 

cancer in smokers (IARC 1974; Skipper and Tannenbaum 

1990; Skipper et al. 1994; Landi et al. 1996; Probst-Hensch 

et al. 2000; Castelao et al. 2001). The most probable cause 

of leukemia in smokers is exposure to benzene, which 

occurs in large quantities in cigarette smoke and is a 

known cause of acute myelogenous leukemia in humans 

(IARC 1982).

Cigarette smoke causes oxidative damage probably 

because it contains free radicals, such as nitric oxide, and 

contains mixtures of hydroquinones, semiquinones, and 

quinones that can induce reduction and oxidation (redox 

cycling) (Pryor et al. 1998; Hecht 1999). Smokers have 

lower levels of ascorbic acid in plasma and, sometimes, 

higher levels of oxidized DNA bases in white blood cells 

than do nonsmokers. However, the role of oxidative damage as a cause of specific tobacco-induced cancers remains 

unclear (Hecht 1999). 

Tobacco Carcinogens, Immune 

System, and Cancer

Cigarette smoke alters a range of immunological functions including innate and adaptive immune 

responses (Sopori 2002). These effects, acting as tumorpromoting or cocarcinogenic stimuli, could affect 

tobacco-related carcinogenesis. Cigarette smoking 

increases the number of alveolar macrophages in the 

lung, possibly leading to higher levels of oxygen radicals 

and MPO activity, which are hypothesized to be important in tumor promotion. Investigators examined the 

effects of smoking on the function of natural killer (NK) 

cells—a lymphoid cell type involved in surveillance of 

tumor growth (Lu et al. 2007). They obtained strong evidence that suppression of NK cell activation was related 

to increased lung metastases in mice exposed to cigarette 

smoke. Other studies demonstrated that nicotine is 

immunosuppressive and thus might be responsible for 

some of the effects of cigarette smoke (Sopori 2002).

Epidemiology of Family History 

and Lung Cancer

Studies of familial aggregation of lung cancer provide indirect evidence supporting the possibility of an 

inherited component to tobacco carcinogenesis. A number of published studies showed that significantly more 

lung cancers were reported in first-degree relatives of probands with lung cancer than were reported in first-degree 

relatives of healthy control participants. Assuming that 

the family structure does not differ between cases and 

controls, this pattern could be explained by shared genes 

among the family members, shared smoking patterns, or 

a combination of both factors. By incorporating smoking 

histories of the probands and the first-degree relatives 

into a study of familial aggregation, researchers can begin 

to assess the level of familial risk of cancer while adjusting 

for tobacco use. However, few studies of familial aggregation incorporate history of involuntary exposure of family members to tobacco smoke. Estimates of the overall 

proportion of patients with lung cancer who have family history of lung cancer in a first-degree relative range 

from 6 (Li and Hemminki 2004) to 16 percent (Sellers et 

al. 1992).

Forty years ago, Tokuhata and Lilienfeld (1963) 

observed that the number of deaths from lung cancer 

was higher among relatives of lung cancer case patients 

than it was among relatives of control participants. These 

researchers also reported a fourfold excess of lung cancer 

mortality in nonsmoking relatives of 270 lung cancer probands. The effect among relatives who smoked was less 

pronounced (twofold). These findings suggest that the 

risk was not solely attributable to shared smoking patterns 

in the relatives. Other studies have since demonstrated a 

familial component of risk for lung cancer. The ORs associated with family history ranged from 1.3 to 7.2 (Ooi et al. 

1986; Samet et al. 1986; Wu et al. 1988, 1996; Osann 1991; 

Shaw et al. 1991; Schwartz et al. 1996; Mayne et al. 1999). 

For example, in a comparison of 336 lung cancer probands with relatives of control spouses, Ooi and colleagues 

(1986) reported an association between a family history 

of lung cancer and a threefold excess risk (OR = 3.09; 95 

percent CI, 1.9–5.0). Shaw and associates (1991) found an 

OR of 2.8 (95 percent CI, 1.2–6.6) for risk of lung cancer 

among two or more relatives of case patients. Brownson 

and colleagues (1997) reported a trend for increasing risk 

associated with the number of first-degree relatives with 
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lung cancer. The risk was more than twofold for persons 

with five affected family members. 

One approach that evaluates familial aggregation 

while controlling for the impact of smoking focused on 

lifetime nonsmokers. Wu and colleagues (2004) evaluated 216 lung cancer probands who were female nonsmokers and reported that family history of lung cancer 

was associated with a 5.7-fold (OR = 5.7; 95 percent CI, 

1.9–16.9) increase in lung cancer risk. Wu and colleagues 

(1988) noted, after adjustment for exposure to secondhand smoke, a 30-percent increase in risk that was not 

statistically significant for history of cancers of the 

respiratory tract. This association was especially evident 

in mothers and sisters. The risk was also slightly elevated 

for lung cancer (OR = 1.3; 95 percent CI, 1.0–1.6). Mayne 

and colleagues (1999) also focused on familial risk in a 

population-based, case-control study of 437 lifetime 

nonsmokers and former smokers who had lung cancer 

and 437 matched control participants. The investigators 

observed increased risk of cancers of the aerodigestive 

tract among parents of case patients (OR = 2.78; 95 percent 

CI, 1.30–5.95) and increased risk of lung cancer among 

siblings and offspring of case patients (OR = 4.14; 95 percent CI, 0.88–19.46; p = 0.07). They also reported approximately twofold increases in risk of breast cancer among 

mothers (OR = 2.52; 95 percent CI, 1.21–5.24) and sisters 

(OR = 2.07; 95 percent CI, 0.99–4.31) of lung cancer 

patients who were nonsmokers. On the other hand, 

Kreuzer and colleagues (2002) reported no evidence of 

familial risk in 234 lung cancer probands who were 

female nonsmokers.

Other investigators have reported familial aggregation of lung cancer among relatives of case patients who 

were nonsmokers with early-onset of lung cancer (at 

≤60 years of age). Schwartz and colleagues (1996) noted 

that family members of these case patients (aged 40 to 59 

years) had a sixfold increase in risk of lung cancer after 

adjustments for the age, gender, and race of each relative. 

In a subsequent study involving 118 population-based probands, Schwartz and colleagues (1999) also showed that 

family members of case patients younger than 40 years of 

age who had lung cancer were at increased risk for other 

cancers. Kreuzer and colleagues (1998) concluded that 

lung cancer in a first-degree relative was associated with a 

2.6-fold increase in risk of lung cancer among young case 

patients younger than 46 years of age. Elevated risk was 

not detected in older case patients. A study in Germany of 

945 lung cancer cases and 983 controls reported increased 

risk of lung cancer among first-degree relatives (RR = 1.7; 

95 percent CI, 1.1–2.5) and a 4.75-fold increase in risk 

among relatives of probands younger than 50 years of age 

who had a diagnosis of lung cancer (Bromen et al. 2000). 

Radzikowska and colleagues (2001) also noted stronger 

evidence from a study in Poland for aggregation of cancers 

among 757 patients with lung cancer who were younger 

than 50 years of age. 

On the other hand, Etzel and colleagues (2003) 

observed the familial aggregation of lung cancer and 

smoking-related cancers in late-onset lung cancers in 

persons older than 55 years of age, but not in early-onset 

lung cancers. An advantage of this study was the ability to 

adjust for the smoking status of the relatives. The study 

noted an excess of cancer among relatives of probands 

who were current smokers but not among relatives of lifetime nonsmokers. More recently, Li and Hemminki (2004) 

evaluated familial risks by using data from the Swedish 

Family Cancer Database and demonstrated that the histologic type of lung cancer in relatives was generally random. These researchers also estimated that 25 percent of 

familial lung cancers were diagnosed before 50 years of 

age, which represented about 1.6 percent of all lung cancers before 68 years of age. 

However, a cohort study of lung cancer mortality 

among male twins showed no role for genetic predisposition (Braun et al. 1994). Li and colleagues (1998b) used 

a parametric likelihood approach and adjustment for 

shared covariates to study familial association in the age at 

onset that they hypothesized to be attributable to genetic 

factors. The analysis indicated that a history of smoking, 

exposure to secondhand smoke, and chronic obstructive 

airway disease were all associated with lung cancer risk. 

After adjustments were made for these factors, there was 

little evidence of familial aggregation.

In a recent series with high-risk multiplex families, Bailey-Wilson and colleagues (2004) mapped a major 

susceptibility locus of lung cancer through a genomewide linkage analysis to chromosome 6q23–25 near the 

PARKIN gene, which carries predisposition for a significantly increased hereditary risk of lung cancer. A study 

of this locus also indicated presence of gene-environment 

interaction, and even light smoking by carriers of this 

gene significantly increased the risk for lung cancer compared with that among heavy smokers. Carriers who did 

not smoke had much lower risk, comparable to risk for 

noncarriers. This finding indicated existence of a sensitive group of persons for whom any amount of smoking 

is deleterious.

Studies have also presented evidence of Mendelian 

inheritance in lung cancer. Sellers and colleagues (1990) 

found that the pattern of occurrence of lung cancer was 

compatible with the Mendelian codominant inheritance 

of a rare and major autosomal gene. However, a similar 

study of families with lung cancer probands who did not 

smoke revealed no evidence for a major gene model and 

reported that an environmental model best explained 

the segregation pattern in the data (Yang et al. 1997). 
Surgeon General’s Report

302 Chapter 5

Gauderman and Morrison (2000) determined that when 

the same data were analyzed but missing data for smoking behaviors were produced from modeling techniques, a 

single autosomal dominant locus provided a slightly better fit than the codominant model suggested by Sellers 

and colleagues (1990). In addition to possible etiologic 

heterogeneity, the inconsistency of these findings may 

be partly due to the insufficient power for the statistical 

analysis of limited sample sizes. A reanalysis by Yang and 

colleagues (1999) found evidence of a major gene with the 

Mendelian codominant model in the families of probands 

of nonsmokers younger than 60 years of age. This analysis 

rejected both the codominant and environmental models 

and suggested that multiple genetic and/or environmental factors contribute to the age at onset of lung cancer. 

Therefore, researchers need more complex genetic models 

for the distribution of age at onset.

Xu and colleagues (2005) completed a segregation analysis on 14,378 persons from 1,561 case families 

with aggregation of lung cancer. In their modeling, these 

researchers adjusted for the effects of smoking, gender, 

and age. This work provided evidence for a model involving multiple gene loci and interactions that contribute to 

the age at onset of lung cancer. 

One caveat that applies to all of these studies is 

the validity of data on family history, an issue indirectly 

addressed in an evaluation of family histories of cancer in participants in the Prostate, Lung, Colorectal and 

Ovarian Cancer Screening Trial (Pinsky et al. 2003). The 

data showed that in the ratios of reported-to-expected 

rates of cancer in family members, there were important differences in rates of reporting family history of 

cancer according to the gender, race, ethnicity, and age 

of the respondents. These differences were mostly due to 

underreporting with respect to these covariates. Ziogas and Anton-Culver (2003) found that family histories 

of cancer reported by probands were more accurate for 

first-degree relatives and that probands referred through 

clinics had lower false-positive rates for reporting of family history than did population-based probands. Bondy 

and colleagues (1994) evaluated the accuracy of cancer 

diagnosis reported by probands among family members 

by comparing reported cancer information with documentation available through medical records and death 

certificates. The study noted high levels of accuracy for 

cancers of first-degree relatives, as evidenced by agreement 

between reporting by probands and information in 

records. Thus, these findings of familial aggregation suggest a role for the inherited susceptibility of lung cancer 

beyond that associated with familial clustering of smoking 

behaviors, taking into account family size and structure.

 A genomewide association study in 2008 identified 

a region of strong linkage disequilibrium on the long arm 

of chromosome 15 as a susceptibility locus for lung cancer (Amos et al. 2008). Studies replicating this association 

have focused attention on the most likely candidate genes 

in this region, CHRNA3 and CHRNA5, which encode subunits of the nAChR (Hung et al. 2008). Le Marchand and 

colleagues (2008) found that carriers of the lung-cancerassociated variants in these genes extract more nicotine 

and are thus exposed to a higher internal dose of carcinogenic nicotine-derived nitrosamines. SNPs in the same 

region have also been associated with nicotine dependence 

and smoking intensity (Caporaso et al. 2009). 

Evidence Summary

Although cigarette smoke contains diverse carcinogens, PAH, N-nitrosamines, aromatic amines, 1,3-butadiene, benzene, aldehydes, and ethylene oxide are among 

the most important carcinogens because of their carcinogenic potency and levels in cigarette smoke. Moreover, the 

major pathways of metabolic activation and detoxification 

of some of the principal carcinogens in cigarette smoke are 

well established. Reactive intermediate agents critical in 

forming DNA adducts include diol epoxides of PAH, diazonium ions generated by α-hydroxylation of nitrosamines, 

nitrenium ions formed from esters of N-hydroxylated aromatic amines, and epoxides such as ethylene oxide. Glutathione and glucuronide conjugation play major roles in 

detoxification of carcinogens in cigarette smoke.

Familial predisposition and genetic polymorphisms 

may play a role in tobacco-related neoplasms. Researchers have established cigarette smoking as a major cause 

of lung cancer; more than 85 percent of lung cancers are 

attributable to smoking. However, not all smokers develop 

lung cancer, and lung cancer can arise in lifetime nonsmokers. This variation in disease has stimulated interest in molecular epidemiology of genetic polymorphisms, 

including genes that regulate the cell cycle and genes 

for carcinogen-metabolizing enzymes that may lead to 

variations in susceptibility to the carcinogens in tobacco 

smoke. Studies to date suggest a role for these genetic 

polymorphisms in the risk of lung and bladder cancer in 

smokers, and they support the possibility of interactions 

between genes and smoking status. 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Quantitative analysis of carcinogens or their metabolites in urine, breath, and blood provides a convenient 

and reliable method of comparing exposure to carcinogens among smokers and between smokers and nonsmokers. Urinary biomarkers of several major types of 

carcinogens in cigarette smoke are reliable indicators of 

exposure, and the measurements provide good estimates 

of minimum doses of relevant carcinogens in smokers 

and allow comparisons with nonsmokers. The total carcinogen dose is generally difficult to calculate because the 

extent of conversion of a given carcinogen to the measured 

metabolite is usually unknown. However, relative carcinogen levels in cigarettes generally correlate with metabolite 

levels in urine. Comparisons of smokers and nonsmokers 

demonstrate that total NNAL is the most discriminatory 

biomarker in that tobacco products are the only source of 

the parent carcinogen NNK.

Evidence is overwhelming that DNA adduct levels 

are higher in most tissues of smokers than in corresponding tissues of nonsmokers. This observation provides 

bedrock support for the major pathway of cancer induction in smokers that proceeds through formation of DNA 

adducts and genetic damage. Studies of specific adducts 

are still scarce and are limited mainly to human lung tissue. Strong evidence supports the presence of a variety of 

specific adducts in the human lung, and in several studies, 

adduct levels are higher in smokers than in nonsmokers. 

Collectively, the results of these biomarker studies clearly 

demonstrate the potential for genetic damage in smokers 

from the persistence of DNA adducts. 

Adducts lead to mutations that drive the process 

of tumor formation and progression through additional 

genetic alterations. Chromosomal losses are more common in tumors from smokers. Furthermore, inactivating 

mutations of the TP53 tumor-suppressor gene and activating mutations of the KRAS oncogene in NSCLCs and other 

tumors are correlated with exposure to cigarette smoke, 

and they contribute to a phenotype that reduces survival 

time in both early and advanced stages of the disease. Different types of lung cancer in smokers all show an excess 

of G→T transversions compared with cancers that are not 

related to exposure to tobacco smoke. The site specificity 

of mutagenesis by PAH diol epoxides implies that targeted 

adduct formation, in addition to phenotypic selection, is 

responsible for shaping the TP53 mutational spectrum 

in lung tumors. Propagation of these genetic alterations 

during clonal outgrowth is consistent with accumulation 

of multiple genetic changes observed in progression of 

lung cancer.

Gene promoter hypermethylation is an epigenetic 

change involving extensive methylation at the 5-position 

of C in CpG islands within the promoter region and often 

extending into exon 1 of regulatory genes. The end result 

of this process can be loss of gene transcription and therefore the silencing of gene function. Promoter methylation 

of several genes including P16 occurs early in tumor formation. P16 methylation was significantly associated with 

pack-years of smoking and was an independent risk factor for shorter survival in patients with early resectable 

adenocarcinomas. Other genes such as RASSF1A may be 

more frequently methylated in various tumor types from 

smokers. Methylation of genes, such as AGT promoter 

hypermethylation, may increase G→A transition mutations at CpG sites within the TP53 gene in NSCLC.

The activation of nAChRs in lung epithelial cells 

by nicotine or NNK promotes survival and proliferation 

of cancer cells and also leads to increased angiogenesis. 

Activation of cell-surface receptors induced by components 

of tobacco smoke and subsequent activation of cytoplasmic kinases stimulate other proteins that dictate cellular 

responses, such as cell survival and proliferation. Although 

activated kinases have many downstream targets, the two 

most studied are the transcription factor NF-kB and proteins in the BCL-2 family. Activation of key intracellular 

proteins by tobacco smoke components through signaling 

cascades promotes processes that are important for initiation, progression, and maintenance of cancer. Apoptosis, 

the normal mechanism of endogenous cell elimination, is 

also commonly suppressed in lung cancer by these components. Thus, key genetic and epigenetic events that lead 

to cancer causation, as well as critical cellular pathways 

that further growth and development of transformed cells, 

are directly targeted by components of cigarette smoke 

individually and in combination as a potent carcinogenic mixture. 
Surgeon General’s Report

304 Chapter 5

Conclusions

1. The doses of cigarette smoke carcinogens resulting 

from inhalation of tobacco smoke are reflected in levels of these carcinogens or their metabolites in the 

urine of smokers. Certain biomarkers are associated 

with exposure to specific cigarette smoke carcinogens, 

such as urinary metabolites of the tobacco-specific 

nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-

butanone and hemoglobin adducts of aromatic amines. 

2. The metabolic activation of cigarette smoke carcinogens by cytochrome P-450 enzymes has a direct effect 

on the formation of DNA adducts.

3. There is consistent evidence that a combination of 

polymorphisms in the CYP1A1 and GSTM1 genes 

leads to higher DNA adduct levels in smokers and 

higher relative risks for lung cancer than in those 

smokers without this genetic profile.

4. Carcinogen exposure and resulting DNA damage 

observed in smokers results directly in the numerous 

cytogenetic changes present in lung cancer.

5. Smoking increases the frequency of DNA adducts of 

cigarette smoke carcinogens such as benzo[a]pyrene 

and tobacco-specific nitrosamines in the lung and 

other organs.

6. Exposure to cigarette smoke carcinogens leads to 

DNA damage and subsequent mutations in TP53 and 

KRAS in lung cancer. 

7. There is consistent evidence that smoking leads to the 

presence of promoter methylation of key tumor suppressor genes such as P16 in lung cancer and other 

smoking-caused cancers. 

8. There is consistent evidence that smoke constituents 

such as nicotine and 4-(methylnitrosamino)-1-(3-

pyridyl)-1-butanone can activate signal transduction 

pathways directly through receptor-mediated events, 

allowing the survival of damaged epithelial cells that 

would normally die. 

9. There is consistent evidence for an inherited susceptibility of lung cancer with some less common 

genotypes unrelated to a familial clustering of smoking behaviors. 

10. Smoking cessation remains the only proven strategy 

for reducing the pathogenic processes leading to cancer in that the specific contribution of many tobacco 

carcinogens, alone or in combination, to the development of cancer has not been identified.
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Cancer 350a

Table 5.2 DNA adducts in human lung tissue

Study Carcinogen DNA base Adduct structuresa

Type of 

evidenceb

Rojas et al. 1998, 2004

Boysen and Hecht 2003

Benzo[a]pyrene dG 1

Wilson et al. 1989

Mustonen et al. 1993

Kato et al. 1995

Blömeke et al. 1996

Petruzzelli et al. 1996

N-nitrosodimethylamine

NNK

Others

dG 7—CH3 2

Wilson et al. 1989

Mustonen et al. 1993

Kato et al. 1995

Blömeke et al. 1996

Petruzzelli et al. 1996

N-nitrosodimethylamine

NNK

Others

dG O6—CH3 2

Wilson et al. 1989

Blömeke et al. 1996

Godschalk et al. 2002

N-nitrosodiethylamine

Others

dG 7—CH3CH2 2

Wilson et al. 1989

Blömeke et al. 1996

Godschalk et al. 2002

N-nitrosodiethylamine

Others

dG O6—CH3CH2 2

Wilson et al. 1989

Blömeke et al. 1996

Godschalk et al. 2002

N-nitrosodiethylamine

Others

T O4—CH3CH2 2

Foiles et al. 1991 NNK

N’-nitrosonornicotine

dG, T, dC 1

Eide et al. 1999 Ethylene oxide dG 7—HOCH2CH2 2

Wilson et al. 1989

Lin et al. 1994

4-aminobiphenyl dG 2
Surgeon General’s Report

350b Chapter 5

Table 5.2 Continued

Study Carcinogen DNA base Adduct structuresa

Type of 

evidenceb

Godschalk et al. 2002 Vinyl chloride

Ethyl carbamate

Oxidants

Deoxyadenosine 2

Godschalk et al. 2002 Vinyl chloride

Ethyl carbamate

Oxidants

dC 2

Asami et al. 1997

Lee et al. 1999a

Oxidants dG 8—oxo 3

Note: dC = deoxycytidine; dG = deoxyguanosine; NNK = 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone; T = thymidine. aAdduct structures show position of attachment to the base (e.g., N2-, O6-, or 7- of dG) and the organic moiety derived from the carcinogen.

b1 = detection of a released adducted moiety by a specific method; 2 = detection of a nucleoside or base by a relatively nonspecific 

method (e.g., 32P-postlabeling or immunoassay); 3 = detection of a nucleoside or base by a specific method (e.g., mass spectrometry, 

high-performance liquid chromatography [HPLC]-fluorescence, or HPLC-electrochemical detection).
351

Chapter 6

Cardiovascular Diseases

Introduction 355

Tobacco Use and Cardiovascular Disease 355

Estimation of Risk 355

Coronary Heart Disease 356

Cigarettes Smoked per Day 356

Duration of Smoking 359

Smoking Cessation 359

Women 360

Race and Ethnicity 361

Sudden Death 361

Stroke 361

Aortic Aneurysm 362

Peripheral Arterial Disease 362

Pipes, Cigars, and Low-Tar Cigarettes 362

Summary 362

Secondhand Tobacco Smoke and Cardiovascular Disease 363

Pathophysiology 363

Cigarette Smoke Constituents and Cardiovascular Disease 363

Mechanisms 367

Hemodynamic Effects 368

Blood Pressure and Heart Rate 368

Coronary Blood Flow 368

Summary 370

Smoking and the Endothelium 370

Endothelial Injury or Dysfunction 370

Regeneration of Endothelium 370

Endothelial Dysfunctions 371

Nitric Oxide and Vascular Homeostasis 371

Endothelium-Dependent Vasodilation 372

Impairment of Endothelium-Dependent Vasodilation 372

Pathologic Angiogenesis 373

Summary 374
352

Thrombogenic Effects 374

Alterations in Blood 375

Platelets 375

Red Blood Cells 377

Leukocytes 378

Circulating Proteins 378

Alterations in Blood Vessels 380

Nitric Oxide 380

Prostacyclin Production 380

von Willebrand Factor 380

Tissue Factor 380

Tissue Plasminogen Activator 380

Summary 381

Exposure to Secondhand Tobacco Smoke 381

Nicotine and Thrombosis 381

Summary 382

Inflammation 382

Smoking and Diabetes 383

Risk 383

Metabolic Control 384

Insulin Resistance 384

Microvascular Complications 385

Nephropathy 385

Retinopathy 386

Neuropathy 386

Macrovascular Complications 386

Pathophysiological Mechanisms 387

Summary 387

Lipid Abnormalities 387

Epidemiologic Observations 387

Lipoprotein Composition and Apolipoprotein Levels 388

Plasma- and Lipoprotein-Associated Lipid Transfer Enzymes 388

Oxidized Lipoproteins 388

Postprandial Lipid Changes 388

Metabolism of Free Fatty Acids 389

Reverse Cholesterol Transport 390

Effects of Smoking Cessation 390

Therapeutic Implications of Pathogenic Mechanisms 390

Summary 391

Cardiovascular Biomarkers 391
353

Smoking Cessation and Cardiovascular Disease 394

Methods 395

Interventions 395

Counseling 398

Nicotine Replacement Therapy 399

Bupropion 400

Other Pharmacotherapy 401

Summary 402

Methods to Reduce Exposure 402

Reduced Smoking 403

Nicotine Replacement Therapy 406

Summary 406

Implications 407

Evidence Summary 407

Conclusions 408

References 409

Cardiovascular Diseases 355

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Introduction

This chapter reviews the epidemiology of smokinginduced cardiovascular disease (CVD) and the mechanisms by which tobacco smoke is thought to cause CVD. 

The discussion includes use of biomarkers to diagnose 

smoking-induced CVD and treatment implications of 

the pathophysiology of the disease. The link between 

secondhand smoke and CVD has been reviewed in the 2006 

report of the Surgeon General, The Health Consequences 

of Involuntary Exposure to Tobacco Smoke (U.S. Department of Health and Human Services [USDHHS] 2006), so 

discussion of secondhand smoke in this report is limited.

Tobacco Use and Cardiovascular Disease

Cigarette smoking is a major cause of CVD, and 

past reports of the Surgeon General extensively reviewed 

the relevant evidence (U.S. Department of Health, Education, and Welfare [USDHEW] 1971, 1979; USDHHS 

1983, 2001, 2004). Cigarette smoking has been responsible for approximately 140,000 premature deaths annually from CVD (USDHHS 2004). More than 1 in 10 deaths 

worldwide from CVD in 2000 were attributed to smoking 

(Ezzati et al. 2005). In the United States, smoking 

accounted for 33 percent of all deaths from CVD and 20 

percent of deaths from ischemic heart disease in persons 

older than 35 years of age (Centers for Disease Control and 

Prevention 2008). Cigarette smoking also influences other 

cardiovascular risk factors, such as glucose intolerance 

and low serum levels of high-density lipoprotein cholesterol (HDLc). However, studies have reported that smoking 

increases the risk of CVD beyond the effects of smoking on 

other risk factors. In other words, the risk attributable to 

smoking persisted even when adjustments were made for 

differences between persons who smoke and nonsmokers 

in levels of these other risk factors (Friedman et al. 1979; 

USDHHS 1983, 2001, 2004; Shaper et al. 1985; Criqui et 

al. 1987; Ragland and Brand 1988; Shaten et al. 1991; Neaton and Wentworth 1992; Freund et al. 1993; Cremer et 

al. 1997; Gartside et al. 1998; Wannamethee et al. 1998; 

Jacobs et al. 1999a). For example, in one study, the effect 

of cigarette smoking on the risk of coronary heart disease 

(CHD) was evident even among persons with low serum 

levels of cholesterol (Blanco-Cedres et al. 2002).

Beyond its status as an independent risk factor, 

smoking appears to have a multiplicative interaction with 

the other major risk factors for CHD—high serum levels 

of lipids, untreated hypertension, and diabetes mellitus 

(USDHHS 1983). For instance, if the presence of smoking 

alone doubles the level of risk, the simultaneous presence 

of another major risk factor is estimated to quadruple the 

risk (2 × 2). The presence of two other risk factors with 

smoking results in approximately eight times the risk (2 × 

2 × 2) of persons with no risk factors. Cigarette smoking 

also is a cause of peripheral arterial disease (PAD), aortic aneurysm, CHD, and cerebrovascular disease, but the 

relative risk (RR) of disease varies with the vascular bed 

(USDHEW 1971, 1979; USDHHS 1983, 2001, 2004). The 

highest RRs are observed for diseases of peripheral arteries in the lower extremities, and the lowest are for stroke; 

RRs are intermediate for CHD and aortic aneurysm.

The general mechanisms by which smoking results 

in cardiovascular events include development of atherosclerotic changes with narrowing of the vascular lumen 

and induction of a hypercoagulable state, which create 

risk of acute thrombosis (USDHHS 1983, 2004). The rapid 

decline in risk of a recurrent myocardial infarction (MI) 

after smoking cessation (USDHHS 1990) supports the role 

of smoking in thrombosis. In addition, abundant evidence 

demonstrates that smoking contributes to development 

of atherosclerotic plaque (Strong and Richards 1976; 

Auerbach and Garfinkel 1980; Solberg and Strong 1983; 

USDHHS 1983, 2004).

Estimation of Risk

The risk of CHD from cigarette smoking can be 

described in terms of RR and excess risk (Thun et al. 

1997). The RR is the ratio of CHD rates for populations 

of smokers to rates for lifetime nonsmokers. Excess risk 

is the difference between the rates of disease for smokers 

and nonsmokers. 

These two estimates of risk can lead to conflicting 

impressions of the changes in smoking-related CHD risks 

with advancing age. The RRs and excess death rates for 

CHD are shown by age group in data from Cancer Prevention Study II (CPS-II) (Thun et al. 1997), sponsored by the 

American Cancer Society (see Figure 6.1 for data on men). 
Surgeon General’s Report

356 Chapter 6

The RRs were highest at younger ages (35 to 54 years) and 

declined steeply with advancing age. This finding leaves 

the false impression that the disease burden of CHD from 

smoking declined with age or was low among older smokers. However, excess CHD death rates for smokers by age 

group presented different evidence. The high RR for CHD 

at younger ages can be explained in part because mortality rates are low for death from CHD at those ages and 

because coronary events in young people occur primarily 

among smokers. Even though RR declined with increasing age, because the absolute rate of deaths from CHD 

increased markedly, the magnitude of the CHD burden 

produced by smoking increased with advancing age.

The age at onset of substantial excess risk differs 

by disease. For smokers, age-specific excess death rates 

attributable to CHD, lung cancer, cerebrovascular disease, 

and chronic obstructive pulmonary disease (COPD) are 

illustrated by data from CPS-II (Figure 6.2 shows data for 

men) (Thun et al. 1997). For persons younger than age 45 

years, CHD was the dominant cause of increased mortality 

attributable to cigarette smoking. Excess rates for death 

from lung cancer increased steeply after age 50 years, and 

excess death rates from COPD were largely confined to 

the seventh and eighth decades of life. Late in life, excess 

deaths from COPD matched and those from lung cancer 

exceeded the excess death rates attributable to CHD. The 

RR for death from a cerebrovascular disease among smokers was substantially elevated among younger smokers 

(RR = 4 to 5; data not shown). However, the absolute rate 

of stroke at these younger ages was low, and this finding 

resulted in a low excess mortality rate. At older ages, the 

death rate from stroke in the general population increased 

and the RR among smokers declined, thus moderating the 

excess death rate attributable to smoking.

Coronary Heart Disease

Cigarettes Smoked per Day

Studies showed increased risk of having CHD at all 

levels of cigarette smoking, and increased risks were evident even for persons who smoked fewer than five cigarettes per day (Rosengren et al. 1992; Prescott et al. 2002; 

Bjartveit and Tverdal 2005). Prospective mortality studies 

conducted in the 1960s and 1970s showed a clear increase 

in CHD mortality with an increase in the number of cigarettes smoked per day, regardless of the actual number 

Figure 6.1 Relative risk and excess death rate for coronary heart disease among men, by age group

Source: Burns 2003. Adapted from Thun et al. 1997 with permission from Elsevier, © 2003.

Note: Data are from the American Cancer Society’s Cancer Prevention Study II; data table for above data found at end of chapter.
Cardiovascular Diseases 357

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

(Doll and Peto 1976; USDHHS 1983). Other studies suggested that risk increased up to at least 40 cigarettes per 

day (Miettinen et al. 1976; Willett et al. 1987). However, 

more recent data appeared to show an increase in CHD 

risk with more cigarettes smoked per day only up to about 

25 cigarettes; the risk increased relatively little even with 

further increases in cigarette consumption (Neaton and 

Wentworth 1992; Rosengren et al. 1992; Thun et al. 1997). 

Law and Wald (2003), who conducted a metaanalysis of five large studies of smoking and CHD, demonstrated a nonlinear dose-response relationship between 

the number of cigarettes smoked per day and the RR of 

disease (Figure 6.3). The researchers suggested that the 

effect of cigarette smoking on risk of CHD may have a low 

threshold and that the dose-response characteristics of 

the risk relationship are less steep at higher doses. This 

hypothesis was used to explain the seeming anomaly of a 

high RR of CHD associated with relatively low exposure to 

secondhand smoke. By using serum levels of cotinine (a metabolite of nicotine) as biomarkers of exposure, Whincup and colleagues (2004) explored the dose 

response relationship between exposure to cigarette 

smoke and CHD in persons involuntarily exposed to 

cigarette smoke. More than 2,000 men who said they 

did not smoke had blood levels of cotinine measured in 

1978–1980 and then had follow-up for 20 years. Nicotine exposure was examined by quartiles of blood cotinine as follows: less than or equal to 0.7 nanograms per 

milliliter (ng/mL), 0 to 1.4, 1.5 to 2.7, and 2.8 to 14.0. 

Hazard ratios for CHD, which included deaths and nonfatal MIs, were significantly increased at all upper quartiles (hazard ratios, 1.43 to 1.57) compared with the lowest 

exposure quartile, after adjustment for established CHD 

risk factors. Hazard ratios were also higher at the first 

and second five-year follow-ups (3.73 to 10.58 and 1.95 

to 2.48, respectively) than those at later follow-ups. The 

Figure 6.2 Age-specific excess death rates among male smokers for coronary heart disease, lung cancer, chronic 

obstructive pulmonary disease (COPD), and cerebrovascular disease

Source: Burns 2003. Adapted from Thun et al. 1997 with permission from Elsevier, © 2003.

Note: Data are from the American Cancer Society’s Cancer Prevention Study II; data table for above data found at end of chapter.
Surgeon General’s Report

358 Chapter 6

Figure 6.3 Dose-response relationship between number of cigarettes smoked per day and relative risk of ischemic 

heart disease

Source: Law and Wald 2003. Reprinted with permission from Elsevier, © 2003.

Note: The dose-response relationship between exposure to tobacco smoke and ischemic heart disease events is compartmentalized into 

separate associations attributable to confounding (difference between smokers and nonsmokers in blood pressure, body weight, blood 

lipids, and diet), cause and effect maximal at low dose, and cause and effect with linear dosimetry.

substantial cardiovascular risk attributable to involuntary 

exposure to cigarette smoke (USDHHS 2006) and the 

practice in most CVD studies of not excluding from the 

control group persons who had secondhand smoke exposure have resulted in underestimation, in many research 

reports, of the effects of active smoking compared with no 

exposure to cigarette smoke. 

The data on secondhand smoke and CHD risk indicate that the dose-response relationship between exposure 

to smoke and cardiovascular effects is nonlinear. Another 

consideration is that the number of cigarettes smoked 

per day may not provide a linear measure of exposure to 

tobacco smoke. When carboxyhemoglobin or serum cotinine levels were used as measures of the smoke taken in, 

persons who smoked more cigarettes per day had higher 

levels of these biologic substances (Benowitz 1996). Even 

so, the carboxyhemoglobin and cotinine levels were substantially lower than those predicted by linear extrapolation from data on persons who reported smoking 1 to 20 

cigarettes per day (Law et al. 1997). Among smokers of 40 

or more cigarettes per day, the levels of these biomarkers were 35 percent lower than those predicted by linear 

extrapolation from data on persons who reported smoking 

fewer than 20 cigarettes per day.

At the same reported number of cigarettes per day, 

cotinine levels varied substantially (Benowitz 1996). 

Smokers titrate cigarette smoke to achieve a consistent 

intake of nicotine by altering the number of cigarettes 

smoked per day or by changing the puffing pattern—

that is, by taking deeper, faster, more, or longer puffs 

(National Cancer Institute [NCI] 2001). When these smoking 

behaviors fail to restore the level of nicotine intake, as they 

may with cigarettes that have very low machine-measured 

yields, smokers may increase the number of cigarettes per 

day to maintain the same level of nicotine intake.

These observations suggest that the number of cigarettes smoked per day may have become a less precise 

measure of exposure to tobacco smoke with the introduction of cigarettes with low machine-measured yields of 

tar and nicotine. This diminished precision of cigarettes 

smoked per day as a measure of exposure may account 

for some of the discordance between studies that define 

increased risk by an increase of more than one pack per 

day in the number of cigarettes smoked. By using serum 

cotinine as an indicator of nicotine intake and exposure 

to tobacco smoke in the population demonstrates a linear 

increase for 10 to 15 cigarettes per day. However, as use 

exceeds 10 to 15 cigarettes per day, a progressively smaller 

increment in serum cotinine for each increment in the 

number of cigarettes smoked per day is observed (Caraballo et al. 1998; O’Connor et al. 2006). This flattening of the 

relationship between exposure and cigarettes smoked per 
Cardiovascular Diseases 359

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

day was similar to flattening of the relationship between 

the RR of CHD and the number of cigarettes smoked per 

day. Thus, researchers should be cautious about defining the absence of a continuing increase in risk among 

smokers of more than 20 cigarettes per day as evidence 

that increases in actual exposure are not accompanied by 

increases in risk. 

Duration of Smoking

Researchers have not always demonstrated a significant relationship between duration of cigarette smoking and CHD risk when adjustment was made for other 

risk factors and the number of cigarettes smoked per day 

(Kuller et al. 1991; Tverdal 1999). Variation in the number 

of cigarettes smoked per day and in the products smoked 

during the lifetime of a smoker is often substantial, but 

this variable is not well captured in epidemiologic studies. 

Age is colinear with duration of smoking, because 

the two variables grow in tandem after a person starts to 

smoke and the RRs for smoking and CHD decline with 

advancing age. Furthermore, most smokers begin to 

smoke during adolescence, which promotes the colinearity. These realities make it difficult to estimate the independent contributions of age and duration of smoking 

to risk of CHD in multivariate models. However, the two 

studies of the American Cancer Society are a good source 

of data, because each study consists of more than 1 million men and women (Burns et al. 1997; Thun et al. 1997). 

Analyses of these data stratified by age and the number 

of cigarettes smoked per day showed steady increases in 

CHD mortality rates with increasing duration of smoking 

for persons younger than age 70 years. Using data from 

CPS-I, investigators calculated the risk of developing CHD 

by age and duration of smoking (see Table 6.1 for data on 

White men) (Burns et al. 1997). For almost all age groups 

younger than age 70 years, RRs increased with increasing duration of smoking. Data from CPS-II on men (Thun 

et al. 1997) also demonstrated a pattern of increasing RR 

with age-specific mortality due to CHD and increasing 

duration of smoking for each level of cigarettes smoked 

per day (Table 6.2). Even though data in these analyses 

were not adjusted for potential differences in other cardiovascular risk factors, the findings presented a convincing picture of increasing risk of CHD with longer duration 

of smoking.

Smoking Cessation

The risks of MI and death from CHD are lower 

among former smokers than among continuing smokers 

in many studies, including those with data adjusted for 

levels of other risk factors (Gordon et al. 1974; Åberg et 

al. 1983; USDHHS 1990; Kuller et al. 1991; Frost et al. 

1996). The risk fell rapidly, decreasing about one-half in 

one year (Lightwood and Glantz 1997). Risks appear to 

remain slightly elevated for more than a decade after persons stopped smoking, but in some studies this increased 

risk was not statistically significant (Dagenais et al. 1990; 

Omenn et al. 1990; Kawachi et al. 1993a, 1994; Jacobs et 

al. 1999a; Qiao et al. 2000). Among smokers who had MI or 

angiographically documented CHD, persons who stopped 

smoking had a substantially lower rate of reinfarction than 

did those who continued to smoke. Reduction in risk was 

evident within the first year after MI. Risk continued to 

be lower among former smokers than among continuing 

Table 6.1 Rate ratios for coronary heart disease among White men, by age and duration of cigarette smokinga

   Duration of smoking (years)

Age (years) 20–24 25–29 30–34 35–39 40–44 45–49 50–54 55–59

40–44 1.95 2.47 4.23 NR NR NR NR NR

45–49 1.79 2.5 2.66 2.64 4.39 NR NR NR

50–54 2.06 2.25 2.22 2.74 2.82 3.4 NR NR

55–59 1.71 1.66 2.13 2.03 2.43 2.99 2.17 NR

60–64 1.83 1.44 1.86 1.75 1.92 2.12 2.45 4.06

65–69 1.34 1.56 1.52 1.61 1.49 1.6 2.09 2.25

70–74 1.17 1.14 1.23 1.08 1.55 1.26 1.53 1.78

75–79 1.09 1.2 1.31 1.12 1.55 1.46 0.94 1.36

Source: Adapted from Burns et al. 1997.

Note: NR = data not reported: data table for above data found at end of chapter. aFrom Cancer Prevention Study I, American Cancer Society.
Surgeon General’s Report

360 Chapter 6

smokers for prolonged periods after the first MI (Daly et al. 

1983; Omenn et al. 1990). Studies also demonstrated rapid 

reduction in risk after persons stopped smoking among 

populations at high risk for CHD (Ockene et al. 1990) and 

among women (Kawachi et al. 1993a, 1994). 

Patients with angiographically documented CHD 

who stopped smoking at the diagnosis of CHD (Vlietstra et 

al. 1986) or before diagnosis (Hermanson et al. 1988) had 

lower death rates from MI or CHD than did continuing 

smokers. In addition, the benefit of stopping smoking did 

not decline with advancing age.

In the 16-year follow-up of the Multiple Risk Factor 

Intervention Trial Research Group (1990, 1996), mortality 

from CHD was 11.4 percent lower in the “special intervention” group than in the “usual care” group. This result 

may illustrate the benefit of stopping smoking, because 

one of the interventions targeted smoking cessation. A 

trial of advice to civil servants in London, England, to stop 

smoking demonstrated an 18-percent reduction in mortality from CHD in the intervention group versus the control 

group after 10 years of follow-up (Rose et al. 1982). Suskin 

and colleagues (2001) reported that in addition to benefits 

for CHD, stopping smoking also reduces morbidity and 

mortality in patients with left ventricular dysfunction. In 

this study, the benefits of stopping smoking on mortality 

and recurrent congestive heart failure requiring hospitalization were similar to the benefits from treatments with 

angiotensin-converting-enzyme (ACE) inhibiting drugs, 

b-blockers, or spironolactone, which are mainstays for 

the treatment of heart failure.

Women

Women have lower absolute rates of CHD than do 

men. However, cigarette smoking has been associated 

with higher RR of MI (Njølstad et al. 1996) and higher 

CHD mortality (Kawachi et al. 1994; Thun et al. 1997) 

among women than among men. The absolute increase in 

risk of CHD from smoking is similar for men and women 

(USDHHS 1983, 2001).

A prospective evaluation of fatal and nonfatal CVD 

events among women in the Nurses’ Health Study (Willett 

et al. 1987) found that smoking was an independent cause 

of CVD. Age-adjusted risks of disease increased progressively with more cigarettes smoked per day up to 45 or 

more per day. Even when the combined risks of fatal CHD 

and nonfatal MI were adjusted for levels of other risk factors, risks increased with increasing numbers of cigarettes 

per day.

Researchers have demonstrated a rapid decline in 

excess risk of CHD in women after they stopped smoking cigarettes. Even so, 10 to 14 years of nonsmoking are 

required before risks approach those of lifetime nonsmokers (Kawachi et al. 1993a, 1994). 

Table 6.2 Death rates and rate ratios for death from coronary heart disease among men, by age and duration of 

smoking by number of cigarettes smoked per daya

      Death rates (per 100,000)b Rate ratiosc

Number of 

cigarettes/

day

Age 

(years)

20–29 yrs 

smoking

30–39 yrs 

smoking

40–49 yrs 

smoking

≥50 yrs 

smoking

20–29 yrs 

smoking

30–39 yrs 

smoking

40–49 yrs 

smoking

≥50 yrs 

smoking

1–19 50–59 241.1 276 277.9 NR 2.7 3.1 3.2 NR

1–19 60–69 340.6 560.3 643.5 866.5 1.1 1.8 2.1 2.8

20 50–59 213.9 272.6 493.4 956.4 2.4 3.1 5.6 NR

20 60–69 299.9 509 729.5 1,088.9 1 1.6 2.4 3.5

21–39 50–59 195.8 237.4 367.2 NR 2.2 2.7 4.2 NR

21–39 60–69 232.2 350.8 607.2 1,113.4 NR 1.1 2 3.6

40 50–59 144.9 281.6 321.4 664.5 1.6 3.2 3.7 NR

40 60–69 470.8 458.3 607.6 988.3 1.5 1.5 2 3.2

Source: Adapted from Thun et al. 1997.

Note: NR = data not reported; data table for above data found at end of chapter. aFrom Cancer Prevention Study II, American Cancer Society (CPS-II).

bCPS-II data, Appendix Table 10, Thun et al. 1997.

cCPS-II data, Appendix Table 12, Thun et al. 1997.
Cardiovascular Diseases 361

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Race and Ethnicity

In 2004, heart disease mortality was higher among 

African Americans than among Whites (National Heart, 

Lung, and Blood Institute [NHLBI] 2007). From 1999 

through 2004, the prevalence of acute MI was higher for 

African Americans than for Whites aged 35 through 54 

years; however, for ages 55 years and older, the prevalence 

of acute MI was higher among Whites (NHLBI 2007).

The INTERHEART study is a case-control investigation of acute MI in 52 countries in Africa, Asia, Australia, 

the Middle East Crescent, and North and South America (Teo et al. 2006). The odds ratio (OR) for acute MI in 

smokers was 2.95 for this large multiethnic population 

compared with lifetime nonsmokers. In addition, the risk 

of MI was higher among persons who smoked bidis than 

among nonsmokers in countries where use of this form of 

tobacco is common.

Researchers also identified cigarette smoking as 

a significant risk factor for CHD among Hispanic populations (Mendelson et al. 1998) and Asian populations 

(Kiyohara et al. 1990; Miyake et al. 2000; Lam et al. 2002).

Sudden Death

Most sudden death is due to CVD. In many epidemiologic studies, RRs for sudden cardiac death were higher 

than RRs for CHD or MI among persons who smoked. The 

RRs for sudden death among current smokers, compared 

with lifetime nonsmokers, often exceeded 3.0 (USDHEW 

1971, 1979; Dawber 1980; Kannel and Thomas 1982; 

USDHHS 1983; Wannamethee et al. 1995; Sexton et al. 

1997). In multivariate analyses of the combined data from 

the Framingham Heart Study and the Albany Study, which 

examined sudden cardiac death in men aged 45 through 

64 years, cigarette smoking was the risk factor with the 

highest statistical significance (Kannel et al. 1975). In a 

study of data from the 1986 National Mortality Followback 

Survey among persons with no history of CHD, cigarette 

smoking was the only modifiable risk factor associated 

with sudden coronary death and it was one factor associated with increased risk of sudden coronary death among 

persons with known CHD (Escobedo and Zack 1996; Escobedo and Caspersen 1997). Cigarette smoking was also 

associated with risk of sudden cardiac death in the 18-year 

follow-up of the Honolulu Heart Program (Kagan et al. 

1989) and the 28-year follow-up of the Framingham Heart 

Study (Cupples et al. 1992).

Peters and colleagues (1995) found an association between smoking cessation and reduction in death 

from cardiac arrhythmia for patients with left ventricular 

dysfunction after MI. Finally, the risk of recurrent cardiac 

arrest among smokers surviving out-of-hospital cardiac 

arrest was lower among persons who then stopped smoking than among those who continued to smoke (Hallstrom et al. 1986). 

Stroke

After adjustment of data for other risk factors, 

cigarette smokers have higher risk of stroke and higher 

mortality from cerebrovascular disease than do lifetime 

nonsmokers, and a dose-response relationship is evident 

(USDHHS 1983, 2001, 2004; Neaton et al. 1984; Colditz 

et al. 1988; Wolf et al. 1988; Kannel and Higgins 1990; 

Kuller et al. 1991; Freund et al. 1993; Hames et al. 1993; 

Håheim et al. 1996; Tanne et al. 1998; Jacobs et al. 1999a; 

Sharrett et al. 1999; Djoussé et al. 2002). In addition, in 

the 20-year follow-up of a prospective study of mortality that controlled for other cardiovascular risk factors, 

cigarette smoking increased the risk of death from stroke 

and mortality rates grew the number of cigarettes smoked 

increased (Hart et al. 1999). 

In a meta-analysis of data from 32 studies, the overall RR for stroke associated with cigarette smoking was 

1.5 (95 percent confidence interval [CI], 1.4–1.6) (Shinton and Beevers 1989). The RRs varied with the stroke 

subtypes: 1.9 for cerebral infarction, 0.7 for cerebral 

hemorrhage, and 2.9 for subarachnoid hemorrhage. The 

researchers reported a dose-response relationship 

between the number of cigarettes smoked per day and the 

RR. The data suggested a sustained higher risk of stroke 

among former smokers younger than age 75 years than 

the risk for nonsmokers in the same age group. For all 

ages combined, RR for former smokers was 1.2.

During the 26-year follow-up of the cohort in the 

Framingham Heart Study, cigarette smoking was a significant risk factor for stroke (Wolf et al. 1988). The risk 

declined, however, among smokers who had stopped 

smoking for two years and was similar to that of lifetime 

nonsmokers after five years of abstinence from smoking. In the 12-year follow-up of the Nurses’ Health Study 

(Kawachi et al. 1993b), RR for stroke among current 

smokers was 2.58 compared with nonsmokers, but it was 

1.34 among former smokers compared with nonsmokers. Once those who stopped smoking had abstained for 

two to four years, their risk for stroke could not be distinguished from that of lifetime nonsmokers. In addition, 

the pattern of decline in total risk for stroke after stopping 

smoking remained the same after adjustments for other 

risk factors.
Surgeon General’s Report

362 Chapter 6

Aortic Aneurysm

Mortality studies consistently demonstrated higher 

risk of death from abdominal aortic aneurysm among cigarette smokers than among nonsmokers (Hammond and 

Horn 1958; Weir and Dunn 1970; USDHHS 1983, 2004; 

Strachan 1991; Nilsson et al. 2001). In addition, the risk 

rose with an increasing number of cigarettes smoked per 

day (Kahn 1966; Hammond and Garfinkel 1969; Burns et 

al. 1997; Blanchard et al. 2000; Vardulaki et al. 2000). 

Studies have demonstrated an association of cigarette smoking with prevalence of aortic aneurysm or aortic dilation, as determined by ultrasonography in cohorts 

of men and women, even after adjustment for a large 

number of known risk factors (Alcorn et al. 1996; Lee et 

al. 1997; Wilmink et al. 1999; Jamrozik et al. 2000; Lederle et al. 2001). The U.S. Preventive Services Task Force 

(2005) recommended a one-time screening by ultrasonography for abdominal aortic aneurysm among men aged 65 

to 75 years who had ever smoked. Cigarette smoking has 

been associated with increased growth of abdominal aortic 

aneurysms (Brady et al. 2004). This finding suggests that 

more frequent monitoring of smokers for this condition 

is necessary. With increasing duration of abstinence from 

smoking, the risk of developing an abdominal aneurysm 

appears to slowly decline (Wilmink et al. 1999). 

Peripheral Arterial Disease

Cigarette smoking and diabetes are well established 

as the major risk factors for PAD, and a strong doseresponse relationship for smoking was observed even after 

adjustment for other CVD risk factors (Weiss 1972; Kannel and Shurtleff 1973; USDHHS 1983; Wilt et al. 1996; 

Price et al. 1999; Meijer et al. 2000; Ness et al. 2000). 

Data from the Framingham Heart Study demonstrated 

increased risk of PAD among both young and older male 

and female cigarette smokers after adjustment for other 

cardiovascular risk factors. In addition, this risk increased 

with the increase in the number of cigarettes smoked per 

day, and this result was statistically significant (Freund 

et al. 1993). The Framingham Offspring Study reported a 

similar finding (Murabito et al. 2002). Finally, researchers 

have observed a significantly higher rate of late arterial 

occlusion in patients who continued to smoke after 

peripheral vascular surgery than in those who stopped 

smoking (Wray et al. 1971; Ameli et al. 1989; Wiseman et 

al. 1989). Among smokers with claudication, progression 

to critical limb ischemia is reduced in those who stopped 

smoking (Jonason and Bergström 1987).

Pipes, Cigars, and 

Low-Tar Cigarettes

“Low-tar” or “light” cigarettes were designed to 

produce low machine-measured yields of tar and nicotine 

(NCI 2001). Design characteristics of low-tar cigarettes 

include increased ventilation and more rapid cigarette 

burn rate. By changing the way they smoke or the number 

of cigarettes smoked, persons who smoke these products 

can obtain as much nicotine as from “regular” or “fullflavored” cigarettes, thereby satisfying their addiction 

(USDHEW 1979; NCI 2001). Comprehensive reviews of 

this issue concluded that use of low-tar cigarettes has not 

resulted in meaningful reduction in the risk of CVD (NCI 

2001; Stratton et al. 2001; Scientific Advisory Committee 

on Tobacco Product Regulation 2002; USDHHS 2004).

Compared with persons who smoke cigarettes, 

smokers who exclusively smoke pipes or cigars have lower 

risk for many smoking-related diseases (NCI 1998). Smoke 

from pipes and cigars contains the same toxic substances 

as cigarette smoke, but those who use a pipe or cigar usually smoke at lower intensity; observation indicates that 

they tend not to inhale the smoke, thus reducing their 

exposure to its toxic substances (USDHEW 1979; NCI 

1998; Shanks et al. 1998). Most current cigar users are 

young males who often smoke less than one cigar daily 

(NCI 1998); no data on risk for this population are available. For older adults who regularly use cigars, particularly those who smoke more than one cigar per day or inhale 

the smoke, risk of CHD is modestly higher than that for 

nonsmokers (NCI 1998; Iribarren et al. 1999; Jacobs et al. 

1999b; Baker et al. 2000). Studies have reported similar 

increases in risks for CHD and cerebrovascular disease for 

persons who smoke a pipe exclusively (Henley et al. 2004).

Summary

Cigarette smoking and involuntary exposure to 

cigarette smoke are major causes of CHD, stroke, aortic 

aneurysm, and PAD. The risk is seen both as an increased 

risk of acute thrombosis of narrowed vessels and as an 

increased degree of atherosclerosis in the blood vessels 

involved. The cardiovascular risks attributable to cigarette 

smoking increase with the number of cigarettes smoked 

and with the duration of smoking. However, risk is substantially increased even by exposure to low levels of cigarette smoke as with exposure to secondhand smoke or 

smoking a few cigarettes per day. Risks are not reduced 

by smoking cigarettes with lower machine-measured 
Cardiovascular Diseases 363

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

yields of tar and nicotine. Smokers of only pipes or 

cigars seem to have lower risks of CVD than do cigarette 

smokers. However, cigarette smokers who switch to pipes 

or cigars often inhale the tobacco smoke and may not 

experience the lower CVD risk of persons who primarily 

smoke a pipe or cigar. Stopping cigarette smoking and 

eliminating exposure to secondhand smoke rapidly and 

substantially reduce risks of various CVDs.

Secondhand Tobacco Smoke and Cardiovascular Disease

The 2006 Surgeon General’s report on involuntary exposure to tobacco smoke (USDHHS 2006) and 

Barnoya and Glantz (2005) extensively reviewed risks of 

CVD among nonsmokers exposed to secondhand tobacco 

smoke. They found a causal relationship among both men 

and women between exposure to secondhand smoke and 

increased risks of CHD morbidity and mortality. Pooled 

RRs from meta-analyses indicated a 25- to 30-percent increase in risk of CHD from exposure to secondhand smoke. 

The study by Whincup and associates (2004), which was 

based on blood levels of cotinine in men, suggested a 

50- to 60-percent increase in risk of CHD from exposure 

to secondhand smoke. The risk of acute MI appeared to 

decline rapidly after cessation of exposure to secondhand 

smoke, as evidenced by a decline in hospital admissions 

for MI after smoke-free laws were put in place (Dinno and 

Glantz 2007; Lightwood and Glantz 2009; Meyers et al. 

2009). As for stroke, the evidence was insufficient to infer 

a causal relationship between increased risk of CHD morbidity and mortality and exposure to secondhand smoke. 

Studies of the effects of secondhand smoke on subclinical vascular disease, particularly thickening of the walls 

of the carotid arteries, also suggest a causal relationship 

between exposure to secondhand smoke and atherosclerosis. As mentioned previously, the substantial CVD risk 

associated with involuntary exposure to cigarette smoke 

indicates that the risks estimated in most studies of active 

smoking are biased downward because the control groups 

generally included large numbers of persons with exposure to secondhand smoke. 

Pathophysiology

This section on pathophysiology focuses primarily 

on mechanisms by which cigarette smoking may increase 

risk of CVD.

Cigarette Smoke Constituents and 

Cardiovascular Disease

Three constituents of cigarette smoke have received 

the greatest attention as potential contributors to CVD: 

nicotine, carbon monoxide (CO), and oxidant gases. Some 

research also investigated the contributions of polycyclic 

aromatic hydrocarbons (PAHs), particulate matter, and 

other constituents of tobacco smoke to the pathophysiology of CVD including atherogenesis (Brook et al. 2004; 

Vermylen et al. 2005; Bhatnagar 2006). 

Nicotine, which is absorbed rapidly from cigarette 

smoke, was found in arterial blood levels of 40 to 100 ng/

mL after each cigarette was smoked (Henningfield et al. 

1993). The typical dose of nicotine systematically absorbed 

from each cigarette is 1 to 2 milligrams (mg). Although 

plasma nicotine levels peaked sharply after each cigarette, 

trough values also rose during the first six to eight hours 

of regular smoking during the day (Benowitz et al. 1982a). 

This accumulation pattern was consistent with an elimination half-life for nicotine of two hours (Benowitz et al. 

1982a). In persons who smoke regularly, venous plasma 

levels of nicotine reached a plateau in early afternoon and 

remained at that level until bedtime (Figure 6.4). Significant levels of nicotine were in the smoker’s venous blood 

even on waking in the morning. Thus, these findings 

indicate that the regular smoker is exposed to significant 

levels of nicotine 24 hours per day. 

Nicotine is a sympathomimetic drug that releases 

catecholamines both locally from neurons and systemically from the adrenal gland. In studies of the pharmacodynamics of nicotine, the intensity of its maximal effect 

was greater with more rapid delivery (Porchet et al. 1987). 

Pharmacodynamic studies also indicated that although 

tolerance to the effects of nicotine developed rapidly, tolerance was incomplete (Porchet et al. 1987). In one study, 

a constant intravenous infusion of nicotine increased the 
Surgeon General’s Report

364 Chapter 6

heart rate even though nicotine levels in the blood were 

relatively low. As the infusion continued, the heart rate 

reached a plateau despite a progressive rise in blood levels 

of nicotine (Benowitz et al. 1982a). The same phenomenon was observed in comparisons of acceleration of heart 

rate with level of blood nicotine during regular cigarette 

smoking throughout the day (Benowitz et al. 1984). 

In another study, heart rate measured by ambulatory 

monitoring was higher throughout the day when persons 

were smoking than when they were not smoking (Benowitz et al. 1984). The extent of elevation was independent of 

the blood level of nicotine absorbed from the cigarettes. 

The researchers concluded that the elevated heart rate 

reflected persistent stimulation of the sympathetic 

Figure 6.4 Plasma nicotine and carboxyhemoglobin concentrations throughout a day of cigarette smoking

Source: Benowitz 2003. Adapted from Benowitz et al. 1982b with permission from Elsevier, © 2003.

Note: Mean (± standard error of measurement) blood nicotine and carboxyhemoglobin concentrations in cigarette smokers. 

Participants smoked cigarettes every half-hour from 8:30 a.m. to 11:00 p.m., for a total of 30 cigarettes per day. ng/mL = nanograms 

per milliliter.
Cardiovascular Diseases 365

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

nervous system, a possible contributing factor to CVD. 

Nicotine may also contribute to endothelial dysfunction, lipid abnormalities, and insulin resistance (Beno

witz 2003). 

CO is a major constituent of cigarette smoke. In 

regular smokers, carboxyhemoglobin levels average 

about 5 percent, compared with 10 percent or higher 

in heavy smokers (Benowitz et al. 1982b). These values 

compare with levels of 0.5 to 2 percent in nonsmokers, 

depending on exposure to automobile exhaust. Like nicotine levels, elevated carboxyhemoglobin levels persist for 

24 hours a day in smokers (Figure 6.4).

CO exposure can aggravate ischemia and worsen 

symptoms in persons with vascular disease, although it is 

not clear that CO contributes directly to atherosclerosis 

(Benowitz 2003). CO binds avidly to hemoglobin, reducing the amount of hemoglobin available to carry oxygen 

and impeding release of oxygen by hemoglobin. In some 

studies, inhalation of CO at levels comparable to those in 

cigarette smokers reduced exercise tolerance in patients 

with angina pectoris, intermittent claudication, or COPD 

(Calverley et al. 1981; Allred et al. 1989). Another study 

reported that CO exposure in persons with obstructive 

coronary disease resulted in a greater degree of exerciseinduced ventricular dysfunction and an increase in the 

number and complexity of ventricular arrhythmias during exercise (Sheps et al. 1990). Inhaling CO reduced the 

threshold for ventricular fibrillation in animals (DeBias et 

al. 1976).

Long-term CO exposure in smokers resulted in 

greater red blood cell mass and reduced the oxygencarrying capacity of red blood cells, resulting in relative 

hypoxemia (Benowitz 2003). In response to hypoxemia, 

red blood cell masses increased to maintain the amount of 

oxygen needed by organs in the body. The increase in red 

blood cell mass increased blood viscosity and may contribute to hypercoagulation in smokers. 

Cigarette smoke delivers a high level of oxidizing 

chemicals to smokers, including oxides of nitrogen and 

many free radicals from both the gas and tar phases of 

cigarette smoke (Church and Pryor 1985). Exposure to 

oxidant chemicals in smoke was associated with depletion 

of endogenous levels of antioxidants, manifested as lower 

blood levels of vitamin C in smokers than in nonsmokers (Lykkesfeldt et al. 2000). Cigarette smoking also was 

reported to increase levels of lipid peroxidation products 

in the plasma and urine of smokers (Morrow et al. 1995). 

Study results also indicated that oxidant stress contributes to several potential mechanisms of CVD, including 

inflammation, endothelial dysfunction, lipid abnormalities such as oxidation of low-density lipoprotein (LDL), 

and platelet activation (Burke and FitzGerald 2003).

Acrolein, a reactive aldehyde produced by endogenous lipid peroxidation, is present at high levels in cigarette smoke. Acrolein binds covalently to form protein 

adducts, and acrolein-induced modification of proteins 

has been implicated in atherogenesis. Acrolein modifies 

apolipoprotein A-I (APO A-I), the major protein in HDL 

(Shao et al. 2005). HDL protects against atherosclerosis. 

Acrolein-protein adducts co-localize with APO A-I in macrophages in the intima of human atheromatous blood vessels (Szadkowski and Myers 2008). 

Acrolein also oxidized thioredoxins 1 and 2 in endothelial cells. Thioredoxins are prominent antioxidant 

proteins that regulate the oxidation-reduction balance 

critical for normal cell function. These results suggest 

that oxidation of thioredoxins can result in dysfunction 

and death of endothelial cells, contributing to atherosclerosis. In addition, acrolein induces production of the 

enzyme cyclooxygenase-2 (COX-2) in human endothelial 

cells in vitro (Park et al. 2007). This finding is relevant 

because COX-2 is expressed in atherosclerotic lesions and 

may participate in atherogenesis. Acrolein may contribute 

to thrombogenicity in smokers by inhibiting antithrombin activity (Gugliucci 2007). Finally, acrolein induces 

hypercontraction in isolated human arteries and could 

contribute to smoking-induced coronary vasospasm 

(Conklin et al. 2006).

Cigarette smoke contains a number of metals, including aluminum, cadmium, copper, lead, mercury, 

nickel, and zinc. Metals in cigarette smoke catalyze the 

oxidation of cellular proteins (Bernhard et al. 2005). This 

reaction may lead to structural damage, endothelial dysfunction, and detachment of endothelial cells from the 

walls of blood vessels. Mixtures of metals and oxidants 

may be particularly damaging to endothelial cells. Cadmium levels are higher in serum of smokers, and cadmium 

accumulates in the aortic walls of smokers (Abu-Hayyeh 

et al. 2001). Epidemiologic evidence indicates an association between serum levels of cadmium and lead and CVD, 

including hypertension and MI (Abu-Hayyeh et al. 2001). 

PAHs found in the tar fraction of cigarette smoke 

reportedly accelerated atherosclerosis in experimental animals. Weekly injections of benzo[a]pyrene and 

7,12-dimethylbenz[a]anthracene, at doses below those 

that produce tumors, increased development of atherosclerotic plaque in the aortas of cockerels (Penn and Snyder 1988). Similarly, inhaled butadiene, a component of 

the vapor phase of cigarette smoke, increased the amount 

of atherosclerotic plaque in the same animal model (Penn 

and Snyder 1996). The researchers speculated that one 

mechanism of atherogenesis is a mutation, followed by 

hyperproliferation of smooth muscle or other cells that 

may contribute to growth of atherosclerotic plaque.
Surgeon General’s Report

366 Chapter 6

Studies of the cardiovascular effects of smokeless tobacco may be informative for understanding the 

pathophysiology of smoking-induced CVD. Oral and nasal 

smokeless tobacco products have been used for centuries 

around the world (International Agency for Research on 

Cancer [IARC] 2007). Traditional smokeless tobacco products vary widely among countries; however, similar to 

Sweden, forms of oral snuff are the most common types 

of products used in the United States (Substance Abuse 

and Mental Health Services Administration 2009). These 

products contain a large array of chemicals, including nicotine, nitrosamines, nitrosamine acids, PAHs, aldehydes, 

and metals (IARC 2007). A recent systematic review 

reported that studies from both the United States and 

Sweden showed an increased risk of death from MI and 

stroke related to the frequency and duration of use of 

smokeless tobacco products (Boffetta and Straif 2009). 

This review relied heavily (85–89 percent of the weight) 

on results of a large U.S. cohort study conducted in 

two waves between 1959–1971 and 1982–1988 and may 

Figure 6.5 Overview of mechanisms by which cigarette smoking causes an acute cardiovascular event

Source: Benowitz 2003. Reprinted with permission from Elsevier, © 2003.
Cardiovascular Diseases 367

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

not represent risk associated with products currently 

marketed in the United States and Europe. As in cigarettes, nicotine is the principal alkaloid in smokeless 

tobacco products, and the concentrations of nicotine (mg/

gram [g] tobacco) are similar between cigarettes and the 

types of oral snuff sold in the United States (Djordjevic 

and Doran 2009). An analysis comparing the effects of 

using oral snuff with those of smoking cigarettes provided insights into the role of nicotine versus the effects 

of other toxins from tobacco smoke on CVD and cardiovascular risk factors (Benowitz et al. 1988, 1989). In 

addition clinical trials of nicotine patches in patients with 

known CVD have not shown that transdermal nicotine 

increased cardiovascular risk (Working Group for the 

Study of Transdermal Nicotine in Patients with Coronary 

Artery Disease 1994; Joseph et al. 1996). In the study 

of 3,094 middle-aged smokers with chronic obstructive lung disease, the U.S. Lung Health Study found no 

evidence of increased cardiovascular risk in subjects who 

quit smoking by using nicotine gum versus those who 

quit without use of nicotine gum (Murray et al. 1996). 

These studies and related evidence suggest that chemicals other than nicotine may contribute to the elevated 

risk of death from MI and stroke. In the INTERHEART 

study, the OR of acute MI was 2.23 among those who 

used only smokeless tobacco compared with those who 

used no tobacco. The OR was comparable to that of current cigarette smokers (OR = 2.95) compared with those 

who used no tobacco (Teo et al. 2006). In addition, the 

risk of acute MI among smokers who also used smokeless 

tobacco was the highest risk related to tobacco use (OR = 

4.09), suggesting that some of the toxicants involved in 

the elevated cardiovascular risk could be contained in both 

tobacco smoke and smokeless products. Smokeless 

tobacco products have been found to have significant 

amounts of numerous other toxicants and carcinogens, 

particularly tobacco-specific nitrosamines as well as 

volatile aldehydes and PAHs (Stepanov et al. 2008). Additional research on these and other toxicants in smokeless 

tobacco, such as heavy metals like cadmium, is needed to 

understand the observed cardiovascular risks among users 

of smokeless tobacco products.

Mechanisms

Cigarette smoking produces acute myocardial ischemia by adversely affecting the balance of demand for 

myocardial oxygen and nutrients with myocardial blood 

supply (Figure 6.5). The increase in demand for oxygen 

in the myocardium is a consequence of nicotine stimulation of the sympathetic nervous system and the heart. 

Cigarette smoking acutely increases levels of plasma 

norepinephrine and epinephrine and enhanced 24-hour 

urinary excretion of these catecholamines (review by 

Benowitz and Gourlay 1997). Regular smoking increases 

the heart rate both in the short term (up to 20 beats per 

minute) and throughout the day (average increase, 7 beats 

per minute), as measured during ambulatory monitoring. 

Nicotine also increases heart rate, blood pressure, and 

myocardial contractility. These hemodynamic changes 

result in increases in myocardial work that in turn require 

increased myocardial blood flow.

In healthy persons, cigarette smoking increases coronary blood flow in response to increases in myocardial 

work. In smokers, the response in coronary blood flow to 

increased myocardial demand was impaired (i.e., reduced 

coronary vasodilatory reserve) (Czernin and Waldherr 

2003). Cigarette smoking played a direct role by constricting coronary arteries through nicotine-mediated action 

on a-adrenergic receptors and by induction of endothelial 

dysfunction by nicotine and oxidizing chemicals (Nicod 

et al. 1984; Puranik and Celermajer 2003). In addition, 

oxidant chemicals contribute to platelet activation and 

thrombogenesis (Burke and FitzGerald 2003). 

Exposure to CO may also contribute to the adverse 

hemodynamic effects of cigarette smoking. By producing 

functional anemia, CO increases the need for coronary blood flow, especially during physical exertion. An 

in-adequate vasodilatory flow reserve produced by cigarette smoking, in the face of need for increased coronary 

blood flow mediated by carbon dioxide, could contribute 

to myocardial ischemia with exercise in smokers.

In addition to the mechanisms described in Figure 6.5, cigarette smoking has effects on inflammation, 

insulin sensitivity, and lipid abnormalities that most likely 

contribute to smoking-induced CVD. 
Surgeon General’s Report

368 Chapter 6

Hemodynamic Effects

Blood Pressure and Heart Rate

In 1907, Erich Hesse published “The Influence of 

Smoking on the Circulation,” which documents his observations on the effects of smoking on heart rate and blood 

pressure (Hesse 1907). In most study participants, both 

heart rate and blood pressure increased immediately after 

smoking. Hesse observed a greater response in blood pressure after smoking in persons who smoked than in nonsmokers. Speculating that the increases in blood pressure 

and heart rate reflected stimulation of the heart or nervous system, he instituted a rule prohibiting patients with 

a “heart weakness” from smoking, to avoid unnecessary 

strain and stress for the heart muscle. Many investigators 

confirmed Hesse’s observations on the hemodynamic 

effects of cigarette smoking (Deanfield et al. 1986; Czernin 

et al. 1995; Barutcu et al. 2004). 

The positive chronotropic, inotropic, and blood 

pressure effects of smoking are explained by nicotineinduced activation of the sympathetic nervous system 

(review by Benowitz 2003). Nicotine promotes the release 

of epinephrine and norepinephrine from the adrenal 

medulla and terminal nerve endings, resulting in 

increased heart rate and greater contractility through 

stimulation of myocardial β1 receptors. Peripheral vascular resistance increases through α-receptor mediated 

vasoconstriction that in turn increases blood pressure. 

Coronary β2 and α2 receptors are also stimulated: stimulation of β2 receptors promoted vasodilation, and stimulation of α2 receptors promoted vasoconstriction (Cryer et 

al. 1976; Benowitz 2003). 

Cryer and colleagues (1976) elucidated the mechanisms behind observed hemodynamic changes during 

smoking. They observed more than a 150-percent increase 

in plasma epinephrine levels (from 44 to 113 picograms 

[pg]/mL) at 10 minutes after participants started to smoke 

a cigarette. Norepinephrine values increased to a smaller 

degree (from 227 to 315 pg/mL) at 12.5 minutes after the 

start of smoking. These increases were associated with 

significant increases in heart rate and blood pressure. 

Pretreatment with α-receptor blockers and β-receptor 

blockers had little effect on the increase in plasma levels of 

catecholamines, but increases in blood pressure and heart 

rate were eliminated. This study confirmed that smokinginduced increases in blood pressure and heart rate are 

attributable to adrenergic mechanisms. 

The hemodynamic effects of cigarette smoking 

are mediated primarily by nicotine, although oxidizing 

chemicals in tobacco smoke also affect vascular function. 

Intravenous nicotine, nicotine nasal spray, and nicotine 

chewing gum all increased the heart rate up to 10 to 15 

beats per minute and raised systolic blood pressure by up to 

5 to 10 millimeters of mercury (mm Hg), responses similar 

to the effects of cigarette smoking (Gourlay and Benowitz 

1997). Nicotine increased cardiac output by increasing 

both heart rate and myocardial contractility. Different vascular beds express different types and ratios of adrenergic 

receptors. Therefore, not all vascular responses to nicotine or tobacco smoke are the same. For example, nicotine 

constricts some vascular beds, such as the skin, and cutaneous vasoconstriction explains the reduced temperature 

of the fingertip observed with administration of nicotine 

(Benowitz et al. 1982a). Conversely, nicotine appears to 

dilate other vascular beds, such as skeletal muscle (Diana 

et al. 1990). Vasodilation of skeletal muscle may partly 

result from the increase in cardiac output, although the 

release of epinephrine from nerve terminals may also 

contribute. The net result of increases in heart rate, blood 

pressure, and myocardial contractility is an increase 

in myocardial work, followed by increased myocardial 

blood flow. 

Coronary Blood Flow

An important hemodynamic consequence of cigarette smoking is its effect on blood flow in the coronary 

arteries. Cigarette smoking acutely increased coronary 

blood flow by up to 40 percent, apparently a response to 

the increase in myocardial work (review by Czernin and 

Waldherr 2003). 

In anesthetized dogs, coronary blood flow showed 

a biphasic response to nicotine. Initially, researchers 

hypothesized that increases in coronary blood flow—

in the large coronary vessels as well as the smaller 

vessels—resulted from an increase in myocardial metabolic demand. 

Cigarette smoking impairs the response of coronary blood flow to an increase in myocardial demand for 

oxygen; that is, it reduces the coronary vasodilatory flow 

reserve. Thus, the increase in coronary blood flow based 

on the level of myocardial work is less than would be 

expected in the absence of exposure to tobacco smoke. 

Considerable evidence indicates that cigarette smoking causes dysfunction of the coronary arterial endothelium (see “Endothelial Injury or Dysfunction” later in 

this chapter). 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Cigarette smoking may also be associated with 

coronary vasoconstriction. Although cigarette smoking 

increases coronary blood flow in a person who does not 

have CHD, it may decrease coronary blood flow in the 

presence of coronary disease. Regan and colleagues (1960) 

measured coronary sinus blood flow in seven male volunteers with documented CHD before and after they smoked 

two cigarettes during a period of about 25 minutes; cardiac work increased by about 30 percent during smoking. 

Even so, in response to smoking, coronary blood flow fell 

in three patients, did not change in three patients, and 

increased in one patient. Similar paradoxical responses 

were observed after long-term smokers were exposed to 

cold by testing with cold pressors (Campisi et al. 1998). 

In the testing, the hand is immersed in ice water for one 

to two minutes. This painful procedure evokes a mixed 

adrenergic response involving coronary receptors α1 and 

α2 (vasoconstriction), β2 (vasodilation), and myocardial 

β1 (indirect coronary vasodilation). Endothelial α2 receptors that promote indirect coronary vasodilation may also 

be involved. In healthy volunteers, cold-induced increases 

of about 30 percent in the product of heart rate and blood 

pressure were associated with appropriate and similar 

increases in blood flow. In contrast, smokers showed no 

measurable increases in blood flow in response to the 

cold. Campisi and colleagues (1998) ascribed this observation to coronary endothelial dysfunction. 

Kaufmann and colleagues (2000) provided additional evidence for the association between smoking and 

endothelial dysfunction. Using quantitative positron emission tomography, they found that coronary microvascular 

function was abnormal in smokers but could be restored 

by infusion of vitamin C. Earlier, Zeiher and colleagues 

(1995) used quantitative coronary angiography to measure the effects of long-term smoking on the diameter of 

the coronary artery at study entry, during flow-mediated 

coronary vasodilation, and after intracoronary administration of nitroglycerin. The study population consisted of 

patients with or without mild disease of the left anterior 

descending coronary artery and no other cardiac problems. Flow-mediated vasodilation was markedly blunted 

in long-term smokers. In a study of smokers with CHD, 

cigarette smoking increased coronary vascular resistance, 

an effect that can be blocked by a-adrenergic blockers. 

This finding indicates that the mechanism of increased 

coronary artery resistance is at least partly due to stimulation of the sympathetic nervous system by nicotine. 

Intracoronary measurements by Doppler ultrasonography demonstrated that cigarette smoking constricts 

epicardial arteries and increases total coronary vascular 

resistance. This result indicates that impairment of coronary blood flow by cigarette smoking results from constriction of both epicardial and resistance blood vessels. 

In one study, after pretreatment with calcium-channelblocking agents or nitroglycerin, cigarette smoking 

increased coronary blood flow in patients with CHD who 

had manifested no increase after cigarette smoking alone 

(Winniford et al. 1987). This finding that coronary vasodilator drugs, which block chemically mediated vasoconstriction, permit the usual increase in coronary blood flow 

in response to increased myocardial work supports the 

hypothesis that cigarette smoking directly produces coronary vasoconstriction. In another study, chewing 4 mg of 

nicotine gum by healthy nonsmokers blunted the increase 

in coronary blood flow that occurs with increased heart 

rate produced by cardiac pacing (Kaijser and Berglund 

1985). This result confirmed that even low doses of nicotine can directly constrict coronary arteries in humans.

Another study found that nicotine worsened myocardial dysfunction in “regionally stunned” ischemic 

myocardium of anesthetized dogs (Przyklenk 1994). In 

a placebo-controlled experiment, transient ischemia was 

induced in dogs by clamping the left anterior descending 

coronary artery for 15 minutes. Segmental shortening 

of the myocardium recovered to only 29 percent of the 

preischemic baseline values in dogs pretreated with nicotine, compared with 54 percent in saline-treated control 

dogs. The doses of nicotine administered to the animals 

did not alter heart rate, blood pressure, or blood flow or 

cause myocyte necrosis. 

In patients with vasospastic angina, cigarette smoking is associated with increased occurrence of the condition and a poorer response to medication compared with 

the response in nonsmokers (Caralis et al. 1992). The 

researchers observed that cigarette smoking during coronary angiography (cardiac catheterization) produced an 

acute coronary vasospasm.

Schelbert and colleagues (1979) extensively studied the relationship of coronary vasomotion, endothelial 

function, and myocardial blood flow to potential reversibility of coronary vasomotor abnormalities. They adopted 

a noninvasive approach by measuring blood flow with 

positron emission tomography using 13N ammonia: (1) 

at rest during testing with cold pressors to probe endothelium-dependent coronary vasomotion and (2) during 

dipyridamole-induced hyperemia to assess endotheliumindependent coronary vasomotion. Using this protocol, 

Czernin and associates (1995) investigated the effects of 

short- and long-term smoking on myocardial blood flow 

and flow reserve in smokers. The investigators sought to 

determine whether abnormalities in coronary vasomotion in response to cold could be reversed in response to 

l-arginine infusion (Campisi et al. 1998, 1999). The findings indicated that short-term and long-term smokers 

had normal coronary vasodilatory capacity. Short-term 

smoking, however, reduced flow reserve in both short- and 
Surgeon General’s Report

370 Chapter 6

long-term smokers. Also, exposure of long-term smokers 

to cold resulted in abnormal blood flow. The smokingassociated abnormalities in vasomotion were restored by 

intravenous l-arginine, and this result further implicates 

the endothelium as the target of toxic substances contained in cigarette smoke. Campisi and colleagues (1999) 

quantified myocardial blood flow during exposure to cold 

while l-arginine, the substrate of ENOS, was infused 

intravenously for 45 minutes at a dose of 30 g as 10 percent arginine hydrochloride. This infusion produced significant improvement in responses of myocardial blood 

flow to cold. In addition to active smoking, exposure to 

secondhand smoke for 30 minutes abruptly reduces coronary blood flow velocity in nonsmokers, as assessed by 

echocardiography (Otsuka et al. 2001).

Summary

Cigarette smoking impairs the vascular endothelial 

function and activates the sympathetic nervous system. 

These effects can result in inappropriate reduction in or 

failure to increase coronary blood flow in response to 

increases in myocardial demand. Together with long-term 

atherosclerotic damage from smoking, these effects contribute to ischemic cardiac events. Coronary endothelial 

dysfunction clearly increases the risk for cardiovascular 

events. The smoking-induced alterations in vasomotor 

function appear to be substantially reversible, which 

underscores the importance of smoking cessation programs and policies to promote a smoke-free environment.

Smoking and the Endothelium

Endothelial Injury or Dysfunction

Endothelial injury and dysfunction are thought to 

contribute to the initiation of atherogenesis and to have a 

major role in acute cardiovascular events. Cigarette smoking produces endothelial injury and dysfunction in both 

peripheral and coronary arteries. Other cardiovascular 

risk factors such as hypercholesterolemia, diabetes, and 

hypertension also produce endothelial dysfunction.

The healthy endothelium is a diaphanous film of tissue that invests the luminal surface of all blood and lymphatic vessels. In larger-conduit vessels, the endothelium 

forms a monolayer between the circulating blood and the 

vessel wall. The tissue capillaries, which are the smallest conduits for blood and lymphatic flow, are composed 

exclusively of endothelial cells. Because of the ubiquity 

of endothelial cells, the surface area of the endothelium 

in a human weighing 70 kilograms (kg) is 1,000 to 4,000 

square meters—equivalent to two to four tennis courts—

with a weight of approximately 1 kg (Wolinsky 1980). The 

endothelium produces a variety of paracrine factors that 

regulate vascular homeostasis, including proteins, lipids, and small molecules that (1) can relax or activate the 

underlying vascular smooth muscle, (2) regulate the interaction of the vessel wall with circulating blood elements, 

and (3) modulate vessel structure (Aird 2005). In healthy 

persons, the endothelium primarily exerts a vasodilator influence that reduces vascular resistance and maintains blood flow. The endothelium maintains the blood’s 

fluidity by elaborating anticoagulant substances and 

generally resists adherence of platelets and infiltration of 

immune cells. 

Regeneration of Endothelium

With aging, the normal functioning of the endothelium requires replacement of apoptotic or injured 

cells. Normally, the turnover of endothelial cells is low, 

on the order of 0.1 percent of the cells undergoing 

mitosis at any time (Wright 1972). The rate of endothelial 

turnover increases, however, in areas of disturbed flow 

(bends, branches, or bifurcations of blood vessels). The 

length of chromosome telomeres documents that endothelial aging occurs more rapidly in these areas (Chang 

and Harley 1995). Furthermore, the accelerated aging in 

these areas may lead to focal senescence, which is demonstrated by impaired endothelium-dependent vasodilation 

(McLenachan et al. 1990). 

Persons who smoke may have impaired ability to 

regenerate the endothelium. The endothelial monolayer is 

regenerated in part from circulating endothelial progenitor cells derived from bone marrow, and the supply of these 

cells may be a key determinant of endothelial health. The 

number of circulating endothelial progenitor cells, which 

is estimated by ex vivo colony counts or by analysis using 

fluorescence-activated cell sorting, is directly associated 

with the ability of the endothelium to induce vasodilation (Hibbert et al. 2003; Hill et al. 2003). Smokers have 

reduced numbers of circulating endothelial progenitor 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

cells and impaired endothelium-dependent vasodilation 

(Vasa et al. 2001, Hill et al. 2003). In addition, smoking 

cessation was associated with a rebound in the number 

of circulating endothelial progenitor cells and improvement in endothelium-dependent vasodilation (Moreno et 

al. 1998; Kondo et al. 2004). 

Endothelial Dysfunctions

A variety of endothelial dysfunctions may contribute 

to disorders of vessel tone and structure that precede clinical vascular disease. Cardiovascular risk factors such as 

hypercholesterolemia, hypertension, diabetes, and use of 

tobacco cause endothelial aberrations long before clinical 

vascular disease becomes evident. Endothelial dysfunction is the first step in vascular disease, because it leads to 

vascular inflammation, cell proliferation, and thrombosis, 

which contribute to progression of vascular disease.

Endothelial generation of adhesion molecules 

increases in smokers, as evidenced by higher plasma 

levels of soluble adhesion molecules (Blann et al. 1997, 

1998). These molecules include soluble forms of the vascular cell adhesion molecule (sVCAM) and the intercellular adhesion molecule (sICAM). The soluble adhesion 

molecules, which are shed from the endothelium, reflect 

the increased endothelial production of these adhesion 

molecules in the context of vascular inflammation. Endothelial adhesion molecules are required for adherence to 

blood leukocytes and their infiltration into the vessel wall 

(Gimbrone 1995). The increased elaboration of adhesion molecules is an endothelial dysfunction that promotes leukocyte infiltration, vascular inflammation, and 

progression of atherosclerosis. Studies have associated 

elevated levels of either sVCAM or sICAM with increased 

risk of cardiovascular events (Blankenberg et al. 2001).

Smoking also impairs the ability of the endothelium to resist thrombosis. Compared with nonsmokers, 

smokers have higher levels of von Willebrand factor protein (MacCallum 2005) and tissue factor (Matetzky et al. 

2000; Sambola et al. 2003), which may be generated by 

the endothelium. Tissue factor activates the coagulation 

cascade, and von Willebrand factor protein mediates 

adherence of platelets to the vessel wall (MacCallum 

2005). Furthermore, study findings indicate that smoking 

impairs capacity to lyse the thrombus that is formed. Plasma levels of tissue plasminogen activator (tPA), a thrombolytic protein produced by the endothelium, are reduced 

in smokers (Newby et al. 2001). In contrast, smoking 

increases levels of plasminogen activator inhibitor-1 

(PAI-1) (Simpson et al. 1997). By interfering with the 

function of tPA, PAI-1 reduces thrombolytic capacity 

(MacCallum 2005). Imbalance in thrombolytic capacity 

attributable to higher PAI-1 values or reduction in tPA 

levels is associated with occurrence of adverse cardiovascular events. 

The healthy endothelium elaborates vasodilator 

substances such as nitric oxide (NO), prostacyclin, atrial 

natriuretic peptide, endothelium-derived hyperpolarizing factor, and adrenomedullin (Chen and Burnett 1998; 

Busse and Fleming 2003; Brain and Grant 2004). In 

doing so, the healthy endothelium increases the diameter 

of the blood vessels and reduces resistance to blood flow. 

When the endothelium becomes diseased, synthesis and 

bioactivity of the vasodilators are reduced, and the balance 

tips in favor of endothelium-derived vasoconstrictors such 

as endothelin and thromboxane (Vanhoutte et al. 2005). 

This derangement in endothelial function has clinical 

consequences. Because vasodilator function is impaired, 

coronary vascular resistance increases, and ischemia can 

result. Furthermore, endothelial vasodilator dysfunction 

in the coronary arteries of humans is associated with 

reversible myocardial perfusion defects, which are 

associated with other vascular abnormalities (Hasdai et al. 

1997b). These abnormalities include expression of adhesion molecules, adherence and infiltration of leukocytes, 

and proliferation of smooth muscle cells. 

Most of the endothelium-derived vasodilators also 

oppose key processes involved in atherogenesis (cell adhesion, proliferation, and inflammation) (Cooke and Dzau 

1997a,b). Thus, by reducing the generation or bioactivity of endothelial vasodilators, exposure to tobacco can 

accelerate atherosclerosis. This mechanistic explanation 

for tobacco-related CVD is supported by the finding that 

dysfunction of endothelial vasodilators is an independent 

predictor of vascular events (Schächinger et al. 2000; 

Suwaidi et al. 2000; Gokce et al. 2003). The role of these 

mechanisms involving NO is vascular protection, which is 

impaired by exposure to tobacco.

Nitric Oxide and Vascular 

Homeostasis

NO induces vasodilation by stimulating soluble guanylate cyclase to produce cyclic guanosine monophosphate (Ignarro et al. 1984). NO, which has a short half-life, 

avidly interacts with sulfhydryl-containing proteins, heme 

proteins, and oxygen-derived free radicals. By virtue of its 
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372 Chapter 6

ability to nitrosylate proteins, NO may change their activity or behavior (Hess et al. 2005). The significant increase 

in vascular resistance induced in animals and humans 

exposed to pharmacologic antagonists of ENOS reflects 

the physiological importance of this endothelium-derived 

vasodilator (Rees et al. 1989; Vallance et al. 1989). 

Endothelium-derived NO also inhibits adherence 

of platelets and leukocytes to the vessel wall (Kubes et 

al. 1991; Tsao et al. 1994). This effect is mediated partly 

by activation of cyclic guanosine monophosphate and 

phosphorylation of intracellular signaling proteins such 

as vasodilator-stimulated phosphoprotein (Smolenski et 

al. 1998). In addition, NO suppresses expression of adhesion molecules and chemokines that regulate endothelial 

interactions with circulating blood elements (Tsao et al. 

1996, 1997). These observations suggest that NO is an 

endogenous antiatherogenic molecule. Impairment of 

ENOS contributes to the pathologic alterations in vascular reactivity and structure observed in atherosclerosis 

(Cooke and Dzau 1997a,b). The pharmacologic inhibition or genetic deficiency of ENOS inhibits endotheliumdependent vasodilation, impairs blood flow in tissues, and 

raises blood pressure (Huang et al. 1995; Kielstein et al. 

2004). Furthermore, NO deficiency promotes adherence 

to and intimal accumulation of mononuclear cells and 

accelerates formation of lesions in animal models of 

atherosclerosis (Kuhlencordt et al. 2001). In contrast, 

enhancing production of NO in the vessel wall slows or 

even reverses atherogenesis and restenosis (Cooke et al. 

1992; von der Leyen et al. 1995; Candipan et al. 1996). 

NO is a survival factor for endothelial cells, and it induces 

apoptosis of macrophages and proliferation of vascular 

smooth muscle cells (Wang et al. 1999).

Certain polymorphisms of the ENOS gene predict 

development of CHD (Ichihara et al. 1998; Tsukada et al. 

1998; Yoshimura et al. 1998). The ENOS gene GLU298ASP

polymorphism is more prevalent in patients with variant angina, essential hypertension, and acute MI (Hibi 

et al. 1998; Miyamoto et al. 1998; Shimasaki et al. 1998; 

Yoshimura et al. 1998). Intriguingly, this polymorphism is 

associated with greater sensitivity to the effects of smoking on endothelial vasodilator function. Young men who 

are carriers of the ENOS *ASP298 allele have increased 

susceptibility to smoking-associated reduction in endothelial function (Leeson et al. 2002). Similarly, a quadruple repeat of a sequence of 27 base pairs in *intron 4 

of the ENOS gene (allele *a) is associated with increased 

risk of CHD and acute MI (Ichihara et al. 1998). Smokers 

who are homozygous for the ENOS allele *a are at risk for 

more severe CHD than are those who are not homozygous 

(Wang et al. 1996). 

Endothelium-Dependent 

Vasodilation

The effect of exposure to tobacco on endotheliumdependent vasodilation in humans was assessed by observing its effect on flow-mediated vasodilation. As blood flow 

through a vessel is increased, the vessel relaxes. In animal 

models, this flow-mediated vasodilation was abolished 

by removing the endothelium (Pohl et al. 1986). When 

a pharmacologic antagonist of ENOS was used, flowmediated vasodilation in the rabbit iliac artery depended 

on the endothelial release of NO (Cooke et al. 1991). Celermajer and colleagues (1992) used duplex ultrasonography to record flow-mediated vasodilation of the brachial 

artery in response to hyperemic vasodilation of the forearm. The investigators induced vasodilation by using 

a blood pressure cuff inflated to suprasystolic pressures 

to transiently occlude blood flow in the forearm. Joannides and colleagues (1995) extended this finding by 

showing that flow-mediated vasodilation of the brachial 

artery could be abolished by pharmacologic antagonism 

of ENOS. Subsequently, numerous studies used this 

approach to document impairment of flow-mediated, 

endothelium-dependent vasodilation in smokers and in 

persons exposed to secondhand smoke (Celermajer et al. 

1993, 1996; Barua et al. 2001). Researchers also observed 

that tobacco use impaired endothelium-dependent vasodilation in the coronary microcirculation. Intracoronary 

infusion of acetylcholine induced vasodilation that was 

partly attributable to release of NO, and this response was 

blunted in persons who smoked (Kugiyama et al. 1996). 

Impairment of EndotheliumDependent Vasodilation

Many factors contribute to the ability of tobacco to 

impair endothelial function. Tobacco use adversely affects 

the ENOS pathway. Exposure of cultured endothelial cells 

derived from human coronary arteries or umbilical veins 

to sera from smokers reduced expression and activity of 

ENOS (Barua et al. 2001, 2003). The researchers attributed this effect partly to the oxygen-derived free radicals 

in tobacco smoke. In addition, the half-life of NO was 

markedly shortened by oxidative stress (Rubanyi and Vanhoutte 1986). 

Superoxide anion reacts avidly with NO to form a 

peroxynitrite (ONOO−) anion, which itself is a highly 

reactive free radical (Beckman and Koppenol 1996). Other sources of free radicals that may inactivate NO and 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

impair endothelial vasodilator function include activated 

leukocytes, xanthine oxidase, the mitochondrial electrontransport chain, and uncoupling of ENOS itself (Heitzer 

et al. 2000; Barua et al. 2003; Kayyali et al. 2003; Sydow 

and Münzel 2003; Guthikonda et al. 2003). Investigators 

postulated that this uncoupling occurs when amounts of 

the NOS cofactor tetrahydrobiopterin or the NO precursor 

l-arginine are insufficient. These conditions involve transfer of electrons from ENOS to oxygen and thus formation 

of a superoxide anion. 

Oxidative stress also impairs the NOS pathway by 

increasing accumulation of asymmetric dimethylarginine 

(ADMA), an endogenous competitive inhibitor of ENOS 

produced by all cells during degradation of methylated 

nuclear proteins (Vallance et al. 1992; Tran et al. 2003). 

Most of the ADMA produced is degraded by the enzyme 

dimethylarginine dimethylaminohydrolase. Oxidative 

stress impairs the activity of this enzyme and leads to 

accumulation of ADMA and suppression of ENOS 

(Cooke 2004). 

Blood levels of antioxidant vitamins are lower than 

normal in smokers, reflecting endogenous consumption 

of these vitamins in response to ongoing oxidant stress 

(Lykkesfeldt et al. 2000). Administration of vitamin C 

reverses the impairment of endothelium-mediated 

vasodilation in smokers, a finding consistent with an 

oxidant mechanism of endothelial dysfunction (Heitzer et 

al. 1996). 

Nicotine itself may injure endothelial cells. Studies showed that in levels similar to those found in the 

blood of cigarette smokers, nicotine altered structural and 

functional characteristics of cultured vascular smooth 

muscle and endothelial cells (Csonka et al. 1985; Thyberg 

1986). In one study, oral nicotine administered to rats to 

achieve blood levels comparable to those in human smokers produced myointimal thickening of the aorta after an 

experimental injury (denudation of the endothelium with 

a balloon catheter) (Krupski et al. 1987). The excessive 

myointimal thickening in nicotine-treated animals is consistent with persistent injury to endothelial cells. Studies reported increased numbers of circulating endothelial 

cells in the venous blood, reflecting endothelial injury, 

and decreased platelet aggregate ratios, reflecting platelet 

aggregation in persons who had never smoked but who, 

for experimental purposes, smoked cigarettes containing tobacco (Davis et al. 1985). These results were not 

observed in nonsmokers who smoked cigarettes that did 

not contain tobacco. These findings further support a role 

for nicotine in injury to endothelial cells.

Nicotine may influence endothelial function in 

other ways. In studies of cultured endothelial cells, nicotine enhanced release of the basic fibroblast growth factor 

and inhibited production of transforming growth factor 

β1 (Villablanca 1998; Cucina et al. 1999). Nicotine also 

increased DNA synthesis, mitogenic activity, and endothelial proliferation. Nicotine has been shown to induce 

endothelial dysfunction (Chalon et al. 2000; Sarabi and 

Lind 2000; Neunteufl et al. 2002).

Pathologic Angiogenesis

Another endothelial function influenced by exposure 

to tobacco is development of new blood vessels (angiogenesis). Angiogenesis requires activation of endothelial cells 

by an angiogenic cytokine, followed by endothelial cell 

proliferation and migration and the formation of tubes. 

Exposure to secondhand smoke promotes tumor angiogenesis and growth (Zhu et al. 2003). Human lung cancer 

cells implanted in a subcutaneous or orthotopic location 

grew more rapidly in mice when they were exposed to secondhand tobacco smoke. Furthermore, these mice had 

higher plasma levels of vascular endothelial growth factor, 

and capillary density in their tumor nodules was greater 

than that in control mice. Mecamylamine, an antagonist 

of the nicotinic acetylcholine receptor (nAChR), abolished the effects of exposure to secondhand smoke. These 

observations indicate that secondhand smoke increases 

tumor angiogenesis and growth, at least partly through a 

nicotine-mediated mechanism. 

Researchers observed the effect of nicotine in promoting pathologic angiogenesis in numerous murine 

models of tobacco-related diseases, including lung cancer, atherosclerosis, and retinopathy (Heeschen et al. 

2001, 2002; Natori et al. 2003; Shin et al. 2004; Suñer 

et al. 2004). Tumor angiogenesis was required for tumor 

growth, and correspondingly, promotion of tumor 

angiogenesis accelerated tumor growth (Folkman 2003). 

Conversely, antiangiogenic agents inhibit progression 

of cancer and are now approved as treatment for some 

advanced human malignant diseases (Jain 2005). The 

effect of nicotine on promotion of tumor angiogenesis 

may be attributable to a direct effect on endothelial cells. 

In clinically relevant levels, nicotine promoted endotheliaprocesses that may be involved in tumor angiogenesis. 

At these doses, nicotine promoted survival, proliferation, 

and migration of endothelial cells (Heeschen et al. 2001, 

2002). Nicotine also induced elaboration and release of 

angiogenic factors, including NO, prostacyclin, vascular 

endothelial growth factor, and fibroblast growth factor 

(Carty et al. 1996; Heeschen et al. 2001a; Lane et al. 2005). 

These effects of nicotine were mediated by nAChRs on the 

endothelium (Heeschen et al. 2002). Conversely, pharmacologic inhibition or genetic deficiency of endothelial 
Surgeon General’s Report

374 Chapter 6

nAChRs reduced angiogenic response to nicotine. A variety of human lung cancer cells synthesized acetylcholine 

or expressed nAChRs. Nicotine increased growth of these 

cells in vitro, but this effect was inhibited by antagonists 

of the nAChRs (Schuller 2002).

The importance of pathologic angiogenesis in 

growth of tumors is well known. Less widely recognized, 

however, is the role of neovascularization in progression 

of atherosclerotic plaque. Large atherosclerotic plaques 

in human coronary arteries are well vascularized by 

microvessels originating from the vasa vasorum (Barger 

et al. 1984). In mice with hypercholesterolemia, growth 

of atheroma can be inhibited by antiangiogenic agents, 

and in the same murine models, nicotine promoted neovascularization of plaque and its progression in the aorta 

(Heeschen et al. 2001; Moulton et al. 2003). The effect of 

nicotine in increasing neovascularization and progression 

of plaque may partially explain increased risk of atherosclerotic disease in persons who smoke. 

Similarly, in a model of age-related macular degeneration in mice, nicotine stimulated retinal neovascularization (Suñer et al. 2004). This effect was antagonized 

by hexamethonium, another antagonist of nAChRs. In a 

clinical study, the most virulent form of age-related maculopathy is associated with retinal neovascularization that 

contributes to visual deterioration, and tobacco smokers 

are at greater risk of age-related macular degeneration 

than are nonsmokers (Christen et al. 1996; Seddon et al. 

1996). Thus, a variety of tobacco-related diseases are characterized by pathologic neovascularization, an effect that 

may be promoted by nicotine.

Notwithstanding nicotine’s effect as a promoter of 

neovascularization, long-term exposure to tobacco may 

impair therapeutic angiogenesis. In a murine model 

of hindlimb ischemia, short-term exposure to nicotine 

paradoxically increased capillary density and improved 

regional blood flow in the ischemic hindlimb (Heeschen et 

al. 2001, 2003). However, long-term exposure to nicotine 

for 16 weeks (about one-third of the life span of a mouse) 

before induction of ischemia obliterated angiogenic 

response to nicotine (Konishi et al. 2010). 

The relevance of animal models for research on 

nicotine and angiogenesis to human smokers is not clear. 

It is important to differentiate studies that show effects 

of pure nicotine from those in which the exposure is to 

tobacco smoke. In mice, effects of nicotine on angiogenesis depended on release of NO, but the net effect of smoking in humans seems to be impaired release of NO. Also, 

most studies on angiogenesis involve short-term administration of nicotine, although tolerance to the effects of 

nicotine may develop with long-term use.

Inhibition of ACE normalized impaired bradykininmediated, endothelium-dependent venodilation in smokers (Chalon et al. 1999). Furthermore, coronary vasomotor 

responses to acetylcholine in patients with CHD 

improved in response to the ACE inhibitor quinapril to 

a much greater extent in smokers than in nonsmokers 

(Schlaifer et al. 1999). ACE inhibitors have an antioxidant 

activity, which could contribute to the clinical benefit 

in smokers.

Summary

The endothelium, a delicate monolayer of cells that 

invests all blood vessels, is a major regulator of vascular 

reactivity and structure. Healthy endothelium maintains 

vascular homeostasis by promoting fluidity of the blood, 

vasodilation, and relaxation of the underlying vascular smooth muscle. Endothelial dysfunction regularly 

accompanies and promotes vascular disease. Endothelial 

vasodilator dysfunction is an independent risk factor for 

major adverse cardiovascular events and mortality. Active 

smoking and involuntary exposure to cigarette smoke 

injure endothelial cells and impair endothelial vasodilation. Thus, each type of exposure to tobacco or tobacco 

smoke contributes to the development of CVD.

Thrombogenic Effects

This section on thrombogenic effects reviews the 

state of knowledge of mechanisms by which smoking 

or secondhand smoke exposure may predispose a person to thrombosis, a pathologic reaction that commonly 

results in smoking-related MI or stroke. Smoking-mediated thrombosis appears to be a major factor in the pathogenesis of acute cardiovascular events. 

Epidemiologic evidence indicates that cigarette 

smoking increases risk of acute MI and sudden death 

more than it increases risk of angina pectoris. Researchers 

hypothesize that risk of acute MI and sudden death is 

mediated by thrombosis, whereas angina is mediated 

primarily by hemodynamic factors. Successful revascularization in patients with MI after treatment with 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

thrombolysis is more likely in smokers than in nonsmokers (Bowers et al. 1996). At the time of MI, smokers 

are younger and have fewer cardiac risk factors and less 

severe underlying coronary disease than do nonsmokers 

(Metz and Waters 2003). Enhanced thrombosis superimposed on less severely stenotic arteries best explains these 

observations. In men who died suddenly, a history of cigarette smoking was significantly more likely when pathologic examination showed acute thrombosis (75 percent of 

cases) than when the finding was plaque with no thrombosis (41 percent) (Burke et al. 1997). Conversely, stable 

plaque with no thrombosis was the more common finding 

in nonsmokers. 

Thrombosis occurs when fibrinogen is converted 

to fibrin, a process involving interaction of platelets, 

blood-borne proteins, endothelial cells, and subendothelial vascular tissue. An endogenous antithrombotic 

mechanism involves these same components. Imbalance 

in these pathways results in predisposition to thrombosis. 

Virchow’s triad, first described in 1856 and modified by 

Aschoff in 1924, provides a framework for risk factors for 

thrombosis that is still valid. These authorities described 

the cardinal risk factors as “alterations in blood coagulation,” “alterations in blood flow,” and “alterations in the 

blood vessel wall.” 

Alterations in Blood

Blood contains platelets, red blood cells, and leukocytes suspended in plasma. Plasma in turn contains a variety of coagulation proteins and lipids that also contribute to the clotting process. Smokers tend to develop MI 

at a lower burden of atheroma than do nonsmokers. This 

finding suggests a greater role for formed elements of 

blood or for cardiac electrical instability in cardiovascular 

events in smokers.

Platelets

Platelets, although only a minor component of the 

solid phase of blood, are critical to the coagulation process 

and are important mediators of the impact of smoking on 

cardiovascular outcomes (Figure 6.6). 

Turnover and Activation

Studies have reported that sudden cardiac death 

is 2.5 times higher in smokers than in nonsmokers 

(Kannel et al. 1984; Goldenberg et al. 2003). Research 

findings broadly implicated activation of platelets and 

subsequent focal ischemia in sudden cardiac death among 

smokers. The turnover of platelets is accelerated in cigarette smokers (Fuster et al. 1981). Researchers related the 

number of newly formed reticulated platelets, rather than 

absolute platelet count, to incidence of thrombotic events 

(Rinder et al. 1998). 

Urinary excretion of thromboxane metabolites 

(TxMs), such as 2,3-dinor thromboxane B2 (TxB2) and 

11-dehydro TxB2, which are markers of platelet activation 

in vivo, increases in smokers in a dose-dependent manner 

(Murray et al. 1985). Studies demonstrated increases in 

levels of urinary TxM among smokers who were monozygotic twins but divergent for smoking behaviors (Lassila 

et al. 1988). These increases were also observed in young 

Swedish army recruits who smoked but had no apparent 

vascular disease (Wennmalm et al. 1991). Studies also 

showed that mainstream and sidestream smoke directly 

promoted platelet activation and enhanced activation 

induced by shear stress (Rubenstein et al. 2004).

Elevated levels of TxM observed in persons who 

smoke decreased substantially within days of smoking 

cessation, although they did not reach the levels found in 

nonsmokers (Rangemark et al. 1993; Saareks et al. 2001). 

In an ex vivo study, platelets from smokers showed greater 

aggregation than those from nonsmokers (Takajo et al. 

2001). A decline in platelet aggregation during 14 days of 

abstinence from smoking was reversed rapidly after smoking was resumed (Morita et al. 2005). Ex vivo aggregability, however, is a crude index of in vivo platelet activation 

and aggregation. Some studies reported diminished ex 

vivo aggregability in smokers. This finding suggests that 

partial activation in vivo resulted in the harvest of a less 

responsive subset of platelets for study ex vivo. Increased 

levels of urinary TxMs in smokers may be attributable to 

activation of both platelets and macrophages. Low-dose 

aspirin, which inhibits COX activity in platelets, substantially depressed the increment of TxM in smokers, leading investigators to hypothesize that TxM was principally 

derived from the activity of platelet COX-1 rather than 

macrophage COX-2 (Nowak et al. 1987; McAdam et 

al. 2005). 

Generation of Nitric Oxide 

Platelets constitutively express ENOS. Although 

platelet-derived NO is a modest inhibitor of platelet activation in vitro, it may be critical to inhibit recruitment 

of platelets to a growing thrombus (Freedman et al. 

1997). Aggregating platelets obtained from patients with 

acute coronary syndromes produced less NO than did 

those from patients with stable angina (Freedman et al. 

1998). Such findings must be interpreted with caution, 

however, because results reflect in vivo platelet activity 

(see “Turnover and Activation” earlier in this chapter). 

In one study, levels of platelet-derived NO were lower in 

smokers than in nonsmokers (Takajo et al. 2001). This 
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376 Chapter 6

finding was associated with lower levels of intraplateletreduced glutathione—a marker of oxidative stress and 

increased platelet aggregation. In another study, both the 

platelet-derived release of NO and the glutathione levels 

recovered in a time-dependent manner after smoking cessation, but they rapidly decreased again when smoking was 

resumed (Morita et al. 2005). Abstinence from smoking 

was also associated with decreased agonist-induced platelet 

aggregation ex vivo. Furthermore, levels of intraplatelet 

nitrotyrosine and urinary 8-hydroxy-2’-deoxyguanosine, 

which are markers of oxidative stress, were also depressed 

after smoking cessation. One study showed that supplementation with vitamin C restored NO levels and platelet 

aggregation in current smokers to levels observed in nonsmokers (Takajo et al. 2001). Another study demonstrated 

that the normal morning increase in platelet sensitivity 

to NO ex vivo was lost in smokers, leaving platelets potentially more susceptible to activation during early morning 

hours, when MIs are most common (Sawada et al. 2002). 

In yet another study, platelets from smokers were less 

Figure 6.6 Potential sites of actions and mechanisms of effects of smoking on platelets

Note: Smoking decreases NO-mediated inhibition of platelet activation and increases platelet activation through oxidative stress and 

other mechanisms. NO = nitric oxide.
Cardiovascular Diseases 377

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

sensitive to administration of nitroglycerin, a documented 

NO donor (Haramaki et al. 2001). 

Oxidative Stress and Platelet Function

Cigarette smoke has been shown to be an abundant 

source of free radicals (Church and Pryor 1985). Levels 

of isoprostanes—quantitative indices of in vivo oxidative 

stress—are higher in smokers than in nonsmokers (Reilly 

et al. 1996; Chehne et al. 2001; Dietrich et al. 2002), and 

they decrease with smoking cessation (Reilly et al. 1996; 

Praticò et al. 1997). In addition to serving as biomarkers of 

oxidative stress, isoprostanes may serve as secondary messengers that exert biologic effects, at least in vitro. 

Studies demonstrated elevated production of isoprostanes and decreased levels of reduced glutathione in 

the platelets of smokers (Takajo et al. 2001). Intraplatelet 

levels of nitrotyrosine, which is a marker of modification 

of proteins induced by oxidative stress, decreased with 

smoking abstinence but increased rapidly when smoking 

was resumed, together with return of increased sensitivity 

to agonist-induced platelet aggregation ex vivo (Morita et 

al. 2005). In another study, products from activated platelets induced oxidative stress in vascular smooth muscle 

cells, which is associated with increased expression of tissue factor, a highly thrombogenic protein (Görlach et al. 

2000). Other investigators showed that administration of 

antioxidants to persons with diabetes, just as to smokers, 

decreased production of isoprostane and urinary TxM 

(Davì et al. 1999) and decreased platelet aggregation ex 

vivo (Salonen et al. 1991). 

Isoprostanes and Platelet Function

In one study, platelets oxidized ex vivo demonstrated 

increased aggregation induced by shear stress, an effect 

that is only partly inhibited by administration of aspirin 

(Chung et al. 2002). In another study, oxidation of platelet membranes was associated with reduced expression of 

glycoprotein Ib, a receptor for the von Willebrand factor 

that is critical to platelet activation and aggregation under 

conditions of shear stress (Escolar and White 2000). The 

researchers postulated that decreased expression of glycoprotein Ib indicates a highly reactive status of platelets. 

Some evidence indicates that isoprostanes may act 

as platelet and vascular agonists through ligation of the 

thromboxane A2 receptor (TP) (Audoly et al. 2000). To 

date, no molecular evidence exists for a distinct isoprostane receptor (Praticò et al. 1996). One study reported that 

infusion of isoprostanes elevated blood pressure and activated platelets—effects that are lost in mice lacking TP. 

Binding of isoprostane iPF2α-III to TP promoted change 

in platelet shape and facilitated response to other proaggregatory stimuli (Praticò et al. 1996). In another study, 

however, isoprostane alone did not induce platelet activation and partially blocked the proaggregatory effects of TP 

agonists and high-dose collagen (Cranshaw et al. 2001). 

Also, isoprostane iPF2α-III was reported to decrease the 

antiplatelet activity of NO (Minuz et al. 1998). Some 

researchers speculated that this isoprostane has a role in 

the resistance to low-dose aspirin observed in patients 

with CVD (Csiszar et al. 2002). It is not known, however, 

how these effects, which are demonstrable in vitro, relate 

to endogenous levels of isoprostanes attained locally in 

vivo under conditions of oxidative stress.

Summary

Thus, platelets from smokers demonstrate a dosedependent increase in activity and adhesiveness that rapidly decreases with smoking abstinence. Findings suggest 

that the inhibitory NO pathway is impaired and responsiveness to other agonists is increased at least partially 

through the mediation of TP. 

Red Blood Cells

Hematocrit in Adults

Smoking is associated with an increase in hematocrit or red blood cell mass attributable to increased levels of CO and carboxyhemoglobin. Hematocrit decreases 

with smoking cessation, but increased blood viscosity and 

deformability of red blood cells may persist (Haustein et 

al. 2004). Increases in hematocrit and blood viscosity are 

associated with increasing risk of CVD. It is unclear, however, whether these risk factors are independent of smoking and other conventional risk factors, particularly in 

women (Lowe et al. 1997; Irace et al. 2003; Woodward et 

al. 2003). When data are adjusted for smoking, hypertension, and high cholesterol, viscosity remains a significant 

risk factor for stroke and for PAD but not for ischemic 

heart disease. This finding suggests that the effect of high 

viscosity may be an independent risk factor for stroke or 

PAD (Lee et al. 1996; Lowe et al. 1997). 

Hematocrit in Neonates

Researchers showed that the effects of smoking on 

hematocrit were transmitted to the fetus during pregnancy. Some studies reported a dose-dependent increase 

in hemoglobin levels in infants of mothers who smoked 

(al-Alawi and Jenkins 2000; Habek et al. 2002). Furthermore, infants born to mothers who smoked more than 20 

cigarettes per day had higher rates of fetal hypoxia, polycythemia, and neurological complications than did infants 

of nonsmoking mothers. 
Surgeon General’s Report

378 Chapter 6

Leukocytes

Polymorphonuclear Leukocytes

In one study, persons who smoked had higher numbers of circulating polymorphonuclear leukocytes than 

did nonsmokers (Sela et al. 2002). In other research, 

neutrophils from smokers had higher levels of myeloperoxidase (Bridges et al. 1985) and increased expression of 

integrins CD11b, CD15, and CD63, which are markers 

of leukocyte activation (Gustafsson et al. 2000). Furthermore, when stimulated, these leukocytes released superoxide at a faster rate than did leukocytes from nonsmokers 

(Sela et al. 2002), which further increased local oxidative 

stress. Studies documented a greater variety of circulating 

cellular adhesion molecules, including ICAM-1, VCAM, 

P-selectin, and E-selectin, in smokers than in nonsmokers 

(Mazzone et al. 2001; Bermudez et al. 2002). An increase 

in these cellular adhesion molecules (monocytes) may 

facilitate recruitment of inflammatory cells to sites of vascular injury (Figure 6.7). 

Monocytes

Monocytes from smokers demonstrated increased 

expression of the integrins CD11b and CD18, which augment adhesiveness of monocytes to endothelial cells, at 

least in vitro (Weber et al. 1996). This process is thought 

to be mediated by activation of protein kinase C (Kalra 

et al. 1994) and is attenuated by supplementation with 

vitamin C (Weber et al. 1996). In one study, isoprostane 

iPF2α-III inhibited adhesion of monocytes to cultured dermal cells or renal endothelial cells in rats but paradoxically increased adhesion of monocytes to human endothelial cells in the umbilical vein (Leitinger et al. 2001; 

Kumar et al. 2005). Adhesion of monocytes to endothelial 

cells may increase their access into the subendothelium, 

where they differentiate into macrophages and promote 

atherogenesis (Ross 1999). Differentiation of monocytes 

into macrophages depends on production of intracellular 

reactive oxygen species induced by nicotinamide adenine 

dinucleotide phosphate, but no evidence exists for a role 

of cigarette smoking in this differentiation (Barbieri et 

al. 2003). 

Summary

In summary, smoking induced changes in the 

numbers and activity of polymorphonuclear leukocytes 

and monocytes. In addition, it promoted expression of 

chemoattractant and adhesion molecules and integrins, 

which would be expected to increase recruitment of 

activated leukocytes to areas of oxidative stress, including 

sites of platelet deposition after vascular injury. 

Circulating Proteins

In addition to its effects on the cellular elements 

of blood, smoking alters the proteins involved in the 

coagulation pathway by changing procoagulant factors in 

Figure 6.7 Potential sites of effects of smoking on thrombosis through oxidative stress and other mechanisms

Note: 1. Increased numbers and activation of polymorphonuclear leukocytes; increased production of superoxide radicals; and 

increased expression of integrins and adhesion molecules on leukocytes and endothelial cells. 2. Increased oxidation of LDL 

cholesterol; oxidized LDL cholesterol taken up more easily into macrophages to produce foam cells; and increased adhesiveness of 

monocytes to endothelial cells. 3. Increased levels of fibrinogen; increased nitration of tyrosine residues on fibrinogen, rendering it 

more thrombogenic; impaired activity of plasmin; and decreased thrombolysis. LDL = low-density lipoprotein.
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

the circulation and anticoagulation factors derived from 

the endothelium. 

Fibrinogen

Study findings indicate that circulating levels of 

fibrinogen increase in smokers and decrease with smoking cessation (Thomas et al. 1995; Hunter et al. 2001; Tuut 

and Hense 2001). Also, research suggests that elevated 

fibrinogen values are an independent risk factor for CHD 

(Paramo et al. 2004) and deep-vein thrombosis (Vayá et al. 

2002). For CVD, the predictive effect was reportedly similar and additive to traditional cardiovascular risk factors 

(Woodward et al. 1998). The effect of fibrinogen on CVD is 

partly attributable to smoking and seems to be mediated 

through alterations in rates of synthesis by the liver. Use 

of snuff is not associated with increased fibrinogen levels 

(Eliasson et al. 1995).

Nitration of tyrosine residues, a marker of 

NO-dependent damage, is increased in smokers (Petruzzelli et al. 1997). Presence of these residues depends 

strictly on availability of nitrogen dioxide radicals that 

are in turn derived from ONOO− (Kirsch et al. 2002). 

Tyrosine nitration modifies a variety of proteins, including 

fibrinogen (Petruzzelli et al. 1997; Pignatelli et al. 2001). 

Nitrogenated fibrinogen is more reactive and thrombogenic than is native fibrinogen (Gole et al. 2000), a fact 

that seems attributable to accelerated formation of clots 

without modification in plasmin-induced thrombolysis 

(Vadseth et al. 2004). The antioxidants glutathione and 

vitamin C protect against formation of nitrogenated 

fibrinogen by interfering with interaction of nitrate radicals with tyrosine (Kirsch and de Groot 2000; Kirsch et al. 

2001). ONOO− is likely to derive from interaction of NO 

from cigarette smoke with superoxide radicals from pulmonary macrophages (Deliconstantinos et al. 1994). In 

studies of both animal models and human volunteers, 

even brief exposure to tobacco smoke induced prolonged 

production (>30 minutes) of ONOO−, apparently from 

pulmonary macrophages (Deliconstantinos et al. 1994). 

Plasmin

Circulating plasminogen is activated to plasmin by 

fibrin, thrombin, and tPA. Plasminogen has fibrinolytic 

and collagenase activities. In vitro studies showed that 

levels of ONOO− increased in smokers and that ONOO−

induced nitration of plasminogen in a concentrationdependent manner and reduced proteolytic activity of plasmin (Nowak et al. 2004). This effect is partially 

reduced by glutathione. 

C-Reactive Protein

Chronic, low-level inflammation—reflected by 

elevated levels of C-reactive protein (CRP) and other biomarkers—is an important risk factor for atherosclerosis 

(Koenig et al. 1999). Investigators reported that levels of 

CRP, which likely contributes to both oxidative stress and 

mitogenic and fibrogenic characteristics of atherosclerotic plaque, are higher in smokers than in nonsmokers 

in a dose-dependent manner (Bakhru and Erlinger 2005). 

This increase persisted even after adjustment for diabetes, 

lipid profile, and CVD, as well as age, gender, and race. 

More important, five years after smoking cessation, CRP 

levels were decreased to levels similar to those in lifetime 

nonsmokers. This finding suggests vascular healing. The 

timeframe is consistent with that observed in the multinational monitoring of trends and determinants of CVD 

(MONICA) (Dobson et al. 1991) and in the Northwick Park 

Heart studies (Meade et al. 1987). In those studies, cardiovascular risk was reduced at two to five years after a person 

stopped smoking. 

Oxidized Low-Density Lipoprotein 

Cholesterol

In vitro research on oxidative modification of LDL 

cholesterol (LDLc) by extracts from cigarette smoke 

showed a significant increase in atherogenicity (Chisolm 

and Steinberg 2000). In one study, LDL isolated after participants smoked six or seven cigarettes was more susceptible to ex vivo oxidation than was LDL isolated after 24 

hours of abstinence from smoking (Harats et al. 1989). In 

another study, oxidizability of LDL ex vivo decreased with 

smoking cessation (Sasaki et al. 1997). Oxidized LDLc, 

but not native LDL, interacted with scavenger receptors on lipid-laden lung cells (foam cells) and was readily 

incorporated into atherosclerotic plaque. Findings in other studies suggest that oxidized LDL prompts migration 

and degranulation of neutrophils (Sedgwick et al. 2003) 

and increases expression of the Toll-like receptor, a transmembrane protein in macrophages, thus promoting their 

activation (Xu et al. 2001). 

Clinical studies produced conflicting data on the 

ability of cigarette smoke to oxidize LDLc and on the role 

of cigarette smoke in the process in vivo. Findings in several studies (Scheffler et al. 1992; Mahfouz et al. 1995; 

Kagota et al. 1996; Gouaźe et al. 1998; Yamaguchi et al. 

2005), but not all studies (Princen et al. 1992; Siekmeier 

et al. 1996; Marangon et al. 1997; van den Berkmortel et al. 

2000), suggest that smoking increases oxidation of LDLc. 

Studies of an animal model suggest a similar oxidative 
Surgeon General’s Report

380 Chapter 6

effect (Yamaguchi et al. 2002, 2004). In one study, modification of LDLc by cigarette smoke was diminished in a 

dose-dependent manner by administration of fluvastatin 

(Yamaguchi et al. 2002; Franzoni et al. 2003). Fluvastatin 

is a potent scavenger of the peroxyl radical. A similar 

clinical study showed no decrease in oxidized LDL with 

administration of atorvastatin, despite improvement in 

endothelial function (Beckman et al. 2004). It is unclear 

whether failure to demonstrate an association between 

improved endothelial function and oxidative stress in 

the study of atorvastatin reflects a true independence of 

these effects, a distinction from fluvastatin, or limitations 

attributable to the small sample size. 

Thus, cigarette smoking may induce changes in 

both coagulation and fibrinolytic pathways to promote a 

prothrombotic state. In addition to its effects on inflammatory cells, smoking promotes production of inflammatory markers and acute-phase reactants. 

Alterations in Blood Vessels

Nitric Oxide

Cigarette smoking has injurious effects on the vascular endothelium (see “Smoking and the Endothelium” 

earlier in this chapter). Abnormalities in the release of 

chemical mediators occur as a consequence of endothelial 

dysfunction and are likely to contribute to the prothrombotic condition of smokers. Examples include decreases in 

NO-mediated inhibition of interactions between platelets 

and the blood vessel wall, in platelet-induced NO, and in 

inhibition of platelet activation (see “Platelets” earlier in 

this chapter). Blood vessel tone is more sensitive to low 

NO levels than is platelet function (Loscalzo 2001). The 

importance of NO deficiency mediated by oxidative stress 

in thrombosis is suggested by familial childhood stroke 

resulting from deficiency in glutathione peroxidase. This 

condition decreases NO levels in association with both increased expression of P-selectin in platelets and platelet 

aggregation and activation (Kenet et al. 1999). 

Prostacyclin Production

In vitro studies showed impaired production of 

prostacyclin by vascular cells exposed to cigarette smoke 

extracts. In vivo studies, however, showed increased biosynthesis of prostacyclin that is presumed to be reactive to 

accelerated interactions of platelets and neutrophils with 

vessel walls in smokers (Murray et al. 1990; Lassila and 

Laustiola 1992). Consistent with this concept, levels of 

markers of platelet and leukocyte activation were greater 

in smokers than in nonsmokers. Thus, the augmented 

biosynthesis of prostacyclin is likely to reflect a compensatory reaction by the vascular endothelium. 

von Willebrand Factor

Studies reported higher circulating levels of von 

Willebrand factor in smokers than in nonsmokers (Blann 

and McCollum 1993; Smith et al. 1993), and findings 

indicated that these levels may precede clinically overt 

atherosclerosis (Prisco et al. 1999). The von Willebrand 

factor is essential for initial adhesion of activated platelets to the vessel wall and for expansion of thrombi. It is 

unclear to what degree high levels of von Willebrand factor might contribute to the increased thrombosis and atherogenesis observed in smokers. 

Tissue Factor

Tissue factor is a prothrombotic protein made by 

numerous cells in the blood vessel wall, predominantly 

macrophages but also vascular smooth muscle and endothelial cells. Tissue factor is released when the endothelium is injured and can start the clotting cascade. Studies 

assessing the effects of smoking on tissue factor yielded 

mixed results (Barua et al. 2002; Sambola et al. 2003). The 

immunoreactivity of tissue factor was higher in specimens 

of plaque obtained during endarterectomy from smokers 

than in those from nonsmokers (Matetzky et al. 2000). In 

mice with APO E deficiency that were fed high-cholesterol 

diets, exposure to cigarette smoke resulted in higher levels of tissue factor and VCAM-1 and higher macrophage 

counts in atherosclerotic plaques than in those of unexposed mice (Lykkesfeldt et al. 2000). Aspirin treatment 

of cigarette smokers and of mice exposed to smoke was 

associated with lower levels of tissue factor in plaque. This 

finding indicates that aspirin may have a protective role 

for smokers.

Tissue Plasminogen Activator

Vascular endothelial cells and other tissues secrete 

tPA. This protein has a central role in fibrinolysis, which 

limits expansion of clots during thrombosis and eventually dissolves the clot during thrombolysis. Evidence from 

the Physicians’ Health Study indicates that high levels 

of tPA are an independent risk factor for stroke and suggests that activation of the endogenous fibrinolytic system 

occurs years before arterial vessels become occluded (Ridker et al. 1994). PAI-1, which is also secreted by vascular 

endothelial cells, opposes the actions of tPA. 

Data on the effects of smoking on tPA and PAI1 are conflicting (Blann et al. 2000; Enderle et al. 2000; 

Matetzky et al. 2000; Newby et al. 2001). Using an in vitro 

model, researchers showed that serum from smokers 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

impaired tPA production by human umbilical vein endothelial cells but that PAI-1 production was unchanged 

(Barua et al. 2002). In an in vivo model, bradykinin (Newby 

et al. 1999; Pretorius et al. 2002) and substance P (Newby 

et al. 1999; Pretorius et al. 2002) stimulated the production of tPA, which had decreased in smokers, but there 

was no effect on the release of methacholine-induced tPA. 

Vitamin C failed to ameliorate this decrease (Pellegrini et 

al. 2004). Studies showed that levels of PAI-1 may decrease 

after smoking cessation (Simpson et al. 1997). 

Thus, the evidence suggests that smoking 

decreases the production of tPA and perhaps also increases the amount of PAI-1 produced. These changes would 

be expected to impair fibrinolytic activity. Alternatively, 

a population-based study demonstrated increased levels of fibrinogen, but fibrinolytic activity in smokers did 

not differ from that in nonsmokers (Eliasson et al. 1995). 

Another study suggested that differences between smokers and nonsmokers in thrombolysis may be evident only 

in older adults (Ikarugi et al. 2003). 

Summary

A variety of abnormalities can be observed in 

endothelial cell function among smokers compared with 

nonsmokers. These abnormalities affect the ability of the 

endothelium to modulate vascular tone, platelet function, thrombogenesis, and thrombolysis. Administration of antioxidants mitigates some but not all of these 

abnormalities. The relative importance of these abnormalities and their interactions in clinical settings remains to 

be elucidated. 

Exposure to Secondhand 

Tobacco Smoke

In one study, levels of fibrinogen and coagulation 

factor VII were higher in nonsmoking adolescent offspring 

of smokers than in nonsmoking adolescent offspring of 

nonsmokers (Stavroulakis et al. 2000). This finding is in 

keeping with a prothrombotic state in smokers. In addition, levels of PAI-1 were lower in nonsmoking offspring of 

smokers. This result suggests decreased fibrinolysis, but 

there was no difference in tPA levels. Levels of thrombomodulin, which is produced by the vascular endothelium 

and has anticoagulant effects, were higher in nonsmoking 

offspring of smokers, but levels of von Willebrand factor 

were unchanged. Another study demonstrated that TxM 

levels increased in one exposure to secondhand smoke; 

after six hours of exposure, levels approached those 

observed in smokers (Schmid et al. 1996). In other 

research, exposure to secondhand smoke decreased sensitivity of platelets to the inhibitory effects of prostacyclin in 

vitro (Burghuber et al. 1986). 

Thus, many of the effects from active smoking can 

be observed in persons involuntarily exposed to cigarette 

smoke. The magnitude of the effect of secondhand smoke 

is relatively large considering the low systemic exposure 

to tobacco smoke for nonsmokers compared with that for 

active smokers and supports the finding of high cardiovascular risk at low levels of exposure to smoke. 

Nicotine and Thrombosis

Nicotine replacement therapy (NRT) does not seem 

to increase the acute risk of thrombosis, even in patients 

with established cardiac disease (Joseph et al. 1996). 

However, investigators have not fully studied cardiovascular effects of extended administration of nicotine, which 

might be used as an adjunct for persons trying to stop 

smoking (Stratton et al. 2001). The high urinary excretion 

of TxM in smokers declines rapidly after smoking cessation. In one study, this decline did not occur in smokers 

who were using NRT, suggesting that nicotine may be 

contributing to platelet activation (Saareks et al. 2001). 

However, other studies in which smokers switched to nicotine patches found a decline in eicosanoid excretion and 

that long-term use of smokeless tobacco, which results 

in nicotine exposure similar to that of cigarette smokers, 

does not increase urinary excretion of TxM (Wennmalm 

et al. 1991; Benowitz et al. 1993). These findings suggest 

that nicotine per se does not activate platelets. When nicotine or cotinine was added to the platelet-rich plasma of 

nonsmokers, platelet-dependent formation of thrombin 

increased (Hioki et al. 2001). The magnitude of the effect 

was similar to that observed in smokers, even though the 

basal nicotine levels in smokers were higher than those 

in nonsmokers. When cultured endothelial cells from the 

human brain were exposed to nicotine, tPA levels were 

unchanged (Zidovetzki et al. 1999). Rather, PAI-1 messenger RNA and protein expression increased, favoring 

a prothrombotic state. Alternatively, when transdermal 

nicotine was administered to nonsmokers, the release 

of tPA induced by substance P was greater than that in 

nonsmokers who had received placebo patches (Pellegrini 

et al. 2001). This finding suggests a more favorable effect 

in vivo. 

A study of cardiovascular biomarkers indicates that 

smokeless tobacco produced neither the inflammatory 

reaction found in smokers nor endothelial dysfunction, activation of platelets, or evidence of oxidant stress 

(Axelsson et al. 2001). Leukocyte counts; levels of CRP, 
Surgeon General’s Report

382 Chapter 6

fibrinogen, and antioxidant vitamins; and lipid profiles 

were similar in users of smokeless tobacco and in persons 

who did not use tobacco. 

Summary

Multiple factors produced in the blood and released 

from the vasculature determine the likelihood of a clinically significant thrombosis. Cigarette smoke and components of the smoke stimulate formation or activity 

of factors that favor the development of thrombosis. It 

remains to be seen whether biomarkers of individual 

cardiovascular risk among smokers will emerge and 

which genetic variants might particularly influence these 

risks in smokers. The implications of the hypercoagulable 

state are observed both in the epidemiology of active and 

involuntary smoking-related cardiovascular events and in 

the rapid rate of decline in the major component of excess 

risk for those events after smoking cessation. A hypercoagulable state can result in acute MI in persons who have 

less severe underlying coronary disease, so smokers who 

stop smoking have a better prognosis than do nonsmokers after MI. A more gradual decline of residual risk may 

reflect resolution of smoking-induced vascular injury, 

which in turn stimulates platelet activation. 

Inflammation

Studies demonstrate that cigarette smoking results 

in a chronic inflammatory state, evidenced by increased 

counts of circulating leukocytes, CRP, and acute-phase 

reactants such as fibrinogen (Tracy et al. 1997; Jensen et 

al. 1998; Tuut and Hense 2001). Cigarette smoking also 

activates monocytes and enhances recruitment and adhesion of leukocytes to blood vessel walls, an integral step 

in vascular inflammation (Lehr et al. 1994). Research 

indicates that inflammation contributes to atherogenesis, 

because high leukocyte counts and high levels of CRP and 

fibrinogen are all powerful predictors of future cardiovascular events (Libby et al. 2002).

However, the mechanisms by which cigarette smoking promotes inflammation are not completely elucidated. 

As discussed previously, oxidant stress appears to be a critical factor; oxidized LDL is a proinflammatory stimulus 

(see “Cigarette Smoke Constituents and Cardiovascular 

Disease” earlier in this chapter). Studies also show that 

the products of lipid peroxidation are proinflammatory, 

acting in part on the receptor for platelet-activating factor 

(PAF). In hamsters, the antioxidant vitamin C prevented 

adhesion of leukocytes to the endothelium and leukocyteplatelet aggregation (Lehr et al. 1994). In the same animal 

model, adhesion of leukocytes and formation of leukocyteplatelet aggregates were mediated by PAF-like agonists 

(Lehr et al. 1997). This PAF-like factor was derived from 

oxidative modification of phospholipids and was distinct 

from biosynthetic PAF. Treatment with vitamin C inhibited 

generation of PAF-like lipids. In contrast, oral l-arginine 

but not vitamin C reversed the effect of sera from smokers by promoting monocyte-endothelial cell adhesion, 

which is associated with higher levels of ICAM (Newby et 

al. 2001). The study findings suggest that smoking-related 

impairment of NO release is an important determinant of 

increased adhesion of monocytes to endothelial cells.

Nicotine may contribute to inflammation by acting 

as a chemotactic agent for migration of neutrophils (Nicod 

et al. 1984). One study indicates that nicotine enhanced 

leukocyte-endothelium interactions, resulting in greater 

leukocyte rolling and adhesion in the cerebral microcirculation of mice (Nitenberg et al. 1993). Nicotine reportedly acts on human monocyte-derived dendritic cells to 

stimulate an inflammatory response (Nowak et al. 1987). 

Dendritic cells, which were detected in the walls of arteries and in atherosclerotic lesions, present antigens and are 

thus required for the start of adaptive immunity. Studies 

showed that nicotine is a potent inducer of expression of 

a variety of co-stimulatory molecules and that it increases 

secretion of the proinflammatory cytokine interleukin-12 

in cultured dendritic cells (Aicher et al. 2003). Nicotine 

augmented the capacity of dendritic cells to stimulate 

proliferation of T cells and cytokines. Finally, intravenous 

injection of nicotine increased the movement of dendritic 

cells into atherosclerotic lesions in vivo in mice deficient 

in APO E. This line of research suggests that nicotine 

could contribute to adaptive immunity, which may have 

a role in atherogenesis. However, switching from smoking 

to transdermal nicotine resulted in a significant decline 

in the leukocyte count (Benowitz et al. 1993). In addition, 

use of smokeless tobacco did not produce higher leukocyte counts or higher CRP levels than are seen in persons 

who do not use tobacco. These observations suggest that 

nicotine is not the main determinant of the inflammatory 

response in smokers. 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Smoking and Diabetes

Cigarette smoking is widely known to increase the 

risks of CVD. Even so, this knowledge does not appear to 

influence smoking behaviors among patients with diabetes, who bear a higher risk of cardiovascular morbidity and 

mortality than those who do not have diabetes (Haffner et 

al. 1998). Surveys found that smoking patterns were similar in patients with diabetes and comparable populations 

without that disorder (Ford et al. 1994; Gill et al. 1996). 

Numerous experimental studies demonstrated 

that smoking had negative effects on the metabolism of 

glucose and lipids in persons with or without diabetes. 

Investigators reported that cigarette smoking in patients 

with diabetes was associated with deterioration of metabolic control (Madsbad et al. 1980; Bott et al. 1994) and 

increased risk of microvascular and macrovascular complications and death (Chase et al. 1991; Morrish et al. 

1991). Furthermore, cigarette smoking increases risk of 

type 2 diabetes in the general population (Will et al. 2001). 

This risk may be mediated through direct metabolic 

effects alone or in combination with a metabolically unfavorable lifestyle. 

Risk

In several prospective studies, cigarette smoking 

was associated with increased risk of type 2 diabetes in 

both men and women (Willi et al. 2007). Generally, these 

prospective studies were large and population based. Most 

of the information was collected by mailing participants 

a questionnaire, which in some cases, was supplemented 

with information from medical records. Most of these 

studies included follow-up of more than 10 years. Results 

were generally presented after adjustments for possible 

covariates. 

In the Health Professionals Follow-Up Study, the 

RR of developing diabetes among men who smoked 25 

or more cigarettes per day was 1.94 (95 percent CI, 1.25–

3.03) when nonsmokers were the reference group (Rimm 

et al. 1995). In a smaller British study, the risk of diabetes 

was 50 percent higher among smokers, but this finding 

was not independent of other risk factors, such as obesity and low levels of physical activity (Perry et al. 1995). 

Another British study demonstrated that RR for diabetes 

in men who smoked was approximately 1.7, after adjustments for the effects of age, body mass index, physical 

activity, alcohol intake, social class, undiagnosed CHD, 

and treatment for hypertension (Wannamethee et al. 

2001). Mean follow-up was almost 17 years. The increased 

risk of diabetes was lower 5 years after smoking cessation, 

and the risk normalized 20 years later. A Japanese study 

found similar results and also reported a positive correlation between use of tobacco products and risk of diabetes 

(Uchimoto et al. 1999).

Almost identical results were presented in the Physicians’ Health Study (Manson et al. 2000). During 12 years 

(255,830 person-years1) of follow-up, the risk of diabetes 

in men who smoked more than 20 cigarettes per day was 

70 percent higher than that in nonsmokers, after adjustment for multiple variables. The results also showed 

a significant positive association between the risk of 

developing diabetes and higher consumption of cigarettes 

(Manson et al. 2000). In addition, the Insulin Resistance 

Atherosclerosis Study monitored a cohort of 906 study 

participants for five years with equal representation of 

African Americans, Hispanics, and Whites (Foy et al. 

2005). For all persons studied, current smoking was associated with development of diabetes: the adjusted OR was 

2.66 (95 percent CI, 1.49–4.77). Among participants who 

had normal glucose tolerance at baseline, the OR was 5.27 

(95 percent CI, 2.11–13.16).

At least three other studies of men confirmed the 

main results of these prospective studies (Feskens and 

Kromhout 1989; Kawakami et al. 1997; Ko et al. 2001). 

There have been fewer studies with women, but two major 

prospective surveys yielded similar results. In the Nurses’ 

Health Study (114,247 women; 1,277,589 person-years 

of follow-up), RR for diabetes in heavy smokers was 1.42, 

after adjustments for other risk factors (Rimm et al. 1993). 

In an analysis of data from the Nurses’ Health Study 

after 16 years of follow-up, Hu and colleagues (2001) 

showed that the strongest predictors of diabetes were 

being overweight or obese. In addition, poor diet, smoking, abstinence from alcohol, and low levels of physical activity were all independently associated with the 

risk of developing diabetes. Adjusted RR for developing 

diabetes was approximately 1.4 for smokers compared 

with nonsmokers.

Data from CPS-I, a prospective cohort study conducted between 1959 and 1972, were used to analyze the 

correlation between tobacco use and risk of diabetes in 

both men and women (Will et al. 2001). In comparison 

1Person-year = the sum of the number of years that each member of a population has been smoking.
Surgeon General’s Report

384 Chapter 6

with the risk of developing diabetes for nonsmokers, the 

risks were higher for men who smoked more than one 

pack of cigarettes per day (RR = 1.19) or two packs per 

day (RR = 1.45). Risks were also higher for women who 

smoked more than one pack per day (RR = 1.21) or two 

packs per day (RR = 1.74). After smoking cessation, the 

risk returned to normal after 5 years for women and after 

10 years for men (Will et al. 2001).

Only a few studies, all from the 1970s or 1980s, failed 

to demonstrate a positive association between smoking 

and diabetes, likely due to inadequate study design or lack 

of power in the study to test this hypothesis (Medalie et al. 

1975; Keen et al. 1982; Wilson et al. 1986).

It is generally accepted that risk increases more for 

type 2 diabetes than for type 1, because type 1 diabetes is 

relatively rare among the age groups in the studies. Risk 

for type 2 diabetes is also consistent with the adverse metabolic effects of smoking (see “Insulin Resistance” later in 

this chapter). Type 1 diabetes is insulin deficiency caused 

by autoimmune destruction of pancreatic beta cells; 

in type 2 diabetes, insulin resistance is combined with 

impaired secretion of insulin (Reaven 1988; Kahn 2001).

Metabolic Control

Some studies examined the effects of cigarette 

smoking on the body’s requirement for insulin and metabolic control in patients with diabetes. In a cross-sectional 

study, Madsbad and colleagues (1980) investigated the 

relationship between insulin doses and related variables 

in patients treated with injections of insulin. Insulin 

doses and serum levels of triglycerides were significantly 

higher in the 114 persons who smoked than in the 163 

who did not smoke, and these values increased in a dosedependent manner in relation to the number of cigarettes 

smoked. Hemoglobin A1c (HbA1c)—a marker of long-term 

glucose elevation—was not measured in this study, but 

blood and urine levels of glucose did not differ between 

the two groups. This finding suggests that in patients who 

smoke, a larger insulin dose is needed to achieve metabolic control similar to that in patients who do not smoke.

In a cross-sectional study of 192 patients with type 

1 diabetes, smoking was more common in those with 

higher HbA1c values (Lundman et al. 1990). Other differences between the smokers and nonsmokers were in 

attitudes toward diabetes, psychological well-being, and 

similar factors. 

In a relatively large prospective study that examined the effects of intensified insulin treatment and 

of an educational program, smoking was the most 

consistent determinant of HbA1c levels in relatively young 

articipants treated with insulin (Bott et al. 1994). The 

investigators performed a three-year follow-up on 697 

patients with diabetes who had no debilitating late complications. HbA1c levels were higher throughout the study 

in smokers but eventually improved to levels similar to 

those in nonsmokers, presumably because of the educational program.

Insulin Resistance

The metabolic effects of smoking have been generally studied in persons who did not have diabetes. Insulin 

sensitivity was usually determined by using the euglycemic hyperinsulinemic clamp technique (DeFronzo et al. 

1979). This technique or a slightly modified version of it 

is considered to be the gold standard in metabolic studies. 

In 1993, Attvall and colleagues showed that shortterm smoking caused impaired insulin sensitivity in 

healthy young men. Separately, two cross-sectional studies of men compared uptake of insulin-mediated glucose 

(insulin sensitivity) in smokers and nonsmokers (Facchini et al. 1992; Eliasson et al. 1997a). Insulin sensitivity 

was significantly lower (by 10 to 40 percent) in smokers. 

The degree of insulin resistance was positively correlated 

with tobacco use, and in long-term users of nicotine gum, 

with serum cotinine values (Eliasson et al. 1994, 1996). 

Because cotinine is a metabolite of nicotine, serum and 

urine levels of cotinine reflect the amount of nicotine use. 

Insulin resistance in smokers normalized eight weeks 

after smoking cessation, despite a weight gain of 2.7 kg 

(Eliasson et al. 1997a). 

Smokers in these two cross-sectional studies had 

signs of insulin-resistance syndrome, such as significantly high serum levels of free fatty acids (FFAs) and 

triglycerides and low levels of HDLc (Facchini et al. 1992; 

Eliasson et al. 1997b). In the study by Eliasson and colleagues (1997b), smokers had a high proportion of atherogenic small and dense LDL particles, high fibrinogen 

levels, and high PAI-1 activity compared with those of 

nonsmokers. PAI-1 activity among long-term users of 

nicotine gum was similar, but effects on lipids were not 

as pronounced as those in smokers (Eliasson et al. 1996). 

One aspect of insulin-resistance syndrome that 

attracted attention was postprandial hypertriglyceridemia, 

a phenomenon associated with CVD and insulin resistance 

(Patsch et al. 1992; Jeppesen et al. 1995). This phenomenon is also observed in smokers (Axelsen et al. 1995; Eliasson et al. 1997b), but its cause is unknown. One possible 
Cardiovascular Diseases 385

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

explanation is the inability of smokers to adequately clear 

triglyceride-rich chylomicrons and their remnants from 

the body (Mero et al. 1997). 

Other studies that did not use exact measurements 

of insulin sensitivity reported changes in glucose metabolism in smokers compared with nonsmokers. Compared 

with nonsmokers, smokers were hyperinsulinemic and 

relatively glucose intolerant (Eliasson et al. 1991; Zavaroni et al. 1994; Frati et al. 1996; Ronnemaa et al. 1996). 

A large cross-sectional study showed that after adjustments for confounding factors, smoking behaviors were 

clearly correlated with HbA1c values in persons who did 

not have diabetes (Sargeant et al. 2001), but researchers 

have debated the importance of HbA1c in persons who do 

not have diabetes. Even so, these findings add support to 

the hypothesis that use of tobacco exerts adverse effects on 

glucose homeostasis.

Results in a few studies did not support these findings. Godsland and Walton (1992) found no differences in 

insulin sensitivity between women smokers and nonsmokers, but this result may be attributable to lower levels of 

tobacco use. In addition, the results were from analysis of 

data obtained to test a different hypothesis. In a study of 

metabolic changes in patients with or without hypertension, no differences in insulin sensitivity between smokers 

and nonsmokers were detected (Nilsson et al. 1995). However, the study design likely did not enable discrimination 

between metabolic changes caused by hypertension and 

those caused by smoking.

In patients with type 1 diabetes, Helve and colleagues 

(1986) examined cross-sectional and short-term effects of 

smoking on insulin sensitivity. Despite elevated levels of 

circulating epinephrine, cortisol, growth hormone, and 

glucagon after smoking, no effect of smoking on insulin 

sensitivity was observed. The investigators concluded that 

fluctuations in blood glucose and metabolic control disguised the influence of smoking in these patients with diabetes. In a study of 28 smokers and 12 nonsmokers with 

type 2 diabetes, the researchers measured insulin sensitivity by using euglycemic clamps (Targher et al. 1997). 

Smokers had higher insulin resistance and glucose intolerance than did nonsmokers. The researchers concluded 

that smoking markedly and in a dose-dependent manner 

aggravated insulin resistance observed in patients with 

type 2 diabetes (Targher et al. 1997). 

Axelsson and colleagues (2001) reported that nicotine administered intravenously to nonsmokers caused a 

marked reduction (about 30 percent) in insulin sensitivity 

in those with type 2 diabetes but not in healthy control 

participants. These results suggest that nicotine and possibly tobacco use or other environmental factors may have 

particularly adverse effects in persons susceptible to diabetes but not in those who are healthy (insulin sensitive). 

Microvascular Complications

Microvascular complications in diabetes (retinopathy, nephropathy, and neuropathy) are linked to metabolic 

control in both type 1 and type 2 disease (New England 

Journal of Medicine 1993; Lancet 1998). The mechanisms 

for development of microvascular complications are not 

fully understood, although several pathogenetic pathways 

have been suggested (Brownlee et al. 1984; Tomlinson 

1999; Cai and Boulton 2002). Hyperglycemia has a central 

role as a trigger for subsequent events, such as conversion 

of glucose to sorbitol by aldose reductase; nonenzymatic 

glycosylation of proteins and receptors in susceptible tissues; increased exposure to oxidative stress; and activation 

of protein kinase C and mitogen-activated protein kinases. 

Researchers have suggested that these pathogenetic pathways lead to the disturbances in morphology and function 

found in diabetic nephropathy, retinopathy, and neuropathy (Brownlee et al. 1984; Tomlinson 1999; Cai and Boulton 2002).

Nephropathy

Some studies showed that smoking increased risk of 

microvascular complications in diabetes. Several studies 

of patients with type 1 diabetes reported negative effects 

of tobacco use on albuminuria and renal function. Chase 

and colleagues (1991), for example, showed that the albumin excretion rate was 2.8 times higher in smokers than 

in nonsmokers, after statistical corrections for glycemic 

control, duration of diabetes, age, gender, and blood pressure. In addition, albuminuria progressed at a more rapid 

rate in smokers than in nonsmokers.

Smoking promoted progression of renal disease 

in persons with type 2 diabetes (Biesenbach et al. 1997; 

Chuahirun and Wesson 2002; Chuahirun et al. 2003). Biesenbach and colleagues (1997) studied only 36 patients, 

but follow-up lasted 13 years. At study entry, smokers and 

nonsmokers had similar clinical and laboratory characteristics, but progression of nephropathy and development 

of atherosclerotic disease progressed more rapidly in the 

smokers than in the nonsmokers. Multiple regression 

analysis showed that only tobacco use and blood pressure levels were independently associated with impairment in renal function. This finding underscored the 

roles of smoking and vascular disease in susceptibility to 

renal disease (Biesenbach et al. 1997). In two prospective 
Surgeon General’s Report

386 Chapter 6

studies by Chuahirun and colleagues (2002, 2003), the 

effects of cigarette smoking on acceleration of nephropathy in patients with type 2 diabetes were confirmed even in 

those who had optimal therapy for hypertension. Research 

presented further evidence of functional and structural 

changes in the glomeruli of patients with type 2 diabetes 

who smoke (Baggio et al. 2002). In a study of 96 patients 

who had biopsy of the kidney, electron and light microscopy demonstrated significant changes in glomeruli and 

basal membranes that corresponded to impaired glomerular filtration rates in the smokers.

Retinopathy

Generally, investigators have not considered smoking to be a substantial risk factor for diabetic retinopathy 

(Porta and Bandello 2002). Findings in fairly large studies with mixed populations showed no strong support for 

such an association, except in older adults with certain 

conditions (Walker et al. 1985; Moss et al. 1991). At least 

two studies of patients with type 1 diabetes, however, suggest that smoking does predispose these patients to retinopathy (Mulhauser et al. 1986, 1996). In addition, Chase 

and colleagues (1991) showed that retinopathy was more 

common in patients with type 1 diabetes who smoked than 

in those who did not smoke, but after adjustments for 

covariates, differences were not statistically significant. 

The study also reported accelerated progression of retinopathy in patients who smoked. Thus, smoking may 

be a risk factor for diabetic retinopathy, but only in certain subgroups.

Neuropathy

The role of tobacco in the development of diabetic 

neuropathy is relatively difficult to examine because of 

methodologic problems and the frequent prevalence of 

confounding factors (Westerman et al. 1992). Diabetic 

neuropathy usually develops during a long period, and it 

may affect different sensory, motor, and autonomic nerve 

fibers in varying degrees in individuals. This variation 

makes it difficult to standardize study methods. One casecontrol study reported that risk of neuropathy was three 

times higher in patients with type 1 diabetes who smoked 

than in those who did not smoke (Mitchell et al. 1990). 

Smoking was not related to neuropathy in patients with 

type 2 diabetes. In a study of young patients treated with 

insulin, independent risk factors for progression of distal 

sensory neuropathy, apart from poor glycemic control, 

were cigarette smoking, greater height, and female gender 

(Christen et al. 1999). Other studies in patients with type 

1 diabetes confirmed the roles of glycemic control and 

smoking behaviors in development of clinical neuropathy 

(Maser et al. 1989; Reichard 1992). 

Macrovascular Complications

The multiple effects of smoking on the vascular and 

hemostatic systems and on inflammation are reviewed 

elsewhere in this chapter (see “Hemodynamic Effects,” 

“Smoking and the Endothelium,” “Nicotine and Thrombosis,” and “Inflammation” earlier in this chapter). Diabetes patients are particularly susceptible to some effects 

of smoking, because their risk of cardiovascular morbidity 

and mortality is elevated (Jarrett et al. 1982; Manson et al. 

1991; Morrish et al. 1991).

In a study cohort in London, England, in the prospective Multinational Study of Vascular Disease in Diabetes, sponsored by the World Health Organization, smokers 

with type 1 or type 2 diabetes had significantly increased 

risk of CHD, but not stroke, during the eight-year followup (Morrish et al. 1991). In the Diabetes Control and Complications Trial (New England Journal of Medicine 1993),

designed to study the role of intensive insulin treatment 

and optimized glycemic control in type 1 diabetes, smoking was not a significant risk factor for macrovascular 

complications. Because the participants were relatively 

young, this trial was not optimally designed to study the 

role of tobacco use. Other studies with slightly older participants who had type 1 diabetes reported that smoking 

increased risk of CHD (Moy et al. 1990; Sinha et al. 1997).

Among patients with type 2 diabetes in the United 

Kingdom Prospective Diabetes Study, cigarette smoking 

was a significant and independent risk factor for CHD 

(Turner et al. 1998), stroke (Kothari et al. 2002), and 

PAD (Adler et al. 2002). Also, an analysis of data from 

the Nurses’ Health Study demonstrated that for women 

with type 2 diabetes, a dose-effect relationship existed 

between smoking behaviors and mortality (Al-Delaimy et 

al. 2001). Compared with nonsmokers, risk of mortality 

from all causes was 1.64 for women who smoked 15 to 34 

cigarettes per day and 2.19 for women who smoked more 

than 34 cigarettes per day. Ten years after smoking cessation, risk of mortality had normalized. Researchers published similar data on smoking and CHD risk in the same 

cohort (Al-Delaimy et al. 2002).

A relatively large prospective study that analyzed 

the effects of smoking cessation on cardiovascular risk in 

persons with diabetes compared mortality risk for former 

smokers with that for lifetime nonsmokers (Chaturvedi et 

al. 1997). Compared with mortality risk for lifetime nonsmokers, risk of death from all causes was approximately 

50 percent higher for patients who had stopped smoking 

during the past one to nine years and 25 percent higher 

for those who had not smoked for more than nine years. 

Smoking cessation reduced mortality risk among persons with diabetes, but risks remained high several years 
Cardiovascular Diseases 387

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

after smoking cessation and were highly dependent on the 

duration of smoking. 

Pathophysiological Mechanisms

Having diabetes, even for nonsmokers, is associated with long-term exposure to oxidative stress, 

impaired endothelial function, and dyslipidemia (Brownlee et al. 1984; Turner et al. 1998; Dogra et al. 2001; Cai 

and Boulton 2002; Komatsu et al. 2002). The causes of 

type 2 diabetes are still not fully understood, although 

the main metabolic aberrations are well characterized. 

Research showed that type 2 diabetes is caused by insulin resistance in combination with relative impairment of 

insulin secretion (Reaven 1988; Kahn 2001). Published 

studies have not demonstrated a significant impairment 

in insulin secretion among cigarette smokers (Epifano et 

al. 1992; Facchini et al. 1992; Persson et al. 2000), but 

several studies documented a negative effect of smoking 

on insulin sensitivity (Facchini et al. 1992; Eliasson et 

al. 1997a,b). 

Cigarette smoking and intake of nicotine increase 

the circulating levels of insulin-antagonistic hormones 

(i.e., catecholamines, cortisol, and growth hormone) 

(Kershbaum and Bellet 1966; Cryer et al. 1976; Wilkins 

et al. 1982; Kirschbaum et al. 1992). Smoking also activates the sympathetic nervous system (Niedermaier et al. 

1993; Lucini et al. 1996). Nicotine likely impairs insulin 

sensitivity directly or indirectly through these and possibly other mechanisms. An additional negative factor for 

insulin-mediated glucose uptake is high circulating levels 

of FFAs, secondary to increased lipolysis (Bergman and 

Ader 2000). Research has shown that smoking acutely elevates circulating FFA levels (Kershbaum and Bellet 1966).

Researchers have proposed, but not fully elucidated, 

the potential role of endothelial dysfunction or inflammation in development of insulin resistance and type 

2 diabetes. 

Summary

Many clinical and experimental studies have found 

significant associations between cigarette smoking and 

development of diabetes, impaired glycemic control, and 

diabetic complications (microvascular and macrovascular). A different lifestyle of smokers, in contrast to that 

maintained by nonsmokers, may also contribute to these 

effects. Most of the reviewed studies, however, either 

attempted to statistically adjust for confounding factors 

or were designed to examine short-term effects of tobacco 

and nicotine.

The development of type 2 diabetes is another harmful consequence of cigarette smoking, one that adds to the 

heightened risks of CVD. In diabetes care, smoking cessation is crucial to facilitating glycemic control and limiting 

development of complications.

Lipid Abnormalities

Cigarette smoking is associated with an atherogenic 

lipid profile likely to contribute to risk of CVD. 

Epidemiologic Observations

Several observations are central to the relationship 

between cigarette smoking and lipids. Compared with 

nonsmokers, smokers have higher levels of triglycerides 

associated with very-low-density lipoprotein (VLDL), 

total triglycerides, and APO B, in addition to modest increases in LDLc and lower levels of plasma HDLc and APO 

A-I (Billimoria et al. 1975; Criqui et al. 1980; Wilson et 

al. 1983; Craig et al. 1989; Muscat et al. 1991; Freeman 

and Packard 1995; Villablanca et al. 2000). These findings 

are robust and are reported in numerous survey studies. 

Researchers observed a dose-response relationship 

between the number of cigarettes smoked per day and 

plasma lipid levels (Muscat et al. 1991). In contrast, plasma lipid and lipoprotein levels in former smokers typically 

are similar to those in nonsmokers. 

The ratio of LDLc to HDLc, which is used as a measure of atherogenic risk, is higher in smokers than in 

nonsmokers. Cigarette smoking is thought to raise the 

LDLc to HDLc ratio by 15 to 20 percent. Increased levels of plasma triglycerides are associated with lower HDLc 

levels, but reduction in HDLc from cigarette smoking persists even after corrections for levels of total triglycerides. 

Early epidemiologic studies, such as the Lipid Research 

Clinics Program Prevalence Study and the Framingham 

Heart Study (Criqui et al. 1980; Muscat et al. 1991; Freeman and Packard 1995), emphasized lower HDLc values as 

the primary effect of cigarette smoking. 
Surgeon General’s Report

388 Chapter 6

Researchers have estimated, however, that these 

effects of cigarette smoking on plasma lipids and lipoproteins account for only 10 percent of the observed 70 percent increase in risk of vascular disease associated with 

cigarette smoking (Craig et al. 1989). In the Edinburgh 

Artery Study, for example, adjusting for known CHD risk 

factors reduced the RR of CHD in heavy smokers from 

3.94 to 2.72 and the RR in moderate smokers from 2.72 to 

1.70 (Price et al. 1999). However, cigarette smoking still 

accounted for 75 percent of the risk of developing PAD, 

after adjustment for other known risk factors, such as 

hyperlipidemia and type 2 diabetes (Lu and Creager 2004). 

Other researchers reported similar findings (Cullen et al. 

1998). Cigarette smoking thus appears to have atherogenic effects that are not explained by traditional CHD risk 

factors, including abnormal levels of blood lipids.

Analyses of mechanisms related to lipid and lipoprotein metabolism may be required for understanding the 

atherogenicity of cigarette smoking. Such mechanisms 

include lipid oxidation; changes in composition of lipoproteins; alterations in plasma- and lipoprotein-associated 

lipid transfer enzymes; changes in metabolism of fatty 

acids; effects on levels of postprandial lipids; and changes in cholesterol fluxes, particularly reverse cholesterol 

transport (RCT). The following discussion reviews the 

effects of cigarette smoking on these potential underlying mechanisms.

Lipoprotein Composition and 

Apolipoprotein Levels

Cigarette smoking clearly reduces APO A-I and the 

ratio of A-I to A-II (Mero et al. 1998). APO A-I is a major 

component of HDL particles. The reduction in A-I levels 

observed in smokers is similar to, although perhaps somewhat lower than, the reduction in HDLc levels seen in this 

population. For example, Mero and colleagues (1998) documented that levels of plasma APO A-I were 4 to 6 percent 

lower and HDLc values were 6 to 9 percent lower in moderate-to-heavy smokers. The effects of cigarette smoking 

on APO B and other APOs are also well documented (Billimoria et al. 1975; Craig et al. 1989; Muscat et al. 1991; 

Villablanca et al. 2000).

Researchers have associated abnormalities in different subfractions of HDL with different risks of CHD. 

Cigarette smoking reduced different HDL subfractions in 

different studies (Billimoria et al. 1975; Craig et al. 1989; 

Muscat et al. 1991). Even so, the true atherogenicity of different HDL subfractions remains controversial. The role 

of altered HDL subfractions in arterial disease associated 

with cigarette smoking requires further study. 

Plasma- and LipoproteinAssociated Lipid Transfer Enzymes

Several enzymes in plasma—either free or associated with lipoproteins—are involved in transport and 

use of lipids. Lipoprotein lipase (LPL) activity is involved 

in clearance of total triglycerides from triglyceride-rich 

lipoproteins (TGRLs), particularly the chylomicra formed 

in persons after a meal containing fat. Cigarette smoking 

reportedly reduced plasma LPL activity after a mixed meal 

(Freeman et al. 1998). Reduced LPL activity may contribute to the reduced clearance of TGRLs reported for total 

triglycerides, APO B, and retinyl-ester components of 

TGRLs (Mero et al. 1998). In another study, the cholesterol 

ester transfer protein (CETP) received considerable attention as a therapeutic target for raising HDLc levels (Brousseau et al. 2004; Ruggeri 2005). CETP mediates transfer 

of cholesterol esters between HDL and other lipoproteins 

(VLDL and LDL). However, controversy exists as to whether CETP activity is beneficial or deleterious to the process 

of RCT. Moreover, the proatherogenic or antiatherogenic 

consequences of changing HDLc by the CETP mechanism 

remain uncertain (Ruggeri 2005). Studies have reported 

both increases and decreases in plasma CETP activity in 

smokers (Dullaart et al. 1994; Zaratin et al. 2004). 

Some studies measured other enzymes in smokers. 

For example, cigarette smoking did not appear to markedly alter lecithin cholesterol acyltransferase activity 

(McCall et al. 1994).

Oxidized Lipoproteins

Many investigators hypothesized that oxidized LDL 

is highly atherogenic (Dullaart et al. 1994; Zaratin et al. 

2004), and studies reported increased oxidative damage 

to LDL in smokers (Ambrose and Barua 2004). However, 

attribution of a precise atherogenic contribution from 

oxidative damage to LDL remains speculative. The inadequacy of the metrics of pro-oxidative and antioxidative 

status in vivo needs to be resolved before the role of oxidative damage to LDL can be adequately evaluated.

Postprandial Lipid Changes

Traditionally, plasma lipid and lipoprotein measurements used to evaluate CHD risks have, for largely 

technical reasons, been performed in the fasting (postabsorptive) state. Plasma levels of metabolites are more 

easily characterized in steady-state conditions than in a 

nonsteady state. From a pathophysiological perspective, 
Cardiovascular Diseases 389

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

however, events in the postprandial state may be critical 

in atherogenesis (Zilversmit 1979). Some studies explored 

effects of cigarette smoking on postprandial lipid metabolism (Mero et al. 1998). For example, total triglycerides 

increased to higher levels after a mixed meal in smokers 

than in nonsmokers. These researchers observed increases 

in plasma APO B level and reductions in levels of APO A-I, 

lipoprotein A-I, HDLc, and LDL-APO B after a meal. Other 

investigators postulated that the mechanisms underlying 

altered postprandial lipid changes in smokers include 

lower LPL activity (Freeman et al. 1998), but higher 

endogenous production of VLDL-total triglycerides by the 

liver has not been excluded. The postprandial effects of 

cigarette smoking in particular and their role in atherogenesis in general are not completely understood.

Metabolism of Free Fatty Acids

Changes in FFAs (nonesterified fatty acids) are 

attributed to an increase in adipocyte lipolysis, and they 

represent the most well-characterized mechanistic action 

of cigarette smoking in the context of alterations in lipids 

and lipoproteins. Many studies reported higher plasma levels of FFAs in smokers than in nonsmokers (Kershbaum et 

al. 1963; Bizzi et al. 1972; Walsh et al. 1977; Hellerstein et 

al. 1994; Neese et al. 1994). 

Using stable (nonradioactive) isotopes to measure 

FFA kinetics, researchers demonstrated that cigarette 

smoking immediately and markedly increased influx of 

FFAs into the bloodstream and thereby raised plasma 

levels of FFA (Hellerstein et al. 1994; Neese et al. 1994). 

Plasma FFAs are primarily derived from adipose tissue 

by lipolytic breakdown of stored triglycerides. Catecholamines stimulate hormone-sensitive lipase activity in 

adipose tissue and oppose various antilipolytic actions of 

insulin. Increases in FFA levels and flux induced by smoking were temporally correlated with increases in plasma 

epinephrine levels (Watts 1960; Bizzi et al. 1972; Arcavi et 

al. 1994; Hellerstein et al. 1994; Neese et al. 1994). These 

increases are prevented by β-adrenergic blockers. Nicotine increases the adrenal medullary release of epinephrine in persons with nontolerance of nicotine (Arcavi et 

al. 1994). Therefore, the model implicated as the cause of 

increases in plasma FFA levels induced by cigarette smoking seems clear: cigarette smoking→nicotine→increased 

plasma epinephrine→increased lipolysis in adipose 

tissue→increased release of FFAs into plasma→increased 

plasma levels of FFA. 

The fate of FFAs released into the bloodstream in 

response to cigarette smoking is also relevant. Cigarette 

smoking increases expenditure of energy through the 

activity of nicotine and catecholamines (Ilebekk et al. 

1975; Perkins et al. 1989; Hellerstein et al. 1994; Neese et 

al. 1994). However, most of the FFAs released in response 

to cigarette smoking are not oxidized but taken up and 

reesterified to triglycerides in tissues, particularly the 

liver. This conclusion was partly based on kinetic studies 

that compared the rates at which plasma FFA appeared 

with whole-body rates of fat oxidation (Hellerstein et al. 

1994; Neese et al. 1994). These studies demonstrated that 

the rate of FFA influx into plasma in response to cigarette smoking greatly exceeded changes in whole-body 

fat oxidation. 

Accordingly, the catabolic effects of cigarette smoking on total adipose triglycerides do not directly promote 

oxidation of body fat (weight loss); instead, the primary 

result is overproduction of VLDL-total triglycerides 

(Hellerstein et al. 1994; Neese et al. 1994). This “futile 

cycle,” a substrate cycle in which adipose triglycerides 

are converted to hepatic VLDL triglycerides, is modestly 

wasteful of energy. It accounts for about 5 percent of the 

thermogenic effects of long-term cigarette smoking—for 

example, fewer than 10 kilocalories (kcal)/day if cigarette 

smoking increases total energy expenditure by 200 kcal/

day. This cycle, however, may be the central driving force 

behind the atherogenic dyslipidemia associated with cigarette smoking. Overproduction of VLDL-total triglycerides 

typically results in elevated plasma levels of VLDL-total 

triglycerides and APO B, as well as increased numbers of 

LDL particles (Sniderman et al. 2001). Furthermore, high 

VLDL-total triglycerides contribute to lowering of HDLc 

through CETP-mediated transfer of cholesterol-ester from 

HDL to VLDL particles (Brousseau et al. 2004; Ruggeri et 

al. 2005). Influx of FFAs into the liver for reesterification 

and secretion of total triglycerides is most likely a major 

reason for the low HDLc levels observed in smokers, but 

perhaps it does not represent the entire effect of smoking 

on HDLc (Criqui et al. 1980; Muscat et al. 1991; Freeman 

and Packard 1995). 

If nicotine-stimulated release of catecholamine is 

responsible for the hypertriglyceridemia and low HDLc 

levels observed in smokers, NRT as an adjunct to smoking cessation should logically prevent improvements in 

plasma lipids and lipoproteins after smoking cessation. 

Moffatt and colleagues (2000) reported that nicotinepatch therapy prevented the normalization of HDLc levels observed with smoking cessation in the absence of the 

nicotine patch. The patch also prevented weight gain after 

smoking cessation (Allen et al. 2005), a finding consistent with the hypothesis that shared catecholamines are 

the basis for two important effects of cigarette smoking: 

weight reduction and dyslipidemia. Other studies, however, did not confirm that use of the nicotine patch as an 

agent for smoking cessation prevents improvements in 

HDL levels (Allen et al. 1994). In addition, lipid profiles 
Surgeon General’s Report

390 Chapter 6

are similar in persons who use smokeless tobacco and in 

those who do not use any form of tobacco. To the extent 

that dyslipidemia contributes to vascular disease associated with cigarette smoking, it is important to determine 

the full range of effects of NRT on lipid and lipoprotein metabolism.

Reverse Cholesterol Transport

RCT refers to the pathway by which cholesterol is 

mobilized from tissues, carried through the blood, and 

excreted from the body. HDL and its associated membrane 

receptors (e.g., SR-B1, ABC-A1, and ABC-G1), plasma 

enzymes (e.g., CETP and phospholipid transfer protein), 

APOs (e.g., APO A-I), and hepatobiliary enzymes (e.g., cholesterol 7α-hydroxylase) constitute a system that mediates 

the complex process of RCT through pathways that are 

increasingly well characterized in molecular terms (Neese 

et al. 1994; Tall 1998). RCT is generally accepted as the 

leading explanation for the cardioprotective activity of 

HDL, although other actions of HDL (e.g., antioxidative 

and anti-inflammatory) may also be involved.

Flux through the RCT pathway and, thus, antiatherogenic activity cannot be predicted simply from plasma 

levels of HDL or APO A-I (Tall 1998). Thus, changes in levels of HDLc, VLDL-total triglycerides, and other lipoproteins may not fully capture the effects of cigarette smoking 

on pro-atherogenic or antiatherogenic fluxes such as RCT. 

Until more recently, however, there were no viable techniques for measuring RCT fluxes. Therefore, this question 

could be addressed only indirectly—for example, through 

changes in lipid transfer proteins in plasma that may 

influence the efficiency of RCT. Studies reported decreases in activity of CETP and phospholipid transfer protein 

in smokers after they had smoked a cigarette (Zaratin et 

al. 2004). 

Reduced capacity for remodeling HDL particles in 

the vascular compartment could alter these fluxes in a 

manner not reflected by HDLc levels. This possibility will 

remain speculative, however, until RCT fluxes are measured in humans. The ability to directly measure effects of 

cigarette smoking on the cardioprotective process of RCT 

could provide a major tool for advancing understanding 

of the role of lipids in causing vascular disease associated 

with cigarette smoking.

Effects of Smoking Cessation

Research on smoking cessation largely confirmed 

the associations observed in smokers (Gordon et al. 1975; 

Rabkin 1984; Stamford et al. 1986; Critchley and Capewell 

2004). Many studies documented the return of normal 

levels of plasma lipids and lipoproteins after cessation of 

cigarette smoking.

Therapeutic Implications of 

Pathogenic Mechanisms

If stimulation of lipolysis underlies the atherogenic 

dyslipidemia associated with cigarette smoking, inhibition of lipolysis might be an effective therapeutic strategy to improve blood lipid profiles in smokers or persons 

receiving NRT. This strategy is an attractive approach in 

one sense because inhibition of lipolysis does not block 

the thermogenic actions of nicotine. The cycle of lipolysis and reesterification accounts for less than 5 percent 

of the increase in energy expenditure observed in cigarette smokers (Hellerstein et al. 1994; Neese et al. 1994). 

Another consideration is that if FFAs released by lipolysis 

are involved in the insulin resistance reportedly associated with cigarette smoking (Facchini et al. 1992), lipolysis 

inhibitors may have an additional therapeutic use. 

Niacin, a hypolipidemic agent, is thought to act 

at least partly by inhibiting total triglyceride lipolysis in 

adipose tissue (Meyers et al. 2004). The use of niacin in 

smokers who are at high risk for CHD has not been fully 

investigated. The side effects of niacin, including cutaneous flushing and worsening of insulin resistance in some 

persons, perhaps from effects on pancreatic islet function, 

may discourage its clinical use. The impact of niacin and 

its analogs on lipolysis is complex. They induce a rebound 

overshoot of lipolysis after initial inhibition, but niacin 

does reduce production of VLDL-total triglycerides (Wang 

et al. 2001). 

Other strategies for use of lipolysis inhibitors to 

prevent CHD related to cigarette smoking may require 

development of specific antilipolytic agents that are well 

tolerated. One possibility is the thiazolidinedione class 

of insulin-sensitizing drugs. In one study, such drugs 

reduced lipolysis in adipose tissue, perhaps by activating 

glyceroneogenesis and thereby promoting intra-adipocytic reesterification of FFAs (Chen et al. 2005). No studies 

are known to have tested the efficacy of thiazolidinediones 

in smokers to determine effects on lipid abnormalities or 

sensitivity to insulin. However, recent research indicates 

that rosiglitazone (a thiazolidinedione) increases CHD 

risk, although pioglitazone, another drug in the same 

class, does not increase this risk (Lincoff et al. 2007; Nissen and Wolski 2007). Thus, it is unclear whether the 

possible benefits of this class of drugs in smokers will 

be pursued.
Cardiovascular Diseases 391

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Summary

Effects of cigarette smoking on standard measures of blood lipids and lipoproteins are well characterized. The most important effects are to lower levels of 

HDLc and increase levels of total triglycerides. The metabolic mechanisms underlying these changes are known 

to some extent, particularly the catecholamine-mediated 

increase in adipocyte lipolysis, changes in plasma levels 

of FFAs, and reesterification of FFAs by the liver. However, the predicted effect from changes in standard lipid 

risk factors for vascular disease associated with cigarette 

smoking appears to be modest. Future research will reveal 

whether this estimation of a modest effect is a true estimate of the pathogenic importance of smoking-induced 

changes in blood lipid levels or an inability to measure the 

full effects of cigarette smoking on atherogenesis. 

Cardiovascular Biomarkers

Biomarkers of smoking-related CVD risk are useful 

for stratifying individual risk and, perhaps, for assessing 

product risk. Biomarkers for CVD risk can be divided into 

three categories: (1) constituents of cigarette smoke that 

contribute to CVD, (2) physiological changes involving 

potential mechanisms of CVD, and (3) chemical biomarkers of cardiovascular dysfunction and disease (Table 6.3). 

Studies showed that cigarette smoking altered many of the 

CVD biomarkers, as evidenced by comparisons of smokers 

with nonsmokers and former smokers. However, fewer 

studies prospectively examined reversal of such changes 

after smoking cessation. More important, to date, there 

are no data on how changes in smoking-related biomarkers predict risk of disease. 

Three constituents of cigarette smoke received the 

greatest attention as potential contributors to CVD: CO 

measured as exhaled CO or as blood carboxyhemoglobin, 

nicotine, and oxidant chemicals (Benowitz 2003). These 

constituents are used as general biomarkers of exposure 

to tobacco or tobacco smoke. Apparently, no direct measures of levels of oxidizing chemicals in the body have 

been developed, but numerous measures of the biologic 

consequences of exposure to oxidizing chemicals exist. 

Exposure to particulate matter in cigarette smoke is likely to contribute to CVD in smokers (Brook et al. 2004; 

Vermylen et al. 2005; Bhatnagar 2006), but no direct biomarkers of particulate exposure are available. Particulate 

matter appears to affect oxidative stress, coagulability, and 

inflammation, for which biomarkers are available. A lesser 

body of research suggests that PAHs and other constituents of tobacco smoke may also contribute to atherogenesis (Penn and Snyder 1988, 1996). Urine levels of PAH 

metabolites can also be measured in smokers; 1-hydroxypyrene is most widely used for this purpose. 

Cigarette smoke exposes the smoker to high levels 

of potentially oxidizing chemicals (Burke and FitzGerald 

2003). In one study, cigarette smoking increased levels of 

lipid peroxidation products, such as F2-isoprostanes, in 

the plasma and urine (Nowak et al. 1987). Other markers 

of oxidative stress in smokers included higher plasma levels of oxidized LDL and oxidized fibrinogen, higher urine 

levels of substances reactive with thiobarbituric acid, and 

reduced plasma levels of antioxidant vitamins such as E, 

C, and beta-carotene. 

The hemodynamic effects of cigarette smoking can 

be observed while a person smokes a cigarette. These 

effects include elevation in heart rate, blood pressure, 

and cardiac output. Coronary blood flow, as assessed by 

coronary perfusion studies, may increase or decrease with 

smoking, depending on underlying atherosclerosis and 

endothelial function (Czernin and Waldherr 2003). 

Researchers have proposed numerous biomarkers 

for measuring endothelial dysfunction, and many of these 

biomarkers are affected by cigarette smoking. The functional assessment most widely used is flow-mediated arterial vasodilation (Puranik and Celermajer 2003), a test that 

measures the diameter of the brachial artery in response 

to changes in forearm blood flow. The brachial artery is 

imaged by using Doppler ultrasonography before and 

after release of a blood pressure cuff that is inflated over 

the forearm to occlude arterial blood flow. With release of 

the cuff, the increase in blood flow triggers an increase 

in the diameter of the brachial artery that is mediated by 

release of NO and prostacyclin by endothelial cells. Many 

researchers demonstrated impairment of flow-mediated 

dilation in populations of active smokers and persons 

exposed involuntarily to cigarette smoke, but estimates of 

impairment in persons with no exposure to smoke overlapped considerably with those for the other two groups. 

Other potential markers of endothelial dysfunction that 

can be measured in the blood include ADMA, von Willebrand factor, tPA, E-selectin, and P-selectin. Prostacyclin 

metabolites can be measured in the urine (Cooke 2000). 

Selectins are adhesion molecules released by both endothelial cells and platelets (Ley 2003). 
Surgeon General’s Report

392 Chapter 6

Table 6.3 Biomarkers of risk for cardiovascular disease from exposure to cigarette smoke

      Study

Biomarker Measurement of:

Smokers vs. 

nonsmokers

Change with 

smoking cessation

Dose-response 

relationship

Change with 

reduced smoking

Chemical biomarkers               

Carbon monoxide Delivery of potential 

chemical toxins

SRNT 

Subcommittee 

on Biochemical 

Verification 2002

SRNT 

Subcommittee 

on Biochemical 

Verification 2002

Benowitz and 

Jacob 1984

Hecht et al. 2004

Nicotine and

cotinine

Delivery of potential 

chemical toxins

SRNT 

Subcommittee 

on Biochemical 

Verification 2002

SRNT 

Subcommittee 

on Biochemical 

Verification 2002

Benowitz and 

Jacob 1984

Benowitz et al. 

1983

Physiological and 

biochemical markers               

Blood pressure Hemodynamic 

effects

Benowitz et al. 

2002

Benowitz et al. 2002      

C-reactive protein Inflammation Bazzano et al. 

2003

Bazzano et al. 2003 Bazzano et al. 

2003

Carotid and femoral 

artery intima-media 

thickness

Atherosclerosis Wallenfeldt et al. 

2001

        

Circulating 

endothelial precursor 

cells

Endothelial function Kondo et al. 2004 Kondo et al. 2004 Kondo et al. 

2004

  

E-selectin Endothelial function Bazzano et al. 

2003

Bazzano et al. 2003      

Fibrinogen Hypercoagulable 

state

Bazzano et al. 

2003

Bazzano et al. 2003 Bazzano et al. 

2003

  

Flow-mediated 

dilation

Endothelial function Czernin and 

Waldherr 2003

Czernin and 

Waldherr 2003

Czernin and 

Waldherr 2003

  

Glucose-clamping 

studies

Insulin resistance Eliasson et al. 

1997a

Eliasson et al. 1997a Eliasson et al. 

1997a

  

HDL cholesterol Lipid marker Stubbe et al. 

1982

Stubbe et al. 1982      

Heart rate Hemodynamic 

effects

Benowitz et al. 

1984

Benowitz et al. 1984      

Hemoglobin A1c Insulin resistance Sargeant et al. 

2001

        

Homocysteine Hypercoagulable

state

Bazzano et al. 

2003

Bazzano et al. 2003 Bazzano et al. 

2003

  
Cardiovascular Diseases 393

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

      Study

Biomarker Measurement of:

Smokers vs. 

nonsmokers

Change with 

smoking cessation

Dose-response 

relationship

Change with 

reduced smoking

Insulin/glucose ratio Insulin resistance Zavaroni et al. 

1994

        

Interleukin-6 Inflammation Bermudez et al. 

2002

Bermudez et al. 

2002

     

Nuclear coronary 

perfusion studies

Hemodynamic 

effects

Czernin and 

Waldherr 2003

      Mahmarian et al. 

1997

Oxidized LDL 

cholesterol

Oxidative stress/lipid 

marker

Panagiotakos et 

al. 2004

Panagiotakos et al. 

2004

     

P-selectin Endothelial function Bazzano et al. 

2003

Bazzano et al. 2003      

Red blood cell mass Hypercoagulable 

state

Blann et al. 1997 Blann et al. 1997      

Serum concentrations 

of vitamin C

Oxidative stress Lykkesfeldt et al. 

2000

        

Serum triglycerides Lipid marker Axelsen et al. 

1995

        

Soluble intercellular 

adhesion molecule-1

Inflammation Scott et al. 2000 Scott et al. 2000 Scott et al. 

2000

  

Thiobarbituric acid 

reactive substances

Oxidative stress            

Tissue plasminogen 

activator

Hypercoagulable 

state 

Simpson et al. 

1997

        

Urine F2- isoprostanes Oxidative stress Morrow et al. 

1995

Pilz et al. 2000      

Urine thromboxane 

A2 metabolite

Hypercoagulable 

state

Nowak et al. 1987 Saareks et al. 2001      

von Willebrand factor Endothelial function Blann et al. 1997 Blann et al. 1997      

White blood cell 

count

Inflammation Jensen et al. 1998 Jensen et al. 1998 Jensen et al. 

1998

  

Note: HDL = high-density lipoprotein; LDL = low-density lipoprotein; SRNT = Society for Research on Nicotine and Tobacco.

Table 6.3 Continued
Surgeon General’s Report

394 Chapter 6

Markers of the hypercoagulable state include 

increased urine levels of thromboxane A2 metabolites. 

Thromboxane A2 is released when platelets aggregate in 

vivo, and its metabolites in urine are a useful noninvasive 

measure of the point of activation (Nowak et al. 1987). 

Other relevant biomarkers of a hypercoagulable state 

include fibrinogen, red blood cell mass, blood viscosity, 

tPA, PAI-1, homocysteine, and P-selectin (Benowitz 2003).

Biomarkers used to assess an inflammatory state 

include total leukocyte and neutrophil counts and levels 

of CRP, fibrinogen, and interleukin-6 (Pearson et al. 2003). 

In addition, the counts of several cell-surface adhesion 

molecules increased in inflammatory states. These molecules included ICAM, sVCAM-1, and monocyte chemoattractant protein-1.

Another study found several markers to be useful for 

assessing insulin resistance (Eliasson 2003). For example, 

in persons with insulin resistance, levels of plasma glucose were likely to be elevated in fasting status and two 

hours after eating. HbA1c levels, which reflect plasma glucose levels throughout the day, were elevated in persons 

in a hyperglycemic state. The ratio of insulin to glucose 

after glucose loading was useful as an index of insulin 

sensitivity. The most definitive investigations were glucose-clamping studies, in which insulin levels were measured when the glucose level was constant or vice versa. 

Numerous standard markers of lipids may be altered 

in cigarette smokers. These markers include HDLc, LDLc, 

the ratio of total cholesterol to HDL, and serum triglyceride levels. 

Nuclear coronary perfusion studies with or without 

physical exercise are among several functional studies for 

diagnosing cardiovascular dysfunction or disease. They 

indicate that cigarette smoking reduces cardiac perfusion 

in patients with coronary disease (Czernin and Waldherr 

2003). Reserve in endothelial function can be assessed 

by studying flow-mediated dilation (see “EndotheliumDependent Vasodilation” earlier in this chapter). Findings in another study indicate that vascular disease can 

be assessed by measuring intima-media thickness of the 

carotid and femoral arteries by ultrasonography, which 

provides a direct measure of early atherosclerotic changes 

in blood vessels (de Groot et al. 2004). 

Numerous cardiovascular biomarkers that might be 

used to assess the effects of cigarette smoking and involuntary smoking and that are expected to increase the risk 

of CVD are discussed here. Many biomarkers, however, 

do not reflect causal pathways related to development of 

CVD. Instead, they reflect the pathophysiological effects 

of the constituents of cigarette smoke. In addition, many 

biomarkers are influenced by processes and risk factors 

that are independent of cigarette smoking. Many of the 

same abnormalities produced by smoking are also produced by diabetes, hypercholesterolemia, and hypertension. Thus, it is unclear which biomarkers are most 

specific to cigarette smoking. It is also unclear which biomarkers best predict the risk of CVD attributable to cigarette smoke. Also, a given biomarker profile can indicate 

any of several marked differences in a person’s susceptibility to CVD. 

The potential exists to develop improved biomarkers 

for CVD by using advances in high-throughput genomics and by examining the relationships of gene polymorphisms or alterations in protein expression or activity to 

smoking-induced disease (Zhang et al. 2001). Emerging 

genomic and proteomic technologies may cast light on 

the signaling pathways activated by smoking and the constituents of tobacco smoke that culminate in cardiovascular dysfunction. Such approaches may also contribute to 

an understanding of individual differences in susceptibility to the cardiovascular complications of smoking. 

Numerous studies of clinical genetics examined differences in susceptibility to smoking-induced CVD as a 

function of different genetic variants (Wang et al. 2003). 

Such studies, combined with genomic and proteomic 

approaches, may provide mechanistic information on 

pathogenesis and, in combination with other biomarkers, may result in better predictions of cardiovascular risk 

in smokers.

Smoking Cessation and Cardiovascular Disease

Smoking cessation reduces the risk of cardiovascular 

morbidity and mortality for smokers with or without CVD 

(USDHHS 1990). Smoking directly accelerates atherogenesis, causes acute cardiovascular events, and contributes 

to and acts synergistically with other risk factors, such 

as hyperlipidemia and diabetes (see “Smoking and Diabetes” earlier in this chapter). Although cigarette smoking 

does not cause hypertension, smoking is associated with 

higher blood pressure in persons with hypertension and 

enhances the likelihood of complications, including progression of renal disease in patients with hypertension 

(Green et al. 1986; Mann et al. 1991; McNagny et al. 1997; 

Regalado et al. 2000). One study demonstrated that cigarette smoking was a substantial contributor to morbidity 
Cardiovascular Diseases 395

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

and mortality in patients with left ventricular dysfunction 

(Suskin et al. 2001). In such patients, the benefit of reducing the likelihood of death by smoking cessation is equal 

to or greater than the benefit of therapy with inhibitors of 

ACE, β-blockers, or spironolactone. Smoking cessation is 

particularly important in patients with diabetes. For these 

patients, smoking markedly increases cardiovascular risks, 

including the risk that diabetic nephropathy will progress. 

Smoking also increases insulin resistance and increases 

the difficulty of controlling diabetes. For these and other 

reasons, smoking cessation in patients with CVD is an 

essential therapeutic intervention. 

The 1990 Surgeon General’s report on smoking cessation (USDHHS 1990) outlines the evidence that stopping smoking helps to prevent CVD, and subsequent 

research has reinforced this concept (Hasdai et al. 1997a; 

van Domburg et al. 2000; Wilson et al. 2000). Estimates 

in case-control and cohort studies indicate that most risk 

reduction for mortality occurred in the first one to three 

years after smoking cessation, and approximately onehalf of the risk of smokers for a nonfatal MI was eliminated in the first year after cessation. It takes about three 

to five years of abstinence from smoking for most of the 

excess CVD risk to be gone (USDHHS 1990; Lightwood 

and Glantz 1997). 

Smoking cessation after MI reduces the risk of cardiovascular morbidity and mortality by 36 to 50 percent 

(USDHHS 1990; Kumanan et al. 2000; Wilson et al. 2000; 

Rea et al. 2002; Critchley and Capewell 2003). Smoking 

cessation is highly cost-effective (Krumholz et al. 1993; 

Lightwood 2003) and is recommended in professional 

guidelines for prevention of recurrent cardiovascular 

events in persons with known CVD (Smith et al. 2001). 

Evidence supports the central roles of smoking cessation 

and eliminating exposure to secondhand smoke in preventing development and progression of CVD (USDHHS 

1990, 2006; Benowitz and Gourlay 1997; Hasdai et al. 

1997a; van Domburg et al. 2000; Wilson et al. 2000; Goldenberg et al. 2003).

Methods

Tobacco use and dependence are determined by 

complex physiological and psychological factors. Use of 

nicotine causes tolerance, physical dependence, and a 

withdrawal syndrome when smoking is stopped (USDHHS 

1988). Use of tobacco is a learned behavior that becomes 

part of the daily routine of a smoker and is often used to 

cope with stress, anxiety, anger, and depression (USDHHS 

1988; Rigotti 2002). 

Interventions to achieve smoking cessation target both the physiological and psychological factors that 

contribute to tobacco use. Evidence from randomized 

controlled clinical trials of cessation methods has been 

summarized in meta-analyses conducted independently 

by two groups—the U.S. Public Health Service (PHS) 

and the Cochrane Database of Systematic Reviews (the 

Cochrane Library). These reviews document the efficacy of 

both psychosocial counseling and pharmacologic agents 

for cessation (Fiore et al. 2000, 2008). Combination of 

the two methods is the most effective strategy. Interventions in psychosocial counseling range from brief counseling by the physician to intensive, cognitive-behavioral 

counseling interventions during several weeks. There is a 

dose-response relationship between behavioral treatment 

and smoking cessation; that is, the efficacy of counseling interventions increases with increased intensity and 

duration of the program (Fiore et al. 2000, 2008; USDHHS 

2000). The U.S. Food and Drug Administration (FDA) 

has approved pharmacotherapy for tobacco dependence. 

The pharmacotherapy includes five types of NRT (gum, 

transdermal patch, nasal spray, vapor inhaler, and lozenge), sustained-release bupropion, and varenicline. PHS 

designated these medications as first-line therapies for 

smoking cessation in Treating Tobacco Use and Dependence: Clinical Practice Guidelines (Fiore et al. 2000). Two 

other drugs—nortriptyline and clonidine—were efficacious in randomized controlled trials and were shown to be 

effective in the Cochrane review and in meta-analyses conducted for development of the PHS guidelines (Fiore et 

al. 2000, 2008; Gourlay et al. 2004; Hughes et al. 2004b). 

These drugs have not been approved by FDA for use in 

smoking cessation, and in the PHS report, they are designated as second-line interventions. There is no evidence to 

support use of alternative therapies such as acupuncture 

and hypnosis for smoking cessation (Abbot et al. 1998; 

Fiore et al. 2000, 2008; White et al. 2002).

Interventions

Multiple randomized controlled clinical trials demonstrated the benefits of counseling patients with CVD 

on smoking cessation (Table 6.4) (Thomson and Rigotti 

2003). In contrast, relatively few clinical trials tested the 

safety or efficacy of pharmacotherapy for treating smokers 

with CVD (Table 6.5). Researchers raised concerns about 

the safety of NRT and sustained-release bupropion in 

patients with CVD, because both agents can have sympathomimetic activity and can theoretically increase 

myocardial work, and NRT might also reduce the myocardial oxygen supply through coronary vasoconstriction by 

aggravating endothelial dysfunction (Benowitz and Gourlay 1997). 
Surgeon General’s Report

396 Chapter 6

Table 6.4 Randomized controlled trials of counseling for smokers hospitalized with cardiovascular disease

Study Population

In-hospital 

counselor, duration 

of counseling

Postdischarge 

counseling

Smoking 

cessation rates 

(%)

RR or OR 

(95% CI) 

p value

Taylor et al. 

1990

Acute MI

I vs. C: 86 vs. 87

5 hospitals 

San Francisco Bay, 

California

Nurse

Average duration 

3.5 hours for baseline 

and postdischarge 

counseling

TC: 1, 2, 3 weeks, 

then every 

month x 4 

CV for relapse after 

smoking cessation

12 months

I vs. C: 61 vs. 32

1.9 (1.3, 2.8)

p <0.001

Ockene et al. 

1992

Coronary angiogram

I vs. C: 135 vs. 132

3 hospitals 

Massachusetts

Health educator 

30 minutes

TC: 1, 3 weeks; 

3 months for relapse 

after smoking 

cessation; 2 and 4 

months for relapse 

after smoking 

cessation

12 months

SR: 57 vs. 48

I vs. C: 35 vs. 28

3-vessel CAD

I vs. C: 65 vs. 41

1.5 (0.9, 2.4)

p = 0.06

1.4 (0.8, 2.4)

p = 0.19

13.4 (3.1, 58.0)

DeBusk et al. 

1994

Acute MI

I vs. C: 131 vs. 121

5 hospitals 

San Francisco Bay, 

California

Nurse

Duration not stated

TC: 2 days, 1 week, 

monthly x 6

12 months

I vs. C: 70 vs. 53 p = 0.03

Rigotti et al. 

1994

Coronary artery 

bypass graft

I vs. C: 44 vs. 43

Massachusetts 

General Hospital,

Boston

Nurse

60 minutes

TC: once per 

week x 3

12 months

I vs. C: 61 vs. 54 p >0.52

Dornelas et 

al. 2000

Acute MI

I vs. C: 54 vs. 46

Hartford Hospital

Hartford, 

Connecticut

Psychologist 

Duration not stated

TC: <1, 4, 8, 12, 16, 

20, and 26 weeks

6 months

SR: 67 vs. 43

12 months

SR: 55 vs. 34

FV: 66 vs. 37

p <0.05

p = 0.04

p <0.05

Hajek et al. 

2002

Acute MI or cardiac 

bypass surgery

I vs. C: 267 vs. 273

17 hospitals 

England

Nurse

20–30 minutes

None 12 months

I vs. C: 37 vs. 41 p = 0.40

QuistPaulsen and 

Gallefoss 

2003

Acute MI, unstable 

angina, or cardiac 

bypass surgery

I vs. C: 100 vs. 118

1 hospital 

Norway

Cardiac nurses 

(no training)

Duration not stated

TC: 2 days, 1 week, 3 

weeks, 3 months, 5 

months

CV: 6 weeks

12 months

I vs. C: 50 vs. 37

Absolute risk 

reduction: 35% 

(0%, 26%)

Note: CAD = coronary artery disease; CI = confidence interval; CV = clinic visit; FV = validated by family; I vs. C = intervention versus 

control; MI = myocardial infarction; OR = odds ratio; RR = relative risk; SR = self-reported; TC = telephone call.
Cardiovascular Diseases 397

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Table 6.5 Randomized controlled trials of pharmacologic interventions for smoking cessation in patients with 

cardiovascular disease

Study Population Treatment

Counseling 

(I & C)

Smoking 

cessation 

ratesa (%)

RR or OR 

(95% CI), 

p value

Adverse events 

(I vs. C)

Transdermal 

nicotine                  

Working Group 

for the Study 

of Transdermal 

Nicotine in 

Patients with 

Coronary Artery 

Disease 1994

Stable outpatients 

with CVD

I vs. C: 77 vs. 79

General medical 

and cardiology 

clinics

Media advertising

4 centers 

United States

14 mg could be 

increased to 

21 mg after 

1 week

5 weeks

Group 

counseling 

weekly x 5

5 weeks

I vs. C: 36 

vs. 22

p <0.05

No differences 

in episodes of 

angina or change 

in blood pressure, 

heart rate, or 

EKG readings

Joseph et al. 

1996

Joseph and 

Antonnucio 1999

Stable outpatient 

veterans with CVD

I vs. C: 288 vs. 287

10 Veterans Affairs 

medical centers

United States

21 mg x 6 weeks

14 mg x 2 weeks

7 mg x 2 weeks

Behavioral 

counseling

15 minutes at 

study entry

10 minutes at 

1 and 6 weeks

14 weeks

I vs. C: 21 

vs. 9

6 months

I vs. C: 14 

vs. 11

12 months

I vs. C: 10 

vs. 12

p = 0.001

p = 0.67

p = 0.41

No difference 

in primary 

endpoints 

(death, MI, 

cardiac arrest, 

or admission 

to hospital) 

or secondary 

endpoints 

(other CVD)

Tzivoni et al. 

1998

Stable outpatients 

with CAD in 

smoking cessation 

program

I vs. C: 52 vs. 54

2 centers

Israel

21 mg (>20 

cigarettes/day) 

or 14 mg (<20 

cigarettes/day)

2 weeks

Smoking 

cessation 

program

Group meetings 

weekly

2 weeks

I vs. C: 73 

vs. 52

p <0.05b

No differences 

in EKG changes, 

exercise testing, 

or heart rate and 

blood pressure

Bupropionsustained 

release                  

Tonstad et al. 

2003

Stable outpatients 

with CVD

I vs. C: 313 vs. 313

28 centers in 

10 European 

countries

150 mg BID

7 weeks

Target date 

for smoking 

cessation 7–14 

days after 

starting drug

TC: 1 day 

before smoking 

cessation 

3 days afterward

Monthly x 12 

CV: brief 

counseling at 3, 

6, and 12 months

12 months

I vs. C: 27 

vs. 12

Continuous 

abstinence 

weeks 4–52

I vs. C: 22 

vs. 9

p <0.001

p <0.001

Cardiovascular 

events

I vs. C: 24 vs. 14 

(p = NS)
Surgeon General’s Report

398 Chapter 6

Table 6.5 Continued

Study Population Treatment

Counseling 

(I & C)

Smoking 

cessation 

ratesa (%)

RR or OR 

(95% CI), 

p value

Adverse events 

(I vs. C)

Rigotti et al. 

2006

Acute MI, unstable 

angina, or other 

CVD hospital 

admission

I vs. C: 124 vs. 124

5 academic medical 

centers

New England

150 mg BID

12 weeks

Started during 

hospitalization

Nurse 

counseling for 

40 minutes in 

hospital

TC: 48 hours, 

1, 3, 8, and 12 

weeks after 

discharge

12 weeks

I vs. C: 37 

vs. 27

12 months

I vs. C: 25 

vs. 21

1.61 (0.74, 

2.76)

p = 0.08

1.23 (0.68, 

2.23)

p = 0.49

No difference in 

CVD mortality 

(0% vs. 2%) or 

in CVD events at 

12 weeks (16% 

vs. 14%, IRR 1.22 

[0.61–2.48]) or 

1 year (26% vs. 

18%, IRR 1.56 

[0.88, 2.82])

Note: BID = twice a day; CAD = coronary artery disease; CI = confidence interval; CV = clinic visit; CVD = cardiovascular disease; 

EKG = electrocardiogram; I vs. C = intervention versus control; IRR = incidence rate ratio; mg = milligrams; MI = myocardial 

infarction; NS = not significant; OR = odds ratio; RR = relative risk; TC = telephone call. aAbstinence measured by point prevalence (no smoking in previous seven days) unless otherwise noted.

bp value calculated with c2 test. 

Counseling

Several randomized controlled clinical trials demonstrated the efficacy of counseling for patients hospitalized 

with CVD (Table 6.4). The evidence for efficacy is strongest 

for patients who had acute MI (Pozen et al. 1977; Taylor et 

al. 1990; Ockene et al. 1992; DeBusk et al. 1994; Dornelas 

et al. 2000). In one study, an intensive, nurse-managed 

intervention to achieve smoking cessation for 173 smokers hospitalized with an acute MI doubled the cessation 

rates at one year (61 versus 32 percent, p <0.001) (Taylor et 

al. 1990). At the bedside, the nurse delivered a 30-minute 

cognitive-behavioral counseling session focused on selfefficacy and prevention of relapse. Additional counseling 

was delivered by telephone at one, two, and three weeks 

after discharge and then every month for four months. 

A second study of the same patients expanded the nursedelivered counseling model to target multiple cardiac risk 

factors (DeBusk et al. 1994). This study also reported rates 

of smoking abstinence higher than those in the first study 

(Taylor et al. 1990). A third trial assigned 100 consecutive smokers admitted with MI to either minimal care or 

bedside counseling with seven follow-up telephone calls 

(Dornelas et al. 2000). Smoking cessation rates at one year 

were higher in the intervention group than in the minimal care group (55 versus 34 percent, p <0.05). A more recent study of 240 smokers admitted to the hospital for MI, 

unstable angina, or cardiac bypass surgery demonstrated 

that counseling by cardiac nurses untrained in counseling and then follow-up counseling during the next five 

months reduced smoking rates at one year (50 versus 37 

percent, absolute risk reduction, 13 percentage points [95 

percent CI, 0 to 26 percentage points]) (Quist-Paulsen and 

Gallefoss 2003). 

Other studies that lacked the same intensity of follow-up after hospital discharge produced less impressive 

results. One study examined a multicomponent behavioral smoking intervention delivered to 267 patients having coronary angiography (Ockene et al. 1992). Compared 

with patients who did not receive the intervention, those 

with angiography had higher rates of validated smoking 

abstinence at 6 months (45 versus 34 percent) and 12 

months (35 versus 28 percent), but these differences were 

not statistically significant. Two randomized trials (Rigotti 

et al. 1994; Hajek et al. 2002) and one partially randomized 

trial (Bolman et al. 2002) examined the effects of inpatient 

counseling with minimal follow-up in cardiac patients. 

These studies showed no improvement in abstinence rates 

with the counseling intervention versus usual care. 

The most successful counseling interventions 

for cardiac inpatients include high-intensity baseline 

counseling with sustained contacts after discharge for 

prevention of relapse. However, even with the most successful counseling interventions, at least 40 percent of 

smokers who have cardiac disease resume smoking within 

one year. Guidelines for smoking cessation recommend 

addition of pharmacotherapy to counseling (Fiore et 

al. 2000, 2008). Pharmacotherapy has the potential to 

improve smoking cessation rates in smokers with CVD 
Cardiovascular Diseases 399

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

(see “Nicotine Replacement Therapy” and “Bupropion” 

later in this chapter).

Nicotine Replacement Therapy

NRT helps smokers stop smoking and also reduces 

nicotine withdrawal symptoms, which begin a few hours 

after the last cigarette is smoked and can last up to four 

weeks (Hughes et al. 1992). The typical withdrawal syndrome is characterized by agitation, anxiety, depressed 

mood, difficulty concentrating, increased appetite, insomnia, irritability, restlessness, and an intense craving to 

smoke. Most smokers who stop smoking relapse to smoking within the first week, when withdrawal symptoms 

are strongest. 

In multiple clinical trials, all the NRT products 

approximately doubled rates of smoking abstinence compared with rates for participants receiving a placebo (Fiore 

et al. 2000; Silagy et al. 2004). Meta-analyses conducted 

for PHS demonstrated ORs of 1.9 (95 percent CI, 1.7–2.2) 

for the nicotine patch and 1.5 (95 percent CI, 1.3–1.8) for 

nicotine gum. Meta-analyses from the Cochrane Library 

found similar results; ORs were 1.74 (95 percent CI, 

1.57–1.93) for the patch and 1.66 (95 percent CI, 1.52–

1.81) for the gum (Silagy et al. 2004). For smokers with 

greater dependence on nicotine, the 4-mg dose of nicotine 

gum was more effective than the 2-mg dose. Maximum 

effectiveness depended on correct chewing techniques. 

Similar ORs were reported after meta-analyses of data on 

the nicotine inhaler and nicotine nasal spray (Fiore et al. 

2000). Only one study compared the efficacy of four forms 

of NRT (patch, gum, inhaler, and nasal spray); they demonstrated similar efficacy rates after 12 weeks of follow-up 

(Hajek et al. 1999).

Nicotine directly affects the cardiovascular system by 

multiple mechanisms (see “Cigarette Smoke Constituents 

and Cardiovascular Disease” earlier in this chapter). The 

various effects lead to increased heart rate, blood pressure, 

and myocardial contractility, and reduced coronary blood 

flow. Nicotine may also contribute to insulin resistance 

and development of a more atherogenic lipid profile. The 

nicotine dose in NRT products is usually lower than the 

dose from smoking, but there have been concerns about 

the safety of NRT in patients with CVD. Case reports in 

the medical literature described atrial fibrillation, MI, and 

stroke in patients receiving NRT (Joseph and Fu 2003). It 

is difficult to assess the cardiovascular risk from NRT on 

the basis of these reports, because of the inability to control for individual risk factors for these events, especially 

that these persons were smokers (Benowitz and Gourlay 

1997; Joseph and Fu 2003). 

To date, three randomized controlled trials of transdermal use of nicotine have been conducted in patients 

with stable CVD. The first study enrolled 156 patients 

with CHD and randomly assigned them to receive either 

14-mg nicotine patches or a placebo for five weeks (Working Group for the Study of Transdermal Nicotine in 

Patients with Coronary Artery Disease 1994). The dose 

was increased to 21 mg if smoking persisted. Smoking 

abstinence was achieved at five weeks by 36 percent in the 

patch group and 22 percent in the placebo group (p <0.05). 

Patients recorded all episodes of angina, palpitations, and 

other cardiac symptoms in daily diaries and had a 12-lead 

electrocardiogram at three time points. The nicotine 

patch did not affect the frequency of angina, arrhythmias, 

or depression of the ST segment (isoelectric period) on 

electrocardiograms during the five weeks of treatment, 

even in patients who smoked intermittently. 

A second randomized trial of transdermal nicotine 

included 584 outpatients with CVD from 10 Veterans 

Affairs hospitals (Joseph et al. 1996). The participants were 

randomly assigned to receive 21-mg patches or a placebo 

for 10 weeks. Primary cardiovascular endpoints during 14 

weeks of follow-up included MI, cardiac arrest, death, and 

hospital admission for angina, dysrhythmia, or congestive 

heart failure. The two groups did not differ in the proportion of patients who reached at least one cardiovascular 

endpoint (5.4 versus 7.9 percent, p = 0.23). Concomitant 

use of the nicotine patch and smoking was not associated 

with an increase in adverse events. Although use of the 

patch was safe in this population, no improvement was 

observed in rates of short-term or long-term smoking 

abstinence in comparisons with the placebo group (Joseph 

et al. 1996; Joseph and Antonuccio 1999).

A third trial tested use of the nicotine patch in 106 

smokers with CHD (Tzivoni et al. 1998). Patients were 

randomly assigned to receive nicotine patches or placebo 

patches for two weeks. All patients had ambulatory electrocardiogram monitoring and exercise testing at study 

entry, after the first application of the patch, and at two 

weeks. No difference was observed at any of the three time 

points, between the patch and placebo groups, in resting 

heart rate, blood pressure, the number or duration of ischemic episodes, frequency of arrhythmias, exercise duration, or time to 1-mm depression of the ST segment on an 

electrocardiogram. In a randomized study of 234 patients 

with both cardiovascular and respiratory diseases, no 

increase in adverse events was observed in patients 

assigned to the nicotine patch or the placebo (Campbell 

et al. 1996).

In a case-control study, Kimmel and colleagues 

(2001) found no increased risk of a first MI with use of the 

nicotine patch in persons who stopped smoking or those 

who continued to smoke. Using a computerized database 

for general practice in the United Kingdom, Hubbard and 
Surgeon General’s Report

400 Chapter 6

colleagues (2005) studied the relative incidence of MI and 

stroke in four two-week periods before and after the first 

prescription for NRT. They found a progressive increase in 

risk in the 56 days after the first NRT prescription but no 

evidence of increased cardiovascular events or mortality 

in the 56 days after the NRT prescription.

Meine and colleagues (2005) addressed the safety 

of transdermal nicotine in the setting of acute CHD. 

These investigators analyzed data in the Duke University Cardiovascular Databank for 9,991 smokers who 

had cardiac catheterization after hospital admission for 

unstable angina or non-ST-segment MI. This retrospective 

observational study compared outcomes of patients who 

did or did not receive transdermal nicotine during hospitalization. The study identified 194 patients who had been 

treated with transdermal nicotine during the hospital 

stay. The investigators used a “propensity score analysis” 

to compare patients receiving transdermal nicotine with 

matched patients from the database who did not receive 

the medication. Because patients were not randomly 

assigned to receive transdermal nicotine, selection bias 

could have confounded these results. In an attempt to 

reduce this bias, patients who did or did not receive transdermal nicotine were matched on demographic characteristics, diagnosis, cardiac risk factors, and mean cardiac 

ejection fraction. Rates of cardiac outcomes in the two 

groups were compared. No differences in 7-day, 30-day, or 

one-year mortality rates were observed. Patients receiving 

transdermal nicotine were not more likely to have coronary artery bypass grafting or percutaneous transluminal 

coronary angioplasty during hospitalization. It was not 

possible to control for the dose of medication received, 

the amount of smoking before hospital admission, or 

relapse to smoking after hospitalization. These results 

provide some evidence that NRT was safe in the setting of 

acute CVD, but randomized controlled trials are needed to 

establish the safety of NRT in patients who have unstable 

cardiac disease.

Other studies examined markers of exposure to 

tobacco smoke related to cardiovascular risk as surrogate endpoints for cardiovascular events in clinical trials. 

There was no evidence that NRT raised blood pressure in 

any of the efficacy trials, but these trials typically excluded 

patients with poor control of hypertension. In one small 

trial of 30 smokers with or without hypertension, NRT 

increased mean arterial pressure in smokers with normal 

blood pressure but not in smokers who had hypertension 

(Tanus-Santos et al. 2001).

To date, two studies have tested the effect of NRT 

on coronary circulation in smokers with CHD. One study 

examined the size of defects in myocardial perfusion in 36 

patients with baseline CHD who were treated with nicotine 

patches (Mahmarian et al. 1997). Participants continued 

to smoke but at reduced levels. The researchers concluded 

that use of the patch, even with concomitant smoking and 

higher plasma levels of nicotine, resulted in reduction of 

exercise-induced ischemia in a comparison with baseline 

values. This finding suggested that components of tobacco 

smoke other than nicotine are responsible for impaired 

coronary blood flow. The second study investigated the 

effect of nicotine gum on coronary perfusion in former 

cigarette smokers having angiography (Nitenberg and 

Antony 1999). The findings demonstrated that the gum 

did not reduce the surface area of normal or diseased segments of the coronary artery. Other studies of the effects of 

smoking cessation on lipids and thrombosis reported 

improvements in these markers, even among smokers 

using NRT (Allen et al. 1994; Lúdvíksdóttir et al. 1999; 

Eliasson et al. 2001; Haustein et al. 2002).

In summary, despite anecdotal reports of cardiovascular events attributable to use of NRT, data from multiple 

clinical trials of smokers with or without CVD show no 

evidence for increased cardiovascular risk when NRT 

is used to treat tobacco dependence. However, the safety of NRT has not been tested in a more acute setting, 

such as during hospitalization for a cardiovascular event. 

Observational data suggest that use of the nicotine patch 

in patients with unstable cardiac disease is probably 

safe (Meine et al. 2005), but randomized trials are needed to confirm these findings. Current PHS guidelines 

recommend that NRT be used with caution in smokers 

with unstable angina, MI in the past two weeks, or serious 

arrhythmia (Fiore et al. 2000).

Bupropion

Bupropion is an aminoketone approved by FDA in 

1989 for treatment of depression and in 1997 for smoking 

cessation. The drug is included in national guidelines as 

first-line therapy for smoking cessation (Fiore et al. 2000, 

2008). Its mechanism of action is not fully understood, but 

researchers think it acts by inhibiting neuronal uptake of 

norepinephrine and dopamine. Bupropion may also block 

activity of nAChRs. The mechanism of action for smoking 

cessation appears to be unrelated to the antidepressant 

effects of bupropion. A preparation of the drug for sustained release provides a better safety profile and more 

convenient dosing than does the immediate-release form. 

Evidence from several randomized controlled trials shows that bupropion doubled the smoking cessation 

rates obtained with a placebo. Meta-analyses of data on 

bupropion for smoking cessation conducted by PHS and 

the Cochrane Library yielded ORs of 2.1 (95 percent CI, 

1.5–3.0) and 2.06 (95 percent CI, 1.77–2.40), respectively 

(Fiore et al. 2000; Hughes et al. 2004b). One trial compared use of bupropion, a nicotine patch, bupropion plus 
Cardiovascular Diseases 401

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

a patch, and a placebo among 893 participants (Jorenby 

et al. 1999). Smoking abstinence rates at one year were 

15.6 percent in the placebo group, 16.4 percent in the 

nicotine-patch group, 30.3 percent in the bupropion 

group (p <0.0001 versus the placebo group), and 35.5 

percent in the bupropion-plus-patch group (p <0.0001 

versus the placebo group; p = 0.06 versus the bupropionalone group). 

The major risk of bupropion is that it lowers a 

person’s seizure threshold. The risk of seizure from the 

sustained-release formulation is 0.1 percent, which is no 

different from that for other antidepressants (Hughes et 

al. 1999; Rigotti 2002). No seizures were reported in any of 

the clinical trials that tested sustained-release bupropion 

for smoking cessation.

As with NRT, early case reports of serious cardiovascular events with sustained-release bupropion raised 

questions about the safety of this agent in patients with 

CVD. These reports, which were mostly in Canada and 

England, included cardiac deaths, chest pain, MI, and 

myocarditis (Joseph and Fu 2003). Assessment of the contribution of bupropion to these events is difficult because 

evaluation of other cardiac risk factors in these patients was 

not possible.

To date, none of the efficacy trials of bupropion for 

smoking cessation has reported a significant increase 

in cardiovascular events. Two randomized controlled 

trials enrolled only smokers with CVD. The first trial 

enrolled 629 outpatients with stable CVD—that is, MI or an 

interventional cardiac procedure more than three months 

earlier and stable angina pectoris, PAD, or congestive 

heart failure (Tonstad et al. 2003). Patients were randomly 

assigned to receive bupropion or a placebo for seven weeks. 

This study found no differences in the number of deaths 

in the two groups—two in the bupropion group and two 

in the placebo group. Overall, 38 participants (6 percent) 

reported a single adverse cardiovascular event—24 in the 

bupropion group and 14 in the placebo group. The most 

common cardiovascular events were angina pectoris, 

hypertension, and palpitations; 13 events occurred in the 

bupropion group versus 8 events in the placebo group. 

No statistical tests were performed on the rates of adverse 

events. Patients who took bupropion were more likely to 

have stopped smoking at one year than were patients who 

took the placebo (27 versus 12 percent, p <0.001).

A second trial enrolled 248 smokers hospitalized 

with acute CVD, including acute MI, unstable angina, 

or other cardiovascular conditions (Rigotti et al. 2006). 

Patients were randomly assigned to receive sustainedrelease bupropion or a placebo for 12 weeks, and all 

patients received intensive counseling during hospitalization and follow-up. At the one-year follow-up, the difference between death rates in the bupropion group (no 

deaths) and in the placebo group (two deaths) was not 

statistically significant. During the 12 weeks of drug treatment, the difference between the number of cardiovascular 

events in the bupropion group (20 events) and the placebo 

group (17 events) was also not significant. Cardiovascular 

events included death, nonfatal MI, unstable angina, congestive heart failure, stroke, and coronary revascularization procedure. At the one-year follow-up, the number of 

cardiovascular events in the bupropion group (32 events, 

26 percent) exceeded the number in the placebo group 

(22 events, 18 percent), but this difference was not significant. In addition, at one year, the difference between the 

smoking abstinence rates for the bupropion group (25 

percent) versus the placebo group (21 percent) was not 

significant. However, the results after 12 weeks of drug 

treatment suggested that bupropion had short-term efficacy (37 versus 27 percent, p = 0.08). 

In summary, sustained-release bupropion is effective 

and safe for treating smokers with stable CVD. The drug 

appears to be less efficacious in smokers hospitalized with 

acute CVD than in other groups of patients. Bupropion is 

the only medication for treating tobacco dependence that 

has been tested in patients with acute CVD, and it appears 

to be safe for those with either stable or acute disease. 

Other Pharmacotherapy

Varenicline, a partial agonist of the α4β2 nAChR, 

has been marketed for the treatment of tobacco dependence but its use in smokers with CVD has not yet been 

studied (Coe et al. 2005). The drug produces approximately 50 percent of the receptor stimulation provided by nicotine, but it blocks the effects of any nicotine taken in from 

cigarette smoking. Clinical trials have found it superior 

to bupropion in promoting smoking cessation, and prolonged administration has been shown to reduce relapse 

in smokers who had been abstinent 12 weeks after initial 

therapy (Gonzalez et al. 2006; Jorenby et al. 2006; Tonstad 

et al. 2006). Two other medications have been demonstrated to be effective for smoking cessation: nortriptyline, a 

tricyclic antidepressant, and clonidine, a central α-agonist 

antihypertension agent. However, neither drug has been 

approved by FDA for smoking cessation. Both agents have 

potential cardiovascular side effects, and the safety profile 

of these drugs should be considered carefully before use in 

smokers with CVD. 

Meta-analyses of data on use of clonidine for treating smokers resulted in ORs for smoking abstinence of 

2.1 (95 percent CI, 1.4–3.2) (Fiore et al. 2000) and 1.89 

(95 percent CI, 1.30–2.74) (Gourlay et al. 2004). To date, 

no safety data for patients with CVD are available. However, clonidine is known to cause orthostatic hypotension, 

rebound hypertension from abrupt cessation of the drug, 
Surgeon General’s Report

402 Chapter 6

and rarely, atrioventricular nodal blockade. Nortriptyline 

is also effective in promoting smoking cessation; metaanalyses yielded ORs of 3.2 (95 percent CI, 1.8–5.7) (Fiore 

et al. 2000) and 2.79 (95 percent CI, 1.70–4.59) (Hughes 

et al. 2004b). Nortriptyline was designated a second-line 

drug for smoking cessation in PHS clinical guidelines 

because of a smaller evidence base of support and greater 

side effects than those of other medications for smoking 

cessation. In general, tricyclic antidepressants are avoided 

in patients with CVD because of concerns about increased 

risks for arrhythmias and depression of myocardial contractility (Joseph and Fu 2003).

Although the focus of the preceding section (“Methods”) was on clinical interventions to reduce smoking, it 

is important to recognize that policy-based interventions, 

such as smoke-free environments and community and 

statewide tobacco control programs, are also important 

elements in a strategy to improve cardiovascular health. 

For example, smoke-free workplaces are a highly costeffective approach to promoting smoking cessation with 

an impact on cardiovascular health (Ong and Glantz 2004). 

Decreases in admissions to hospitals have been observed 

after smoke-free laws have gone into effect (Dinno and 

Glantz 2007). The California Tobacco Control Program 

substantially accelerated the decline in the heart disease 

death rate in the state (Fichtenberg and Glantz 2000).

It should be noted that although long-term smoking quit rates after various interventions in cardiovascular 

patients may appear to be low (most less than 30 percent), 

smoking cessation therapy has an important impact on 

CVD, and the cost per life saved is lower than that of many 

other therapeutic interventions for CHD that are considered to be the standard (such as treatment of hypertension 

and hyperlipidemia) (Lightwood 2003).

Summary

Smoking cessation is a key element in both primary 

and secondary prevention of CVD. Guidelines from PHS 

recommend counseling, NRT, sustained-release bupropion, and varenicline as first-line treatments to achieve 

smoking cessation. Studies show that NRT and bupropion 

are effective in patients with CVD, although not all trials 

demonstrated efficacy. Several studies have demonstrated 

the safety of NRT in patients with stable CVD, but randomized trials are needed to establish the safety of this 

treatment for patients hospitalized with acute disease. 

Bupropion appears to be safe in patients with stable or 

unstable CVD, but it is less effective in patients with acute 

disease. Varenicline is a partial agonist of the α4β2 nAChR 

that is effective in treating tobacco dependence, but it has 

not yet been studied in smokers with CVD. The development of more effective pharmacotherapies to aid smoking cessation that are safe in persons with CVD is a high 

research priority.

Methods to Reduce Exposure

Evidence-based interventions for treating smokers include behavioral and pharmacological treatments, 

which significantly increase rates for long-term abstinence from smoking. Even so, absolute rates of abstinence 

are modest; they range from 8 to 25 percent, depending 

on the study population and the treatment. In addition, 

only a small proportion of smokers are interested in treatment at any given time. Interest in smoking cessation and 

success in achieving long-term abstinence are greater 

among patients with CVD than in the general population 

of smokers (Thomson and Rigotti 2003). Nevertheless, 

abstinence rates remain disappointingly low, particularly in light of the important health benefits for this 

population when they do stop smoking (USDHHS 1990; 

Burns 2003). 

Suboptimal treatment outcomes prompted interest in testing interventions that might decrease the risk 

of smoking among those who continue to use tobacco. 

These strategies are often termed “harm reduction” interventions, although data are limited as to whether harm is 

really lessened with reduced exposure to tobacco. To date, 

the effect of methods for reducing exposure on risk factors 

for CVD and on development of CVD has been evaluated 

in a limited number of clinical trials, prospective cohort 

studies, and epidemiologic studies.

Endpoints with respect to CVD that have been measured in studies of reduced exposure include measures of 

exposure to tobacco constituents (e.g., nicotine and CO); 

biomarkers of inflammation (e.g., CRP, leukocyte counts, 

and fibrinogen); thrombosis (e.g., fibrinogen and PAI-1); 

lipid abnormalities (e.g., levels of total cholesterol, HDLc, 

LDLc, triglycerides, APOs A-I and B, and HDLc to LDLc 

ratio); oxidative stress that reflects and may contribute 

to cardiovascular risk (e.g., F2-isoprostanes); and clinical 

outcomes (blood pressure, heart rate, angina, exercise tolerance, MI, other adverse events, and death) (Table 6.3). 
Cardiovascular Diseases 403

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Reduced Smoking

Important methodologic considerations in evaluating studies of reduced smoking include the extent and 

duration of smoking reduction, use of nicotine replacement products, doses, and timing of endpoint measurements (Table 6.6). In addition, some studies report 

outcome data on the basis of intention to treat all participants, regardless of whether treatment was successful. Others report only on subgroups who achieve specific 

goals for smoking reduction.

Eliasson and colleagues (2001) tested the effect of 

nicotine nasal spray on achieving smoking reduction and 

abstinence among 58 healthy adult smokers in an openlabel cohort study. The primary goal for the first eight weeks 

of the study was to reduce daily smoking by 50 percent; 

participants were asked to stop smoking after eight weeks. 

Cardiovascular risk factors were evaluated at baseline, at 

eight weeks, and after eight weeks of abstinence. The 33 

study participants provided data at all three time points. 

After participants completed eight weeks of smoking 

reduction, mean cigarette use decreased by 50.2 percent, 

expired CO dropped 17 percent, and plasma thiocyanate 

decreased by 20.1 percent. Significant improvements 

included fibrinogen levels (from 2.9 g/liter [L] to 2.65 

g/L, p = 0.011); hemoglobin values (from 13.8 to 13.3 

g/L, p <0.001); leukocyte counts (from 7.0 to 6.2 x 109/L, 

p = 0.005); and HDLc to LDLc ratio (from 0.33 to 0.37, 

p <0.005). Eight weeks of abstinence from smoking was 

associated with further improvements in hemoglobin levels, leukocyte counts, and HDL and LDL levels, and significant reduction in PAI-1 activity. These researchers did 

not observe improvements in HDLc and LDLc levels with 

reduction in smoking. 

Hurt and colleagues (2000) conducted a small, openlabel cohort study to test the effect of a nicotine inhaler 

on biomarkers of exposure to cigarette smoke among 23 

heavy smokers. Levels of blood thiocyanate, several urine 

carcinogens, and expired CO were measured at study entry 

and at 4, 8, 12, and 24 weeks. Despite an average reduction 

among participants from 40 or more to 10 cigarettes per 

day, expired CO decreased only from 30.4 to 26.0 parts per 

million (ppm), reflecting compensatory smoking or misreporting of reduction in smoking. This change was not 

statistically significant.

In the U.S. Lung Health Study, 5,887 male and 

female smokers were randomly assigned to one of three 

groups: intervention for smoking cessation, including 

nicotine gum, plus bronchodilator therapy; intervention 

plus a placebo; or usual care (Hughes et al. 2004a). Among 

3,923 participants in the intervention at the one-year 

follow-up, 1,722 continued to smoke daily. Reduction in 

the number of cigarettes smoked was not an objective of 

the intervention, but 16 percent of those who continued 

to smoke daily smoked 1 to 24 percent fewer cigarettes 

than at baseline; another 27 percent reduced smoking by 

25 to 49 percent; 19 percent, by 50 to 74 percent; and 11 

percent, by 75 to 99 percent. The mean reduction in cigarettes smoked was 29 percent (from 32 to 22 cigarettes 

per day), and the mean reduction in CO levels was 24 percent (from 34 to 26 ppm). Thus, more than 80 percent of 

those who did not stop smoking achieved some level of 

reduction. However, the reduction in CO was not as large 

as the reduction in cigarettes per day. This finding again 

suggests compensatory smoking.

Hatsukami and colleagues (2005) examined the 

effect of smoking reduction on cardiovascular risk factors among 151 cigarette smokers interested in stopping 

smoking but not in reducing their smoking. Nicotine 

patches and gum were used to assist with reduction of 

smoking. The cardiovascular risk factors (CO and cholesterol levels, leukocyte counts, blood pressure, and heart 

rate) were measured for 12 weeks after study entry. Biomarkers did not change among persons who continued to 

smoke ad libitum, but the 61 persons who reduced smoking achieved significant improvements. Smokers who 

reduced the self-reported number of cigarettes smoked per 

day by 40 percent or more had significantly reduced leukocyte counts (from 7.39 to 6.98 x 109/L, p <0.001); higher HDLc levels (from 50.3 to 52.8 mg per deciliter [dL], 

p <0.0167); improved HDL to LDL ratios (from 0.47 to 

0.49, p <0.0167); lower APO B levels (from 103.7 to 103.0 

mg/dL, p <0.0167); lower systolic blood pressure (from 

123.0 to 120.3 mm Hg, p <0.0167); and lower heart rate 

(from 75.7 to 70.2 beats per minute, p <0.001). Although 

some of these changes were statistically significant, they 

are modest, and the clinical importance is undetermined. 

Levels of triglycerides, total cholesterol, APO A-I, and 

diastolic blood pressure did not change, and LDLc levels 

increased from 122.1 to 124.4 mg/dL (p <0.0167). 

To date, only one randomized controlled trial of an 

intervention for smoking reduction among persons with 

known CVD has been conducted (Joseph et al. 2005). Treatment included behavioral counseling and NRT with patches and gum. The goal of this study of 152 participants was 

at least a 50-percent reduction in cigarettes smoked per 

day; usual care was the standard for comparison. At study 

entry, participants smoked an average of 27.4 cigarettes 

per day. At six months, the intervention group had reduced 

cigarette use by 39 percent, versus a decline of 25 percent 

in the usual care group, but this difference was not statistically significant. Biomarkers for carcinogenesis and CVD 

were measured, as were clinical outcomes. No significant 

differences between the treatment groups were observed 

for levels of CO, fibrinogen, F2-isoprostanes, or CRP, or 

for leukocyte counts. The groups did not differ in clinical 
Surgeon General’s Report

404 Chapter 6

outcomes, including body weight, distance completed in 

a six-minute walking test, the proportion of participants 

completing that test, the prevalence and frequency of 

angina, the need for urgent cardiac care, and other serious 

adverse events. Because no significant differences between 

treatment groups were observed and because both groups 

achieved significant reductions in cigarette use from baseline, results for the entire cohort at six months were compared with the baseline data. There were no significant 

differences in biomarkers of cardiovascular risk, including 

leukocyte counts and levels of F2-isoprostanes or CRP, but 

CO had decreased by 6.0 ppm (p = 0.007). 

Godtfredsen and colleagues (2003) conducted a prospective cohort study in Denmark to examine changes 

in the incidence of MI after spontaneous reductions in 

cigarette use. This study included 10,956 men and 8,467 

women who provided detailed information on smoking 

behavior during two examinations. Mortality registers and 

hospital registers were searched for an incident of hospital 

admission or a death attributable to MI. A sample consisting of pooled data from three population studies yielded 

643 participants who were heavy smokers at study entry 

and were evaluated for the effects of reduced smoking. 

These persons reported unassisted reductions in 

tobacco use by at least 50 percent and were compared 

Table 6.6 Smoking reduction and cardiovascular disease endpoints: biomarkers and clinical outcomes

               Reduction from baseline

Study Design n Follow-up NRT CPD Nicotine CO (ppm)

Hurt et al. 

2000

Open-label 

cohort

23 24 weeks Inhaler ≥40 to 10** -a NS

Eliasson et al. 

2001

Open-label 

cohort

33 9 weeks Nasal spray 21.5 to 10.8**; 

50.2%

- -

Godtfredsen et 

al. 2003

Prospective 

cohort study

643c Mean 13.8 

years

NA ≥50%d Significant 13.2 vs. 8.7***

Hughes et al. 

2004a

Reduction 

cohort in RCT

1,722 1 year Gum 32 to 22; 29% - NS

Hatsukami et 

al. 2005

Reduction 

cohort in RCT

61 12 weeks Patch and 

gum

24.16 to 6.93*; 

>40%

-

f 19.9 to 

6.77***

Joseph et al.h

2005

RCT 152 6 months Patch and 

gum

27.7 to 16.8* NS NS

Note: APO A-I = apolipoprotein A-I; APO B = apolipoprotein B; BP = blood pressure; CCSC = Canadian Cardiovascular Society 

classification; CO (ppm) = carbon monoxide (parts per million); CPD = cigarettes/day; Fibr = fibrinogen concentrations; 

g/L = grams per liter; Hb = hemoglobin; HDL = high-density lipoprotein; hs-CRP = high-sensitivity C-reactive protein; 

LDL = low-density lipoprotein; mg/dL = milligrams per deciliter; MI = myocardial infarction; n = number in sample (or study) 

population; NA = not applicable; NRT = nicotine replacement therapy; NS = not significant; PAI-1 = plasminogen activator 

inhibitor-1; Plts = platelets; RCT = reverse cholesterol transport; SAEs = serious adverse events; Trigly = triglycerides; 

WBC = white blood cells.
Cardiovascular Diseases 405

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

with 1,379 persons who reported abstinence from smoking. Outcomes were adjusted for baseline cardiovascular risk factors. Smoking cessation was associated with 

a hazard ratio for MI of 0.71 (95 percent CI, 0.59–0.85), 

but smoking reduction was not associated with a statistically significant reduction in risk of MI (hazard ratio, 

1.15 [95 percent CI, 0.94–1.40]). A subgroup analysis 

demonstrated significant reductions in levels of expired 

CO among persons who reduced cigarette smoking. The 

investigators concluded that the results were consistent with a short-term thrombogenic effect of tobacco 

exposure rather than with a cumulative effect of exposure. 

They speculated that an approximate 50-percent reduction (from 20 g to 10 g of tobacco smoked per day) was 

not sufficient to improve cardiovascular risk. These epidemiologic data make an important contribution because 

they are population based and come from a large cohort 

of smokers who reduced their smoking during a period 

longer than the usual timeframe for clinical trials. 

In summary, these studies show that a significant 

reduction in cigarette use, even to levels as low as 10 cigarettes per day, results in reduction of exposure to CO from 

tobacco smoke that is smaller than expected. This finding most likely reflects compensatory smoking. Some but 

   Reduction from baseline

Study Hb (g/L) WBC x 109/L

Fibr 

(g/L)

LDL 

(mg/dL) HDL (mg/dL) Other biomarkers Clinical outcomes

Hurt et al. 

2000

- - - - - - -

Eliasson et al. 

2001

13.8 to 

13.3**

7.0 to 6.2** 2.9 to 

2.6*

NSb NS Plts NS

PAI-1 NS

-

Godtfredsen 

et al. 2003

- - - -

e NS - Systolic BP NS

Diastolic BP 80.7 

vs. 78.8***

Risk of MI NS

Hughes et al. 

2004a

- - - - - - -

Hatsukami et 

al. 2005

14.49 to 

14.40*

7.39 to 

6.98***

- 122.14 

to 

124.36*g

50.27 to 52.82* Trigly NS

APO A-I NS

APO B 103.74 to 

103.0*

Systolic BP 122.97 

to 122.29*

Diastolic BP NS

Heart rate 75.7 to 

70.18***

Joseph et al.h

2005

NS NS NS - - hs-CRP NS

F2-isoprostanes 

NS

6-minute walk, 

angina presences/

frequency, CCSC 

classification, 

cardiac or other 

SAEs NS

aThiocyanate concentrations increased from 189 to 198 micromoles/L (p <0.05).

bHDL to LDL ratio increased from 0.33 to 0.37, p <0.005. 

cTotal cohort = 19,423.

d22.2 grams tobacco per day in continued heavy smokers versus 10.5 grams per day in reducers (p <0.001).

eTotal cholesterol NS.

f

Anatabine decreased from 4.69 to 3.02 nanograms per milligram of creatinine (statistically significant).

gHDL to LDL ratio increased from 0.47 to 0.49, p <0.0167.

hReduction in CPD reported for smoking reduction intervention group, significance tests reported for smoking reduction versus 

control group. 

*p <0.05, **p <0.01, ***p <0.001.
Surgeon General’s Report

406 Chapter 6

not all studies showed reduced exposure to nicotine, as 

well as improvements in values for hemoglobin, leukocyte 

counts, and fibrinogen and cholesterol levels. However, 

the improvements in values are relatively minor compared 

with those observed with abstinence from smoking. Many 

of these improvements occurred in study participants who 

were using NRT (see “Nicotine Replacement Therapy” 

below). None of the studies showed improvements in clinical outcomes of heart disease, consistent with evidence 

presented earlier that low levels of smoke exposure trigger many of the adverse cardiovascular effects of smoke 

(see “Exposure to Secondhand Tobacco Smoke” earlier in 

this chapter). 

Nicotine Replacement Therapy

In addition to providing data on smoking reduction, 

the Lung Health Study of 3,094 persons offered a unique 

opportunity to examine the natural history and safety of 

prolonged use of nicotine gum among thousands of people during a five-year follow-up (Murray et al. 1996). Persistent smoking, but not use of nicotine gum, predicted 

fatal and nonfatal cardiovascular events and elevation of 

diastolic blood pressure. 

In general, trials of smoking cessation and smoking 

reduction showed improvements in lipid profiles, even 

with NRT. Eliasson and colleagues (2001) observed that 

use of nicotine nasal spray for smoking reduction or cessation yielded significant improvements in HDLc to LDLc 

ratios at 9 weeks, with further improvements if smokers abstained from smoking for 17 weeks (see “Reduced 

Smoking” earlier in this chapter). In addition, significant 

improvements in fibrinogen levels and leukocyte counts 

were observed. A clinical trial of smoking cessation also 

reported significant decreases in hemoglobin values, leukocyte counts, and total and LDLc concentrations (Lúdvíksdóttir et al. 1999). In addition, HDLc to LDLc ratios 

improved among participants who abstained from smoking after three months of treatment with a nicotine nasal 

spray. Allen and colleagues (1994) also observed significantly increased HDLc levels in participants treated with 

the nicotine patch. 

Investigators have noted improvements in markers 

of thrombogenesis among persons who abstained from 

smoking and were using medicinal nicotine. In one study, 

plasma fibrinogen levels were reduced among 164 men 

using a combination of a nicotine patch and gum for 12 

weeks to stop smoking (Haustein et al. 2002). In another 

study, use of transdermal nicotine appeared to activate 

platelet aggregation less than smoking did (Benowitz et 

al. 1993). 

Mahmarian and colleagues (1997) used single photon emission computed tomography to measure the combined effects of smoking and use of nicotine patches on 

myocardial perfusion. In 36 patients with known CHD who 

were treated with nicotine patches, the amount of heart 

muscle deprived of normal blood flow (size of perfusion 

defects) decreased despite increased serum nicotine levels. The baseline size of defects and changes in CO levels, 

but not in nicotine levels, predicted the size of perfusion 

defects. The researchers concluded that the reduction in 

the size of defects resulted from reduction in smoking that 

was facilitated by NRT and from decreased exposure to CO. 

They also concluded that nicotine patches were safe to use 

in smokers with heart disease. 

Nitenberg and Antony (1999) used angiography to 

examine short-term effects of use of nicotine gum on perfusion of the coronary arteries in former cigarette smokers at study entry, after a test with immersion of the hand 

in cold water (cold pressor test) before and after administration of the gum. The gum did not augment the result 

of the cold pressor test, which constricted normal and 

diseased segments of the coronary artery, reducing their 

cross-sectional area, and it did not reduce the surface area 

of the arterial segments at rest or under conditions of 

sympathetic stimulation. 

These results suggest that reduction of exposure to 

tobacco smoke through use of NRT or with abstinence 

from smoking is associated with improvements in biomarkers of cardiovascular risk. 

Summary

Epidemiologic studies demonstrate a strong doseresponse relationship between the number of cigarettes 

smoked per day and cardiovascular risk. The relationship 

is not linear, however, and even low levels of exposure to 

tobacco, such as a few cigarettes per day, occasional smoking, or exposure to secondhand tobacco smoke are sufficient to substantially increase risk of cardiac events. Some 

interventions have accomplished significant reductions in 

the number of cigarettes smoked per day, but the reductions in levels of biomarkers of exposure and biomarkers of 

cardiovascular risk factors are not proportional, probably 

because of compensatory smoking by study participants 

and the nonlinear dose-response relationship. The limited 

data on clinical outcome do not confirm reduction in cardiovascular events due to reduced smoking. Other methods for reducing exposure, including NRT with abstinence 

from smoking, are associated with more improvement in 

risk factors for CVD than is smoking reduction with or 
Cardiovascular Diseases 407

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

without pharmacologic support. Accordingly, these methods hold more potential for reducing risk. 

Implications

These findings suggest that to lower cardiac risk, 

interventions would have to reduce exposure to tobacco 

smoke to extremely low levels or eliminate the exposure. 

Studies of smoking reduction to date suggest that goals 

would be difficult to accomplish. Reducing exposure by 

reducing smoking, therefore, appears to have limited 

promise for improving cardiac risk unless this method 

contributes to eventual smoking cessation (Hughes 2000).

Because smoking cessation is associated with marked 

improvements in the risk of MI, sudden death, and stroke, 

it should be stressed as the goal for interventions dealing with dependence on tobacco. The safety and efficacy of 

long-term NRT use to reduce cardiovascular risk by maintaining smoking cessation have not been established. 

Evidence Summary

Exposure to tobacco smoke is associated with accelerated atherosclerosis and an increased risk of acute MI, 

stroke, PAD, aortic aneurysm, and sudden death. Smoking appears to have both causal relationships and multiplicative interactions with other major risk factors for 

CHD, including hyperlipidemia, hypertension, and diabetes mellitus. 

The cardiovascular risk attributable to cigarette 

smoking increases sharply at low levels of cigarette consumption and with exposure to secondhand smoke. The 

risk then tends to plateau at higher levels of smoking. This 

finding indicates a low threshold for effect and a nonlinear 

dose-response relationship. Some of the nonlinearity of 

the relationship between the number of cigarettes smoked 

per day and CVD risk may be due to impreciseness of this 

measure of actual exposure to smoke. However, the data 

on risk associated with exposure to secondhand smoke 

indicate a true nonlinear relationship between exposure 

and CVD risk. Cardiovascular risk is not reduced by smoking cigarettes of lower machine-delivered yields of nicotine or tar. 

The constituents of tobacco smoke believed to be 

responsible for cardiovascular disease include oxidizing chemicals, nicotine, CO, and particulate matter. 

Oxidizing chemicals, including oxides of nitrogen and 

many free radicals, increase lipid peroxidation and contribute to several potential mechanisms of CVD, including 

inflammation, endothelial dysfunction, oxidation of LDL, 

and platelet activation. 

Nicotine is a sympathomimetic drug that increases 

heart rate and cardiac contractility, transiently increasing 

blood pressure and constricting coronary arteries. Nicotine may also contribute to endothelial dysfunction, insulin resistance, and lipid abnormalities. However, international epidemiologic evidence and data from clinical trials 

of nicotine patches suggest that chemicals other than nicotine contribute to an elevated risk of death from MI and 

stroke. CO reduces the delivery of oxygen to the heart and 

other tissues and can aggravate angina pectoris or PAD 

and can lower the threshold for arrhythmias in the presence of CHD. Exposure to particulates is associated with 

oxidant stress and cardiovascular autonomic disturbances 

that potentially contribute to acute cardiovascular events. 

Cigarette smoking causes acute cardiovascular 

events such as MI and sudden death by adversely affecting the balance of myocardial demand for oxygen and 

nutrients and coronary blood flow. Smoking results in 

increased myocardial work, reduced coronary blood flow, 

and enhanced thrombogenesis. Enhancement of thrombogenesis appears to be particularly important in that 

smokers with acute MI have less severe underlying coronary artery disease than do nonsmokers with MI, but 

smokers have a greater burden of thrombus.

Several potential mechanisms appear to contribute 

to the effects of smoking in accelerating atherosclerosis. 

These mechanisms include inflammation, endothelial 

dysfunction, impaired insulin sensitivity, and lipid abnormalities. Cigarette smoking is a risk factor for diabetes 

and aggravates insulin resistance in persons with diabetes. 

The mechanism appears to involve both the effects of oxidizing chemicals in the smoke and the sympathomimetic 

effects of nicotine. 
Surgeon General’s Report

408 Chapter 6

Conclusions

1. There is a nonlinear dose response between exposure to tobacco smoke and cardiovascular risk, with 

a sharp increase at low levels of exposure (including 

exposures from secondhand smoke or infrequent 

cigarette smoking) and a shallower dose-response 

relationship as the number of cigarettes smoked per 

day increases.

2. Cigarette smoking leads to endothelial injury 

and dysfunction in both coronary and peripheral 

arteries. There is consistent evidence that oxidizing 

chemicals and nicotine are responsible for endothelial dysfunction.

3. Tobacco smoke exposure leads to an increased risk 

of thrombosis, a major factor in the pathogenesis of 

smoking-induced cardiovascular events.

4. Cigarette smoking produces a chronic inflammatory state that contributes to the atherogenic disease 

processes and elevates levels of biomarkers of inflammation, known powerful predictors of cardiovascular events.

5. Cigarette smoking produces an atherogenic lipid profile, primarily due to an increase in triglycerides and a 

decrease in high-density lipoprotein cholesterol.

6. Smoking cessation reduces the risk of cardiovascular 

morbidity and mortality for smokers with or without 

coronary heart disease.

7. The use of nicotine or other medications to facilitate 

smoking cessation in people with known cardiovascular disease produces far less risk than the risk of 

continued smoking.

8. The evidence to date does not establish that a reduction of cigarette consumption (that is, smoking fewer 

cigarettes per day) reduces the risks of cardiovascular disease.

9. Cigarette smoking produces insulin resistance and 

chronic inflammation, which can accelerate macrovascular and microvascular complications, including 

nephropathy.
Cardiovascular Diseases 409

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Cardiovascular Diseases 434a

Data table for Figure 6.1 Relative risk and excess death rate for coronary heart disease among men, by age group

Age group (years) Relative Risk Excess Death Rate

35-39 3.3 20.5

40-44 6.3 70.7

45-49 5.5 119.8

50-54 3.8 156.6

55-59 2.7 204.1

60-64 2.4 317.3

64-69 1.9 366.7

70-74 1.7 473.2

75-79 1.4 439.6

 80+ 1.4 825.7

Data table for Figure 6.2 age-specific excess death rates among male smokers for coronary heart disease, lung cancer, chronic obstructive pulmonary disease (COPD), and cerebrovascular disease

Age group (years) Lung Cancer Coronary Heart Disease

Cerebro-Vascular 

Disease COPD

35-39 1.4 20.5 11.9   

40-44 18.7 70.7 0.2   

45-49 35.5 119.8 16.3 3.2

50-54 109.9 156.6 19.0 11.1

55-59 200.8 204.1 29.0 19.9

60-64 349.5 317.3 49.8 40.3

64-69 560.1 366.7 81.4 140.5

70-74 874.1 473.2 108.2 234.5

75-79 1066.3 439.6 252.8 522.0

 80+ 1138.6 825.7 264.8 722.0

435

Chapter 7

Pulmonary Diseases

Introduction 437

Characteristics of Tobacco Smoke 438

Dosimetry of Tobacco Smoke in the Respiratory System 439

Major Pulmonary Diseases Caused by Smoking 440

Chronic Bronchitis 441

Chronic Obstructive Pulmonary Disease 443

Obstruction of Small Airways 444

Emphysema 445

Centrilobular and Panacinar Forms of Emphysema 446

Other Forms of Emphysema 447

Pulmonary Hypertension 447

Smoking and Respiratory Defense Mechanisms 450

Infiltration of Innate Inflammatory Immune Cells 451

Adaptive Immune Response 452

Tissue Remodeling 453

Summary 456

Oxidative Stress 457

Generation of Reactive Oxygen Species 457

Antioxidants in Lungs 459

Enzyme Antioxidants 459

Nonenzymatic Antioxidants 461

Oxidants and Cigarette Smoke 462

Cell-Derived Oxidants 462

Assessment of Oxidative Stress 463

Evidence of Smoking-Induced Oxidative Stress 463

In Vitro Studies 463

Animal Studies 465

Consequences of Smoke-Induced Oxidative Stress 465

Epithelial Injury 465

Inflammatory Responses 465

Susceptible Animal Models 465

Human Studies 467

Summary 470

Oxidative Stress in Chronic Obstructive Pulmonary Disease 471

Pathogenesis of Chronic Obstructive Pulmonary Disease 471

Protease-Antiprotease Imbalance 472

Hypersecretion of Mucus 472

Lung Inflammation 472

Apoptosis 473

Systemic Involvement 473

Summary 474
436

Genetics of Pulmonary Disease and Susceptibility to Tobacco Smoke 475

α1-Antitrypsin Deficiency 475

Genetic Etiology 475

Natural History 476

Familial Aggregation of Phenotypes Related to Chronic Obstructive Pulmonary Disease 476

Pulmonary Function in the General Population 476

Airflow Obstruction 477

Chronic Bronchitis 477

Linkage Analysis of Phenotypes Related to Chronic Obstructive Pulmonary Disease 477

Chronic Obstructive Pulmonary Disease in Families 479

Genetic Association with Chronic Obstructive Pulmonary Disease 479

Mouse Models of Genetics for Chronic Obstructive Pulmonary Disease 486

Summary 487

Pathogenesis of Emphysema 487

Sources of Information 487

Introduction 487

Proteases 489

Data from Human Studies 489

Therapy to Control Proteases 491

Data from Animal Models 491

Models of Emphysema Involving Cigarette Smoke 492

Antiprotease Therapy for Experimental Smoke-Induced Emphysema 493

Apoptosis 493

Summary 494

Summary 494

Evidence Summary 494

Oxidative Stress 494

Genetic Susceptibility to Cigarette Smoke 495

Protease-Antiprotease Imbalance 495

Conclusions 496

Implications 496

References 497
Pulmonary Diseases 437

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Introduction

The respiratory system extends from the nose and 

upper airway to the alveolar surface of the lungs, where 

gas exchange occurs. Inhaled tobacco smoke moves from 

the mouth through the upper airway, ultimately reaching the alveoli. As the smoke moves more deeply into the 

respiratory tract, more soluble gases are adsorbed and 

particles are deposited in the airways and alveoli. The substantial doses of carcinogens and toxins delivered to these 

sites place smokers at risk for malignant and nonmalignant diseases involving all components of the respiratory 

tract including the mouth.

Consider, for example, the lungs of a 60-year-old 

person with a 40-pack-year1 smoking history starting at 

age 20 years. By age 60 years, this person will have inhaled 

the smoke from approximately 290,000 cigarettes and will 

bear a substantial risk for chronic obstructive pulmonary 

disease (COPD) and lung cancer. The dose of inhaled toxic 

particles and gases received from each of these cigarettes 

varies depending on the nature of the tobacco, the volume 

and number of puffs of smoke drawn from the cigarette, 

the amount of air drawn in through ventilation holes as 

the smoke is inhaled, and local characteristics within the 

lung that determine the diffusion of toxic gases and the 

deposition of particles. Because of this repetitive and sustained injurious stimulus, the repair and remodel process 

that heals the damaged lung tissue takes place at the same 

time the lung’s defenses continue to deal with this unrelenting inhalation injury.

This chapter addresses the mechanisms by which 

tobacco smoke causes diseases other than cancer in the 

lower respiratory tract: the trachea, bronchi, and lungs. 

Beginning with the first Surgeon General’s report in 

1964 (U.S. Department of Health, Education, and Welfare 

[USDHEW] 1964), cigarette smoking has been causally linked to multiple diseases and to other adverse 

effects on the respiratory system (Table 7.1). In addition 

to causing lung cancer and COPD, smoking increases the 

risk of death from pneumonia and causes chronic bronchitis (U.S. Department of Health and Human Services 

[USDHHS] 2004). Typically, the lungs of smokers show 

evidence of diffuse changes affecting the lining of the airways, the epithelium, and the structure of the bronchioles, which are the smaller air-conducting tubes.

Previous reports of the Surgeon General have also 

addressed the effects of smoking on the respiratory tract. 

In discussing the plausibility of associations of cigarette 

smoke with chronic bronchitis and emphysema, the 1964 

report gave full consideration to the nature of tobacco 

smoke and its effects on the respiratory tract (USDHEW 

1964). That report concluded that cigarette smoking “...

is the most important of the causes of chronic bronchitis 

in the United States...” (p. 302) and that “a relationship 

exists between pulmonary emphysema and cigarette 

smoking, but it has not been established that the relationship is causal” (p. 302). The 1984 report, which focused 

on COPD, covered mechanisms by which smoking affects 

the lung’s structure and function and the deposition and 

toxicity of cigarette smoke in the lung (USDHHS 1984). 

The report concluded that “cigarette smoking is the 

major cause of chronic obstructive lung disease in the 

United States...” (p. vii). The mechanisms of lung injury were considered further in the 1990, 2004, and 2006 

reports (USDHHS 1990, 2004, 2006). 

The principal nonmalignant respiratory diseases 

caused by cigarette smoking—COPD, emphysema, chronic bronchitis, and asthma—are defined in Table 7.2. The 

definitions indicate that chronic bronchitis is a specific set 

of symptoms, whereas emphysema refers to a particular 

pattern of lung damage. COPD comprises a clinical syndrome characterized by limitation in airflow; persons with 

COPD often have chronic bronchitis as well, and their 

lungs typically display emphysema. Other nonmalignant 

respiratory diseases that have been linked to smoking 

include asthma and idiopathic pulmonary fibrosis 

(USDHHS 2004), but the evidence has not reached a level 

of certainty sufficient to warrant a conclusion of cause 

and effect.

The nonmalignant respiratory diseases caused by 

smoking contribute substantially to the burden of morbidity and mortality attributable to smoking in the United 

States (Table 7.1). In 2005, the Centers for Disease Control and Prevention (CDC) estimated that an average of 

123,836 deaths per year could be attributed to lung cancer 

caused by smoking for the period 1997–2001 (CDC 2005). 

CDC estimated an additional 90,582 deaths from COPD 

and 10,872 from pneumonia and influenza annually.

Great advances have been made in our understanding of how smoking causes these diseases. Research has 

been facilitated by methods that directly assess changes 

in the lungs. Methods for obtaining biologic material from human lungs include bronchoalveolar lavage 

(BAL), a technique that allows recovery of cellular and 

1Pack-years = the number of years of smoking multiplied by the number of packs of cigarettes smoked per day.
Surgeon General’s Report

438 Chapter 7

noncellular components of the epithelial surface of the lower 

respiratory tract (Cantrell et al. 1973; Hunninghake et 

al. 1979; Reynolds 1987). BAL is of value in the study of 

immune and inflammatory mechanisms in the lower airways, because most of the cells recovered are believed to be 

derived from both air spaces and lung interstitium. Lung 

tissue obtained by biopsy or autopsy procedures can be 

used for cellular, protein, and nucleic acid assays. Exhaled 

breath condensate provides information about the composition of epithelial lining fluid (ELF) that can be used 

to detect inflammation and redox disturbance (Paredi et 

al. 2002). Blood samples may be used to assess systemic 

inflammatory responses, and blood cells serve as a source 

of nucleic acids.

Table 7.1 Causal conclusions on smoking and diseases of the respiratory tract other than lung cancer: the 2004 

and 2006 reports of the Surgeon General

Active Smoking

The evidence is sufficient to infer a causal conclusion between smoking and

	 •	 Acute respiratory illnesses, including pneumonia, in persons without underlying smoking-related chronic obstructive lung

disease 

	 •	 Impaired lung growth during childhood and adolescence

	 •	 Early onset of decline in lung function (during late adolescence and early adulthood)

	 •	 A premature onset of and an accelerated age-related decline in respiratory symptoms related to lung function in children and

adolescents, including coughing, phlegm, wheezing, and dyspnea

	 •	 Asthma-related symptoms (i.e., wheezing) in childhood and adolescence

	 •	 All major respiratory symptoms among adults, including coughing, phlegm, wheezing, and dyspnea

	 •	 Poor asthma control

	 •	 Chronic obstructive pulmonary disease morbidity and mortality

	 •	 A reduction of lung function in infants of mothers who smoked during pregnancy

Involuntary Exposure to Tobacco Smoke

The evidence is sufficient to infer a causal conclusion between secondhand smoke exposure 

From parental smoking and

	 •	 Lower respiratory illnesses in infants and children

	 •	 Middle ear disease in children, including acute and recurrent otitis media and chronic middle ear effusion

	 •	 Cough, phlegm, wheeze, and breathlessness among children of school age

	 •	 Ever having asthma among children of school age

	 •	 Onset of wheeze illnesses in early childhood

From maternal smoking during pregnancy and

	 •	 Persistent adverse effects on lung function across childhood

After birth and

	 •	 Lower level of lung function during childhood

And

	 •	 Odor annoyance

	 •	 Nasal irritation

Source: U.S. Department of Health and Human Services 2004, 2006.

Characteristics of Tobacco Smoke

Tobacco smoke, which comprises an aerosol (a mixture of solid and liquid particles) and gases, has thousands 

of chemical components, including many well-characterized toxins and carcinogens (International Agency for 

Research on Cancer [IARC] 2004). Many of these components are in the gas phase, and others are components of 

the particles. Nicotine, for example, is bound to particles in 

mainstream smoke. The chemical components in tobacco 

smoke were covered comprehensively in IARC Monograph 

83 (IARC 2004) and described in previous reports of the 

Surgeon General. Numerous components of the smoke 

have the potential to injure the airways and alveoli. 
Pulmonary Diseases 439

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Table 7.2 Definitions for principal nonmalignant respiratory diseases caused by cigarette smoking

Chronic obstructive 

pulmonary disease (COPD)

A preventable and treatable disease characterized by airflow limitation that is not fully reversible. 

The limitation is usually progressive and is associated with an abnormal inflammatory response 

of the lungs to noxious particles or gases, primarily caused by cigarette smoking. Although COPD 

affects the lungs, it also produces significant systemic consequences. 

Emphysema Permanent enlargement of the airspaces distal to the terminal bronchioles, accompanied by 

destruction of their walls and without obvious fibrosis. In patients with COPD, either condition 

may be present. However, the relative contribution of each to the disease process is often difficult 

to discern. 

Chronic bronchitis Chronic productive cough for 3 months in each of 2 successive years in a patient in whom other 

causes of productive chronic cough have been excluded. 

Asthma A chronic inflammatory disease of the airways in which many cell types play a role—in particular, 

mast cells, eosinophils, and T lymphocytes. In susceptible persons, the inflammation causes 

recurrent episodes of wheezing, breathlessness, chest tightness, and cough, particularly at night 

and/or in the early morning. These symptoms are usually associated with widespread and variable 

airflow obstruction that is at least partly reversible either spontaneously or with treatment. The 

inflammation also causes an associated increase in airway responsiveness to a variety of stimuli. 

Source: American Thoracic Society 2000 and American Thoracic Society/European Respiratory Society Task Force 2005.

Components of tobacco smoke with the potential 

to injure the lungs through a variety of mechanisms are 

listed in Table 7.3. Some components adversely affect host 

defenses; others act through specific or nonspecific mechanisms. Notably, cigarette smoking has very strong oxidant potential in that both the gas and tar phases contain 

high concentrations of free radicals (Repine et al. 1997). 

Many of the components of cigarette smoke are the targets 

of regulations because of their toxic effects: these include 

nitrogen dioxide, carbon monoxide, and various metals. 

For information on the toxic effects of components, see 

reports of the U.S. Environmental Protection Agency 

(EPA) and other agencies (USEPA 1993, 2000; USDHHS 

2000) and standard resources in toxicology (Gardner et al. 

2000; Klaassen 2001). 

Assessment of toxic effects of cigarette smoke in the 

respiratory tract requires consideration of the complexity 

of the mixture inhaled and the possibility of synergistic 

interactions among its many components. Although it 

is little studied, the possibility of numerous interactions 

has great plausibility because of the myriad components 

of cigarette smoke and the interlocking pathways of 

lung injury.

Table 7.3 Selected components of cigarette smoke 

and potential mechanisms of injury

Component Mechanism

Acrolein Cilia toxic; impairs lung defenses

Formaldehyde Cilia toxic; irritant

Nitrogen oxides Oxidant activity

Cadmium Oxidative injury; promotion of 

emphysema

Hydrogen cyanide Oxidative metabolism of cells 

affected

Dosimetry of Tobacco Smoke 

in the Respiratory System

To protect the lungs from injury, the respiratory 

tract has an elegant set of mechanisms for handling the 

particles and gases in inhaled air (Figure 7.1). These 

defenses include physical barriers, reflexes and the cough 

response, the sorptive capacity of the epithelial lining, 

the mucociliary apparatus, alveolar macrophages, and 

immune responses of the lung (Schulz et al. 2000). These 

defenses are critical because of the substantial volume of 

air inhaled daily: about 10,000 liters per day are inhaled 

by an adult. Even harmful substances present at low 

concentrations may eventually achieve a toxic dose after 

sustained exposure. In addition, high-level exposures, 

particularly when sustained, may overwhelm the lung’s 

defenses, and some agents have the potential to reduce the 

efficacy of these defenses. Cigarette smoke, for example, 
Surgeon General’s Report

440 Chapter 7

Figure 7.1 Lung defenses

Host Defenses

Nasal hair

Convoluted

passages of

sinuses

Coughing,

sneezing,

swallowing

Mucociliary cells

Normal flora

Inflammatory

cells

Alveolar

macrophages

Source: Cook 2000. Reprinted with permission from Elsevier Health, © 2000.

contains components that impair mucociliary clearance 

(Table 7.3).

The size of particles in the smoke inhaled directly 

from a cigarette (mainstream smoke) has been studied 

in a variety of systems. These studies indicate that the 

mass median aerodynamic diameter of particles is 0.3 to 

0.4 micrometers (μm) (Martonen 1992; Bernstein 2004). 

Particles of this size penetrate to and are deposited in the 

deep lung. 

The handling of particles by the lung’s defense 

mechanisms depends on their size (Figure 7.2). Large particles (e.g., many pollens and road dust) are removed in 

the upper airway, largely by impaction (USDHHS 1984). 

Small particles, with a mean aerodynamic diameter less 

than about 2.5 μm, reach the lungs, where they deposit 

in airways and alveoli by impaction, sedimentation, or diffusion. About 60 percent of the particles inhaled in mainstream smoke are deposited. Although these particles are 

subject to handling by the mucociliary apparatus and 

alveolar macrophages, removal is not complete because 

of their very high numbers in the lungs of long-term 

smokers, which show evidence of a substantial burden of 

retained particles. Similarly, evidence shows that smokers 

clear these particles at a reduced rate (Cohen et al. 1979; 

USDHHS 1984; Kreyling and Scheuch 2000). 

The removal of gases in the respiratory tract is 

accomplished through sorption by the liquid that lines 

the epithelial layer (Kreyling and Scheuch 2000). Both the 

site and the efficacy of removal of gases depend on the solubility of the gas. Highly soluble gases are removed high 

in the respiratory tract, but insoluble gases (e.g., carbon 

monoxide) may reach the alveoli and diffuse across the 

alveolar-capillary membrane. These dosimetric considerations indicate a high potential for lung injury in active 

smokers, who inhale a rich mixture of gases and particles 

that penetrates throughout the lungs, with deposit of particles and sorption of gases in the two anatomic sites most 

critical to respiration, the airways and alveoli.

Major Pulmonary Diseases Caused 

by Smoking

This section provides a brief overview of the principal diseases of the lung that are caused by smoking. A 

brief description of pathophysiology and pathogenesis is 

provided as background for the more comprehensive discussions of mechanisms. These topics are covered in great 

detail elsewhere (Mason et al. 2005) and were addressed in 

the 1984 and 2004 Surgeon General’s reports (USDHHS 

1984, 2004).
Pulmonary Diseases 441

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Figure 7.2 Fractional deposition of inhaled particles in the human respiratory tract

Source: Oberdörster et al. 2005. Reprinted with permission from Environmental Health Perspectives, © 2005. Figure based on data 

from the International Commission on Radiological Protection 1994. Drawing courtesy of Dr. Jack R. Harkema, Michigan State 

University. 

Note: μm = micrometers.

Chronic Bronchitis

The symptom complex of chronic bronchitis has 

been investigated for decades. In the 1950s, the British 

Medical Research Council suggested that a diagnosis of 

chronic bronchitis was warranted when the symptoms of 

chronic cough and production of sputum were present on 

most days of the month for at least three months in two 

consecutive years without any other explanation (BMJ

1965). This proposal is reflected in the current definition 

of chronic bronchitis (Table 7.2). Earlier, Reid (1960) had 

used the size of the mucous gland layer as a predictor for 

the postmortem diagnosis of this condition but did not 

implicate the inflammatory process in the pathogenesis 

of either enlargement of the gland or the production of 

excess mucus. Subsequent studies of lung tissue surgically removed from cancer patients (Figure 7.3) have shown 

that the symptoms of chronic bronchitis are associated 

with an inflammatory response involving the mucosal 

surface, submucosal glands, and gland ducts, particularly 

in the small bronchi that are 2 to 4 millimeters (mm) in 

diameter (Mullen et al. 1985; Saetta et al. 1997). In addition, longitudinal studies of chronic bronchitis in persons 

with normal lung function have clarified that its presence does not predict future progression to more severe 

obstructive lung disease (Fletcher et al. 1976; Saetta et 

al. 1997). Presence of chronic bronchitis in persons who 

already have limited airflow, however, is predictive of a 

more rapid decline in lung function and a higher risk of 

hospitalization than are seen with a similar limitation of 

airflow but no chronic bronchitis (Saetta et al. 1997). 

The inflammatory immune cells that infiltrate 

the epithelium, subepithelium, and glandular tissue in 

chronic bronchitis include the polymorphonuclear neutrophils (PMNs), macrophages, CD8-positive (CD8+) and 
Surgeon General’s Report

442 Chapter 7

CD4-positive (CD4+) T lymphocytes, and B cells that are 

part of the adaptive inflammatory immune process (Di 

Stefano et al. 1996; O’Shaughnessy et al. 1997; Saetta 

et al. 1997). This chronic inflammation, consisting of 

enlargement of the mucous glands and remodeling of the 

walls of both large and small bronchi reflects a deregulated healing process in tissue persistently damaged by 

the inhalation of tobacco smoke (Hogg 2004). The consequences of this process include both the development of a 

chronic cough and the accumulation of excess mucus in 

the airway’s lumen. However, this inflammatory process 

has little influence on airflow limitation unless it extends 

to the small conducting airways that account for much of 

the increase in airway resistance in COPD. 

Studies reported from the laboratory of Snider and 

associates in Israel (Breuer et al. 1993) were the first to 

show that elastase from PMNs was an important agent for 

the secretion of mucus by epithelial goblet cells. Later, 

Nadel (2001) and other investigators (Takeyama et al. 

1999, 2000, 2001a,b; Burgel et al. 2000; Lee et al. 2000; 

Kohri et al. 2002) extended these observations by linking the PMN-induced production of mucin to stimulation of EGFR. They showed that PMN elastase triggered 

the cleavage of membrane-tethered transforming growth 

factor alpha (TGFα), allowing it to attach to the external 

binding site of EGFR. This step is followed by phosphorylation of the intracellular component of this receptor and 

stimulation of downstream signaling pathways that activate the expression of the MUC5AC gene and lead to the 

production of mucus (Takeyama et al. 1999). This type of 

experiment established that EGFR and its ligands provide 

a regulatory axis for the production of mucin that involves 

several membrane-bound ligands of EGFR, such as TGFα

and heparin-binding EGF. Nadel (2001) has also shown 

that reactive oxygen species (ROS) can bypass the extracellular sphere of influence of this regulatory axis. Other 

studies have shown that ROS can directly activate EGFR’s 

intracellular domain (Burgel et al. 2000; Takeyama et al. 

2000; Kohri et al. 2002).

Figure 7.3 Comparison of normal bronchial gland (A) with enlarged bronchial glands (B and C) from a patient with 

chronic bronchitis

Source: Hogg 2004. Reprinted with permission from Elsevier, © 2004.

Note: (A) Histology of bronchus with epithelial lining that extends from lumen into gland duct and gland. (B) Enlarged glands from a

patient with chronic bronchitis. (C) One of these glands at higher magnification showing inflammatory cells (arrow and arrowhead). 

Several studies of human lungs showed that the symptoms of chronic bronchitis were associated with an inflammatory response 

involving the mucosal surface, submucosal glands, and gland ducts, particularly in the smaller bronchi 2–4 millimeters in diameter.
Pulmonary Diseases 443

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

More recent work in transgenic mice has found that 

overexpression of epithelial sodium ion channels resulted 

in excess reabsorption of epithelial sodium and volume 

depletion of periciliary fluid (Mall et al. 2004). The depletion of the periciliary fluid layer interferes with the frequency of ciliary beats and results in decreased clearance 

and adherence of mucus to the airway surface. Results of 

this study showed that depletion of the periciliary fluid 

in animals is associated with the accumulation of mucus 

in the lumen of both large and small airways, leading to 

greater susceptibility to infection of the lower respiratory 

tract and early death. 

Chronic Obstructive Pulmonary Disease

The hallmark of COPD is chronic airflow obstruction 

demonstrated with spirometry and the accompanying 

dyspnea and limitation of activity. Maximum expiratory 

flow is determined by the product of the resistance to flow 

in the small conducting airways (centimeters of water 

[H2O] per liter per second) and the elastic recoil of the 

lung parenchyma that drives expiratory flow (liters per 

centimeter of H2O). The product of these two variables, 

the time constant, characterizes the rapidity with which 

the lung fills and empties during respiration. Surprisingly, 

the time constant of the lung remains stable over a wide 

range of breathing frequencies in healthy lungs, but if disease increases either the compliance as in emphysema or 

the resistance as in obstruction of small airways, the time 

required to empty the lung is prolonged (Otis et al. 1956). 

The presence of a fixed limitation in airflow can be diagnosed by using a spirometer to measure the volume of air 

that can be forcibly expired from the lungs in one second 

(forced expiratory volume [FEV1]) and then determining its ratio to forced vital capacity (FEV1/FVC) after the 

administration of a bronchodilator. 

The classic cohort study of the natural history of 

chronic bronchitis and emphysema performed by Fletcher and colleagues (Lancet 1965; Fletcher 1976) used this 

type of measurement to test the hypothesis of a sequence 

beginning with tobacco smoking and then moving to 

symptoms of chronic bronchitis or recurrent chest infections and, finally, chronic limitation of airflow. The natural history of the decline in FEV developed by Fletcher and 

colleagues (1976) to summarize findings of a six-year longitudinal study of men working in West London is illustrated in Figure 7.4. Subsequent studies have confirmed 

these findings (USDHHS 1984). The horizontal lines 

added to the Fletcher diagram indicate the boundaries of 

the five-stage classification of the severity of COPD by the 

Global Initiative for Chronic Obstructive Lung Disease 

(GOLD). The measurements used were FEV1 and FEV1/

FVC (Pauwels et al. 2001; GOLD 2006). According to this 

classification, GOLD stage 0 defines persons with a normal 

FEV1 and FEV1/FVC who have symptoms attributable to 

significant exposure to tobacco smoke as being at risk for 

developing COPD. Those with mild, moderate, severe, or 

very severe COPD are placed in GOLD stages 1 through 4, 

respectively (Takeyama 2001b). 

Fletcher and colleagues (1976) observed that only 

15 to 25 percent of the smokers in the study developed airflow limitation, and they showed that smoking cessation 

slowed the rate of decline in FEV1 in those who stopped 

smoking permanently. In subsequent studies of various 

populations, only a minority of smokers developed COPD. 

This repeated finding indicates a role for genetic factors 

that may determine susceptibility to cigarette smoke. 

These investigators rejected the hypothesis of a pathogenetic continuum from smoking to obstructive bronchitis. 

Most persons who developed airflow limitation during the 

study had no evidence of chronic bronchitis, a finding that 

was not consistent with the hypothesis of a continuum 

from smoking to bronchitis to obstruction. Subsequent 

studies have confirmed that the presence of chronic bronchitis in persons with normal lung function (GOLD stage 

0) does not predict progression of disease (Vestbo and 

Lange 2002). Using data from the Copenhagen City Heart 

Study, however, Vestbo and colleagues (1996) found that 

the symptoms of chronic bronchitis were associated with 

an accelerated decline in FEV1. 

Acute exacerbations, a concern in treatment of 

COPD, are attributed to viral infections (Monto et al. 

1975; Smith et al. 1980; Seemungal et al. 2001), bacterial infections, and occupational and environmental air 

pollution; an important residual of cases had no obvious cause (Pauwels et al. 2001; Rabe et al. 2007). Some 

unexplained exacerbations of COPD might be attributable to latent viral infection, because such infections can 

deregulate the expression of adhesion proteins that might 

initiate this response (Gonzáles et al. 1996; Keicho et al. 

1997). Although Fletcher and colleagues (1976) found 

that these exacerbations had no effect on the rate of 

decline of FEV1 in the working men in West London, the 

U.S. Lung Health Study showed that such exacerbations 

were associated with a more rapid decline in persons with 

mild disease who continued to smoke (Kanner et al. 2001). 

Subsequently, other investigators found that frequent 

exacerbations in patients with more severe COPD, especially those resulting from a higher bacterial load, were 

associated with more accelerated decline in FEV1 (Donaldson et al. 2002; Wilkinson et al. 2003). Collectively, these 

data suggest that when lung defenses become compromised in the later stages of COPD, chronic infection might 

play a role in the pathogenesis of the airflow limitation. 
Surgeon General’s Report

444 Chapter 7

Obstruction of Small Airways

Although spirometric measurement of FEV1 and 

the FEV1/FVC provides a reliable method for diagnosing 

airflow limitation and classifying its severity, spirometry cannot distinguish the contributions of either the 

obstruction of small airways or emphysematous destruction to the airflow limitation in COPD. Direct measurements of pressures and flows within the lung have shown 

that the small bronchi and bronchioles (<2 mm in diameter) are the major sites of airway obstruction in COPD 

(Hogg et al. 1968; van Brabandt et al. 1983; Yanai et al. 

1992). This obstruction is related to an inflammatory process that thickens the airway wall, fills the lumen with 

exudates containing mucus, and narrows the airway by 

depositing connective tissue in the airway wall (Figure 7.5). 

McLean (1956) and Leopold and Gough (1957) recognized 

that an inflammatory process was present in the small 

bronchi and bronchioles of lungs affected by centrilobular 

emphysema. Leopold and Gough (1957) hypothesized that 

centrilobular emphysema resulted from an extension of 

this process from the small conducting airways into the 

respiratory bronchioles. Later, Matsuba and Thurlbeck 

(1972) demonstrated an excess deposition of connective 

tissue in the adventitia of the small conducting airways in 

advanced emphysema and suggested that peribronchiolar 

fibrosis narrowed the airway lumen. In addition, crosssectional studies of the pathology of COPD have shown 

that the peripheral inflammatory immune process found 

in the lungs of all smokers is amplified in severe (GOLD 

stage 3) and very severe (GOLD stage 4) COPD (Fletcher 

et al. 1976; Hogg et al. 2004). More recent evidence indicates that at these levels of disease severity, these changes 

are associated with an increase in the adaptive immune 

response. These findings may reflect the response to an 

antigenic stimulus from a limited number of antigens that 

might be microbial or possibly from autoantigens that 

develop within the damaged lung tissue (Agustí et al. 

2003; Voelkel and Taraseviciene-Stewart 2005). 

Figure 7.4 Natural history of decline in forced expiratory volume with aging measured in a group of working men 

in West London over about six years

Source: Hogg 2004. Reprinted with permission from Elsevier, © 2004.

Note: Adapted from Fletcher et al. 1976. Horizontal lines have been added to their diagram to indicate the boundaries of the 

classification of severity of chronic obstructive pulmonary disease by the Global Initiative for Chronic Obstructive Lung Disease 

(GOLD).
Pulmonary Diseases 445

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Figure 7.5 Nature of an obstruction in the small conducting airways (<2 millimeters in diameter)

Source: Hogg 2004. Reprinted with permission from Elsevier, © 2004.

Note: A normal airway (A) is compared with another airway (B) in which the lumen is partially filled with a bland mucous plug 

containing a few epithelial cells. (C) An airway in which the wall contains an active inflammatory process that partially fills the lumen 

with inflammatory exudates containing mucus. (D) Airway narrowed by collagen deposition in the peribronchiolar space.

Emphysema

Emphysema was first described by René Laënnec in 

1834 on the basis of observations made on the cut surface of postmortem human lungs that had been air-dried 

in inflation (Laënnec 1834), but the concept that emphysematous destruction produced airflow limitation by 

decreasing the elastic recoil forces required to drive air 

out of the lung was not fully developed until 1967 (Mead et 

al. 1967). The earliest concept regarding the pathogenesis 

of emphysema postulated that overinflation compressed 

the lung capillaries, leading to atrophy of lung tissue; this 

concept was mentioned in major textbooks of pathology 

as late as 1940 (McCallum 1940). As mentioned previously (see “Obstruction of Small Airways” earlier in this 

chapter), McLean (1956) and Leopold and Gough (1957) 

were the first to implicate the inflammatory response in 

the pathogenesis of alveolar destruction in their early 

descriptions of centrilobular emphysema, but skepticism 

about this association persisted because of the possibility that preterminal bronchopneumonia may have been 

responsible for the inflammation observed in the postmortem studies. The subsequent demonstration that emphysema could be produced experimentally by depositing 

the enzyme papain in the lung (Gross et al. 1964), combined with observational studies showing the association 

between emphysema and deficiency of α1-antitrypsin 

(AAT) (Laurell and Eriksson 1963), led naturally to the 

hypothesis that the pathogenesis of emphysema was 

based on a functional proteolytic imbalance within the 
Surgeon General’s Report

446 Chapter 7

inflammatory response induced by tobacco smoke (Gadek et 

al. 1979). 

Currently, emphysema is defined as “abnormal, permanent enlargement of air spaces distal to the terminal 

bronchiole, accompanied by the destruction of their walls, 

and without obvious fibrosis” (Snider et al. 1985, p. 183). 

The condition can now be diagnosed and quantified during life by several techniques. Postmortem examinations 

have provided indirect information on the prevalence of 

emphysema (Thurlbeck 1963; Ryder et al. 1971). 

An important study from the United Kingdom 

(Ryder et al. 1971) found emphysema in 62 percent (219) 

of 353 consecutive postmortem examinations. On average, 

when present, the condition occupied 12.6 percent (range, 

0.5 to 95 percent) of total lung volume. Smoking history 

was established in 179 of the 353 patients, and emphysema was present in 75 percent (80) of the 106 smokers. 

The mean proportion of total lung volume occupied by 

emphysema in smokers was 10.8 percent (range, 0 to 90 

percent). Emphysema was also present in 28 percent (21) 

of 73 nonsmokers, but the mean proportion of the lung 

taken up by emphysema in nonsmokers was only 1.7 percent (range, 0 to 40 percent). In addition, the nonsmokers 

lived longer than the smokers (aged 64.8 versus 60.2 years; 

p <0.05) and emphysema appeared at a later age (Ryder 

et al. 1971).

A laboratory study of more than 400 lungs removed 

from patients being treated for lung cancer (Hogg 2004) 

confirmed that a small proportion of smokers had emphysema and that the proportion with emphysema increases 

with the number of pack-years of smoking. However, the 

dose-response relationship plateaus at 50 to 100 packyears, and about 40 percent of smokers are affected (Figure 7.6). Although imaging by computed tomography 

(CT) has now confirmed that emphysema can be found in 

persons with a normal FEV1, population-based studies of 

its prevalence, as detected by CT, have not been attempted. 

Centrilobular and Panacinar Forms of Emphysema

Pathologically, emphysema is characterized by its 

location as centrilobular or panlobular; the radiographic 

correlates are centriacinar emphysema and panacinar 

emphysema, respectively (Friedlander et al. 2007). Centrilobular emphysema is characteristic of smokers, whereas 

panacinar emphysema is found with AAT deficiency. In 

general, persons with a predominance of centrilobular 

emphysema have physiological abnormalities consistent 

with abnormal function of small airways, whereas panlobular emphysema is associated with high lung compliance. 

A substantial portion of people with emphysema have 

both types.

Figure 7.6 Dose-response relationship between level of smoking and the percentage of 408 patients in the 

St. Paul’s Lung Study with morphologic evidence of significant emphysema in their lungsa

Source: Hogg 2004. Reprinted with permission from Elsevier, © 2004. aThe relationship plateaued with about 40 percent of the heavy smokers having emphysema.

bPack-years = the number of years of smoking multiplied by the number of packs of cigarettes smoked per day.
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

A postmortem bronchogram from a patient with 

lesions of centrilobular emphysema visible at a microscopic low power is shown in Figure 7.7. The nature of 

these lesions is shown to better advantage in Figure 7.8. 

Several normal terminal bronchioles within a secondary lung lobule (A) and the histology of a normal acinus 

beyond a single terminal bronchiole (B) can be compared 

with a line drawing from Leopold and Gough’s (1957) 

original description of centrilobular emphysema (C) and 

a postmortem radiograph showing the destruction of the 

respiratory bronchioles (D). These centrilobular lesions 

affect the upper regions of the lung more commonly than 

the lower regions (Figure 7.9) and are also larger and 

more numerous in the upper lung (Gadek et al. 1979). 

Heppleston and Leopold (1961) used the term “focal 

emphysema” to describe a less severe form of centrilobular emphysema, but Dunnill (1982) argued that this 

distinction was not helpful and that the two conditions 

probably had a similar origin, with focal emphysema being 

more widely distributed and less severe than the classic 

centrilobular form. Dunnill also preferred the term “centriacinar” to “centrilobular.” “Centriacinar” seems more 

suitable in that each secondary lobule contains several 

acini (Figure 7.8A) and not all are involved in emphysematous destruction.

Wyatt and colleagues (1962) provided the first 

detailed account of the panacinar form of emphysema, 

in which more uniform destruction of the entire acinus 

takes place. Thurlbeck (1963) showed that it can be difficult to distinguish normal lung from lung with mild forms 

of panacinar emphysema, unless fully inflated specimens 

are carefully examined under a dissecting microscope. In 

contrast to centrilobular emphysema, the panacinar form 

tends to be more severe in the lower lobes than in the 

upper lobes (Figure 7.9), but this difference is substantial only in severe disease (Thurlbeck 1963). Panacinar 

emphysema is commonly associated with AAT deficiency 

but is also found in cases with no identified genetic abnormality (Thurlbeck 1963).

Other Forms of Emphysema

“Distal acinar,” “mantle,” and “paraseptal” emphysema describe lesions in the periphery of the lobule. 

These types of lesions are found along the lobular septa, 

particularly in the subpleural region (Hogg and Senior 

2002). They also occur in isolation and have been associated with spontaneous pneumothorax in young adults 

(Ohata and Suzuki 1980) and bullous lung disease in older 

adults, whose lung function improved after the removal of 

large cysts (Morgan 1995). Less frequent forms of emphysema include the unilateral form (McLeod syndrome) that 

occurs as a complication of severe childhood infection by 

rubella or adenovirus; the congenital lobar form, a developmental abnormality in newborns; and paracicatricial 

emphysema, which forms around scars and lacks any special distribution within the acinus or lobule (Thurlbeck 

1963; Dunnill 1982).

Pulmonary Hypertension

The invasive nature of right-heart catheterization 

in older adults with comorbid disease has made it difficult to study the prevalence of pulmonary hypertension in 

patients with COPD. In one six-year study of 131 patients 

(Kessler et al. 2001), COPD ranged from moderate (GOLD 

stage 2) to very severe (GOLD stage 4). At baseline, none 

of the patients had pulmonary hypertension, but after six 

years, it was present in 25 percent of the patients at rest 

and in more than 50 percent during exercise. These data 

suggest that the prevalence of pulmonary hypertension 

increases steadily with progression of COPD, appearing 

first during exercise and later at rest. 

Figure 7.7 Postmortem bronchogram performed on 

the lungs of a person with centrilobular 

emphysema

Source: Hogg 2007. Reprinted with permission from Informa 

Healthcare, © 2007.

Note: The lesions hang from the distal airways like “Christmas 

tree balls” (arrow). 
Surgeon General’s Report

448 Chapter 7

When pulmonary hypertension is absent at rest, but 

present during exercise, some of the increase in pulmonary vascular pressures can be attributed to the mechanical events associated with dynamic hyperinflation of the 

lung in persons with airflow limitation (Horsfield et al. 

1968; Jezek et al. 1973; Weitzenblum et al. 1981; Wright 

et al. 1983a). When the time required to exhale becomes 

longer than the time between breaths, lung volume tends 

to increase, first as the breathing rate increases during 

exercise and later as it does so at rest. This increase in 

lung volume increases intrathoracic pressure, an increase 

that is transmitted to all the vessels within the thorax. As 

a result, both pulmonary artery and left atrial pressures 

are higher than atmospheric pressure but not higher than 

intrathoracic pressure. Treatment with oxygen at this 

stage of the disease lowers both pulmonary artery and 

left atrial pressure by slowing the breathing rate, thereby 

relieving the dynamic hyperinflation and lowering intrathoracic pressure. However, when lung emptying is 

more severely prolonged and alveolar pressure rises above 

intrathoracic pressure, there is a true increase in pulmonary artery pressure (Weitzenblum et al. 1981). Hypoxic 

vasoconstriction of the muscular pulmonary arteries and 

emphysematous destruction of the pulmonary vascular 

bed are more likely to contribute to pulmonary hypertension in severe (GOLD stage 3) and very severe (GOLD 

stage 4) COPD. At these more advanced stages, affected 

persons commonly experience chronic hypoxia and extensive destruction of the pulmonary capillary bed. 

Studies of the microvessels of the lung in mild 

(GOLD stage 1) and moderate (GOLD stage 2) COPD show 

consistent changes in the intima. In more severe (GOLD 

Figure 7.8 Details of centrilobular emphysema lesions

Source: Hogg 2004. Reprinted with permission from Elsevier, © 2004. 

Note: (A) Several normal terminal bronchioles within a secondary lung lobule defined by its surrounding connective tissue septa 

(solid arrow) are shown for comparison with (B) the histology of a normal acinus beyond a single terminal bronchiole. (C) Line 

drawing from Leopold and Gough’s original (1957) description of centrilobular emphysema showing the destruction of the respiratory 

bronchioles, and (D) a postmortem radiograph of the dilatation and destruction of the respiratory bronchioles. AD = alveolar duct; 

CLE = centrilobular emphysema; RB = respiratory bronchioles; TB = terminal bronchioles.
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

stage 3) and very severe (GOLD stage 4) COPD, the vessel 

wall is commonly altered by fibroelastic thickening—the 

proliferation of smooth muscle and extension of the muscle into small vessels that do not normally contain muscle. 

However, the contribution of smooth muscle to thickness 

of the vessel wall is also reported to be greater in smokers with normal lung function than in nonsmokers and 

still greater in smokers whose lung function is impaired 

(Horsfield et al. 1968). In patients who have very severe 

emphysema, the overall wall thicknesses of vessels with 

external diameters of 100 to 200 μm correlate with both 

the rise in pulmonary arterial pressure during exercise 

and the difference between the pulmonary artery pressures measured during rest and during exercise (Hale et 

al. 1984; Kubo et al. 2000). The increase in muscle in the 

pulmonary arteries, which is variable, probably depends 

on the severity of the COPD. A greater amount of muscle 

has been observed in the pulmonary vessels of smokers 

than in those of nonsmokers (Horsfield et al. 1968), but 

in mild COPD, little if any increase in muscle has been 

observed (Weitzenblum et al. 1981; Haniuda et al. 2003). 

Muscular medial thickening (Barberà et al. 2003), as 

opposed to overall wall thickening (Hale et al. 1984; Kubo 

et al. 2000), does not appear to be related to the severity of 

the pulmonary hypertension or the vascular response to 

oxygen in patients with COPD (Wright et al. 1992). 

Reports from Barberà and associates (2003) from 

Spain indicate that this vascular remodeling process is 

also associated with, and possibly preceded by, an inflammatory process in which the vessels become infiltrated 

with a population of cells similar to those found around 

the small airways. The precise meaning of this finding and 

its role in the pathogenesis of the peripheral lung lesions 

observed in COPD is under investigation. 

Figure 7.9 Cut surface of lungs removed from two patients with different forms of emphysema before receiving 

a lung transplant

Source: From Dr. Joel Cooper in Hogg 2004. Reprinted with permission from Elsevier, © 2004. 

Note: (A) The lung on the left is affected by centrilobular emphysema, which affected the upper lobe more severely than the lower 

lobe. (B) The lung on the right is from a patient who had a1-antitrypsin deficiency, which involved the lower lobe to a greater degree 

than the upper lobe.
Surgeon General’s Report

450 Chapter 7

Smoking and Respiratory Defense Mechanisms

of tobacco smoke interferes with these defenses, resulting in both increased production of mucus and decreased 

effectiveness of the clearance process in the airway’s 

lumen (Hogg 2008). Impairment of these defenses 

increases the potential for infection (Knowles and Boucher 2002; Drannik et al. 2004). Tobacco smoke also disrupts 

the tight junctions that form the epithelial barrier (Jones 

et al. 1980; Hulbert et al. 1981) and initiates the infiltration of the damaged tissue by a variety of inflammatory 

The innate defense system of the lung includes 

the apparatus for producing and clearing mucus, the 

epithelial cell barrier, and infiltrating inflammatory 

immune cells (Figure 7.10) (Abbas et al. 2000c; Knowles 

and Boucher 2002). The pulmonary epithelium plays a 

critical role in the host defense by recognizing insults 

and initiating innate responses (Greene and McElvaney 

2005; Martin and Frevert 2005; Mayer and Dalpke 2007; 

Sabroe et al. 2007; Torrelles et al. 2008). The inhalation 

Figure 7.10 Innate and adaptive immune system of the lung, including the mucous production and clearance 

apparatus, the epithelial barrier, and the inflammatory immune response

Source: Hogg 2007. Reprinted with permission from Informa Healthcare, © 2007.

Note: Chronic stimulation of this system by the tobacco-smoking habit results in both increased production and decreased clearance 

of mucus from the airway’s lumen, disruption of the tight junctions that form the epithelial barrier and infiltration of the damaged 

tissue by polymorphonuclear and mononuclear phagocytes as well as natural killer cells and CD4+ and CD8+ T cells, and B-cell 

lymphocytes. The adaptive immune response requires antigen presentation primarily by dendritic cells and the organization of 

the lymphocytes into follicles with germinal centers. This type of response is rarely found in healthy nonsmokers but has been 

documented in about 5 percent of peripheral lung units of smokers with normal lung function, increasing to about 20 to 30 percent 

of airways in the later stages of chronic obstructive pulmonary disease. The source of antigen that drives this sharp increase in the 

adaptive immune response is unknown and may be related to either the colonization or infection of the lower airways by a variety 

of microbes in the later disease stages or to autoantigens that develop in the damaged tissue. DCs = dendritic cells; GC = germinal 

center; NK = natural killer.
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

immune cells, including polymorphonuclear and mononuclear phagocytes, natural killer cells, CD4+ and CD8+ T 

cells, and B lymphocytes (Nagaishi 1972; Niewoehner et al. 

1974; Bosken et al. 1992; Richmond et al. 1993; Di Stefano 

et al. 1996; O’Shaughnessy et al. 1997; Ekberg-Jansson et 

al. 2001; Retamales et al. 2001; Cosio et al. 2002; Aoshiba 

et al. 2004; Hogg et al. 2004; Buzatu et al. 2005). The lymphocytes become organized into lymphoid follicles with 

germinal centers to mount an effective adaptive immune 

response. Lymphoid collections with these characteristics have been demonstrated in about 5 percent of the 

smaller airways of smokers (Hogg et al. 2004), and their 

frequency increases to about 20 to 30 percent of airways in 

the later stages of COPD (Nagaishi 1972; Richmond et al. 

1993; Hogg et al. 2004). The source of antigen that drives 

this sharp increase in the adaptive immune response is 

unknown and may be related to either the colonization 

or infection of the lower airways by a variety of microbes 

in the later stages of the disease or to autoantigens that 

develop in the damaged tissue. This inflammatory immune 

process persists after cessation of smoking (Wright et al. 

1983b; Rutgers et al. 2000). Smoking cessation slows the 

rate of decline in lung function and delays death (Fletcher 

et al. 1976; Anthonisen et al. 2005). 

This section of the chapter briefly reviews both the 

inflammatory immune process in relation to the repair 

and remodeling of the tissue damaged by tobacco smoke 

and discusses the roles of these processes in the pathogenesis of the lesions that define COPD. This section of the 

chapter briefly reviews the inflammatory immune process 

in relation to the repair and remodeling of the tissue damaged by tobacco smoke and discusses its contribution to 

the pathogenesis of the lesions that define COPD. Both of 

these aspects of the pathogenesis of COPD are the focus of 

substantial research at present.

Infiltration of Innate 

Inflammatory Immune Cells

The epithelial cells covering the lung surface and 

the alveolar macrophages protecting that surface are key 

in defending the lung against inhaled gases and particles. 

Both of these cell types produce a broad array of proinflammatory chemokines and cytokines. When these signaling molecules are stimulated by tobacco smoke, they 

can be measured in induced sputum (Traves et al. 2002), 

in BAL fluid from patients with COPD (Morrison et al. 

1998b), and in supernates of cultured cells exposed to 

particles and gases under controlled in vitro conditions 

(Becker et al.1996; Quay et al. 1998; Mukae et al. 2000; 

Fujii et al. 2001, 2002; van Eeden et al. 2001). More than 

50 types of chemokine ligands (L) in four families were 

identified by the position of the cysteine residue; they were 

designated as CC, CXC, C, and CX3C (Proudfoot 2002; 

Lukacs et al. 2005). These ligands interact with more than 

20 chemokine receptors (R) to direct leukocyte traffic in 

the inflammatory immune response. Many chemokines, 

such as interleukin-8 (IL-8, or CXCL8), interact with more 

than one receptor (CXCR1 and CXCR2) to control the 

infiltration of PMN into damaged lung tissue (Keatings et 

al. 1996; Yamamoto et al. 1997). IL-8 is markedly increased 

in the sputum of patients with COPD (Keatings et al. 1996; 

Yamamoto et al. 1997) and can readily be measured in the 

supernates of cultured human bronchial epithelial cells 

(HBECs) as they take up toxic particles (Fujii et al. 2001, 

2002). CXCL1 is also secreted by airway epithelial cells and 

alveolar macrophages and activates PMNs, monocytes, 

basophils, and T lymphocytes through CXCR2 (Proudfoot 

2002; Lukacs et al. 2005). The migration of T lymphocytes 

is controlled by the chemokine receptor CXCR3 that is 

expressed in human peripheral airways (Saetta et al. 2002) 

and interacts with other chemokines, including CXCL9, 

CXCL10, and CXCL11 (Clark-Lewis et al. 2003). Increasingly, evidence indicates that safe and effective inhibitors 

of proinflammatory chemokines and cytokines may benefit persons who have COPD (Proudfoot 2002; Lukacs et 

al. 2005). 

In studies involving the coculture of alveolar macrophages and HBECs, paracrine stimulation between these 

cell types enhances their production of chemokines and 

cytokines capable of controlling the recruitment and activation of leukocytes (TNFα, IL-1β, IL-8, and macrophage 

inflammatory protein 1α), enhancing phagocytosis (interferon-gamma), stimulating natural killer cell and T-cell 

function (IL-12), and initiating the repair process (granulocyte-macrophage colony-stimulating factor) (Mukae 

et al. 2001; Goto et al. 2004). Furthermore, instillation 

of the supernatants from alveolar macrophages and/or 

HBECs challenged with particles in vitro produces a systemic response similar to that achieved by instilling the 

same number of particles directly into the lungs of animals (Goto et al. 2004). The magnitude of the systemic 

response correlates with the number of particles phagocytosed by the macrophages (Mukae et al. 2001). More 

limited studies of living persons indicate that cytokines 

produced in the lungs (TNFα, IL-1β, and IL-6) enter the 

blood after smoke inhalation during natural forest fires 

and stimulate the liver to produce acute phase proteins 

and the bone marrow to increase production of leukocytes 

and release them into the circulation (Tan et al. 2000; van 

Eeden and Hogg 2000). Other studies in humans have 

shown a relationship among the count of circulating leukocytes, decline in lung function, and risk for early death 

from COPD (Chan-Yeung et al. 1988; Weiss et al. 1995). 
Surgeon General’s Report

452 Chapter 7

These and other reports indicate that the inhalation of 

toxic particles and gases causes a local innate inflammatory immune response in the lung, initiating an adaptive 

immune response. 

Adaptive Immune Response

The transition from the innate response to the more 

sophisticated adaptive immune response takes place in 

lymphoid follicles with germinal centers (Figure 7.10), 

found either in regional lymph nodes or in lymphoid 

collections within lung tissue (Figure 7.11). Those in 

the lung tissue are similar to those in the lymphoid 

collections observed in tonsils and adenoids in the 

nasopharynx and to Peyer’s patches in the small bowel and 

the appendix of the large bowel (Nagaishi 1972; Pabst and 

Gehrke 1990; Richmond et al. 1993; Hogg et al. 2004). All 

of these structures are part of the mucosal immune system and differ from true lymph nodes in having no capsule and not receiving afferent lymphatic vessels (Nagaishi 

1972; Hogg et al. 2004). The epithelium that covers the 

follicles in lung tissue contains specialized M cells (Figure 7.11) that transport antigens from the lumen to the 

lamina propria but do not function as antigen-presenting 

cells. Dendritic cells located in the epithelium and lamina propria pick up the antigen, which either penetrates 

the epithelial barrier or is transported by the M cells, and 

Figure 7.11 Lymphoid collections within lung tissue

Source: Adapted from Hogg et al. 2007 with permission from Massachusetts Medical Society, © 2007.

Note: (A) Collection of bronchial lymphoid tissue with a lymphoid follicle containing a germinal center (GC) surrounded by a rim of 

darker-staining lymphocytes extending to the epithelium of both the small airway and alveolar surface (Movat’s stain, x6). (B) Follicle 

in which GC stains strongly for B cells (x6). (C) Serial section of the same airway stained for CD4-positive T cells, which are scattered 

around the edge of the follicle and in the airway wall (x6.5). (D) Diagram of immune process triggered by antigens.
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

carry it to either the mucosal lymphatic collections or the 

regional lymph nodes (Buzatu et al. 2005). Lymphocytes 

enter these collections from the blood by attaching to specialized high endothelial cells lining the microvessels that 

supply mucosal lymphoid follicles (Abbas et al. 2000a,b). 

The B cells concentrate in germinal centers rich in B 

lymphocytes, and the CD4+ and CD8+ T cells concentrate 

at the edge of the follicles and in the spaces between them 

(Hogg et al. 2004). This separation and concentration of 

B and T lymphocytes (Figure 7.11) greatly increases the 

opportunity for the migrating dendritic cells to present 

antigen to immature T and B lymphocytes as they make 

their way through the lymphoid collections to the efferent lymph. The T and B cells activated by the presented 

antigen migrate to the outer edge (dark zone) surrounding the germinal center (Figure 7.11) and enrich this zone 

with CD4+ helper T cells and B and T lymphocytes that 

have recognized similar antigens. This aggregation greatly 

increases the opportunity for CD4+ helper T cells, B cells, 

and T cells that have recognized the same antigen to interact to initiate an adaptive response. 

The primary stimulus for production of antibodies is provided by the interaction between CD4+ helper 

T-cell receptors and the major histocompatibility complex 

class II antigen complex on the B cell (Abbas et al. 2000b). 

Secondary costimulatory signals delivered by interactions 

between B-7 on the dendritic cell and its ligand CD28 

on the B cell and between CD40 on CD4+ helper T cells 

and its ligand on B cells stimulate clonal proliferation 

of the B cell and the production of antibodies (Abbas et 

al. 2000a,b). 

The rich diversity of antigen receptors expressed 

on mature T and B lymphocytes is made possible by a 

somatic recombination of a limited number of gene segments encoded in spatially segregated regions of the germ 

line. The specificity of the antibodies produced is further 

enhanced by an affinity maturation process that depends 

on the presentation of the antigen to maturing B cells by a 

network of follicular dendritic cells in the germinal center 

(Abbas et al. 2000b). The B cells expressing high-affinity 

antibody to the antigen presented to them bind tightly 

to it and receive signals that allow them to survive and 

develop into either memory cells or antibody-producing 

plasma cells (Figure 7.11). Those B cells producing lowaffinity antibody fail to make this tight connection and are 

removed through apoptosis (Abbas et al. 2000b). 

The antigens that drive the production of antibodies in the lungs of cigarette smokers in either the early or 

late stages of COPD are poorly understood. The marked 

increase in the adaptive immune response that occurs in 

the later stages of the disease has been attributed to antigens introduced by colonization and infection of the lung 

with microorganisms (Sethi et al. 2002; Hogg et al. 2004; 

Murphy et al. 2005) and to autoantigens arising from 

within damaged lung tissue (Agustí et al. 2003; Voelkel 

and Taraseviciene-Stewart 2005). 

The persistent innate and adaptive immune inflammatory response described here is present in the lungs 

of all long-term smokers and appears to be amplified in 

those smokers who develop severe COPD (Figure 7.12) 

(Keatings et al.1996; Retamales et al. 2001; Hogg et al. 

2004). Hogg and colleagues (2004), who examined predictors of FEV1 obtained from quantitative analysis of lung 

specimens, measured inflammation, as well as the amount 

of tissue remodeling of airway walls. The various tissue 

indicators were compared across strata of GOLD stages 

for COPD. The extent of the immune response increased 

from the least to the most severe stage, although the total 

accumulated volume of cells increased only for B cells and 

CD8+ cells. In a multivariate analysis, these investigators 

found that the index of the remodeling of the wall tissue 

of small airways had the strongest association with the 

level of FEV1, greater than the association with infiltration of the tissue by inflammatory cells (Hogg et al. 2004). 

Ongoing research should provide greater insight into the 

roles of innate and adaptive immune responses (Curtis et 

al. 2007).

Tissue Remodeling

Tissue remodeling in general is an intrinsic property 

of the wound-healing process most carefully studied in 

tissue damaged by an isolated injury (Clark 1996; Kumar 

et al. 2005). Observations of changes in small airways in 

lungs that represent the full range of COPD severity indicate the importance of a repair or remodeling process that 

thickens small airway walls (Hogg 2004). This type of injury initiates an acute inflammatory response lasting about 

three days (Figure 7.13). The increase in microvascular 

permeability that is part of this inflammatory process 

allows large molecules, such as fibrinogen, to leak from 

the vessels and initiate the formation of primitive granulation tissue. This tissue is subsequently organized by the 

processes of angiogenesis and fibrogenesis, which lead to 

the formation of a mature scar (Kumar et al. 2005). Studies of the details of these processes in the lungs of smokers 

have been reported (Hogg 2004).

Angiogenesis is the formation of new blood vessels 

within the granulation tissue by both budding from existing vessels at the edge of the wound and deposition of 

angioblasts derived from bone marrow, such as endothelial progenitor cells (EPCs) in the provisional matrix (Rafii 

et al. 2002; Reyes et al. 2002; Hill et al. 2003; Kubo and Alitalo 2003). Studies by Conway and associates (2001) and 
Surgeon General’s Report

454 Chapter 7

Kumar and colleagues (2005) laid a foundation for understanding the process of angiogenesis. Vascular endothelial 

growth factor (VEGF) and one of its receptors (VEGFR-2) 

enhance vascular permeability, encourage the proliferation of EPCs in the bone marrow and at the injury site, 

and control differentiation of EPCs in the granulation tissue as they form the fragile endothelial tubes. These early 

vascular structures are stabilized by the interaction of 

angiopoietin 1 with tyrosine kinase receptors on endothelial cells. Platelet-derived growth factor and TGFβ control 

the recruitment of smooth muscle to their outer surface 

and enhance production of the extracellular matrix that 

stabilizes these newly formed vessels. The migration 

of endothelial cells formed from EPCs is controlled by 

integrins, especially αvβ3 and matricellular proteins. 

These integrins, which participate in angiogenesis, 

include tenascin-C and thrombospondin, a secreted acidic 

protein rich in cysteine (Conway et al. 2001; Kumar et 

al. 2005). 

The fibrogenic process is initiated by the activation of 

resting interstitial fibroblasts that migrate into the primitive granulation tissue (Kumar et al. 2005). These resting 

fibroblasts have a stellate shape with octopus-like projections that form a network connecting the epithelial to the 

endothelial boundaries of the interstitial compartment 

(Walker et al. 1995; Behzad et al. 1996; Burns et al. 2003). 

The fibroblasts’ projections send small, short extensions 

through tiny preformed holes in both the endothelial and 

epithelial basement membranes. The investigators also 

used three-dimensional reconstructions of serial electron 

micrographs of the interstitial space of the alveolar wall 

to demonstrate that the migrating inflammatory immune 

cells use both the preformed holes in the basement membrane and the surface of the fibroblast to navigate through 

the interstitial space. They found (Figure 7.14) that by 

seeking corners where three endothelial cells meet, the 

migrating inflammatory cells exit the microvessels in the 

alveolar wall without disrupting the tight junctions. After 

exiting, the migrating cells come into contact with the 

endothelial basement membrane and follow its surface 

until they contact one of the preformed holes that normally accommodate a fibroblast extension; the cells then 

crawl through the holes to enter the interstitial space. 

There, they contact the surface of a fibroblast that guides 

their movement through the interstitial compartment to 

bring them to the preformed holes in the epithelial basement membrane, where they exit. The cells then seek the 

junctions between alveolar type 1 and 2 epithelial cells to 

reach the alveolar surface (Walker et al. 1995; Burns et 

al. 2003). Pathways that are similar but not as well studied are used by migrating inflammatory cells to move 

Figure 7.12 Persistent innate and adaptive immune inflammatory response in alveolar tissue

Source: Data from Table 3 in Retamales et al. 2001. 

Note: Adaptive immune inflammatory response is present in the lungs of long-term smokers with normal lung function, 

is amplified in smokers who develop severe chronic obstructive pulmonary disease, and persists many years after smoking cessation. 

CD4+ = CD4-positive T cells; CD8+ = CD8-positive T cells; Mac = macrophages; PMN = polymorphonuclear neutrophils. aPack-years = the number of years of smoking multiplied by the number of packs of cigarettes smoked per day.

*p <0.05.
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

from the bronchial microvasculature to the conducting 

airways’ surface. 

Activation of the resting fibroblasts at the edge of 

a wound starts their migration into the primitive granulation tissue to initiate fibrogenesis (Cross and Mustoe 

2003; Werner and Grose 2003). This process begins with 

differentiation of the fibroblasts into proto-myofibroblasts 

that contain bundles of microfilaments termed stress 

fibers and these proto-myofibroblasts then mature into 

myofibroblasts containing both stress fibers and α-SM 

actin (Kumar et al. 2005). The myofibroblasts generate 

contractile force within the granulation tissue in response 

to agonists such as endothelin; the increase in force they 

generate correlates with the level of expression of α-SM 

actin (Tomasek et al. 2002; Cross and Mustoe 2003; 

Kumar et al. 2005). Together with the reorganization of 

the extracellular matrix secreted by these cells, the forces 

generated by the myofibroblast reduce the size of the damaged tissue. Other reports indicate presence in the lung of 

myofibroblast precursors with a mesenchymal stem cell 

phenotype that has potential for differentiation along different pathways and for direction of specific types of tissue 

repair (Sabatini et al. 2005). 

The inflammatory immune cells infiltrating the 

damaged tissue disappear within a few days of an uncomplicated single wound (Figure 7.13) but persist in the 

face of the relentless tissue damage caused by sustained 

smoking (Kumar et al. 2005). This persistent infiltration of inflammatory cells is associated with deregulation of the process of repair and remodeling that leads 

to the formation of a healthy scar. In a healthy scar, the 

balance between cellular and matrix synthesis and degradation controls the deposition of collagen that forms the 

scar (fibrosis). Synthesis is regulated by a wide variety of 

cytokines and growth factors, and degradation is controlled by the secretion and activation of proteolytic 

enzymes, including both matrix metalloproteinases 

(MMPs) and serine proteases. These processes are deregulated by the persistent injury that occurs in numerous 

chronic diseases, including diseases of the joint tissues 

such as rheumatoid arthritis, of the liver (hepatic cirrhosis), and of the lungs (pulmonary fibrosis). Deregulated 

healing may also underlie the pathogenesis of the lesions 

that develop in the lungs of smokers with COPD. 

The more specific aspects of lung remodeling are 

a focus of research. Lung remodeling is central in the 

Figure 7.13 Remodeling process after a single clean surgical wound

 

Source: Kumar et al. 2005. Adapted from Clark 1996 with permission from Springer Science and Business Media, © 1996. 

Note: A clean surgical wound initiates an acute inflammatory response that lasts for about 3 days and is associated with an increase 

in microvascular permeability that allows large molecules such as fibrinogen to leak from the vessels and participate in the formation 

of primitive granulation tissue. This tissue is subsequently organized by the processes of angiogenesis and fibrogenesis leading to 

the formation of a mature scar. A major difference between this process and that observed in the lung tissue of tobacco smokers is 

persistent stimulation of the tissue by tobacco smoke as it heals, resulting in a persistent inflammatory immune response. 
Surgeon General’s Report

456 Chapter 7

process that leads to airway fibrosis and narrowing in 

small airway obstruction, emphysema, and pulmonary 

hypertension (Postma and Timens 2006). Both the innate 

and adaptive immune responses are involved in these processes (Hogg 2008). Inflammation caused by smoking is 

central in driving these processes, but the heterogeneity 

of phenotypes among persons with COPD remains unexplained (Kim et al. 2008).

Summary

The healing of wounds inflicted by stimuli that persist as the healing takes place provides a model to study 

the pathogenesis of a wide variety of chronic inflammatory lesions. This model provides useful insights into the 

pathogenesis of the lesions found in the lungs of longterm smokers because the damage to lung tissue induced 

by the smoking habit must heal in the presence of a 

chronic stimulus. As a result, the normal tissue remodeling process essential to repair lung tissue damaged by 

inhaled smoke takes place in the presence of a chronic immune inflammatory process. Evidence is growing that this 

chronic process deregulates the normal healing process in 

which the deposition of collagen to form a mature scar 

is determined by a combination of both deposition and 

degradation of collagen. Deregulation of the chemokines, 

cytokines, and growth factors that determine collagen 

Figure 7.14 Diagram based on three-dimensional reconstructions of serial electron micrographs illustrating how 

inflammatory immune cells navigate through interstitial space of alveolar wall

Source: Walker et al. 2005. Reprinted with permission from Elsevier, © 2005.

Note: Migrating inflammatory cells exit the microvessels in the alveolar wall without disrupting the tight junctions by seeking corners 

where 3 endothelial cells meet (arrows). They contact the endothelial basement membrane and follow it to preformed holes that allow 

them to enter the interstitial space and contact the surface of a fibroblast. They use the fibroblast surface to guide their movement 

across the interstitial compartment to the epithelial basement membrane where they find similar preformed holes and enter the 

epithelial compartment. They exit this compartment between the type 1 and type 2 alveolar epithelial cells. AL = alveolar airspace; 

CL = capillary lumen; En = endothelium; F = fibroblast; I = interstitial space; P = pericytes; T1 = type 1; T2 = type 2.
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

deposition and the MMPs and serine proteases that control its degradation could account for both the thickening 

of the airway walls and the emphysematous destruction of 

the peripheral lung in COPD. An important feature of this 

hypothesis is that the application of what is known about 

the healing of chronic wounds to the pathogenesis of the 

pulmonary problems associated with smoking tobacco 

might lead to a better understanding of pathogenesis and 

new and better insights into targets for the development 

of new treatments for COPD. 

Oxidative Stress

Rahman and MacNee (1998) elucidated the mechanisms by which oxidative stress is considered to play a 

central role in the lung injury caused by inhaling tobacco 

smoke. The lungs are directly exposed to the oxygen in 

inhaled air, and because the respiratory tract has direct 

contact with the environment through the large volume of inhaled air, it is subject to oxidative injury from 

inhaled oxidants generated exogenously. These exogenous 

oxidants come from cigarette smoke, ozone, nitrogen 

oxides, sulfur oxides, and other airborne pollutants. 

Endogenous oxidants are also generated from phagocytes 

and other lung cells. Consequently, the lungs have evolved 

an efficient antioxidant system to protect the airways and 

alveoli against both exogenous and endogenous oxidants. 

The lungs are protected against oxidative challenges by 

well-developed enzymatic and nonenzymatic antioxidant 

systems. If the balance between oxidant and antioxidant 

shifts unfavorably because of either an excess of oxidants 

or a depletion of antioxidants, oxidative stress occurs. Oxidative stress not only produces direct injurious effects in 

the lungs but also activates molecular mechanisms that 

initiate lung inflammation.

Generation of Reactive 

Oxygen Species

Oxygen, which constitutes 21 percent of the air 

inhaled, is a key element in the oxidation of organic compounds, the process by which mammalian cells produce 

the energy needed to sustain life (Davies 1995). One-ninth 

of all inhaled oxygen undergoes tetravalent reduction to 

produce H2O in a reaction catalyzed by cytochrome oxidase in the mitochondrial electron-transport chain. Oxygen is also reduced in a nonenzymatic pathway in four 

reductions of single electrons:

O2 + 4H+ + 4e– → 2H2O (Davies 1995) (1)

The terminal electron acceptor in the respiratory chain is cytochrome oxidase, which must donate its 

reducing equivalents to oxygen to sustain electron transport for the production of adenosine triphosphate. The 

sequential tetravalent reduction of oxygen by the mitochondrial electron-transport chain is the process of aerobic energy production, but it can lead to the production of 

ROS (Davies 1995). 

Free radicals are molecules with at least one 

unpaired electron (Davies 1995). The superoxide anion 

(O2•–), the hydroxyl radical (•OH), and nitric oxide (NO) 

are examples of free radicals, whereas hydrogen peroxide 

(H2O2) is not a free radical, because all of its electrons are 

paired. Together, the free radicals are termed ROS. The 

addition of one electron to oxygen produces O2•–; adding 

a second electron leads to formation of H2O2, and a third 

electron results in the formation of •OH (Figure 7.15). 

Addition of a fourth electron to oxygen results in its full 

reduction to H2O. 

The mitochondria are a major intracellular locus 

for the generation of O2•– (Davies 1995). A further source 

for generating O2•– is the reduced nicotinamide adenine 

dinucleotide phosphate (NADPH) oxidase enzymatic system (Davies 1995; Conner and Grisham 1996). O2•– is also 

generated by other mechanisms, including xanthine, sulfite, and aldehyde oxidases and metabolism of arachidonic 

acid. This anion, which is relatively unstable, has a halflife of milliseconds. Because of its charge, O2•– does not 

cross cell membranes easily, but it will react with proteins 

that contain transition metal groups, such as heme moieties or clusters of iron sulfur. These reactions may result 

in damage to amino acids or loss of protein or enzyme 

function. The majority of O2•– generated in vivo undergoes reactions that are nonenzymatic or are catalyzed by 

superoxide dismutase (SOD) and produce H2O2.

H2O2 is also produced directly by several oxidase 

enzymes, including xanthine oxidase, monoamine oxidase, and amino acid oxidase (Davies 1995):

O2•– + O2•– + 2H+ → H2O2 + O2 (2)
Surgeon General’s Report

458 Chapter 7

H2O2 can undergo oxidation by eosinophil-specific 

peroxidase (EPO) and neutrophil-specific myeloperoxidase (MPO), a reaction that uses halides (X–) as a cosubstrate to form hypohalous acids (HOX), which are potent 

oxidants, and other reactive halogenating species:

H2O2 + X– + H+ → HOX + H2O (3)

where X = bromide and chloride (Davies 1995).

In a series of reactions catalyzed by transition metal 

irons, O2•– and H2O2 react in vivo to produce •OH (Halliwell and Gutteridge 1990). One such reaction is the 

iron-catalyzed Haber-Weiss reaction in which the ferric 

ion (Fe3+) is reduced to the ferrous ion (Fe2+). The Fenton 

reaction follows, as Fe2+ catalyzes the transformation of 

H2O2 into •OH:

O2•– + Fe3+ → Fe2+ + O2

H2O2 + Fe2+ → Fe3+ + OH– + •OH (4)

•OH can also be formed in vivo by reactions involving MPO and EPO (Halliwell and Gutteridge 1990). In 

conditions with physiological concentrations of halides, 

MPO produces hypochlorous acid and EPO produces 

hypobromous acid. Hypochlorous acid can generate •OH 

after reacting with O2•–: 

O2•– + HOX → •OH + X+ + O2 (5)

•OH is the most reactive of all the radicals produced, 

reacting immediately with organic molecules at its site of 

production (Halliwell and Gutteridge 1995).

NO, which is produced endogenously throughout 

the human body, has a variety of roles. NO is produced 

from its amino acid substrate l-arginine by the reaction 

of NO synthases (NOSs) (Figure 7.16). Several forms of 

NOS have been characterized (Lowenstein and Snyder 

1992) and are classified as either constitutive or inducible 

(Nathan and Xie 1994; Wink et al. 1996). The constitutive forms (NOS I and III) are cytosolic and were originally 

described and cloned from neuronal and endothelial cells, 

respectively (Nathan and Xie 1994). They are dependent 

on calcium and calmodulin and release relatively small 

amounts of NO for short periods in response to receptor 

and physical stimulation. The inducible form of NOS (NOS 

II) is independent of the calcium ion, and it generates NO 

in large amounts for long periods (Wink et al. 1996). NO 

contains an odd number of electrons and is therefore a 

radical and highly reactive in nature. 

Figure 7.15 Formation of reactive oxygen species

Source: Bowler et al. 2004. Reprinted with permission from Taylor & Francis Group, © 2004. http://www.informaworld.com.

Note: Sequential reduction of oxygen by the addition of electrons (e–) results in the formation of reactive oxygen species: superoxide 

anion (O2•–), hydrogen peroxide (H2O2), and the hydroxyl radical (•OH). O2•– can combine with nitric oxide (NO) to form 

peroxynitrite (ONOO–). O2•– and the hydroxide radical OH– can initiate lipid peroxidation to form lipid peroxides (ROO•) that 

propagate free radical chain reactions. R and R represent lipid substituent groups. H+ is a cationic hydrogen, and 2H+ represents 

2 cationic hydrogens.
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

The reaction of NO with O2 results in the formation 

of nitrite (NO2

–) (Beckman and Koppenol 1996). Physiological concentrations of NO and O2 may be too low for 

this reaction, but this result may have little importance in 

vivo. NO2

– is also a substrate for MPO and EPO, which catalyze peroxidase-mediated oxidation and chlorination of 

biologic targets (Weiss et al. 1986). Peroxidase-catalyzed 

oxidation of NO2

– results in the formation of a nitrogen 

dioxide radical (NO2•). NO2

– is a major end product of NO 

that does not accumulate in vivo, because it is rapidly oxidized to nitrate (NO3

–) (Wink et al. 1996). NO also reacts 

rapidly with free radicals to form reactive nitrogen species 

(RNS) (Parks et al. 1981; Singh and Evans 1997). One such 

reaction is that of NO with O2•– to form the potent oxidant 

peroxynitrite (ONOO–). ONOO– is relatively stable, but it 

can be protonated to yield peroxynitrous acid (ONOOH), 

which then rapidly decomposes to NO3

– (Conner and 

Grisham 1996). ONOOH is highly reactive, unstable, and 

capable of both oxidizing and nitrating reactions. The 

amino acid tyrosine is particularly susceptible to nitration 

with the formation of free or protein-associated 3-nitrotyrosine, which has been used as a marker for the generation of RNS in vivo (Ramezanian et al. 1996; van der Vliet 

et al. 1999).

NO also reacts with compounds containing thiol 

groups, resulting in the formation of S-nitrosothiols 

(SNOs). This reaction is considered to be the mechanism 

by which NO groups are transported and targeted to specific effector sites acting as signaling molecules (Patel 

et al. 1999). SNOs such as S-nitroso-l-glutathione may 

inhibit enzymes that respond to oxidative stress, such 

as glutathione peroxidase (GPX), glutathione reductase 

(GRX), glutathione-S-transferase (GST), and glutamate 

cysteine ligase (GCL) (Clark and Debnam 1988; Becker et 

al. 1995; Han et al. 1996). 

Antioxidants in Lungs

Although ROS and RNS have physiological functions, they also have the potential to cause tissue injury. 

The balance between these physiological functions and 

the potential to cause injury or damage is determined 

by their relative rates of formation and removal (Gutteridge 1994). Normally, ROS and RNS are removed rapidly, 

before they produce cellular dysfunction and eventually 

cell death. An antioxidant is defined as a substrate that, 

when present at lower concentrations than those of an 

oxidizable substrate, significantly delays or inhibits oxidation of that substrate. Antioxidants can be classified 

as either enzymatic or nonenzymatic (Figure 7.17). The 

enzyme antioxidants include SOD and catalase (Kinnula 

and Crapo 2003), the glutathione (GSH) redox system 

(Rahman and MacNee 2000), and the thioredoxin system 

(Arnér and Holmgren 2000).

Enzyme Antioxidants

The SOD family of enzymes is made up of ubiquitous antioxidant enzymes that catalyze the dismutation 

of O2•– into H2O2 and oxygen. Three SOD enzymes have 

been identified in mammals: manganese SOD (MNSOD), 

Figure 7.16 Synthesis of nitric oxide (NO) and related products

Note: FAD = flavin adenine dinucleotide; FMN = flavin mononucleotide; H4B = tetrahydrobiopterin; H2O = water; 

NADP+ = glutamate dehydrogenase; NADPH = reduced nicotinamide adenine dinucleotide phosphate; O2 = oxygen; 

S-GSNO = S-nitrocysteine.
Surgeon General’s Report

460 Chapter 7

copper zinc SOD (CUZNSOD), and extracellular SOD 

(ECSOD) (McCord and Fridovich 1970; Marklund 1984; 

Oury et al. 1996). All three enzymes are expressed widely 

in human lungs (Kinnula and Crapo 2003). CUZNSOD, 

the major intracellular SOD, is present in both the cytosol 

and the nucleus of lysosomes (Slot et al. 1986) of human 

lungs. It is highly expressed in bronchial epithelium and is 

the most abundant SOD in the lungs (Lakari et al. 1998). 

MNSOD, which is localized in the mitochondria, is highly 

expressed in alveolar macrophages and type II alveolar 

epithelial cells in human lungs (Lakari et al. 1998, 2000).

ECSOD, the major extracellular SOD, is localized 

to the extracellular matrix and is particularly abundant 

in the blood vessels of the lungs, but it has also been 

found in bronchial and alveolar epithelium and in alveolar 

macrophages (Kinnula and Crapo 2003). CUZNSOD and 

MNSOD are generally considered to be the major scavengers of O2•–. ECSOD is present at relatively high concentrations in the lungs, and its localization to the extracellular 

matrix suggests that it may provide an important protective mechanism in the lung matrix. Marklund (1984) 

showed that concentrations of ECSOD in the lungs were 2 

to 10 times higher than those in other solid organs. SODs 

can also be induced by cytokines and oxidants (Kinnula 

and Crapo 2003).

Catalase is a tetrameric hemoprotein that undergoes 

oxidation and reduction at its active site in the presence 

of H2O2 (Chance et al. 1979). Accordingly, it has reductive activity for small molecules, such as H2O2 and methyl 

or ethyl hydroperoxide (Pietarinen et al. 1995; Carter et 

al. 2004). Catalase does not metabolize the peroxides with 

larger molecules, such as hydroperoxide products of lipid peroxidation. It is expressed intracellularly, mainly in 

alveolar macrophages and neutrophils. 

The most important and abundant intracellular 

thiol antioxidant, GSH, has a critical function in maintaining the redox status within cells, and it is involved in 

the detoxification of compounds by conjugation reactions 

through GST (Meister and Anderson 1983). The enzymes 

associated with reduced GSH metabolism include GPXs, 

GCL, and GSH synthase. 

The GSH peroxidases are a selenium-containing 

family of enzymes that play a central role in reducing 

H2O2, but they can also reduce lipid peroxides. There 

are five GPX gene products, one of which (GPX3) can be 

detected in the ELF of the human lung (Comhair et al. 

2001). GPX requires GSH to serve as an electron donor. 

The oxidized GSH that results from this reaction (oxidized 

glutathione [GSSG]) is subsequently reduced back to GSH 

by GRX, a reaction generated by NADPH from the hexose 

monophosphate shunt as an electron donor (Meister and 

Anderson 1983; Deneke and Fanburg 1989).

In healthy nonstressed cells, the intracellular ratio 

of GSH to GSSG is high, which ensures the availability 

Figure 7.17 Oxidant and antioxidant systems in the lungs

Note: Cu+ = copper ion; Fe2+ = iron ion; H2O2 = hydrogen peroxide; O2•– = superoxide anion; •OH = hydroxyl radical.
Pulmonary Diseases 461

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

of GSH and thereby promotes active reduction of H2O2

through the GSH system (Doelman and Bast 1990; Bast et 

al. 1991). GSH can also function as a water-soluble antioxidant interacting directly with reactive oxygen intermediates in nonenzymatic catalyzed reactions. Scavenging of 

O2•– by GSH leads to the formation of thiol radicals (GS•) 

and H2O2. Thus, a substance that is generally thought of 

as an antioxidant may possess pro-oxidant activity under 

certain conditions.

GSH is synthesized by GCL and GS (Slot et al. 1986; 

Soini et al. 2001). The rate-limiting enzyme in GSH synthesis is GCL, which therefore plays a fundamental role in 

the regulation of GSH homeostasis in the lungs. GCL is 

a heterodimer with two subunits: a catalytic active heavy 

subunit and a light subunit that regulates the affinity of 

the heavy subunit for substrates and inhibitors. Both subunits of GCL are localized in the cytosol of cells and are 

particularly expressed in human bronchial epithelium and 

to a lesser extent in alveolar macrophages.

The fluid lining the alveolar epithelium has particularly high GSH levels. Cantin and colleagues (1987) 

estimated GSH levels in ELF specimens obtained by BAL. 

Total GSH levels in ELF, including reduced GSH and oxidized GSSG, were 140 times higher than those in plasma.

Most of the GSH was present in the reduced form. GSH 

levels were higher for smokers than for nonsmokers. 

The thioredoxin (TRX) system consists of the thioredoxin proteins TRX-1 and TRX-2; thioredoxin-like proteins (e.g., TLX-1 and 2; SPTRX-1 and 2); thioredoxin 

reductases (e.g., TRXR-1 and 2); peroxiredoxins (PRXs, 

thioredoxin peroxidases); and glutaredoxins (Rhee et al. 

1999; Holmgren 2000; Powis et al. 2000; Gromer et al. 

2004). These enzymes are important in reducing protein 

disulfides and may have additional antioxidant properties. They protect cells against high oxygen tensions and 

participate in the proliferation and survival of cells. TRX 

and TRXR are expressed in bronchial and alveolar epithelium and macrophages (Tiitto et al. 2003). Human lung 

expresses PRXs in bronchial epithelium, alveolar epithelium, and macrophages (Kinnula et al. 2002).

Nonenzymatic Antioxidants

Nonenzymatic antioxidant compounds may act 

directly with oxidizing agents and are therefore said to be 

“scavengers.” Vitamin E (α-tocopherol) is a membranebound antioxidant that terminates the chain reaction 

of lipid peroxidases by scavenging lipid peroxyl radicals 

(LOO•) (Bast et al. 1991; van Acker et al. 1993; Davies 

1995), thus producing the vitamin E radical, which is 

much less reactive than LOO•. At high concentrations, 

however, the radical form of vitamin E may be pro-oxidant 

(Bast et al. 1991). Vitamin C can also directly scavenge 

O2•– and •OH to form a semidehydroascorbate free radical 

subsequently reduced by GSH (McCay 1985). Vitamin C is 

not considered a major antioxidant because it also has peroxide properties. Whether the pro-oxidant or antioxidant 

properties of vitamin C predominate in a particular tissue 

is determined by the available iron stores; iron overload 

favors excess generation of oxidants (Rowley and Halliwell 

1983; Bast et al. 1991).

Other nonenzymatic antioxidants include betacarotene, which scavenges O2•– and peroxyl radicals, and 

uric acid, which scavenges •OH, O2•–, and peroxyl radicals. In addition, glucose can scavenge •OH, bilirubin 

scavenges LOO•, taurine quenches hypochlorous acid, 

albumin binds transition metals, and cysteine and cysteamine donate sulfhydryl groups (Bast et al. 1991).

Mucin is a glycoprotein with a core rich in serine 

and threonine to which sulfhydryls are attached. The 

antioxidant properties of mucus are derived from the 

abundance of sulfhydryl moieties in its structure (Gum 

1992), which actively scavenge oxidants such as •OH 

(Cross et al. 1984, 1997). Alveolar ELF contains high 

concentrations of GSH (100-fold higher than in plasma), 

90 percent of which is in the reduced form (Cantin et al. 

1987). ELF also contains catalase, SOD, and GPX (Cantin and Crystal 1985). Other antioxidants in ELF include 

ceruloplasmin, transferrin, ascorbate, vitamin E, ferritin, 

albumin, and small molecules such as bilirubin (Heffner 

and Repine 1989).

The GSTs and multidrug-resistance proteins (MRPs) 

are a group of detoxifying enzymes that require intracellular GSH for catalytic activity. Researchers have 

identified three mammalian GST families (cytosolic, 

mitochondrial, and microsomal) (Hayes et al. 2005) and 

nine related MRPs (Kruh and Belinsky 2003). Both of 

these classes of detoxification enzymes are expressed in 

healthy lungs, predominantly in the airways (Anttila et 

al. 1993). They function to protect cells against oxidantgenerating compounds, drugs, and other end products of 

oxidative metabolism.

γ-glutamyltranspeptidase (gGT), an enzyme in plasma membrane is expressed in lung epithelial cells and 

induced by oxidative stress (Kugelman et al. 1994). GSH 

is not freely diffusible into cells because it must first be 

broken down into its amino acids. gGT breaks down the 

g-glutamyl bond of GSH. Heme oxygenase-1 is a stress 

response protein with important functions in cell protection and homeostasis; this enzyme can also be induced by 

oxidants and cytokines (Choi and Alam 1996).
Surgeon General’s Report

462 Chapter 7

Oxidants and Cigarette Smoke

Cigarette smoke is a complex mixture of more than 

4,700 chemical compounds, including free radicals and 

other oxidants at high concentrations (Church and Pryor 

1985; Pryor and Stone 1993). Among the reported consequences of oxidants in cigarette smoke are direct damage 

to lipids, nucleic acids, and proteins; depletion of antioxidants; and enhancement of the respiratory burst in phagocytic cells (Bowler et al. 2004; MacNee 2005a). Inactivation 

of proteases and enhancement of molecular mechanisms 

involved in the expression of proinflammatory mediator 

genes are other oxidant-induced effects.

Cigarette smoke is often separated into two phases 

(tar and gas), which both contain free radicals. The gas 

phase is less stable and contains approximately 1015

radicals per puff; and the more stable tar phase has been 

estimated to contain more than 1017 free radicals per 

gram (Zang et al. 1995). Short-lived oxidants, such as 

O2•– and NO, are predominantly found in the gas phase 

(Pryor and Stone 1993). NO and O2•– immediately react 

to form the highly reactive ONOO− molecule. NO is present in cigarette smoke at concentrations of 500 to 1,000 

parts per million. Free radicals in the tar phase of cigarette 

smoke, such as the long-lived semiquinone radical (Q•–), 

are organic and can react with O2•– to form •OH and H2O2

(Nakayama et al. 1989). Q•– is an example of a radical in 

the tar phase of cigarette smoke that can reduce oxygen 

to produce superoxide, the •OH, and H2O2. The aqueous phase of cigarette smoke condensate may undergo 

redox recycling for a considerable time in ELF of smokers 

(Nakayama et al. 1989; Zang et al. 1995). The tar phase of 

cigarette smoke is also an effective metal chelator and can 

bind iron to produce tar-semiquinone + tar-Fe2+, which 

can generate H2O2 continuously.

Quinone (Q), hydroquinone (QH2), and Q•– in 

the tar phase are present in equilibrium (Pryor and 

Stone 1993):

Q + QH2 → 2H+ + Q•– (6)

Aqueous extracts of cigarette tar contain Q•–. This 

radical can reduce oxygen to form O2•–, which may dismutate to form H2O2:

Q•– + O2 → Q + O2•– (7)

2 O2•– + 2H+ → O2 + H2O2 (8)

In addition, cigarette tar and lung ELF contain 

metal ions such as iron. In these circumstances, the Fenton reaction results in the production of •OH. Cigarette 

smokers deposit up to 20 mg of tar per day (≤1 gram per 

day) in their lungs per cigarette smoked. 

Cell-Derived Oxidants

In smokers, inflammation is a characteristic feature 

of the lungs and other organs (Saetta et al. 2002; Bowler et 

al. 2004; Di Stefano et al. 2004). This inflammation generates additional oxidants that contribute to oxidative stress. 

Alveolar macrophages obtained by BAL from the lungs of 

smokers are more activated than those obtained from the 

lungs of nonsmokers (Schaberg et al. 1992). One consequence of this activation is the release of higher levels 

of ROS, such as O2•– and H2O2, thereby further increasing the oxidative burden produced directly by inhaling 

cigarette smoke. Exposure to cigarette smoke in vitro has 

also been shown to increase the oxidative metabolism of 

alveolar macrophages (Hoidal et al. 1981). Subpopulations 

of higher-density alveolar macrophages, which are more 

common in the lungs of smokers, may be responsible for 

the increased production of O2•– that occurs in the macrophages of smokers (Schaberg et al. 1995).

Lung epithelial cells are another source of ROS. 

Type II alveolar epithelial cells have been shown to release 

both H2O2 and O2•– in quantities similar to the amounts 

released by alveolar macrophages (Rochelle et al. 1998). 

ROS released from type II cells are able, in the presence 

of MPO, to inactivate AAT in vitro (Wallaert et al. 1993).

ROS can also be generated intracellularly from several sources, such as mitochondrial respiration, which is 

the largest source of free radicals. In the mitochondria, 

electrons leak from the electron-transport chain onto 

oxygen to form O2•– (Halliwell and Gutteridge 1990). A 

further significant cytosolic source of superoxide is the 

enzyme xanthine dehydrogenase, which has been shown 

to be present at higher levels in cell-free BAL fluid in 

patients with COPD than in that of healthy persons, in 

association with increased production of superoxide and 

uric acid (Pinamonti et al. 1996). A substantial amount of 

superoxide is also produced by membrane oxidases, such 

as cytochrome P-450 and the NADPH oxidase system. In 

addition, NO is generated from arginine by the action of 

NOS. Depending on the relative amounts of ROS and RNS, 

particularly superoxide and NO, which are almost always 

produced simultaneously at sites of inflammation, these 

species can react together to produce the powerful oxidant 

ONOO− (Beckman and Koppenol 1996). The generation of 

ONOO− is thought to prolong the action of NO and to be 

responsible for most of the adverse effects of excess generation of NO.
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Assessment of Oxidative Stress

Oxidative stress can be measured by direct measurements of the oxidative burden, indirectly as the responses 

to oxidative stress, and by examining the effects of oxidative stress on target molecules (Table 7.4). Assessments of 

the oxidative burden in the air spaces can be derived by 

measuring H2O2 in BAL fluid or in exhaled breath condensate (Dekhuijzen et al. 1996; Nowak et al. 1998). Air space 

leukocytes obtained by BAL can be assessed ex vivo for 

the ability to produce ROS. Spin trapping, a technique in 

which a radical reacts with a more stable molecule, can be 

used to measure oxidants in biologic systems; spin trapping has shown increased ROS in the BAL fluid from patients with COPD (Pinamonti et al. 1998). NO is produced 

in the lungs by the catalytic activity of NOS as a marker 

of inflammation and indirectly as a marker of oxidative 

stress, and it can be measured in exhaled breath. Among 

the indirect measures for assessing oxidative stress is an 

examination of the increased activity of the hemoxygenase 

system, which is reflected in the carbon monoxide levels 

in exhaled breath. Assessment of the effects of oxidative 

stress on target molecules may include measuring the 

reaction of ROS with lipids, proteins, or nucleic acids to 

form markers of oxidative stress. For example, ROS attack proteins to form protein carbonyls, ONOO− reacts 

with tyrosine to form nitrotyrosine, and ROS react with 

lipids to liberate ethane and isoprostane and with DNA to 

form base-paired adducts (e.g., 7-hydroxy-8-oxo-2’-deoxyguanosine) or with GSH to produce oxidized GSH. These 

markers can be measured in blood, breath condensate, 

BAL fluid, and lung tissue as an indicator of the effects of 

free radicals on target molecules.

Evidence of Smoking-Induced 

Oxidative Stress

In Vitro Studies

Studies have examined the consequences of acute 

(short-term) exposure to cigarette smoke for a wide range 

of cells (Table 7.5). Many studies have focused on oxidative stress and have shown an increase in markers of such 

stress after exposure to whole cigarette smoke or condensate of cigarette smoke. The cell types studied have 

included alveolar macrophages, type II alveolar epithelial 

cell lines consisting largely of A549 cells, and neutrophils. 

For exposure to cigarette smoke, most of the studies have 

used cigarette smoke extract (CSE) as the exposure agent; 

a smaller number have used cigarette smoke. The concentrations of CSE and the duration of exposure have differed among studies, and concentrations of CSE from that 

produced by one cigarette per milliliter to that produced 

by four cigarettes per milliliter. The exposure times have 

varied between 1 second and 24 hours. All of the studies 

have shown that acute exposure to cigarette smoke causes 

increased oxidative stress.

Exposure of plasma to cigarette smoke in vitro 

depletes antioxidants, including vitamin C, ubiniquol-10, 

α-tocopherol, cryptoxanthin, retinol, and beta-carotene 

and leads to lipid peroxidation (Eiserich et al. 1995; Handelman et al. 1996; Scott et al. 2005). In vivo, smokers 

are well documented to have lower serum levels of vitamin C and beta-carotene and perhaps α-tocopherol than 

do nonsmokers (Tribble et al. 1993; Faruque et al. 1995; 

Adams et al. 1997; Lykkesfeldt et al. 1997; Motoyama et 

al. 1997; Munro et al. 1997; Alberg 2002; Northrop-Clewes 

and Thurnham 2007). This relationship between smoking 

status and reduced vitamin C levels may be dose related 

(Tribble et al. 1993; Faruque et al. 1995; Marangon et al. 

1998). The hypothesis was that reduced levels of vitamin C 

in smokers are due to the activation of leukocytes and subsequent generation of ROS (Winklhofer-Roob et al. 1997).

Table 7.4 Measurements of oxidative stress

Direct measurements of oxidative burden

Hydrogen peroxide in breath condensate or BAL fluid

Reactive oxygen species in BAL fluid and peripheral blood 

leukocytes 

Nitric oxide in exhaled breath

Responses to oxidative stress

Carbon monoxide in breath, reflecting hemoxygenase 

activity

Antioxidants, antioxidant enzymes in blood, sputum, BAL 

fluid, and lung tissue

Effects of oxidative stress on target molecules

Oxidized proteins (e.g., carbonyl residues and oxidized and 

nitrated proteins)

Lipid peroxidation products (e.g., F2-isoprostanes and 

4-hydroxy-2-nonenal)

DNA oxidation products (e.g., 8-hydroxy-2’-deoxyguanosine)

Hydrocarbons in breath condensate, sputum, BAL fluid, 

blood, urine, and lung tissue

Note: BAL = bronchoalveolar lavage. 
Surgeon General’s Report

464 Chapter 7

GSSG, the oxidized form of GSH, is released from 

endothelial cells after 30 minutes of exposure to cigarette smoke (Noronha-Dutra et al. 1993). Although 

intracellular GSH decreased within 3 hours of exposure 

to cigarette smoke (Bridgeman et al. 1991; Li et al. 1994; 

Carnevali et al. 2003), GSH and GCL increased 24 hours 

after exposure. This finding suggests a protective cellular mechanism against the oxidative stress induced by 

cigarette smoke (Rahman et al. 1996b). Immediately after 

exposure to six puffs of cigarette smoke, H2O2 and superoxide molecules were detected in the membranes of epithelial cells in the tracheal explant model (Hobson et al. 

1991), but this consequence of exposure was prevented by 

antioxidants. Twenty-four hours after exposure to CSE, NO 

was released from endothelial cells (Tuder et al. 2000). In 

contrast, inducible NOS (INOS) expression and release of 

nitrate from epithelial cells exposed to CSE were decreased 

(Hoyt et al. 2003). Exposure to cigarette smoke was also 

Table 7.5 Studies of oxidative stress in smokers

Study

Number of 

participants by 

smoking status

Abstinence

time

Cigarettes

smoked

Time between 

inhalation and 

measurement Effect of smoking

Kharitonov 

et al. 1995

17 smokers 8 hours 1 5 and 15 

minutes

Exhaled air: ENO decreased after 5 minutes

(65 ± 6.3 to 44 ± 6.4 ppb); returned to control 

values within 15 minutes (53 ± 6.3 ppb)

Morrow et 

al. 1995

10 smokers 

10 nonsmokers

10 hours 3 30 minutes Blood: F2-isoprostane showed no significant 

change

Rahman et 

al. 1996a

12 smokers 

14 nonsmokers

Unknown 1 60 minutes Blood: TEAC decreased; TBARS increased

Chambers 

et al. 1998

24 smokers 1 hour 1 1 and 10 

minutes

Exhaled air: ENO increased

Morrison et 

al. 1999

14 smokers 

7 nonsmokers

12 hours 2 60 minutes BAL fluid: leukocyte superoxide anions 

increased; TBARS showed no significant 

change; TEAC increased; glutathione showed 

no significant change; oxidized glutathione 

showed no significant change; neutrophils 

increased

Blood: TEAC decreased; TBARS increased

Epithelial permeability increased

Guatura et 

al. 2000

12 smokers

10 nonsmokers 

10 hours 1 30 minutes Breath condensate: hydrogen peroxide 

increased

Montuschi 

et al. 2000

12 smokers 12 hours 2 15 hours Breath condensate: 8-isoprostane increased 

after 15 minutes; no significant change after 

5 hours

Balint et al. 

2001

15 smokers

15 nonsmokers

4 hours 2 30 and 90 

minutes

Breath condensate: nitrate + nitrite increased 

after 30 minutes; no significant change after 

90 minutes; nitrite, peroxynitrite, and ENO 

showed no significant change

Tsuchiya et 

al. 2002

20 smokers 6 hours 1 5 and 60 

minutes

Blood: nitrate, nitrite, ascorbic acid, cysteine, 

methionine, and uric acid decreased after 

5 minutes; no significant change after 

30 minutes

Source: Adapted from van der Vaart et al. 2004 with permission from BMJ Publishing Group Ltd., © 2004.

Note: BAL = bronchoalveolar lavage; ENO = exhaled nitric oxide; ppb = parts per billion; TBARS = thiobarbituric acid reactive 

substances; TEAC = trolox equivalent antioxidant capacity.
Pulmonary Diseases 465

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

shown to activate the pentose phosphate pathway, which 

is a source of NADPH for the enzyme GRX in endothelial cells (Noronha-Dutra et al. 1993). The activities of the 

main enzymes in the GSH redox cycle have been shown to 

be decreased by the acute exposure of alveolar epithelial 

cells to cigarette smoke (Rahman et al. 1996a). Cigarette 

smoke causes depletion of intracellular GSH in cultured 

airway epithelial cells and transient decreases in GPX 

and glucose-6-phosphate activities (Rahman et al. 1998). 

Exposure to cigarette smoke also causes an increase in the 

expression of GPX (Rahman and MacNee 1999). In vitro 

studies also suggest that after initial GSH depletion, GSH 

levels increased, apparently due to GCL induction (Rahman et al. 1996a). Exposure of neutrophils and alveolar 

macrophages to cigarette smoke produces morphologic 

changes in the cells that result in cell blebbing, which 

indicates oxidant-induced damage (Lannan et al. 1994).

Animal Studies

Several studies have assessed the short-term effects 

of the inhalation of cigarette smoke on markers of oxidative stress in lung tissue, BAL fluid, and blood in animals 

(Table 7.6). These studies have found increased levels of 

oxidative stress after such exposure.

GSH, the major thiol antioxidant in the lungs, rapidly and immediately decreases in the lung tissue of rats 

and other laboratory animals after exposure to cigarette 

smoke (Cotgreave et al. 1987; Bilimoria and Ecobichon 

1992; Ishizaki et al. 1996; Li et al. 1996). GSH levels 

may return to normal by two to six hours after exposure 

to smoke (Cotgreave et al. 1987; Bilimoria and Ecobichon 1992) or may remain at levels higher than baseline 

(Ishizaki et al. 1996). GSSG levels increased 1 hour after 

exposure to smoke in animal models and decreased at 

6 hours after acute exposure, returning to normal levels 

after 24 hours (Li et al. 1996). Acute exposure to cigarette 

smoke in rats did not produce any change in the amount 

of cysteine in the lungs; cysteine is an essential amino 

acid for the synthesis of GSH (Cotgreave et al. 1987). 

Other markers of oxidative stress, including 4-hydroxy-2-

nonenal (4-HNE) and 8-hydroxy-2’-deoxyguanosine 

(8-OH-dG), were elevated in lung tissue after acute exposure to cigarette smoke (Ishizaki et al. 1996; Aoshiba et 

al. 2003a). Furthermore, INOS messenger RNA (mRNA) 

and endothelial NOS are increased after acute exposure to 

cigarette smoke (Wright et al. 1999).

ELF is the initial target for oxidative stress, and 

extracellular GSH levels obtained by BAL in rats were 

reduced immediately (Cotgreave et al. 1987) and remained 

at reduced levels six hours after smoke inhalation (Li et al. 

1996). Twenty-four hours after acute exposure to cigarette 

smoke, GSH concentrations return to baseline values (Li 

et al. 1996). Evidence indicates that short-term cigarette 

smoking depletes intracellular GSH concentrations (Cotgreave et al. 1987) and increases levels of GSSG (Cavarra 

et al. 2001b) and 8-OH-dG (Aoshiba et al. 2003a) that are 

associated with decreased antioxidant capacity in BAL 

fluid (Cavarra et al. 2001b). Evidence of systemic oxidative stress has been shown in animal models after acute 

exposure to cigarette smoke, as shown by a decrease in 

antioxidants (Uotila 1982; Ishizaki et al. 1996). This finding is associated with an increase in products of lipid peroxidation such as 8-epi-prostaglandin2a in blood (Cavarra 

et al. 2001b).

Consequences of Smoke-Induced 

Oxidative Stress

Epithelial Injury

Among the first injurious effects of cigarette smoke 

on the lungs is an increase in epithelial permeability, 

which has been demonstrated in animal models (Li et al. 

1994). In the lung tissue of rats, increased epithelial permeability is associated with a decrease in GSH levels and 

an increase in GSSG levels. Depletion of GSH in the lungs 

increased epithelial permeability both in vivo and in vitro 

with use of cultured epithelial monolayers (Li et al. 1994).

Inflammatory Responses

Oxidative stress has been shown to enhance gene 

expression of proinflammatory mediators through the 

redox-sensitive transcription factors nuclear factor-kappa 

B (NF-kB) and activator protein-1 (AP-1). Animal studies have shown enhanced NF-kB nuclear binding after 

exposure to cigarette smoke, which was associated with 

increased gene expression and protein release of proinflammatory cytokines (Nishikawa et al. 1999). Furthermore, 

the molecular mechanisms associated with enhanced 

inflammatory responses after exposure to cigarette smoke 

are thought to involve an increase in histone acetylation 

and decreased histone deacetylase (HDAC) activity, resulting in enhanced histone acetylation, unwinding of chromatin, and hence, enhanced gene expression (Marwick et 

al. 2004). These effects have been demonstrated in animal 

models of exposure to cigarette smoke.

Susceptible Animal Models

The role of oxidative stress in the development of 

lung disease induced by cigarette smoke has been demonstrated in animal models: increasing oxidative stress has 

led to higher frequency of emphysema induced by cigarette smoke. NRF-2 is a controlling transcription factor 
Surgeon General’s Report

466 Chapter 7

Table 7.6 Studies of oxidative stress in animals exposed to smoke

      Smoke exposure      

Study

Animals 

(number)

Number 

of 

cigarettes

Exposure 

time

Time between 

exposure and 

measurement

Route of 

administration Effect

Uotila 

1982

Syrian 

hamsters 

(NR)

5

12

1 hours 

2 hours

20 hours

Measurement 

during 

exposure

Smoking 

chamber

Experiment 1a—Blood: MUG 

increased after 20 hours

Experiment 2b—Blood: MUG 

increased during smoking

Cotgreave 

et al. 1987

SpragueDawley rats

(NR)

8 1 hour 0 hours Nose only BAL fluid: intracellular GSH 

decreased; free GSH decreased; 

extracellular GSH decreased

Blood: GSH showed no significant 

change; cysteine increased

Lung tissue: cysteine showed no 

significant change

Bilimoria 

and 

Ecobichon 

1992

SpragueDawley rats

(8)

Hartley 

guinea pigs

(NR)

40, 120, 

and 240 

puffs

NR 0, 3, and 6 

hours

Nose only Lung homogenate: GSH 

decreased at 0 hours in rats 

but only at high exposures in 

guinea pigs; levels returned to 

preexposure within 3 hours

Ascorbic acid: no reduction in 

either species

Wright et 

al. 1999

Rats

(NR)

7 2 hours 24 hours Nose only Lung homogenate CNOS mRNA 

and protein showed no significant 

change; INOS mRNA increased, 

protein showed no significant 

change; ENOS mRNA increased, 

protein showed no significant 

change

Cavarra et 

al. 2001b

C57BL/6J 

mice with 

smoke 

exposure 

(35), 

controls (70) 

5 20 

minutes

0, 20, and 60 

minutes

Smoking 

chamber

BAL fluid at 0 hours: trolox 

equivalent antioxidant capacity 

decreased, levels returned to 

preexposure within 20 minutes;

glutathione disulfide increased;

ascorbic acid decreased; protein 

thiols decreased; neither 

total glutathione nor vitamin 

E showed any significant 

change; 8-epi-PGF2α increased; 

prevented in a subgroup of case/

controls by pretreatment with 

N-acetylcysteine 

Plasma: 8-epi-PGF2α increased 

at 0, 20, and 60 minutes; total 

cell count, alveolar macrophages, 

polymorphonuclear neutrophils, 

and lymphocytes showed no 

significant change; human 

secretory leukoprotease inhibitor 

inactivated
Pulmonary Diseases 467

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

      Smoke exposure      

Study

Animals 

(number)

Number 

of 

cigarettes

Exposure 

time

Time between 

exposure and 

measurement

Route of 

administration Effect

Aoshiba et 

al. 2003a

C57BL/6 

mice 

(6)

10 1 hour 1, 3, 16, and 24 

hours

Smoking 

chamber

Lung tissue: 8-oxo-dG and 4-HNE 

increased after 1 hour in bronchial 

epithelial cells and type II alveolar 

cells; cellularity increased after 

1–16 hours 

BAL fluid: 8-oxo-dG levels 

increased after 1 hour; no 

significant change after 24 hours

Source: Adapted from van der Vaart et al. 2004 with permission from BMJ Publishing Group Ltd., © 2004.

Note: 4-HNE = 4-hydroxy-2-nonenal; 8-epi-PGF2a = 8-epi-prostaglandin F2a; 8-oxo-dG = 7-hydroxy-8-hydroxy-2’-deoxyguanosine; 

BAL = bronchoalveolar lavage; CNOS = constitutive nitric oxide synthase; ENOS = endothelial nitric oxide synthese; GSH = reduced 

glutathione; INOS = inducible nitric oxide synthase; mRNA = messenger RNA; MUG = methylumbelliferyl glucuronide; NR = data not 

reported.

aLungs were isolated, ventilated with cigarette smoke, and perfused with 4-MUG.

bIsolated lungs were simultaneously ventilated with cigarette smoke and perfused with MUG.

for the expression of antioxidant genes. In NRF-2 knockout mice, exposure to smoke produced more evidence of 

oxidative stress in the lungs, which was associated with 

an increased inflammatory response and enhanced development of emphysema compared with those in wild-type 

mice (Foronjy et al. 2006). Furthermore, a transgenic animal that overexpressed SOD showed diminished smokeinduced emphysema. These findings suggest a role for 

oxidative stress in the development of emphysema (Rangasamy et al. 2004).

Antioxidants have been shown to reduce the effects 

of oxidative stress after exposure to cigarette smoke. The 

thiol antioxidants nacystelyn and N-acetylcysteine have 

each been used to reduce the inflammatory responses after 

exposure to cigarette smoke and also the injurious effects, 

principally emphysema (Antonicelli et al. 2004; Rubio et 

al. 2004). After exposure to cigarette smoke, recombinant 

SOD has been shown to reduce the inflammatory response 

in several ways: by decreasing the inflammatory response 

in the lungs, reducing the influx of neutrophils, decreasing IL-8 gene expression and release, and decreasing 

NF-kB activation (Nishikawa et al. 1999).

Human Studies

Several studies have shown evidence of both 

local and systemic oxidative stress in humans after acute 

exposure to cigarette smoke (Table 7.7). Some studies 

were undertaken in long-term smokers with normal lung 

function, and some have been performed in smokers who 

were instructed to refrain from smoking before the acute 

exposure at intervals between 7 and 24 hours. Reports 

of other studies have not provided information on 

abstention, and in some studies, the participants were not 

instructed to refrain from smoking.

Local Oxidative Stress in Lungs

The acute effects of cigarette smoking on oxidative 

stress have been assessed with markers in exhaled air, 

BAL fluid, and blood. Most of these studies have shown an 

immediate increase in oxidative stress after acute exposure, but some have shown no effect (Table 7.7). Five studies have described the effects of acute exposure to cigarette 

smoke on markers of oxidative stress in breath condensate 

or exhaled air. In breath condensate, the lipid peroxidation product 8-isoprostane increased 15 minutes after 

acute exposure (Montuschi et al. 2000). In addition, lipid 

peroxides have been shown to increase in exhaled breath 

30 minutes after exposure to smoke (Guatura et al. 2000). 

Furthermore, exhaled NO has been shown to increase 1 

and 10 minutes after acute exposure to smoke (Chambers 

et al. 1998), but in another study it decreased 5 minutes 

after exposure (Kharitonov et al. 1995). The inconsistency 

between these studies probably relates to differences in 

the measurements of exhaled NO and among the groups 

studied. High levels of exhaled NO have not been observed 

at time points after exposure (15, 30, and 90 minutes) 

(Kharitonov et al. 1995; Balint et al. 2001). Nitrate, an end 

product of NO, increased 30 minutes after acute exposure, 

Table 7.6 Continued
Surgeon General’s Report

468 Chapter 7

Table 7.7 In vitro studies of oxidative stress

      Smoke exposure   

Study Cell types Source

Dose 

(cigarettes/

mL)

Exposure 

time

Time between 

exposure and 

measurement Effect of smoke exposure

Powell and 

Green 1971

Rabbit AMs CSE NR NR NR G3PD activity in AMs decreased, effect 

prevented by cysteine; G6PD and LDH 

activities not significantly different 

from controls

Bridgeman 

et al. 1991

Erythrocytes

Neutrophils

A549 cell line

CS 1, 3, and 5 

puffs

NR NR Intracellular GSH decreased, not 

prevented by reducing agents

Hobson et 

al. 1991

Rat tracheal 

explants

CS 1, 3, and 6 

puffs

10 

minutes

40 minutes Hydrogen peroxide and O2 – increased 

along epithelial cell membranes, 

prevented by SOD

3 and 6 puffs: cell separation, focal 

membrane blebbing, and loss of cilia, 

cell disintegration

Tsuchiya et 

al. 1992

Rat PMNs CSE 1 20 

minutes

20 minutes Radical oxidant scavenger production 

from PMNs decreased, prevented by 

SOD; oxygen consumption from PMNs 

increased

NoronhaDutra et al. 

1993

HUVEC CSE 0.5 30 

minutes

30 minutes Pentose phosphate pathway activated; 

GSSG release increased

Li et al. 

1994

A549 cell line CSE 1 1–6 hours 1, 4, 6, and 24 

hours

Epithelial permeability increased 

at 1 hour, prevented by GSH, no 

significant change 24 hours after 

wash; intracellular GSH decreased, no 

significant change 24 hours after wash

Rahman et 

al. 1996b

A549 cell line CSE 1 puff/3 mL 4, 16, or 

28 hours

0 hours Intracellular CSE GSH increased after 

24 hours; GSSG no significant change; 

γGCS activity increased; γGCS-HS 

mRNA increased

Pinot et al. 

1999

Human 

peripheral 

blood 

monocytes

CSE 0, 0.006, 

0.024

Overnight Directly after O2 – production showed no significant 

change; HSP 70 increased; membrane 

pseudopodes decreased; submembrane 

vacuoles increased; surfactant 

prevented CSE effects 

Tuder et al. 

2000

Bovine artery 

endothelial 

cells

Monocytic 

U937

Hep G2

A549 cell line

CSE 0.1 24 hours 24 hours VEGF decreased protein and mRNA in 

all cells except A549 cell line;

apoptosis increased bovine artery 

endothelial cells

.

.
Pulmonary Diseases 469

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Table 7.7 Continued

      Smoke exposure   

Study Cell types Source

Dose 

(cigarettes/

mL)

Exposure 

time

Time between 

exposure and 

measurement Effect of smoke exposure

Hoyt et al. 

2003

LA-4

A549 cell line

HBEC

CSE 0.0004–

0.00008

4 and 24 

hours

24 hours Nitrate decreased at 4 and 24 hours in 

all cell types; INOS-positive LA-4 cells 

decreased at 24 hours; INOS mRNA 

decreased; ENOS and NNOS mRNA 

showed no change in LA-4 cells; ENOS 

in A549 cells showed no significant 

change

Kayyali et 

al. 2003

RPMEC CSE 20 μg/mL 4 and 24 

hours

4 and 24 hours XO activity increased at 4 and 24 

hours; mRNA XO increased at 6 hours

Wickenden 

et al. 2003

A549 cell line

HUVEC

Jurkat cells

CSE 0.05–0.1 24 hours 24 hours Necrosis increased, no apoptosis;a

GSH inhibits necrosis and apoptosis 

(Jurkat cells); GSH/GSSG decreased 

intracellularly; inhibition CASPASE-3 

activation (Jurkat cells)

Source: Adapted from van der Vaart et al. 2004 with permission from BMJ Publishing Group Ltd., © 2004.

Note: A549 = human lung adenocarcinoma epithelial cell line; AMs = alveolar macrophages; CS = cigarette smokers; 

CSE = cigarette smoke extract; G3PD = glyceraldehyde 3-phosphate dehydrogenase; G6PD = glucose 6-phosphate dehydrogenase; 

γGCS = gamma-glutamylcysteine synthetase; γGCS-HS = gamma-glutamylcysteine synthetase heavy subunit; GSH = reduced 

glutathione; GSSG = oxidized glutathione; HBEC = human bronchial epithelial cells; Hep G2 = human hepatocellular carcinoma cell 

line; HSP 70 = heat shock protein 70; HUVEC = human umbilical vein endothelial cells; INOS = inducible nitric oxide synthase; 

LA-4 = mouse lung epithelial cell line; LDH = lactate dehydrogenase; mL = milliliter; μg = microgram; mRNA = messenger RNA; 

NNOS = neuronal nitric oxide synthase; NR = data not reported; O2•– = superoxide anion; PMN = polymorphonuclear neutrophil; 

RPMEC = rat pulmonary microvascular endothelial cells; SOD = superoxide dismutase; U937 = human leukemic monocyte 

lymphoma cell line; VEGF = vascular endothelial growth factor; XO = xanthine oxidase. aLight microscopy, TUNEL (terminal dUTP nick-end labeling) assay, electron microscopy.

but nitrite and nitrotyrosine, which are also products 

of NO metabolism, did not increase (Balint et al. 2001). 

In humans, all the oxidative markers of oxidative stress 

increase within the first hour after acute exposure, and 

most markers return to normal within 90 minutes (van 

der Vaart et al. 2004). 

Only one study has investigated the effects of smoking on markers of oxidative stress in ELF or BAL fluid. 

In this study, release of O2•– by air space leukocytes 

increased after exposure to smoke (Morrison et al. 1999). 

In addition, systemic antioxidant capacity decreased, as 

measured by the Trolox Equivalent Antioxidant Capacity 

(Rahman et al. 1996a; Morrison et al. 1999). Surprisingly, 

however, the antioxidant capacity in BAL fluid increased 

after exposure to smoke, possibly because all of the participants were long-term smokers and already had a high 

antioxidant capacity in BAL fluid. After smoking, no differences were observed in levels of reduced or oxidized GSH 

in leukocytes or in thiobarbituric acid reactive substances 

(TBARS), as evidenced by measuring lipid peroxidation in 

BAL fluid or in ELF. 

Systemic Oxidative Stress

After just one cigarette has been smoked, nitrite, 

nitrate, and cysteine decrease in peripheral blood (Tsuchiya et al. 2002). In a study by Hockertz and colleagues 

(1994), no differences were observed in the production 

of reactive oxygen intermediates from circulating neutrophils after exposure to smoke, but an earlier study 

gave conflicting findings (Drost et al. 1992). In contrast 

to levels in BAL fluid, TBARS in plasma increased after 

exposure to smoke and antioxidant capacity was decreased 

when measured within one hour after smoking (Rahman 

et al. 1996a; Tsuchiya et al. 2002). However, in smokers, 

levels of the lipid peroxidation product F2-isoprostane 

did not change in plasma after exposure to smoke (Morrow et al. 1995), possibly because all participants were 
Surgeon General’s Report

470 Chapter 7

long-term smokers who had already developed high 

F2-isoprostane levels.

Epithelial Injury 

Increased epithelial permeability, which can be 

measured by 99mTc-DTPA lung clearance (Morrison et al. 

1998a), has been shown to increase in cigarette smokers 

one hour after exposure to smoke (Morrison et al. 1999). 

Another study (Gil et al. 1995), however, showed no difference in epithelial permeability 15 minutes after exposure to cigarette smoke in long-term smokers. Epithelial 

permeability, measured by radiolabeled urea, decreased 

after acute exposure to cigarette smoke (Ward et al. 2000), 

but no differences could be detected when measurements 

were made by positron emission tomography scanning 

with use of radiolabeled transferrin (Kaplan et al.1992). 

Inflammatory Responses 

The numbers of neutrophils in the blood and BAL 

fluid from long-term smokers are higher than in those 

from nonsmokers (Hunninghake and Crystal 1983; Kuschner et al. 1996; van Eeden and Hogg 2000). Findings on 

the effect of short-term cigarette smoking on the number 

of neutrophils in BAL fluid have been inconsistent. Some 

studies reported an increase (Morrison et al. 1999), and 

others reported no change (Janoff et al. 1983b). Exposure 

to smoke has not been shown to change the number of 

monocytes or the total number of leukocytes in BAL fluid 

(Janoff et al. 1983b). However, counts of peripheral blood 

granulocytes increase after acute exposure to cigarette 

smoke (Winkel and Statland 1981; Abboud et al. 1986; 

Hockertz et al. 1994), and counts of peripheral blood 

eosinophils decrease after such exposure (Winkel and 

Statland 1981). Acute exposure to cigarette smoke has 

also been shown to reduce the number of B cells (Hockertz et al. 1994) and the total number of lymphocytes in 

peripheral blood (Winkel and Statland 1981). In contrast, 

the number of CDB-positive cells and the ratio of CD4+ to 

CD8+ cells are not affected by acute exposure to cigarette 

smoke (Hockertz et al. 1994). In capillary blood, the total 

number of basophils decreased 10 minutes after the smoking of two cigarettes (Walter and Nancy 1980), and the 

number of degranulated basophils increased (Walter and 

Walter 1982).

Neutrophil kinetics in the lungs have been examined 

after exposure to cigarette smoke by using an assessment 

of the first pass of radiolabeled neutrophils through the 

pulmonary circulation. Retention of neutrophils in the 

lungs increased after acute exposure to cigarette smoke 

(MacNee et al. 1989). This increased retention was not due 

to an alteration of pulmonary hemodynamics (Skwarski 

et al. 1993) but resulted from decreased deformability of 

leukocytes (Drost et al. 1993) and/or the increased expression of the adhesion molecule l-selectin in blood neutrophils after acute exposure to cigarette smoke (Patiar et al. 

2002).

After acute exposure to cigarette smoke, changes in 

GSH have been studied in human, animal, and in vitro 

models. The ratio of GSH to GSSG, which reflects oxidative stress, has been shown to decrease after acute exposure in both animal and in vitro studies but not in a single 

human study (Morrison et al. 1999). This discrepancy may 

be explained by differences in species and dose of smoke 

and differences between human BAL fluid and animal 

lung homogenate. 

Exposure to cigarette smoke has been shown to 

damage fatty acids in cell membranes and thereby result in increased products of lipid peroxidation both in 

humans, as seen in exhaled air and plasma (Rahman et al. 

1996a; Montuschi et al. 2000), and in animals, as seen in 

BAL fluid and lung tissue (Ishizaki et al. 1996; Aoshiba et 

al. 2003a).

Summary

The time courses of the changes in markers of oxidative stress after exposure to smoke have been studied in 

humans and in animal models. In humans, all the oxidative markers of oxidative stress increase within the first 

hour after acute exposure, and most markers return to 

normal quickly. In animal models, markers of oxidative 

stress generally increase during the first 6 hours after 

exposure to cigarette smoke and return to normal by 24 

hours. These findings have been demonstrated in lung tissue, BAL fluid, and blood. In studies with in vitro models, 

only a few time points have been examined. Initial depletion of GSH after acute exposure to cigarette smoke is followed in most cases by an increase in GSH 24 hours later. 

This finding suggests a protective mechanism against oxidative stress from smoke that may reflect the increase in 

GSH seen in long-term cigarette smokers. 
Pulmonary Diseases 471

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Oxidative Stress in Chronic Obstructive Pulmonary Disease

There is considerable evidence, largely indirect, for 

increased oxidative stress in the lungs of COPD patients. 

As explained previously, oxidative stress can be measured 

in several ways, including direct measurements of oxidant burden, indirect measures using response to oxidative stress, and measurements of the effects of oxidative 

stress on target molecules (see “Assessment of Oxidative 

Stress” earlier in this chapter). Spin trapping, a technique 

by which a radical reacts with a more stable molecule, can 

be used to measure oxidants in biologic systems. The technique of spin trapping has been applied to measure BAL 

fluid in patients with COPD and has shown increased ROS 

(Pinamonti et al. 1998).

Numerous studies have shown that markers of oxidative stress are increased in the lungs of COPD patients 

compared not only with those in healthy persons but also 

with those in smokers having a similar smoking history 

who have not developed COPD (MacNee 2000). Patients 

with COPD have higher levels of H2O2 in exhaled breath 

condensate, a direct measurement of air space oxidative 

burden, than do former smokers with COPD or nonsmokers (Dekhuijzen et al. 1996; Nowak et al. 1998). Elevated levels of H2O2 in the exhaled breath of smokers are 

thought to derive partly from increased release of O2•– by 

alveolar macrophages (Hoidal et al. 1981).

NO has been used as a marker of airway inflammation and indirectly as a measure of oxidative stress. 

Increased NO in exhaled breath has been seen in some 

studies of patients with COPD, but the levels are not as 

high as those reported in asthma (Maziak et al. 1998; Delen et al. 2000). Other studies have found either normal or 

even lower-than-normal levels of exhaled NO in patients 

with stable COPD compared with those in healthy persons 

(Clini et al. 1998; Rutgers et al. 1999). Smoking directly 

increases exhaled NO levels, however, thereby limiting 

the usefulness of this marker in COPD. The rapid reaction of NO with O2•–, described previously, or with thiols 

may alter NO levels in breath (see “Generation of Reactive 

Oxygen Species” earlier in this chapter). Nitrosothiol levels have been shown to be higher in breath condensate in 

smokers and in COPD patients than those in nonsmokers 

(Corradi et al. 2001). ONOO−, formed by the reaction of 

NO with O2•–, can cause nitration of tyrosine to produce 

nitrotyrosine (Petruzzelli et al. 1997). Nitrotyrosine levels 

are elevated in sputum leukocytes of patients with COPD, 

and they are correlated negatively with FEV1 (Ichinose et 

al. 2000).

Exhaled carbon monoxide, as a measure of the 

response of heme oxygenase to oxidative stress, has been 

shown to be elevated in exhaled breath in persons with 

COPD compared with that in persons without COPD 

(Montuschi et al. 2001). Carbon monoxide is also present 

in cigarette smoke, however, which limits its usefulness as 

a marker of oxidative stress in persons who smoke. 

Lipid peroxidation products such as TBARS or 

malondialdehyde are elevated in sputum from COPD 

patients, and the levels correlate negatively with FEV1

(Nowak et al. 1999; Tsukagoshi et al. 2000; Corradi et al. 

2003). Urinary levels of 8-isoprostane, another lipid peroxidation product, are also higher in persons with COPD 

(Praticò et al. 1998). Levels of 8-isoprostane in breath 

condensate are also higher in persons with COPD than 

in healthy persons and smokers who have not developed 

the disease, and they correlate with the degree of airway 

obstruction (Paredi et al. 2000a). Isoprostanes may also 

reflect systemic effects caused by ROS (Morrow et al. 

1995). Plasma levels of free F2-isoprostanes are higher in 

smokers than in nonsmokers and are decreased after cessation of smoking. 

Lipid peroxides can interact with enzymatic or 

nonenzymatic antioxidants and can decompose by reacting with metal ions or iron-containing proteins, thereby 

forming hydrocarbon gases and unsaturated aldehydes. 

Hydrocarbons are thus by-products of fatty acid peroxidation (Paredi et al. 2000b). COPD patients have higher 

levels of exhaled ethane in breath than do persons in the 

control group, and these levels correlate negatively with 

lung function (Habib et al. 1995; Paredi et al. 2000b).

There is evidence that concentrations of these markers of oxidative stress are also increased in the lung tissue 

of COPD patients. The lipid peroxidation product 4-HNE 

reacts quickly with extracellular proteins to form adducts, 

which have been shown to be present at higher concentrations in airway epithelial and endothelial cells in the lungs 

of COPD patients than in those of smokers with a similar smoking history who have not developed the disease 

(Rahman et al. 2002). Other markers of oxidative stress, 

such as 8-OH-dG and 4-HNE, have been shown to have 

increased expression associated with emphysematous 

lesions in the lungs (Tuder et al. 2003c).

Pathogenesis of Chronic 

Obstructive Pulmonary Disease

Many studies have shown higher levels of biomarkers of oxidative stress in COPD patients than in healthy 

smokers. Furthermore, several studies show relationships 
Surgeon General’s Report

472 Chapter 7

between markers of oxidative stress and the degree of 

airflow limitation in COPD (Repine et al. 1997; MacNee 

2000). However, the presence of oxidative stress and its 

relationship to airflow limitation may be an epiphenomenon because oxidative stress occurs in any inflammatory 

response. Cohort studies have not shown that the presence of enhanced oxidative stress relates to the decline in 

FEV1 or to the progression of COPD.

Protease-Antiprotease Imbalance

In COPD, the protease burden in the lungs is 

increased because of the influx and activation of inflammatory leukocytes that release proteases. It has been proposed that a relative “deficiency” of antiproteases such as 

AAT, because of their inactivation by oxidants, creates a 

protease-antiprotease imbalance in the lungs. This hypothesis forms the basis of the protease-antiprotease theory 

of the pathogenesis of emphysema (Janoff et al. 1983a; 

Stockley 2001). Inactivation of AAT by oxidants occurs at 

a critical methionine residue in its active site and can be 

produced by oxidants from cigarette smoke or oxidants 

released from inflammatory leukocytes, resulting in a 

marked reduction in the inhibitory capacity of AAT in vitro 

(Bieth 1985; Evans and Pryor 1992). In vivo study of the 

acute effects of cigarette smoke on the functional activity of AAT show a transient but nonsignificant fall in the 

antiprotease activity of BAL fluid one hour after cigarette 

smoking (Abboud et al. 1985). In addition, in vitro exposure of lung epithelial cells to proteases leads to increased 

release of ROS, suggesting that proteases increase oxidative stress (Aoshiba et al. 2001b).

Hypersecretion of Mucus

Oxidant-generating systems such as xanthine and 

xanthine oxidase have been shown to cause the secretion 

of mucus from airway epithelial cells (Adler et al. 1990; 

Wright et al. 1996). Oxidants are also involved in the signaling pathways for EGF, which has an important role in 

the production of mucus (Nadel 2001). In addition, H2O2

and superoxide have been shown to cause a significant 

impairment of ciliary function after short-term exposure 

at low concentrations (Feldman et al. 1994). These effects 

may have important implications in the pathogenesis 

of COPD.

Lung Inflammation

Oxidative stress is present wherever inflammation 

exists. It may also be a mechanism for enhancing the air 

space inflammation that is characteristic of COPD (Pauwels et al. 2001). Oxidative stress can result in the release 

of chemotactic factors, such as IL-8, from airway epithelial cells (Gilmour et al. 2003), and epithelial cells from 

COPD patients have been shown to release more IL-8 than 

those of smokers or healthy persons (Profita et al. 2003). 

Lipid peroxidation products such as 8-isoprostane can also 

act as signaling molecules and cause the release of inflammatory mediators such as IL-8 from lung cells (Scholz et 

al. 2003). The lipid peroxidation product 4-HNE can cause 

increased production of TGFβ (Leonarduzzi et al. 1997) 

and increased expression of the gene encoding for the antioxidant enzyme γ-glutamylcysteine synthetase (Arsalane 

et al. 1997). 

An enhanced inflammatory response in the lungs 

is characteristic of COPD (Di Stefano et al. 2004; Hogg 

2004). Oxidative stress may have a fundamental role in 

enhancing inflammation through the increased production of redox-sensitive transcription factors, such as 

NF-kB and AP-1, and also by activation of the extracellular signal-regulated kinase, C-JUN N-terminal kinase, and 

p38 mitogen-activated protein kinase pathways (Rahman 

and MacNee 1998; MacNee and Rahman 2001). Cigarette 

smoke has been shown to activate all of these signaling 

mechanisms.

Genes for many inflammatory mediators are regulated by NF-kB, which is present in the cytosol in an 

inactive form linked to its inhibitory protein IkB. Many 

stimuli, including oxidants, result in activation of IkB 

kinase, producing phosphorylation and cleaving of IkB 

from NF-kB. The release of NF-κB is a critical event in the 

inflammatory response and is redox sensitive (JanssenHeininger et al. 1999; MacNee 2000). Studies both in macrophage cell lines and in alveolar and bronchial epithelial 

cells show that oxidants cause the release of inflammatory 

mediators (e.g., IL-8, IL-1, and NO) and that these events 

are associated with increased expression of the genes for 

these inflammatory mediators and with increased nuclear 

binding and activation of NF-kB (Jiménez et al. 2000; Parmentier et al. 2000). The linking of NF-kB to its consensus site in the nucleus leads to enhanced transcription of 

proinflammatory genes and hence inflammation, which 

induces more oxidative stress, creating a vicious circle 

as enhanced inflammation and increased oxidative stress 

perpetuate each other.
Pulmonary Diseases 473

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Nuclear binding of NF-kB is increased in the airway 

macrophages and airway epithelial cells of COPD patients 

(Di Stefano et al. 2002). In a guinea pig model, exposure to 

cigarette smoke led to influx of neutrophils into the lungs 

and increased IL-8 gene expression, protein release, and 

NF-kB activation (Nishikawa et al. 1999). These increases 

and the neutrophil influx were reduced by pretreatment 

with superoxide dismutase, suggesting a role for oxidant 

stress. NF-kB is activated and translocated to the nucleus to a greater extent in lung tissue in smokers and in 

patients with COPD than in healthy persons (Szulakowski 

et al. 2006), and NF-kB activation in lung tissue has been 

shown to correlate with FEV1 (Crowther et al. 1999).

A study of gene expression in rat epithelium after 

exposure to cigarette smoke showed that smoke causes 

rapid induction of antioxidant stress-response genes and 

drug-metabolizing enzymes, such as heme oxygenase 

and quinone oxidoreductase, all of which had decreased 

expression after long-term exposure to cigarettes (Gebel 

et al. 2004). The protein kinase C signaling pathway is 

also sensitive to tobacco smoke and increases its activity 

by twofold to threefold when stimulated by 5-percent CSE 

(Wyatt et al. 1999).

A further event controlling gene transcription that 

may be affected by oxidative stress and may enhance lung 

inflammation is chromatin remodeling. Under normal 

circumstances, DNA is wound tightly around a core of 

histone residues. This configuration prevents access for 

transcription factors to the transcriptional machinery and 

also reduces access of RNA polymerase to DNA, thereby 

resulting in transcriptional repression and gene silencing (Rahman and MacNee 1998; MacNee 2001). Histone 

acetyltransferases (HATs) cause the acetylation of histone residues, resulting in a change in their charge and 

unwinding of DNA and allowing access for transcription 

factors such as NF-kB and RNA polymerase to the transcriptional machinery, thereby enhancing gene expression. This process is reversed by HDACs, enzymes that 

deacetylate histone residues, resulting in the rewinding 

of DNA and gene silencing. The exact role of oxidative 

stress in modifying HAT and HDAC activity is unknown, 

but it appears that oxidative stress can result in increased 

HAT activity and decreased HDAC activity (Gilmour et al. 

2003), which would enhance gene transcription.

Oxidative stress results in HAT activity in epithelial 

cells (Tomita et al. 2003). Histone acetylation can be shown 

to occur after the exposure of epithelial cells to cigarette 

smoke and is prevented by the antioxidant therapy N-acetylcysteine, indicating that the process is redox sensitive 

(Anderson et al. 2004). Furthermore, in animal models, 

exposure to cigarette smoke results in increased acetylated histone in the lung and decreased HDAC activity, 

and both of these events would enhance gene expression 

(Marwick et al. 2002). In addition, HDAC activity in alveolar macrophages obtained from cigarette smokers has 

been shown to be decreased, which would also enhance 

gene expression (Ito et al. 2001). This event may be due 

to nitration of HDAC2 by ONOO− (Ito et al. 2001, 2004a). 

More recent studies have suggested that acetylate histone 

residues, such as H4, are present to a greater extent in 

lung tissue in smokers and in COPD patients who smoke. 

These increases in H4 are associated with a decrease in 

HDAC2 in COPD patients who smoke and in patients with 

severe COPD (Ito et al. 2005; Szulakowski et al. 2006). A 

correlation has also been shown between decreased HDAC 

activity in lung tissue and FEV1 in patients with COPD.

Apoptosis

There are two types of cell death: apoptosis, which 

is organized and noninflammatory, and necrosis, which 

is unorganized, destructive, and proinflammatory. One 

hypothesis is that loss of alveolar endothelial cells by apoptosis may be an initial event in the development of emphysema (Tuder et al. 2003b). Apoptosis has been shown to 

occur to a greater extent in endothelial cells in emphysematous lungs than in lungs of nonsmokers (Kasahara et 

al. 2001).

Airway lymphocytes (Majo et al. 2001) and stimulated peripheral blood leukocytes (Hodge et al. 2003) from 

patients with COPD also show increased apoptosis. The 

process of endothelial apoptosis is thought to be under 

the influence of VEGFR-2 receptors. Decrease of VEGFR-2 

has been shown to produce emphysema in animals, and 

reduced expression of VEGFR-2 is evident in emphysematous human lungs (Kasahara et al. 2001). Studies have 

also shown that the apoptosis and emphysema induced 

by VEGF inhibition in animal models is associated with 

increased markers of oxidative stress and is prevented by 

antioxidants, suggesting that oxidative stress is involved 

in this process (Tuder et al. 2003c).

Systemic Involvement

Although COPD predominantly affects the lungs, it 

has important systemic consequences, including cachexia 

and skeletal muscle function (Wouters et al. 2002; Langen et al. 2003). Increasing evidence suggests that similar 

mechanisms involving oxidative stress and inflammation 

in the lungs may also be responsible for many of the systemic effects of COPD (Langen et al. 2003).
Surgeon General’s Report

474 Chapter 7

Peripheral blood neutrophils from COPD patients 

have been shown to release more ROS than such neutrophils from unaffected persons (Rahman et al. 1996a). 

Products of lipid peroxidation are also increased in plasma in smokers and patients with COPD (Rahman et al. 

1996a). In addition, increased levels of nitrotyrosine have 

been shown to occur in the plasma of COPD patients (Ichinose et al. 2000).

Patients with COPD often display weight loss, which 

correlates inversely with the occurrence of exacerbations 

and is seen as an independent indicator of outcome (GrayDonald et al. 1996; Landbo et al. 1999). In addition, loss 

of fat-free mass results in peripheral muscle dysfunction, 

decreased exercise capacity, and reduced health status 

(Palange et al. 1995; Baarends et al. 1997; Engelen et al. 

2000b). Several factors influence the loss of weight and 

fat-free mass in COPD patients, including malnutrition, 

imbalance in overall protein turnover and the hormones 

involved in this process, tissue hypoxia, and pulmonary 

inflammation (Jenkins and Ross 1996; Engelen et al. 

2000b; Eid et al. 2001; Wouters et al. 2002).

Oxidative stress may also have a role in the cachexia 

and loss of fat-free mass that occurs in COPD. Skeletal 

muscle is exposed continuously to changes in the redox 

environment that occur during exercise. Several studies have shown evidence of increased oxidative stress in 

patients with COPD both locally and systemically, particularly during exercise (Couillard et al. 2002, 2003; Langen et al. 2003). Presence of lipid peroxidation products 

in the serum, accompanied by an increase in the ratio of 

oxidized to reduced GSH, occur during exercise in COPD 

patients to a greater extent than in healthy persons (Sastre et al. 1992; Viña et al. 1996; Heunks and Dekhuijzen 

2000). Skeletal muscle cells adapt to oxidative stress by 

increasing production of antioxidant enzymes such as 

SOD, catalase, and GPX (Franco et al. 1999). Study findings also showed evidence of disturbed redox homeostasis in COPD associated with emphysema. GSH levels in 

skeletal muscle were lower in COPD patients with emphysema than in those who did not have emphysema and were 

associated with reduced concentrations of glutamate, an 

important substrate in the synthesis of glutamine and 

GSH (Engelen et al. 2000a). Other studies demonstrate 

a decrease in GPX activity, elevated GRX activity, and 

increased lipid peroxidation, which indicate oxidative 

damage in the skeletal muscle of experimental hamsters 

with emphysema (Mattson et al. 2002). These results suggest that GSH metabolism is impaired in COPD.

Increased ROS production in skeletal muscle during 

exercise may result from stimulation of the mitochondrial 

electron-transport chain by TNFα (Li et al. 1999), which 

is known to be elevated in the circulation of patients with 

COPD who lose weight (Di Francia et al. 1994). Leukocytes infiltrating skeletal muscles in COPD patients may 

be another source of ROS (Adams et al. 2002). In addition, 

exercise increases the activity of xanthine and xanthine 

oxidase, a further source of ROS (Andrade et al. 1998). 

ROS also contribute to oxidative stress in muscles, and 

inducible NO expression has been shown to increase in 

skeletal muscle in response to inflammatory cytokines and 

activation of NF-kB (Adams et al. 2002). Oxidative stress 

may directly compromise muscle function by decreasing 

contractility and by increasing the susceptibility of muscle to oxidants (Barclay and Hansel 1991; Andrade et al. 

1998). ROS may also oxidize proteins in the contractile 

apparatus, such as sulfhydryl residues in the contractile 

proteins, which may impair muscle function (MacFarlane 

and Miller 1992). In addition to impairing muscle function, resulting in muscle fatigue, oxidative stress may 

induce muscle atrophy. Atrophy is the result of an imbalance in muscle protein metabolism, which has been 

described in studies showing that oxidative stress induced 

inhibition of muscle-specific protein expression (Buck and 

Chojkier 1996; Langen et al. 2004). Furthermore, oxidative stress may result in apoptosis of muscle cells, which 

has been described in skeletal muscle cells, and may contribute to muscle atrophy (Stangel et al. 1996).

Summary

Considerable evidence now exists for both local and 

systemic oxidative stress in COPD patients. Increasing evidence suggests that oxidative stress is involved in many of 

the pathogenic processes involved in COPD, as well as in 

systemic phenomena such as skeletal muscle dysfunction. 

Cigarette smoke provides an extraordinarily strong dose of 

free radicals to the lung, initiating processes of oxidative 

injury that involve multiple cell types and the entire lung.

Local inflammation results and markers of inflammation 

are higher, both in smokers and in persons with COPD, 

than are those in nonsmokers. Oxidative stress unfavorably tips the protease-antiprotease balance toward protease, leading to tissue damage and COPD.
Pulmonary Diseases 475

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Genetics of Pulmonary Disease and Susceptibility to 

Tobacco Smoke

α1-Antitrypsin Deficiency

Genetic Etiology

AAT deficiency is a long-established genetic risk factor for COPD and a model for the determination of susceptibility to cigarette smoking by causing COPD through 

a genetic mutation. However, only a minority of patients 

with COPD (1 to 2 percent) inherit the severe AAT deficiency that places them at highly increased risk of COPD 

(Lieberman et al. 1986). Consequently, only a small proportion of COPD cases are thought to be attributable 

to this gene-environment interaction (Lieberman et 

al. 1986).

The AAT protein is encoded by the SERPINA1 gene 

on chromosome 14q32.1. Approximately 100 protease 

inhibitor (PI) alleles have been identified, some resulting 

in decreased serum levels of AAT (American Journal of 

Respiratory and Critical Care Medicine 2003). The *M

allele accounts for more than 95 percent of the PI alleles 

in U.S. populations and is associated with normal serum 

levels of AAT (Brantly et al. 1988). The *S allele, which 

leads to mildly reduced AAT levels, and the *Z allele, which 

leads to severely reduced AAT levels, occur at frequencies 

above 1 percent in U.S. populations. A smaller percentage 

of people inherit *NULL alleles, which lead to the absence 

of any AAT production through a heterogeneous set of 

mutational mechanisms. Persons with two *Z alleles or 

one *Z and one *NULL allele are commonly referred to 

as having the PI *Z phenotype, because their serum samples cannot be distinguished by the isoelectric focusing 

technique commonly used to assess PI type (Ogushi et al. 

1987). Persons with PI *Z alleles have approximately 15 

percent of normal serum AAT levels, and this quantitative 

reduction in circulating AAT is the primary determinant 

of increased risk for emphysema. In addition, molecule by 

molecule, the Z protein is a slightly less effective serine PI 

than is the M protein.

Immunologic assay of the AAT level in serum is a 

common test for AAT deficiency, but confirmation of the 

diagnosis of AAT deficiency requires determination of PI 

type, which is typically performed by isoelectric focusing 

of serum in specialized laboratories. Molecular genotyping by polymerase chain reaction can distinguish the common PI alleles (*M, *S, and *Z) with use of DNA from a 

variety of cellular sources (von Ahsen et al. 2000; Stockley 

and Campbell 2001). However, high-throughput complete 

sequencing tests for rare PI alleles are not yet widely available, so rare alleles that produce severe AAT deficiency 

(e.g., *NULL alleles) can be misclassified as normal if 

comprehensive molecular tests are not used.

AAT is one of the serpin protease inhibitors (serpins), an important family of PIs. The association between 

inherited AAT deficiency and pulmonary emphysema was 

critical for the development of the protease-antiprotease 

hypothesis on the pathogenesis of emphysema (Janoff 

1985; Niewoehner 1988; Churg and Wright 2005). AAT 

is the major serum PI of neutrophil elastase, which is 

encoded by the ELA2 gene. Neutrophil elastase is a potent 

elastase considered to be involved in the elastin degradation that leads to emphysema (Travis and Salvesen 1983). 

Although AAT demonstrates some inhibitory activity 

against a range of proteases, it is an extremely effective 

inhibitor of neutrophil elastase (Beatty et al. 1980). The 

functional specificity of AAT is determined by a methionine at amino acid position 358 of the AAT protein, which 

is the PI residue at the active inhibitory site (Mahadeva 

and Lomas 1998). The *Z allele encodes a single base substitution that replaces glutamic acid at amino acid position 342 in the M protein with lysine, thus eliminating a 

critical salt bridge in the AAT protein. The low serum AAT 

levels in PI *Z alleles occur because the Z protein polymerizes within the endoplasmic reticulum of hepatocytes, 

the primary site of AAT synthesis, preventing release of 

the protein. 

The prevalence of AAT deficiency is particularly high 

in populations of Northern European descent. Molecular 

haplotype analysis of polymorphic loci adjacent to the 

AAT *Z allele suggests a single mutational origin for the 

majority of *Z alleles in modern populations, an ancestral 

mutation that likely occurred in Northern Europe (Byth 

et al. 1994). Hutchison (1998), who reviewed the European screening studies for AAT deficiency, found that the 

highest frequencies of the *Z allele were in northwestern 

Europe. Although screening studies have typically found 

low frequencies of the *Z allele in populations of African 

and Asian descent (Kellermann and Walter 1970), the 

review of the worldwide screening literature in control 

cohorts, prepared by de Serres (2002), suggested that 

there could be significant numbers of PI *Z carriers in 

almost every region of the world. These estimates were 

based on calculations assuming Hardy-Weinberg equilibrium and accurate AAT typing in these control populations, but it remains to be determined how significantly 

these estimates were affected by PI typing errors, new 

mutations, or migration from populations in Northern Europe.
Surgeon General’s Report

476 Chapter 7

Natural History

Although increased risk for the development of 

COPD among persons with the PI *Z allele has been well 

established, the magnitude of this risk and the natural history of the entire population with the PI *Z allele remain 

unclear. This population in the United States is estimated 

at 80,000 to 100,000. Among persons known to have the 

PI *Z allele, early-onset COPD is often observed clinically. 

Classic emphysema with the greatest severity in the lower lobes has been described among adults with the PI *Z

allele and COPD, but diffuse or upper lobe emphysema can 

also be observed in this population (Parr et al. 2004). 

Several early studies of large numbers of persons 

with the PI *Z allele demonstrated that PI *Z-type persons 

who smoked cigarettes tended to develop more severe 

COPD at an earlier age than did PI *Z-type persons who 

were nonsmokers (Larsson 1978; Tobin et al. 1983; Janus 

et al. 1985). More recently, Seersholm and colleagues 

(1994) demonstrated significantly higher mortality rates 

in smokers with PI *Z than in nonsmokers with PI *Z. 

Silverman and colleagues (1992) demonstrated an interaction between PI type and cigarette smoking, by comparing the patterns of phenotypic expression in smokers by 

the percentage with specific predicted FEV1 values and the 

patterns in participants with the PI *M, PI *M/*Z, or PI *Z

allele, in the St. Louis Alpha-1-Antitrypsin Study.

The St. Louis Alpha-1-Antitrypsin Study also demonstrated the importance of ascertainment bias in limiting 

insight into the natural history of AAT deficiency. If most 

persons with the PI *Z allele are identified because they 

already have COPD, it would appear that most persons with 

this genotype will develop COPD. Among 52 persons with 

this allele, Silverman and colleagues (1989) confirmed the 

expected result that persons with the PI *Z allele who were 

tested for AAT deficiency because they already had COPD 

(index persons) all had significantly reduced FEV1 values. 

However, marked variability in development of airflow 

obstruction was demonstrated in nonindex persons with 

the PI *Z allele whose genotype was ascertained, not 

because of existing COPD, but by genotyping in family 

studies or because they had liver disease. In Denmark, 

Seersholm and colleagues (1995) confirmed differences 

between lung function in index and nonindex persons 

with the PI *Z allele that were independent of age and 

smoking history.

The PI *Z type is a major risk factor for COPD, and 

cigarette smoking increases the risk for COPD in persons with the PI *Z allele (Silverman et al. 1989). Even 

so, some smokers with PI *Z maintain normal pulmonary 

function into older ages, whereas some nonsmokers with 

PI *Z develop COPD at an early age (Black and Kueppers 

1978). For example, among 18 lifetime nonsmokers with 

the PI *Z allele, the investigators found significant variability in lung function and respiratory symptoms, despite 

the absence of a history of smoking or other significant 

environmental exposures.

In a study of 205 nonsmokers with the PI *Z allele in 

Sweden, Piitulainen and colleagues (1998) observed that 

using a kerosene heater and working in agriculture were 

associated with lower lung function. Among 128 persons 

with PI *Z, Mayer and associates (2000) found that high 

exposure to mineral dust was associated with increased 

cough symptoms and reduced FEV1.

Because less than 10 percent of the estimated total 

of persons with the PI *Z genotype in the United States 

have been identified (American Journal of Respiratory 

and Critical Care Medicine 2003), the natural history of 

COPD in persons with the PI *Z allele remains uncertain. 

In addition to cigarette smoking, other environmental 

factors and genetic modifiers likely influence the development of COPD among persons with PI *Z. Largely in 

response to the underdiagnosis of persons with PI *Z, 

the American Thoracic Society and European Respiratory 

Society Task Force (American Journal of Respiratory and 

Critical Care Medicine 2003) recommended testing for 

AAT deficiency in all adults with COPD, emphysema, or 

asthma with chronic airflow obstruction.

Familial Aggregation of Phenotypes 

Related to Chronic Obstructive 

Pulmonary Disease

Pulmonary Function in the General Population

Several types of studies have suggested that genetic 

factors influence variation in spirometric measurements 

in the general population. Studies of twins who were not 

selected for lung disease have found greater correlations in 

the measure of lung function between monozygotic twins, 

who share all of their genetic variation, than between 

dizygotic twins, who share approximately one-half of their 

genetic variation. Comparison of correlations between 

monozygotic and dizygotic twins allows for estimating 

the heritability of lung function, the percentage of total 

phenotypic variation in lung function that is related to 

genetic factors. For example, in a study of 127 monozygotic and 141 dizygotic twin pairs by the National Heart, 

Lung, and Blood Institute (NHLBI), the estimated heritability for FEV1 values, after adjustment for age, height, 

weight, and smoking was 74 percent (Hubert et al. 1982). 

Redline and colleagues (1987) also observed significantly 

higher correlations for FEV1 between monozygotic twins 

than between dizygotic twins. Tishler and associates 
Pulmonary Diseases 477

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

(2002) studied 352 adult twin pairs and found evidence 

suggesting a relationship between history of cigarette 

smoking and unidentified potential susceptibility genes. 

Studies in nuclear families have also supported a 

role for genetic determinants of pulmonary function in 

the general population; both path analysis and variance 

component analysis have been used. Lewitter and colleagues (1984), who used path analysis in a study of 404 

nuclear families, estimated that 41 to 47 percent of variation in FEV1 values was related to genetic factors. Using 

variance component analysis in a study of 439 persons 

from 108 families, Astemborski and associates (1985) 

estimated that after adjustment for age, gender, race, and 

smoking history, 28 percent of the variation in FEV1 and 

24 percent of the variation in FEV1/FVC were related to 

genetic determinants. More recently, Palmer and colleagues (2001) performed variance component modeling 

of spirometric phenotypes in the Busselton Health Study 

and estimated the heritability of FEV1 as 39 percent. 

Although these studies in the general population provide 

compelling evidence that genetic factors influence variation in level of pulmonary function, they do not necessarily provide insight into the role of genetic factors in the 

development of COPD.

Airflow Obstruction

Studies assessing the role of familial aggregation 

of phenotypes in the occurrence of airflow obstruction in 

relatives of patients with COPD have supported a role for 

genetic factors in the development of COPD. In an early 

study, Larson and colleagues (1970) reported higher rates 

of airflow obstruction in first-degree relatives of COPD 

patients than in the control group. Later, Kueppers and 

associates (1977), who studied 114 persons with COPD, 

compared the spirometric values in siblings with those in 

a matched control group and found that the siblings had 

significantly lower FEV1 values after adjustment for smoking history.

In the Boston Early-Onset COPD Study, Silverman 

and colleagues (1998) focused on persons with severe, 

early-onset COPD without AAT deficiency. Among nonsmokers who were first-degree relatives of these probands 

with early-onset COPD, FEV1 and FEV1/FVC values were 

similar to those in nonsmokers in the control group. 

Using generalized estimating equations to adjust for age 

and pack-years of smoking, the investigators found, however, that current or former smokers among first-degree 

relatives of the probands with early-onset COPD had significantly higher risk for reduced FEV1 values than did 

smokers in the control group. In Great Britain, McCloskey and associates (2001) compared the rates of airflow 

obstruction in 173 siblings of probands who had severe 

COPD with those for a population-based control cohort. 

As was found in the Boston Early-Onset COPD Study, 

nonsmokers who were siblings of COPD patients had 

risk of airflow obstruction similar to that for nonsmokers in the control group. In contrast, current or former 

smokers who were siblings of probands with COPD had 

a significantly higher risk of airflow obstruction than did 

smokers from the general population. The significant 

familial aggregation of phenotypes for airflow obstruction in COPD families, which persists after adjustment for 

intensity of cigarette smoking, strongly suggests genetic 

influences on susceptibility to developing chronic airflow obstruction. 

Chronic Bronchitis

Familial aggregation of chronic cough and production of phlegm (chronic bronchitis) has also been demonstrated. In a sample of 9,226 persons from the general 

population, Higgins and Keller (1975) found significantly 

higher rates of chronic bronchitis in offspring when at 

least one parent had chronic bronchitis than if neither 

parent had the disorder, but there was no adjustment for 

cigarette smoking. Speizer and colleagues (1976), using 

National Health Interview Survey data and adjusting for 

cigarette smoking, demonstrated significantly higher 

rates of bronchitis or emphysema among offspring when 

at least one parent had bronchitis or emphysema. Tager 

and associates (1978) also adjusted for history of cigarette 

smoking in their analysis and found that rates of chronic 

bronchitis or airflow obstruction in first-degree relatives 

of probands with chronic bronchitis or airflow obstruction were significantly higher than those in first-degree 

relatives of the control group. Finally, in the Boston EarlyOnset COPD Study, Silverman and colleagues (1998) 

found significantly higher risk of chronic bronchitis among smokers who were first-degree relatives of 

probands with early-onset COPD than among control 

smokers. This analysis was adjusted for the intensity of 

cigarette smoking. 

Linkage Analysis of Phenotypes 

Related to Chronic Obstructive 

Pulmonary Disease

Several studies of genetic linkage across the 

human genome were perfomed in families from the 

general population who were not selected because of the 

presence of particular respiratory disease (Table 7.8). The 

purpose was to examine the relationship between spirometric values and genetic determinants of pulmonary 
Surgeon General’s Report

478 Chapter 7

function. These genetic determinants may predispose 

family members to COPD, or they may only contribute 

to variation in pulmonary function within the normal 

range. Joost and colleagues (2002) analyzed linkage to 

quantitative spirometric measurements made before use 

of a bronchodilator in 1,578 persons from 330 pedigrees 

in the Framingham Heart Study. The largest linkage signal, which did not reach the criteria for genomewide significance, was on chromosome 6q for prebronchodilator 

FEV1. The score of the logarithm of the odds (LOD) ratio, 

or likelihood ratio, was 2.4. In a subset of this study population, flanking short tandem repeat (STR) markers were 

Table 7.8 Genomewide linkage analysis studies in general-population samples and in families with chronic 

obstructive pulmonary disease (COPD) 

Study Study design Sample size Phenotype

Chromosomal 

region/ 

maximum limit 

of detection 

scorea Comments

General 

Population               

Joost et al. 

2002

Framingham Heart 

Study pedigrees

1,578 persons 

330 pedigrees

FEV1 •	 4p: 1.6

•	 6q: 2.4

  

Malhotra et al. 

2003

Extended Utah 

Centre d’Etude du 

Polymorphisme 

Humain pedigrees

264 persons 

26 pedigrees

FEV1/FVC •	 2q: 2.0 Parametric limit of 

detection score without 

heterogeneity showed 

most significant linkage 

evidence on 2q

Wilk et al. 

2003a

Family Heart Study 

pedigrees

2,178 persons 

391 pedigrees

FEV1

FEV1/FVC

•	 3q: 2.0

•	 1p: 1.7

•	 4p: 3.5

•	 9p: 2.0

•	 17p: 2.3

Untransformed values 

were reported; 

normalized values were 

also analyzed

Boston EarlyOnset COPD 

Study

              

Silverman et 

al. 2002a

Extended pedigrees 

ascertained in 

proband with earlyonset COPD

585 persons 

72 pedigrees

Moderate airflow 

obstruction

•	 12p: 1.7

•	 19q: 1.5

Some regions 

demonstrated increased 

limit of detection scores 

for smokers only

Palmer et al. 

2003

Extended pedigrees 

ascertained in 

proband with earlyonset COPD

Same 

population

560 persons 

with 

spirometry

FEV1 

(postbronchodilation)

FEV1/FVC 

(postbronchodilation)

•	 1p: 2.2

•	 8p: 3.3

•	 8q: 2.0

•	 19q: 1.9

•	 1p: 2.5

•	 2q: 4.4

•	 17q: 2.4

  

DeMeo et al. 

2004

Extended pedigrees 

ascertained in 

proband with earlyonset COPD

Same 

population

FEF25–75 

(postbronchodilation)

FEF25–75/FVC 

(postbronchodilation)

•	 8p: 1.8

•	 12p: 1.7

•	 2q: 2.6

  

Note: FEF25–75 = forced expiratory flow between 25 and 75 percent of FVC; FEV1 = forced expiratory volume in 1 second; 

FVC = forced vital capacity. aLimit of detection scores >1.5 are presented.
Pulmonary Diseases 479

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

genotyped to increase the information available for linkage analysis, and significant linkage of FEV1 to chromosome 6q was identified with a maximum LOD score of 5.0 

(Wilk et al. 2003b).

Wilk and colleagues (2003a) performed genomewide linkage analysis with prebronchodilator spirometric 

phenotypes in 2,178 participants in the NHLBI Family 

Heart Study, a population that partially overlapped that 

with the pedigrees from the Framingham Heart Study 

used by Joost and colleagues (2002). Even so, the linkage 

results differed substantially from those in the Framingham Heart Study. The most impressive signals suggested 

linkage of FEV1 to chromosome 3q and FEV1/FVC to chromosome 4p. 

Finally, Malhotra and associates (2003) performed 

genomewide linkage analysis of quantitative prebronchodilator spirometric measurements in extended pedigrees. 

The findings suggested linkage of FEV1/FVC values to 

chromosome 2q and to chromosome 5q but no linkage for 

either FEV1 or FVC. 

Chronic Obstructive Pulmonary 

Disease in Families

The Boston Early-Onset COPD Study includes 

extended pedigrees obtained through persons with severe 

early-onset COPD but without AAT deficiency. Genomewide linkage analysis has been performed with 585 members of 72 pedigrees involving early-onset COPD (Table 

7.8). Initially, qualitative phenotypes of airflow obstruction and chronic bronchitis were analyzed, and no statistically significant or even suggestive regions of linkage were 

identified (Silverman et al. 2002a). Although limiting the 

sample to smokers only and genotyping of flanking STR 

markers identified several linkage regions of potential 

interest, linkage analysis of quantitative spirometric phenotypes provided more compelling evidence for linkage, 

especially with use of postbronchodilator spirometric 

values (Silverman et al. 2002b; Palmer et al. 2003). Findings suggested linkage of the postbronchodilator values 

of FEV1 to chromosomes 8p (LOD = 3.30) and 1p (LOD 

= 2.24). Postbronchodilator FEV1/FVC was also linked to 

multiple regions, most significantly to markers on chromosomes 2q (LOD = 4.42) and 1p (LOD = 2.52).

Genotyping additional STR markers and repeating 

linkage analysis of quantitative spirometric phenotypes 

provided stable-to-increased evidence for linkage on chromosomes 2q, 12p, and 19q (Celedón et al. 2004; DeMeo et 

al. 2004). Stratified linkage analysis of samples only from 

smokers also provided stable-to-increased evidence for 

linkage to these genomic regions. Findings suggested that 

genetic determinants in those regions confer increased 

risk for COPD because of a relationship between history of 

cigarette smoking and unidentified potential susceptibility genes. 

Overall, the linkage results of quantitative spirometric measurements in the persons with pedigrees from the 

Boston Early-Onset COPD Study (Hersh et al. 2005) and 

samples from the general population have demonstrated 

only modest concordance. The most impressive linkage 

signals in the study have been obtained with postbronchodilator spirometric measures, which have not been used in 

the linkage studies of the general population. The Boston 

Early-Onset COPD Study demonstrated linkage of FEV1/

FVC to chromosome 2q. The suggestive linkages of FEV1/

FVC to chromosome 1p in the NHLBI Family Heart Study 

and the Boston Early-Onset COPD Study indicate a region 

that may influence spirometric measurements in both the 

general population and persons with COPD. One explanation for inconsistent linkage results in studies of COPD 

families and studies of pedigrees in the general population 

is that different genetic determinants could influence normal variation in spirometry and COPD. In addition, the 

lack of concordance among results from linkage studies in 

the general population could relate to genetic heterogeneity among study populations, false-positive evidence for 

linkage in some regions, or inadequate power of the study 

to replicate linkage signals.

Genetic Association with Chronic 

Obstructive Pulmonary Disease

A large number of studies to determine associations 

have assessed genetic variants in candidate genes hypothesized to be involved in the development of COPD. These 

were primarily case-control studies of patients with COPD 

and control groups. Candidate gene loci significantly 

associated with COPD in at least two studies are listed in 

Table 7.9. In addition to the PI *M/*Z genotype of AAT, 

which has been variably associated with COPD (Hersh et 

al. 2004), replicated associations have been demonstrated 

for genes of α1-antichymotrypsin (SERPINA3) (Poller et 

al. 1993; Sandford et al. 1998; Benetazzo et al. 1999; Ishii 

et al. 2000a), GSTM1 (GSTM1) (Baranova et al. 1997; Harrison et al. 1997; Yim et al. 2000; He et al. 2004), GSTP1 

(GSTP1) (Ishii et al. 1999; Yim et al. 2002; He et al. 2004), 

vitamin D binding protein (GC) (Kauffmann et al. 1983; 

Horne et al. 1990; Schellenberg et al. 1998; Ishii et al. 

2001; Sandford et al. 2001; Kasuga et al. 2003; Ito et al. 

2004b), TGFβ1 (TGFß1) (Celedón et al. 2004; Wu et al. 

2004), TNF (TNF) (Huang et al. 1997; Higham et al. 2000; 

Ishii et al. 2000b; Patuzzo et al. 2000; Sakao et al. 2001; 
Surgeon General’s Report

480 Chapter 7

Table 7.9 Replicated candidate gene associations in chronic obstructive pulmonary disease (COPD)

Study Sample size Genetic variants studied

α1-antitrypsin PI 

*M/*Z heterozygotes      

Hersh et al. 2004 >100 studies

Meta-analysis

PI *M/*Z heterozygotes

TGFß1      

Celedon et al. 2004 585 persons in 72 pedigrees

304 cases vs. 441 controls

5 SNPs (including same exonic SNP)

Wu et al. 2004 165 cases vs. 146 blood donor controls

76 healthy smokers

1 exonic SNP

EPHX1      

Smith and Harrison 1997 68 COPD cases

94 emphysema cases vs. 203 blood donor controls

Exon 3 nonsynonymous SNP (slow) and Exon 

4 nonsynonymous SNP (fast)

Takeyabu et al. 2000 79 emphysema cases vs. 58 smoking controls and 

114 healthy controls

Exon 3 and 4 SNPs

Yim et al. 2000 83 cases vs. 76 smoking controls Exon 3 and 4 SNPs

Yoshikawa et al. 2000 40 COPD cases and 140 controls among poison-gas 

workers

Exon 3 and 4 SNPs

Sandford et al. 2001 283 COPD persons with rapid FEV1 decline vs. 308 

COPD persons with slow FEV1 decline in the U.S. 

Lung Health Study

Exon 3 and 4 SNPs

Hersh et al. 2005 949 persons in 127 pedigrees with early-onset COPD

304 cases vs. 441 smoking controls

8 SNPs including Exon 3 and 4 SNPs

TNFα      

Huang et al. 1997 42 cases vs. 42 smoking controls and 99 blood donor 

controls

1 promoter SNP at -308

Higham et al. 2000 86 cases vs. 63 smoking controls and 199 blood 

donor controls

-308 SNP

Ishii et al. 2000b 53 cases vs. 65 smoking controls -308 SNP

Patuzzo et al. 2000 66 cases vs. 98 healthy controls and 45 cases of 

nonobstructive pulmonary disease

-308 SNP
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Study Phenotype Results/p value for association Comments

α1-antitrypsin PI 

*M/*Z heterozygotes

  

     

Hersh et al. 2004 Presence or absence of COPD

FEV1 in persons with PI *M/*Z vs. 

PI *M/*M alleles

Typically positive

Typically negative

No overall consensus 

on risk for lung disease 

in persons with 

PI *M/*Z alleles

TGFß1         

Celedon et al. 2004 Families with early-onset COPD: qualitative 

and quantitative airflow obstruction 

phenotypesa

Case/control: presence/absence of COPD

3 significant SNPs at p <0.05 (1 

promoter and 2 in the 3’ genomic 

region)

3 significant SNPs at p <0.05 (2 

promoter SNPs and 1 exonic SNP)

1 promoter SNP 

replicated in both 

study populations

Wu et al. 2004 Presence/absence of COPD p ≤0.01 vs. both control groups Exonic SNP replicated 

in both case-control 

studies but not in 

family-based study

EPHX1         

Smith and Harrison 

1997

Presence/absence of COPD or emphysema Significant associations of exon 3 

SNP with emphysema group and 

of exon 4 SNP with COPD group

Several negative studies 

had small samples

Takeyabu et al. 2000 Presence/absence of emphysema No significant association   

Yim et al. 2000 Presence/absence of COPD No significant association   

Yoshikawa et al. 2000 Presence/absence of COPD No significant association   

Sandford et al. 2001 Rapid vs. slow FEV1 decline in persons with 

COPD

Significant association of exons 3 

and 4 SNP haplotypes with rapid 

FEV1 decline

  

Hersh et al. 2005 Families with early-onset COPD: 

quantitative and qualitative airflow 

obstruction phenotypesa

Case/control: presence/absence of COPD

Significant association of exon 4 

SNP only in case-control sample

  

TNFα         

Huang et al. 1997 Presence/absence of COPD with chronic 

bronchitis

Significant association vs. both 

control groups (p <0.001)

Several studies with 

significant associations, 

but many negative 

studies; many studies 

had small sample sizes

Higham et al. 2000 Presence/absence of COPD No significant association   

Ishii et al. 2000b Presence/absence of COPD No significant association   

Patuzzo et al. 2000 Presence/absence of COPD No significant association   
Surgeon General’s Report

482 Chapter 7

Table 7.9 Continued

Study Sample size Genetic variants studied

Sakao et al. 2001 106 cases vs. 110 smoking controls and 129 blood 

donor controls

-308 SNP

Sandford et al. 2001 283 cases with rapid vs. 304 cases with slow FEV1

decline `U.S. Lung Health Study

-308 SNP

Kucukaycan et al. 2002 169 cases vs. 358 blood donor controls 4 SNPs including -308 and +489

Ferrarotti et al. 2003 63 cases vs. 86 smoking controls -308 SNP

Hersh et al. 2005 949 members of 127 pedigrees with early-onset 

COPD and 304 cases vs. 441 smoking controls

5 SNPs including -308 and +489

GSTM1      

Baranova et al. 1997 87 cases of severe chronic bronchitis vs. 102 cases 

of moderate chronic bronchitis vs. 172 smoking 

controls

Null variant

Harrison et al. 1997 111 lung cancer patients with emphysema vs. 57 

without emphysema

Null variant (homozygous null vs. all others)

Yim et al. 2000 83 cases vs. 76 smoking controls Null variant

He et al. 2004 544 persons with COPD and low FEV1 vs. 554 with 

high FEV1 U.S. Lung Health Study

Null variant

Hersh et al. 2005 Families with early-onset COPD: 949 persons in 127 

pedigrees

Case/control: 304 cases vs. 441 smoking controls

Null variant

GSTP1      

Ishii et al. 1999 53 cases vs. 50 healthy controls 1 nonsynonymous SNP (ILE105VAL)

Yim et al. 2002 89 cases vs. 94 smoking controls 1 nonsynonymous SNP (ILE105VAL)

He et al. 2004 544 persons with COPD and low FEV1 vs. 554 with 

high FEV1

U.S. Lung Health Study

1 nonsynonymous SNP (ILE105VAL)

Hersh et al. 2005 949 members of 127 pedigrees with early-onset 

COPD and 304 cases vs. 441 smoking controls

2 nonsynonymous SNPs (ILE105VAL and 

ALA114VAL)
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Study Phenotype Results/p value for association Comments

Sakao et al. 2001 Presence/absence of COPD Significant differences in allele 

frequencies in COPD cases vs. both 

control groups 

(p <0.01)

  

Sandford et al. 2001 Rapid vs. slow FEV1 decline in persons with 

COPD

No significant association   

Kucukaycan et al. 2002 Presence/absence of COPD Significant association with +489 

variant only

  

Ferrarotti et al. 2003 Presence/absence of COPD with reduced 

Dl,co

No significant association   

Hersh et al. 2005 Families with early-onset COPD: 

quantitative and qualitative airflow 

obstruction phenotypesa

Case/control: presence/absence of COPD

Significant associations with 

qualitative and quantitative airflow 

obstruction phenotypes with SNP 

-308 in COPD pedigrees only

  

GSTM1         

Baranova et al. 1997 Presence/absence of COPD Higher null/null frequency in 

both cases of moderate and severe 

chronic bronchitis and severe 

chronic bronchitis vs. controls (p 

<0.001)

  

Harrison et al. 1997 Presence/absence of emphysema in resected 

lung tissue

Significantly increased frequency 

of homozygosity for null variant in 

persons with emphysema (p <0.05)

Only homozygosity 

for null variant was 

typically assessed

Yim et al. 2000 Presence/absence of COPD No significant association   

He et al. 2004 High vs. low FEV1 in persons with COPD No significant association   

Hersh et al. 2005 Families with early-onset COPD: qualitative 

and quantitative airflow obstruction 

phenotypesa

Case/control: presence/absence of COPD

No significant association   

GSTP1         

Ishii et al. 1999 Presence/absence of COPD Homozygous 105ILE more 

common in COPD cases

Several studies with 

significant associations, 

but different alleles, 

are associated at 

amino acid 105 SNP in 

different studies

Yim et al. 2002 Presence/absence of COPD No significant association   

He et al. 2004 High vs. low FEV1 in persons with COPD Homozygous 105VAL gene more 

common in low FEV1 group

Hersh et al. 2005 Families with early-onset COPD: qualitative 

and quantitative airflow obstruction 

phenotypesa

Case/control: presence/absence of COPD

Borderline higher frequency of 

*105VAL allele in case-control 

analysis only

  
Surgeon General’s Report

484 Chapter 7

Study Sample size Genetic variants studied

SFTPB      

Guo et al. 2001 97 cases vs. 82 smoking controls 4 SNPs, 1 promoter, and 3 intragenic indels

Seifart et al. 2002 118 cases vs. 118 matched controls and 110 

population-based controls

SP-B INTRON 4 indels

Hersh et al. 2005 949 members of 127 pedigrees with early-onset 

COPD and 304 cases vs. 441 smoking controls

1 nonsynonymous SNP (THR131IL3) and 1 

short tandem repeat

α1-antichymotrypsin      

Poller et al. 1993 100 COPD cases vs. 100 controls 2 nonsynonymous SNPs: PRO229ALA and 

LEU55PRO

Sandford et al. 1998 168 COPD cases vs. 61 controls PRO229ALA and LEU55PRO

Benetazzo et al. 1999 66 COPD cases vs. 45 controls with nonobstructive 

pulmonary disease and 98 healthy volunteers

4 coding SNPs (THR15ALA, LEU55PRO, 

PRO229ALA, and MET389VAL) and 1 indel 

(1258DELAA)

Ishii et al. 2000a 53 COPD cases vs. 65 controls 2 coding SNPs in protein (PRO229ALA and 

LEU55PRO) and 1 coding SNP in signal 

peptide (ALA15THR)

Hersh et al. 2005 949 members of 127 pedigrees with early-onset 

COPD and 304 cases vs. 441 smoking controls

ALA15THR, LEU55PRO, and PRO229ALA

polymorphisms

Vitamin D binding protein 

(group-specific component 

[GC])      

Kauffmann et al. 1983 43 lifetime nonsmokers with low FEV1 vs. 45 heavy 

smokers with high FEV1

GC*1S/F and GC*2 alleles

Horne et al. 1990 104 COPD cases vs. 413 controls GC phenotype by isoelectric focusing

Schellenberg et al. 1998 75 COPD cases vs. 64 smoking controls SNPs THR420LYS (GC*2) and ASP416GLU

(GC*1S)

Ishii et al. 2001 63 COPD cases vs. 82 controls GC*1F/*1S and GC*2 alleles

Sandford et al. 2001 283 persons with COPD with rapid FEV1 decline vs. 

308 persons with COPD with slow FEV1 decline

THR420LYS and ASP416GLU polymorphisms

Kasuga et al. 2003 537 persons with COPD with high FEV1 vs. 533 with 

low FEV1

U.S. Lung Health Study

GC* haplotypes

Table 7.9 Continued
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Study Phenotype Results/p value for association Comments

SFTPB         

Guo et al. 2001 Presence/absence of COPD Significant association with SNP at 

+1580 (p <0.05)

  

Seifart et al. 2002 Presence/absence of COPD and COPD 

severity

INTRON 4 variants significantly 

associated 

(p <0.05) with respiratory failure 

subgroup

  

Hersh et al. 2005 Families with early-onset COPD: 

quantitative and qualitative airflow 

obstruction phenotypesa

Case/control: presence/absence of COPD

Significant SNP association 

with moderate-to-severe airflow 

obstruction (p <0.05)

Significant SNP association only 

with gene-x-smoking interaction 

term (p <0.01)

  

α1-antichymotrypsin         

Poller et al. 1993 Presence/absence of COPD Significant SNP association (p 

<0.05) with PRO229ALA

No studies replicated 

associations of the same 

genetic variants

Sandford et al. 1998 Presence/absence of COPD No significant association   

Benetazzo et al. 1999 Presence/absence of COPD No significant association   

Ishii et al. 2000a Presence/absence of COPD Significant SNP association with 

ALA15THR only

  

Hersh et al. 2005 Families with early-onset COPD: 

quantitative and qualitative airflow 

obstruction phenotypesa

Case/control: presence/absence of COPD

No significant association   

Vitamin D binding 

protein (group-specific 

component [GC])

  

     

Kauffmann et al. 1983 Presence/absence of COPD No significant association   

Horne et al. 1990 Presence/absence of COPD Significant association with 

inferred GC* allele (p <0.01)

  

Schellenberg et al. 1998 Presence/absence of COPD Significant protection against 

COPD with GC*2/GC*2 genotype

  

Ishii et al. 2001 Presence/absence of COPD Significantly increased frequency 

of GC*1F allele in COPD cases

  

Sandford et al. 2001 Rapid vs. slow FEV1 decline in COPD cases No significant association   

Kasuga et al. 2003 High vs. low FEV1 among COPD cases No significant association   
Surgeon General’s Report

486 Chapter 7

Study Sample size Genetic variants studied

Ito et al. 2004b 103 COPD cases vs. 88 smoking controls GC*1S/*1F and GC*2

Hersh et al. 2005 949 members of 127 pedigrees with early-onset 

COPD and 304 cases vs. 441 smoking controls

THR420LYS and ASP416GLU

Note: Dl,co = diffusing capacity of the lung for carbon monoxide; FEV1 = forced expiratory volume in 1 second; FVC = forced vital 

capacity; indel = DNA mutation; PI = protease inhibitor; SNP = single nucleotide polymorphism; SP-B = surfactant protein B. aIn families with early-onset COPD, quantitative spirometric phenotypes included FEV1/FVC before and after use of a bronchodilator; 

qualitative phenotypes included mild-to-severe airflow obstruction (FEV1 <80% predicted with FEV1/FVC <90% predicted) and 

moderate-to-severe airflow obstruction (FEV1 <60% predicted with FEV1/FVC <90% predicted).

Table 7.9 Continued

Sandford et al. 2001; Küçükaycan et al. 2002; Ferrarotti et 

al. 2003), surfactant protein B (SFTPB) (Guo et al. 2001; 

Seifart et al. 2002; Hersh et al. 2005), and microsomal 

epoxide hydrolase (EPHX1) (Smith and Harrison 1997; 

Takeyabu et al. 2000; Yim et al. 2000; Yoshikawa et al. 

2000; Sandford et al. 2001). Although at least two studies support an association of a genetic variant with COPD 

in these candidate genes, every case also has at least one 

negative study.

Several factors could contribute to the inconsistent 

results from case-control studies of genetic association 

with COPD. Genetic heterogeneity in different populations could contribute to difficulty in replicating associations between studies, and false-positive or false-negative 

results could contribute to inconsistent replication. A 

potentially important factor is that case-control studies 

of association are susceptible to supporting associations 

based only on population stratification; that is, they reflect 

differences between populations rather than true associations (Freedman et al. 2004). Population stratification can 

result from incomplete matching between cases and controls, which might include failure to account for differences in ethnicity and geographic origin that may affect 

the results. In addition, most published studies on genetic 

associations of COPD have not focused on genomic 

regions linked to COPD-related phenotypes, regions in 

which association studies may be more fruitful. 

As of 2008, only one study, a linkage analysis of familybased genetic association for COPD, has been reported (Celedón 

et al. 2004). The design of the study is typically not vulnerable to 

effects of population stratification. The study focused on genetic variants in TGFß1, a gene that is located within the region of 

linkage to FEV1 on chromosome 19q in the Boston Early-Onset COPD Study and that was associated with COPD in another 

case-control study of genetic association (Wu et al. 2004). Five 

TGFß1 single nucleotide polymorphisms (SNPs) were genotyped in families in the Boston Early-Onset COPD Study. Family-based association analysis showed that one SNP in the promoter region of TGFß1 (RS2241712) and two SNPs in the 3’

untranslated region of TGFß1 (RS2241718 and RS6957) 

were significantly associated with FEV1 (p <0.05). Among 

304 case patients with severe COPD from the National 

Emphysema Treatment Trial and 441 smokers in the control 

group from the Normative Aging Study, two SNPs in the promoter region of TGFß1 (RS2241712 and RS1800469) and one 

SNP in exon 1 of TGFß1 (RS1982073) were significantly associated with COPD (p ≤0.02) (Celedón et al. 2004). Additional 

research to replicate the genetic associations in TGFß1 and 

identify the functional variants in or near TGFß1 is required. 

A variety of candidate genes have been examined 

in genetic association studies focused on COPD, but no 

genetic loci other than the SERPINA1 gene for severe AAT 

deficiency proved to be significant risk factors for COPD. 

Mouse Models of Genetics for 

Chronic Obstructive Pulmonary 

Disease

Although rodent models have provided important insights into the potential biochemical mechanisms of COPD, 

there has been no publication of research using quantitive trait 

locus mapping to identify susceptibility loci through experimental crosses of relatively susceptible and relatively nonsusceptible strains. Significant differences between murine strains 

in susceptibility to the development of smoking-induced 

COPD have been demonstrated (Guerassimov et al. 2004), and 

use of these strain-specific differences to perform quantitative trait locus mapping may provide unique opportunities to 

uncover genetic determinants of COPD (Shapiro et 

al. 2004).
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Study Phenotype Results/p value for association Comments

Ito et al. 2004b Presence/absence of COPD Significantly increased frequency 

of 

GC*1F allele in COPD cases

  

Hersh et al. 2005 Families with early-onset COPD: 

quantitative and qualitative airflow 

obstruction phenotypesa

Case/control: presence/absence of COPD

No significant association   

Summary

Severe AAT deficiency is a proven genetic risk factor for COPD. Although considerable insight into the 

pathogenesis of COPD has been provided by studies of AAT 

deficiency, fundamental questions about the natural history of this deficiency remain unanswered.

Only a small percentage of patients with COPD 

inherit severe AAT deficiency, and additional genetic factors likely influence the development of the disorder. 

Further efforts in linkage analysis, association studies, 

and research on animal models may lead to identification 

of such factors. To achieve a complete understanding of 

COPD pathophysiology, characterization of the interactions among genetic determinants, cigarette smoking, 

and possibly other environmental factors is required. 

Identification of genetic factors influencing the development of COPD unrelated to AAT deficiency could elucidate the biochemical mechanisms causing COPD, allow 

identification of more susceptible persons, and lead to new 

therapeutic interventions as pathways of injury are better characterized.

Pathogenesis of Emphysema

Sources of Information

The information on pathogenesis of emphysema discussed here was obtained from original research articles, 

most published since the early 1990s. These articles were 

found by consulting reviews of the literature (Pardo and 

Selman 1999; Mahadeva and Shapiro 2002; Barnes et al. 

2003; Tuder et al. 2003a; Barnes 2004b; MacNee 2005b) 

and by searching the Internet with use of a variety of 

terms relevant to the pathogenesis of emphysema. The 

review includes citations through June 2005. 

In reviewing the literature, special attention was 

paid to reports that distinguished between “emphysema” 

and the all-encompassing term “chronic obstructive pulmonary disease.” In recent years this distinction has been 

made by using chest CT and microscopy of lung tissue. 

Introduction

One long-accepted definition of emphysema is “a 

condition of the lung characterized by abnormal, permanent enlargement of air spaces distal to the terminal bronchiole, accompanied by destruction of their walls, and 

without obvious fibrosis” (Snider et al. 1985, p. 183). This 

definition emphasizes the loss of alveolar tissue. However, 

in emphysema induced by tobacco smoke, the lung tissue 

exhibits active synthesis of extracellular matrix (Lang et 

al. 1994; Wright and Churg 1995; Vlahovic et al. 1999), 

apoptosis, and proliferation of alveolar cells (Calabrese et 

al. 2005). Accordingly, emphysematous lung tissue should 

be viewed as undergoing remodeling rather than simply 

resulting from a destructive process. 

The current model of the pathogenesis of emphysema, which involves diverse processes of varying importance, is summarized in Figure 7.18. In this pathogenetic 
Surgeon General’s Report

488 Chapter 7

scheme, accumulation of inflammatory cells in the peripheral tissues of smokers’ lungs appears to be pivotal (Finkelstein et al. 1995; Abboud et al. 1998), and proteases 

from inflammatory cells have multiple potential roles in 

causing injury. 

Inflammatory cells linked to the development of 

emphysema include neutrophils, macrophages, and lymphocytes. How inflammatory cells are first recruited and 

activated in response to smoking remains incompletely 

understood, but the inflammatory process, once initiated, can persist for years after smoking has stopped. Thus, 

emphysematous tissues from transplant surgery and surgery to reduce lung volume show large numbers of inflammatory cells, even among persons who stopped smoking 

long before the surgery (Retamales et al. 2001; Shapiro 

2001). In addition, some evidence from serial chest CT 

examinations indicates that emphysema also progresses 

after the cessation of smoking (Soejima et al. 2000). Products of neutrophils and macrophages can degrade extracellular matrix, inactivate PIs, and convert proenzymes to 

their active matrix-degrading form. 

The role of lymphocytes in emphysema has been a 

topic of research over the past decade (Finkelstein et al. 

1995; Cosio et al. 2002; Boschetto et al. 2003), and findings indicate that T-cell factors can induce macrophages 

to express proteases (Grumelli et al. 2004). ROS, both in 

cigarette smoke and released by inflammatory cells or epithelial cells, impinge on protease-antiprotease balance in 

the lungs in multiple ways, including inactivation of AAT, 

increased expression of chemokines such as IL-8, activation of MMPs, and induction of the transcription of NF-κB, 

leading to increased expression of MMPs (MacNee 2005b). 

Three discoveries in the 1960s linked elastases to 

emphysema: (1) association between early-age onset of 

Figure 7.18 Pathogenesis of smoking-induced pulmonary emphysema

Note: Three pathways for pathogenesis are shown. The circles indicate steps in which proteases are or may be involved. (1) Smoke 

components recruit inflammatory cells to the lower respiratory system via factors released from alveolar macrophages and structural 

cells of the lungs. Recruited cells, macrophages, and structural cells release proteases and reactive oxygen species that degrade the 

extracellular matrix of the respiratory tissues. (2) Smoke components directly affect viability of lung cells, leading to liberation of 

proteases that can degrade lung matrix. (3) Smoke components may disrupt the function of protease inhibitors such as a1-antitrypsin, 

facilitating the activity of proteases. AAT = a1-antitrypsin; PMNs = polymorphonuclear neutrophils.
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

emphysema and deficiency of AAT (Eriksson 1965); (2) 

production of emphysema in experimental animals by 

putting elastolytic proteases, such as papain, directly 

into the lung (Gross et al. 1965); and (3) demonstration 

that neutrophils contain and release a potent elastolytic 

enzyme (Janoff and Scherer 1968). Together, these discoveries led to formulation of the “elastase-antielastase” 

hypothesis for the pathogenesis of emphysema. This 

hypothesis posits development of emphysema in response 

to unchecked intrapulmonary activity of neutrophil elastase due to an excess of inflammatory cells, a deficiency 

of intrapulmonary elastase inhibition, or a combination 

of increased elastolytic burden and decreased elastase 

inhibitory capacity. This hypothesis remains tenable, but 

it does not incorporate more recent data indicating that 

(1) MMPs, including collagenases from inflammatory 

cells and lung structural cells (Table 7.10) (Foronjy and 

D’Armiento 2001), are associated with emphysema and (2) 

the destruction of alveolar walls in emphysema may begin 

with death of alveolar cells rather than with degradation 

of the alveolar extracellular matrix (Kasahara et al. 2001; 

Aoshiba et al. 2003b; Tuder et al. 2003b). 

Proteases

Data from Human Studies

Several types of data link proteases to the causation of emphysema in humans: (1) assays of proteolytic 

Table 7.10 Matrix metalloproteinases in emphysema

Study

Emphysema 

detection Test samples Observations Comments

Finlay et al.

1997a

Computed 

tomography 

AM mRNA and 

culture media

•	 Increased collagenase 1 (MMP-1)

•	 Increased gelatinase B (MMP-9)

No increase in expression 

of macrophage elastase 

(MMP-12)

Finlay et al. 

1997b

Computed 

tomography 

BAL fluid •	 Increased collagenase activity

•	 Increased gelatinase B (MMP-9)

MMPs probably neutrophil 

derived 

Ohnishi et al.

1998

Histology Lung tissue from 

LVRS

•	 Increased MT-MMP-1 (MMP-14)

•	 Increased gelatinase A (MMP-2)

No increase in expression 

of macrophage elastase 

(MMP-12)

Betsuyaku et al. 

1999

Computed 

tomography

BAL fluid and AM 

culture media

•	 Increased collagenase 2 (MMP-8)

•	 Increased gelatinase B (MMP-9)

MMPs in BAL fluid from 

inflammatory cells; no 

increase in gelatinase B 

(MMP-9) in AM culture 

media in emphysema 

Segura-Valdez 

et al. 2000

Histology Lung tissue from 

autopsy and LVRS; 

BAL fluid

•	 Increased collagenases 1, 2, 3

(MMP-1, -8, -13)

•	 Increased gelatinases A, B

(MMP-2, -9)

MMPs expressed by both 

inflammatory cells and 

structural cells of lung

Imai et al. 2001 Histology Lung tissue from 

lung transplantation 

and LVRS

•	 Increased collagenase 1 (MMP-1) Collagenase expressed by 

type II cells; no increase in 

expression of macrophage 

elastase (MMP-12) 

Minematsu et 

al. 2001

Computed 

tomography

Cellular DNA •	 Increased gelatinase B (MMP-9)

polymorphism in smokers with 

emphysema

Polymorphism also 

associated with increased 

incidence of coronary 

atherosclerosis

Source: Adapted from Hogg and Senior 2002 with permission from BMJ Publishing Group Ltd., © 2002.

Note: AM = alveolar macrophage; BAL = bronchoalveolar lavage; LVRS = lung volume reduction surgery; MMP = matrix 

metalloproteinase; mRNA = messenger RNA; MT = membrane type. 
Surgeon General’s Report

490 Chapter 7

activity and protease content in BAL fluid; (2) measurements of protease proteins, proteolytic activities, and protease mRNAs associated with alveolar macrophages from 

emphysematous lung; (3) immunostains of proteases in 

emphysematous tissue; and (4) determinations of protease mRNAs in lung tissue. The association between AAT 

deficiency and emphysema is perhaps the strongest evidence (American Journal of Respiratory and Critical Care 

Medicine 2003).

Bronchoalveolar Lavage

The BAL technique samples cells and mediators 

from the lower respiratory tract, but in COPD the volumes 

of lavage recovered are often low (Linden et al. 1993; Soler 

et al. 1999), and the presence of emphysema adversely 

influences the recovery of BAL fluid (Löfdahl et al. 2005). 

In one study of patients with COPD who were scored for 

emphysema by chest CT, patients with high scores had 

recoveries of fluid less than one-half the volume for those 

with low scores. 

Numerous studies have examined proteases in BAL 

fluid. In studies with evaluation for emphysema, it appears 

that protease levels were higher in some persons with 

emphysema than they were in control groups (Muley et 

al. 1994; Yoshioka et al. 1995; Betsuyaku et al. 1995, 1996, 

1999, 2002, 2003; Finlay et al. 1997a,b; Abboud et al. 1998; 

Takeyabu et al. 1998). The proteases included elastase, 

both free and in complex with AAT; MMP-1, -8, -9, -12, and 

-14; and cysteine proteases. However, interpretation of 

these data is limited by three considerations: (1) although 

emphysema is documented by CT, quantification of the 

emphysema is not reported in most studies; (2) studies do 

not always explicitly state whether persons with emphysema are current smokers; and (3) some control groups 

included nonsmokers and smokers. Regardless of these 

problems, the presence of emphysema is associated with 

no more than modest, approximately twofold, increases in 

proteases.

Numerous factors are known to regulate MMPs, a 

class of proteases increasingly implicated in emphysema, 

but few studies have assessed the expression of MMP regulatory factors in the context of emphysema. In one study, 

levels of the extracellular MMP inducer, basigin, a transmembrane protein that stimulates production of several 

MMPs, were much higher in BAL fluid from current and 

former smokers than from those who never smoked (Betsuyaku et al. 2003). Among smokers, however, levels did 

not differ for persons with or without emphysema.

Alveolar Macrophages

Alveolar macrophages appear to have a central 

role in orchestrating inflammation in COPD through 

production of cytokines, chemokines, and ROS, in addition to being a source of proteases and PIs (Barnes 2004a; 

Shapiro 2005). However, few studies have focused on 

macrophages from lungs with documented emphysema 

(Muley et al. 1994; Betsuyaku et al. 1995; Finlay et al. 

1997b), and in these studies the measurements have been 

from macrophages that have been in culture, making 

the relevance of the findings to the in vivo state unclear. 

Despite these caveats, studies of emphysema suggest an 

increase in alveolar macrophage mRNA for MMP-1 (collagenase 1) and MMP-9 (gelatinase B) (Finlay et al. 1997a; 

Betsuyaku et al. 1999). Regardless of the presence of 

emphysema, however, alveolar macrophages from smokers express more MMP-9, an elastolytic protease, than 

do those from nonsmokers (Russell et al. 2002a). MMPs 

appear to account for most of the elastolytic activity

released from alveolar macrophages of persons with COPD 

(Russell et al. 2002b). MMP-12, a protease strongly implicated in smoke-induced emphysema in mice (Hautamaki 

et al. 1997), was more recently found to be increased in 

macrophages of persons with COPD (Molet et al. 2005). 

The role of current smoking is not clear in this observation, however, and diagnosis of emphysema was not documented in the study.

Promising techniques are becoming available for 

analysis of the products of alveolar macrophages in association with smoking, COPD, and emphysema (Koike et 

al. 2002; Wu et al. 2005). Considering that most of the 

macrophages within the lungs are associated with tissue,

analysis of alveolar macrophages harvested by BAL may 

not represent all the phenotypes of macrophages in the 

lung. Laser-capture microdissection of pulmonary macrophages from histological lung sections is a method for 

procuring macrophages within the tissue, as well as in 

alveolar spaces (Fuke et al. 2004), and future use of this 

approach is expected to provide much more data on macrophage proteases in the context of emphysema. 

Studies of Lung Tissue

Immunohistochemistry. Studies of emphysematous lung tissue support the hypothesis that proteases are 

involved in the pathogenic process. With use of antibody 

to human elastin, several types of abnormalities of elastic 

fiber were found in the lungs of persons with emphysema, 

including fragmented elastic fibers in AAT deficiency and 

poorly formed elastic fibers and clumps of elastin in smokers with centriacinar emphysema (Fukuda et al. 1989). 

The clumps appear to be from synthesis of new aberrant 

elastin, resembling changes observed in experimental 

elastase-induced emphysema (Kuhn et al. 1976). In lungs 

confirmed to have emphysema, alveolar macrophages, 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

interstitial cells, and epithelial cells express immunoreactive MMP-1 and MMP-2 (gelatinase A) (Segura-Valdez 

et al. 2000). Structural cells in emphysematous lungs 

express MMP-1 (Imai et al. 2001) and MMP-14 (membrane-type 1 MMP [MT1-MMP]) (Ohnishi et al. 1998).

Gene profiling. Gene profiling of emphysematous 

lung tissue has found only limited changes in proteases 

and PIs in comparisons with control lung tissue (Golpon 

et al. 2004; Ning et al. 2004; Spira et al. 2004). However, 

these data represent small numbers of lungs, and estimates of emphysema by chest CT or morphometry of fixed 

lung have not been uniformly provided. Also, the tissue 

analyzed has not always been limited to alveolar parenchyma. Gene profiling does not quantify neutrophil proteases 

and circulating PIs produced at sites other than the lungs.

Direct effects of cigarette smoke. Cigarette 

smoke has long been thought to induce protease expression in the lungs indirectly through cytokines (Churg 

et al. 2002, 2004), but smoke may act directly on structural cells of the lungs to induce protease expression. 

In response to exposure to smoke, human small airway 

epithelial cells (Mercer et al. 2004) and human lung fibroblasts (Kim et al. 2004) in culture increased expression of 

MMP-1 without a concomitant increase in the expression 

of tissue inhibitor of metalloproteinase (TIMP)-1. In some 

studies, cytokines enhanced the direct effects of smoke 

(Mercer et al. 2004). 

Biomarkers of Protease Involvement in 

Emphysema

As noted previously, elastic fibers in emphysematous 

lung tissue show disruptions and fenestrations of the elastin (Fukuda et al. 1989; Finlay et al. 1996) that suggest 

degradative events (see “Studies of Lung Tissue” earlier 

in this chapter). Elastin-derived peptides (desmosines) 

in plasma, serum, and BAL fluid are markers of elastin 

breakdown. A number of desmosine assays have been 

devised, and a highly sensitive, precise assay method (Ma 

et al. 2003) has been applied in studies of AAT supplementation therapy (Stolk et al. 2005). Increased urinary desmosines have been reported in smokers (Stone et al. 1995) 

and in persons who had rapid declines in FEV1 (Gottlieb et 

al. 1996), but the presence of emphysema was not determined. Similarly, levels of elastin-derived peptides found 

in BAL fluid from current smokers were higher than those 

from former smokers and lifetime nonsmokers, regardless of associated mild COPD or emphysema (Betsuyaku et 

al. 1996). 

Therapy to Control Proteases

The most direct antiprotease therapy for control 

of emphysema is supplementation with AAT for patients 

with severe AAT deficiency (American Journal of Respiratory and Critical Care Medicine 2003). Usually given 

intravenously once a week, this therapy appears to slow 

the rate of decline in FEV1, reduce the number of lung 

infections, enhance survival, and reduce lung inflammation as measured by sputum markers, although the optimal dose is still under study (Stoller and Aboussouan 2004; 

Stolk et al. 2005). In patients with moderate-to-advanced 

emphysema who are not AAT deficient, oral all-trans retinoic acid lowered plasma levels of MMP-9 and release of 

MMP-9 from alveolar macrophages without affecting levels of TIMP-1, so the balance of protease activity appeared 

to shift toward protease inhibition (Mao et al. 2003). 

Whether these effects translate into a therapeutic benefit 

for emphysema is uncertain.

Data from Animal Models

By incorporating measurements and experimental 

designs that are not possible in human studies, animal 

models have improved understanding of the role of proteases in emphysema and are useful in evaluating agents for 

antiprotease therapy in patients with emphysema (Hele 

2002; Voelkel 2004). 

Most recent models of emphysema have used mice. 

These animals provide the convenience of genetic manipulation, and findings indicate that humans and mice may 

have shared susceptibility factors for exposure to smoke 

(Shapiro et al. 2004). Emphysema can be induced in normal mice with cigarette smoke (Hautamaki et al. 1997) 

but significant differences in susceptibility exist among 

strains (Cavarra et al. 2001a; Guerassimov et al. 2004). 

By genetic manipulation, emphysema can be induced in 

resistant strains. For example, mice deficient in Nrf2, a 

transcription factor for antioxidant and detoxifying genes, 

develop emphysema in response to smoke, even though 

their ICR strain is normally resistant to the effect of smoke 

(Rangasamy et al. 2004). Overexpression of certain proteins in the lung (e.g., IL-13) can lead to emphysema without exposure to an exogenous factor (Table 7.11) (Zheng 

et al. 2000). However, deleting the expression of certain 

proteins, such as surfactant protein D (Wert et al. 2000) 

and TIMP-3 (Leco et al. 2001), in the lungs can also lead to 

the development of emphysema. Inflammation is a common feature of these and other models, but inflammation 

does not appear to be required in all models. Emphysema 

induced by an MMP-1 transgene (D’Armiento et al. 1992) 

or by severe caloric restriction (Massaro and Massaro 

2004) occurs without overt inflammation.

Although enlarged terminal air spaces are the 

hallmark of emphysema, it is important to distinguish 

between enlargement attributable to faulty alveolar formation during development and that occurring after normal 
Surgeon General’s Report

492 Chapter 7

lung development. Thus, models of enlargement in which 

alveolar development is abnormal, such as in MT1-MMP 

deficiency (Atkinson et al. 2005), may not be relevant to 

human emphysema associated with smoking, in which 

the presumption is that the lung was previously normal. 

Despite strong evidence implicating elastases in 

the pathogenesis of emphysema, research findings beginning in 1992 (D’Armiento et al. 1992) indicate that collagenolytic enzymes that do not degrade elastin may also 

be involved in the pathogenesis of emphysema. The key 

discovery was the finding of emphysema in mice engineered to harbor a transgene consisting of a haptoglobin 

promoter linked to the human MMP-1 (interstitial collagenase) gene. These mice show expression of the Mmp-1

gene in lung tissue, enlarged air spaces, bullous lesions, 

and reduced collagen fibers in alveolar walls and pleura. 

Depending on the level of transgene expression, the lung 

lesions can start either soon after birth or later, indicating 

that the emphysema is clearly postdevelopmental (Foronjy et al. 2003). Apart from demonstrating that collagenase 

activity could lead to emphysema, results with these mice 

also suggest two conclusions: (1) lung inflammation was 

minimal, indicating that proteases causing emphysema 

could come from structural cells of the lungs; and (2) the 

elastic fibers in the lung showed minimal inflammation, 

indicating that emphysema can occur without obvious 

disruption and resynthesis of elastic fibers. 

Models of Emphysema Involving Cigarette Smoke

Model systems for exposing mice to cigarette smoke 

to produce emphysema vary in the cigarettes used, the 

manner in which cigarette smoke is delivered, and assessment of the dose of smoke actually reaching the animals. 

Standard research cigarettes are commonly used, and the 

exposure is produced by directing smoke from a single 

cigarette to the nose of a mouse restrained in a singlebody compartment or by exposing groups of mice that are 

free to move in a chamber in which cigarette smoke is put 

into the atmosphere. The intensity of exposure to smoke, 

if monitored, is typically indexed by the level of carboxyhemoglobin in the blood (Wright and Churg 1995). The 

smoking regimens usually require nearly daily exposures 

for months to achieve emphysema. 

As noted previously, strains of mice can exhibit 

extremely different susceptibility to the development of 

emphysema from smoke inhalation (see “Susceptible Animal Models” earlier in this chapter). These differences in 

susceptibility are matched by differences in the accumulation of lymphocytes and neutrophils in the lung tissue. 

Higher numbers of these cell types in the tissue is associated with emphysema.

For four decades, elastases have been foremost in 

pathogenetic schemes linking proteases to the pathogenesis of emphysema, and in recent years, the importance 

of elastases has been supported in studies involving mice 

Table 7.11 Mouse models of overexpression of a protein leading to emphysema

Study Mediator Promoter Lung pathology Mechanism

D’Armiento et al. 

1992

Human interstitial 

collagenase (MMP-1)

Haptoglobulin Disruption of alveolar 

walls and coalescence of 

alveolar spaces

Degradation of collagen by 

collagenase

Wang et al. 2000 Interferon-gamma CC10-rtTA Emphysema with alveolar 

enlargement, enhanced 

lung volumes, and 

enhanced pulmonary 

compliance

Increased macrophages and 

neutrophils in BAL fluid; 

decreased secretory leukocyte 

proteinase inhibitor; increased 

MMP-9 and -12 and cathepsins 

B, D, H, L, and S

Zheng et al. 2000 Interleukin-13 CC10-rtTA Emphysema with 

enhanced lung volumes 

and compliance, 

mucus metaplasia, and 

inflammation

Increased MMP-2, -9, -12, -13, 

and -14 and cathepsins B, H, K, 

L, and S; treatment with MMP or 

cysteine proteinase antagonists 

significantly decreased 

emphysema and inflammation 

but not mucus

Source: Adapted from Mahadeva and Shapiro 2002 with permission from BMJ Publishing Group Ltd., © 2002. 

Note: BAL = bronchoalveolar lavage; CC10-rtTA = clara cell 10-kDa protein promoter-reversible tetracycline transactivator; 

MMP = matrix metalloproteinase.
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

with deficiencies of macrophage elastase (Hautamaki et al. 

1997) or neutrophil elastase (Shapiro et al. 2003). Mice 

with no macrophage elastase have virtually complete protection from smoke-induced emphysema; mice without 

neutrophil elastase have approximately 70 percent protection. The finding that a “knockout” of either of these elastolytic enzymes is protective indicates interplay between 

these enzymes in the pathogenesis of emphysema. The 

evidence suggests that neutrophil elastase is the principal 

culprit in matrix degradation and that macrophage elastase acts, at least partly, as a proinflammatory agent by 

facilitating release of TNFα (Churg et al. 2004) and as a 

shield for neutrophil elastase by the capacity to cleave AAT. 

Although overexpression of collagenase, as described 

above, has been associated with emphysema, studies 

have performed only limited assessment of collagenase 

expression in response to smoke. In guinea pigs exposed 

to smoke, collagenase mRNA and protein were found in 

alveolar macrophages and structural cells of the lungs 

coincident with decreased lung collagen and enlarged air 

spaces (Selman et al. 1996). 

Antiprotease Therapy for Experimental SmokeInduced Emphysema

As noted previously, studies of gene disruption have 

shown that inactivating the genes for MMP-12 (Hautamaki et al. 1997) or neutrophil elastase (Shapiro et al. 

2003) provides major protection against the development 

of emphysema from cigarette smoke (see “Alveolar Macrophages” earlier in this chapter). Similarly, PIs against 

MMPs or neutrophil elastase have proved effective in mice, 

in limiting the enlargement of air spaces associated with 

exposure to cigarette smoke (Table 7.12). Various routes 

of administration have been tried; ilomastat, a broadspectrum MMP inhibitor, produced highly significant protection when inhaled (Pemberton et al. 2005). These studies consistently show that compounds protecting against 

emphysema also produce a concurrent reduction of the 

typical inflammatory response to exposure to smoke. 

Accordingly, PIs should be regarded as anti-inflammatory 

agents, as well as antiproteases. 

Apoptosis

In contrast to findings in the lungs of nonsmokers, 

apoptotic epithelial cells are identifiable in the lungs of 

smokers (Segura-Valdez et al. 2000; Kasahara et al. 2001; 

Calabrese et al. 2005), and they are found in isolated 

alveolar macrophages subjected to cigarette smoke in 

vitro (Aoshiba et al. 2001a). The apoptotic cell types include 

alveolar macrophages and lung structural cells. Apoptosis, 

proteases, and emphysema were linked when emphysema 

developed within six hours after the protease CASPASE-3 

was instilled into the lungs of mice (Aoshiba et al. 2003b). 

Apoptosis and emphysema have also been produced by 

intrapulmonary instillation of VEGF receptor blockers (Kasahara et al. 2000) and by producing a temporary 

reduction in lung VEGF by intratracheal administration of 

an adeno-associated CRE recombinase virus to mice that 

have a floxed VEGF (Tang et al. 2004). The mechanisms 

by which apoptosis leads to emphysema are still not well 

Table 7.12 Effects of protease inhibitors in experimental smoke-induced emphysema

Study Animal Drug/route/frequency Smoking protocol Protection against emphysemaa

Wright et al. 2002 Guinea pig ZD0892

Oral

Twice a day

5 cigarettes/day

5 days/week

45% (6 months)

Churg et al. 2003 Mouse AAT

Intraparenteral 

48-hour intervals

2 cigarettes/day

5 days/week

63% (6 months)

Selman et al. 2003 Guinea pig CP-471,474

Subcutaneous

Once a day

Group smoke 

chamber

5 days/week

30% (4 months)

Pemberton et al. 2005 Mouse Ilomastat

Aerosol 

Daily

2 cigarettes/day

6 days/week

96% (6 months)

Note: AAT = α1-antitrypsin. aGraded by air space enlargement in comparison of animals exposed to tobacco smoke with unexposed animals. 
Surgeon General’s Report

494 Chapter 7

understood. In the CASPASE-3 study (Aoshiba et al. 

2003b), elastase activity was found in BAL fluid, and 

induction of apoptosis of alveolar type II cells in culture 

resulted in liberation of elastin peptides from an elastin 

substrate culture medium. Accordingly, in this model, 

apoptosis appears to induce emphysema by causing proteolytic degradation of extracellular matrix. 

Summary

Since its inception about 40 years ago, the protease-antiprotease hypothesis of emphysema pathogenesis 

has gained increasing support from studies in persons 

with emphysema and from those using animal models 

of emphysema. The high risk of emphysema among persons with AAT deficiency, particularly current smokers, 

continues to be compelling evidence for the linking of 

smoking and neutrophil elastase to emphysema. However, 

other proteases, particularly certain MMPs, appear to be 

involved in emphysema. Success in protecting mice from 

smoke-induced emphysema through genetic manipulations of proteases or by treatment with PIs has reinforced 

the protease-antiprotease hypothesis. For many years, the 

hypothesis specifically focused on elastase-antielastase 

imbalance and inflammatory cells infiltrating the lung as 

the source of proteases. These ideas have been modified 

in recent years to encompass discoveries that collagenolytic activity may produce emphysema and that structural 

cells of the lungs may contribute to the protease burden 

of the lung. Despite great progress, much more needs 

to be known about the proteolytic mechanisms involved 

in the pathogenesis of emphysema, such as the role of 

immune cells in protease regulation in emphysema 

and the effects of proteases on structural cells of the 

lungs. New techniques for analyzing biologic materials, 

combined with the capacity to document and quantify emphysema noninvasively, offer promise for better 

understanding of the role of proteases in emphysema in 

the years ahead. 

Summary

COPD is a rising cause of morbidity and mortality 

in the United States and elsewhere. Smoking has long 

been causally linked to COPD, and decades of clinical and 

experimental research have provided insights into the 

mechanisms underlying this causal linkage. The extensive 

evidence reviewed in this chapter highlights the critical 

role of oxidative injury, driven by the high level of ROS in 

cigarette smoke. COPD is the only disease caused by cigarette smoking that is associated with genetic mutations 

leading to AAT deficiency. This genetic association led to 

the protease-antiprotease hypothesis on the pathogenesis 

of emphysema that is now well supported by work in animal models. The ROS in cigarette smoke and secondarily 

released by epithelial and inflammatory cells can unfavorably tip the protease-antiprotease scale in multiple ways. 

Although these mechanisms are now well characterized, 

the factors leading to COPD in the minority of affected 

smokers are not completely understood.

Evidence Summary

This chapter addresses mechanisms of lung injury 

by tobacco smoke that lead to development of COPD and 

considers the role of genetic factors, including specific 

genes, in increasing risk for COPD. The chapter acknowledges that COPD is a broad phenotypic designation with 

underlying damage and structural changes in the lung’s 

airways and alveoli. This section systematically evaluates 

the evidence related to genetic susceptibility and to the 

two major mechanisms of injury considered: oxidative 

stress and protease-antiprotease imbalance.

Oxidative Stress

Cigarette smoke contains massive quantities of free 

radicals in its gas and tar phases; concentrations of free 

radicals are 1015 per puff and 1017 per gram, respectively. 

The approximately 200 or more puffs inhaled daily by a 

typical smoker of one pack per day would lead to a sustained high-level daily dose of free radicals. The chemical 

pathways by which these free radicals produce damaging 

ROS have been well characterized, as have the chemical 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

reactions by which ROS damage target molecules, including lipids, proteins, and DNA. The plausibility of oxidative 

stress as a mechanism of disease production is well documented and further affirmed through biomarker studies.

In various experimental systems, oxidative stress 

from exposure to cigarette smoke causes damage to components of the lung: the epithelium, the airways, and 

the alveoli. In humans, smoking is followed by a rise in 

markers of systemic oxidative stress and of oxidative stress 

affecting the lungs more specifically. The time course of 

the response to oxidative stress from smoking has also 

been characterized, showing a rise in markers after exposure to tobacco smoke. There is also substantial evidence 

for increased levels of oxidative stress markers in the lungs 

of persons with COPD. This large body of experimental and 

observational evidence is consistent in demonstrating that 

ROS can damage the lung and that evidence of oxidative 

stress is strongly linked with COPD. Oxidative stress is one 

of several mechanisms contributing to the development of 

COPD. However, the available evidence has not addressed 

whether oxidative stress is a necessary mechanism or sufficient by itself to cause COPD.

Genetic Susceptibility to 

Cigarette Smoke

All smokers do not develop COPD, indicating that 

smoking alone is not sufficient to cause COPD. A variety 

of lines of evidence support a role for genetic factors in 

determining susceptibility to cigarette smoke. Familial 

aggregation of phenotypes for lung function and for COPD 

has been repeatedly demonstrated. In addition, there is 

strong clinical and epidemiologic evidence on genetically 

inherited AAT deficiency and risk for emphysema. This 

chapter offers the conclusion that protease-antiprotease 

imbalance is involved in the development of emphysema 

and sufficient by itself to produce it.

The general observation that smoking alone does 

not lead universally to COPD, and the specific observation that genotypes associated with severe AAT deficiency 

lead to emphysema, imply a role for genetic factors in the 

pathogenesis of emphysema. To date, however, genetic 

loci other than SERPINA1 have not been linked to risk 

for COPD. 

Protease-Antiprotease Imbalance

Emphysema is a prominent and highly prevalent 

component of the COPD phenotype. The potential role of 

a protease-antiprotease balance shifted toward unchecked 

proteolytic activity was first identified with the finding of 

enhanced risk for emphysema in persons with AAT and the 

supporting experimental demonstration that emphysema 

could be produced experimentally by proteolytic enzymes. 

These enzymes damage the elastin in the lung, which is 

essential to maintaining the lung’s elasticity and ventilatory function. Thus, it is directly plausible that this mechanism has a role in producing emphysema. 

Three lines of evidence support a role for proteaseantiprotease imbalance in causing emphysema. First, in 

experimental models and in smokers, a shift of proteaseantiprotease balance in a destructive direction has been 

repeatedly demonstrated, as has corresponding injury to 

elastin fibers. Second, in animal models, instillation of 

proteolytic enzymes can produce emphysema, as does 

exposure to cigarette smoke. Genetically engineered mice 

with deficient macrophage or neutrophil elastase are protected from smoke-induced emphysema. Third, persons 

with homozygous AAT deficiency who smoke develop 

emphysema at a young age.

This substantial consistent and complementary 

evidence supports a causal role for protease-antiprotease 

imbalance in the pathogenesis of emphysema, a critical element of the COPD phenotype. This mechanism 

is also substantially plausible because of the importance of elastin in determining ventilator function. The 

evidence further indicates that protease-antiprotease 

imbalance is sufficient to produce emphysema in smokers. 

Human evidence comes from the long-described and welldocumented occurrence of early-onset emphysema in 

smokers with low levels of AAT consequent to mutations 

of SERPINA1. Findings in animal models confirm the sufficiency of this mechanism.
Surgeon General’s Report

496 Chapter 7

Conclusions

1. Oxidative stress from exposure to tobacco smoke has 

a role in the pathogenetic process leading to chronic 

obstructive pulmonary disease.

2. Protease-antiprotease imbalance has a role in the 

pathogenesis of emphysema.

3. Inherited genetic variation in genes such as SERPINA3 is involved in the pathogenesis of tobacco-caused 

chronic obstructive pulmonary disease.

4. Smoking cessation remains the only proven strategy 

for reducing the pathogenetic processes leading to 

chronic obstructive pulmonary disease.

Implications

Two major mechanisms underlying the causation of 

COPD by cigarette smoking have been identified: oxidative 

stress (injury) and protease-antiprotease imbalance. These 

mechanisms are triggered by the inhalation of combustion products directly into the lungs of smokers. Although 

the lung has defense mechanisms that function to check 

injury by inhaled agents, these defenses are overwhelmed 

by the sustained inhalation of cigarette smoke. Doses of 

inhaled smoke that could be tolerated without resulting in 

oxidative injury and protease-antiprotease imbalance have 

not been identified. Smoking cessation remains the only 

way to check and halt these processes.

COPD is the only disease caused by smoking that 

is strongly associated with a specific genetic disorder, 

namely, AAT deficiency. The occurrence of COPD in young 

smokers should trigger testing for AAT deficiency, but 

such screening is not recommended for the general population. Studies in progress are expected to extend understanding of the genetic basis of COPD.
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521

Chapter 8

Reproductive and Developmental Effects

Introduction 523

Review of Epidemiologic Literature on Smoking 524

Reproductive Endpoints 524

Menstrual Function, Menarche, and Menopause 524

Fertility 525

Pregnancy Complications 527

Spontaneous Abortion 527

Ectopic Pregnancy 531

Preeclampsia 534

Placenta Previa 535

Placental Abruption 535

Preterm Delivery 536

Preterm Premature Rupture of Membranes 537

Developmental Endpoints 537

Fetal Size and Growth 538

Perinatal and Infant Mortality 538

Birth Defects 539

Neurodevelopment 540

Pathophysiological and Cellular and Molecular Mechanisms of Smoking 555

Endocrine System 555

Premenopausal Women 555

Pregnant Women 557

Men 557

Tubal Function 566

Placenta 566

Normal Development 566

Effects of Smoking 567

Maternal and Fetal Cardiovascular Systems 568

Basal Function 568

Acute Effects of Smoking 574

Blood Flow in Uterus, Placenta, and Fetus 576

Fetal Tissue and Organogenesis 577

Timing and Critical Periods 577

Evidence on Effects of Smoking 577

Immune System 583

Tobacco Smoke Toxicants and the Reproductive System 584

Carbon Monoxide 584

Nicotine 586

Metals 587

Polycyclic Aromatic Hydrocarbons 589

Other Compounds 598
522

Other Molecular Mechanisms 599

Genetic Damage to Sperm 599

Nutrient Deficiencies 599

Nitric Oxide Activity 600

Smoking and Maternal and Neonatal Genetic Polymorphisms 600

Birth Defects 601

Other Reproductive Endpoints 601

Implications 606

Smoking Prevention and Cessation 606

Regulation and Policy 607

Evidence Summary 608

Conclusions 612

References 613
Reproductive and Developmental Effects 523

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Introduction

Health professionals have long considered exposure to tobacco smoke harmful to reproduction, affecting 

aspects from fertility and pregnancy outcome to fetal and 

child development. Tobacco smoke contains thousands 

of compounds, some of which are known to have toxic 

effects on reproductive health, such as carbon monoxide 

(CO), nicotine, and metals. Along with more than four 

million births in the United States annually, 10 to 20 percent of pregnancies end in miscarriage or stillbirth before 

delivery, and another 10 percent of couples who want to 

conceive a child experience infertility or reduced fertility. In 2007, 17.4 percent of all women and approximately 

19 percent of women of reproductive age (18 through 44 

years) smoked cigarettes (Centers for Disease Control and 

Prevention [CDC] 2008). Smoking rates among women of 

reproductive age vary by other factors such as education, 

race, and geographic area, ranging from about 10 percent 

in Utah to nearly 30 percent in Kentucky and West Virginia 

(CDC 2005). From 2002 to 2005, 17.3 percent of pregnant 

women reported smoking cigarettes in the past month 

(NSDUH Report 2007). CDC’s Pregnancy Risk Assessment 

Monitoring System is an ongoing, population-based surveillance system designed to identify and monitor selected 

self-reported maternal behaviors and experiences that 

occur before, during, and after pregnancy among women 

who deliver a live infant. In 2002, the prevalence of smoking in the three months before pregnancy ranged from 

13.6 percent (Utah) to 37.0 percent (West Virginia); in the 

last three months of pregnancy, from 6.8 percent (Utah) 

to 25.3 percent (West Virginia); and after pregnancy, from 

9.0 percent (Utah) to 33.7 percent (West Virginia) (Williams et al. 2006). Prevalence of smoking is generally 

higher among men. In 2003, 24.1 percent reported smoking and prevalence was higher among younger men than 

among older men. This chapter examines reproductive 

and developmental outcomes, although the term “reproductive” may be used generally to describe both, in relation to smoking.

The reproductive endpoints include aspects 

affecting a person’s ability to conceive a child, such as 

menstrual cycle function, semen quality, fertility, and 

menopause, in addition to complications of pregnancy, 

such as miscarriage, ectopic pregnancy, and preterm 

delivery. Developmental endpoints that affect child 

health status include birth weight, congenital anomalies, and perinatal and infant deaths—especially sudden 

infant deaths and sudden unexplained infant deaths 

which have been associated with exposure to secondhand smoke—and they extend into childhood with neurobehavioral endpoints and puberty. Previous Surgeon 

General’s reports have examined epidemiologic data for 

most of these endpoints. This chapter cites conclusions 

from those earlier reports, examines in more detail 

endpoints for which the evidence was not sufficient to 

establish causality, and provides an updated review of the 

epidemiologic literature for these endpoints. Other sections explore the possible biologic basis for an effect of 

smoking on reproduction and development from the 

pathophysiological levels to the cellular and genetic levels. 

When studying the reproductive effects of smoking 

in humans, there are several exposure issues to bear in 

mind. Most studies have examined the effects of active 

smoking on fertility or pregnancy. For the past decade, 

interest has also increased in the effects of secondhand 

exposure to tobacco smoke, so these studies are mentioned when available (U.S. Department of Health and 

Human Services [USDHHS] 2006). Because smoking rates 

have declined, persons who are involuntarily exposed to 

tobacco smoke probably now outnumber active smokers. Thus, many nonsmokers are exposed to some of the 

same toxins to which smokers are exposed. The problem 

of involuntary exposure may be particularly pervasive 

for women who stop smoking during pregnancy. They 

may live with partners or family members who continue 

to smoke, so the potential still exists for exposure to 

tobacco smoke in the household. Such an exposure may 

also occur in the workplace. However, local, state, and federal laws against smoking in the workplace have led to 

a decline in this type of exposure. The critical exposure 

periods may be very specific for certain pregnancy outcomes or congenital anomalies, but most epidemiologic 

studies do not seek such detailed information about 

exposure to tobacco smoke. For endpoints of child development, postnatal exposure to tobacco smoke may also 

be important but difficult to separate from prenatal exposure, because the two are correlated. 

Current smoking may be assessed for reproductive 

endpoints such as fertility, but this timing may not reflect 

exposure during the critical period when fertility began 

if the woman has stopped smoking as a result of ongoing fertility problems. Fertility may also be affected by her 

partner’s smoking, either directly or indirectly as exposure 

to secondhand smoke. Research shows the long-lasting 

effects of prenatal exposures on later health, even in adulthood. Thus, age at puberty, fertility, or even maintenance 

of a pregnancy may be affected by in utero exposure to 

tobacco smoke, but this relationship is rarely studied. For 

age at menopause, patterns of exposure to tobacco smoke 

over a lifetime may be important. 
Surgeon General’s Report

524 Chapter 8

Review of Epidemiologic Literature on Smoking

Reproductive Endpoints

Menstrual Function, Menarche, and Menopause

Menstrual Cycling

The effects of exogenous exposures on menstrual 

function have become the focus of much research. Studies of these effects are hindered because cyclic patterns of 

menstruation vary and do not have one well-defined health 

endpoint. For example, some menstrual disturbances such 

as irregularity do not have standard definitions, and others, such as dysmenorrhea (painful menstruation), may 

be subjective. However, menstrual morbidity has a significant impact on women’s health and economics (e.g., physician visits and time lost from work) (Harlow and Ephross 

1995). Furthermore, menstrual cycle patterns are a useful 

marker of ovarian function and reproductive health and 

may affect risks of chronic disease. The 2004 Surgeon 

General’s report on the health consequences of smoking 

did not examine menstrual function or menopause, but 

the 2001 report on women and smoking reached suggestive conclusions that are expanded upon here (USDHHS 

2001, 2004).

Beginning in the 1960s, numerous studies have 

examined menstrual function in relation to smoking, 

but most were focused on dysmenorrhea or other selfreported symptoms. As summarized in the 2001 Surgeon 

General’s report on women and smoking (USDHHS 2001), 

the prevalence of dysmenorrhea was increased with current smoking, with intermediate effects among former 

smokers (Brown et al. 1988; Parazzini et al. 1994; Harlow 

and Park 1996; Mishra et al. 2000), but not in all studies 

(Andersch and Milsom 1982). A Chinese study of exposure 

to secondhand smoke in nonsmoking women reported an 

adjusted risk for dysmenorrhea that increased with higher 

exposure levels (Chen et al. 2000). In examining multiple endpoints or symptoms, a community survey in Los 

Angeles, California, revealed that the prevalence of physician-attended menstrual disorders (e.g., dysmenorrhea 

and oligomenorrhea) was higher among heavy smokers 

(≥15 cigarettes per day) than among nonsmokers (Sloss 

and Frerichs 1983). A postal survey in England found that 

compared with nonsmokers, smokers more frequently 

reported six of seven aspects of “abnormal” menstruation, 

including frequent, short, or irregular periods and prolonged and heavy bleeding (Brown et al. 1988). 

Similarly, other worldwide studies have reported 

higher risks of multiple symptoms, including premenstrual tension, heavy periods, severe pain, and frequent 

and irregular periods among smokers, especially heavy 

smokers (Kritz-Silverstein et al. 1999; Mishra et al. 2000). 

Additional studies reported increased risks of short and/or 

irregular cycles among smokers, with some dose-response 

relationships observed (Kato et al. 1999; Rowland et al. 

2002). Using prospective menstrual diaries to improve 

ascertainment, Hornsby and colleagues (1998) found more 

reporting of dysmenorrhea, an increased daily amount of 

bleeding, and a shorter duration of bleeding among smokers. The findings suggested that heavy smokers (>10 cigarettes per day) had irregularity or greater variability in 

cycle length than did nonsmokers. However, the study had 

limited power to examine higher smoking levels, and the 

study sample was selective in that the participants’ mothers had participated in a clinical trial of diethylstilbestrol 

while pregnant with them.

Other studies have assessed menstrual cycle parameters by measuring hormone levels to define lengths of 

phases in the cycle. A small study noted cycles of heavy 

smokers that were, on average, 1.6 days shorter than cycles 

of nonsmokers, and the mean follicular phase was shorter 

by 1.4 days (Zumoff et al. 1990). A study based on diaries and daily measurement of urinary levels of hormone 

metabolites reported that heavy smoking (≥20 cigarettes 

per day) was also associated with menstrual cycle lengths 

that were shorter by 2.6 days and more variable than those 

of nonsmokers (Windham et al. 1999b). The shortening of 

the cycle occurred primarily during the follicular phase. 

The findings also suggested an increased risk of a short 

luteal phase (<11 days) and anovulation, but the confidence intervals (CIs) for these endpoints were wide and 

not significant. The mean duration of bleeding in smokers was not different. Another study, based on diaries of 

workers in the semiconductor industry, as well as levels 

of hormone metabolites, found little difference in cycle 

length among smokers compared with nonsmokers (Liu 

et al. 2004a). However, this finding was modified by age: 

shorter follicular phases were associated with smoking 

only among women older than 35 years of age. The data 

also revealed a nonsignificant increase in risk of anovulation among smokers. Dose-response relationships were 

not examined (Liu et al. 2004b).

Alterations in menstrual cycle function may have 

several ramifications, including a burden on the health 

care system. Dysmenorrhea may lead to a loss of work 

productivity. Women with variable cycle lengths may 

have difficulty trying to conceive, because the timing of 

ovulation is less predictable. Anovulation has an obvious 

relevance for time to conception or fertility. Cycles that 
Reproductive and Developmental Effects 525

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

are shortened during the follicular phase might indicate 

abnormal folliculogenesis and ovum maturation. A short 

luteal phase may indicate a progesterone response that is 

inadequate for implantation and maintenance of the trophoblast. Studies have implicated a luteal phase defect as 

a cause of infertility as well as a cause of recurrent spontaneous abortion (SAB) (Regan et al. 1990; Tulppala et al. 

1991). These effects are consistent with evidence for association of smoking with decreased fertility (see “Fertility” 

later in this chapter). Women with short menstrual cycles 

may also be at a higher risk of breast cancer (Kelsey et 

al. 1993).

Reproductive Life Span—Menarche 

to Menopause

Smoking may also affect the duration of menstrual 

cycling (reproductive life span). The 2001 Surgeon General’s report on women and smoking summarized numerous 

studies that consistently found a younger age at natural 

menopause among women who smoked than that for 

nonsmokers (USDHHS 2001). The studies also concluded 

that smokers may have more menopausal symptoms. In 

an earlier meta-analysis, the difference in the mean age 

at natural menopause ranged from 0.8 to 1.7 years (Midgette and Baron 1990). This same meta-analysis showed 

a prevalence ratio for being postmenopausal that was 

nearly doubled among current smokers versus lifetime 

nonsmokers, with dose-response trends by the number of 

cigarettes smoked. Later studies confirmed these findings 

(Cooper et al. 1999; Harlow and Signorello 2000; Meschia 

et al. 2000; Brett and Cooper 2003). One study reported 

a decrease in mean age at natural menopause with current active smoking but did not find an association among 

former smokers or with exposure to secondhand smoke 

(Cooper et al. 1999). However, two studies that were more 

briefly described found an earlier age at menopause with 

exposure to secondhand tobacco smoke (Everson et al. 

1986; Tajtakova et al. 1990). In a population-based study 

in the United States, smoking was weakly associated with 

transition to menopausal status and strongly associated 

with postmenopausal status (Brett and Cooper 2003). This 

finding led the authors to suggest that the menopausal 

transition period may be shortened in smokers. 

On the other end of the spectrum, some studies have 

examined age at menarche (start of menstrual periods) in 

relation to parental smoking. On the basis of data from a 

longitudinal birth cohort study, daughters whose mothers 

had smoked heavily during pregnancy had an earlier mean 

age at menarche by several months (Windham et al. 2004). 

This effect was greater among non-Whites than among 

Whites. Two studies from Poland reported a younger 

age at menarche for daughters of smoking mothers than 

that for daughters of nonsmoking mothers (Kolasa 1997; 

Kolasa et al. 1998). A retrospective study of teachers found 

a slightly higher risk of early menarche among women 

who reported that during their childhoods, their parents had smoked at home (Reynolds et al. 2004). These 

later studies primarily examined exposure to secondhand 

smoke, and the timing with respect to puberty was not 

established. However, mothers who smoked postnatally, 

especially before smoking was socially prohibited, may 

have smoked during pregnancy as well. Windham and colleagues (2004) showed that girls with high prenatal and 

childhood exposure to secondhand smoke had the earliest 

mean age at menarche. One study examined the effects of 

parental smoking on puberty in both boys and girls and 

reported earlier pubertal milestones in boys whose mothers had smoked during pregnancy, but not in girls. However, the study had such small numbers that the power 

to examine age at menarche was insufficient (Fried et al. 

2001). 

Changes that affect the reproductive life span can 

have an impact on other aspects of a woman’s health. 

Shorter cycles may lead to a more rapid depletion of 

oocytes, shortening the reproductive life span and leading 

to earlier menopause (Whelan et al. 1990; Bromberger et 

al. 1997). Early menopause is associated with other hormone-related health problems such as osteoporosis and 

cardiovascular disease (Harlow and Ephross 1995; Sowers and La Pietra 1995; Cooper and Sandler 1998). Early 

menarche or puberty may lead to psychosocial problems, 

adolescent pregnancy and attendant risks, other adverse 

reproductive outcomes, and breast cancer (Hardy et al. 

1978; Liestol 1980; MacMahon et al. 1982a; Martin et al. 

1983; Sandler et al. 1984; Wilson et al. 1994; Ge et al. 

1996; He and Karlberg 2001).

Fertility

Fertility is an endpoint that is difficult to compare 

across studies, because no standard definition exists. 

Fecundity refers to the biologic ability to conceive, given 

unprotected intercourse, and depends on the reproductive 

capacity of both sexual partners. The clinical definition of 

infertility in the United States usually connotes lack of conception after one year of unprotected intercourse during 

the fertile phase. However, couples who delay childbearing 

may seek treatment before one year, which further complicates studies. Subfertility refers to any form of reduced 

fertility in couples trying to conceive, and one way to study 

it is by measuring time to conception or pregnancy. One 

commentary indicated that about 20 percent of couples 

experience subfertility, defined as the inability to conceive 

within six months (Gnoth et al. 2005). About 50 percent 

of these couples conceive in the next six months, leaving 
Surgeon General’s Report

526 Chapter 8

10 percent of couples that match the clinical definition of 

infertility. Another 50 percent will likely conceive spontaneously in the next three years, leaving 5 percent infertile. 

Smoking affects fertility in men and women, as well as the 

success of in vitro fertilization (IVF).

Fertility in Females

Numerous studies have found associations of smoking with reduced fertility. The 2001 Surgeon General’s 

report concluded that “women who smoke have increased 

risks for conception delay and for both primary and secondary infertility” (USDHHS 2001, p. 14). The 2004 Surgeon General’s report also reviewed the literature and 

concluded that “the evidence is sufficient to infer a causal 

relationship between smoking and reduced fertility in 

women” (USDHHS 2004, p. 7). Other reviews have found 

consistent decrements in fertility associated with smoking, 

as well as evidence for dose-response trends. In a metaanalysis of data from 12 studies, the odds ratio (OR) was 

1.6 (95 percent CI, 1.3–1.9) for infertility among smokers 

(Augood et al. 1998). Furthermore, meta-analyses of data 

on IVF treatment indicated a reduction in fecundity (conception rate per cycle) among women smokers ranging 

from 0.57 (95 percent CI, 0.42–0.78) to 0.66 (95 percent 

CI, 0.49–0.88) (Hughes and Brennan 1996; Augood et al. 

1998). In a later qualitative review of 22 studies, all but 3 

of the studies indicated a detrimental effect of smoking on 

female fecundity (Wilks and Hay 2004). The Practice Committee of the American Society for Reproductive Medicine 

(PCASRM) also issued a statement strongly supporting 

evidence for an association between smoking and infertility, estimating that 13 percent of infertility may be attributable to smoking (PCASRM 2004).

Several studies also examined the effects of exposure to secondhand tobacco smoke on fertility, but these 

effects may be difficult to separate from the direct effects 

of smoking on the partner’s fecundity. Researchers have 

reviewed these studies and found suggestive but inconsistent results (National Cancer Institute [NCI] 1999; 

USDHHS 2001, 2006), so there are insufficient data to 

reach conclusions. A study published since two of those 

reviews examined the effects of exposure to mainstream 

and sidestream smoke on IVF outcomes. The researchers found that implantation and pregnancy rates were 

reduced by about one-half from both types of exposure to 

tobacco smoke among smokers compared with nonsmokers (Neal et al. 2005). The investigators noted that the 

association of exposure to sidestream smoke may reflect 

some direct effect of smoking on the male partners. However, they claimed that this could not explain the entire 

effect in that they observed no difference in implantation 

and pregnancy rates by the partner’s smoking level. 

Intriguingly, some studies have also examined the 

effects of in utero exposure to maternal smoking on later 

fertility or fecundability. One study found a significantly 

reduced likelihood of conception in smokers versus nonsmokers (fecundability ratio [FR]) of 0.5 (Weinberg et al. 

1989); another study found a slightly reduced FR of 0.9 

(Wilcox et al. 1989); and a third study found a slightly 

increased FR of 1.1 but also observed no effect of active 

smoking among the women (Schwingl 1992). In the 

range of these studies, a Danish study reported FRs for in 

utero exposure to cigarette smoking of 0.70 among adult 

nonsmokers and 0.53 among smokers, as well as 0.67 for 

female smokers with no in utero exposure, all compared 

with that for nonsmokers who had no in utero exposure 

(Jensen et al. 1998b). This study also found a similarly 

decreased fecundability in males exposed to smoking 

in utero.

Effects on Semen Quality and Male Fertility

For decades, epidemiologic studies have investigated the effects of cigarette smoking on semen quality, 

because of its relationship to male fertility (Campana et al. 

1996; Eggert-Kruse et al. 1996; Bonde et al. 1998; Chia et 

al. 2000), although this relationship is not always predictive (Polansky and Lamb 1988; Guzick et al. 2001). Semen 

quality is measured by seminal plasma constituents and 

sperm cell characteristics such as ejaculate volume, sperm 

count, sperm motility, and sperm morphology. The World 

Health Organization (WHO) Laboratory Manual for the 

Examination of Human Semen and Sperm-Cervical Mucus Interaction (WHO 1980, 1987, 1992, 1999b) provides 

reference values for many semen parameters associated 

with fertility. A number of epidemiologic studies of smoking effects have used WHO reference values to categorize 

participants by their fertility status. Reproductive hormones are important determinants of normal sperm production and male sexual function and have thus also been 

studied in relation to exposure to cigarette smoking (see 

“Endocrine System” later in this chapter).

The 2004 Surgeon General’s report reviewed the 

published epidemiologic literature evaluating semen 

quality and fertility and concluded that “the evidence is 

inadequate to infer the presence or absence of a causal 

relationship between active smoking and sperm quality” 

(USDHHS 2004, p. 28). However, “the evidence suggests 

that smokers may have decreased semen volume and 

sperm number and increased abnormal [morphologic] 

forms, although any clinical relevance of these findings 

is not clear” (USDHHS 2004, p. 534). A stronger causal 

statement could not be made at that time because of variability in published findings across studies. Reviews on 

this topic (Mattison 1982; Stillman et al. 1986; Little and 
Reproductive and Developmental Effects 527

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Vainio 1994; Vine 1996; Marinelli et al. 2004; PCASRM 

2004) and one meta-analysis of data from 20 studies covering 1966–1992 (Vine et al. 1994) attribute this variation in 

the findings across studies to weaknesses in study designs. 

These weaknesses include a failure to adjust for potential 

confounders, small sample sizes, inadequate exposure 

assessments, and the use of fertility clinic populations. 

Subsequent to the 2004 Surgeon General’s report 

(USDHHS 2004), the PCASRM review (2004), and the 

review by Marinelli and colleagues (2004), some publications have strengthened the evidence for decrements in 

adult semen quality and fertility associated with exposure 

to tobacco smoke either prenatally or in adulthood (Table 

8.1). Both studies in Table 8.1 that evaluated adult semen 

quality after in utero exposure found decrements in sperm 

concentration (Storgaard et al. 2003; Jensen et al. 2004). 

Studies conducted in clinical settings using assisted 

reproductive technology with extremely sensitive measures of fertilization and very early pregnancy loss also 

reported adverse effects from paternal smoking. Some 

studies had low power for detecting effects, but one of the 

largest studies, which was based on a retrospective review 

of records, did not find independent effects of cigarette 

smoking. However, the researchers reported a reduction 

in seminal volume, sperm concentration, and the percentage of motile sperm in men who smoked and consumed 

alcohol, behaviors that tend to be correlated (Martini et 

al. 2004). Another study based on a retrospective review 

of medical records for exposure assessments could not 

include more than 46 percent of the medical records initially reviewed, because of insufficient data, particularly 

data related to smoking (Ozgur et al. 2005). Although the 

study found no significant differences in sperm density, 

normal sperm tail morphology decreased or abnormal 

forms increased. 

Spermatogenesis in the adult testes depends on a 

hormonal milieu that is temporally and compartmentally 

specific (e.g., seminiferous tubule, interstitial space, and 

epididymis). Thus, factors likely to be responsible for the 

decrements seen in semen quality and male fertility are 

constituents of cigarette smoke that influence the normal development and adult function of the hypothalamus 

and pituitary gland or that influence the differentiation, 

development, and adult function of Leydig and/or Sertoli 

cells that secrete hormones (see “Endocrine System” later 

in this chapter). Support for the contribution of smoking 

effects on hormonal factors to male fertility is still evolving (Meikle et al. 1989; Michnovicz et al. 1989; Sofikitis 

et al. 1995; Chapin et al. 2004). Other potential mechanisms of smoking for male infertility include effects on 

the sperm plasma membrane (Belcheva et al. 2004) and 

tobacco-related damage to DNA and/or chromosomes in 

gametes (PCASRM 2004) (see “Genetic Damage to Sperm” 

later in this chapter). Studies have associated in utero 

exposure to polycyclic aromatic hydrocarbons (PAHs) in 

tobacco smoke with adverse effects on male fertility and 

on testes (see “Polycyclic Aromatic Hydrocarbons” later in 

this chapter). Additional targeted research in human populations with use of molecular laboratory tools will help to 

elucidate the mechanisms underlying these observations.

Study designs have not addressed the timing of 

exposures in relation to sperm cell maturation in the 

testes, the formation and secretion of fluids contributed 

by accessory organs outside the testes, and events during fertilization. This information is critical to unraveling mechanisms of the toxic effects of tobacco smoke, 

determining whether these exposures result in long-term 

risks to male reproductive health, and documenting the 

benefits of smoking cessation. For example, if spermatogonial stem cells prove to be the cells most sensitive to 

exposure to tobacco smoke, then long-term consequences 

might be observed even after smoking cessation. However, 

if mechanisms of toxic effects relate primarily to effects 

on epididymal sperm or to direct effects on mature sperm 

in the ejaculate from seminal plasma constituents, then 

smoking cessation could result in immediate benefits.

Pregnancy Complications

This section addresses a variety of complications 

that may occur during pregnancy. These complications 

primarily represent difficulties the pregnant mother may 

experience trying to maintain a healthy pregnancy, but 

there also may be wide-ranging effects on the health of 

the fetus or the offspring. In general, these conditions 

may be influenced by maternal age, reproductive history, 

and medical history or conditions affecting the maternal 

endocrine or immune systems, uterine structure, and 

cardiovascular system, among others. Exogenous exposures may also play a role in causing or exacerbating these 

conditions. This section briefly presents the etiology of 

these complications and puts potential smoking-induced 

mechanisms into context. (For details on the mechanisms 

of these complications, see “Pathophysiological and Cellular and Molecular Mechanisms of Smoking” later in 

this chapter.) 

Spontaneous Abortion

SAB is typically defined as the involuntary termination of an intrauterine pregnancy before 20 weeks 

of gestation. Studies have reported recognized SABs in 

approximately 12 percent of pregnancies, and most occur 
Surgeon General’s Report

528 Chapter 8

Table 8.1 Association of adult cigarette smoking and in utero exposure to cigarette smoke with semen parameters 

and fertility in adultsa

Study Population

Study 

period Definition of smoking Findings

Effects from 

adult smoking

           

Chia et al. 2000 240 fertile and 218 

infertile men from 

obstetric and andrology 

clinic populations

NR Self-reported number 

of cigarettes/day and 

smoking history

• Smoking predictive of risk of infertility

Trummer et al. 

2002

260 smokers, 70 

former smokers, and 

258 nonsmokers 

from infertility clinic 

population

1993–

2000

Self-reported number 

of cigarettes/day

• NS difference in density, motility, and morphology

Gaspari et al. 

2003

69 current smokers, 22 

former smokers, and 

88 lifetime nonsmokers 

from infertility clinic 

population, 75 with 

1-year follow-up for 

fertility

2001 Self-reported number 

of cigarettes/day and 

smoking history

• PAH-DNA adducts in sperm associated with 

infertility but not cigarette smoking 

• PAH-DNA adducts associated directly with 

abnormal forms of sperm and inversely with 

asthenospermia

Künzle et al. 

2003

655 smokers and 

1,131 nonsmokers 

from infertility clinic 

population

1991–

1997

Self-reported >1 

cigarette/day

• Lower sperm density, total motile cells, and 

citrate concentration

• Fewer morphologically normal cells

• Higher pH

• No significant difference in volume, vitality, 

and fructose concentration

Loft et al. 2003 225 women with first 

pregnancy, 74 male 

smokers, and 151 male 

nonsmokers

1992–

1994

Self-reported number 

of cigarettes/day

• Likelihood of pregnancy in a menstrual 

cycle inversely associated with 8-oxo-dG 

concentrations, but levels not associated 

with smoking status

Zitzmann et al. 

2003

48 IVF couples and 153 

ICSI couples

1999–

2001

Self-reported lifetime 

nonsmoker or smoker 

(≥5 cigarettes/day for 

2 years)

• Paternal smoking predictive of fertilization 

in IVF but not in ICSI

• Paternal smoking predictive of clinical pregnancy in ICSI and IVF

• Increased progressive motility and decreased 

normal forms of sperm among smokers

Chen et al. 

2004

22 smokers, 57 former 

smokers, and 227 

nonsmokers from 

infertility clinic 

population in study of 

seasonal effects and 

environmental exposures

2000–

2002

Self-reported current 

smoker, former 

smoker, or lifetime 

nonsmoker

• NS differences in concentration, motility, 

and morphology of sperm

Jurasovic et al. 

2004

61 smokers and 62 

nonsmokers from 

infertility clinic 

population

NR Self-reported number 

of cigarettes/day

• Decreased blood prolactin

• Positive correlation with blood cadmium

• NS differences in concentration, motility, 

and morphology of sperm

Martini et al. 

2004

3,430 nonsmokers, 

422 light smokers, and 

124 heavy smokers 

from infertility clinic 

population

1990–

1999

Retrospective 

review of records 

for cigarettes/day: 0, 

1–20, >20

• NS differences in concentration, motility, 

and morphology of sperm across categories 

of smoking independent of alcohol intake
Reproductive and Developmental Effects 529

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Study OR, RR, or % (95% CI or p value) Comments

Effects from 

adult smoking

     

Chia et al. 2000 Infertility in smokers compared with nonsmokers = 2.96 

(1.98–4.42)

None

Trummer et al. 

2002

NR None

Gaspari et al. 

2003

Smokers = 1.58 

Nonsmokers = 1.62 in relative staining intensity (NS)

PAH-DNA adducts associated with abnormal head (r = 0.3), 

abnormal neck (r = -0.2), and abnormal physiological forms 

(r = -0.2)

None

Künzle et al. 2003 Decreased density by 15.3%, p = 0.0001

Decreased total motile cells by 16.6%, p = 0.002

Decreased normal forms by 10.6%, p = 0.0007

Decreased citrate concentration by 22.4%, p = 0.007

Correlation of alcohol intake 

and smoking (p = 0.002) after removing 

heavy drinkers because moderate alcohol 

intake has not been associated with 

infertility; no adjustment

Loft et al. 2003 Correlation of smoking and 8-oxo-dG 

concentrations

Spearman correlation 0.02 (NS)

Adequate semen count required to 

extract enough DNA for bioassay because 

variance by smoking may bias findings

Zitzmann et al. 

2003

ICSI pregnancy failures in partners of male smokers compared 

with partners of nonsmokers 

2.95 (1.32–6.59)

IVF pregnancy failures in partners of male smokers compared 

with partners of nonsmokers

2.65 (1.33–5.30)

None

Chen et al. 2004 NS 20% decrease in sperm density in current smokers compared 

with lifetime nonsmokers

Small number of smokers

Jurasovic et al. 

2004

Decreased blood prolactin (p = 0.02)

Correlations with blood: Cadmium, +0.80 (p <0.001),

Selenium, -0.26 (p <0.01), Selenium-glutathione, 

peroxidase, -0.30 (p <0.001)

None

Martini et al. 

2004

Significantly decreased density by 11%, decreased total motile 

sperm 10%, decreased rapid sperm by 14% for men who smoked 

>1 cigarette and drank ≤52 grams of ethanol/day compared with 

no smoking or drinking

Retrospective review of record with no 

exposure validation measures
Surgeon General’s Report

530 Chapter 8

before 12 weeks of gestation (Regan et al. 1989). However, 

very early pregnancy loss may go unrecognized and/or 

unreported. An estimated 30 to 45 percent of conceptions 

actually end in pregnancy loss (Wilcox et al. 1988; Eskenazi et al. 1995). Studies of tissue from SABs suggest that 

50 to 80 percent of losses have an abnormal karyotype, 

depending on the mother’s age and the gestational age at 

the time of the loss; a higher proportion of abnormalities 

is found in losses at earlier gestational ages (Kajii et al. 

1980; Hogge et al. 2003; Philipp et al. 2003). In addition 

to fetal abnormalities, other factors that likely contribute 

to SAB include maternal anatomical abnormalities of the 

uterus, immunologic disturbances, thrombotic disorders, 

and endocrine abnormalities (Christianson 1979; Cramer 

and Wise 2000; Regan and Rai 2000). Infections may also 

play a role, but data are limited and inconsistent (Cramer 

and Wise 2000; McDonald and Chambers 2000; Matovina 

et al. 2004). 

Several studies have demonstrated a moderate 

association between smoking and SAB (DiFranza and Lew 

1995). The 2004 Surgeon General’s report on the health 

consequences of smoking found the evidence suggestive 

but not sufficient to infer a causal relationship between 

smoking and SAB (USDHHS 2004). However, numerous 

studies are available since the handful reviewed at that 

time (Table 8.2), and most show positive associations. 

These results represent both retrospective and prospective study designs from a number of different countries, 

with adjustment for various confounders. One study 

found an association with amount smoked before pregnancy (Nielsen et al. 2006), and another reported an 

association among former smokers (Mishra et al. 2000), 

but others did not observe these associations (Chatenoud 

et al. 1998; Wisborg et al. 2003). The later study had a 

very low SAB rate of approximately 1 percent, so many 

SABs were likely missed, particularly early in pregnancy. 

Two studies used a measurement of cotinine to verify 

exposure to tobacco smoke and found relatively high risks 

of SAB (Ness et al. 1999; George et al. 2006). Estimates of 

the increase in risk of SAB from smoking are 30 to 100 

percent, some in a dose-response pattern (Kline et al. 

1977; Chatenoud et al. 1998; USDHHS 2004; George et al. 

2006; Nielsen et al. 2006). In a meta-analysis of data from 

13 studies, the pooled ORs for SAB in smokers were 1.24 

(95 percent CI, 1.19–1.30) for cohort studies and 1.32 (95 

percent CI, 1.18–1.48) for case-control studies (DiFranza 

and Lew 1995). In one study, the association with smoking 

appeared stronger in chromosomally normal SABs (Kline 

Table 8.1 Continued

Study Population

Study 

period Definition of smoking Findings

Ozgur et al. 

2005

116 heavy smokers, 

82 light smokers, and 

98 nonsmokers from 

infertility clinic patients

2000–

2002

Retrospective 

review of records 

for cigarettes/day: 0, 

1–19, ≥20

• Increased rapidly motile cells among smokers 

of ≥20 compared with 1–19 cigarettes/day

• Increased coiled-tail defects among smokers

• NS difference in density and total motile cells 

in nonsmokers compared with heavy smokers

Effects during 

adulthood of in 

utero exposure 

to cigarette 

smoke

           

Storgaard et al. 

2003

265 Danish men 

identified from 

population-based birth 

registries

1999–

2000

Maternal recall of 

smoking during 

pregnancy: 0, 1–10, 

11–20, >20 cigarettes/

day

• In utero exposure to >10 cigarettes/day 

associated with lower sperm density (48%), 

lower inhibin B, and higher follicle-stimulating hormone

• No dose-response relationship or significant change in other semen parameters or 

hormones

Jensen et al. 

2004

1,770 military inductees 

from Denmark, Estonia, 

Finland, Lithuania, and 

Norway

1996–

1999

Maternal recall of 

maternal and paternal 

smoking during 

pregnancy: yes, no

• Lower sperm concentration and total sperm 

count among those exposed to smoking

• NS difference in sperm motility, 

morphology, or testis size

Note: 8-oxo-dG = 7-hydroxy-8-oxo-2’-deoxyguanosine; CI = confidence interval; ICSI = intracytoplasmic sperm injection; 

IVF = in vitro fertilization; NR = not reported; NS = not statistically significant; OR = odds ratio; PAH = polycyclic aromatic 

hydrocarbon; RR = rate ratio. aNot included in the 2004 Surgeon General’s report on the health consequences of smoking.
Reproductive and Developmental Effects 531

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

et al. 1995), but another study did not find a differential 

effect by chromosomal abnormality (George et al. 2006).

In examining exposure to secondhand smoke, 

the 2006 Surgeon General’s report on the health consequences of involuntary exposure to tobacco smoke concluded that the evidence was “inadequate to infer the 

presence or absence of a causal relationship” with SAB, 

on the basis of a few studies with inconsistent results 

(USDHHS 2006, p. 13). Since then, two studies have found 

an association with secondhand smoke on the order of 60 

to 80 percent, one with a biomarker of cotinine (George 

et al. 2006) and one that examined very early fetal loss 

(Venners et al. 2004). Another study did not find an association in examining only paternal smoking (Chatenoud 

et al. 1998), and one found an effect of exposure to secondhand smoke at either home or work only among women 

who also consumed alcohol or high amounts of caffeine 

(Windham et al. 1999c). 

Proposed mechanisms for an effect from tobacco 

smoke include fetal hypoxia from exposure to CO, vasoconstrictive and antimetabolic effects resulting in placental insufficiency and the subsequent death of the embryo 

or fetus (PCASRM 2004), and direct toxic effects of constituents of cigarette smoke. 

Ectopic Pregnancy

Ectopic pregnancy occurs when a fertilized egg is 

implanted outside the uterus, usually within the fallopian 

tube. It is estimated to occur in 1 to 2 percent of pregnancies (Chow et al. 1987; Goldner et al. 1993; Van Den Eeden 

et al. 2005) and accounts for approximately 6 percent of 

pregnancy-related deaths in the United States (Berg et al. 

2003; Chang et al. 2003). Factors associated with ectopic 

pregnancy include a history of sexually transmitted diseases and pelvic inflammatory disease, increased number 

of sexual partners, maternal age, history of SAB, history 

of surgical procedures affecting the fallopian tubes, previous use of an intrauterine device, and vaginal douching 

(Kendrick et al. 1997; Pisarska et al. 1998; Bouyer et al. 

2003). Affected women are at increased risk of infertility 

and recurrent ectopic pregnancy in subsequent pregnancies (Chow et al. 1987; Coste et al. 1991; Washington and 

Katz 1993; Skjeldestad et al. 1998), as would be expected 

among women with tubal damage.

The 2004 Surgeon General’s report found the 

evidence suggestive but not sufficient to infer a causal 

relationship between smoking and ectopic pregnancy 

(USDHHS 2004). A number of studies have associated 

Study OR, RR, or % (95% CI or p value) Comments

Ozgur et al. 

2005

Decreased rapidly motile cells by 30% at ≥20 compared with 

1–19 cigarettes/day (p <0.05)

Decreased normal tail morphology by 18% for smokers of ≥20 

cigarettes/day compared with nonsmokers (p <0.05)

Retrospective review of records with no 

exposure validation measures; missing 

data on more than 46% of records

Effects during 

adulthood of in 

utero exposure to 

cigarette smoke

     

Storgaard et al. 

2003

Decreased sperm concentration by 48%

(-69 to -11%) at exposure of >10 cigarettes/day

None

Jensen et al. 

2004

Decreased sperm concentration by 20.1%

(6.8–33.5%)

Decreased total sperm count by 24.5%

(9.5–39.5%)

None
Surgeon General’s Report

532 Chapter 8

Table 8.2 Association between maternal smoking and spontaneous abortion (SAB), 1998–2006
Reproductive and Developmental Effects 533

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Table 8.2 Continued
Surgeon General’s Report

534 Chapter 8

smoking with ectopic pregnancy, and in a meta-analysis 

of data from nine studies, the OR from pooled data on 

ectopic pregnancy from smoking was 1.77 (95 percent CI, 

1.31–2.22) (Castles et al. 1999). In addition, two other 

studies also reported significant associations between 

smoking and ectopic pregnancy (Bouyer et al. 2003; Karaer 

et al. 2006). Both found evidence of a dose-response relationship, even after adjustment for important potential 

confounders, such as a history of sexually transmitted diseases and infertility. In one study, the magnitude of the 

association of ectopic pregnancy and smoking was similar 

to that seen with infectious causes (Bouyer et al. 2003). 

In addition, plausible mechanisms for a relationship 

between smoking and ectopic pregnancy exist. The oviduct plays a critical role in the pickup and transport of the 

oocyte, and failure of this function can result in ectopic 

pregnancy. Both in vivo and in vitro studies showed that 

smoking impairs mammalian oviduct function (Talbot and 

Riveles 2005).

Preeclampsia

Preeclampsia is a syndrome of reduced organ perfusion attributable to vasospasm and endothelial activation 

with an onset after 20 weeks of gestation that is marked by 

proteinuria, hypertension, and dysfunction of the endothelial cells lining the uterus (National High Blood Pressure 

Education Program 2000; Sibai et al. 2005). The disease 

can be mild or severe. When accompanied by seizures 

that cannot be attributed to other causes, the diagnosis is 

established as eclampsia by exclusion. Preeclampsia affects 

approximately 2 to 8 percent of pregnancies (American 

Journal of Obstetrics and Gynecology 1988; Duley 2003; 

Zhang et al. 2003; Villar et al. 2004), and the incidence 

is highest in nulliparous women. The reported incidence 

varies widely, likely because of variation in population 

characteristics such as parity, race and/or ethnicity, and 

environmental factors (Zhang et al. 1997), as well as heterogeneity in classification systems (American Journal of 

Obstetrics and Gynecology 1988; Villar et al. 2004). Preeclampsia is a leading cause of pregnancy-related mortality in the United States (Berg et al. 2003). Morbidity and 

mortality are particularly high with early-onset disease 

(<33 weeks of gestation) (Sibai 2003; von Dadelszen et al. 

2003). Preeclampsia is also associated with fetal growth 

restriction, placental abruption, and perinatal death (Sibai 

et al. 2005). 

Risk factors for preeclampsia include preexisting medical conditions, multifetal gestation, an elevated 

body mass index (BMI), and older maternal age (Sibai et 

al. 2005). Immunologic factors have also been implicated 

(Zhang et al. 1997; Dekker and Robillard 2003; Einarsson 

et al. 2003), as have infectious and/or inflammatory 

conditions (Sibai et al. 2005). Evidence from epidemiologic and physiological studies has led to several hypotheses on the cause of preeclampsia. First, preeclampsia 

seems to be characterized by poor formation of the 

placenta (placentation) with a shallow invasion of the 

decidua and myometrium by trophoblast cells, resulting in 

an incomplete transformation of maternal spiral arteries 

that then retain their muscular characteristics (Brosens 

et al. 1972; Naicker et al. 2003). This process leads to placental ischemia and reperfusion and results in increased 

oxidative stress and vascular disease. Poor placentation in 

preeclamptic pregnancies could be the result of maternalfetal immune maladaptation (Sibai et al. 2005). Researchers think that the clinical manifestations of preeclampsia 

result from the release of placental factors in response to 

ischemic conditions, resulting in the endothelial dysfunction of maternal circulation (Roberts and Redman 1993). 

Endothelial dysfunction is characterized by a disruption 

in regulatory functions of vasomotor tone through coagulation, by platelet activity, and by fibrinolysis in the vascular endothelium (Roberts et al. 1989, 1991). It is unclear 

which placental factors may be involved, but one hypothesis is that an imbalance between proangiogenic and antiangiogenic factors may contribute. Animal and human 

studies support the hypothesis that angiogenic proteins 

may play a role in the etiology of preeclampsia (Maynard 

et al. 2003; Levine et al. 2004).

Smoking is inversely associated with preeclampsia; 

the pooled risk reduction is 32 percent (Conde-Agudelo et 

al. 1999). The 2004 Surgeon General’s report found the 

evidence sufficient to infer a causal relationship between 

smoking and a reduced risk of preeclampsia (USDHHS 

2004). Whether a dose-response relationship exists is 

unclear because study results are conflicting (Marcoux et 

al. 1989; Klonoff-Cohen et al. 1993; Zhang et al. 1999). 

Investigators have proposed three mechanisms through 

which smoking could reduce the risk of preeclampsia 

(Maynard et al. 2003; Fisher 2004): 

1. exposure to thiocyanate, which has a hypotensive 

effect (Andrews 1973); 

2. inhibition of thromboxane A2 production, a potent 

vasoconstrictor and platelet aggregation stimulator, 

or increase in levels of prostacyclin, a vasodilator and 

platelet aggregation inhibitor (Ylikorkala et al. 1985; 

Davis et al. 1987; Marcoux et al. 1989), both of which 

would improve the ratio of thromboxane A2 to prostacyclin (Lindqvist and Maršál 1999); and 

3. stimulation of proangiogenic factors, such as vascular endothelial growth factor (VEGF), and/or 
Reproductive and Developmental Effects 535

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

reduction in antiangiogenic factors, such as soluble 

VEGF receptor Flt-1 (sFlt-1) (Maynard et al. 2003; 

Fisher 2004; Jeyabalan et al. 2008). 

Placenta Previa

Placenta previa is the complete or partial obstruction of the cervical os by the placenta that affects approximately 0.4 percent of all births (Comeau et al. 1983; Iyasu 

et al. 1993; Faiz and Ananth 2003). Placenta previa has 

been associated with maternal and infant complications, 

such as preterm delivery, a hemorrhage that requires a 

blood transfusion, maternal death, and fetal or neonatal 

death (Salihu et al. 2003; Creasy et al. 2004). Neonatal 

mortality in pregnancies complicated by placenta previa 

may be up to three times higher than that in the general obstetric population (Salihu et al. 2003). The cause 

of placenta previa is unknown. However, risk factors with 

plausible etiologic mechanisms include advanced maternal age, multiparity, multifetal gestation, and a history of 

a cesarean section or a previous abortion (Ananth et al. 

2003; Faiz and Ananth 2003; Creasy et al. 2004). 

Epidemiologic studies have consistently reported 

an increased risk of placenta previa among smokers, and 

many studies show a dose-response relationship (Meyer et 

al. 1976; Zhang and Fried 1992; Monica and Lilja 1995). 

The estimated relative risks (RRs) from smoking are 1.3 to 

3.0 (Castles et al. 1999; Andres and Day 2000; Cnattingius 

2004). The 2004 Surgeon General’s report found the evidence sufficient to infer a causal relationship between 

smoking and placenta previa (USDHHS 2004). A mechanism commonly proposed to explain this association is the 

chronic hypoxemia and ischemia that result from smoking, with compensatory placental enlargement. However, 

not all studies have shown a clinically significant increase 

in placental size in smokers (Zhang et al. 1999; Larsen et 

al. 2002). 

Placental Abruption

Placental abruption, the premature separation of 

the placenta from the uterine wall, affects 0.5 to 2 percent of pregnancies (Rasmussen et al. 1996a; Ananth et 

al. 2001, 2005; Kyrklund-Blomberg et al. 2001). However, 

reported perinatal mortality in affected women is 8 to 12 

percent (Raymond and Mills 1993; Ananth and Wilcox 

2001; Kyrklund-Blomberg et al. 2001). Abruption may 

account for up to 14 percent of perinatal deaths (Rasmussen et al. 1996b; Ananth and Wilcox 2001). Ananth and 

Wilcox (2001) estimated that the perinatal mortality rate 

associated with abruption was 119 per 1,000 births compared with 8.2 per 1,000 among all births. Abruption can 

also result in neonatal asphyxia (Heinonen and Saarikoski 

2001), preterm delivery, and maternal disseminated intravascular coagulation if thromboplastic material is released 

into the mother’s circulatory system (Hladky et al. 2002). 

It is likely that the etiology of placental abruption 

is multifactorial (Misra and Ananth 1999). Potential risk 

factors include advanced maternal age (35 years or older), 

high parity, previous abruption, a history of infertility, 

preterm premature rupture of membranes (PPROM), 

small for gestational age (SGA), infant congenital malformations, multifetal pregnancy, hypertensive disorders, 

polyhydramnios, thrombophilia, diabetes, trauma, sudden uterine decompression, previous cesarean section, 

and uterine infections (Abdella et al. 1984; Williams et 

al. 1991; Raymond and Mills 1993; Ananth et al. 1996a,b; 

Kramer et al. 1997; Rasmussen et al. 1999; Cunningham 

et al. 2001; Kyrklund-Blomberg et al. 2001). Underlying 

causes of abruption could include vessel fragility, vascular 

malformations, uterine scarring from previous cesarean 

section, and placentation abnormalities (Dommisse and 

Tiltman 1992; Rasmussen et al. 1999; Hladky et al. 2002). 

In addition, failure of the maternal spiral arteries to transform into low-resistance dilated vessels could predispose 

the mother to ischemia and vessel rupture (Eskes 1997). 

In one study, a high percentage of placentas from women 

with severe abruption showed an absence of trophoblastic 

transformation, and not all cases were attributable to preeclampsia (Dommisse and Tiltman 1992). 

Studies have consistently associated smoking with 

an increased risk of placental abruption. Relative risks 

range from 1.4 to 1.9 (Raymond and Mills 1993; Ananth 

et al. 1999; Castles et al. 1999; Andres and Day 2000). 

The 2004 Surgeon General’s report found the evidence 

sufficient to infer a causal relationship (USDHHS 2004). 

In addition, study findings support a dose-response relationship (Ananth et al. 1999). Raymond and Mills (1993) 

found a 20-percent increase in the risk of abruption for 

every 10 cigarettes the mother smoked per day. Etiologic mechanisms proposed by researchers to explain this 

relationship include smoking-related degenerative and/or 

inflammatory changes in the placenta (Cnattingius 2004); 

decreased vitamin C (ascorbic acid) levels in smokers 

(Faruque et al. 1995), leading to impaired collagen synthesis (Cnattingius 2004); microinfarcts; and atheromatous changes in placental vessels (Naeye 1979; Andres 

and Day 2000) (see “Placenta” and “Maternal and Fetal 

Cardiovascular System” later in this chapter). Analyses 

of consecutive pregnancies indicate that abruption risk is 

decreased when women stop smoking between pregnancies, suggesting that effects of smoking are transient and 

not cumulative across pregnancies (Ananth and Cnattingius 2007).
Surgeon General’s Report

536 Chapter 8

Preterm Delivery

Delivery at less than 37 completed weeks of gestation 

(preterm delivery) is a leading cause of neonatal mortality 

and morbidity in developed countries and is often divided 

into categories of moderate preterm (32 to 36 weeks) and 

very preterm (<32 weeks) delivery. Preterm delivery complicated 12.3 percent of pregnancies in the United States 

in 2003 (Hamilton et al. 2004). Rates of preterm delivery 

in the United States and other industrialized countries 

have been increasing in the past decade and are partially 

attributable to an increase in the frequency of multiple 

births (Hamilton et al. 2004).

The underlying causes of preterm delivery are complex and multifactorial. Contributing factors include 

multigestational pregnancy, preeclampsia, placental 

abruption, placenta previa, intrauterine infections, uterine overdistension, and abnormal uterine anatomy, in 

addition to disorders of the cervix, endocrine system, and 

placenta. Other risk factors include race (e.g., African 

Americans have higher risk), low socioeconomic status 

(SES), underlying maternal medical conditions, genitourinary infections, poor maternal weight gain or nutrition, young or advanced maternal age, short maternal 

stature, and fetal abnormalities (Haram et al. 2003; Iams 

2003). Approximately 25 percent of preterm deliveries 

are medically indicated and are attributable to conditions 

affecting the mother and/or the fetus, and the remaining 

75 percent are spontaneous (Meis et al. 1995; Iams 2003). 

A substantial body of evidence indicates that intrauterine bacterial infections are associated with preterm labor 

and delivery, especially at earlier gestational ages (Cassell 

et al. 1993; Kimberlin and Andrews 1998; Andrews et al. 

2000; Goldenberg and Culhane 2003). Most intrauterine 

infections are believed to result from ascending infection, 

resulting from changes in vaginal/cervical flora, including 

bacterial vaginosis, or from the introduction of pathologic 

organisms. If these organisms ascend to the intrauterine cavity, they can cause an inflammatory reaction. The 

infection may progress to involve the chorion and/or 

amnion, fetal vessels, or the amniotic cavity, and even 

the fetus (review by Gonçalves et al. 2002; Romero et al. 

2002). Systemic maternal infection or maternal infections 

remote from the genitourinary tract have also been associated with preterm labor and delivery, but the risk of preterm labor and delivery attributable to these conditions is 

thought to be low (Romero et al. 2002). One mechanism 

proposed to explain the onset of preterm labor attributable to intrauterine infection is that bacterial invasion of 

the choriodecidual space results in the release of endotoxins and exotoxins, which, in turn, stimulate the production of cytokines such as TNFα, interleukin-6 (IL-6), IL-8, 

IL-1α, IL-1β, and granulocyte colony-stimulating factor. 

One hypothesis is that cytokines, endoxins, and exotoxins 

stimulate the release of prostaglandins and initiate neutrophil activation, which results in the release of metalloproteases. This process results in stimulation of uterine 

contractions by prostaglandins, rupture of chorioamniotic 

membranes, and softening of the cervix by metalloproteinases (review by Goldenberg et al. 2000).

Researchers have consistently associated smoking 

with preterm delivery, and smoking likely increases the 

risk of both very preterm and moderate preterm births 

(Kyrklund-Blomberg and Cnattingius 1998; Ancel et al. 

1999; Cnattingius et al. 1999; Gardosi and Francis 2000). 

The 2004 Surgeon General’s report found that the evidence was sufficient to infer a causal relationship between 

smoking and preterm delivery (USDHHS 2004). Smoking 

appears to increase the risk of both medically indicated 

and spontaneous preterm delivery (Kyrklund-Blomberg 

and Cnattingius 1998). However, estimates of the magnitude of the association vary among studies. In a metaanalysis of pooled data from 20 prospective studies, the 

estimate for any maternal smoking versus none was 1.27 

(95 percent CI, 1.21–1.33), and the ORs were 1.25, 1.38, 

and 1.31 for light, moderate, and heavy maternal smoking, respectively (Shah and Bracken 2000), suggesting a 

truncated dose-response relationship.

Exposure to secondhand smoke is also associated 

with preterm delivery in several studies. The 2006 Surgeon General’s report concluded that the evidence was 

suggestive but not sufficient to infer a causal relationship (USDHHS 2006). A study by Kharrazi and colleagues 

(2004) included measurement of cotinine and found that 

nonsmokers with higher levels had earlier delivery than 

did those with no measurable exposure to secondhand 

smoke. The risk increased about 30 percent with each log 

increase in cotinine (adjusted OR [AOR] = 1.29 [95 percent CI, 0.97–1.72]). 

Parity may modify the association between preterm 

delivery and smoking. As previously stated, the incidence 

of preeclampsia is highest among nulliparous women (see 

“Preeclampsia” earlier in this chapter). Because smoking 

protects against preeclampsia and preeclampsia can result 

in preterm delivery, the adverse effects of smoking on risk 

of preterm delivery may be masked in nulliparous women 

(Burguet et al. 2004). 

Mechanisms through which smoking may contribute to preterm delivery are unknown. Researchers have 

proposed that smoking could increase risk of intrauterine 

infections (review by Cnattingius 2004). Smokers have 

a twofold-to-threefold increase in risk for bacterial vaginosis, which is a risk factor for preterm delivery (Morris 

et al. 2001). Researchers have hypothesized that smoking increases this risk through its effects on vaginal flora 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

or through depletion of Langerhans cells, resulting in 

local immunosuppression (Smart et al. 2004). Alterations 

in the cervical cytokine profile have been associated with 

increased risk of preterm delivery; women with a high 

anti-inflammatory and low proinflammatory profile are at 

highest risk (Simhan and Krohn 2009). Cigarette smoking 

has been associated with increased cervical anti-inflammatory cytokines in early pregnancy, which could make 

women who smoke more vulnerable to reproductive tract 

infections and subsequent preterm delivery (Simhan et al. 

2005). Smoking can also reduce zinc levels, which could 

increase susceptibility to vaginal infections (Edman et al. 

1986; Sikorski et al. 1990; Shubert et al. 1992). Immunosuppressive effects of smoking could also increase the 

risk of upper genital infections, known to be associated 

with preterm labor and PPROM. Neonates born to smokers have been noted to have a decrease in all leukocytes, 

indicating possible fetal immune dysregulation (Pachlopnik Schmid et al. 2007). Pathways other than those 

involving infections have also been proposed. For example, 

investigators have suggested that smoking during pregnancy increases contractile sensitivity and activity of the 

myometrium, with exposure to oxytocin by upregulating 

expression of messenger RNA (mRNA) for oxytocin receptor (Egawa et al. 2003). Compared with unexposed pregnant rats, those with exposure to cigarette smoke were 

found to have higher contractile sensitivity and activity in 

response to oxytocin (Egawa et al. 2003).

Finally, findings have also suggested that smoking may disrupt the integrity of type III collagen, leading to weakening and rupture of the membranes and an 

increased risk of medical indications for preterm delivery, such as placental abruption and intrauterine growth 

restriction (IUGR) (Cnattingius 2004). 

Preterm Premature Rupture of Membranes 

PPROM is defined as the rupture of amniotic membranes before the onset of labor and before 37 completed 

weeks of gestation. PPROM occurs in up to 4.5 percent 

of deliveries and in approximately 40 percent of preterm 

births (Mercer et al. 2000). Pregnancies complicated by 

PPROM have higher rates of neonatal morbidity than 

do pregnancies complicated by idiopathic preterm labor 

(Arias and Tomich 1982). 

Factors that researchers have associated with 

PPROM include (1) nutritional deficiencies in vitamin C 

(Hadley et al. 1990; Casanueva et al. 1993), copper (Artal 

et al. 1979; Kiilholma et al. 1984), and zinc (Sikorski et 

al. 1990; Scholl et al. 1993); (2) vaginal bleeding (Harger 

et al. 1990; Ekwo et al. 1992); (3) multifetal pregnancies 

(Mercer et al. 1993); (4) a history of preterm delivery or 

PPROM in a previous pregnancy (Naeye 1982; Harger et al. 

1990; Ekwo et al. 1992; Mercer et al. 2000); (5) obstetric 

complications involving uterine overdistension (French 

and McGregor 1996); and (6) bacterial vaginosis (Kurki et 

al. 1992; Mercer et al. 2000) and intra-amniotic infections 

(Naeye and Peters 1980; Ekwo et al. 1993; Heffner et al. 

1993). However, it can be difficult to determine whether 

an intra-amniotic infection precedes or follows the rupture of membranes. A review by Lee and Silver (2001) discusses in detail the risk factors for PPROM.

Researchers suggest that structural deficiencies in 

the architecture of the amniotic membrane could increase 

the risk of PPROM (Shubert et al. 1992; Lee and Silver 

2001). Studies of spontaneously ruptured membranes 

demonstrate that membranes are thinner and collagen 

content is lower near the site of rupture. Moreover, these 

alterations appear to be focal rather than generalized 

(Skinner et al. 1981; Kanayama et al. 1985; French and 

McGregor 1996). The tensile strength of tissue depends 

on the collagens, especially types I and III. The amniotic membranes of women with PPROM have decreased 

amounts of type III, type V, and total collagen (Skinner 

et al. 1981; Kanayama et al. 1985; al-Zaid et al. 1988). In 

addition, Athayde and colleagues (1998) found that women 

with PPROM had higher amniotic fluid levels of metalloproteinases that degrade collagen types IV and V than did 

women with term labor. These researchers also suggested 

that infection could be an additional trigger if the host 

responds to an infection by activating matrix-degrading 

enzymes (Athayde et al. 1998). 

Many studies have associated smoking with an 

increased risk of PPROM (Lee and Silver 2001). The 2004 

Surgeon General’s report found sufficient evidence to 

infer a causal relationship between smoking and PPROM 

(USDHHS 2004). Researchers have hypothesized that 

smoking increases the risk of PPROM through several 

pathways. The effects of smoking on the immune system 

could increase the risk of genital tract infection or disrupt 

the cytokine system (French and McGregor 1996). Smoking could increase the inflammatory response and reduce 

the availability of nutrients such as vitamin C or decrease 

the uptake of nutrients by the placenta (French and 

McGregor 1996; Lykkesfeldt et al. 1996, 2000) (see “Other 

Molecular Mechanisms” later in this chapter). 

Developmental Endpoints

This section on developmental effects summarizes 

the epidemiologic evidence for prenatal effects of maternal smoking on the infant and child, including endpoints 

such as birth weight, perinatal or infant mortality, birth 

defects, and neurobehavioral. The discussion also briefly 
Surgeon General’s Report

538 Chapter 8

notes the evidence for effects from exposure to secondhand smoke on these outcomes. Studies have examined 

the effects of smoking on child growth, but this topic is 

not addressed in this report. Studying childhood health 

in relation to prenatal smoking is complicated by the possibility of exposure to secondhand smoke subsequent to 

birth, as well as other intervening factors between birth 

and some later outcomes that are difficult to assess.

Fetal Size and Growth

The first and the most widely studied effect of maternal smoking is the influence on fetal growth. Fetal growth 

cannot be directly assessed, so birth weight is used as a 

surrogate. However, birth weight reflects not only growth 

but also gestational age, as well as genetic potential, which 

is not commonly assessed. To account for gestational age, 

studies may examine IUGR, which is usually assessed from 

the distribution of birth weight by gestational week, in a 

standard population. The common definition of SGA is 

less than the 10th percentile of weight for the age. Another 

parameter that is examined includes low birth weight 

(LBW) (<2,500 grams [g]), sometimes among term births 

only (≥37 weeks).

The first Surgeon General’s report on smoking and 

health in 1964 noted an association of maternal smoking with LBW (U.S. Department of Health, Education, 

and Welfare 1964). The 2001 Surgeon General’s report 

on women and smoking concluded that “infants born to 

women who smoke during pregnancy have a lower average birth weight and are more likely to be SGA than are 

infants born to women who do not smoke” (USDHHS 

2004, p. 15). Furthermore, the 2004 Surgeon General’s 

report concluded that “the evidence is sufficient to infer a 

causal relationship between maternal active smoking and 

fetal growth restriction and low birth weight” (USDHHS 

2004, p. 28). These conclusions are based on a multitude 

of studies with consistent evidence of a dose-response 

relationship, confirmed by more recent studies using a 

biomarker of exposure to tobacco smoke.

Infants of smokers typically weigh 150 to 200 g 

less than infants of nonsmokers and are twice as likely 

(ORs = 1.5 to 2.5) to be LBW or SGA. Maternal smoking 

appears to have the strongest effect on birth weight through 

growth retardation and, to a lesser extent, through a shortened gestation (Ananth and Platt 2004; USDHHS 2004). 

On the basis of a maternal smoking rate of about 12 percent during pregnancy, the etiologic fraction (EF) for LBW 

from smoking was calculated as 6.4 percent for all births 

and 10.9 percent for single births (Magee et al. 2004). The 

EF for LBW from smoking among births at full term was 

slightly higher at 13.4 percent or 16.7 percent for single 

births, which comprise most births. The authors also 

reported that 60 percent of the effect of smoking on LBW 

in the overall population was among light smokers. 

Because of the established effects of maternal active 

smoking, many studies have also examined fetal growth in 

relation to exposure of the mother to secondhand smoke. 

Several reviews concluded that exposure to secondhand 

smoke is associated with adverse effects on infant growth 

or an increased risk of LBW and SGA (NCI 1999; WHO 

1999a; USDHHS 2001; British Medical Association 2004). 

Moreover, the 2006 Surgeon General’s report concludes 

that “the evidence is sufficient to infer a causal relationship between exposure to secondhand smoke and a small 

reduction in birth weight” (USDHHS 2006, p. 13). The 

highest quality studies indicate birth weight decrements 

of 15 to 100 g and an OR for LBW or SGA of 1.1 to 1.7 

from exposure to secondhand smoke (NCI 1999). A metaanalysis of pooled data conducted through 1995 calculated 

a mean weight decrement of 28 g (95 percent CI, 16–40) 

among infants of mothers who did not smoke but were 

exposed to secondhand smoke and ORs of 1.2 for IUGR and 

1.4 for LBW (Windham et al. 1999a). One study based on 

a sensitive assay for cotinine showed a birth weight decrement of 27.2 g (95 percent CI, 0.6–53.7) per unit change 

in log cotinine, which represented a decrement of about 

100 g between the highest and lowest cotinine quintiles 

(Kharrazi et al. 2004). 

Several studies have shown that the effects of exposure to tobacco smoke, primarily active but also involuntary exposure, appear to be stronger among older mothers

(Wen et al. 1990; Wisborg et al. 1996; Haug et al. 2000; 

Windham et al. 2000; Salihu et al. 2005). Risk may also 

vary by racial and ethnic groups, and some studies (Mainous and Hueston 1994; USDHHS 1998; Windham et al. 

2000) noted stronger effects among non-Whites or Blacks. 

Some of these variations may be a result of differences in 

nicotine metabolism among racial groups or differences 

in smoking and exposure patterns. Smoking may cause 

reduced birth weight or fetal growth due to fetal hypoxia

resulting from exposure to CO, other effects on fetal 

nutrition, or the action of PAHs (see “Tobacco Smoke Toxicants and the Reproductive System” and “Other Molecular Mechanisms” later in this chapter). 

Perinatal and Infant Mortality

The definition of perinatal mortality may vary 

slightly across studies, but it commonly includes stillbirth at more than 28 weeks of gestation and early neonatal deaths (first 7 days of life). Infant mortality includes 

death of a live-born child in the first year of life and can 

be divided into the neonatal (first month) and postneonatal (1 month to 1 year) periods. Neonatal mortality is 

more related to prenatal conditions. Previous reports of 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

the Surgeon General have reviewed the data for an effect 

of smoking on mortality. The 2001 report concluded, “the 

risk for perinatal mortality—both stillbirth and neonatal 

deaths—and the risk for sudden infant death syndrome 

(SIDS) are increased among the offspring of women who 

smoke during pregnancy” (USDHHS 2001, p. 15). The 

2004 Surgeon General’s report also concluded, “the evidence is sufficient to infer a causal relationship between 

sudden infant death syndrome and maternal smoking during and after pregnancy” (USDHHS 2004, p. 7). However, 

the report noted the difficulty of separating prenatal from 

postnatal effects of maternal smoking.

Many studies have found a slightly increased risk 

of approximately 20 to 30 percent for stillbirth or neonatal mortality associated with smoking (USDHHS 2004). 

A meta-analysis of pooled data from 23 cohort studies of 

perinatal mortality calculated a RR of 1.26 (95 percent CI, 

1.19–1.34) (DiFranza and Lew 1995). In one study, the 

risk was higher for postneonatal death (AOR = 1.6; 95 percent CI, 1.41–1.85) than for neonatal death (AOR = 1.2; 

95 percent CI, 1.05–1.30), which was primarily attributable to two causes: respiratory disease and SIDS (Malloy et 

al. 1988). A study in India (Gupta and Subramoney 2006) 

reports an adjusted risk for stillbirth three times higher 

for mothers who use smokeless tobacco than for those 

who do not use smokeless tobacco. Some evidence for a 

dose-response relationship was shown for frequency of 

use. Two previous studies from India had also reported an 

increased risk of stillbirth or perinatal death with use of 

smokeless tobacco (primarily chewing tobacco) (Krishna 

1978; Shah et al. 2000). These investigations lend further 

support to the literature on the adverse effects of tobacco 

use, which may be related to heavy metals or nicotine, 

because CO from tobacco smoke would not be present (see 

“Tobacco Smoke Toxicants and the Reproductive System” 

later in this chapter).

Studies of SIDS and maternal smoking that controlled for other factors showed ORs of 1.8 to 3.1. Several 

of those studies also report a dose-response relationship 

(NCI 1999; USDHHS 2004). A meta-analysis comparing women who did or did not smoke during pregnancy, 

regardless of smoking status after delivery, calculated a 

pooled OR of 2.98 (95 percent CI, 2.51–3.54) (DiFranza 

and Lew 1995). Some studies have attempted to separate 

the effects of prenatal exposure from those of postnatal 

exposure. In one study, the risk of SIDS was increased in 

infants with only postpartum exposure to tobacco smoke 

but was even greater with both prenatal and postnatal 

exposures (Schoendorf and Kiely 1992). A large study

in which participants were asked detailed questions on 

exposure to tobacco smoke found similar risks for maternal or paternal smoking, but the risks increased with more 

smokers in the household (Klonoff-Cohen et al. 1995). 

In addition, some studies that attempted to examine the 

independent effects of paternal smoking observed elevated 

risks of SIDS (Mitchell et al. 1993; Blair et al. 1996). Rates 

of SIDS have decreased over time with strong public 

education campaigns to place infants in the supine position while they sleep. Subsequent studies found that the 

risk attributable to maternal smoking has concomitantly 

increased and smoking may now be the greatest preventable cause of SIDS (Chong et al. 2004; Anderson et 

al. 2005).

Birth weight is one of the strongest predictors of 

infant survival. However, the effects of reduced growth 

versus shortened gestation are important to consider in 

determining etiology. Both reduced growth and shortened 

gestation appear to be related to infant mortality and SIDS 

(McCormick 1985; Oyen et al. 1995; Paneth 1995; Ananth 

and Platt 2004). The longer the gestation for a given birth 

weight, the lower is the mortality (McCormick 1985; Wilcox and Skjærven 1992). The increased risk of mortality 

associated with LBW appears to continue beyond infancy 

into childhood (Samuelson et al. 1998; Xu et al. 1998). 

Furthermore, studies suggest an association of maternal smoking with a higher mortality rate that continues 

beyond infancy. This effect was greater after adjustment 

for birth weight (Hofvendahl 1995). Infants who experience symmetrical growth retardation (in weight, length, 

and head circumference) associated with maternal smoking may be less likely to exhibit later “catch-up” growth 

and appear to be more likely to have cognitive deficits 

and difficulties in school (McCormick 1985). Thus, other 

effects associated with maternal smoking, such as perinatal mortality, may be mediated through reduced fetal 

growth and, to some extent, through a shortened gestation period (Ananth and Platt 2004). Some studies have 

found higher risks of infant mortality associated with 

smoking among mothers who are 35 years of age or older 

or of certain racial groups (Cnattingius et al. 1988; Li and 

Daling 1991). Studies have also found an increased risk of 

SIDS with placental abnormalities (Li and Wi 1999), thus 

suggesting another mechanism by which smoking may 

lead to SIDS. 

Birth Defects 

The 2004 Surgeon General’s report summarized 

epidemiologic studies published between 1974 and 1998 

on the relationship between maternal smoking during 

pregnancy and the risk for congenital malformations 

(USDHHS 2004). The report concluded that “the evidence 

is inadequate to infer the presence or absence of a causal 

relationship between maternal smoking and congenital 

malformations in general” (USDHHS 2004, p. 28). For oral 

clefts, however, several studies reported increased risks, 
Surgeon General’s Report

540 Chapter 8

and the evidence was considered to be suggestive, but not 

sufficient, to infer a causal relationship with smoking.

Since the 2004 Surgeon General’s report, additional 

studies have examined possible associations of maternal 

smoking with major birth malformations. The evidence 

in support of an association between smoking and an 

increased risk for oral clefts has become stronger (Table 

8.3). A meta-analysis of data from studies published 

between 1974 and 2001 focused on 9 studies that examined total orofacial clefts and 15 that examined cleft lip 

with or without cleft palate and cleft palate alone. The 

study found an association between maternal smoking 

and a 34-percent increase in the risk of cleft lip with or 

without cleft palate and a 22-percent increase in the risk 

of cleft palate alone (Little et al. 2004a). More recently, 

similar findings were also observed by Honein and colleagues (2007). Other studies provide evidence of a doseresponse relationship for maternal smoking and the risk 

for cleft lip with or without cleft palate (Wyszynski and 

Wu 2002; Little et al. 2004b; Honein et al. 2007) and 

for cleft palate alone (Little et al. 2004b). A recent study 

assessing maternal tobacco exposure by cotinine levels in 

mid-pregnancy serum samples found an OR of 2 for cleft 

lip with or without cleft palate (Shaw et al. 2009).

Studies on interactions between genes and smoking 

and between vitamin use and smoking contribute to an 

understanding of the etiology of oral clefts (van Rooij et al. 

2002; Jugessur et al. 2003; Shi et al. 2007) (see “Fetal Tis- “Fetal Tissue and Organogenesis” and “Smoking and Maternal and 

Neonatal Genetic Polymorphisms” later in this chapter).

One study reported an increase in the risk for cleft lip with 

or without cleft palate that was strongest among offspring 

whose mothers had smoked but had not consumed multivitamins during the periconceptive period (Shaw et al. 

2002). Results did not suggest an interaction for isolated 

cleft palate. Study findings also supported an increased 

risk of clefting with paternal smoking or involuntary 

exposure to tobacco smoke (Savitz et al. 1991; Zhang et al. 

1992; Shaw et al. 1996). Whether paternal smoking acts 

through exposure of the mother to secondhand smoke or 

directly on male gametes is not clear.

A number of studies have also investigated maternal smoking in relation to cardiovascular malformations. 

A review of data from 13 studies published between 1971 

and 1999 found mixed results. Twelve of the studies provided results for cardiovascular malformations combined 

and seven studies for specific subgroups of cardiovascular 

defects examined separately (Källén 2002a). Combining 

all cardiovascular malformations represents a heterogeneous group but examining subgroups resulted in low 

power for several studies. The conflicting results probably 

reflect differences in research methods, including case 

ascertainment, classification, control of confounding, and 

sample size of the case group. Other studies have reported 

associations of maternal smoking with cardiovascular 

malformations (Table 8.4), including conotruncal defects, 

atrial septal defects, and atrioventricular septal defects 

(Torfs and Christianson 1999); l-transposition of the great 

arteries (Steinberger et al. 2002; Kuehl and Loffredo 2003); 

and conotruncal defects among offspring whose mothers 

did not use vitamins (Shaw et al. 2002). Steinberger and 

colleagues (2002) found an association between paternal 

smoking and single-ventricle defects. These more recent 

exploratory studies present methodologic issues similar 

to those noted in the meta-analysis by Källén (2002a). In 

addition, Malik and colleagues (2008) found an association between periconceptual smoking and septal heart 

defects. There is a need for further research with large, 

population-based studies that incorporate standardized 

methods for case ascertainment and classification to 

determine whether a relationship exists between maternal 

smoking and the risk of cardiovascular malformations.

Studies of other birth defects have found an association between maternal smoking and an increased risk 

for clubfoot (Honein et al. 2000; Skelly et al. 2002), craniosynostosis (Källén 1999; Carmichael et al. 2008), and 

gastroschisis (Werler et al. 2003), but not for spina bifida 

(Table 8.5) (Shaw et al. 2002; van Rooij et al. 2002). Studies report mixed results for maternal smoking and limb 

deficiency defects (Hwang et al. 1998; Shaw et al. 2002; 

Carmichael et al. 2004), Down syndrome (Chen et al. 

1999; Yang et al. 1999), and for cryptorchidism and hypospadias (Akre et al. 1999; Källén 2002b; Pierik et al. 2004). 

Maternal smoking may interfere with normal 

organ development in offspring in several ways, including through fetal hypoxia, alterations in essential nutrients, teratogenic effects, and DNA damage. Those effects 

may be related to exposure to tobacco smoke components 

such as CO, nicotine, cadmium, and PAHs (Chernoff 1973; 

Mochizuki et al. 1984; Lammer et al. 2004; Munger et al. 

2004; Ziaei et al. 2005). In addition, certain populations 

with genetic polymorphisms may be more susceptible to 

damage attributable to exposure to tobacco smoke because 

of alterations in metabolic pathways (see “Fetal Tissue and 

Organogenesis” and “Smoking and Maternal and Neonatal 

Genetic Polymorphisms” later in this chapter). 

Neurodevelopment

Maternal smoking and exposure to secondhand 

tobacco smoke during pregnancy affect infant health status at birth as described earlier and are hypothesized to 

affect physical and mental development in infancy and 

early childhood as well. Studies have reported evidence 

of lower weights and shorter heights into the preschool 

period (Fox et al. 1990), in addition to correlations of 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

maternal smoking with microcephaly and hydrocephaly, 

particularly among female infants (Honein et al. 2001). 

Reviews have also examined the links between maternal 

smoking and mental development in offspring (Hardy 

and Mellits 1972; Lassen and Oei 1998). Earlier Surgeon 

General’s reports examined this topic and reported possible effects. However, at the time of the 2004 Surgeon 

General’s report, the evidence was considered “inadequate 

to infer the presence or absence of a causal relationship 

between maternal smoking and physical growth and neurocognitive development of children” (USDHHS 2004, p. 

601), and this conclusion was echoed in the examination 

of secondhand smoke (USDHHS 2006). Some key studies, as well as others published since those included in the 

prior reports of the Surgeon General (e.g., 2004 and later), 

are summarized below. 

Researchers have suggested that prenatal exposure 

to smoking poses a unique risk for neurologic development and intellectual abilities attributable to impairments 

of the central nervous system (Olds et al. 1994). Drews and 

colleagues (1996) studied a sample of 221 children aged 

10 years and reported that those with mental retardation 

were more likely than control participants with no mental retardation to have mothers who had smoked during 

pregnancy. Moreover, the rates of retardation increased 

with the number of cigarettes mothers smoked. McCartney and colleagues (1994) speculated that intrauterine 

exposure to nicotine specifically affects the physiology of 

outer hair cells in the ear that underlies language ability 

and leads to poorer performance scores among offspring 

on assessments that rely heavily on verbal abilities.

Investigators have found it difficult to document 

a consistent impact of maternal smoking on cognitive 

development in infants and young children, because many 

factors affect cognitive development. For example, in a 

study of two- and four-year-old children of mothers who 

smoked compared with children in the same age groups 

whose mothers did not smoke, Baghurst and colleagues 

(1992) reported small but significant group differences on 

the Bayley Scales of Infant Development (BSID) and the 

McCarthy Scales of Children’s Abilities (MSCA). However, 

group differences were not significant after controlling 

for SES, maternal intelligence quotient, and quality of 

the home learning environment. Sexton and colleagues 

(1990) also reported better scores among three-year-olds 

whose mothers had stopped smoking during pregnancy 

compared with children whose mothers had smoked 

more than 10 cigarettes a day during pregnancy. Group 

differences in performance on the Minnesota Child 

Development Inventory and the MSCA were small, but differences remained significant after adjustment for birth 

weight, SES, and certain maternal and child characteristics. Trasti and colleagues (1999) reported lower scores 

on the Wechsler Preschool and Primary Scale of Intelligence-Revised for a sample of 369 children aged five years 

whose mothers had smoked during pregnancy compared 

with children of mothers who did not smoke. However, 

significant group differences were not found after adjustment for maternal education level. These researchers also 

reported no differences on the BSID in a sample of 376 

children from the same population at 13 months of age by 

mothers’ smoking status. 

Batstra and colleagues (2003) reported poorer performance on mathematics and spelling achievement tests 

among a group of 1,186 children aged 5 through 11 years 

whose mothers smoked, and differences remained after 

adjustment for SES and for prenatal and perinatal complications. A Danish study found effects of prenatal smoking 

during the third trimester on adult intelligence even after 

adjustment for sociodemographic variables (Mortensen 

et al. 2005). In contrast to other studies, Eskenazi and 

Trupin (1995) reported slightly higher but nonsignificant 

scores on the Peabody Picture Vocabulary Test and the 

Raven Progressive Matrices Test for five-year-old children 

whose mothers had smoked during pregnancy compared 

with those for children of mothers who had not smoked, 

even after adjustment for parental education, SES, age, 

race, and preschool attendance. Some significant decrements in performance on these same measures and significant differences in the maternal-rated activity levels were 

attributable to exposure to secondhand tobacco smoke 

during childhood. Other studies show cognitive deficits 

with prenatal exposure to secondhand smoke that are 

exacerbated by conditions of material hardship (Rauh et 

al. 2004). After adjustment, decrements in cognitive and 

academic abilities were reported with increasing cotinine 

levels within the range indicating exposure to secondhand 

smoke during childhood (Yolton et al. 2005).

Despite these inconsistent findings on general 

assessments of children’s cognition and intelligence, 

findings more consistently show an association between 

maternal smoking and children’s lower performance on 

assessments of verbal skills in general, as well as on specific language and auditory tests. For example, a sample 

of 110 children aged 6 to 11 years whose mothers had 

smoked during pregnancy performed more poorly on 

tasks tapping phonologic processing skills that are known 

to be related to both language and reading abilities 

(McCartney et al. 1994). Follow-up studies of the same 

cohort reported that maternal smoking and maternal 

involuntary exposure to tobacco smoke negatively affected 

the performance of children aged 9 and 12 years on standardized assessments of language and reading, as well 

as on assessments of general intelligence skills (Fried et 

al. 1997). Butler and Goldstein (1973) studied a sample 

of more than 9,000 children aged 7 and 11 years whose 
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542 Chapter 8

Table 8.3 Association between maternal smoking and orofacial clefts (OFCs), 1999–2009a
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544 Chapter 8

Table 8.3 Continued
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease
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546 Chapter 8

Table 8.4 Association between maternal smoking and cardiovascular malformations, by phenotype, 

1999–2008
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548 Chapter 8

Table 8.5 Association between maternal smoking and noncardiovascular congenital malformations, by type of 

malformation, 1998–2008
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Table 8.5 Continued
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Table 8.5 Continued
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mothers had smoked during pregnancy. These children 

were three to five months behind children of nonsmoking mothers in reading, mathematics, and general cognitive abilities. In more than 5,000 youth aged 6 through 

16 years from the Third National Health and Nutrition 

Examination Survey, deficits in reading and mathematics 

scores were associated with higher current exposure to 

secondhand smoke (Yolton et al. 2005).

Researchers have used various types of tests that 

measure both cognitive and behavioral aspects of development to study the relationship between possible language 

impairments and maternal smoking. Data from studies 

using evoked brain responses indicate that infants born to 

mothers who smoked approximately one pack of cigarettes 

per day showed atypical patterns of brain organization, 

which reflected poorer speech discrimination than that of 

infants born to mothers who did not smoke. Compared 

with infants of smokers, the unexposed infants exhibited 

more common forms of brain lateralization for speech 

and showed evidence of better discrimination of consonant and vowel syllables (Molfese et al. 2004). This finding parallels findings in studies that reported long-term 

impacts on language and cognitive domains in children 

whose mothers smoked (Makin et al. 1991; McCartney et 

al. 1994). These results indicate that prenatal exposure 

to smoking in otherwise healthy infants can be linked to 

significant changes in brain physiology associated with 

basic perceptual skills. These effects may be long term, 

with impacts noted in later school performance. A study 

of gravid mice exposed to tobacco smoke supports these 

findings. The study revealed that the offspring had a 

developmental delay in neonatal reflexes and notable 

behavioral deficits in adulthood, including impaired 

learning and memory abilities (Li and Wang 2004). CO 

in tobacco smoke induces fetal hypoxia and may contribute to these effects (see “Carbon Monoxide” later in 

this chapter).

Table 8.5 Continued
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Pathophysiological and Cellular and Molecular 

Mechanisms of Smoking

This section explores various mechanisms by which 

smoking may affect reproductive and developmental outcomes at the pathophysiological and cellular levels.

Endocrine System

One mechanism by which smoking may contribute 

to various reproductive outcomes is alterations in hormone function. Researchers have suggested that smoking 

has antiestrogenic effects (Baron et al. 1990). However, 

there is also evidence of effects on hormones other than 

estrogen, which may vary by gender and the stage of life.

Premenopausal Women 

Hormone function has been difficult to study in 

non-clinic-based populations, because of the cyclic 

nature of hormone excretion and day-to-day variations in 

premenopausal women. During regular menstrual cycles, 

the hormone dynamics are predictable in a pattern that 

reflects the integrity of the hypothalamic-pituitary-gonadal 

(HPG) axis. Excretion of the follicle-stimulating hormone 

(FSH) from the pituitary gland is critical for ovarian follicle recruitment, development, and maturation (van Santbrink et al. 1995). The synthesis and excretion of estrogen 

by the follicles reflect ovarian activity that then modulates 

the release of gonadotropins from the pituitary through a 

negative-feedback loop. After ovulation has occurred, the 

follicle undergoes luteinization, and the corpus luteum 

excretes progesterone and some estrogen to prepare the 

uterine lining for implantation. In the absence of conception, estrogen and progesterone levels decline, followed 

by menstruation. Should fertilization occur, the steroid 

levels continue to rise along with levels of other hormones, such as human chorionic gonadotropin (hCG), to 

maintain the pregnancy. The placenta takes over hormone 

production during pregnancy.
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Smoking has been considered potentially antiestrogenic (Baron et al. 1990), primarily because of the nature 

of its association with hormonally related diseases such as 

reproductive cancers. However, the 2001 Surgeon General’s report on women and smoking concluded that circulting levels of the major endogenous estrogens are not 

altered among smokers (USDHHS 2001). Some studies 

were hampered by a lack of biosampling points, small 

numbers of participants, or the inclusion of postmenopausal or potentially perimenopausal women. Details on 

15 studies of premenopausal women are provided in Table 

8.6. Most of these studies excluded women who were taking hormones or who were known to have menstrual problems. Nevertheless, the studies represent a variety of ages 

and did not always adjust for factors such as age and obesity. Two studies (MacMahon et al. 1982b; Westhoff et al. 

1996) reported levels of urinary excretion of estrone, estradiol, and/or estriol in the luteal phase among smokers that 

were lower than those among nonsmokers, suggesting 

reduced estrogen production. However, several other 

studies did not observe significant differences in serum 

levels of estradiol by smoking status among premenopausal women (Longcope and Johnston 1988; Key et al. 

1991; Berta et al. 1992). The study by Michnovicz and colleagues (1986) is often cited for the discovery that smoking 

induced the 2-hydroxylation of estrone to relatively inactive metabolites and decreased estriol excretion. A later, 

much larger study, however, did not find differences in the 

circulating levels of the 2a- or 16a-hydroxy metabolites in 

nulliparous smokers versus nonsmokers after adjustment 

for age, ethnicity, and length of menstrual cycle (Jernström et al. 2003). Zumoff and colleagues (1990) measured 

serum at multiple points during the cycle and found that 

estradiol was actually increased among heavy smokers in 

the follicular phase, particularly early, at baseline. A study 

with only a single serum sample obtained in the early follicular phase (Lucero et al. 2001) found that current smokers had higher baseline estradiol levels than did former 

olifetime nonsmokers, but this finding was not significant 

after adjustment. Examination of dose by pack-years1 did 

not indicate a dose-response pattern, but this analysis may have been diluted by including former smokers 

with smokers if the effects do not persist after smoking cessation. 

Among women who had IVF, smokers had higher 

baseline levels of 17-b-estradiol than did nonsmokers 

(Weigert et al. 1999). A later study examined hormonal 

dynamics by daily measurement of urinary levels of 

estrone and progesterone metabolites throughout the 

cycle, in relation to smoking level that was verified by 

cotinine bioassay (Windham et al. 2005). This analysis 

showed that heavy smokers had elevated baseline (e.g., 

early follicular phase) levels of the steroid metabolites, a 

finding consistent with results in other studies (Longcope 

and Johnston 1988; Zumoff et al. 1990; Key et al. 1996; 

Lucero et al. 2001). A study of Chinese nonsmokers examined the effects of secondhand smoke on urinary levels of 

hormone metabolites and found an association with lower 

mean levels of estrone conjugates only for nonconceptive 

cycles (Chen et al. 2005). 

Some of the disease patterns observed with smoking may reflect changes in androgen or progesterone levels, rather than estrogen levels, or changes in the ratio of 

androgens to estrogens. Some studies have reported that 

smoking increases adrenal activity and have found elevations in adrenal androgens among postmenopausal smokers (Friedman et al. 1987; Khaw et al. 1988; Longcope and 

Johnston 1988; Key et al. 1991). Researchers have found 

elevated serum testosterone levels in female smokers that 

were positively correlated with estradiol levels in menstrual cycling women who had IVF (pre-hCG treatment) 

(Barbieri et al. 2005). Elevated testosterone levels in 

female smokers were also positively correlated with obesity (Longcope and Johnston 1988; Sowers et al. 2001). 

Zumoff and colleagues (1990) reported elevated serum 

levels of progesterone among heavy smokers during the 

early follicular phase, a time when most progesterone is 

from the adrenal cortex. This finding is again consistent 

with the urine metabolite results reported by Windham 

and colleagues (2005) (Table 8.6). However, Zumoff and 

colleagues (1990) observed little difference in progesterone levels in the luteal phase. Windham and colleagues 

(2005) observed dampened progesterone metabolites in 

the luteal phase with heavy smoking. Berta and colleagues 

(1992) found that regular smokers had lower plasma levels of progesterone in a single sample per day during the 

mid-luteal phase. However, the small study by Westhoff 

and colleagues (1996) did not find these differences in 

examining data on all smokers without considering the 

amount smoked. In addition, the study on exposure to secondhand smoke did not report reductions in progesterone 

metabolite levels with exposure (Chen et al. 2005). 

In vitro experiments support the effects on progesterone by showing that granulosa and tumor cells treated 

with alkaloids found in cigarette smoke or with an aqueous extract of cigarette smoke showed a dose-dependent 

inhibition of progesterone production (Bódis et al. 1997; 

Gocze et al. 1999; Gocze and Freeman 2000; Miceli et al. 

2005). In contrast, estradiol production was little affected 

or was slightly stimulated. Cell growth and DNA content 

1Pack-years = the number of years of smoking multiplied by the number of packs of cigarettes smoked per day.
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also decreased with treatment, leading the authors to 

suggest that smoking directly inhibits cellular progesterone synthesis through less specific cytotoxic effects on 

progesterone-producing cells (Gocze and Freeman 2000). 

Other proposed mechanisms include modulations in the 

prostaglandin system (Miceli et al. 2005) or inhibition of 

aromatase enzymes. 

Some studies examined gonadotropin FSH levels 

by smoking status (Table 8.6). Three studies that measured a single serum FSH level in the first few days of the 

cycle found higher levels associated with smoking (Cramer et al. 1994; Cooper et al. 1995; Lucero et al. 2001). 

Another study with a similar finding of higher FSH in 

smokers did not include the time during the menstrual 

cycle when the single serum sample was obtained (Backer 

et al. 1999). In addition to the limitation of single serum 

samples, these studies tended to include some perimenopausal or postmenopausal older women even though FSH 

levels naturally rise during and after menopause. Another 

study measured daily urinary levels of FSH metabolites in 

women of reproductive age. These findings also showed 

mean FSH levels among moderate-to-heavy smokers (≥10 

cigarettes per day) that were higher than those among 

nonsmokers during the luteal-follicular phase transition 

between cycles (Windham et al. 2005).

Serum levels of FSH increase with age, and researchers think this increase reflects the diminishing supply of 

oocyte- and gonadotropin-responsive follicles that leads to 

the release of the HPG axis from ovarian control (Marcus et al. 1993; Cramer et al. 1994; Westhoff et al. 1996). 

The FSH level is thus considered a marker of ovarian 

reserve or competence, and as such, it may also be useful for 

identifying agents with toxic effects on the ovaries (Scott 

et al. 1989; Scott and Hofmann 1995). As progesterone 

modulates FSH in the endocrine feedback loop, the lower 

levels of luteal phase progesterone metabolites observed 

in some studies are consistent with the decreased entrainment of FSH, which would lead to the observed elevations. 

The increase in FSH may accelerate the recruitment and 

development of follicles, moving ovulation earlier, and 

perhaps leading to inadequate follicle development followed by inadequate function of the corpus luteum. Progesterone controls the endometrial response and is critical 

for early maintenance of pregnancy. Studies have implicated a luteal phase deficiency as a cause of infertility and 

fetal loss (Pittaway et al. 1983; Tulppala et al. 1991). Earlier 

ovulation would also be consistent with the shortening of 

the menstrual cycle or of the follicular phase observed 

in smokers (see “Menstrual Function, Menopause, and 

Menarche” earlier in this chapter). The pattern of higher 

FSH levels, shorter cycles, and thus more frequent ovulation in smokers is also consistent with the observation 

that smokers tend to experience earlier menopause (see 

“Menstrual Function, Menopause, and Menarche” earlier 

in this chapter). 

Pregnant Women

The 2001 Surgeon General’s report noted that 

smoking more clearly affects estrogen levels during pregnancy than when a woman is not pregnant (USDHHS 

2001). Several studies show that smokers have lower circulating levels of estriol and estradiol than do nonsmokers 

(USDHHS 2001), confirmed for estriol measured multiple 

times throughout pregnancy (Kaijser et al. 2000). Furthermore, the study found a positive correlation of estriol 

and birth weight. This study’s results support the hypothesis of Michnovicz and colleagues (1986) that smokers 

and nonsmokers may metabolize estrogens differently, 

with acceleration of the 2-hydroxylation versus the 

16α-hydroxylation pathway in smokers. In addition, some 

studies show an increase in 2-hydroxylation and 4-hydroxylation activity in placental tissues of smokers (Chao et al. 

1981; Juchau et al. 1982). In a later study using placental microsomes, smokers had increased placental formation of 4-hydroxyestradiol, 7α-hydroxyestradiol, and most 

markedly, 15α-hydroxyestradiol, but little or no difference 

in the overall rate of placental estradiol metabolism or in 

the formation of the estrone, 2α-hydroxyestradiol, and 

other metabolites (Zhu et al. 2002). A study of progesterone in placental tissue samples revealed that levels among 

smokers were lower than those among nonsmokers 

(Piasek et al. 2001), a finding consistent with the data for 

nonpregnant women. 

Using stored serum samples, Kandel and Udry 

(1999) found that the cotinine levels were positively correlated with the testosterone levels, especially in samples 

obtained during the second trimester of pregnancy. In 

turn, maternal testosterone levels were correlated with 

those in adult daughters. An animal study also showed 

that nicotine infusion resulted in increased plasma testosterone in ovine fetuses. This study also associated maternal exposure to nicotine with increased testosterone levels 

in 30-day-old (adolescent) female offspring of rats but not 

in male offspring (Smith et al. 2003). Changes in hormone 

patterns during pregnancy may therefore affect both pregnancy outcome and the endocrine profile of the offspring, 

thus relating to possible effects on neurobehavioral endpoints, puberty, or later reproductive status, including 

semen quality.

Men

Numerous studies have also examined hormone 

levels in men in relation to smoking (Table 8.7). Some 

studies examined the acute effects of smoking cigarettes 

in a standardized protocol, and others studied baseline 
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Table 8.6 Association between smoking and reproductive hormones in women
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hormone levels in smokers compared with those in nonsmokers. The results from studies spanning many years 

are inconsistent. These studies also vary in considering obesity, which may be important because increased 

weight is associated with the peripheral conversion of androgens to estrogens. Also, studies generally report total 

circulating levels of hormones but vary in reports of free 

or bioavailable levels. 

The most consistent finding is an increase of androstenedione in smokers in three studies (Barrett-Connor 

and Khaw 1987; Dai et al. 1988; Field et al. 1994). Testosterone levels also increased with smoking in many studies, 

but some studies found decreases or no differences (Table 

8.7). The study by Sofikitis and colleagues (1995) is noteworthy for demonstrating differences between apparent 

endocrine versus paracrine levels of testosterone related 

to effects from smoking. Animal studies show that prenatal exposure to nicotine is related to decreased testosterone levels in adult male rats (Segarra and Strand 1989) 

Table 8.6 Continued
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and that cotinine, but not nicotine, inhibits testosterone 

synthesis in testes of neonatal rats (Sarasin et al. 2003). 

Four studies that measured estradiol or estrone had 

inconsistent results. However, results from one of the 

studies showing an association with smoking were not 

adjusted for BMI or weight, although adjustment was 

made for age. The findings for the gonadotropins, FSH 

and luteinizing hormone (LH), tend to show no effect of 

smoking. 

In 1990, one study (Barrett-Connor 1990) suggested 

that the ratio of androgen to estrogen is critical in determining the gender-specific risk of some hormone-related 

diseases and that smoking may alter this ratio. Nicotine or 

its metabolites may influence endocrine profiles directly 

and indirectly. PAHs also act on the cytochrome P-450 

systems involved in the metabolism of endogenous 

hormones and of xenobiotics such as those found in 

tobacco smoke.
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Table 8.7 Association between smoking and reproductive hormones in healthy men
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Table 8.7 Continued
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Tubal Function

The mammalian oviduct transports gametes to the 

fertilization site and provides a suitable environment for 

fertilization and development before implantation. Factors 

that impair oviductal physiology can lead to reproductive 

problems, such as fertilization failure, ectopic pregnancy, 

and failure of implantation. Numerous epidemiologic 

studies have correlated maternal smoking with reproductive problems that can originate in the oviduct, including 

increased infertility and ectopic pregnancy (Stillman et al. 

1986; Buck et al. 1997) (see “Review of Epidemiologic Literature on Smoking” earlier in this chapter). 

The mammalian oviduct has three anatomic 

regions: (1) the infundibulum, which picks up the oocyte 

cumulus complex after it is ovulated from the ovary; (2) 

the ampulla, where fertilization occurs; and (3) the isthmus, which conducts sperm to the ampulla and provides a 

site for preimplantation development. Proper functioning 

of each region is necessary for normal reproduction.

The oviduct is an in vivo target of cigarette smoke 

and its components. Contraction of both the human oviduct (Neri and Eckerling 1969) and the rabbit oviduct 

(Ruckebusch 1975) is altered by exposure to tobacco 

smoke. Inhalation of mainstream or sidestream smoke 

at doses that produce serum cotinine levels within the 

range of those found in active smokers and persons 

involuntarily exposed to tobacco smoke caused blebbing 

of the oviductal epithelium and decreased the ratio of ciliated to secretory cells in hamsters (Magers et al. 1995). In 

another study of hamsters, in which the oviduct was 

directly observed before, during, and after inhalation 

of tobacco smoke at doses equivalent to those received 

by humans, both mainstream and sidestream smoke 

decreased ampullary smooth muscle contractions and 

slowed embryo transport through the oviduct (DiCarlantonio and Talbot 1999). Nicotine altered the motility of 

oviducts of rhesus monkeys (Neri and Marcus 1972), 

decreased oviductal blood flow (Mitchell and Hammer 

1985), decreased sodium and potassium levels in oviductal 

epithelial cells of mice (Jin et al. 1998), and increased lactate dehydrogenase levels in oviductal epithelium of rats 

(Rice and Yoshinaga 1980). 

In vitro studies using oviductal explants have been 

valuable in characterizing the effects of cigarette smoke 

on various biologic processes, including ciliary beat frequency, oocyte pickup rate, and smooth muscle contraction (Huang et al. 1997; Riveles et al. 2003). Solutions of 

particulate matter, whole mainstream smoke, and 

mainstream and sidestream smoke in the gas phase inhibited ciliary beat frequency, oocyte pickup rate, and 

smooth muscle contraction in a dose-dependent manner in hamsters (Knoll and Talbot 1998). Although this 

inhibition was originally reported for unfiltered (2R1) 

research cigarettes, a similar inhibition was subsequently 

shown for filter-tipped (1R4F) research cigarettes, unfiltered and filter-tipped commercial cigarettes, and “harmreduction” cigarettes that are lower in carcinogens than 

are traditional brands (Riveles 2004). The data on harmreduction cigarettes are important in demonstrating that 

these cigarettes still contain toxicants that can adversely 

affect diverse biologic processes. Exposure to sidestream 

whole smoke, in contrast to mainstream smoke, stimulated ciliary beat frequency (Knoll and Talbot 1998). The 

oocyte pickup rate was inhibited even in samples in which 

beat frequency was stimulated, which shows that pickup 

depends on factors other than ciliary beating. Adhesion 

between the extracellular matrix of the oocyte cumulus 

complex and the tips of the cilia is an additional factor 

essential for pickup (Talbot et al. 1999; Lam et al. 2000). 

If adhesion is too strong or too weak, oocyte pickup can 

fail (Lam et al. 2000). Exposure to both mainstream and 

sidestream smoke increases adhesion (Gieseke and Talbot 2003), which could account for decreased pickup 

rates even when cilia beat at normal or accelerated rates. 

Exposure to tobacco smoke adversely affects other adhesive processes involving cells, asbestos, and bacteria (Cantral et al. 1995; Churg et al. 1998; El Ahmer et al. 1999).

Therefore, in vitro studies demonstrate that 

exposure to tobacco smoke adversely affects oviductal 

structure and functioning and that nicotine can impair 

oviductal physiology. Together with in vitro data, in vivo 

studies demonstrate that maternal smoking adversely 

affects the oviduct in ways that could impair fertility and 

complicate pregnancy. 

Placenta

Normal Development

Formation of the placenta in the uterus (placentation) is a complex process that is not fully understood. 

Fetal stem cells (cytotrophoblasts) form a polarized epithelium attached to a basement membrane that surrounds a 

stromal core containing the placental vasculature and 

forming chorionic villi. These villi are surrounded by 

a multinucleate syncytial covering. Floating villi are 

attached only to the fetal side of the placenta. In contrast, anchoring villi are formed when cytotrophoblastic 

cells detach from the basement membrane, penetrate the 

uterine wall, and invade maternal arteries and veins. 

Cytotrophoblasts travel deeply into uterine arterioles, 

replace the maternal endothelial lining, and disrupt the 

smooth muscle wall. This physiological transformation 

converts the maternal vasculature from a high-resistance, 
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low-capacitance system to a low-resistance, high-capacitance system that allows for increased blood flow to the 

fetus. Blood from the spiral arteries then enters the intervillous space where an exchange of substances between the 

mother and the fetus occurs (Khong 2004). As the placenta 

develops, the villous system also undergoes remodeling. 

The terminal villi elongate, and there is a large increase in 

the peripheral villi capillary volume (Mayhew 2002; Torry 

et al. 2004). In addition, the thickness of the collective layers of the villi that separate maternal and fetal circulatory 

systems (villous membrane) decreases, enhancing the 

exchange of nutrients and metabolic products between 

the mother and fetus (Mayhew 1998). Interference with 

the development and remodeling of the placental vasculature likely contributes to adverse pregnancy outcomes. 

Effects of Smoking 

Studies have examined the effects of maternal smoking on the placenta, but the results are often conflicting. 

Real or apparent inconsistencies among studies may 

reflect differences in laboratory techniques and terminology. However, many studies appear to fall into one of three 

general areas of research: (1) cytotrophoblastic invasion 

of the uterus and subsequent transformation of uterine 

blood vessels; (2) development of the fetal capillary and 

villous system, particularly with respect to whether the 

placenta can compensate for maternal hypoxia by increasing the supply of oxygen (O2) and nutrients to the fetus; 

and (3) transportation of nutrients across the placenta 

(see “Amino Acids” later in this chapter).

As previously stated, cytotrophoblastic cells in normal pregnancy invade the uterine arterioles and transform them into a high-capacitance system that allows for 

an increase in blood flow to the fetus. Incomplete transformation of the spiral arteries results in a high vascular 

resistance in the placenta and a decrease in blood flow to 

the intervillous space. Studies have described a diminished physiological transformation in placentas from 

women with preeclampsia (Brosens et al. 1972; Naicker 

et al. 2003), SAB (Khong et al. 1987), IUGR (Khong et al. 

1986), PPROM (Kim et al. 2002), preterm labor (Kim et al. 

2003), preterm birth (Kim et al. 2003), or placental abruption (Dommisse and Tiltman 1992).

Physiological transformation appears to be disturbed in women who smoke cigarettes during pregnancy. 

In vitro studies have shown that formation of cytotrophoblastic cell columns, which is necessary for the invasion 

of the uterine wall, is disrupted, perhaps from the effects 

of exposure to nicotine (Genbacev et al. 1995). Among 

women who smoke, there also appears to be a reduction in the number of cytotrophoblastic stem cells in the 

floating villi and a reduction in the number of anchoring 

villi that successfully invade the uterine wall, which may 

reflect a premature depletion of cytotrophoblastic stem 

cells (Genbacev et al. 1995). The interference by smoking in cytotrophoblastic invasion of the uterine wall could 

lead to increased risk of adverse pregnancy outcomes.

Paradoxically, maternal smoking is protective 

against preeclampsia, which is also characterized by an 

incomplete transformation of the spiral arteries. As previously noted, an imbalance between proangiogenic and 

antiangiogenic placental factors may contribute to manifestations of preeclampsia, and smoking may exert its 

protective effects by affecting this imbalance (Genbacev et 

al. 2003; Maynard et al. 2003) (see “Pregnancy Complications” earlier in this chapter). In a normal pregnancy, 

the placenta releases proangiogenic factors, VEGF, and the 

placental growth factor (PlGF). Placental soluble FMS-like 

sFlt-1, which is elevated in preeclampsia, is an antagonist 

of both VEGF and PlGF. An elevated sFlt-1 level is associated with lower levels of VEGF and PlGF and leads to 

endothelial dysfunction. Maternal smoking appears to 

increase the placental expression of VEGF-A (Zhou et al. 

2002), a major regulator of cytotrophoblastic differentiation along the invasive pathway that is decreased in the 

preeclamptic placenta. In contrast, studies have found 

decreased levels of sFlt-1 in the plasma of smokers (Belgore 

et al. 2000), but not in pregnant smokers (Kämäräinen et 

al. 2009). The 2004 Surgeon General’s report on the health 

consequences of smoking noted that “the decreased risk of 

preeclampsia among smokers compared with nonsmokers does not outweigh the adverse outcomes that can 

result from prenatal smoking” (USDHHS 2004, p. 576). 

Additional research is needed to confirm or refute the 

notion that the effects on VEGF-A and/or sFlt-1 explain 

the reduced risk of preeclampsia in smokers. 

Findings on the effects of maternal smoking on the 

development of the villous capillary system are inconsistent. The fetus of a smoker develops under conditions 

of reduced partial pressure of O2, because hemoglobin 

has an affinity for CO from cigarette smoke that greatly 

exceeds its affinity for O2. Thus, the expectation is to see 

compensatory responses in the placenta similar to those 

observed with other hypoxic conditions. Such compensatory responses to hypoxia could include increased volume 

density, branching, and dilation of the fetal capillary system; increased density and proliferation of the cytotrophoblasts; thinning of the villous membrane (Kingdom 

and Kaufmann 1997; Mayhew 1998; Bush et al. 2000); 

and increased maternal and fetal hematocrits. Studies 

have documented increases in both the maternal and fetal 

hematocrits among smokers (Bodnar et al. 2004), which 

should lead to increased delivery of O2 to the fetus. 

In addition, several studies have found that the 

placentas of smokers are heavier or larger than those in 
Surgeon General’s Report

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nonsmokers (Naeye 1978; van der Veen and Fox 1982; 

Howe et al. 1995; Williams et al. 1997), which suggests an 

expansion of the peripheral villous tree. However, other 

researchers have found no increase or only a small 

increase in placental size and/or weight in smokers (Spira 

et al. 1975; Picone et al. 1982; Demir et al. 1994; Sanyal et 

al. 1994; Williams et al. 1997; Zhang et al. 1999; Larsen et 

al. 2002). In many of these studies, the ratio of placental 

to fetal weight was higher in smokers than in nonsmokers even when the placental weight did not increase. This 

increase in the ratio of placental to fetal weight could 

result from a compensatory response to hypoxia, but this 

explanation has not been established. Studies of morphology have described increase (Pfarrer et al. 1999), decrease 

(Asmussen 1980; Burton et al. 1989; Teasdale and Ghislaine 1989; Bush et al. 2000; Larsen et al. 2002), and no 

appreciable difference (van der Velde et al. 1983; Mayhew 1996) in dimensions of the villous capillary system 

of smokers.

In contrast, studies have consistently shown that 

maternal smoking is associated with a thickening of the 

villous membrane, which would decrease the ability of 

nutrients to diffuse through the placenta (Burton et al. 

1989; Jauniaux and Burton 1992; Demir et al. 1994; Bush 

et al. 2000; Larsen et al. 2002). This increased thickness 

was attributed to the increased thickness of the trophoblastic component (Jauniaux and Burton 1992; Bush et 

al. 2000) and to a thickening of the basement membrane 

(Asmussen 1980; Demir et al. 1994). The thickening of 

the villous membrane is opposite from an expected compensatory thinning in response to a hypoxic environment and could contribute to fetal growth restriction. 

Researchers have hypothesized that direct toxic effects of 

maternal smoking on the placenta are responsible for the 

thickening of the villous membrane, perhaps due to the 

accumulation of cadmium that is associated with a reduction in fetal capillary volume (Burton et al. 1989; Bush et 

al. 2000).

Studies have also explored other effects of maternal 

smoking on the cellular and noncellular composition of 

the villous system. Researchers have described changes 

in placental morphology of smokers, including cytotrophoblastic hyperplasia, focal syncytial necrosis, the loss 

or distortion of syncytial microvilli, decreased vasculosyncytial membranes, decreased syncytial pinocytotic vesicles, the degeneration of cytoplasmic organelles, increased 

syncytial knots and decreased syncytial buds, and 

increased collagen levels in the villous stroma (van 

der Veen and Fox 1982; van der Velde et al. 1983, 1985; 

Demir et al. 1994). Evidence of increases in syncytial 

knots and necrotic areas suggests an increase in syncytial 

damage among smokers (Demir et al. 1994). However, 

these effects are not consistent in all studies (Teasdale and 

Ghislaine 1989; Ashfaq et al. 2003). Researchers have found 

it difficult to clearly connect these findings with adverse 

pregnancy outcomes, because the observed changes are 

not pathognomonic for any particular disorder. However, 

these cellular and molecular abnormalities of the villous 

system could lead to an impaired exchange of metabolic 

products, O2, and nutrients between the mother and fetus.

Maternal and Fetal 

Cardiovascular Systems

Smoking acutely increases the heart rate and blood 

pressure of smokers, particularly after a period of abstinence from smoking (e.g., first cigarette of the day). This 

finding has led to the suggestion that changes in blood 

flow may be a mechanism for the lower birth weight 

observed in infants of smokers. Numerous studies have 

investigated the effect of cigarette smoke on the cardiovascular system of pregnant women or their fetuses. The 

studies can be broadly divided into those that examined 

differences in basal cardiovascular parameters between 

nonsmokers and smokers after an interval of abstinence 

and those that examined the acute cardiovascular effects 

immediately after the pregnant women had each smoked 

one or two cigarettes. A body of work investigating the 

relationships of smoking with maternal blood pressure 

and preeclampsia is not presented here, as preeclampsia 

is described above. 

Seven studies investigated the basal cardiovascular state of mothers who smoked and their fetuses compared with those in a control group of mothers who did 

not smoke and their fetuses (Table 8.8). Four studies used 

a radioisotope to study blood flow through the placenta 

(Table 8.9). In 28 studies, the acute maternal and fetal 

cardiovascular effects of maternal smoking were examined, and some of these studies also reported baseline differences (Table 8.10). The participants in these 39 studies 

had healthy singleton pregnancies unless otherwise noted. 

Most of the percentage differences in the parameters were 

calculated for this Surgeon General’s report from data and 

graphs in the original articles, but the statistically significant data are those of the original investigators. 

Basal Function 

Maternal Heart Rate and Blood Pressure 

During Smoking Abstinence

One prospective study of 203 smokers and 292 nonsmokers at 18, 24, 28, and 34 weeks of gestation found no 

differences in maternal heart rate during abstinence from 

smoking (Table 8.8) (Newnham et al. 1990). Two smaller 
Reproductive and Developmental Effects 569

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Table 8.8 Basal maternal and fetal cardiovascular effects of smoking 

Study Design/population Outcome and comments 

MacGillivray et 

al. 1969

226 women

144 nonsmokers, 82 smokers

Gestational age >20 weeks 

Healthy and high-risk pregnancies 

Lifetime nonsmokers vs. smokers

Unadjusted data

Maternal heart rate: no data collected; Maternal blood pressure: 

diastolic blood pressure at first prenatal clinic visit during 

abstinence 9% lower (p <0.05) in smokers than in nonsmokers; 

systolic blood pressure higher in smokers than in nonsmokers but 

no significant data or actual numbers given

Phelan 1980 478 women

350 nonsmokers, 128 smokers

Gestational age 32–40 weeks

All high-risk pregnancies

Repeated NST between 32 and 40 weeks’ 

gestation

NST: smokers had higher rate of nonreactive NST (21% vs. 13%, 

p <0.005), but nonreactive NST in nonsmokers stayed nonreactive 

on subsequent NST; usually, nonreactive NST in a smoker may or 

may not be nonreactive on subsequent NST

Eldridge et al.

1986

24 women

19 nonsmokers, 5 smokers

Gestational age 20–38 weeks

Fetal heart rate: no difference in second or early third trimester; 

heart rate 9% higher in smokers than in nonsmokers (p <0.01) 

in late pregnancy; Fetal blood flow: aorta—significant increase in 

blood flow (30–50% depending on gestational age) in smokers vs. 

nonsmokers (no p value given)

Newnham et al. 

1990

495 women

292 nonsmokers, 203 smokers

Gestational age 18–34 weeks

Study conducted at 18, 24, 28, and 34 

weeks’ gestation

 

Maternal heart rate: no difference between smokers and 

nonsmokers during abstinence; Maternal blood pressure: no 

difference between smokers and nonsmokers; Fetal heart rate: 

no difference between smokers and nonsmokers; Blood flow: no 

difference in umbilical artery or uteroplacental S/D ratio between 

smokers and nonsmokers

Matkin et al. 

1999

5,369 women

2,478 smokers, 2,891 nonsmokers

Gestational age 20–40 weeks

Maternal blood pressure: in general, lower mean diastolic blood 

pressure and higher mean systolic blood pressure in smokers; no 

significant differences between nonsmokers and any of smokers’ 

groups (p >0.05); no dose-response relationship demonstrable 

between smoking levels and blood pressure 

Lees et al. 2001 5,121 women

4,821 nonsmokers, 800 smokers

Gestational age 23 weeks

Uterine artery: at pulsatile index of >1.45 (>95% for cohort), 

likelihood ratio for severe adverse outcome was 5 for nonsmokers 

and 10 for smokers; odds ratio for severe adverse outcome for 

smokers, after adjustment for pulsatile index, was 2.18 (95% 

confidence interval, 1.27–3.74; p <0.005)

Albuquerque et 

al. 2004

143 women

69 nonsmokers, 74 smokers

28 smokers <10 cigarettes/day

45 smokers >10 cigarettes/day

Median gestational age 34–35 weeks

Abstinence 20 minutes–4 hours before 

study

Blood flow: uterine arteries—no difference in S/D ratio or 

RI values in smokers vs. nonsmokers; umbilical arteries—

median S/D ratio 13% greater and median RI value 5% greater 

in smokers than in nonsmokers (p <0.05); Fetal middle cerebral 

artery: no difference in S/D ratio or RI values between smokers and 

nonsmokers

Note: Sonographic technology (ultrasound/Doppler) was used to determine maternal heart rate and blood pressure and for fetal 

monitoring. Prospective studies were conducted during variable periods of abstinence (no smoking before or during protocol). Most 

percentages were calculated for this Surgeon General’s report from data in the study articles or estimated from graphs in the articles. 

NST = nonstress test; RI = resistance index; S/D = systolic/diastolic.
Surgeon General’s Report

570 Chapter 8

studies also found no differences in the maternal heart 

rate in smokers and nonsmokers at baseline (Table 8.10) 

(Bruner and Forouzan 1991; Kimya et al. 1998). Many 

other studies that investigated maternal blood pressure 

or fetal heart rate did not report data on maternal heart 

rate, possibly indicating that they did not find a difference 

between smokers and nonsmokers. 

The first study that prospectively evaluated maternal blood pressure during abstinence from smoking found 

a significantly lower diastolic blood pressure among 

smokers than among nonsmokers (MacGillivray et al. 

1969). Three later studies have not replicated these results 

(Newnham et al. 1990; Kimya et al. 1998; Matkin et al. 

1999). The largest study, of more than 5,000 participants, 

also found that smokers tended to have a lower mean 

diastolic blood pressure of 1 to 3 millimeters of mercury, 

but this difference was not statistically significant and is 

unlikely to be clinically significant (Table 8.8) (Matkin et 

al. 1999). The study by Newnham and colleagues (1990) 

was larger than that by MacGillivray and colleagues 

(1969) and of a similar design, but no significant differences in maternal diastolic or systolic blood pressure were 

observed. Two investigations found that the systolic blood 

pressure of smokers was higher than that of nonsmokers 

(MacGillivray et al. 1969; Matkin et al. 1999). However, 

MacGillivray and colleagues (1969) did not report significance data, and Matkin and colleagues (1999) found the 

difference to be nonsignificant. 

Sufficient clinical data indicate that there is no clinically significant difference in the mean maternal heart 

rate or blood pressure in healthy pregnant nonsmokers 

and smokers during abstinence from smoking. Further 

study of the blood pressure distribution, especially in 

the tails of the statistical distribution, may be warranted, 

because the percentage of women with blood pressure at 

or near the hypertensive range is most important clinically, and this group is at a higher risk of adverse pregnancy outcomes (Lees et al. 2001).

Fetal Heart Rate

Four studies provide data on fetal heart rate collected 

from smokers during periods of abstinence and compared with data from nonsmokers (Eldridge et al. 1986; 

Table 8.9 Maternal and fetal cardiovascular effects: radioisotope studies of placental intervillous blood flow (IBF) 

conducted before and after smoking

Study Design/population Outcome and comments 

Lehtovirta and 

Forss 1978a

12 nonsmokers

Gestational age 35–40 weeks

Xenon133 IBF: overall mean decrease in IBF of 21% (p <0.05) resolved 

within 15 minutes, but 7 with decreased IBF and 5 with increased IBF

Lehtovirta and 

Forss 1980a

12 healthy women

Unknown smoking status

11 women with hypertension

(9 nonsmokers, 2 smokers) 

Gestational age 34–40 weeks

Maternal heart rate: mean increase of 15% in both groups 

(p >0.001); Maternal blood pressure: increase of 6% (p <0.001) in 

healthy women and 2.5% (p <0.05) in women with hypertension;

Xenon133 IBF: baseline IBF 19% lower in women with hypertension; 

smoking resulted in mean 21% (p <0.05) decrease in IBF in healthy 

women, and a 28% (p <0.05) increase in IBF in women with 

hypertension; no change in myometrial blood flow in either group

Rauramo et al. 

1983a

7 women

1 smoker, 6 nonsmokers

Gestational age 37–38 weeks

Xenon133 IBF: decrease in mean IBF of 20% in 7 measurements 

(p <0.001), with a concomitant 54% fall in mean differential indices 

and 45% fall in interval indices; in 5 measurements, an increase in 

mean IBF, differential indices, and interval indices (24%, p not 

significant; 37%, p <0.001; and 45%, p <0.01, respectively); 

relationship between change in IBF and smoking was not clearly 

stated, but it appears that rise in IBF occurred after fall in IBF; IBF 

returned to baseline within 20 minutes

Philipp et al. 

1984

40 women

20 smokers, 20 nonsmokers

Gestational age 32–38 weeks 

Smokers studied after smoking 

2 cigarettes and compared with 

nonsmokers 

Uteroplacental blood flow measured by indium113 labeled transferrin:

significant difference in distribution of scan types (p <0.005); normal 

flow in 15% of smokers vs. 55% of nonsmokers; intermediate flow in 

65% of smokers vs. 30% of nonsmokers; and abnormal flow in 20% of 

smokers vs. 15% of nonsmokers

aSame group of investigators.
Reproductive and Developmental Effects 571

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Table 8.10 Acute maternal and fetal cardiovascular effects of smoking

Study Design/population Outcome and comments 

Gennser et al. 

1975a

12 smokers

Gestational age 33–39 weeks

Maternal heart rate: median increase of 29% (p <0.01) and 

correlated with nicotine plasma level; Fetal heart rate: no 

consistent change

Nylund et al. 1979 12 smokers

Gestational age 39–45 weeks

Hospitalization, high-risk pregnancies 

Data graphically displayed

Maternal heart rate: mean increase of 27% (p <0.001); Maternal 

blood pressure: mean increase in systolic blood pressure of 12% 

(p <0.05) and in diastolic blood pressure of 14% (p <0.05); Fetal 

heart rate: mean increase of 15% (p <0.001)

Quigley et al. 

1979

8 smokers

20–40 cigarettes/day

Gestational age 34 weeks

Maternal heart rate: mean increase of 35% during smoking and 

25% after smoking (p <0.01); Maternal blood pressure: mean 

increase in systolic blood pressure and diastolic blood pressure 

of 7% and 13%, respectively, during smoking (p <0.01); return 

to baseline by 20 minutes after smoking; Fetal heart rate: mean 

increase of 17% (p <0.01); return to baseline by 30 minutes after 

smoking

Barrett et al. 1981 26 smokers

Gestational age 31–44 weeks

All high-risk pregnancies 

1 hour abstinence before testing

NST: none developed a nonreactive NST after smoking; Fetal heart 

rate: slight transient increase in 7 smokers, no change in 

18 smokers, and decrease in 1 smoker

Kariniemi et al. 

1982a

N = 8: 1 smoker, 7 nonsmokers

Gestational age 37–41 weeks

Maternal heart rate: mean increase of 17% (p <0.001); Maternal 

blood pressure: mean systolic blood pressure increase of 11% 

(p <0.001) and mean diastolic blood pressure increase of 20% 

(p <0.001); fetal heart rate and variability data not given in 

relationship to smoking

Forss et al. 1983a 8 women

3 smokers, 5 nonsmokers

Gestational age 22–26 weeks

Data provided only graphically

Maternal heart rate: increased (p <0.001); Maternal blood pressure: 

increased (p <0.01); Fetal heart rate and variability: heart rate

increased (p <0.01); no change in short-term variability, decreased 

long-term variability

Jouppila et al. 

1983

19 smokers

Gestational age 29–39 weeks

Maternal heart rate: 13% increase (p >0.05); Fetal heart rate: 4% 

increase (p >0.05); Fetal blood flow: aorta—no change in diameter, 

1% decrease in blood flow (p not significant); umbilical vein—no 

change in diameter, 10% increase in blood flow (p not significant) 

Lehtovirta et al. 

1983a

8 women 

1 smoker, 7 nonsmokers

Gestational age 37–40 weeks

Data provided only graphically

Maternal heart rate: increased (p <0.001); Maternal blood pressure: 

increased (p <0.001); Fetal heart rate and variability: no significant 

increase in heart rate but significant decreases in short- and longterm variability

Goodman et al. 

1984

10 smokers

10–20 cigarettes/day

Gestational age 37–40 weeks

Studied on 2 days, smoking on 1 day 

and no smoking on 1 day

Order of smoking randomized

Fetal heart rate: increase of 2% with smoking (p not significant); 

Fetal heart rate variability: decrease of 63% in number of 

accelerations lasting ≥40 minutes (p <0.01)

Kariniemi et al. 

1984a

8 women

Smoking status not given

Gestational age 27–32 weeks

Maternal heart rate: 24% increase (p <0.001); Maternal blood 

pressure: 9% increase in systolic blood pressure (p <0.01), 15% 

increase in diastolic blood pressure (p <0.001); Fetal heart rate and 

variability: 11% increase in heart rate (p <0.001), decrease in both 

DI and II of 24% (p <0.001)
Surgeon General’s Report

572 Chapter 8

Table 8.10 Continued

Study Design/population Outcome and comments 

Pijpers et al. 1984 14 smokers

Gestational age 34–38 weeks

All abstained for 24 hours

7 smoked cigarette and were studied 

before, during, and after smoking, and 

7 abstained

Both studied at similar time points

Maternal heart rate: 11% increase for smokers (p <0.05) compared 

with women who abstained; Maternal blood pressure: 5% and 10% 

increase in systolic and diastolic blood pressure, respectively 

(p <0.05), with no change in women who abstained; Fetal heart 

rate: 4.5% increase (p <0.05) compared with women who abstained; 

Fetal blood flow: aorta—no significant change in velocity or in 

systolic or diastolic diameters

Sindberg Eriksen 

et al. 1984

10 smokers

Gestational age 34–40 weeks

Fetal heart rate: 14% increase (p <0.01), returned to baseline by 

20 minutes after smoking; Fetal heart rate variability: significant 

decrease in short-term variability of fetal heart rate but no 

significant change in long-term variability

Sindberg Eriksen 

and Gennser 1984

17 smokers

Gestational age 33–37 weeks

Maternal heart rate: median increase of 42% (p <0.01); Fetal 

heart rate: median increase of 14% (p <0.01); Fetal blood flow: 

aorta—11.6% increase in median diastolic diameter (p <0.01); 

13.8% increase in median pulsatile index (p <0.01); significant 

changes in aorta waveform with smoking; no signs of fetal hypoxia

Sindberg Eriksen 

and Marsál 1984

30 smokers

Gestational age 31–40 weeks

Maternal heart rate: median increase of 29% (p <0.01); Maternal 

blood pressure: median increase in systolic and diastolic blood 

pressure of 14% and 12.5%, respectively (p <0.01); Fetal heart rate: 

median increase of 13% (p <0.01); Fetal blood flow: aorta—5% 

increase in median diameter, 15% increased peak, 20% increased 

mean blood velocity, and 30% increased flow (p <0.01); umbilical 

vein—9% increase in median diameter, 38.5% increase in flow 

(both p <0.05), and no change in velocity

Sindberg Eriksen 

and Marsál 1987a

10 smokers

Gestational age 33–40 weeks

Fetal heart rate: 15% increase (p <0.05), return to baseline by 

30 minutes after smoking; Fetal blood flow: aorta—5 minutes 

after smoking, pulsatile index decreased by 9%, and least diastolic 

blood velocity increased by 22% (p <0.05 for both), but mean peak 

velocity was unchanged

Sorensen and 

Borlum 1987

21 smokers

6–20 cigarettes/day

Gestational age 24–39 weeks

Abstinence 2–12 hours

Maternal heart rate: 15% median increase (p <0.05); Maternal 

blood pressure: 8.7% median increase in systolic blood pressure 

(p <0.05), and no increase in diastolic blood pressure; Fetal heart 

rate: 4.3% median increase (p <0.05); Blood flow: no change in 

fetal cardiac output

Lindblad et al. 

1988a

24 smokers

Gestational age 33–36 weeks

Maternal heart rate: 16% increase (p <0.01); Maternal blood 

pressure: no significant increase in systolic blood pressure; 

11% increase in diastolic blood pressure (p <0.01); Fetal heart rate: 

14% increase (p <0.001); Fetal blood flow: aorta—11% increase in 

flow (p <0.01); umbilical vein—20% increase in flow (p <0.01)

Morrow et al. 

1988

15 smokers

Gestational age 36–41 weeks

Maternal heart rate: 30% increase (p <0.0001); Maternal blood 

pressure: slight increase in systolic blood pressure (p not 

significant), and 14% increase in diastolic blood pressure 

(p = 0.0002); Fetal heart rate: 7% increase (p = 0.001); Blood flow: 

uterine artery—increase in S/D ratio (p = 0.08, powered [80%] to 

detect 17% change in S/D ratio); umbilical artery—26% increase in 

S/D ratio (p = 0.0001)
Reproductive and Developmental Effects 573

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Table 8.10 Continued

Study Design/population Outcome and comments 

Bruner and 

Forouzan 1991

47 women

24 nonsmokers, 23 smokers

Gestational age 26–34.5 weeks 

Smokers studied before and after 

smoking and compared with control 

nonsmokers

Maternal heart rate and fetal heart rate: no significant difference at 

baseline between nonsmokers and smokers; no significant change 

after smoking; Uterine artery and umbilical artery blood flow: no 

significant difference at baseline between nonsmokers and smokers; 

no difference after smoking in flow velocity waveform or S/D ratio

Graca et al. 1991 51 women

Gestational age 34–38 weeks

Fetal heart rate: increase of >10 beats per minute in most fetuses 

after maternal smoking (estimated to be increase of approximately 

6–8%) and decreased short-term variability

Castro et al. 1993 19 smokers

Mean gestational age 28 weeks 

+1 week

Maternal heart rate: 27% increase (p < 0.001); Maternal blood 

pressure: 8% increase in systolic and 19% increase in diastolic 

blood pressure (p <0.001); Uterine artery blood flow: baseline S/D 

ratio >90% in 13 subjects; significant decrease in S/D ratio (15%) 

and resistance index (12%)

Oncken et al. 

1996

9 smokers

Gestational age 24–36 weeks

Percentages estimated from graphs

No p value or statement of significance 

given

Maternal heart rate: 17% increase; Maternal blood pressure: 4% 

increase in mean arterial pressure; Fetal heart rate: 2% increase; 

Blood flow: umbilical artery—8% decrease in resistance index; 

uterine artery—1% decrease in resistance index

Huisman et al. 

1997

5 smokers

Gestational age 8–16 weeks (studied 

weekly)

All twin pregnancies

Maternal heart rate: 12% increase (p <0.005); Maternal blood 

pressure: no significant change; Fetal heart rate: no significant 

change; Umbilical artery blood flow: 13% increase in pulsatile 

index (p <0.01) 

Oncken et al. 

1997

15 smokers

Gestational age 24–34 weeks

Overnight abstinence, then studied 

every 2 hours during 8 hours of ad lib 

smoking

Maternal heart rate: significant increase 2 hours after baseline 

(p <0.001); Maternal blood pressure: approximately 6% mean 

increase in systolic blood pressure at 2 hours after baseline 

(p <0.001); Fetal heart rate: 0.7% increase (p not significant); Fetal 

heart rate reactivity: nonsignificant change: 1 loss of reactivity at 

4 hours, 2 gained reactivity, and 12 had no change in reactivity; 

Blood flow: fetal MCA—2.4% decrease in resistance index at 

4 hours (p = 0.02); umbilical artery—3% increase in resistance 

index at 2 hours (significance not stated); uterine artery—

nonsignificant fluctuation (decrease and increase) in mean 

resistance index over 8 hours

Kimya et al. 1998 43 women

22 smokers, 21 nonsmokers

Gestational age 20–40 weeks

Smokers studied before and after 

smoking and compared with control 

nonsmokers

Maternal heart rate: no difference at baseline between smokers and 

nonsmokers, 23% increase (p <0.01) after smoking; Maternal blood 

pressure: no difference at baseline, systolic and diastolic blood 

pressure increased by 11% and 23%, respectively, after smoking 

(p <0.05); Blood flow: uterine artery—at baseline, smokers had 

12% lower S/D ratio, 19% lower pulsatile index, and 19% lower 

resistance index compared with those of smokers (p <0.001); after 

smoking—no significant change in S/D ratio, pulsatile index, or 

resistance index; umbilical artery—no difference in pulsatile index 

or resistance index for nonsmokers vs. smokers at baseline and 

after smoking; S/D ratio was 13% lower in nonsmokers, with no 

change in S/D ratio after smoking
Surgeon General’s Report

574 Chapter 8

Table 8.10 Continued

Study Design/population Outcome and comments 

Coppens et al. 

2001

26 women

13 smokers, 13 nonsmokers

>10 cigarettes/day

Mean gestational age 37–38 weeks

Smokers studied before and after 

smoking and compared with control 

nonsmokers

Fetal heart rate: no difference between smokers and nonsmokers at 

baseline or after smoking; Fetal heart rate variability: at baseline, 

percentage of time in high variability was 31% lower in smokers 

than in nonsmokers (p <0.05); similar differences remained after 

smoking; Blood flow: umbilical artery—at baseline, no difference 

in pulsatile index between nonsmokers and smokers; pulsatile 

index increased by 76% after smoking (p <0.05)

Oncken et al. 

2002

15 smokers

Gestational age 29–36 weeks

Smoked 1 cigarette/hour for 

8 hours

Studied at baseline and at 4 hours, just 

before 4th cigarette

Fetal heart rate: baseline vs. 4 hours—no change (p = 0.17); 

Fetal heart rate variability: nonstress test—20% were nonreactive 

at baseline, and 73% were nonreactive at 4 hours (p = 0.013); 

nonreactive tests at baseline were also nonreactive at 4 hours; all 

fetuses demonstrated fetal breathing movements indicating fetal 

well-being

Ates et al. 2004 67 smokers

Gestational age 32–40 weeks

Maternal heart rate: 6% increase (p <0.001); Maternal blood 

pressure: no significant increase (p = 0.2); Fetal heart rate:

no significant increase; Fetal heart rate variability: 7% decrease in 

variability (p = 0.08) and 19% decrease in number of accelerations 

(p = 0.035); Blood flow: umbilical artery and fetal MCA—no 

significant change in resistance index, pulsatile index, S/D ratio, or 

maximum and minimum velocity

Note: Maternal heart rate and blood pressure measurements and fetal monitoring used sonographic technology (ultrasound/

Doppler). Prospective studies were conducted before and after smoking. Unless noted otherwise in description of study design, the 

following applies to all studies: overnight (>8 hours) smoking abstinence before smoking study cigarette. All were healthy singleton 

pregnancies, and percentage changes are for means. Most percentages were calculated for this Surgeon General’s report from numeric 

data in article or estimated from graphs. DI = differential index or indices; II = interval index or indices; MCA = middle cerebral 

artery; S/D = systolic/diastolic. aSame group of investigators.

Newnham et al. 1990; Bruner and Forouzan 1991; Coppens et al. 2001). These studies found no differences 

except for the small study by Eldridge and colleagues 

(1986). This study compared 19 nonsmokers with 5 smokers and found no difference in fetal heart rate during the 

second or early third trimester, but it did find a significant 

9-percent elevation among smokers late in the pregnancy.

Acute Effects of Smoking 

Maternal Heart Rate

Twenty-one studies provide data on the immediate 

effect of smoking one or two cigarettes on maternal heart 

rate (Table 8.10). The general design of these studies is 

similar. Healthy active smokers with singleton births in 

the latter half of pregnancy abstained from smoking overnight and were then studied before and after smoking one 

or two cigarettes. The different designs of the studies are 

noted in Table 8.10. All but two of the studies (Jouppila et 

al. 1983; Bruner and Forouzan 1991) found a statistically 

significant transient increase in maternal heart rate immediately after smoking. The largest study, with 67 pregnant 

smokers, found a significant increase of 6 percent in maternal heart rate (Ates et al. 2004), and one smaller study, 

with 17 pregnant smokers, found a significant 42-percent 

increase in maternal heart rate immediately after smoking 

(Sindberg Eriksen and Gennser 1984). Other increases in 

maternal heart rate ranged from 10 to 30 percent, which 

were similar to the nonsignificant effect in the study conducted by Jouppila and colleagues (1983). 

Sufficient clinical data establish that smoking a 

cigarette after a period of abstinence transiently elevates 

maternal heart rate, although the magnitude of the 

increase varies. This finding holds true even when studies involving nonsmokers are excluded. Only one study 

(Oncken et al. 1997), however, addressed the effect of ad 

lib smoking throughout the day on maternal heart rate. 

Oncken and colleagues (1997) found a maximal increase of 

11 beats per minute in maternal heart rate two hours after 
Reproductive and Developmental Effects 575

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

baseline—an increase of approximately 13 percent—with 

ad lib smoking. The clinical significance of a transiently 

elevated maternal heart rate during pregnancy 

is unknown. 

Maternal Blood Pressure

Of the 16 studies that examined the acute effects 

of smoking on maternal blood pressure (Table 8.10), all 

but 2 (Huisman et al. 1997; Ates et al. 2004) reported a 

transient but significant elevation in the mean or median 

diastolic or systolic blood pressure or in the mean arterial 

pressure. The largest increases, ranging from 10 to 23 percent, were observed for diastolic blood pressure, but most 

studies found an increase of less than 15 percent. The largest study, with 67 participants, found a small but nonsignificant increase in diastolic blood pressure after smoking 

(Ates et al. 2004). In general, the acute effect of smoking 

on maternal systolic blood pressure was less than the 

effect on diastolic blood pressure. Three studies reported 

no significant increase in systolic blood pressure, and the 

largest study found a small but nonsignificant (p = 0.2) 

increase (Table 8.10) (Ates et al. 2004). In the remaining 

10 studies, transient increases ranged from 5 to 14 percent. These data indicate that smoking after abstinence 

transiently increases diastolic blood pressure and, to a 

lesser extent, systolic blood pressure. Because one large 

study (Ates et al. 2004) found a nonsignificant effect of 

smoking on maternal blood pressure, additional large 

studies may be needed. 

The release of catecholamine may mediate the elevations in maternal heart rate and blood pressure reported 

in these studies. In a study of pregnant women, smoking 

was associated with an acute rise in plasma levels of norepinephrine, epinephrine, and dopamine and an associated acute rise in maternal heart rate and blood pressure 

(Quigley et al. 1979).

Fetal Heart Rate

Twenty-five studies (Table 8.10) collected data on 

fetal heart rate before and after mothers smoked one or 

two cigarettes. Ten studies, including the largest study 

(Ates et al. 2004) and two studies with a control group 

of nonsmokers (Bruner and Forouzan 1991; Coppens et 

al. 2001), found no effect of smoking on fetal heart rate. 

Five studies reported that smoking after abstinence was 

associated with a 2- to 8-percent transient increase in 

fetal heart rate, and eight studies reported an increase 

of 11 to 17 percent in fetal heart rate. The studies that 

found mean elevations in the fetal heart rate above 10 

percent were conducted between 1979 and 1988. The 

five studies published after 1996 reported no statistically 

significant difference. 

Variability in Fetal Heart Rate 

Healthy fetal heart rate is variable, and there are 

short- and long-term patterns to this variability. The 

“differential index” is an alternative term for short-term 

variability, and the “interval index” is an alternative term 

for long-term variability. Healthy fetal heart rate also has 

episodes of accelerations. Researchers use the variability 

in fetal heart rate and the presence of episodes of accelerations to measure fetal well-being. This variability and 

acceleration are measured in the noninvasive nonstress 

test (NST). A reactive NST is a sign of fetal well-being, and 

a nonreactive NST is a sign of fetal distress. The NST is 

routinely used in the third trimester of pregnancy and 

during labor to monitor high-risk pregnancies and to 

assess low-risk pregnancies if concerns develop. Healthy 

fetuses have transient periods of decreased variability and 

accelerations, which would appear as a transiently nonreactive NST. 

Data on fetal heart rate reactivity and accelerations 

and the NST are presented in Tables 8.8 and 8.10. A large 

cohort of mothers with high-risk pregnancies among 

smokers and nonsmokers was studied repeatedly over 

the course of the pregnancies (Table 8.8) (Phelan 1980). 

Although smokers had a high rate of nonreactive NSTs, 

many were reactive at a subsequent visit. A nonreactive 

NST in a pregnant smoker should generally be repeated 

to rule out a false nonreactive result. There are no reports 

on the prevalence of nontransient, abnormal NSTs among 

healthy smokers versus healthy nonsmokers. 

Nine studies investigated variability in fetal heart 

rate before and after maternal smoking (Table 8.10). All 

but two studies (Oncken et al. 1997; Coppens et al. 2001) 

found that either maternal smoking transiently decreased 

short- and long-term variability or the NST became nonreactive. Three of the studies with positive findings were 

conducted with a control group of nonsmokers by the 

same team of investigators (Forss et al. 1983; Lehtovirta 

et al. 1983; Kariniemi et al. 1984). One investigator did 

not find a loss of reactivity from smoking one cigarette but 

did find a large increase in nonreactive NSTs with additional smoking (Oncken et al. 2002). The two largest studies (Graca et al. 1991; Ates et al. 2004) found a significant 

decrease in variability of fetal heart rate and an accelerated 

increase after smoking.

These data indicate that maternal smoking transiently decreases variability of fetal heart rate. However, 

the clinical significance of these transient decreases in the 

heart rate of fetuses of smokers is not clear. Generally, the 

nontransient changes in these parameters are the clinically important changes. 
Surgeon General’s Report

576 Chapter 8

Blood Flow in Uterus, Placenta, and Fetus

Table 8.9 presents data on blood flow in the uterus 

and placenta from studies that used a radioisotope, which 

is considered the “gold standard” because it directly 

measures flow. The development of fetal sonographic 

technology has replaced radioisotope studies, because 

radioisotopes measure only maternal blood flow and 

expose the mother and fetus to radiation. Sonography is 

noninvasive and can be used to assess blood flow in both 

the fetus and the mother. Table 8.10 presents data from 

ultrasound and Doppler sonography on vessel diameter 

and blood velocity. These data are then used to calculate 

blood flow, which is difficult to measure, because the 

sonographer must visually mark the diameter of a vessel. Flow is proportional to the fourth power of the vessel 

radius, so even very small changes in the measurement of 

the diameter have a large effect on the calculation. Furthermore, all of the studies are unblinded. Sonographic 

technology advanced greatly between 1978 and 2004, 

which may partly explain the variations in the results from 

more than 25 years of publications, as is discussed here. 

The most commonly used surrogate measures of 

blood flow are the ratio of systolic to diastolic blood flow 

velocity (S/D ratio), pulsatile index, and resistance index 

(RI). The S/D ratio is defined as the ratio of the timeaveraged maximal systolic and diastolic blood flow 

velocities. The pulsatile index is defined as the difference 

between peak velocity and the lowest diastolic velocity, 

divided by the mean velocity during the heart cycle. The 

RI is defined as the difference between the maximal systolic and diastolic flow velocities, divided by the systolic 

flow velocity.

Independent of studies of smoking, researchers have 

used the S/D ratio, pulsatile index, and RI measures to 

monitor high-risk pregnancies and to predict outcomes 

(Maulik et al. 1990; Alatas et al. 1996; Fong et al. 1999; 

Özeren et al. 1999; Coleman et al. 2000; Gudmundsson et 

al. 2003; Axt-Fliedner et al. 2005; Li et al. 2005). In lowrisk pregnancies, these measures of blood flow are not sensitive to or specific predictors of adverse outcomes such 

as preeclampsia or IUGR (Kurmanavichius et al. 1990; 

Irion et al. 1998; Albaiges et al. 2000; Harrington et al. 

2004; Schwarze et al. 2005), except when the measures are 

markedly abnormal (Becker et al. 2002; Papageorghiou et 

al. 2005).

Four radioisotope studies of placental intervillous 

blood flow (IBF) have been performed (Table 8.9). Historically, these four studies have provided the initial data for 

the hypothesis that decreased maternal blood flow through 

the placenta caused fetal growth retardation. Three studies by the same group of investigators used xenon133 to 

determine the acute effect of smoking on IBF among 

nonsmokers (Lehtovirta and Forss 1978, 1980; Rauramo 

et al. 1983). The results of the three studies are contradictory. Smoking resulted in either an acute increase or a 

decrease in IBF, depending on the patient and the study. 

The fourth radioisotope study used indium113-labeled 

transferrin to compare smokers immediately after smoking with nonsmokers (Philipp et al. 1984). This study 

found a significant difference in the distribution of normal and abnormal blood flow between the two groups, 

and a smaller proportion of scans were normal among 

the smokers.

Of four studies conducted during abstinence from 

smoking, two found no difference in blood flow parameters of uterine arteries between nonsmokers and smokers (Table 8.8) (Newnham et al. 1990; Albuquerque et 

al. 2004); the latter did find a difference in blood flow in 

umbilical arteries, but the larger Newnham study did not. 

The very small study by Eldridge and colleagues (1986) 

found an increase in aortic blood flow. The most important study found an association between the risk of a 

severe adverse pregnancy outcome and a pulsatile index 

for the uterine artery that doubled among smokers (Lees 

et al. 2001).

Sixteen studies used Doppler sonography to

examine blood flow parameters in maternal smokers 

and their fetuses before and after smoking or in smokers 

after smoking compared with nonsmokers and their 

fetuses (Table 8.10). Four studies by the same group of 

investigators found that smoking dramatically increased 

four parameters (blood flow, velocity, diameter, and pulsatile index) (Sindberg Eriksen et al. 1984; Sindberg Eriksen 

and Marsal 1984, 1987; Lindblad et al. 1988). One study 

found an acute 76-percent increase in the pulsatile index 

of the umbilical artery after maternal smoking (Coppens 

et al. 2001). Six studies found no effect on blood flow, 

velocity, diameter, S/D ratio, pulsatile index, and RI in the 

uteroplacental or fetal blood vessels (Jouppila et al. 1983; 

Pijpers et al. 1984; Sorensen and Borlum 1987; Bruner 

and Forouzan 1991; Kimya et al. 1998; Ates et al. 2004). 

However, Oncken and colleagues (1997) found a negligible change, and four studies found either increases or 

decreases in the S/D ratio and the pulsatile index (Table 

8.10) (Morrow et al. 1988; Castro et al. 1993; Oncken et al. 

1996; Huisman et al. 1997).

In summary, differences between blood flow in 

smokers during abstinence and that in nonsmokers do 

not appear to be significant. However, the study by Lees 

and colleagues (2001) raises concerns because it indicates 

that with an elevated pulsatile index in the uterine artery, 

maternal cigarette smoking doubles the risk of a severe, 

adverse pregnancy outcome. The data on the acute effects 

of smoking on maternal and fetal blood flow are more 
Reproductive and Developmental Effects 577

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

contradictory, and no generalizations can be made at 

this time.

Fetal Tissue and Organogenesis 

Timing and Critical Periods

The embryonic period includes the first eight 

weeks after fertilization and constitutes a significant 

period in human development. During this time, all 

major internal and external structures start to develop, 

involving many complex interactions that must occur in 

an orderly sequence. The embryonic period is a time of 

rapid differentiation, and the developing organs are particularly susceptible to the effects of exogenous agents. The 

stage of embryonic development determines the embryo’s 

susceptibility to unfavorable environmental factors. The 

embryo is most easily disturbed during the organogenesis 

period, from day 15 to day 60 after conception. In addition, 

each system or organ of an embryo has a critical period 

when its development may be altered. The effects of some 

environmental toxins on the developing embryo and fetus 

can be direct and lethal or subtle with delayed but serious 

consequences. Thus, multiple factors are involved in identifying and evaluating the effects of exposure to tobacco 

smoke on the developing baby. 

Evidence on Effects of Smoking

Some epidemiologic studies report an association 

between maternal smoking and various congenital malformations. In this area of research, the associations with 

smoking most frequently examined and published relate 

to nonsyndromic orofacial clefting, congenital heart disease, malformations of the lower extremities such as clubfoot or limb deficiency defects, hypospadias, gastroschisis, 

and craniosynostosis (see “Birth Defects” earlier in this 

chapter). Data supporting a causal association between 

nonsyndromic orofacial clefting and maternal smoking 

have strengthened, but few studies have addressed possible pathogenetic mechanisms. 

Traditionally, investigators have used animal models 

and postmortem tissues to detect the effects on organogenesis of exposure to tobacco smoke by conducting gross 

morphologic, soft tissue, and skeletal examinations. Early 

studies of this type involving exposure to mainstream cigarette smoke provide little data supporting an effect on 

organogenesis. Of seven studies, four did not find any 

effects (Wagner et al. 1972; Reznik and Marquard 1980; 

Peterson et al. 1981; Bassi et al. 1984), and three mentioned limited findings but lacked sufficient details for a 

full evaluation (Schoeneck 1941; Tachi and Aoyama 1983; 

Amankwah et al. 1985). 

A subsequent set of experiments exposed pregnant 

Wistar rats to sidestream cigarette smoke, and the pups 

were then examined for gross morphologic changes (Table 

8.11). Researchers observed a dose-dependent reduction 

in birth weight (p <0.001) but no increase in macroscopically visible gross anomalies (Nelson et al. 1999a). Ossification was delayed throughout the skeleton in all exposed 

groups regardless of the dose. The second part of the 

experiment studied the histopathologic changes in tissues 

such as the lung, liver, stomach, kidney, and intestines 

(Nelson et al. 1999b). The lung tissues of pups of dams 

exposed to smoke showed increased apoptosis, mesenchymal changes, and hyperplasia of bronchial muscles. 

Researchers found abnormal hematopoiesis, proliferation of bile ducts in the liver, and delayed maturation 

of the glomeruli, gastric epithelia, and intestinal villi. 

Another study exposed Sprague-Dawley rats to mainstream tobacco smoke by nose-only inhalation (Carmines et al. 2003). Males were exposed four weeks before 

and during mating, and females were exposed two weeks 

before and during mating and through gestational day 

20. Exposure to tobacco smoke was confirmed by biomarker evaluation. Researchers evaluated external and 

internal abnormal macroscopic findings, histopathology 

of the placenta and fetal tissue, and skeletal radiograms. 

They concluded that exposure to tobacco smoke was not 

associated with any congenital malformations in the offspring. However, numerous abnormalities were described, 

including hypoplasia of the internal genital structures in 

the exposed adult male rats and decreased ossification in 

the fetuses of the exposed dams. 

Epidemiologic studies show that offspring of 

maternal smokers have abnormal lung function and 

associated higher incidences of lower respiratory disorders. The identification of nicotinic acetylcholine receptors in fetal lung suggests a mechanism that may underlie 

the observed postnatal pulmonary abnormalities. This 

hypothesis was tested in monkeys to determine whether 

maternal exposure to nicotine would produce changes in 

lung function or morphology in newborn monkeys similar 

to the changes observed in human infants (Sekhon et al. 

2001). Pregnant rhesus monkeys were infused with either 

nicotine comparable to heavy smoking in humans (1.5 

milligrams per kilogram per day [mg/kg/day], n = 7) or 

saline (n = 7) timed to days 26 through 160 of gestation. 

The fetuses were delivered by cesarean section and on the 

next day had pulmonary function testing. They were then 

sacrificed, and their lungs were weighed and fixed. There 

was a significant decrease in fetal lung weight (16 percent) 

and fixed lung volume (14 percent) after in utero exposure 

to nicotine. All lung function tests (e.g., peak tidal expiratory volume, mean mid-expiratory volume, and forced 

expiratory volume at peak expiratory flows) were also 
Surgeon General’s Report

578 Chapter 8

Table 8.11 Animal and in vitro studies on association between maternal smoking and congenital abnormalities with 

relevant genetic and/or molecular hypotheses

Study Design

Developmental 

defect studied

Proposed mechanism or 

hypothesis Findings

Nelson et 

al. 1999a

Pregnant Wistar rats were 

exposed to sidestream 

cigarette smoke (13 mg of 

tar, 0.9 mg of nicotine)

Pups examined

Histopathologic changes 

in tissues such as lung, 

liver, stomach, kidney, and 

intestines

Define microscopic 

morphology after 

exposure to cigarette 

smoke

• Lung tissues showed 

increased apoptosis, 

mesenchymal changes, 

and hyperplasia of 

bronchial muscles

• Abnormal 

hematopoiesis and 

proliferation of bile 

ducts in liver

• Delayed maturation 

of glomeruli, gastric 

epithelia, and intestinal 

villi

Nelson et 

al. 1999b

Pregnant Wistar rats were 

exposed to sidestream 

cigarette smoke (13 mg of 

tar, 0.9 mg of nicotine)

Pups examined

Gross morphologic 

changes in tissues

Define macroscopic 

morphology after 

exposure to cigarette 

smoke

• Dose-dependent 

reduction of birth 

weight was observed 

(p <0.001)

• No macroscopically 

visible gross anomaly 

was observed

• Delay in ossification 

in entire skeleton was 

observed in all exposed, 

regardless of dose

Subramaniam et al. 

1999

12-week-old female 

Sprague-Dawley rats 

exposed to sidestream 

cigarette smoke and 

unexposed control group

2 weeks after exposure, 

females inseminated by 

unexposed males

Exposure continued during 

mating and pregnancy

Pups from the exposed 

group continued to be 

exposed to cigarette smoke 

until examination

Lung surfactant proteins 

SP-A and SP-B in 

bronchoalveolar lavage 

fluids, preparations from 

postnatal days 1, 3, 7, 14, 

21, and 35 from shamand smoke-exposed pups

Determine whether 

perinatal exposure to 

sidestream cigarette 

smoke decreases 

amount of surfactant in 

developing rat pups

• Smoke-exposed pups 

showed reduced level 

of SP-A on day 1 and a 

higher level of SP-A and 

phospholipids on day 21

• Perinatal exposure to 

sidestream smoke can 

have deleterious effects 

on the developing lung
Reproductive and Developmental Effects 579

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Table 8.11 Continued

Study Design

Developmental 

defect studied

Proposed mechanism or 

hypothesis Findings

Panter et 

al. 2000

27 Spanish-type female 

goats and 28 Western 

ewes were given Nicotiana 

glauca during pregnancy

Concentration of anabasine 

in the dried plants was 

0.175–0.23% vs. 2.4% in 

extracts

Treatment groups divided 

into 6 subgroups and fed 

dried plant by gavage or 

anabasine-rich extract by 

capsule on days 32 and 41 

of gestation

Low initial dose (5–8 mg/

kg) titrated until clinical 

signs of toxicity (maximum 

18 mg/kg)

Intrauterine growth, 

presence or absence of 

CP, facial asymmetry, and 

skeletal contractures in 

newborn goats and sheep

Compare incidence 

of plant-induced CP 

formation between sheep 

and goat treatment 

groups

Determine differences 

in sensitivity of study 

animals exposed to same 

toxicants in similar doses 

and manner

Determine other 

variables that might 

explain cause of CP 

formation

• Fetuses from both 

study groups showed 

decreased fetal 

movement, as 

determined by 

ultrasound

• 21 of 45 (47%) 

newborn goats exposed 

during the early part 

of pregnancy (32–41 

gestational days) had 

CP; only 1 of 45 

(2.2%) had skeletal 

contractures

• 1 of 35 (2.9%) lambs 

had CP, and 6 of 35 

(17%) had contractures

• Goat model is more 

efficient and reliable for 

studying CP deformities

• Tobacco plant and 

its extract is a wellestablished cause 

of congenital cleft 

formation

• Exact mechanism 

is undetermined, 

but neuromuscular 

blockade may play a 

role

Sekhon et 

al. 2001

Pregnant rhesus monkeys 

received subcutaneous 

infusion of nicotine 

(1.5 mg/kg per day 

(n = 7) or saline (n = 7) on 

gestational days 26–160

After delivery by cesarean 

section, fetuses had 

pulmonary function testing 

on next day

Pulmonary function 

before and after exposure 

to nicotine

Lung weight and 

morphology

Interaction of nicotine 

with nicotinic 

acetylcholine receptor 

in developing lung 

responsible for 

altered pulmonary 

morphogenesis and 

mechanics observed in 

human infants whose 

mothers smoked during 

pregnancy

• Lung weight and fixed 

lung volume were 

significantly decreased 

in exposed monkeys 

(16% and 14%, 

respectively)

• Fixed lung volume 

and lung volume 

normalized to body 

weight decreased (14%, 

p = 0.001; 11%, 

p = 0.006, respectively)

• All lung function 

test results were 

significantly lower 

in newborns exposed 

to nicotine during 

gestation
Surgeon General’s Report

580 Chapter 8

Table 8.11 Continued

Study Design

Developmental 

defect studied

Proposed mechanism or 

hypothesis Findings

Carmines 

et al. 2003

Potential developmental 

effects of smoke from 

1R4F reference cigarette 

examined

Sprague-Dawley rats 

exposed for 2 hours/day, 

7 days/week, by noseonly inhalation at target 

mainstream smoke levels 

of 150, 300, and 600 mg/m3

of total particulate matter 

Males exposed 4 weeks 

before and during mating 

and females for 2 weeks 

before and during mating 

and through gestational 

day 20

Sham controls: filtered 

air to simulate nose-only 

exposure, and cage controls 

maintained untreated

Smoke exposure confirmed 

through biomarker 

evaluation

Histopathologic 

evaluation of placenta and 

fetal tissue 

External and internal 

malformations

Macroscopic and 

microscopic findings and 

changes determined by 

skeletal radiograms

Parental exposure to 

tobacco smoke may 

cause congenital 

malformations

• Exposure duration was 

limited

• Number of study and 

control subjects was 

inadequate

• Morphologic and 

dysmorphic evaluations 

were not thorough

• Adult male rats showed 

hypoplasia of the 

internal male genital 

structures

• Fetuses from dams 

exposed to tobacco 

smoke showed 

decreased ossification

• Possibility of an 

association

Lavezzi et 

al. 2004

54 sudden and unexplained 

fetal and infant deaths 

(13 stillbirths, 7 neonatal 

deaths, and 34 from sudden 

infant death syndrome)

Postmortem examination

33 (61%) nonsmokers

21 (39%) smokers

Sections of brainstem 

and medulla oblongata 

examined with 

morphometric methods

Brainstem histopathology 

and morphometric 

analysis of arcuate nucleus

Decrease in size of 

the arcuate nucleus of 

brainstem was expected 

in group exposed to 

smoke

• Mothers of 18 of 34 

infants with hypoplasia 

in >20% of arcuate 

nucleus were smokers 

(p <0.05)

• Homeobox-containing 

gene

• EN2 is a candidate gene 

thought to regulate 

development of arcuate 

nucleus

• Cigarette smoke may 

directly affect this gene, 

resulting in brainstem 

abnormalities
Reproductive and Developmental Effects 581

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Table 8.11 Continued

Study Design

Developmental 

defect studied

Proposed mechanism or 

hypothesis Findings

de la Chica 

et al. 2005

Prospective study

25 control mothers and 

25 mothers who smoked 

(≥10 cigarettes/day for ≥10 

years)

Amniocytes obtained by 

routine amniocentesis for 

prenatal diagnosis

Questionnaire about 

smoking patterns used

Chromosomal instability 

in routine chromosome 

spreads

Breakpoints implicated 

in chromosomal 

abnormalities identified by 

G-banding

Determine whether 

maternal smoking 

has a genotoxic effect 

on amniotic cells, 

expressed as increased 

chromosomal instability

Analyze whether any 

chromosomal regions 

are especially affected by 

tobacco

• Smoking as defined 

and during pregnancy 

is associated with 

increased chromosomal 

instability in 

amniocytes

• Band 11q23, known 

to be involved in 

leukemogenesis, seems 

especially sensitive to 

genotoxic compounds 

contained in tobacco

Ejaz et al. 

2005

Chicken embryo model

In vivo examination of 

neonatal development

Effects examined of 

different preparations of 

nicotine and solutions of 

whole mainstream smoke 

on embryonic movements 

during neonatal 

development

Activity level before and 

after exposure to nicotine 

was measured

Kinematic analysis Evaluate effects of 

nicotine and solutions 

of whole mainstream 

smoke on embryonic 

movements

• Low doses of nicotine 

induced hyperactivity, 

and higher doses 

induced hypoactivity

• Significant (p <0.01) 

decrease in movements 

with application of 10 

mg of nicotine and 

different preparations 

of solution of whole 

mainstream smoke
Surgeon General’s Report

582 Chapter 8

Table 8.11 Continued

Study Design

Developmental 

defect studied

Proposed mechanism or 

hypothesis Findings

Lavezzi et 

al. 2005

Postmortem examination 

of 42 stillborn babies

In 30 of 42, no cause 

of death was identified 

(sudden intrauterine 

unexplained death)

In 12 of 42, causes of death 

were known (intrauterine 

explained death)

15 sudden intrauterine 

unexplained deaths and 

1 intrauterine explained 

death of infants born to 

maternal smokers

16 maternal smokers

25 nonsmokers

Brainstems studied by 

immunohistochemistry 

to assay expression of 

EN2 gene, somatostatin, 

and tyrosine hydroxylase 

enzyme

Brainstem histopathology/

morphology

Morphologic changes of 

brainstem expected in 

the smoke-exposed group

• Brainstem sections 

from 13 stillbirths with 

no definite cause of 

death but with known 

exposure to tobacco 

smoke showed varying 

degrees of hypoplasia 

of arcuate nucleus 

and abnormal staining 

pattern with antibodies 

applied

• Exposure in utero to 

maternal smoking 

may strongly 

interfere with brain 

biologic parameters, 

including decrease in 

noradrenergic activity 

in brainstem

Note: CP = cleft palate; mg = milligrams; mg/kg = milligrams per kilogram; mg/m3 = milligrams per cubic meter.

significantly lower in the newborns exposed to nicotine, 

demonstrating that prenatal exposure to nicotine compromises lung growth and pulmonary function. Although 

there was no histopathologic description of the examined 

lungs, researchers have described changes in lung morphology in humans (DiFranza et al. 2004), as well as in 

rats (Nelson et al. 1999b). Another experiment exposed 

female Sprague-Dawley rats aged 12 weeks to tobacco 

smoke and then mated them to unexposed males. Postnatal measurements of the pups’ lung surfactant levels of 

protein (SP-A and SP-B) in bronchoalveolar lavage fluids 

showed a reduced level of SP-A on day 1 and a higher level 

of SP-A and phospholipid on day 21 among pups exposed 

to smoke (Subramaniam et al. 1999). 

One study examined the induction of cleft palate 

by Nicotiana glauca (wild-tree tobacco) or anabasinerich extracts during the first trimester of pregnancy and 

compared Spanish-type goats with crossbred Westerntype sheep (Panter et al. 2000). Bilateral cleft palate was 

induced in 100 percent of the embryonic and fetal goats 

by gavage of the pregnant mothers with anabasine-rich 

extracts. Eleven percent of the newborn goats showed 

extracranial abnormalities, mainly contractures of the 

metacarpal joints, in addition to bilateral cleft palate. Most 

of these contractures resolved spontaneously within four 

to six weeks after delivery. In contrast, only two lambs 

from ewes exposed to both substances had cleft palate. 

However, all lambs exposed to both substances had contractures, which indicated differential susceptibility of 

the species. The researchers postulated that an alkaloidinduced reduction in fetal movement during the period of 

normal palate closure caused the cleft palate and the multiple flexion contractures. This postulation is supported by 

a later study that used the chick embryo model to conduct 

an in vivo examination of the effects of different preparations of solutions of nicotine and of mainstream whole 

smoke on embryonic movements during neonatal development (Ejaz et al. 2005). In this experiment, low doses 
Reproductive and Developmental Effects 583

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

of nicotine induced hyperactivity and high doses induced 

hypoactivity. Accordingly, there was a significant (p <0.01) 

decrease in movements after applying 10 mg of nicotine 

and different preparations of whole mainstream smoke 

solutions. The decrease in embryonic movements was 

dose dependent and did not resolve by the end of the 

experiment. The researchers concluded that nicotine 

could alter embryonic movements that are important during embryogenesis for the differentiation and maturation 

of the body systems. 

In a clinical study, researchers collected amniocytes from routine amniocenteses of 25 control women 

and 25 women who smoked (≥10 cigarettes per day for 

≥10 years). Amniocytes of the smokers showed increased 

chromosomal instability; breakpoints involving band 

11q23, which is commonly implicated in hematopoietic 

malignancies, was the chromosomal region most affected 

(de la Chica et al. 2005). Another study examined autopsy 

specimens from 42 stillborn infants (Lavezzi et al. 2005). 

Researchers studied the brainstem tissue by immunohistochemistry to evaluate the expression of the EN2 gene, 

somatostatin, and the tyrosine hydroxylase enzyme. 

Brainstem sections from stillborn infants whose mothers 

had smoked during pregnancy showed hypoplasia of the 

arcuate nucleus and an abnormal staining pattern with 

the antibodies applied. Thus, in utero exposure to maternal smoking may strongly interfere with brain biologic 

parameters of brain development, including a decrease 

in the noradrenergic activity in the brainstem, resulting 

in pulmonary hypodevelopment and even an apparently 

unexplained sudden death of the fetus (Lavezzi et al. 2005).

Researchers have identified an increasing number 

of polymorphisms of genes encoding drug- and/or toxinmetabolizing enzymes, transporters, and receptors. Some 

of these genetic factors have a major impact on drug sensitivity, adverse reactions, or variations of responses to 

environmental toxins. As a result, many investigators have 

studied polymorphisms of certain candidate genes to elucidate the pathogenesis of the effects of maternal smoking 

on the developing embryo and fetus (see “Smoking and 

Maternal and Neonatal Genetic Polymorphisms” later in 

this chapter). 

Investigators have proposed other mechanisms for 

the adverse effects of smoking on organogenesis, particularly orofacial clefting. CO contributes to fetal hypoxia, 

which investigators have associated with an increased risk 

for cleft lip and cleft palate in susceptible strains of mice 

(Millicovsky and Johnston 1981; Bronsky et al. 1986; Bailey et al. 1995). Impaired uteroplacental circulation may 

result in a reduced supply of essential nutrients for embryonic tissues (van Rooij et al. 2001). Studies have associated 

poor intake of vitamin B6 and multivitamins with a risk of 

oral clefts (Botto et al. 2004; Munger et al. 2004). Other 

possible mechanisms include (1) reductions in serum 

folate levels mediated by maternal smoking (McDonald et 

al. 2002; Mannino et al. 2003; Ortega et al. 2004), (2) exposure to cadmium that is present in increased amounts in 

the placentas of smokers (Ronco et al. 2005) and is associated with teratogenic effects in certain rats (Ferm 1971; 

Chernoff 1973), and (3) DNA damage by PAHs (Lammer 

et al. 2004; Perera et al. 2004). Further work is needed to 

elucidate the extent to which these or other mechanisms 

involving the complex mixture of chemicals in cigarette 

smoke account for the increased risk of oral clefts. 

Immune System

Cigarette smoking is associated with an increased 

risk for many types of infectious diseases including pneumococcal pneumonia, Legionnaires’ disease, meningococcal disease, influenza, the common cold, and infection 

with Helicobacter pylori (Arcavi and Benowitz 2004). In 

addition, studies have associated smoking with seropositivity for human immunodeficiency virus (HIV) and an 

increase in the transmission of HIV from infected mothers 

to their offspring (Boulos et al. 1990; Royce and Winkelstein 1990; Burns et al. 1991, 1994). 

The mechanisms through which smoking increases 

the risk of infection are not well defined and are likely 

complex, involving both innate and adaptive immune 

responses. Compared with nonsmokers, smokers appear 

to have a leukocytosis (Corre et al. 1971; Friedman et al. 

1973; Yeung and Buncio 1984; Hughes et al. 1985; Calori 

et al. 1996; Jensen et al. 1998a) and elevations in levels of 

all major blood cell types (Corre et al. 1971). This leukocytosis could be a result of nicotine-induced increases in the 

release of catecholamine (Friedman et al. 1973). However, 

the consequences of an increased white blood cell count 

are unclear. It appears that there are increases in both 

CD4+ (an HIV-helper white blood cell) and CD8+ (an HIVsuppressor white blood cell) T-cell populations in smokers, although heavy smokers may have reduced CD4+ cell 

counts, and effects may vary by race (Sopori 2002; Arcavi 

and Benowitz 2004). A decline in CD4+ cell counts could 

contribute to a decrease in B-cell proliferation and immunoglobulin (Ig) synthesis, which would increase the risk of 

infection (Arcavi and Benowitz 2004). However, in a study 

of pregnant smokers compared with pregnant nonsmokers, a decline in CD4+ count was not described (Luppi et 

al. 2007). 

In general, smoking appears to have immunosuppressive effects. For example, lymphocytes in smokers 

appear to have a decreased response to T-cell mitogens 

(Sopori 2002), and polymorphonuclear leukocytes show 

decreases in chemotaxis and migration (Noble and Penny 
Surgeon General’s Report

584 Chapter 8

1975; Corberand et al. 1979), which do not appear to be 

attributable to exposure to nicotine (Sasagawa et al. 1985). 

Study findings suggest that smokers have reduced titers of 

antibodies to the influenza virus and low serum levels of 

all Ig classes except IgE (Gerrard et al. 1980; Sopori 2002). 

In addition, smoking may increase levels of autoantibodies, perhaps contributing to some autoimmune disorders 

(Mathews et al. 1973; Másdóttir et al. 2000; Sopori 2002). 

Smoking may also affect the balance of function between 

helper T-cell subsets 1 and 2 (Th1 and Th2), because 

researchers have observed increases in Th2- and/or Th1-

related cytokines in smokers (Tsunoda et al. 2003; Cozen 

et al. 2004). In vitro experiments suggest that nicotine 

impairs the immunostimulatory activity of dendritic cells 

(antigen-presenting cells) and adversely affects the differentiation of monocytes into dendritic cells (Nouri-Shirazi 

and Guinet 2003; Guinet et al. 2004). Finally, studies have 

also associated smoking with low counts and reduced 

cytotoxic activity of natural killer cells, which are important components of innate immunity (Tollerud et al. 1989; 

Zeidel et al. 2002). Potential mechanisms through which 

exposure to tobacco or nicotine might result in an altered 

immune function include the induction of glucocorticoid 

hypersecretion and the increased release of catecholamines, which both inhibit the immune response or the 

activation of the autonomic nervous system (Sopori and 

Kozak 1998; Borovikova et al. 2000; Sopori 2002). Activation of the parasympathetic arm of the autonomic nervous 

system attenuates the systemic inflammatory response.

Studies suggest that smoking also induces systemic 

chronic inflammatory effects, which is possibly a consequence of increased oxidative stress (Cross et al. 1999; 

Hecht 1999; van der Vaart et al. 2005). As described earlier 

in this section, smokers have a leukocytosis compared with 

white blood cell counts in nonsmokers, and studies have 

associated smoking with elevated levels of C-reactive protein (Tracy et al. 1997; Wong et al. 2001; Bermudez et al. 

2002). However, findings in studies of cytokine profiles in 

blood are not consistent (van der Vaart et al. 2005). Some 

studies suggest that smoking suppresses the production of 

proinflammatory cytokines such as IL-1, IL-6, and TNFα, 

which are important components of the immune response 

to intracellular pathogens such as viruses and fungi 

(Sopori and Kozak 1998; Ouyang et al. 2000). However, 

other studies have shown an enhanced production of IL-6 

and TNFα, as well as other cytokines including IL-1β

(Zeidel et al. 2002; van der Vaart et al. 2005).

Smoking could contribute to an increased risk of 

adverse pregnancy outcomes by its effects on the immune 

system through an increased risk of maternal infection, 

an alteration of the inflammatory response, or both. For 

example, studies have consistently associated smoking 

with a twofold-to-threefold increase in risk for bacterial 

vaginosis (Morris et al. 2001), which is a risk factor for 

preterm delivery. Researchers have hypothesized that 

smoking increases this risk through its effects on vaginal flora or through the depletion of Langerhans cells, 

resulting in local immunosuppression (Smart et al. 

2004). Smoking can also reduce zinc levels, which could 

increase susceptibility to vaginal infections (Edman et al. 

1986; Sikorski et al. 1990; Shubert et al. 1992). Cigarette 

smoking has been associated with increased cervical antiinflammatory cytokines in early pregnancy, which could 

make women who smoke more vulnerable to reproductive 

tract infections and subsequent preterm delivery (Simhan 

et al. 2005, 2009). Finally, the immunosuppressive effects 

of smoking could contribute to protective effects against 

preeclampsia, because preeclampsia appears to involve 

an exaggerated or inappropriate immune response. More 

research is needed to fully define these potential relationships and pathways. 

Tobacco Smoke Toxicants and 

the Reproductive System

Carbon Monoxide

Toxicity

CO is formed as a by-product of combustion and 

is thus present in tobacco smoke. It is a potent and even 

lethal toxin whose primary target organ is the brain. The 

fetus is more susceptible to the toxic effects of CO than 

is the mother. Symptomatic exposures to CO that the 

mother will fully recover from may end in permanent 

neurologic damage to the fetus or even fetal death (e.g., 

stillbirth) (Norman and Halton 1990; Koren et al. 1991). 

The fetal effects of CO are well studied (Koren et al. 1991; 

Penney 1996). 

CO is the toxin found in the highest concentration 

in cigarette smoke. The dose per cigarette is 10 to 20 times 

the dose of nicotine (Hoffman et al. 1997). Furthermore, 

CO is not found in unsmoked tobacco products. The toxic 

effects of CO result predominantly from its binding to 

hemoglobin (Longo 1976, 1977). Each molecule of hemoglobin can carry four molecules of O2 (Hsia 1998). The 

binding and unbinding of O2 to hemoglobin depends on 

the local level of O2. High levels of O2 facilitate binding to 

hemoglobin, and low levels (hypoxia) facilitate the release 

of O2 from hemoglobin. The O2 binds to hemoglobin as 

blood passes through the O2-rich lungs and is delivered 

to tissues as blood traverses the capillary beds. When one 

molecule of O2 is released from hemoglobin, a conformational change in hemoglobin facilitates the release of further O2 molecules. 
Reproductive and Developmental Effects 585

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Hypoxia, Fetal Growth, and 

Other Abnormalities

CO binds to hemoglobin with an affinity more than 

200 times that of O2 (Sauter 1994). Once CO binds to one 

of the four binding sites of hemoglobin, the hemoglobin 

is altered so greater tissue hypoxia is required before O2

will be released from the other binding sites (Hsia 1998). 

In addition, CO prevents the conformational change in 

hemoglobin that occurs with O2 unbinding. The release 

of one O2 molecule does not facilitate the release of subsequent O2 molecules when hemoglobin also binds CO.

The binding of CO to hemoglobin is tenacious, with 

a half-life of five to six hours. Fetal hemoglobin binds CO 

more tightly than does adult hemoglobin, and the fetus 

has higher levels of carboxyhemoglobin than those of the 

mother; the average ratio of fetal to maternal carboxyhemoglobin is 1.8 (Cole et al. 1972; Longo 1977; Bureau et 

al. 1982). It takes approximately seven hours for CO to 

equilibrate between the mother and the fetus (Bureau 

et al. 1982). The net effect of the CO and hemoglobin 

interaction is chronic hypoxia in fetal tissue (Longo 1977) 

or, more accurately, chronic cellular hypoxia that persists during periods of maternal abstinence from smoking, such as during sleep. Simply put, CO from cigarette 

smoke deprives the fetus of O2, which is essential for the 

aerobic metabolism that produces adenosine triphosphate 

(ATP). ATP stores chemical energy that is ubiquitously 

used to drive all manner of chemical reactions in the body. 

This chronic yet mild O2 deprivation in the fetus is likely a 

major underlying mechanism of smoking-associated fetal 

growth retardation (Longo 1976, 1977). 

Data from both clinical and animal studies indicate that CO is probably the foremost toxin responsible 

for the LBW associated with maternal smoking (Garvey 

and Longo 1978; Lynch and Bruce 1989; Penney 1996; 

England et al. 2003). A well-designed study found a 

decrease in birth weight that was almost five times greater 

for infants of smokers than for infants of snuff users, 

even after adjustment for variables (England et al. 2003). 

The mean adjusted decrease in birth weight was 39 g for 

infants of snuff users and 190 g for infants of smokers 

compared with infants of nonsmokers. Because CO is the 

main toxin in cigarette smoke but not in snuff, this difference in birth weight implicates CO as the likely hazard. 

Even mild, long-term exposure to CO in animals resulted 

in fetal growth retardation; maternal carboxyhemoglobin 

levels were 4 to 9 percent (Garvey and Longo 1978; Penney 1996). The carboxyhemoglobin levels associated with 

smoking are 5 to 10 percent.

Studies have found central nervous system abnormalities in fetuses and pups of pregnant rats with longterm exposure to CO (Storm and Fechter 1985a,b; Storm 

et al. 1986; Fechter 1987; Carratù et al. 1993a,b; Packianathan et al. 1993). Behavioral studies of prenatally exposed 

animals have revealed persistent postnatal effects associated with CO exposure that produced maternal carboxyhemoglobin levels of 6 to 16 percent. These levels were 

not associated with small litter size or altered duration of 

gestation but with LBW (Fechter and Annau 1976, 1980, 

1997; Abbatiello and Mohrmann 1979; Mactutus and Fechter 1984, 1985; Singh 1986; Fechter 1987). CO-induced 

hypoxia appears related to other congenital anomalies 

including cleft lip and cleft palate in susceptible strains of 

mice (Millicovsky and Johnston 1981; Bronsky et al. 1986; 

Bailey et al. 1995). Subsequent epidemiologic studies of 

birth defects in relation to CO levels from air pollution 

early in gestation found associations between higher CO 

levels and various cardiac defects, but the findings were 

not consistent (Ritz et al. 2002; Gilboa et al. 2005).

Blood Hyperviscosity

Carboxyhemoglobin results in functional anemia in 

both the mother and fetus that stimulates production of 

red blood cells and elevates maternal and fetal hematocrits (Meberg et al. 1979; Bureau et al. 1983; Bili et al. 

1996). As the hematocrit increases, the viscosity of the 

blood increases. At birth, the healthy newborn hematocrit 

is normally 44 to 64 percent, which is well above adult values. Because of the increased viscosity, healthy newborns 

are at risk for stroke if the hematocrit is above 65 percent. 

The hematocrit can be lowered with partial-exchange 

transfusions. Compared with newborns of nonsmokers, 

newborns of smokers have higher hematocrits that therefore increase the risk of stroke and a need for exchange 

transfusion (D’Souza et al. 1978; Buchan 1983). Elevated 

maternal hematocrits and a consequently higher blood 

viscosity in the mother may also be risk factors for suboptimal placental perfusion (Bureau et al. 1983; Knottnerus 

et al 1990).

Preeclampsia

Data indicate that CO functions as a gaseous localized messenger (Ryter et al. 2004). CO appears to activate 

guanylate cyclase and modulate the mitogen-activated 

protein kinase signaling pathway (Ryter et al. 2004). 

Heme oxygenases (HO-1, HO-2, and HO-3) degrade 

heme into ferrous ion, CO, and biliverdin, which all have 

important physiological functions at low concentrations 

but are toxic in high concentrations (Ryter et al. 2004). 

CO appears to have localized functions similar to those 

of nitric oxide (NO), a gas that affects vascular tone and 

platelet aggregation (Ryter et al. 2004). CO also appears 

to have cytoprotective effects against oxidative stress by 
Surgeon General’s Report

586 Chapter 8

reducing inflammation and suppressing apoptosis (Ryter 

et al. 2004; Tsuchihashi et al. 2004). 

Researchers think it is likely that the CO from cigarette smoke is responsible for the reduced risk of preeclampsia associated with smoking. The basis for this 

rationale is that users of snuff, which does not contain 

CO, have an increased risk of preeclampsia (England et 

al. 2003). The pathophysiology of preeclampsia remains 

to be elucidated, but the transformation of the spiral 

arterioles, which supply blood to the placenta, into lowresistance high-flow vessels appears to be incomplete (see 

“Preeclampsia” and “Placenta” earlier in this chapter). 

Spiral arteries may still be responsive to vasoconstrictive 

stimuli. Episodic constriction resulting in reduced blood 

flow to the placenta can cause hypoxia-reperfusion injury, 

which elicits endothelial damage and an inflammatory 

response. A hypoxic uterine environment appears to be a 

normal stimulus for the transformation of spiral arterioles 

during pregnancy (Lyall 2003). CO via carboxyhemoglobin can augment this tissue hypoxia and may stimulate 

the normal transformation of spiral arterioles. Additionally, CO functions similarly to NO as a vasorelaxant and 

may counteract the effects of circulating vasoconstrictive 

agents on preeclamptic spiral arterioles. Both hypoxic 

environment and vasorelaxation may help to prevent 

hypoxia-reperfusion injury and the consequential inflammation and endothelial damage, thereby reducing the risk 

of preeclampsia (Bainbridge et al. 2005). 

Independent of preventing hypoxia-reperfusion 

injury, CO may function similarly to NO in maintaining normal endothelial function and preventing platelet 

aggregation. Also, research in the area of tissue transplantation has found that exogenous CO significantly reduces 

the inflammatory environment in allograft rejections 

(Tsuchihashi et al. 2004). Researchers postulate that CO 

may have a similar role in the heightened inflammatory 

environment of the preeclamptic placenta. Although some 

evidence supports this model of CO and preeclampsia, the 

data are not extensive (Barber et al. 2001; McLaughlin et 

al. 2001). Investigators do not know how important CO is 

as a local messenger during pregnancy or how exogenous 

CO supplements endogenous CO.

Summary

CO is the toxin in cigarette smoke that is found in 

the highest concentrations. The major effect of CO is to 

deprive the fetus of O2 by binding to hemoglobin. The 

binding of CO to hemoglobin also results in functional 

anemia that eventually produces a rise in the hematocrit. 

Elevated hematocrit in the mother may adversely affect 

blood flow in the placenta, leading to placental problems 

and potentially to fetal growth retardation. CO appears 

to prevent preeclampsia by augmenting uterine hypoxia 

and, thus, development of arterioles or other local effects 

similar to those of NO. However, this possibly beneficial 

role for CO is far outweighed by its hypoxic effects involving hemoglobin.

Nicotine

Nicotine, the principal alkaloid in tobacco, is a 

major contributor to the addictive properties of smoking. 

The diverse pharmacologic and toxicologic properties of 

nicotine are discussed in Chapter 4, “Nicotine Addiction: 

Past and Present,” and are only briefly touched on here. 

Nicotine has both short- and long-term effects and is 

likely causally related to several of the endpoints discussed 

in this chapter. The Office of Environmental Health Hazard Assessment of the California Environmental Protection Agency (Cal/EPA) lists nicotine as a developmental 

toxicant. Nicotine is known to cross the placenta and concentrate in the fetus at levels slightly higher than those 

in the mother. Nicotine may decrease placental perfusion, 

leading to hypoxia of the fetus and acidosis.

As noted earlier in this chapter, nicotine may be 

involved in the development of various congenital anomalies or neurobehavioral problems. Experimental studies 

of rhesus monkeys exposed to nicotine in utero showed 

decreases in fetal lung weight, volume, and function (Sekhon et al. 2001) similar to those observed in offspring of 

maternal smokers (see “Fetal Tissue and Organogenesis” 

earlier in this chapter). Thus, nicotine may be the key 

constituent of tobacco smoke to impair fetal lung development and lead to altered lung function and perhaps 

increased respiratory illness. In an experiment with chick 

embryos, low doses of nicotine induced hyperactivity and 

higher doses induced hypoactivity (Ejaz et al. 2005). The 

researchers concluded that nicotine could alter embryonic 

movements that are important during embryogenesis for 

the differentiation and maturation of the embryo’s organ 

systems. McCartney and colleagues (1994) speculated that 

intrauterine exposure to nicotine specifically affects the 

outer hair cells in the ear, which influence language ability, leading to poorer performance scores on assessments 

that rely heavily on verbal abilities.

Nicotine may also interfere with pregnancy by affecting oviduct function, which may lead to ectopic pregnancy 

or problems with fertilization and implantation, or by 

affecting transport of essential nutrients, which could 

affect fetal growth (see earlier sections). For example, 

nicotine altered oviduct motility in rhesus monkeys 

(Neri and Marcus 1972), decreased oviductal blood flow 

in rats (Mitchell and Hammer 1985), and decreased 

sodium and potassium concentrations in oviductal epithelial cells of mice (Jin et al. 1998). In vitro studies report 
Reproductive and Developmental Effects 587

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

that nicotine, CO, and cyanide impair amino acid uptake 

in placental microvilli (Rowell and Sastry 1978; Horst 

and Sastry 1988; Sastry 1991). In addition, nicotine may 

impair amino acid transport (Fisher et al. 1984). Studies 

show reduced levels of several amino acids in fetal plasma, 

umbilical plasma, and placental villi in maternal smokers 

compared with those in nonsmokers (Jauniaux et al. 1999, 

2001), and nicotine inhibits in vitro transport of arginine 

in human placentas (Pastrakuljic et al. 2000) (see “Amino 

Acids” later in this chapter). The reports of associations 

of smokeless tobacco use with several adverse pregnancy 

outcomes, such as LBW, preterm delivery, stillbirth, and 

placental morphologic changes (Agrawal et al. 1983; 

Gupta and Sreevidya 2004; Gupta and Subramoney 2006), 

suggest that a component of tobacco smoke in addition to 

CO, perhaps nicotine, contributes to these toxic effects. 

Nicotine appears to be one of the components of 

tobacco smoke that has endocrine-disrupting effects, 

which, in turn, may affect several other reproductive and 

developmental endpoints. In vitro experiments show that 

treatment of cells with alkaloids found in tobacco smoke 

(namely, nicotine, cotinine, anabasine, or a combination of 

these substances) or with an aqueous extract of cigarette 

smoke resulted in a dose-dependent inhibition of progesterone production (Bódis et al. 1997; Gocze et al. 1999; 

Gocze and Freeman 2000; Miceli et al. 2005), whereas 

estradiol production showed little effect or was slightly 

stimulated. These findings support the effects of smoking 

on progesterone observed in epidemiologic studies. Cell 

growth and DNA content also decreased with treatment, 

leading the authors to suggest that smoking directly 

inhibits cellular progesterone synthesis through less specific cytotoxic effects on progesterone-producing cells 

(Gocze and Freeman 2000). Other scientists concluded 

that nicotine and M-nicotine, the methylated metabolite, 

can induce a type of luteal insufficiency by inhibiting progesterone release, probably through modulations in the 

prostaglandin system (Miceli et al. 2005) or inhibition of 

aromatase enzymes.

In animal models, nicotine acts on the HPG axis to 

increase secretion of adrenocorticotropic hormone from 

the pituitary gland, which then stimulates production of 

adrenocortical hormone (Matta et al. 1998). This finding 

is consistent with hormone profiles observed in clinical 

studies (see “Endocrine System” earlier in this chapter). 

Studies have also reported that nicotine acts directly 

on steroidogenesis by inhibiting various hydroxylases 

involved in their metabolism and on aromatases involved 

in converting androgens to estrogens (Barbieri et al. 

1986a,b, 1987). Animal studies show that prenatal exposure to nicotine is related to decreased testosterone levels 

in adult male rats (Segarra and Strand 1989). They also 

report that cotinine, but not nicotine, inhibits testosterone synthesis in testes of neonatal rats (Sarasin et al. 

2003). A small study of administration of nicotine to men 

and women by a transdermal patch found that the patch 

significantly lengthened the interpulse interval of pulsatile LH secretion in male nonsmokers but not in female 

nonsmokers or in smokers (Funabashi et al. 2005).

Metals

Presence in Tobacco Smoke

The particulate component of tobacco smoke contains metals. Their presence depends on the origin of the 

tobacco, the formulation of the cigarette product, and the 

method of smoking; detection depends on the method 

and sensitivity of the analysis. Analyses have quantified 

cadmium (<1.2 to 90.3 nanograms [ng] per cigarette), 

lead (0 to 41.4 ng/microgram [μg]), and mercury (<0.25 

to 4.3 ng/μg) in mainstream smoke (Houlgate 2003). 

Nickel and chromium were not detectable (limit of detection = 1.8 and 1.7 ng per cigarette, respectively), although 

other studies have identified these metals in tobacco 

smoke (Smith et al. 1997; Torjussen et al. 2003). Arsenic 

was detectable but not quantifiable (limit of quantitation 

= 2.7 ng per cigarette). Studies have also detected additional metals such as zinc (U.S. Environmental Protection Agency [USEPA] 1992) and beryllium (Smith et al. 

1997) in cigarette smoke. In sidestream smoke, there are 

estimated amounts only for cadmium, nickel, and zinc 

(National Research Council 1986). Very few animal toxicology studies of metals, which are reviewed here, used 

inhalation exposure. Clinical data are available on the bioavailability of cadmium and nickel from cigarette smoke, 

but researchers have studied only cadmium in connection with smoking-induced toxic effects on reproduction 

and development. 

Exposure of reproductive organs to metals from cigarette smoke depends on (1) the uptake from the lung to 

the circulation, (2) the presence of transporters at bloodtissue barriers, and (3) the regulation of uptake and egress 

at the cellular level. In the fetus and the testes, there 

are physical barriers to blood flow (the placenta and the 

blood-testes barrier) and highly selective metal transport 

mechanisms (Hidiroglou and Knipfel 1984; Sylvester and 

Griswold 1994; Ballatori 2002; Asano et al. 2004; Gruper 

et al. 2005). 

General Mechanisms

Metals reaching the cells and reproductive organs of 

the fetus can act through several common mechanisms. 

Transition metals, which can assume more than one 
Surgeon General’s Report

588 Chapter 8

valence state, can influence electron-exchange reactions 

and oxidative stress within cells. Metals can also substitute for the appropriate trace element at sites where 

nutritionally essential trace elements are important, such 

as active sites of enzymes, sites for regulatory elements 

of transcription factors, and metal-binding sites in receptor complexes or ion channels. Metals can also displace 

essential trace elements at storage sites, such as the bone 

matrix or heme molecules. Most mechanisms are posited 

for metals in the ionic form. Various compounds that 

incorporate metals may take metals from cigarette smoke 

before reaching the circulatory system and reproductive 

organs. However, the relevance of the various biologic 

actions of metals in smoking-related reproductive disease 

awaits further research. Current assessments must rely 

on parallels between smoking-related and metal-induced 

adverse reproductive effects.

Reproductive Effects of Specific Metals

The toxic effects of the heavy metals lead, mercury, 

and cadmium on reproduction and development are well 

known and widely reviewed in both clinical and animal 

studies (Clarkson et al. 1985; Andrews et al. 1994; Goyer 

and Clarkson 2001). The toxicity of mercury and lead 

is highly dependent on whether the metal is organic or 

inorganic. The most sensitive endpoint for lead and methyl 

mercury is the neurobehavior of children (Mendola et 

al. 2002). In addition, male and female reproductive effects from metal toxicity are well documented, including 

effects on fertility, menstrual cycle function, and adverse 

pregnancy outcomes (Ward et al. 1987; Golub 2005b; 

Hoyer 2005; Sokol 2005). At low levels of exposure that 

are potentially relevant to cigarette smoke, studies have 

not demonstrated effects on fertility in women but have 

associated infertility with paternal occupational exposure 

to lead (Sallmén et al. 2000). Literature reviews have indicated associations between prenatal exposure to lead and 

SAB, preterm delivery, and reduced birth weight (Andrews 

et al. 1994; Antilla and Sallmén 1995; Borja-Aburto et al. 

1999). One study associated exposure to lead with delayed 

puberty (Selevan et al. 2003), but exposure to mercury had 

little effect on the timing of puberty (Denham et al. 2005).

An extensive number of studies on exposure to lead 

in male animals all report abnormalities in spermatogenesis and production of reproductive hormones. Studies of 

men report an inverse relationship between levels of lead 

in blood and levels in sperm, in addition to adverse pregnancy outcomes in their partners (Anttila and Sallmén 

1995; Lin et al. 1998; Sokol 2005). The use of mercury in 

dental amalgams has led to studies of dentists and dental 

assistants, but evidence for reproductive effects in either 

males or females is limited. One study found decreased 

fertility in female dental assistants with greater exposure 

to lead (Rowland et al. 1994). Sperm production is affected 

in animal models with exposure to some mercury doses. 

Finally, experimental studies of exposure to mercury in 

birds and fish demonstrate hormonal effects relevant to 

endocrine disruption (Golub 2005b). 

Researchers have investigated cadmium as the agent 

in cigarette smoke responsible for LBW in newborns of 

smokers. Studies document that cadmium accumulation 

in the blood and placentas of pregnant smokers correlated 

with LBW (Kuhnert et al. 1982, 1987a). Other studies 

associated placental cadmium, but not blood cadmium, 

with LBW of newborns of smokers (Ward et al. 1987; 

Sikorski et al. 1988). Studies have reported inconsistent 

associations between exposure to cadmium and birth 

weight in newborns of women exposed to cigarette smoke 

in the workplace or by environmental contamination 

(Huel et al. 1981, 1984; Bonithon-Kopp et al. 1986; Berlin 

et al. 1992; Loiacono et al. 1992; Fréry et al. 1993; Nishijo 

et al. 2002). LBW was a significant finding in some studies 

that administered cadmium, usually as cadmium chloride, 

to rats and mice by injection, inhalation, or orally in food 

and drinking water (Cal/EPA 1996). Many of these studies 

found delayed ossification, another indicator of developmental delay. At higher doses, fetal viability was affected. 

One proposed mechanism of the effect of cadmium 

on birth weight is interference with the placental transfer of the essential trace elements zinc and copper (Sowa 

et al. 1982; Steibert et al. 1984; Sasser et al. 1985; Sowa 

and Steibert 1985; Kuhnert et al. 1987a; Chmielnicka and 

Sowa 1996). Researchers hypothesize that cadmium also 

interferes with progesterone production in the placenta 

(Jolibois et al. 1999a,b; Piasek et al. 2001; Kawai et al. 2002; 

Henson and Chedrese 2004). Studies have found that cadmium acts as an estrogenic agent. Initially, in vitro studies demonstrated that cadmium binds to a specific site 

on the estrogen receptor and mimics estradiol-induced 

gene transcription (Garcia-Morales et al. 1994; Choe et al. 

2003; Johnson et al. 2003b). Other studies found that the 

effects of in vivo administration of cadmium on the uterus 

and mammary glands could be blocked by antiestrogenic 

agents (Johnson et al. 2003b). Animal studies show that 

cadmium accumulates in ovaries, that there is a loss of 

ovarian follicles, and that steroid production declines 

(Hoyer 2005). Elevated levels of cadmium in the follicular fluid of smokers (Zenzes et al. 1995) were not associated with impaired fertility (Drbohlav et al. 1998; Younglai 

et al. 2002). Studies have also associated smoking with 

elevated cadmium levels in seminal fluid. At least one 

study noted a negative correlation with cadmium levels 
Reproductive and Developmental Effects 589

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

and semen quality, but another found no correlation (Saaranen et al. 1989; Chia et al. 1994). Animal studies have 

shown some negative effects on spermatogenesis. 

Chromium, nickel, and zinc are essential human 

dietary nutrients (Institute of Medicine 2000). They are 

present in tobacco and have been studied for their toxic 

effects on reproduction and development (Keen 1996; 

Golub 2005a). Almost all information on toxicity comes 

from laboratory animal studies, and very little is known 

about exposure through inhalation. Exposure to chromium (as Cr+6) produced embryo and fetal loss, growth 

restrictions, and malformations when administered in 

drinking water to mice at a minimum dose of 60 mg/kg per 

day (Trivedi et al. 1989; Junaid et al. 1995, 1996). Studies 

show that chromium is a testicular and ovarian toxicant 

that also affects fertility when administered in drinking 

water to rodents (Saxena et al. 1990; Zahid et al. 1990; 

Murthy et al. 1991, 1996; Bataineh et al. 1997). Nickel 

is teratogenic in mice and rats when it is injected (Lu et 

al. 1979; Mas et al. 1985). When nickel was administered 

over a long period in drinking water, perinatal mortality 

was a common finding (Smith et al. 1993). Studies have 

also demonstrated the testicular toxicity of nickel that was 

injected intraperitoneally or administered orally to 

rodents, but ovarian toxicity and male fertility were not 

studied (Kakela et al. 1999; Doreswamy et al. 2004). Longterm studies that administered zinc to male and female 

rodents found no effects on fertility (Ogden et al. 2002; 

Johnson et al. 2003a).

Growing evidence suggests adverse effects on 

human pregnancy outcomes (e.g., stillbirth, SAB, and 

LBW) from exposure to arsenic in drinking water (Hopenhayn-Rich et al. 2000; Ahmad et al. 2001; Hopenhayn et 

al. 2003; Yang et al. 2003). Animal studies demonstrate 

toxic effects on ovaries and testicles from arsenic in drinking water (Chattopadhyay et al. 1999, 2001; Pant et al. 

2001), and earlier literature discusses arsenic teratogenesis (Golub et al. 1998). These studies support further 

efforts to assess the bioavailability of arsenic from cigarette smoke.

Most of these metals, such as lead, cadmium, mercury and mercury compounds, nickel carbonyl, and inorganic oxides of arsenic, are listed as “known by the state to 

cause reproductive toxicity” under California’s Proposition 

65 program, affecting a variety of endpoints. (Information 

supporting the listings can be found at the agency’s web 

site [http://www.oehha.ca.gov].) Thus, some or all of these 

compounds may contribute to the adverse effects of smoking on reproduction, but direct links in smokers have not 

been established.

Polycyclic Aromatic Hydrocarbons

Formation and Toxicity

PAHs are ubiquitous products of the partial combustion of carbon-containing materials, and they appear 

as important components of environmental pollution. 

Although some sources are natural, the predominant 

sources of PAHs found in the air are usually anthropogenic. Examples include vehicle exhausts, products from 

industrial processes, and emissions from fossil fuel power 

plants (International Agency for Research on Cancer 

[IARC] 1983), as well as tobacco smoke (IARC 1986, 2004; 

USEPA 1992). The usual definition of a PAH specifies 

hydrocarbons with no heteroatom substitutents or ring 

members that include at least two or, according to some 

authors, three concatenated aromatic (usually benzenelike) rings. The two-ring members of the class, primarily naphthalenes, are included within the definition used 

in EPA’s identification of “polycyclic organic material” as 

a hazardous air pollutant. These two-ring members are 

abundant in tobacco smoke and show some chemical and 

toxicologic differences from other PAHs. This discussion 

primarily addresses the effects of PAHs with three or more 

rings, while also noting some specific effects of naphthalenes. The five-ring compound benzo[a]pyrene (B[a]P) is 

one of the most extensively studied PAHs. In addition to 

carcinogenesis, studies have reported direct fetotoxic and 

teratogenic effects associated with PAHs, as well as adverse 

effects on reproduction. Other notable effects include 

immunotoxicity, endocrine effects, and toxic effects on the 

lungs. Key studies are summarized in Table 8.12, and the 

results are discussed in detail here.

The toxic effects and dose-response relationships 

described for specific PAHs are primarily based on experiments on toxic effects in animals, which are the focus of 

this summary. Several corresponding effects in humans 

result from exposure to pollutant mixtures containing 

PAHs, such as diesel exhaust. Human exposure to PAHs 

generally involves mixtures that are ill defined and poorly 

quantified, so it is difficult to separate the effects of PAHs 

from those of other components of the mixtures. 

Most of the toxic endpoints described for PAHs 

appear to result from the generation of reactive intermediate agents by metabolism, followed by reactions of 

these intermediates (e.g., as B[a]P 7,8,9,10-dihydrodiol) 

with the cellular components, particularly DNA, in both 

adult and fetal tissues (Kleihues et al. 1980; Bolognesi et 

al. 1985; Shugart and Matsunami 1985). Unless repaired, 

the adducts that are produced give rise to mutations that 
Surgeon General’s Report

590 Chapter 8

Table 8.12 Reproductive and developmental effects of polycyclic aromatic hydrocarbons (PAHs), 

by endpoint

Study Design: animal model or population Endpoint

Krarup 1969 Direct application of 9:0-dimethyl-1:2-benzanthrene to mouse ovary Toxic effects to 

reproductive system

in adults

Mattison and 

Thorgeirsson 

1979

PAH treatment (80 mg/kg) of juvenile mice (4–6 weeks old):

C57BL/6N (AHH inducible) and DBA/2N (AHH noninducible)

Toxic effects to 

reproductive system

in adults

Shum et al. 

1979

C57BL/6 (AHH responsive) or AKR (nonresponsive) mice

exposed to B[a]P (50–300 mg/kg intraperitoneally) at day 7, 10, 

or 12 of gestation

Teratogenicity

Mackenzie and 

Angevine 1981

Mice exposed prenatally to B[a]P (10, 40, or 160 mg/kg per day) on days 7–16 

of gestation

Fertility study

Beginning at 7 weeks of age, each F1 male was placed with 10 untreated 

females for 25 days

Beginning at 6 weeks of age, each F1 female was cohabitated continuously 

with an untreated male for 6 months

Fertility index = females pregnant/females exposed to males x 100

Birth weight

Adult reproductive 

function after prenatal 

exposure

Mattison and 

Nightingale 

1982

Mice (AHH responsive or nonresponsive) exposed to B[a]P (100 mg/kg 

intraperitoneally)

Toxic effects to 

reproductive system

in adults

Urso and 

Gengozian 

1982; Urso and 

Johnson 1988; 

Urso et al. 1992

Series of experiments in mice: single exposure to B[a]P during pregnancy 

(150 mg/kg intraperitoneally)

Developmental 

immunotoxicity

Immune response 

measure: degree of 

anti–sheep erythrocyte 

plaque-forming 

response, mixed 

lymphocyte response of 

cultured lymphocytes, 

measures of T-cell 

function
Reproductive and Developmental Effects 591

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Study Findings Comments

Krarup 1969 • Oocyte destruction and ovarian tumorigenesis A typical effect reported early, 

although the route of application is 

artificial

Mattison and 

Thorgeirsson 

1979

• Number of primordial oocytes severely depleted in ovaries 

of mice exposed to carcinogenic PAHs (B[a]P, 3-methylcholanthrene, 7,12-dimethylbenz[a]anthracene, but not 

by a noncarcinogenic PAH or an AHH inducer (pyrene, 

β-naphthoflavone)

• PAHs eventually resulted in complete destruction of oocytes in 

both strains, but effect is faster in AHH inducible strain

Destruction of oocytes is related to 

inducibility of AHH; researchers 

assumed in this case that activation 

of the enzyme led to generation of 

more reactive metabolites, which 

caused greater oocyte destruction: 

this is supported by the inactivity 

of β-naphthoflavone, an AHH 

inducer not metabolized to reactive 

intermediates; however, other AH 

receptor actions may also be involved

Shum et al. 

1979

• In utero toxicity and teratogenicity: stillbirths, resorptions, 

malformations increased in exposed mice

• Effects approximately 2–3 times as severe in C57BL/6 mice, 

which are responsive to AHH induction at all exposure times

• B[a]P (200 mg/kg intraperitoneally)

  

Mackenzie and 

Angevine 1981

• Pup weights significantly reduced compared with those for 

controls at all doses (p <0.01) at 20 and 42 days; decreasing 

trend in pup weight with dose at day 4

• Exposed mice of both sexes as adults showed loss of fertility in 

controlled breeding studies with untreated partners

• Mice given B[a]P at 40 or 160 mg/kg per day essentially infertile 

(p <0.01) with histologic abnormalities of gonads

• Testes of males exposed to B[a]P at 40 mg/kg showed severe 

atrophy and aspermic seminiferous tubules

• Ovaries of exposed females hypoplastic or atrophied with few 

follicles or corpora lutea

• Mean litter size reduced (p <0.01) with treatment of females but 

not with treatment of males

  

Mattison and 

Nightingale 

1982

• 30% oocyte destruction of primordial oocytes Effect was not linked to AHH 

induction in this experiment

Urso and 

Gengozian 

1982; Urso and 

Johnson 1988; 

Urso et al. 1992

• Increases in Lyt2 cells in fetal liver

• Often profound immunosuppression in neonatal offspring and 

later in life; postnatal thymic and splenic suppression 

• Approximately 50% reduction in plaque-forming cells in sheep 

erythrocyte assay in 1-week-old offspring after mid- or lategestational treatment with 150 μg of B[a]P

• Changes in maternal immune system, which may affect 

maintenance of pregnancy: thymic suppression, including 

reduction in several classes of T lymphocytes and inhibition of 

mixed lymphocyte response

  
Surgeon General’s Report

592 Chapter 8

Table 8.12 Continued

Study Design: animal model or population Endpoint

Holladay 

and Smith 

1994

B6C3F1 mice exposed to B[a]P (maternal dose of 50, 100, 

or 150 mg/kg/day) on days 13–17 of gestation

Developmental immunotoxicity

Offspring examined for T-cell and 

fetal liver cell markers on gestational 

day 18

Lummus 

and 

Henningsen 

1995

BALB/c mice exposed to B[a]P in utero: single dose of 

150 mg/kg of B[a]P on days 11–13 of gestation

Developmental immunotoxicity

Nicol et al. 

1995 

Exposure to B[a]P in utero

Normal mice and mice deficient in the P53 tumor suppressor gene

Teratogenicity

Perera et al. 

1998

Epidemiologic exposure to PAHs by ambient air pollution in 

Poland

70 newborns from Krakow (industrialized) and 90 from Limanowa 

(rural but coal used for home heating)

PAH-DNA adducts in leukocytes and plasma cotinine measured in 

umbilical cord blood

Birth weight and developmental delay
Reproductive and Developmental Effects 593

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Study Findings Comments

Holladay and 

Smith 1994

• Severe depletion of T cells in both thymus and liver

• Changes in proportions of surface antigens (CD4, CD8, and 

heat stable) in isolated thymocytes

• Reduction in total cellularity of thymus and liver

Researchers suggested that these 

changes indicated impaired maturation 

in surviving thymocytes consistent with 

long-term immunosuppression seen in 

mice exposed to B[a]P in utero

Lummus and 

Henningsen 

1995

• Numbers of T cells in fetal liver severely reduced compared 

with those for untreated controls; severe atrophy of fetal 

thymus

• Neonates showed decreased overall thymic cells and 

increases in some splenic cells

• 6-week-old juvenile mice showed recovery of total T cells to 

control levels in spleen and thymus but depletion of thymic 

cells bearing fetal liver T-cell antigen

Changes in relative proportions of 

different types of T cells, distinguished 

by various surface antigens, result 

in disturbance of immune system 

development; some apparently B[a]

P-resistant cell types repopulate depleted 

lymphoid organs, but overall function 

of the immune system is changed and 

remains depressed

Nicol et al. 1995 • Malformations and increased rate of fetal death

• Embryotoxicity and teratogenicity 2- to 4-fold higher in 

P53-deficient mice than in controls

The P53 gene, which is important in 

regulation of DNA repair and apoptosis, 

has a significant embryo-protective effect 

in the B[a]P-exposed fetus

Perera et al. 

1998

• In newborns with high (>median) versus low (≤median) 

levels of PAH-DNA adducts:

– Mean birth weight reduced by 147 g (p <0.05)

– Birth length reduced by 1.1 cm (p <0.02)

– Head circumference reduced by 0.9 cm (p <0.001)

• Cotinine also significantly and inversely associated with low 

birth weight and reduced length

  
Surgeon General’s Report

594 Chapter 8

Table 8.12 Continued

Study Design: animal model or population Endpoint

Dejmek et al. 2000 Epidemiologic exposure to PAHs and PM 

by ambient pollution in Czech Republic

3,349 births in Teplice and 1,505 in 

Prachatice between April 1994 and March 

1998

Continuous measurement of PAH, PM10, 

and PM2.5

AOR for IUGR correlated monthly with 

PAH and PM pollution levels

Birth weight and developmental delay

Matikainen et al. 2001 Young mice, oocytes, and human 

ovarian tissue explants exposed to 

7,12-dimethylbenz[a]anthracene

Toxic effects to reproductive system

in adults

Note: AH = aryl hydrocarbon; AHH = aryl hydrocarbon hydroxylase; AOR = adjusted odds ratio; B[a]P = benzo[a]pyrene; 

CI = confidence interval; cm = centimeters; g = grams; IUGR = intrauterine growth retardation, where birth weight is <10th 

percentile by gender and gestational week; mg/kg = milligrams per kilogram; ng = nanograms; ORs = odds ratios; PM = particulate 

material; PM10 = particulate matter in which particles are ≤10 micrometers; PM2.5 = particulate matter in which particles are ≤2.5 

micrometers; μg = micrograms.
Reproductive and Developmental Effects 595

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Study Findings Comments

Dejmek et 

al. 2000

• AORs for IUGR show significant increases with levels of PAH 

at both locations early in pregnancy during first month of 

gestation; AOR for medium exposure = 1.63 (95% CI = 0.87–

3.06) and for high exposure, 2.39) (95% CI = 1.01–5.65)

• In Prachatice, relationship was more noticeable (AOR 2.44 [95% 

CI, 0.6–9.83]) in subset closer to pollutant source

• Pollution in Teplice high in both PM and PAH, but in Prachatice, 

high in PAH and generally lower in PM

• IUGR was observed in 9.6% of pregnancies in Teplice and 8.2% in 

Prachatice

Because the ratio of PM and PAH varied 

between locations and with time, the 

continuous model was able to show that 

the risk of IUGR increased with level of 

PAH exposure, rather than with PM, and 

resulted from an early developmental 

defect

Matikainen 

et al. 2001

• Oocyte destruction and ovarian failure; mechanism involves 

enhancement of apoptosis

Effect is dependent on the BAX promoter 

gene and the AH receptor
Surgeon General’s Report

596 Chapter 8

are then followed by cytotoxicity and/or cancer and possibly teratogenicity (Wells and Winn 1996). Both phase 

I (activation) enzymes and phase II (detoxification and 

conjugation) enzymes are important in the metabolism 

and toxicity of PAHs, and both are inducible by PAHs. The 

structural genes determining the stability and activity 

of the enzymes and the regulatory genes controlling the 

expression of the enzymes, show polymorphisms in both 

humans and animals. One of these enzymes is aryl hydrocarbon hydroxylase (AHH), which is influenced by induction of cytochrome P-450 activity. Animals are described 

as genetically “responsive” when AHH activity is induced 

by exposure to PAHs and to other activators of the AH 

receptor. There are also important changes in the levels 

and types of enzymes expressed at different developmental 

stages, particularly during the latter part of fetal development and the immediate postnatal period (Cresteil et 

al. 1986). Researchers have used the resulting variations 

in metabolic capabilities of the fetus and young animal to 

investigate the mechanisms of and differential susceptibility to PAH toxicity.

Toxic Effects on Reproduction

Investigators have known for some time that 

exposure of the adult female rodent to PAHs damages 

the resting ovarian follicle complexes, leading to oocyte 

destruction (Krarup 1969; Mattison and Thorgeirsson 

1979; Mattison and Nightingale 1982) (Table 8.12). Studies have revealed similar effects in women, primarily as 

premature reproductive senescence (menopause), after 

exposure to mixed pollutants. As noted previously, premature senescence is associated with smoking (Jick et 

al. 1977; USDHHS 1980) (see “Menstrual Function, Menarche, and Menopause” earlier in this chapter).

Mattison and Nightingale (1982) reported a 30-percent destruction of primordial oocytes in adult mice 

exposed to a single dose of B[a]P. After comparing susceptibility to this effect in different strains of mice that were 

responsive or unresponsive to inducers of cytochrome 

P-450 enzymes, these researchers suggested that the 

determining factor for oocyte destruction involves the 

ratio of phase II (detoxifying) to phase I (activating) 

enzyme activities. Later investigations have shown the 

involvement of mechanisms that control apoptosis in 

oocyte destruction (e.g., Matikainen et al. 2001). The 

researchers described three sets of studies using treatment with 7,12-dimethylbenz[a]anthracene in young 

mice, isolated oocytes, or xenografts of human ovary 

tissue. They found that both a functional AH receptor 

and a functional BAX promoter gene were necessary for 

oocyte destruction in mice. Moreover, this apoptosis control system was induced in oocytes by the activation of 

the aryl-hydrocarbon-responsive AH receptor. This finding provides an alternative direct route for triggering the 

cytotoxic response to PAHs, which is in contrast to the 

earlier proposal involving reactive PAH metabolites.

Toxic Effects on Development

Teratogenicity. Many fetotoxins, including PAHs, 

produce a spectrum of effects: anatomic and functional 

teratogenesis; prenatal, perinatal, and postnatal mortality; 

growth retardation; and developmental delay. To observe 

the combination of these outcomes in a particular experiment may depend on dose level and timing, the test species used, and other experimental conditions. The most 

commonly observed effects of PAHs in animal studies are 

growth retardation and fetal mortality, but a few experiments have demonstrated anatomic teratogenic effects. 

The number of surviving offspring is reduced in these 

experiments, so it appears that the dose range over 

which surviving, but malformed, offspring are produced 

is narrow. 

Intraperitoneal B[a]P given to mice at day 7 or 10 

of gestation causes toxic effects in utero (e.g., a reduction in the number of surviving offspring) and teratogenicity (Table 8.12) (Shum et al. 1979). The severity of the 

effect was correlated with the ability of the fetus and the 

maternal systems to metabolize B[a]P. A greater impact 

on prenatal and postnatal mortality was noted in C57BL/6 

mice, which are responsive to induction of AHH, than 

in unresponsive AKR inbred mice. This finding suggests 

a role for reactive intermediate agents of PAHs. Malformations observed only in the responsive mice included 

clubfoot, hemangioendothelioma, cleft palate, and other 

anomalies of the skeleton and soft tissues. 

Nicol and colleagues (1995) also observed malformations and an increased rate of fetal death after in utero 

exposure to B[a]P. The embryotoxicity and teratogenicity 

were twofold-to-fourfold higher in mice deficient in the 

P53 tumor-suppressor gene than in the controls with the 

normal P53 gene. The P53 gene, which is important in the 

regulation of DNA repair and apoptosis, thus has a significant embryoprotective effect in the fetus exposed to B[a]P, 

which is also characteristic in relation to other DNAdamaging teratogens such as phenytoin (Nicol et al. 1995; 

Wells and Winn 1996).

Prenatal impacts on adult reproductive function. Animal studies have demonstrated similar but more 

drastic reproductive effects in both males and females 

exposed to PAHs in utero rather than as adults. As adults, 

offspring exposed to B[a]P in utero showed a loss of fertility in controlled breeding studies with untreated partners 

(Table 8.12). High doses of B[a]P resulted in complete 

infertility and histologic abnormalities of the gonads 
Reproductive and Developmental Effects 597

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

(Mackenzie and Angevine 1981). Although most observations of reduced fertility in adults focused on females, 

this experiment also showed a clear reduction in fertility 

among the treated F1 males. Examination of the testes 

showed severely atrophied and essentially aspermic seminiferous tubules. The ovaries of females were hypoplastic 

and had very few follicles or corpora lutea. Most of the animals exposed to the high doses had no identifiable ovaries 

or only remnants of ovarian tissue. 

Kristensen and colleagues (1995) also reported 

reductions in fertility among female NMRI mice after 

exposure in utero to 10 mg of B[a]P/kg per day given 

orally. Watanabe (2005) reported decreases in the number 

of spermatozoa and Sertoli cells in the testes of adult rats 

exposed in utero to diesel exhaust.

Investigations of the mechanism of oocyte depletion 

have emphasized the importance of the AH receptor and 

BAX activation in the induction of apoptotic destruction 

of oocytes and in the natural process that reduces the initial fetal complement of primordial oocytes early in their 

development to the lower levels that characterize the adult 

female. These findings do not necessarily exclude a separate role for cytotoxic effects from DNA damage by reactive PAH metabolites in the destruction of germ cells. The 

mechanisms involved in the induction of impaired sperm 

quality and male infertility after adult or fetal exposure to 

PAHs are less extensively studied. Therefore, it is unclear 

whether other factors and/or mechanisms apply.

Effects on birth weight and developmental 

delay. Clinical studies of exposure to PAH-containing 

mixtures of pollutants in utero have reported reductions 

in birth weight, apparently attributable to both premature 

birth and IUGR, as well as variations in other size measures, such as length and head circumference at birth. 

More recent studies have used correlations with PAHderived DNA adducts and the differential impact of pollution sources with high versus low PAH levels to more 

clearly establish the role of PAHs on LBW.

Perera and colleagues (1998) studied developmental effects of fetal exposure to PAHs through ambient pollution from burning coal in Poland (Table 8.12). Plasma 

cotinine and PAH-DNA adducts in leukocytes were measured in umbilical cord blood as dosimeters of cigarette 

smoke and transplacental PAH, respectively. Newborns 

whose levels of PAH-DNA adducts were above the median 

(3.85 per 108 nucleotides) had a significantly decreased 

birth weight, length, and head circumference. Cotinine 

was also significantly and inversely associated with birth 

weight and length. Similarly, Dejmek and colleagues 

(2000) studied birth outcomes in relation to air pollution in two towns in the Czech Republic, one industrialized (Teplice) and one rural (Prachatice) (Table 8.12). The 

authors defined IUGR as a birth weight below the 10th 

percentile by gender and gestational week. In Teplice, 

IUGR was observed in 9.6 percent of pregnancies, while at 

Prachatice, 8.2 percent were affected. There was a significant association of IUGR with exposure to air pollution, 

particularly to PAHs rather than to particulate matter 

(Table 8.12). The association between PAH exposure and 

IUGR was only significant during the first month of gestation. The AOR was 1.63 (95 percent CI, 0.87–3.06) for a 

medium exposure and 2.39 (95 percent CI, 1.01–5.65) for 

a high exposure. Researchers interpreted these findings as 

indications that the induction of IUGR by a PAH exposure 

resulted from an early developmental effect. 

Despite the exposures to mixed pollutants, these 

studies provide specific correlations of impacts on birth 

weight and development with PAH exposure either 

through a determination of specific DNA adducts or on 

the basis of differential exposures to PAHs and other pollutants. Extensive evidence from other studies shows an 

impact of air pollution on birth weight and other pregnancy outcomes (Šrám et al. 2005), supporting the plausibility of a causal relationship between LBW and exposure 

to PAHs, in spite of the difficulties in assigning causality to 

specific compounds within mixtures. 

Animal studies also show developmental delay and 

LBW after in utero exposure to pure PAHs, thus strengthening the epidemiologic data. MacKenzie and Angevine 

(1981) reported statistically significant reductions in 

weights of exposed pups compared with those of controls 

for all in utero doses of B[a]P, as well as evidence of a 

progressive dose response. Similarly, Bui and colleagues 

(1986) observed reductions in fetal weight in a mechanistic study that compared the effects of B[a]P with those 

of methadone, another known fetotoxicant. These authors also observed reductions in uterine weight among 

the pregnant dams, which suggest that B[a]P treatment 

affects both the fetus and the maternal system. 

Developmental Immunotoxicity

PAH exposures have a variety of effects on the 

immune system. Extensive literature describes the 

effects of exposure to pollutant mixtures containing PAHs 

in adult humans. Researchers have demonstrated interest 

in performing studies on the initiation and exacerbation 

of asthma and other allergic respiratory conditions from 

exposure to diesel exhaust, often in combination with 

other allergens (Riedl and Diaz-Sanchez 2005). Findings 

suggest that these exposures can potentiate allergic reactions to antigens such as pollen. Exposure early in life may 

result in a shift in T-cell activity patterns toward a more 

atopic profile. Studies have also linked these effects to 
Surgeon General’s Report

598 Chapter 8

exposures to other pollutant mixtures that contain PAHs, 

including tobacco smoke (NCI 1999). Literature reviews 

also describe mechanistic studies of similar processes in 

animals. As noted earlier, the presence of PAHs in these 

pollutant mixtures raises the likelihood that these substances are among the causative agents. However, it is not 

generally possible to separate the PAH effects from those 

of other components in the mixture. Synergistic interactions among these components may also be a significant factor. 

In contrast to the stimulatory or adjuvant effects at 

comparatively low exposure levels, higher doses of PAHs 

in humans have immunosuppressive effects (Karakaya 

et al. 2004). Similar findings and investigations of the 

mechanisms involved have been extensively described in 

adult animals (Table 8.12). The primary effects noted after 

fetal and neonatal exposures involved immunosuppression, which is often profound and persistent (Urso and Gengozian 1982; Urso and Johnson 1988; Urso et al. 1992), and 

includes both selective and overall reductions in various 

cellular components of the immune system, particularly 

T cells (Holladay and Smith 1994; Lummus and Henningsen 1995). Holladay and Luster (1996) have reviewed 

the effects of B[a]P on T-cell development and the longterm consequences on the development of the immune 

system. Although development of the immune system 

begins in utero, important structural and functional 

changes occur after birth. In view of this continuing 

development, enhanced sensitivity to exposures to 

immunotoxicants both during gestation and infancy is to 

be expected.

Toxic Effects of Naphthalene

Studies have not widely reported or characterized 

naphthalene as a cause of toxic effects on reproduction 

and fetotoxic or teratogenic effects. However, Plasterer 

and colleagues (1985) did report a slight reduction in the 

number of pups per litter, as well as toxic effects in the 

mother after high oral doses of naphthalene, that is, the 

lethal dose for 50 percent of the population (LD50). However, the reports of preferential toxic effects in the neonate 

or infant described here are examples of toxic effects on 

postnatal development.

Researchers have reported hemolysis in infants 

exposed to very high doses of naphthalene (Siegel and Wason 1986). This effect appears to be caused by the metabolites (1- and 2-naphthol and 1- and 2-naphthoquinones) 

that produce methemoglobinemia. Also, naphthalene 

damaged both ciliated and Clara cells of the bronchiolar 

epithelium in mice (Plopper 1992a,b; Van Winkle et al. 

1995). Neonatal mice were more sensitive to this damage 

than were adult mice (Fanucchi et al. 1997). Although the 

experiment involved intraperitoneal dosing, the effects 

appear to depend on the metabolism of naphthalene in the 

target tissues and are therefore probably independent of 

the route of administration. 

Endocrine Disruption

Many investigators have reported that PAHs disrupt 

reproductive and developmental events and other physiological processes under endocrine control. Some of these 

effects appear to reflect direct action on hormones and 

their receptors as opposed to the cytotoxic action of reactive metabolites noted earlier. The nuclear AH receptor is 

responsible for regulating several cytochrome P-450 isoenzymes and triggering their induction in the presence 

of various xenobiotics, including PAHs, chlorinated dioxins, and coplanar polychlorinated biphenyls. This receptor 

also appears to have a range of other functions, including the modulation and proliferation of cell growth. The 

role of this receptor in the regulation of apoptosis, which 

includes the BAX gene product, has already been noted 

in the context of oocyte loss and may be involved in other 

processes in which apoptosis occurs.

The AH receptor also appears to interact with and 

in some cases control the expression of other nuclear 

receptors. B[a]P reduces the expression of receptors for 

the epidermal growth factor and the in vitro secretion of 

chorionic gonadotropin by human placental cells (Zhang 

et al. 1995). PAHs reportedly have antiestrogenic effects. 

Chaloupka and colleagues (1992) used MCF-7 human 

breast cancer cells to investigate in vitro the inhibition 

by 3-methylcholanthrene (a synthetic PAH) of estradiolstimulated cell growth. Subsequently, Navas and Segner 

(2000) described antiestrogenic effects of various PAHs on 

synthesis of vitellogenin in cultured hepatocytes of rainbow trout by 17-b-estradiol. In both systems, the binding 

of the PAH to the AH receptor appears to be the event that 

triggers a range of cellular responses, including a reduced 

expression of the estrogen receptor. 

Other Compounds

Tobacco smoke contains thousands of compounds, 

some of which have also been identified as known or suspected reproductive toxicants, in addition to the compounds already described here in detail. Examples include 

toluene, carbon disulfide, dichlorodiphenyltrichloroethane, styrene, benzene, and vinyl chloride. 

Other compounds that are less well studied may also 

influence reproductive outcomes. As noted earlier in this 

chapter (see “Tubal Function”), cigarette smoke impairs 

oviductal functioning (Knoll and Talbot 1998) and inhibits 

the growth of the chick chorioallantoic membrane (CAM) 
Reproductive and Developmental Effects 599

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

(Melkonian et al. 2000, 2002). To identify which chemicals 

in tobacco smoke are responsible for these toxic effects, 

solutions of mainstream smoke were fractionated and the 

eluates were screened for inhibitory activity in the CAM 

and oviductal assays. The CAM assay measures CAM and 

embryonic growth, and the oviductal assays measure ciliary beat frequency, oocyte pickup rate, and rate of smooth 

muscle contraction. The chemicals in each eluate that 

retained 80 percent or more of the inhibitory activity were 

identified by gas chromatography and mass spectrometry. This approach identified pyridine, pyrazine, phenol, 

indole, and quinoline derivatives as the major groups of 

inhibitory compounds (Ji et al. 2002; Melkonian et al. 

2003; Riveles et al. 2003, 2004, 2005). Members of each 

group were highly effective in both the CAM and oviductal 

assays that measure diverse biologic processes. In every 

group, some chemicals were inhibitory at nanodoses and 

picomolar doses, and indole was inhibitory in the oviductal 

assays at femtomolar doses. In general, methyl and ethyl 

substitutions increased the toxicity of these compounds. 

Some of the inhibitory chemicals (e.g., 3-ethylpyridine 

and pyrazine) are on the Flavor and Extract Manufacturer’s Association’s Generally Recognized as Safe list and the 

“Everything” Added to Food in the United States list from 

the U.S. Food and Drug Administration (FDA); some are 

added to cigarettes to enhance flavor.

Other Molecular Mechanisms

In addition to the molecular mechanisms of specific 

toxins outlined here, researchers have conducted general investigations of smoking in relation to pathways for 

molecular mechanisms.

Genetic Damage to Sperm

Concern exists that exposures to toxins such as 

those in cigarette smoke may cause damage to sperm 

DNA that could be transmitted to offspring (Chapin et al. 

2004). This important question of male-mediated toxic 

effects on development can now be addressed directly 

through use of tools of molecular genetics that detect 

and measure chromosomal changes and DNA damage 

in ejaculated sperm cells (Perreault et al. 2003). Studies 

have reported significant increases in sperm DNA and 

chromatin damage, including oxidative DNA damage, in 

smokers compared with nonsmokers from both infertility 

clinic and nonclinic populations (Fraga et al. 1996; Shen 

et al. 1997); strand breaks (Sun et al. 1997; Potts et al. 

1999); native DNA stainability (Sofikitis et al. 1995; Spanò 

et al. 1998); denaturation of labile sites (Potts et al. 1999); 

DNA adducts (Zenzes et al. 1999a,b; Horak et al. 2003); 

and apoptosis (Belcheva et al. 2004). Only a few studies 

did not find statistically significant differences related to 

exposure to cigarette smoke. One of these studies focused 

on DNA strand breaks (Sergerie et al. 2000) and another 

on oxidative DNA damage (Loft et al. 2003). Both studies 

were conducted in nonclinical populations.

Researchers have determined a statistically significant trend across published studies (p <0.001) for sperm 

aneuploidy associated with smoking (Robbins et al. 2005). 

Sperm carrying aberrant chromosomes are capable of 

fertilizing eggs that result in aneuploid offspring. For 

example, the father contributes the extra Y chromosome 

in 100 percent of XYY offspring, the extra chromosome 

in approximately 30 to 50 percent of XXY offspring with 

Klinefelter syndrome, and in up to an estimated 80 percent of the offspring with missing X in Turner’s syndrome 

(Hassold 1998; Martínez-Pasarell et al. 1999). In addition 

to congenital anomalies, damage to genetic material could 

affect sperm quality and could be manifested as infertility 

or very early pregnancy loss if the damage is incompatible 

with survival. 

Nutrient Deficiencies

Micronutrients

Deficiencies of micronutrients may contribute 

to adverse pregnancy outcomes, and smoking could act 

through this relationship. As previously mentioned, a 

decrease in the amount of collagen III likely leads to a 

weakening of the tensile strength of amniotic membranes, 

which could increase the risk of PPROM. Vitamin C is 

required for collagen formation in amnion epithelial cells, 

and studies have noted reduced vitamin C in women with 

PPROM (Wideman et al. 1964; Casanueva et al. 1993). 

Studies consistently show that plasma vitamin C levels are lower in smokers than in nonsmokers, a finding 

that appears to be attributable to a lower intake as well as 

increased utilization in the body (Preston 1991; Lykkesfeldt et al. 2000; Cogswell et al. 2003). Vitamin C levels in 

the amniotic fluid of smokers are also lower than those 

in nonsmokers (Barrett et al. 1991). Vitamin C is important for normal immune functioning. Deficiencies of vitamin C are associated with impaired immunocompetence, 

reduced counts of polymorphonuclear leukocytes, phagocytosis, and depressed cell-mediated immunity (Long and 

Santos 1999). A vitamin C deficiency in smokers could 

contribute to adverse pregnancy outcomes by impairing 

maternal immune responses to genital tract infections. 

Data on other antioxidant levels in smokers are conflicting (Cogswell et al. 2003).

Zinc deficiency may also play a causal role in PPROM 

and other adverse outcomes. Zinc is necessary for DNA 
Surgeon General’s Report

600 Chapter 8

synthesis, transcription, and translation, as well as cell 

division and cell growth (Fisher 1975; Vallee and Falchuk 

1993; Prasad 1996). Low zinc levels result in impaired 

immune function (Fraker and King 2004), increased susceptibility to infectious diseases (Fischer Walker and Black 

2004), and cell death (Fraker 2005). Researchers have 

found reduced serum and amniotic fluid levels of zinc 

in pregnant women with PPROM (Anderson 1979; Kiilholma et al. 1984). A prospective study of pregnant women 

associated a low zinc intake with a threefold increase in 

PPROM (Scholl et al. 1993). Some data suggest that smokers are more likely to experience a zinc deficiency than 

are nonsmokers (Cogswell et al. 2003). Levels of maternal dietary zinc, plasma zinc, and zinc in red blood cells 

are similar in smokers and nonsmokers close to the time 

of delivery. However, shortly after delivery, zinc levels in 

cord blood and polymorphonuclear cells, which may be 

a more sensitive indicator of zinc depletion, were lower 

in smokers than in nonsmokers (Simmer and Thompson 

1985; Kuhnert et al. 1987b). Cadmium, which accumulates in the placenta and binds to zinc, may contribute to 

a local zinc deficiency in smokers (Kuhnert et al. 1987a,b, 

1988a,b; Preston 1991).

Amino Acids

In addition to a supply of nutrients delivered to the 

fetus through the uteroplacental circulation, fetal growth 

depends on nutrient transport across the syncytiotrophoblast. Because the placenta is impermeable to most proteins, almost all of the fetal proteins are synthesized by 

the fetus from amino acids supplied by the mother. Amino 

acids from the mother’s blood are taken up by the active 

transport of placental trophoblasts and then diffused into 

the umbilical venous blood. There is accumulating evidence that abnormalities in amino acid transport across 

the placenta can contribute to impaired fetal growth (Pastrakuljic et al. 1999). In addition, many studies suggest 

that maternal smoking adversely affects this transport, 

and this effect may be one mechanism by which smoking 

restricts fetal growth. Levels of several amino acids in fetal 

plasma, umbilical plasma, and placental villi are lower in 

smokers than in nonsmokers (Jauniaux et al. 1999, 2001) 

(see “Carbon Monoxide” and “Nicotine” earlier in this 

chapter). Additional research is needed to determine more 

precisely how the results of the in vivo and in vitro studies may be related to adverse pregnancy outcomes among 

maternal smokers.

Nitric Oxide Activity

Researchers have also studied the effects of smoking on NO activity. Endothelial NO is a potent vasodilator 

synthesized by NO synthase in vascular endothelial cells 

(ENOS) (Moncada and Higgs 1993). NO regulates blood 

pressure by its effects on vascular resistance. Evidence 

suggests that a decrease in the release of basal NO may predispose a person to hypertension, vasospasm, and thrombosis, whereas elevated levels may be associated with shock 

(Moncada and Higgs 1993; Änggård 1994; Cooke and Dzau 

1997; Oemar et al. 1998). In pregnancy, NO is also present 

in placental villi and is believed to play an important role 

in the vasodilatory response of the maternal, uteroplacental, and fetoplacental circulatory systems (Myatt et al. 

1991, 1992; Poston et al. 1995). Reductions of NO activity 

in placental villi from pregnancies with preeclampsia and 

IUGR suggest a role for NO in pregnancy complications 

(Sooranna et al. 1995). In vitro research indicates that the 

mRNA and the protein expression of ENOS are decreased 

in endothelial cells from preeclamptic pregnancies (Wang 

et al. 2004).

Studies have associated maternal smoking with a 

dose-dependent decrease in endothelial-dependent vessel 

dilation (Lekakis et al. 1998; Poredoš et al. 1999) and with 

an inhibition of ENOS activity, depending on the ENOS

genotype (Wang et al. 2000b). Researchers have reported 

that endothelial cells from the umbilical cords of infants 

born to smokers had a 40-percent reduction in ENOS 

activity and a 32-percent reduction in ENOS levels compared with those in cells from infants born to nonsmokers. Furthermore, the ENOS activity level was associated 

with the number of cigarettes smoked per day (Andersen 

et al. 2004). The effects of maternal smoking on ENOS 

activity could lead to lower NO levels, resulting in a loss of 

dilatory capacity and contributing to IUGR.

Smoking and Maternal and 

Neonatal Genetic Polymorphisms

Investigators have reported differences in the 

human metabolism of toxic constituents in tobacco 

smoke (Benowitz et al. 1999; Lee et al. 2000; Yang et al. 

2001). These metabolic differences may reflect a differential induction of toxins and drug-metabolizing enzymes, 

such as phase I cytochrome P-450; phase II glutathioneS-transferase (GST); NAT1 and 2; placental alkaline phospholipase; lysyl oxidase; the platelet-activating factor 

acetylhydrolase; TGFα; TGFβ3; and microsomal epoxide 

hydrolase. Genetic polymorphisms that alter the expression of these enzymes are in the pathway of development 

of disease such as lung cancer. These polymorphisms 

also appear to modify the relationship between prenatal 

exposure to tobacco smoke and birth outcomes. Studies of 

prenatal exposure to fetotoxins present in tobacco smoke 

(e.g., PAHs, AH, and benzene) have linked these toxins 
Reproductive and Developmental Effects 601

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

to adverse pregnancy outcomes through the inducibility of phase I enzymes such as CYP1A1 (Huel et al. 1993; 

Lagueux et al. 1999; Dejmek et al. 2000; Wang et al. 

2000a), which can vary by host genotype.

Birth Defects

Initial investigations of the mechanisms of maternal or neonatal metabolism of tobacco smoke toxins and 

adverse birth outcomes were conducted in studies of birth 

defects. Several studies examined the potential interaction 

of maternal exposure to tobacco smoke and maternal and/

or neonatal genotypes in association with orofacial cleft in 

newborns (Table 8.13). The genetic polymorphisms that 

code for the expression of tissue damage, inflammatory 

response, and immune mediator enzymes and that were 

examined in those studies include TGFα and TGFß3, 

MSX1, and EPHX1, as well as gene variants of both phase 

I activation and phase II detoxification enzymes CYP1A1, 

GSTM1, GSTT1, NAT1, and NAT2. Prenatal exposure to 

tobacco smoke was measured by self-reports of maternal 

active smoking, maternal exposure to secondhand smoke, 

and paternal active smoking. Most of these studies examined the TGFα genotype in neonates. In one study, genotyping was performed in both neonates and parents. 

A case-control study of infants with a TGFα *TAQ1

genotype that contained a rare allele and whose mothers had smoked during pregnancy found a significantly 

elevated risk for cleft palate in offspring (Table 8.13) 

(Hwang et al. 1995). In a large, population-based, casecontrol study conducted by the California Birth Defects 

Monitoring Program registry, the risks of cleft palate and 

cleft lip with or without cleft palate were significantly 

elevated among White infants with TGFα *rare genotypes (*A2) whose mothers were heavy smokers (Shaw et 

al. 1996). However, three subsequent case-control studies (Christensen et al. 1999; Romitti et al. 1999; Beaty et 

al. 2001) that failed to replicate these findings had fewer 

cases and one study had used a lower cutpoint for smoking 

than that used by Shaw and colleagues (1996). None of the 

five studies cited above presented regression models with 

terms for estimating maternal smoking levels and the 

TGFα genotype interactions. Zeiger and colleagues (2005) 

conducted a meta-analysis of data from these five studies and found a marginally significant interaction between 

maternal smoking and infant TGFα *allele genotypes 

(*A2) in relation to cleft palate (OR = 1.95 [95 percent CI, 

1.22–3.10]). There was no evidence of an interaction in 

relation to cleft lip and cleft palate (OR = 0.86 [95 percent 

CI, 0.53–1.40]).

Romitti and colleagues (1999) also examined the 

TGFß3 genotype and maternal smoking in relation to 

the risk of cleft palate or cleft lip and cleft palate (Table 

8.13). These researchers found a significantly elevated risk 

for the conditions among infants who were homozygous 

for the common *1 allele at the X5.1 or 5’UTR.1 site and 

whose mothers had smoked 10 or more cigarettes per day. 

There was no evidence of an interaction for infant genotypes that included the rare *2 allele.

Hartsfield and colleagues (2001) did not observe 

any significant interaction between maternal smoking 

and EPHX1 (codon 113) or null GSTM1 genotypes in a 

case-control study of isolated cleft lip and cleft palate 

(Table 8.13). van Rooij and colleagues (2001) examined the 

association of maternal prenatal smoking and the maternal GSTT1 genotype. The researchers found that mothers

who smoked and carried the GSTT1 null genotype had a 

marginally higher risk for delivering an infant with oral 

clefting than that of nonsmokers who carried the wild-type 

genotype. Although the RR was not statistically significant, 

it was almost five times greater when both mothers and 

their infants carried the GSTT1 null genotype. There was 

no evidence of an interaction between maternal smoking 

and the CYP1A1 genotype with a recessive allele in relation to oral clefting. In a case-control study, the CYP1A1, 

GSTT1, and GSTM1 polymorphisms were also examined 

as risk factors for hypospadias, a congenital anomaly of 

the male reproductive organs (Kurahashi et al. 2005). 

The study did not observe any increased risk of hypospadias among children born to mothers who smoked and 

had various genotypes, including CYP1A1 *MSPI variant 

allele genotype or the GSTT1 null genotype or GSTM1 

null genotype. In a case-only, haplotypic analysis of an 

intronic CA repeat of the MSX1 gene in 206 infants with 

oral clefting, there was evidence for an interaction with 

maternal prenatal smoking (Fallin et al. 2003). In the Iowa 

study (Romitti et al. 1999), infants whose MSX1 X1.3 or 

MSX1 X2.4 genotype contained the *2 allele and whose 

mothers smoked 10 or more cigarettes per day also had 

a significantly elevated risk of cleft palate (Table 8.13). In 

a study of limb deficiency defects, Carmichael and colleagues (2004) did not observe any significantly elevated 

risk for infants with MSX1 intronic CA repeat genotype 

whose mothers smoked during pregnancy. In another 

case-control study from the California Birth Defects Monitoring Program, the NAT1 1088 genotype *A/*A and the 

NAT1 1095 genotype *A/*A, but not NAT2 polymorphisms, 

were strongly associated with isolated oral clefting in 

infants whose mothers had smoked during pregnancy 

(Table 8.13) (Lammer et al. 2004).

Other Reproductive Endpoints

Several studies have also examined the potential 

interaction among phase I and II toxins, genes for drug 

metabolism, and prenatal exposure to tobacco smoke in 
Surgeon General’s Report

602 Chapter 8

Table 8.13 Studies of interactions between genotype and exposure to tobacco related to oral clefting

Study Study period Population Definition of smoking Key results

Hwang et al. 

1995

1984–1992 69 case infants 

with CP

114 case infants 

with CL/P

284 control infants 

with no cleft 

defects

Pregnant smokers

Pregnant nonsmokers 

Light smokers: ≤10 cigarettes/day

Heavy smokers: >10 

cigarettes/day

• Among White infants with TGFα genotype 

containing the *A2 (rare) allele at the TAQ1

site whose mothers were heavy smokers, 

risks of CP and CL/P were significantly 

elevated (OR = 5.60 [95% CI, 1.36–22.9]) 

in infants with no family history of birth 

defects

• By amount smoked, risk for CP was elevated 

among infants with *A2 allele born to light 

smokers (OR = 6.16 [95% CI, 1.09–34.7]) as 

well as infants whose mothers were heavy 

smokers (OR = 8.69 [95% CI, 1.57-47.7])

Shaw et al. 

1996

1987–1989 731 case infants 

with orofacial 

clefting

348 with isolated 

CL/P

141 with isolated 

CP

99 with multiple 

CL/P

74 with multiple 

CP

69 with known 

cause

939 control infants

California Birth 

Defects Monitoring 

Program

Smokers: 1–19 cigarettes/

day, ≥20 cigarettes/day

Nonsmokers exposed to 

secondhand smoke from 

anyone inside mother’s 

home who smoked daily 

during 4 months after 

conception or from 

regularly frequented 

places where others 

smoked

• White infants whose TGFα genotype 

contained the *A2 allele born to maternal 

heavy smokers had increased risk of isolated 

CL/P (OR = 6.1 [95% CI, 1.1–36.6])

• Risks were also elevated in the same group 

for isolated CP (OR = 9.0 [95% CI, 1.4–

61.9]) and for “known etiology clefts” 

(OR = 10.8 [95% CI, 1.2–111.7])

• Sample size in non-White racial groups was 

too small to permit reliable estimates of 

effect

Christensen 

et al. 1999

1991–1994 316 case infants

233 with CL/P

83 with CP

604 control infants

Smokers (before 

conception and/or 

during pregnancy): mean 

cigarettes/day

Nonsmokers

• No evidence was found for increased risk of 

CP or CL/P among infants with the *rare

allele for TGFα whose mothers had smoked 

while pregnant

Romitti et al. 

1999

1987–1994 225 case infants

161 with CL/P

64 with CP

393 control infants

Smokers (before 

conception and/or 

during pregnancy): 

1–9 cigarettes/day, ≥10 

cigarettes/day

Nonsmokers

• For infants whose genotype contained the 

*rare allele for TGFα or TGFß3, maternal 

smoking did not increase risk of having CP 

or CL/P

• Infants whose genotype contained common 

*1 allele for TGFß3 (X5.1 or 5’UTR.1 sites) 

were at increased risk of having CP or CL/P 

• With maternal smoking of ≥10 cigarettes/

day, infants whose MSX1 X1.3 genotype 

contained *A2 allele had elevated risk of CP 

(OR = 2.7 [95% CI, 1.1–6.3])

• Similar results were found among infants 

whose MSX1 X2.4 genotype contained *A2

allele (OR = 2.8 [95% CI, 1.1–6.9])
Reproductive and Developmental Effects 603

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Table 8.13 Continued

Study Study period Population Definition of smoking Key results

Beaty et al. 

2001

1992–1998 175 infants

111 with CL/P

64 with CP

182 control infants

Smokers (before 

conception and/or during 

pregnancy) 

Nonsmokers (survey 

of passive exposure to 

cigarette smoke)

• No evidence was found for increased risk of 

isolated CL, CP, or CL/P among infants with 

*rare allele for TGFα whose mothers had 

smoked while pregnant

Hartsfield et 

al. 2001

1987–1989 85 case infants 

with CL/P 

110 control infants 

Pregnant smokers • With maternal smoking, infants whose 

genotype was homozygous for EPHX1

codon 113 *H allele were not at higher 

risk of CL/P than were infants with EPHX1

codon 113 wild-type allele 

(OR = 0.4 [95% CI, 0.1–1.3])

van Rooij et 

al. 2001

Not reported 113 infants with 

nonsyndromic oral 

clefts

104 control infants

Smokers (before 

conception and/or 

during pregnancy and/or 

postpartum)

Nonsmokers

• Attributable fraction for oral clefting 

in maternal smokers with GSTT1 null

genotype was 7.3%, increased to 7.7% when 

both mother and infant had GSTT1 null

genotype

• No interaction was observed with maternal 

smoking and CYP1A1 polymorphism 

(maternal or infant) associated with risk of 

oral clefting

Fallin et al. 

2003

1992–1998 206 case infants 

with oral clefting

No controls

Smokers (before 

conception and/or during 

pregnancy)

Nonsmokers (survey 

of passive exposure to 

secondhand smoke)

• Case-only (combined CP and CL/P) tests of 

association between MSX1 haplotypes and 

maternal smoking during first trimester 

showed excess cases of haplotype containing 

intronic CA repeat marker among infants of 

mothers who smoked

Lammer et 

al. 2004

1987–1989 437 case infants

309 with isolated 

CL/P 

128 with CP

California Birth 

Defects Monitoring 

Program

Smokers: 1–19 cigarettes/

day or ≥20 cigarettes/day

Nonsmokers exposed to 

secondhand smoke from 

anyone inside mother’s 

home who smoked daily 

during 4 months after 

conception or from 

regularly frequented 

places where others 

smoked

• NAT1 1088 homozygous *A/*A genotype 

among infants whose mothers smoked was 

strongly associated with CL/P 

(OR = 3.9 [95% CI, 1.1–17.2]) 

• NAT1 1095 homozygous *A/*A genotype 

was also strongly associated with CL/P 

(OR = 4.2 [95% CI, 1.2–18.0]) 

• No significant interaction was observed 

for NAT2 polymorphisms and maternal 

smoking in relation to CL/P or CP

Zeiger et al. 

2005

1984–1998 

Meta-analysis 

of data from 

5 studies

726 case infants 

with CL/P

335 with CP

1,565 control 

infants (metaanalysis)

Smokers (before 

conception and/or 

during pregnancy and/or 

postpartum)

Nonsmokers 

• Meta-analysis results indicated that with 

maternal smoking at any level during 

pregnancy, risk of CP increased for infants 

whose TGFα genotype contained *A2 allele 

(OR = 1.95 [95% CI, 1.22–3.10])

• No significant interaction for maternal 

smoking and infant carrying TGFα *A2

allele was associated with CL/P

Note: CI = confidence interval; CL/P = cleft lip with or without cleft palate; CP = cleft palate; OR = odds ratio.
Surgeon General’s Report

604 Chapter 8

Table 8.14 Decreased birth weight, preterm delivery, intrauterine growth retardation, and neonatal oxidative 

damage: interactions between host genotype and exposure to tobacco smoke

Study Study period Population Definition of smoking Key results

Hong et 

al. 2001

1999 81 maternal 

and infant 

pairs measured 

for neonatal 

oxidative 

damage

Nonsmokers exposed 

and unexposed to 

secondhand smoke 

during pregnancy, 

determined by 

measuring cotinine 

levels

• Urinary concentrations of neonatal oxidative damage 

from 8-OH-dG were correlated with maternal 

exposure to secondhand smoke 

• Infants of mothers with GSTM1 null genotype and 

exposure to secondhand smoke had significantly 

higher concentrations of 8-OH-dG than did infants 

of mothers with GSTM1 present genotype and no 

exposure to secondhand smoke

Wang et 

al. 2002

1998–2000 207 mothers of 

preterm and/or 

LBW infants

534 control 

infants

Smokers (continuously 

or with cessation during 

pregnancy)

Self-reported lifetime 

nonsmokers

• Mothers with CYP1A1 MSPI genotype containing 

the *a allele who smoked throughout pregnancy had 

infants with mean birth weight decrements of -520 g 

compared with mothers with CYP1A1 MSPI *A/*A

genotype who never smoked (from stratified models: 

LBW OR = 3.2 [95% CI, 1.6–6.4]; from interaction 

term model: LBW OR = 3.1 [95% CI, 1.2–7.8])

• Infants of mothers with GSTT1 null genotype 

who smoked throughout pregnancy had mean 

birth weight decrements of -642 g compared with 

mothers with the GSTT1 present genotype who 

never smoked (from stratified models: LBW 

OR = 3.5 [95% CI, 1.5–8.3]; from interaction term 

model: LBW OR = 2.4 [95% CI, 0.9–6.6])

• Among mothers with CYP1A1 MSPI *Aa/*aa and 

GSTT1 null genotypes, infants of mothers who 

smoked throughout pregnancy had mean birth 

weight decrements of -1,285 g (test of interaction: 

-1086 g, p <0.001) 

• Interaction between maternal GSTT1 genotype and 

maternal smoking in relation to preterm birth was 

significant (OR = 2.9 [95% CI, 1.0–8.2])

• Interaction between maternal CYP1A1 MSPI

genotype and maternal smoking in relation to 

intrauterine growth retardation was significant 

(OR = 3.0 [95% CI, 1.2–7.8])

Hong et 

al. 2003

1999 266 maternal 

and infant 

pairs measured 

for birth 

weight

Nonsmokers exposed 

or unexposed to 

secondhand smoke 

during pregnancy, 

determined by 

measuring cotinine 

levels

• Mothers exposed to secondhand smoke during 

pregnancy and having GSTM1 null genotype 

delivered infants with mean birth weight 

decrements of -158 g compared with unexposed 

women with GSTM1 present genotype, after 

adjustment for gestational age

• Similarly, women exposed to tobacco as secondhand 

smoke and having GSTT1 null genotype delivered 

infants with mean birth weight decrements of -203 g 

compared with unexposed women with GSTT1 

present genotype, after adjustment for gestational 

age
Reproductive and Developmental Effects 605

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Table 8.14 Continued

Study Study period Population Definition of smoking Key results

Magrini 

et al. 

2003

NR 214 maternal 

and infant 

pairs measured 

for birth 

weight

Smokers

Nonsmokers

• Placental specimens from maternal smokers who 

did not have PLAP *1/*1 genotype were associated 

with elevated risk of LBW infants (OR = 6.02 [95% 

CI, 1.65–23.02])

• This effect was more marked in mothers aged >28 

years

Nukui et 

al. 2004 

NR 955 mother 

and infant 

pairs assessed 

for preterm 

birth and LBW

Smokers (cigarettes/

day for first and third 

trimesters)

Nonsmokers (hours of 

exposure to secondhand 

smoke)

• Maternal smokers during third trimester and their 

infants, both with GSTT1 null genotype, had higher 

risk of premature birth than did mothers and infants 

with GSTT1 present genotype among nonsmokers in 

third trimester (OR = 4.0 [95% CI, 1.7–9.5])

• When both mother and infant had GSTT1 null

genotype, the risk of premature birth was elevated 

for smokers and nonsmokers and their infants

Note: 8-OH-dG = 8-hydroxy-2’-deoxyguanosine; CI = confidence interval; g = grams; LBW = low birth weight; NR = data not reported; 

OR = odds ratio.

relation to other outcomes, such as LBW, preterm birth, 

IUGR, and neonatal oxidative damage (Table 8.14).

A large case-control study described an interaction 

between self-reported smoking during pregnancy and 

maternal genetic polymorphisms for CYP1A1 MSPI and 

GSTT1, which were associated with reduced birth weight, 

preterm delivery, reduced gestation, and IUGR (Table 

8.14) (Wang et al. 2002). Mothers who had smoked continuously during pregnancy and who were heterozygous 

variant type (*A/*a) or homozygous variant type (*a/*a) 

for CYP1A1 MSPI, were at a threefold higher risk of having a LBW (<2,500 g) infant compared with lifetime nonsmokers who were homozygous wild type (*A/*A). In these 

genotype-exposure groups, gestation was reduced on average by 1.5 weeks among smokers who were CYP1A1 MSPI

*A/*a or *a/*a. Smokers with the GSTT1 null genotype 

gave birth to infants with significant decrements in birth 

weight compared with birth weight of infants of nonsmokers who carried at least one GSTT1 allele. The risk of 

growth retardation, defined as less than 85 percent of the 

ratio of observed birth weight to mean birth weight for 

gestational age, was associated with smoking in mothers 

who carried the CYP1A1 MSPI *A/*a or *a/*a. This study 

was unique because it presented regression models that 

evaluated interaction terms along with analyses stratified 

by gene variant and smoking status, but it lacked an objective measure of smoking.

In a study conducted in Korea, Hong and colleagues 

(2003) examined the potential interaction of the GST family gene variants and exposure to secondhand smoke in 

association with mean birth weight (Table 8.14). Women 

classified as exposed to secondhand smoke, as determined 

by assays of urinary levels of cotinine, who carried the 

GSTM1 null genotype delivered infants with a mean birth 

weight decrement of -158 g, after adjustment for gestational age. A similar pattern was observed among mothers 

with the GSTT1 null genotype (decrement of -203 g). In 

a subsample of 81 women in the same study population, 

Hong and colleagues (2001) examined the effect of exposure to secondhand smoke and maternal GST family genotypes in relation to measurements of neonatal oxidative 

damage as urinary levels of 8-hydroxy-2’-deoxyguanosine 

(8-OH-dG). Infants born to women classified as exposed to 

secondhand smoke who carried the GSTM1 null genotype 

had significantly higher levels of log urinary 8-OH-dG 

(geometric mean level = 4.03 [95 percent CI, 2.13–7.61]) 

than did women classified as unexposed who carried the 

GSTM1 wild type. Significant differences in 8-OH-dG 

remained after adjusting for confounders.

One study evaluated phase I and II metabolic 

enzyme gene variants (Table 8.14) (Nukui et al. 2004). The 

authors reported that the most significantly elevated risk 

of premature birth occurred when both mother and infant 

carried the GSTT1 null genotype. The results were the 

same for smokers and nonsmokers, so no interaction was 

observed. Phase I genetic polymorphisms (e.g., CYP1A1) 

were not associated with an elevated risk of a premature 

birth. A study that examined PLAP polymorphisms found 

an elevated risk of LBW when the PLAP *1/*1 genotype 

was absent in mothers who smoked (Magrini et al. 2003). 
Surgeon General’s Report

606 Chapter 8

Implications

The evidence of a causal relationship between smoking during pregnancy and increased risk for adverse 

pregnancy outcomes is sufficient to warrant promoting 

smoking cessation among women early in pregnancy or 

before they become pregnant, because the critical period 

may be quite early. For example, the impact of smoking on 

oral clefts could be lessened by 5 to 22 percent if women 

stopped smoking before pregnancy. Thus, there is a need 

for widespread implementation of interventions for effective smoking cessation that target all women of childbearing age. 

Smoking may have several ramifications of alterations in fertility, menstrual cycle function, or sperm quality, including a burden on the health care system and loss 

of work productivity. These changes may affect a woman’s 

ability to conceive and maintain a pregnancy at a desired 

time in a couple’s life. The reproductive life span may be 

shortened, and early menopause is associated with other 

hormone-related health problems such as osteoporosis and 

cardiovascular disease (Harlow and Ephross 1995; Sowers 

and La Pietra 1995; Cooper and Sandler 1998). Women 

with short menstrual cycles may also be at a higher risk 

of breast cancer (Kelsey et al. 1993). Such effects warrant 

smoking cessation early in the reproductive age span, or 

ideally, prevention of smoking initiation among youth.

Smoking Prevention and Cessation

Smoking cessation is one of the most important 

actions a woman can take to improve the outcome of her 

pregnancy, and most women who stop smoking during 

pregnancy do so on their own. Because women know about 

the adverse effects of smoking on their health and that of 

a fetus, pregnancy may be a time when smoking cessation 

efforts and interventions are potentially more effective 

(Mullen 1999; Fiore et al. 1996, 2008). Nevertheless, most 

smokers do not stop smoking during pregnancy. Tobacco 

addiction is progressive and chronic and, in consequence, 

smoking cessation interventions focusing on the prenatal 

period have failed to achieve long-term abstinence among 

most pregnant smokers. Two-thirds of women who smoke 

during the first pregnancy also smoke during the second, 

exposing the first infant to tobacco smoke both in utero 

and postnatally (Dietz et al. 1997).

Population-based, cross-sectional surveys have been 

widely used to monitor prenatal smoking rates (Connor 

and McIntyre 1999; Owen and Penn 1999; Ebrahim et al. 

2000). However, such data do not provide information 

on changes in smoking behaviors during pregnancy, in 

contrast to data collected during prenatal care, in which 

smoking behaviors are recorded on more than one occasion, as described by Kirkland and colleagues (2000). Such 

longitudinal data can usefully supplement survey data 

to monitor progress in control of prenatal exposure to 

tobacco smoke. Because of the social desirability of nonsmoking status, which is greater during pregnancy, the 

actual prevalence of smoking may be even higher than 

is self-reported. In the United Kingdom, 16 percent of 

respondents to a survey reported that they did not 

admit to their physicians that they smoked (Bulletin of the 

World Health Organization 1999). A study in the United 

States found nondisclosure rates of 28 percent at enrollment into prenatal care and 35 percent at follow-up (Kendrick et al. 1995). Therefore, biochemical verification of 

smoking status of each woman during each contact with 

a clinician is needed to evaluate cessation interventions. 

Clinicians who provide health care to women have 

an important role in reducing the burden of smoking 

among women. Clinically proven programs for smoking 

cessation that can be delivered in primary care settings 

are now available. However, there is a dearth of information specifically addressing the most effective smoking 

prevention and cessation interventions for women of 

childbearing age, especially those of low socioeconomic 

status. For this reason NC1 has implemented the TReND: 

Low SES Women and Girls Project. This project was created to strategically address and examine the effects of 

multiple tobacco control policies on diverse populations 

of low SES women and girls. In addition, the USDHHS 

Office of Women’s Health has developed an interagency 

work group to address this issue. The FDA Office of Women’s Health has also developed a guide for providers to 

educate women about medications available to assist them 

if they are ready to quit smoking.

Experts attending the 1998 Consensus Workshop 

on Smoking Cessation During Pregnancy reviewed the 

evidence related to counseling on smoking cessation during pregnancy, including the U.S. Public Health Service 

Clinical Practice Guideline, Treating Tobacco Use and 

Dependence (Fiore et al. 1996; Mullen 1999). This group 

concluded that brief cessation counseling (5 to 15 minutes), delivered by a trained provider with pregnancyspecific self-help materials, significantly increases rates 

of cessation among pregnant smokers. The 5A strategy 

of smoking intervention—Ask, Advise, Assess, Assist, and 

Arrange—and recommended procedures are outlined in 

the one-page form, Brief Smoking Cessation Counseling 
Reproductive and Developmental Effects 607

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

for Pregnant Patients. More intense efforts may be needed 

for groups of women who are less likely to stop smoking and more likely to relapse (Connor and McIntyre 

1999). Smoking cessation interventions should be continued after delivery to prevent relapse, and partners 

who smoke should be included in such interventions. 

More than 50 percent of women do not recognize that 

they are pregnant until after the fourth week of gestation. Therefore, efforts to prevent exposure to tobacco 

smoke should begin before conception to avoid pregnancy 

complications or to avoid exposing the fetus to tobacco 

smoke. Furthermore, to prevent subfertility, cessation 

efforts should begin even earlier in the reproductive period. 

Despite evidence that provider-administered cessation counseling significantly increases rates of cessation 

among pregnant smokers, evidence suggests that such 

interventions may do little to decrease overall prenatal 

smoking prevalence. It has been estimated that universal 

implementation of a provider-administered psychosocial 

cessation intervention on a national level would result in 

only a modest decline (0.8 percentage points) in the overall prevalence of smoking among pregnant women (Kim 

et al. 2009). Larger reductions in prenatal smoking prevalence will likely require implementation of comprehensive 

tobacco control policies that effectively decrease smoking 

prevalence among women of reproductive age.

Unfortunately, pregnant women who smoke most 

heavily do not appear to respond to the type of behavioral 

intervention indicated here. The U.S. Public Health Service has suggested, as have others, the need to explore 

the use of pharmacologic approaches to achieve cessation in women who are unable to stop smoking (Fiore et 

al. 1996, 2000, 2008). These approaches include nicotine 

replacement therapy (e.g., gum, patch, inhaler, or spray); 

nonnicotine products, such as varenicline and bupropion 

hydrochloride; and second-line pharmacotherapies, such 

as clonidine and nortriptyline. However, the efficacy and 

safety of these approaches during pregnancy are not well 

documented. Pharmacologic interventions should be considered on an individual basis as an adjunct to behavioral 

interventions. These interventions should be considered 

for pregnant women only if the increased likelihood of 

smoking cessation outweighs the harmful effects on the 

fetus of nicotine replacement therapy and possible continued smoking.

To minimize the effects of smoking among all 

women and to foster effective perinatal tobacco control, 

focus and efforts should expand beyond prenatal care to 

include both the whole family and the entire reproductive life span of women. The complexities associated with 

smoking cessation among established smokers are underscored by reports of persistent high smoking rates among 

pregnant women in Canada, the United Kingdom, and 

the United States (Connor and McIntyre 1999; Owen and 

Penn 1999; Ebrahim et al. 2000). Long-term reduction in 

tobacco exposure during pregnancy can be achieved only 

by encouraging adolescent girls and young women not to 

start smoking.

Regulation and Policy

Ranking of infant mortality rates in established market economies placed the United States twenty-eighth in 

2005 compared with twelfth in 1960. Rates of smoking 

remain high among women in three categories related 

to pregnancy—pregnant, planning a pregnancy, and at 

risk of pregnancy. Substantial efforts would be needed to 

reduce known risks to pregnancy and infant health, to 

reverse the stagnant trends in infant mortality rates in the 

near future. Because only about 20 percent of women successfully control tobacco dependence during pregnancy, 

smoking cessation is recommended before pregnancy 

(U.S. Preventive Services Task Force [USPSTF] 2003). 

National recommendations to support preconception care 

as an opportunity to reduce maternal risks during pregnancy have been introduced (USPSTF 2003). Therefore, 

high rates of smoking in the preconception period, almost 

the same as that among all women of childbearing age, 

pose both a challenge and an opportunity to the implementation of the preconception care initiative. After childbirth, smoking does not usually decline below the level 

achieved during pregnancy (USPSTF 2003). Therefore, 

further challenges to preventing smoking-related harm to 

infant health include continued postnatal exposure to secondhand tobacco smoke from maternal smoking. 

Intervention tools to aid smoking cessation among 

pregnant women are now available. One report estimated 

that the costs of implementing such interventions range 

from $24 to $34 per pregnant smoker counseled (Ayadi 

et al. 2006). Potential neonatal cost savings that could be 

accrued for women who stop smoking during pregnancy 

were estimated at $881 per maternal smoker (Ayadi et al. 

2006). A woman’s contact with the health care system 

during and after pregnancy provides enough opportunities to engage women for smoking cessation and provide 

follow-up and support services to prevent relapse during the interconception period. Furthermore, women of 

childbearing age in the United States have on average 6.4 

health care visits per year (Adams and Marano 1995), and 

such opportunities can be used to improve access to the 

5A strategy of smoking intervention. 

Smoking behaviors of partners of women who smoke 

are important considerations for achieving cessation and 

prevention of relapse. Extension of services or facilitation 
Surgeon General’s Report

608 Chapter 8

of use of services by the partners would be needed to maintain the benefit from smoking cessation services provided 

to the women. Because men have fewer contacts with the 

health care system than do women (Everett et al. 2005), 

smoking cessation efforts among women provide an 

opportunity for access to health care for their male partners also for cessation efforts. 

Efforts to reduce smoking in the United States have 

shifted from a primary focus on smoking cessation for 

individuals to more population-based interventions that 

emphasize prevention of smoking initiation, reduction 

of exposure to secondhand tobacco smoke, and policy 

changes in health care systems to promote cessation. Parallel to these efforts, concerted efforts are needed to reduce 

the disparity in smoking rates among socially disadvantaged women and White women; targeted efforts aimed 

at women in the preconception period and those at risk 

for pregnancy; and efforts to promote smoking cessation 

among women who are pregnant. One report indicated 

that bundling of services to address common preventable risks, such as tobacco and alcohol use and risks for 

sexually transmitted diseases, through a preconceptional 

approach, would benefit about one-half of all women of 

childbearing age in the United States (CDC 2006). Tobacco 

use in women coexists with other risk behaviors or morbidities, including mental health disorders and substance 

use. Some factors, such as illicit drug use or alcohol use, 

may synergistically elevate the risk from other factors 

such as tobacco use or acquisition of sexually transmitted infections, requiring intervention approaches through 

case management that address more than one risk factor. Use of tobacco and alcohol are comorbidities that 

can benefit from many efforts to provide several interventions to a woman simultaneously. Such case-management 

approaches may help to increase adherence to treatment 

and reduce relapse to smoking after delivery. 

Earlier data have indicated that the observed 

declines during the past four decades in the United States 

in smoking rates among pregnant women reflect declines 

that occurred in general among women and were not specific to pregnancy. Therefore, efforts to close the gaps in 

the diffusion of smoking cessation intervention to individual smokers are still needed and should be a priority. However, large reductions in smoking rates among pregnant 

women over time are more likely to come from efforts to 

reduce smoking initiation by young women. 

Evidence Summary

Health professionals have long considered exposure to tobacco smoke harmful to reproduction, affecting 

aspects from fertility to fetal and child development and 

pregnancy outcome. Tobacco smoke contains thousands 

of compounds, some of which are known toxicants to 

reproductive health, such as CO, nicotine, and metals. 

About 10 percent of couples who want to conceive a child 

experience infertility or reduced fertility, approximately 

10 to 20 percent of women who do conceive have miscarriage or stillbirth before delivery, and others have pregnancy complications and adverse outcomes that affect 

infant health and survival (CDC 2005). 

In 2007, 17.4 percent of women and approximately 19 percent of women of reproductive age (18 

through 44 years) smoked cigarettes (CDC 2008). 

From 2002 to 2005, 17.3 percent of pregnant women 

reported smoking cigarettes in the past month (NSDUH 

Report 2007). Because smoking rates have declined, persons involuntarily exposed to tobacco smoke probably 

now outnumber active smokers and they are exposed to 

some of the same toxins to which smokers are exposed. 

Previous Surgeon General’s reports and subsequent 

studies have found that smoking is related to several 

reproductive health endpoints. The 2001 report on women 

and smoking and the 2004 report on the health consequences of smoking noted a causal link between smoking 

and reduced fertility in women. Smoking may contribute 

to reduced fertility and other related reproductive endpoints, including earlier menopause or altered menstrual 

cycle parameters, through similar mechanisms such as 

by producing alterations in hormone function. Study 

findings suggest effects of smoking on estrogen and other 

hormones, which may vary by gender and the stage of life. 

Researchers have suggested that smoking has antiestrogenic effects, but more recent data are less consistent, at 

least for nonpregnant, premenopausal women. Studies 

implicate smoking and its effects on other hormones, such 

as progesterone, gonadotropins (FSH), and androgens 

(including in men). In animal studies, cells treated with 

alkaloids found in tobacco smoke, including nicotine, 

showed a dose-dependent inhibition of progesterone 

production, whereas estradiol production showed little 

effect or was slightly stimulated (Bódis et al. 1997; Gocze 

et al. 1999; Gocze and Freeman 2000; Miceli et al. 2005). 

Other scientists concluded that nicotine affects the menstrual cycle by inhibiting progesterone release just after 

ovulation. In animal models, nicotine acts on the HPG 
Reproductive and Developmental Effects 609

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

axis, which is involved in normal sexual development and 

control of reproductive function (Matta et al. 1998). Studies show that prenatal exposure to nicotine is related to 

decreased testosterone levels in adult male rats and that 

cotinine, but not nicotine, inhibits testosterone synthesis 

in testes of neonatal rats (Sarasin et al. 2003). 

Spermatogenesis is also affected by the hormonal 

milieu. Recent studies have provided more evidence that 

tobacco smoke exposure is associated with reduced sperm 

quality, which, in turn, may be a mechanism leading to 

reduced fertility in couples. Smoking-associated DNA 

damage in sperm could also be related to birth defects in 

offspring or producing nonviable gametes, resulting in 

apparent infertility or early fetal loss.

Many epidemiologic studies have related maternal smoking to reproductive problems that can originate in the oviduct (e.g., fallopian tube) (Stillman et al. 

1986; Buck et al. 1997), including infertility and ectopic 

pregnancy. Studies have shown that exposure to tobacco 

smoke diminishes oviductal functioning. Exposure to 

cigarette smoke and its components has been shown to 

alter contraction in human and rabbit oviducts (Neri and 

Eckerling 1969; Ruckebusch 1975) and to form blebs on 

the oviductal epithelium in hamsters (Magers et al. 1995). 

In other studies of hamster oviducts, effects included 

decreased smooth muscle contractions and changed the 

ratio of ciliated to secretory cells, both of which would 

affect transit time of the egg through the oviduct (Huang 

et al. 1997; Knoll and Talbot 1998; DiCarlantonio and 

Talbot 1999; Riveles et al. 2003). Adhesion between the 

extracellular matrix of the oocyte cumulus complex and 

the tips of the cilia is essential for pickup of the oocyte and 

transport through the oviduct (Talbot et al. 1999; Lam et 

al. 2000). Exposure to both mainstream and sidestream 

smoke increases adhesion, which could account for 

decreased pickup rates even when cilia beat at normal or 

accelerated rates. 

Ectopic pregnancy occurs when a fertilized egg is 

implanted outside the uterus, usually in the fallopian 

tube; it is estimated to occur in 1 to 2 percent of pregnancies. This condition accounts for approximately 6 percent 

of pregnancy-related deaths in the United States (Chow et 

al. 1987; Goldner et al. 1993; Berg et al. 2003; Chang et 

al. 2003; Van Den Eeden et al. 2005). Affected women are 

at increased risk of subsequent infertility and recurrent 

ectopic pregnancy, as would be expected among women 

with tubal damage (Chow et al. 1987; Coste et al. 1991; 

Washington and Katz 1993; Skjeldestad et al. 1998). 

The 2004 Surgeon General’s report found the evidence 

suggestive but not sufficient to infer a causal relationship between smoking and ectopic pregnancy (USDHHS 

2004) on the basis of a number of studies with significant 

associations between smoking and increased risk of 

ectopic pregnancy, yielding a pooled OR of 1.8 or an 

80-percent increase with smoking (Castles et al. 1999). 

Two subsequent methodologically strong studies also 

indicate an increased risk with dose-response effects, further strengthening the evidence.

Studies have found evidence of a dose-response 

relationship even after adjustment for important potential confounders such as a history of sexually transmitted 

diseases and infertility (Bouyer et al. 2003; Karaer et al. 

2006). In addition, plausible mechanisms for a relationship between smoking and ectopic pregnancy exist. As 

noted, the oviduct plays a critical role in the pickup and 

transport of the oocyte, and failure of this function can 

result in ectopic pregnancy (Talbot and Riveles 2005). 

Spontaneous abortion, the involuntary termination 

of an intrauterine pregnancy before 20 weeks of gestation, 

has been reported in approximately 12 percent of recognized pregnancies; the majority occur before 12 weeks of 

gestation. Including very early pregnancy loss that may 

be unreported suggests an estimated 30 to 45 percent of 

conceptions actually end in pregnancy loss, some before 

implantation (Wilcox et al. 1988; Eskenazi et al. 1995). In 

addition to fetal abnormalities, other factors that likely 

contribute to SAB include maternal anatomic abnormalities of the uterus, immunologic disturbances, thrombotic 

disorders, and endocrine abnormalities (Christianson 

1979; Cramer and Wise 2000; Regan and Rai 2000), some 

of which are affected by tobacco smoke. The 2004 Surgeon General’s report (USDHHS 2004) found the evidence 

suggestive but not sufficient to infer a causal relationship 

between tobacco and SAB. Additional studies have shown 

positive associations, including two with measurement 

of cotinine (Ness et al. 1999; George et al. 2006) and two 

showing associations with secondhand smoke (Venners et 

al. 2004; George et al. 2006). Proposed mechanisms for 

an effect from tobacco smoke include vasoconstrictive and 

antimetabolic effects resulting in placental insufficiency 

and the subsequent demise of the embryo or fetus, fetal 

hypoxia from CO exposure, and direct toxic effects of cigarette smoke constituents. 

Preeclampsia, marked by proteinuria, hypertension, 

and dysfunction of the cells lining the uterus, is a leading 

cause of pregnancy-related mortality in the United States 

(Berg et al. 2003). The 2004 Surgeon General’s report 

found the evidence sufficient to infer a causal relationship between smoking and a reduced risk of preeclampsia 

(USDHHS 2004). Smoking has been proposed to reduce 

the risk of preeclampsia by effects of exposure to thiocyanate, which has a hypotensive effect (Andrews 1973), by 

changing the thromboxane A2 to prostacyclin ratio, which 

would alter the way blood vessels constrict and dilate 

(Ylikorkala et al. 1985; Davis et al. 1987; Marcoux et al. 

1989; Lindqvist and Maršál 1999), or by stimulating the 
Surgeon General’s Report

610 Chapter 8

growth of new blood vessels in the placenta (Maynard et 

al. 2003; Fisher 2004; Jeyabalan et al. 2008). 

Numerous studies have demonstrated the immediate effect of smoking one or two cigarettes on maternal heart rate and blood pressure (Lindblad et al. 1988; 

Morrow et al. 1988; Castro et al. 1993; Kimya et al. 1998; 

Ates et al. 2004). The clinical significance of a transiently 

elevated maternal heart rate on pregnancy is unknown. 

Studies that examined the acute effects of smoking after 

abstinence reported a transient increase in diastolic blood 

pressure and, to a lesser extent, systolic blood pressure. 

The release of catecholamine may trigger the elevations 

in maternal heart rate and blood pressure reported in 

these studies. However, smoking was also associated with 

an acute rise in plasma levels of norepinephrine, epinephrine, and dopamine, which could mediate the rise in 

maternal heart rate and blood pressure (Quigley et al. 

1979). The literature indicates a transient increase in 

fetal heart rate with acute maternal smoking that was 

not statistically significant, although fetal heart rate variability, used to assess fetal well-being, was significantly 

transiently decreased (Graca et al. 1991; Ates et al. 2004). 

The clinical significance of these transient changes is not 

known. Studies on uterine and placental blood flow did 

not indicate basal differences between smokers and nonsmokers and results were inconsistent with respect to 

acute changes from smoking, so this mechanism is not 

supported as a possible cause of the well-documented fetal 

growth retardation among smokers.

Maintenance of pregnancy and fetal growth and 

development are dependent on normal formation of the 

placenta for exchange of nutrients and metabolic products between the mother and fetus. Studies have consistently shown that maternal smoking is associated with a 

thickening of the villous membrane of the placenta, which 

would decrease the ability of nutrients to pass through the 

placenta by diffusion (Burton et al. 1989; Jauniaux and 

Burton 1992; Demir et al. 1994; Bush et al. 2000; Larsen 

et al. 2002). The thickening of the villous membrane could 

contribute to fetal growth restriction. Researchers have 

hypothesized that toxic effects of maternal smoking on 

the placenta are responsible for the thickening of the villous membrane, perhaps caused by the accumulation of 

cadmium that is associated with a reduction in fetal capillary volume (Burton et al. 1989; Bush et al. 2000). Smoking appears to interfere with transformation of uterine 

spiral arteries, which is critical for the formation of the 

high-capacitance system that allows increased blood flow 

from the mother to the fetus. Such interference could 

lead to increased risk of adverse pregnancy outcomes such 

as miscarriage.

Epidemiologic studies have consistently found 

an increased risk of partial obstruction of the cervix by 

the placenta (placenta previa) among maternal smokers, 

which may lead to preterm delivery or maternal or fetal or 

neonatal death (Meyer et al. 1976; Zhang and Fried 1992; 

Monica and Lilja 1995). One mechanism commonly proposed to explain this association is the lower blood levels 

of O2 and reduced blood flow that result from smoking, 

with compensatory placental enlargement. 

Premature separation of the placenta from the 

uterus (placental abruption) increases the risk of perinatal mortality, and although several factors are involved 

(Misra and Ananth 1999), studies have consistently associated smoking with an increased risk (Raymond and Mills 

1993; Ananth et al. 1999; Castles et al. 1999; Andres and 

Day 2000). The 2004 Surgeon General’s report found the 

evidence sufficient to infer a causal relationship (USDHHS 

2004), and researchers have observed a dose-response 

relationship (Raymond and Mills 1993; Ananth et al. 1999). 

One researcher has hypothesized that smoking-related 

degenerative and/or inflammatory changes in the placenta 

are factors related to abruption (Cnattingius 2004). Other 

hypotheses include low levels of vitamin C in maternal 

smokers (Faruque et al. 1995), leading to impaired collagen synthesis (Cnattingius 2004), microinfarcts, and 

accumulation of fatty deposits in placental vessels (Naeye 

1979; Andres and Day 2000).

The 2004 Surgeon General’s report found that 

the evidence was sufficient to infer a causal relationship 

between smoking and preterm delivery, a leading cause of 

neonatal morbidity and mortality in developed countries 

(USDHHS 2004). Smoking appears to increase the risk of 

both medically indicated and spontaneous preterm delivery (Kyrklund-Blomberg and Cnattingius 1998). Mechanisms through which smoking may contribute to preterm 

delivery include placental abruption or effects on the 

integrity of collagen, leading to a weakening and rupture 

of the membranes and increased risk of infections.

The same Surgeon General’s report found sufficient 

evidence to infer a causal relationship between smoking 

and preterm premature rupture of membranes (PPROM) 

(USDHHS 2004). Researchers have hypothesized that 

smoking increases the risk of PPROM through several 

pathways. The effects of smoking on the immune system 

could increase the risk of genital tract infection or disrupt 

the cytokine system (French and McGregor 1996). Smoking could also increase the inflammatory response and 

reduce the availability of nutrients such as vitamin C or 

decrease the uptake of nutrients by the placenta (French 

and McGregor 1996; Lykkesfeldt et al. 1996, 2000), which 

would affect collagen content and membrane structure.

Maternal smoking has also been investigated for an 

association with birth defects, and although the 2004 Surgeon General’s report (USDHHS 2004) found inadequate 

evidence for birth defects in general, maternal smoking 
Reproductive and Developmental Effects 611

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

was considered suggestive for oral clefts. Evidence accumulated since the studies in that report is even stronger 

in supporting an association with smoking and cleft lip 

and/or palate (Little et al. 2004a), with some dose-response 

effects noted (Little et al. 2004b). Animal studies support these findings with evidence that nicotine can alter 

embryonic movements that are important during embryogenesis for the differentiation and maturation of organ 

systems, including palate closure (Panter et al. 2000; Ejaz 

et al. 2005). Other possible mechanisms include smokinginduced reductions in supply of essential nutrients for 

embryonic tissues, such as multivitamins and folate, fetal 

hypoxia from CO, or DNA damage from PAHs.

Deficiencies of micronutrients may contribute to 

adverse pregnancy outcomes, and smoking may contribute to this relationship. Vitamin C is required for collagen formation in amnion epithelial cells, and studies have 

noted reduced vitamin C levels in women with PPROM 

(Wideman et al. 1964; Casanueva et al. 1993). A decrease 

in the amount of collagen III likely leads to a weakening 

of the tensile strength of amniotic membranes, which 

could increase the risk of PPROM. Studies consistently 

show that smokers consume less and metabolize more 

vitamin C than do nonsmokers and thus have lower levels 

of vitamin C in plasma (Preston 1991; Lykkesfeldt et al. 

2000; Cogswell et al. 2003) and in amniotic fluid (Barrett 

et al. 1991). Vitamin C is important for normal immune 

functioning, and a vitamin C deficiency in maternal smokers could contribute to adverse pregnancy outcomes by 

impairing maternal immune responses to genital tract 

infections. Because the placenta is impermeable to most 

proteins, proteins are usually synthesized by the fetus 

from amino acids supplied by the mother. Abnormalities 

in amino acid transport across the placenta can contribute to impaired fetal growth. Compared with nonsmokers, 

smokers have reduced levels of several amino acids in fetal 

plasma, umbilical plasma, and placental villi (Jauniaux et 

al. 1999, 2001).

CO forms as a by-product of combustion and is the 

toxin found in the highest concentration in cigarette 

smoke—10 to 20 times the dose of nicotine (Hoffman et 

al. 1997). The toxic effects of CO result predominantly 

from its binding to hemoglobin (Longo 1976, 1977), 

which is more than 200 times that of O2 to hemoglobin 

(Hsia 1998). Fetal hemoglobin binds CO more tightly than 

does adult hemoglobin, so the fetus of a smoking mother 

has much higher levels of carboxyhemoglobin than those 

of the mother. The fetus experiences chronic hypoxia of 

fetal tissue, which persists for five or six hours of maternal 

smoking abstinence, such as during sleeping (Cole et al. 

1972; Longo 1977; Bureau et al. 1982). CO from cigarette 

smoke deprives the fetus of O2, which is essential for the 

aerobic metabolism that produces ATP, a coenzyme that 

stores the energy to fuel cellular activity throughout the 

body. Chronic mild O2 deprivation in the fetus is likely a 

major underlying mechanism of smoking-associated fetal 

growth retardation, one of the most consistent and earliest 

identified adverse effects in infants of maternal smokers 

(Longo 1976, 1977; USDHHS 1980, 2004). Furthermore, 

infants of maternal smokers showed a decrease in birth 

weight nearly five times lower than that in infants of snuff 

users, even after adjustment for variables, implicating 

CO as the likely hazard (Longo 1976, 1977; England et 

al. 2003). Reduced fetal growth is associated with adverse 

effects on other endpoints, including perinatal mortality, 

birth defects, and neurodevelopment, which may also be 

directly affected by CO exposure.

Other components of tobacco smoke, including nicotine (see Chapter 3, “Chemistry and Toxicology 

of Cigarette Smoke and Biomarkers of Exposure and 

Harm”); heavy metals such as cadmium, lead, and mercury; and PAHs have been found to be causally associated 

with several adverse reproductive outcomes described 

here. Furthermore, levels of these components are found 

to be higher in smokers than in nonsmokers. It is more 

difficult to determine whether the levels generated from 

tobacco smoke are sufficient to cause these outcomes, but 

the evidence is suggestive for several of the components. 

The metabolism of these toxic constituents likely varies 

by genetic polymorphisms that reflect differential induction of drug- or toxin-metabolizing enzymes, such as 

cytochrome P-450s and GSTs, which, in turn, may 

modify the relationship between maternal smoking and 

birth outcomes, such as LBW or congenital anomalies. 

Genetic polymorphisms coding for the expression of tissue 

damage, inflammatory response, and immune mediator 

enzymes have been examined for interaction with maternal smoking in several studies of oral facial clefts, with 

TGFα and TGFß3 alleles most often implicated.
Surgeon General’s Report

612 Chapter 8

Conclusions

1. There is consistent evidence that links smoking in 

men to chromosome changes or DNA damage in 

sperm (germ cells), affecting male fertility, pregnancy 

viability, and anomalies in offspring.

2. There is consistent evidence for association of periconceptional smoking to cleft lip with or without 

cleft palate. 

3. There is consistent evidence that increases in folliclestimulating hormone levels and decreases in estrogen 

and progesterone are associated with cigarette smoking in women, at least in part due to effects of nicotine 

on the endocrine system. 

4. There is consistent evidence that maternal smoking 

leads to transient increases in maternal heart rate and 

blood pressure (primarily diastolic), probably mediated by the release of norepinephrine and epinephrine 

into the circulatory system.

5. There is consistent evidence that links maternal 

smoking to interference in the physiological transformation of spiral arteries and thickening of the villous 

membrane in forming the placenta; placental problems could lead to fetal loss, preterm delivery, or low 

birth weight.

6. There is consistent evidence of the presence of histopathologic changes in the fetus from maternal smoking, particularly in the lung and brain.

7. There is consistent evidence that suggests smoking 

leads to immunosuppressive effects, including dysregulation of the inflammatory response, that may 

lead to miscarriage and preterm delivery. 

8. There is consistent evidence that suggests a role 

for polycyclic aromatic hydrocarbons from tobacco 

smoke in the adverse effects of maternal smoking on a 

variety of reproductive and developmental endpoints.

9. There is consistent evidence that tobacco smoke 

exposure leads to diminished oviductal functioning, 

which could impair fertilization. 

10. There is consistent evidence that links prenatal smoke 

exposure and genetic variations in metabolizing 

enzymes such as GSTT1 with increased risk of adverse 

pregnancy outcomes such as lowered birth weight 

and reduced gestation.

11. There is consistent evidence that genetic polymorphisms, such as variants in transforming growth factor-alpha, modify the risks of oral clefting in offspring 

related to maternal smoking.

12. There is consistent evidence that carbon monoxide 

leads to birth weight deficits and may play a role in 

neurologic deficits (cognitive and neurobehavioral 

endpoints) in the offspring of smokers.
Reproductive and Developmental Effects 613

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

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Table 8.2 Association between maternal smoking and spontaneous abortion (SAB), 1998–2006

Study Design/population Definition of smoking OR (95% CI) Comments

Chatenoud et 

al. 1998

Case-control study

782 cases of SAB by 12 weeks’ 

gestation, confirmed pathologic 

examination

1,543 women who delivered term 

healthy infants in same hospitals as 

cases

Italy

Lifetime nonsmokers 

vs. women who smoked 

during pregnancy

None, 1–4, 5–9, ≥10 

cigarettes/day

Any smoking 1.3 (1.0–1.6) 

No association with 

smoking before 

pregnancy or with 

paternal smoking; 

adjustment for center, 

age, marital status, 

history of SAB, 

nausea, and use of 

alcohol and coffee

Chatenoud et 

al. 1998

Case-control study

782 cases of SAB by 12 weeks’ 

gestation, confirmed pathologic 

examination

1,543 women who delivered term 

healthy infants in same hospitals as 

cases

Italy

Lifetime nonsmokers 

vs. women who smoked 

during pregnancy

None, 1–4, 5–9, ≥10 

cigarettes/day

≥10 cigarettes/day 1.4 (1.0–2.1)

No association with 

smoking before 

pregnancy or with 

paternal smoking; 

adjustment for center, 

age, marital status, 

history of SAB, 

nausea, and use of 

alcohol and coffee

Ness et al. 

1999

Case-control study

400 adolescents or women with SAB 

<22 weeks’ gestation at initial visit or 

during follow-up

570 adolescents or women with 

pregnancies beyond 22 weeks’ 

gestation seeking care at inner-city 

emergency room

Low SES population

Pennsylvania

Urinary cotinine 

>500 ng/mL used to 

identify heavy smokers

1.8 (1.3–2.6)

Adjustment for use of 

cocaine, marijuana, 

and alcohol, and living 

with partner, weeks of 

gestation at interview, 

and prenatal care; 

stronger among SABs 

during follow-up 

(OR 2.4)

Ness et al. 

1999

Case-control study

400 adolescents or women with SAB 

<22 weeks’ gestation at initial visit or 

during follow-up

570 adolescents or women with 

pregnancies beyond 22 weeks’ 

gestation seeking care at inner-city 

emergency room

Low SES population

Pennsylvania

Urinary cotinine

Self-reported smoking 

during pregnancy

1.4 (1.0–1.9) 

Crude data

Adjustment for use of 

cocaine, marijuana, 

and alcohol, and living 

with partner, weeks of 

gestation at interview, 

and prenatal care; 

stronger among SABs 

during follow-up 

(OR 2.4)
Table 8.2 Continued

Study Design/population Definition of smoking OR (95% CI) Comments

Windham et 

al. 1999c

Prospective study of women seeking 

prenatal care at large health 

maintenance organization (Kaiser) by 

12 weeks’ gestation

499 SABs by 20 weeks’ gestation, from 

medical records

5,144 pregnancies after excluding 

therapeutic abortions

California

Smoking at 8 weeks of 

gestation and amount 

vs. nonsmoking

≥5 cigarettes/day 1.3 (0.9–1.9)

Adjustment for age, 

previous fetal loss, 

gestational age at 

interview, use of 

alcohol and caffeine; 

effect modification 

with high use of 

caffeine or alcohol 

(>3 drinks/week)

Windham et 

al. 1999c

Prospective study of women seeking 

prenatal care at large health 

maintenance organization (Kaiser) by 

12 weeks’ gestation

499 SABs by 20 weeks’ gestation, from 

medical records

5,144 pregnancies after excluding 

therapeutic abortions

California

Smoking at 8 weeks of 

gestation and amount 

vs. nonsmoking

Spouse smoking status No association

Adjustment for age, 

previous fetal loss, 

gestational age at 

interview, use of 

alcohol and caffeine; 

effect modification 

with high use of 

caffeine or alcohol 

(>3 drinks/week)

Windham et 

al. 1999c

Prospective study of women seeking 

prenatal care at large health 

maintenance organization (Kaiser) by 

12 weeks’ gestation

499 SABs by 20 weeks’ gestation, from 

medical records

5,144 pregnancies after excluding 

therapeutic abortions

California

Smoking at 8 weeks of 

gestation and amount 

vs. nonsmoking

Hours of exposure to 

SHS at home and work 

for nonsmokers

No association, 

unless 

consumption 

of caffeine or 

alcohol OR ~3 

for any exposure 

to SHS

Adjustment for age, 

previous fetal loss, 

gestational age at 

interview, use of 

alcohol and caffeine; 

effect modification 

with high use of 

caffeine or alcohol 

(>3 drinks/week)
Table 8.2 Continued

Study Design/population Definition of smoking OR (95% CI) Comments

Mishra et al. 

2000

Prospective study

14,779 women (aged 18–23 years), 

from baseline survey

Self-reported SABs (≥1)

Australia

Lifetime nonsmokers 

vs. current and former 

smokers 

Amount (cigarettes/day)

 Former smokers 1.6 (1.3–2.2)

Adjustment for parity, 

therapeutic abortion, 

age, education, 

marital status, and 

area of residence; 

higher risk for 

smoking initiation at 

younger age

Mishra et al. 

2000

Prospective study

14,779 women (aged 18–23 years), 

from baseline survey

Self-reported SABs (≥1)

Australia

Lifetime nonsmokers 

vs. current and former 

smokers 

Amount (cigarettes/day)

 Current smokers

 1–9 1.7 (1.1–2.5)

Adjustment for parity, 

therapeutic abortion, 

age, education, 

marital status, and 

area of residence; 

higher risk for 

smoking initiation at 

younger age

Mishra et al. 

2000

Prospective study

14,779 women (aged 18–23 years), 

from baseline survey

Self-reported SABs (≥1)

Australia

Lifetime nonsmokers 

vs. current and former 

smokers 

Amount (cigarettes/day)

 Current smokers

 10–19

1.6 (1.6–2.3)

Adjustment for parity, 

therapeutic abortion, 

age, education, 

marital status, and 

area of residence; 

higher risk for 

smoking initiation at 

younger age

Mishra et al. 

2000

Prospective study

14,779 women (aged 18–23 years), 

from baseline survey

Self-reported SABs (≥1)

Australia

Lifetime nonsmokers 

vs. current and former 

smokers 

Amount (cigarettes/day)

 Current smokers

 ≥20

2.0 (1.5–2.8)

Adjustment for parity, 

therapeutic abortion, 

age, education, 

marital status, and 

area of residence; 

higher risk for 

smoking initiation at 

younger age
Table 8.2 Continued

Study Design/population Definition of smoking OR (95% CI) Comments

Rasch 2003 Case-control study

330 women with SAB ascertained by 

evacuation procedure at hospital, 6–16 

weeks’ gestation

1,168 pregnant women receiving 

prenatal care in weeks 6–16

Denmark

Smoking during 

pregnancy and amount 

vs. none

≥20 cigarettes/day vs. 

none

0.95 (0.4–2.2) 

Adjusted data

2.2 (1.1–4.8) 

Crude data

Large effect of 

adjustment for age, 

parity, occupation, 

and use of alcohol 

and caffeine; doseresponse relationship 

before adjustment; 

40% of original 

eligible subjects not 

included in study

Rasch 2003 Case-control study

330 women with SAB ascertained by 

evacuation procedure at hospital, 6–16 

weeks’ gestation

1,168 pregnant women receiving 

prenatal care in weeks 6–16

Denmark

Smoking during 

pregnancy and amount 

vs. none

≥20 cigarettes/day vs. 

none

0.95 (0.4–2.2) 

Adjusted data

2.2 (1.1–4.8) 

Crude data

Large effect of 

adjustment for age, 

parity, occupation, 

and use of alcohol 

and caffeine; doseresponse relationship 

before adjustment; 

40% of original 

eligible subjects not 

included in study

Wisborg et al. 

2003

Prospective study among women 

seeking prenatal care

24,608 pregnant women who 

completed questionnaire by 28 weeks’ 

gestation

321 SABs by 28 weeks (104 first 

trimester, 217 second trimester) from 

Danish patient registry

Denmark

Smoking before or 

during pregnancy 

(and amount) vs. 

nonsmokers

≥10 cigarettes/day 

during pregnancy for 

second trimester SABs

0.88 (0.59–1.31) 

Crude estimates; 

adjustment made 

no difference; very 

low SAB rate (~1%), 

especially with 

extended definition 

(28 weeks); median 

entry time was second 

trimester, so most 

earlier SABs were 

missed

Wisborg et al. 

2003

Prospective study among women 

seeking prenatal care

24,608 pregnant women who 

completed questionnaire by 28 weeks’ 

gestation

321 SABs by 28 weeks (104 first 

trimester, 217 second trimester) from 

Danish patient registry

Denmark

Smoking before or 

during pregnancy 

(and amount) vs. 

nonsmokers

First trimester 0.92 (0.55–1.54)

Crude estimates; 

adjustment made 

no difference; very 

low SAB rate (~1%), 

especially with 

extended definition 

(28 weeks); median 

entry time was second 

trimester, so most 

earlier SABs were 

missed
Table 8.2 Continued

Study Design/population Definition of smoking OR (95% CI) Comments

George et al. 

2006

Case-control population-based study

463 women with SAB at 6–12 weeks’ 

gestation, interviewed after SAB (most 

within 2 weeks)

864 pregnant women with viable 

pregnancy, matched to cases by 

gestational week

Sweden

Plasma cotinine

>15.0 ng/mL = active 

smoking

2.1 (1.4–3.3)

Adjustment for age, 

country of birth, 

education, marital 

status, shift work, 

parity, previous SAB, 

caffeine intake, folate 

level, change of eating 

habits, pregnancy 

symptoms; SHS 

exposed may include 

light smokers

George et al. 

2006

Case-control population-based study

463 women with SAB at 6–12 weeks’ 

gestation, interviewed after SAB (most 

within 2 weeks)

864 pregnant women with viable 

pregnancy, matched to cases by 

gestational week

Sweden

Plasma cotinine

0.1–15.0 ng/mL for 

exposure to SHS vs. 

<0.1 ng/mL

1.7 (1.2–2.4)

Adjustment for age, 

country of birth, 

education, marital 

status, shift work, 

parity, previous SAB, 

caffeine intake, folate 

level, change of eating 

habits, pregnancy 

symptoms; SHS 

exposed may include 

light smokers

George et al. 

2006

Case-control population-based study

463 women with SAB at 6–12 weeks’ 

gestation, interviewed after SAB (most 

within 2 weeks)

864 pregnant women with viable 

pregnancy, matched to cases by 

gestational week

Sweden

Plasma cotinine

No exposure to 

cigarette smoke

   Adjustment for age, 

country of birth, 

education, marital 

status, shift work, 

parity, previous SAB, 

caffeine intake, folate 

level, change of eating 

habits, pregnancy 

symptoms; SHS 

exposed may include 

light smokers
Table 8.2 Continued

Study Design/population Definition of smoking OR (95% CI) Comments

Nielsen et al. 

2006

Nested case-control study from 

population-based cohort of 11,088 

women with baseline survey and 

2-year follow-up

343 SAB or fetal loss by 28 weeks’ 

gestation, self-reported or in Danish 

registry

1,578 women with pregnancy of >28 

weeks during follow-up period

Denmark

Smoking at baseline, 

before pregnancy, by 

amount and number of 

years of smoking

1.0 (current 

smokers vs. 

never smoked)

Adjustment for 

age, marital status, 

previous SAB, oral 

contraceptive use, 

IUD use, and smoking 

status and duration 

of smoking—but 

did not affect ORs; 

no association for 

former smokers or by 

duration of smoking; 

odd reference group

Nielsen et al. 

2006

Nested case-control study from 

population-based cohort of 11,088 

women with baseline survey and 

2-year follow-up

343 SAB or fetal loss by 28 weeks’ 

gestation, self-reported or in Danish 

registry

1,578 women with pregnancy of >28 

weeks during follow-up period

Denmark

Amount (cigarettes/day)

 1–14 Reference group

Adjustment for 

age, marital status, 

previous SAB, oral 

contraceptive use, 

IUD use, and smoking 

status and duration 

of smoking—but 

did not affect ORs; 

no association for 

former smokers or by 

duration of smoking; 

odd reference group

Nielsen et al. 

2006

Nested case-control study from 

population-based cohort of 11,088 

women with baseline survey and 

2-year follow-up

343 SAB or fetal loss by 28 weeks’ 

gestation, self-reported or in Danish 

registry

1,578 women with pregnancy of >28 

weeks during follow-up period

Denmark

Amount (cigarettes/day)

 15–19 1.4 (0.9–2.1)

Adjustment for 

age, marital status, 

previous SAB, oral 

contraceptive use, 

IUD use, and smoking 

status and duration 

of smoking—but 

did not affect ORs; 

no association for 

former smokers or by 

duration of smoking; 

odd reference group
Table 8.2 Continued

Study Design/population Definition of smoking OR (95% CI) Comments

Nielsen et al. 

2006

Nested case-control study from 

population-based cohort of 11,088 

women with baseline survey and 

2-year follow-up

343 SAB or fetal loss by 28 weeks’ 

gestation, self-reported or in Danish 

registry

1,578 women with pregnancy of >28 

weeks during follow-up period

Denmark

Amount (cigarettes/day)

 ≥20 1.6 (1.1–2.5)

Adjustment for 

age, marital status, 

previous SAB, oral 

contraceptive use, 

IUD use, and smoking 

status and duration 

of smoking—but 

did not affect ORs; 

no association for 

former smokers or by 

duration of smoking; 

odd reference group

Nielsen et al. 

2006

Nested case-control study from 

population-based cohort of 11,088 

women with baseline survey and 

2-year follow-up

343 SAB or fetal loss by 28 weeks’ 

gestation, self-reported or in Danish 

registry

1,578 women with pregnancy of >28 

weeks during follow-up period

Denmark

Amount (cigarettes/day)

 Each additional 5 1.2 (1.0–1.4)

Adjustment for 

age, marital status, 

previous SAB, oral 

contraceptive use, 

IUD use, and smoking 

status and duration 

of smoking—but 

did not affect ORs; 

no association for 

former smokers or by 

duration of smoking; 

odd reference group

Note: CI = confidence interval; IUD = intrauterine device; ng/mL = nanograms per milliliter; OR = odds ratio; SES = socioeconomic 

status; SHS = secondhand smoke.
Table 8.3 Association between maternal smoking and orofacial clefts (OFCs), 1999–2009a

Study Design/population

Definition of smoking(smoking rate in controls) Findings OR (95% 

van Rooij et al. 2001

Case-control study113 infants with nonsyndromic OFCs104 infants with no defects White, aged 9 months–3 yearsThe NetherlandsStudy period not specified

Smokers (20.2%) vs. nonsmokers

•	 Maternal smoking not associated with 

oral clefting

1.1 (0.6–

Shaw et al. 2002 Case-control study

489 infants and fetal deaths with OFCs734 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1989

Smoking in periconceptional period—1 month before to 3 months after 

conception—(24%) vs. none

•	 Association of maternal smoking with 

isolated CL/P among women not using vitaminsVitamins/Smoking

Yes/No 1.0

Shaw et al. 2002 Case-control study

489 infants and fetal deaths with OFCs734 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1989

Smoking in periconceptional period—1 month before to 3 months after conception—(24%) vs. none

•	 Association of maternal smoking with 

isolated CL/P among women not using vitaminsVitamins/Smoking

No/Yes 2.8 (1.8–

Shaw et al. 2002 Case-control study

489 infants and fetal deaths with OFCs734 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1989

Smoking in periconceptional period—1 month before to 3 months after conception—(24%) vs. none

•	 Association of maternal smoking with 

isolated CL/P among women not using vitaminsVitamins/Smoking

No/No 1.9 (1.3–

Shaw et al. 2002 Case-control study

489 infants and fetal deaths with OFCs734 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1989

Smoking in periconceptional period—1 month before to 3 months after conception—(24%) vs. none

•	 Association of maternal smoking with 

isolated CL/P among women not using vitaminsVitamins/Smoking

Yes/Yes 1.5 (1.0–
Table 8.3 Continued

Study Design/population

Definition of smoking(smoking rate in controls) Findings OR (95% C

Shaw et al. 2002 Case-control study

489 infants and fetal deaths with OFCs734 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1989

Smoking in periconceptional period—1 month before to 3 months after 

conception—(24%) vs. none

•	 Relationship marginally significant for 

isolated CP

 Vitamins/Smoking

Yes/No 1.0

Shaw et al. 2002 Case-control study

489 infants and fetal deaths with OFCs734 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1989

Smoking in periconceptional period—1 month before to 3 months after 

conception—(24%) vs. none

•	 Relationship marginally significant for 

isolated CP

 Vitamins/Smoking

No/Yes 2.0 (1.0–3.9

Shaw et al. 2002 Case-control study

489 infants and fetal deaths with OFCs734 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1989

Smoking in periconceptional period—1 month before to 3 months after 

conception—(24%) vs. none

•	 Relationship marginally significant for 

isolated CP

 Vitamins/Smoking

No/No 1.6 (1.0–2.6

Shaw et al. 2002 Case-control study

489 infants and fetal deaths with OFCs734 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1989

Smoking in periconceptional period—1 month before to 3 months after 

conception—(24%) vs. none

•	 Relationship marginally significant for 

isolated CP

 Vitamins/Smoking

Yes/Yes 1.7 (1.0–2.9

van Rooij et al. 2002

Case-control study45 mothers of children with OFCs39 mothers of children with spina bifida75 control mothersDNA for possible effect modificationThe Netherlands1997–1999

Smokers (18.1%) vs. nonsmokersSmoking in periconceptional periodNumber of cigarettes/day

•	 Association with OFCs •	 No association between maternal NAT2 

acetylator status and OFCs

•	 No interaction between NAT2 

acetylator status and maternal smoking 

2.0 (0.8–5.0
Table 8.3 Continued

Study Design/population

Definition of smoking(smoking rate in controls) Findings OR (95% 

Wyszynski and Wu 2002

Case-control study2,029 births with nonsyndromic oral clefts4,050 control infants with no malformation, matched on maternal and paternal race and child’s gender, county of birth, and month of birthUnited States Natality database 1997

Smoking

Any (16.9%) vs. none

•	 Maternal smoking associated with CL/P 

in infants Any vs. none 1.16 (1.0

Trend tes

Wyszynski and Wu 2002

Case-control study2,029 births with nonsyndromic oral clefts4,050 control infants with no malformation, matched on maternal and paternal race and child’s gender, county of birth, and month of birthUnited States Natality database 1997

Number of cigarettes/day

1–10 (10.8%)

•	 Number of cigarettes/day vs. none

1–10 1.10 (0.9

Trend tes

Wyszynski and Wu 2002

Case-control study2,029 births with nonsyndromic oral clefts4,050 control infants with no malformation, matched on maternal and paternal race and child’s gender, county of birth, and month of birthUnited States Natality database 1997

Number of cigarettes/day

11–20 (4.9%)

•	 Number of cigarettes/day vs. none

11–20 1.11 (0.8

Trend tes
Table 8.3 Continued

Study Design/population

Definition of smoking(smoking rate in controls) Findings OR (95% 

Wyszynski and Wu 2002

Case-control study2,029 births with nonsyndromic oral clefts4,050 control infants with no malformation, matched on maternal and paternal race and child’s gender, county of birth, and month of birthUnited States Natality database 1997

Number of cigarettes/day

>20 (1.1%)

•	 Number of cigarettes/day vs. none

>20 1.55 (0.8

Trend tes

Jugessur et al. 2003

Case-parent triad study261 case-parent triads (88 CPO and 173 CL/P) Norway1996–1998

Smoking in last year or during first trimester 

Before pregnancy (31%) First trimester (27%)

•	 Risk for smoking alone not stated•	 No interaction between maternal 

smoking and TGFa gene TAQ1 *A2/*A2 genotype in infant 

Little et al. 2004a Meta-analysis of data from 24 case-control 

and cohort studies 9 studies addressed only OFCs15 studies assessed CL/P and CP separatelyStudies published between 1974 and 2001

Smokers vs. nonsmokers varied by study 

•	 Consistent, moderate, and statistically 

significant associations between maternal smoking and CL/P

1.34 (1.2

Little et al. 2004a Meta-analysis of data from 24 case-control 

and cohort studies 9 studies addressed only OFCs15 studies assessed CL/P and CP separatelyStudies published between 1974 and 2001

Smokers vs. nonsmokers varied by study 

•	 Evidence of a dose-response

relationship between maternal smoking and CP

1.22 (1.1
Table 8.3 Continued

Study Design/population

Definition of smoking(smoking rate in controls) Findings OR (95% 

Little et al. 2004b Case-control study

190 children with OFCs248 children with no malformationScotland and Manchester and Merseyside regions of England1997–2000

Number of cigarettes/dayActive smoking and involuntary exposure to cigarette smokeMaternal smoking

Ever (37.5%)During pregnancy (24.2%)First trimester (23.8%)

Exposure to cigarette smoke among mothers who did not smoke (28.2%)Exposure to cigarette smoke among mothers who smoked (31.0%)

•	 First trimester smoking associated

with CL/P

Any vs. none 1.9 (1.1–

Little et al. 2004b Case-control study

190 children with OFCs248 children with no malformationScotland and Manchester and Merseyside regions of England1997–2000

Number of cigarettes/dayActive smoking and involuntary exposure to cigarette smokeMaternal smoking

Ever (37.5%)During pregnancy (24.2%)First trimester (23.8%)

Exposure to cigarette smoke among mothers who did not smoke (28.2%)Exposure to cigarette smoke among mothers who smoked (31.0%)

•	 First trimester smoking associated

with CL/P

≤10 cigarettes/day 1.7 (0.9–
Table 8.3 Continued

Study Design/population

Definition of smoking(smoking rate in controls) Findings OR (95% 

Little et al. 2004b Case-control study

190 children with OFCs248 children with no malformationScotland and Manchester and Merseyside regions of England1997–2000

Number of cigarettes/dayActive smoking and involuntary exposure to cigarette smokeMaternal smoking

Ever (37.5%)During pregnancy (24.2%)First trimester (23.8%)

Exposure to cigarette smoke among mothers who did not smoke (28.2%)Exposure to cigarette smoke among mothers who smoked (31.0%)

•	 First trimester smoking associated

with CL/P

>10 cigarettes/day 2.5 (1.1–

Little et al. 2004b Case-control study

190 children with OFCs248 children with no malformationScotland and Manchester and Merseyside regions of England1997–2000

Number of cigarettes/dayActive smoking and involuntary exposure to cigarette smokeMaternal smoking

Ever (37.5%)During pregnancy (24.2%)First trimester (23.8%)

Exposure to cigarette smoke among mothers who did not smoke (28.2%)Exposure to cigarette smoke among mothers who smoked (31.0%)

•	 First trimester smoking associated

with CP

Any vs. none 2.5 (1.3–
Table 8.3 Continued

Study Design/population

Definition of smoking(smoking rate in controls) Findings OR (95% 

Little et al. 2004b Case-control study

190 children with OFCs248 children with no malformationScotland and Manchester and Merseyside regions of England1997–2000

Number of cigarettes/dayActive smoking and involuntary exposure to cigarette smokeMaternal smoking

Ever (37.5%)During pregnancy (24.2%)First trimester (23.8%)

Exposure to cigarette smoke among mothers who did not smoke (28.2%)Exposure to cigarette smoke among mothers who smoked (31.0%)

•	 First trimester smoking associated

with CP

≤10 cigarettes/day 2.1 (1.1–

Little et al. 2004b Case-control study

190 children with OFCs248 children with no malformationScotland and Manchester and Merseyside regions of England1997–2000

Number of cigarettes/dayActive smoking and involuntary exposure to cigarette smokeMaternal smoking

Ever (37.5%)During pregnancy (24.2%)First trimester (23.8%)

Exposure to cigarette smoke among mothers who did not smoke (28.2%)Exposure to cigarette smoke among mothers who smoked (31.0%)

•	 First trimester smoking associated

with CP

>10 cigarettes/day 3.1 (1.2–
Table 8.3 Continued

Study Design/population

Definition of smoking(smoking rate in controls) Findings OR (95% 

Little et al. 2004b Case-control study

190 children with OFCs248 children with no malformationScotland and Manchester and Merseyside regions of England1997–2000

Number of cigarettes/dayActive smoking and involuntary exposure to cigarette smokeMaternal smoking

Ever (37.5%)During pregnancy (24.2%)First trimester (23.8%)

Exposure to cigarette smoke among mothers who did not smoke (28.2%)Exposure to cigarette smoke among mothers who smoked (31.0%)

•	 An effect of involuntary smoking could

not be excluded in mothers who did not smoke

Honein et al. 2007 Case-control study

933 CL/P528 CPO3,390 controls with no defects8 sites in the United StatesOct 1997–Dec 2001 births

Periconceptual smoking (1 month before to 3 months after conception)20% controls exposed

•	 CL/P 1.3 (1.0–

Honein et al. 2007 Case-control study

933 CL/P528 CPO3,390 controls with no defects8 sites in the United StatesOct 1997–Dec 2001 births

Periconceptual smoking (1 month before to 3 months after conception)20% controls exposed

•	 CPO 1.2 (0.9–
Table 8.3 Continued

Study Design/population

Definition of smoking(smoking rate in controls) Findings OR (95% 

Shi et al. 2007 Case-control study

DNA samples from 1,244 children with CL/P, CPO4,183 parents, siblings, and unrelated population controlsDanish samples from two independent casecontrol studies (Dec 1991–Aug 1994; born between 1981–1990)Iowa samples from cases in Iowa Registry for Congenital and Inherited DisordersControl children born without major anomalies were matched by birth month, year, and gender 

Number of cigarettes/day 0 1–9 10–19 ≥20

•	 Maternal smoking was associated with

OFC in both Danish and Iowa data

CL/PDanish10–19 1.71 (1.1

Shi et al. 2007 Case-control study

DNA samples from 1,244 children with CL/P, CPO4,183 parents, siblings, and unrelated population controlsDanish samples from two independent casecontrol studies (Dec 1991–Aug 1994; born between 1981–1990)Iowa samples from cases in Iowa Registry for Congenital and Inherited DisordersControl children born without major anomalies were matched by birth month, year, and gender

Number of cigarettes/day 0 1–9 10–19 ≥20

•	 Maternal smoking was associated with

OFC in both Danish and Iowa data

CL/PDanish≥20 1.16 (0.5
Table 8.3 Continued

Study Design/population

Definition of smoking(smoking rate in controls) Findings OR (95% 

Shi et al. 2007 Case-control study

DNA samples from 1,244 children with CL/P, CPO4,183 parents, siblings, and unrelated population controlsDanish samples from two independent casecontrol studies (Dec 1991–Aug 1994; born between 1981–1990)Iowa samples from cases in Iowa Registry for Congenital and Inherited DisordersControl children born without major anomalies were matched by birth month, year, and gender

Number of cigarettes/day 0 1–9 10–19 ≥20

•	 Maternal smoking was associated with

OFC in both Danish and Iowa data

CL/PIowa1–4 0.93 (0.4

Shi et al. 2007 Case-control study

DNA samples from 1,244 children with CL/P, CPO4,183 parents, siblings, and unrelated population controlsDanish samples from two independent casecontrol studies (Dec 1991–Aug 1994; born between 1981–1990)Iowa samples from cases in Iowa Registry for Congenital and Inherited DisordersControl children born without major anomalies were matched by birth month, year, and gender

Number of cigarettes/day 0 1–9 10–19 ≥20

•	 Maternal smoking was associated with

OFC in both Danish and Iowa data

CL/PIowa5–14 2.24 (1.1
Table 8.3 Continued

Study Design/population

Definition of smoking(smoking rate in controls) Findings OR (95% 

Shi et al. 2007 Case-control study

DNA samples from 1,244 children with CL/P, CPO4,183 parents, siblings, and unrelated population controlsDanish samples from two independent casecontrol studies (Dec 1991–Aug 1994; born between 1981–1990)Iowa samples from cases in Iowa Registry for Congenital and Inherited DisordersControl children born without major anomalies were matched by birth month, year, and gender

Number of cigarettes/day 0 1–9 10–19 ≥20

•	 Maternal smoking was associated with

OFC in both Danish and Iowa data

CL/PIowa≥15 2.78 (1.4

Shi et al. 2007 Case-control study

DNA samples from 1,244 children with CL/P, CPO4,183 parents, siblings, and unrelated population controlsDanish samples from two independent casecontrol studies (Dec 1991–Aug 1994; born between 1981–1990)Iowa samples from cases in Iowa Registry for Congenital and Inherited DisordersControl children born without major anomalies were matched by birth month, year, and gender

Number of cigarettes/day 0 1–9 10–19 ≥20

•	 Maternal smoking was associated with

OFC in both Danish and Iowa data

CPODanish10–19 1.17 (0.6
Table 8.3 Continued

Study Design/population

Definition of smoking(smoking rate in controls) Findings OR (95% 

Shi et al. 2007 Case-control study

DNA samples from 1,244 children with CL/P, CPO4,183 parents, siblings, and unrelated population controlsDanish samples from two independent casecontrol studies (Dec 1991–Aug 1994; born between 1981–1990)Iowa samples from cases in Iowa Registry for Congenital and Inherited DisordersControl children born without major anomalies were matched by birth month, year, and gender

Number of cigarettes/day 0 1–9 10–19 ≥20

•	 Maternal smoking was associated with

OFC in both Danish and Iowa data

CPODanish≥20

0.35 (0.0

Shi et al. 2007 Case-control study

DNA samples from 1,244 children with CL/P, CPO4,183 parents, siblings, and unrelated population controlsDanish samples from two independent casecontrol studies (Dec 1991–Aug 1994; born between 1981–1990)Iowa samples from cases in Iowa Registry for Congenital and Inherited DisordersControl children born without major anomalies were matched by birth month, year, and gender

Number of cigarettes/day 0 1–9 10–19 ≥20

Maternal smoking was associated with 

OFC in both Danish and Iowa data

CPOIowa1–4 0.91 (0.3
Table 8.3 Continued

Study Design/population

Definition of smoking(smoking rate in controls) Findings OR (95% 

Shi et al. 2007 Case-control study

DNA samples from 1,244 children with CL/P, CPO4,183 parents, siblings, and unrelated population controlsDanish samples from two independent casecontrol studies (Dec 1991–Aug 1994; born between 1981–1990)Iowa samples from cases in Iowa Registry for Congenital and Inherited DisordersControl children born without major anomalies were matched by birth month, year, and gender

Number of cigarettes/day 0 1–9 10–19 ≥20

Maternal smoking was associated with 

OFC in both Danish and Iowa data

CPOIowa5–14 2.52 (1.0

Shi et al. 2007 Case-control study

DNA samples from 1,244 children with CL/P, CPO4,183 parents, siblings, and unrelated population controlsDanish samples from two independent casecontrol studies (Dec 1991–Aug 1994; born between 1981–1990)Iowa samples from cases in Iowa Registry for Congenital and Inherited DisordersControl children born without major anomalies were matched by birth month, year, and gender

Number of cigarettes/day 0 1–9 10–19 ≥20

Maternal smoking was associated with 

OFC in both Danish and Iowa data

CPOIowa≥15 1.58 (0.5
Table 8.3 Continued

Study Design/population

Definition of smoking(smoking rate in controls) Findings OR (95% 

Shi et al. 2007 Case-control study

DNA samples from 1,244 children with CL/P, CPO4,183 parents, siblings, and unrelated population controlsDanish samples from two independent casecontrol studies (Dec 1991–Aug 1994; born between 1981–1990)Iowa samples from cases in Iowa Registry for Congenital and Inherited DisordersControl children born without major anomalies were matched by birth month, year, and gender

Number of cigarettes/day 0 1–9 10–19 ≥20

•	 There was an interaction between

maternal smoking and fetal inheritance of a GSTT1 null deletion (Fisher combined p value <0.001)

Shaw et al. 2009 Case-control study nested within a cohort 

of pregnancies with mid-pregnancy serum specimens89 pregnancies with CL/P409 pregnancies without malformations

Mid-pregnancy serum cotinine levelsNo smoke exposure: cotinine value <2 μg/mLAny exposure: cotinine value ≥2 μg/mL

•	 Association of maternal serum midpregnancy cotinine levels with CL/P 2.1 (1.0–

Note: CI = confidence interval; CL/P = cleft lip with or without cleft palate; CP = cleft palate; CPO = cleft palate only; mL = milliliter; OR = odds ratio; μg 

aNot included in 2004 Surgeon General’s report on the health consequences of smoking.
Table 8.4 Association between maternal smoking and cardiovascular malformations, by phenotype, 1999–2008

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Torfs and Christiansen 1999

Case-control study687 infants with Down syndrome385 case infants with cardiac defects also302 control infants with no heart defects and no other specific defectCalifornia Birth Defects Monitoring Program1991 and 1993

First trimester participants

Yes vs. no

Smoking during pregnancy 

12% of all participants 8% of controls for cardiac defects

•	 Maternal smoking associated with

grouped cardiac defects

2.1 (1.2–

Torfs and Christiansen 1999

Case-control study687 infants with Down syndrome385 case infants with cardiac defects also302 control infants with no heart defects and no other specific defectCalifornia Birth Defects Monitoring Program1991 and 1993

First trimester participants

Yes vs. no

Smoking during pregnancy 

12% of all participants 8% of controls for cardiac defects

•	 Maternal smoking associated with

Atrioventricular septal defects 2.3 (1.2–

Torfs and Christiansen 1999

Case-control study687 infants with Down syndrome385 case infants with cardiac defects also302 control infants with no heart defects and no other specific defectCalifornia Birth Defects Monitoring Program1991 and 1993

First trimester participants

Yes vs. no

Smoking during pregnancy 

12% of all participants 8% of controls for cardiac defects

•	 Maternal smoking associated with

Tetralogy of Fallot 4.6 (1.2–

Torfs and Christiansen 1999

Case-control study687 infants with Down syndrome385 case infants with cardiac defects also302 control infants with no heart defects and no other specific defectCalifornia Birth Defects Monitoring Program1991 and 1993

First trimester participants

Yes vs. no

Smoking during pregnancy 

12% of all participants 8% of controls for cardiac defects

•	 Maternal smoking associated with

Atrial septal defects 2.2 (1.1–
Table 8.4 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Woods and Raju 2001

Retrospective cohort study of 18,016 live births in TriHealth Hospital System (Cincinnati, Ohio)Congenital defects grouped in 22 categories, including oral clefts1987–1999

Smokers vs. nonsmokersCohort included 1,943 mothers who were smokers

•	 Smoking associated with increased risk

of cardiovascular system abnormalities

•	 Patent ductus arteriosus (n = 153) and

ventricular septal defect (n = 48) most common abnormalities 

•	 Maternal smoking not associated with

21 other defects

1.56 (1.1

Källén 2002a Meta-analysis of 13 case-control studies 

published in 1971–1999

Smokers vs. nonsmokers

None, 1–20 cigarettes/day, and>20 cigarettes/day

Prevalence varied by study 

•	 Mixed results for cardiovascular defects

overall

•	 Mixed results for specific

cardiovascular defects

Data not 

Shaw et al. 2002 Case-control study

207 infants and fetal deaths with conotruncal defects489 infants and fetal deaths with orofacial clefts265 infants and fetal deaths with neural tube defects734 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1989

Maternal smoking during periconceptional period (1 month before to 3 months after conception) Smoking among case mothersSmoking among controls

•	 Smoking associated with conotruncal

defects among infants of women who did not use vitamins

Vitamins/Smoking

Yes/No 1.0

Shaw et al. 2002 Case-control study

207 infants and fetal deaths with conotruncal defects489 infants and fetal deaths with orofacial clefts265 infants and fetal deaths with neural tube defects734 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1989

Maternal smoking during periconceptional period (1 month before to 3 months after conception) Smoking among case mothersSmoking among controls

•	 Smoking associated with conotruncal

defects among infants of women who did not use vitamins

Vitamins/Smoking

No/Yes 2.2 (1.3–
Table 8.4 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Shaw et al. 2002 Case-control study

207 infants and fetal deaths with conotruncal defects489 infants and fetal deaths with orofacial clefts265 infants and fetal deaths with neural tube defects734 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1989

Maternal smoking during periconceptional period (1 month before to 3 months after conception) Smoking among case mothersSmoking among controls

•	 Smoking associated with conotruncal

defects among infants of women who did not use vitamins

Vitamins/Smoking

No/No 1.4 (0.9–

Shaw et al. 2002 Case-control study

207 infants and fetal deaths with conotruncal defects489 infants and fetal deaths with orofacial clefts265 infants and fetal deaths with neural tube defects734 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1989

Maternal smoking during periconceptional period (1 month before to 3 months after conception) Smoking among case mothersSmoking among controls

•	 Smoking associated with conotruncal

defects among infants of women who did not use vitamins

Vitamins/Smoking

Yes/Yes 1.0 (0.6–

Steinberger et al. 2002

Case-control study48 infants with single ventricle and abnormal situs3,572 infants without cardiac defectsBaltimore-Washington Infant Study (Maryland; northern Virginia; and Washington, DC)1981–1989

Parental smoking of >1 pack/day (maternal 4.9%, paternal 9%) vs. no smokingExposure period during gestation not stated 

•	 No association with maternal smoking 1.9 (0.6–
Table 8.4 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Steinberger et al. 2002

Case-control study48 infants with single ventricle and abnormal situs3,572 infants without cardiac defectsBaltimore-Washington Infant Study (Maryland; northern Virginia; and Washington, DC)1981–1989

Parental smoking of >1 pack/day (maternal 4.9%, paternal 9%) vs. no smokingExposure period during gestation not stated

•	 Increased risk with paternal smoking

of >1 pack/day 

2.2 (1.1–

Steinberger et al. 2002

Case-control study48 infants with single ventricle and abnormal situs3,572 infants without cardiac defectsBaltimore-Washington Infant Study (Maryland; northern Virginia; and Washington, DC)1981–1989

Parental smoking of >1 pack/day (maternal 4.9%, paternal 9%) vs. no smokingExposure period during gestation not stated

•	 Increased risk with paternal smoking

of increasing number of cigarettes/day

1–19 1.0

trend tes

Steinberger et al. 2002

Case-control study48 infants with single ventricle and abnormal situs3,572 infants without cardiac defectsBaltimore-Washington Infant Study (Maryland; northern Virginia; and Washington, DC)1981–1989

Parental smoking of >1 pack/day (maternal 4.9%, paternal 9%) vs. no smokingExposure period during gestation not stated

•	 Increased risk with paternal smoking

of increasing number of cigarettes/day

20–39 1.9

trend tes
Table 8.4 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Steinberger et al. 2002

Case-control study48 infants with single ventricle and abnormal situs3,572 infants without cardiac defectsBaltimore-Washington Infant Study (Maryland; northern Virginia; and Washington, DC)1981–1989

Parental smoking of >1 pack/day (maternal 4.9%, paternal 9%) vs. no smokingExposure period during gestation not stated

•	 Increased risk with paternal smoking

of increasing number of cigarettes/day

≥40 3.7

trend tes

Kuehl and Loffredo 2003

Case-control study36 infants with single l-transposition of 

great arteries3,495 infants without cardiac defectsBaltimore-Washington Infant Study Maryland; northern Virginia; and Washington, DC)1981–1989

Not statedPrevalence of maternal smoking for control infants not mentioned

•	 Maternal cigarette smoking associated

with increased risk of l-transposition of great arteries

1.6 (1.1–

Malik et al. 2008 Case-control study

3,067 infants with congenital heart defects3,947 controls without defects

Those who reported smoking any time from 1 month before conception and through each month of pregnancy <1 cigarette/day to >2 packs/day

•	 Septal heart defects

Light smoking 1.44 (1.1

Malik et al. 2008 Case-control study

3,067 infants with congenital heart defects3,947 controls without defects

Those who reported smoking any time from 1 month before conception and through each month of pregnancy <1 cigarette/day to >2 packs/day

•	 Septal heart defects

Medium smoking 1.50 (1.1
Table 8.4 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Malik et al. 2008 Case-control study

3,067 infants with congenital heart defects3,947 controls without defects

Those who reported smoking any time from 1 month before conception and through each month of pregnancy <1 cigarette/day to >2 packs/day

•	 Septal heart defects

Medium smoking 1.50 (1.1

Malik et al. 2008 Case-control study

3,067 infants with congenital heart defects3,947 controls without defects

Those who reported smoking any time from 1 month before conception and through each month of pregnancy <1 cigarette/day to >2 packs/day

•	 Septal heart defects

Heavy smoking 2.06 (1.2
Table 8.5 Association between maternal smoking and noncardiovascular congenital malformations, by type of malformation, 1998–

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Hwang et al. 1998 Case-control study

34 infants with isolated LDD482 control infants with other isolated defectsMaryland Birth Defects Reporting and Information System1984–1992

Maternal smoking during pregnancy (27.5% among all participants)

Any vs. noneEffect modification by MSX1 gene

•	 Interaction with MSX1 *rare alleles 

and risk of isolated limb deficiency

Smoking only 0.7 (0.03

Hwang et al. 1998 Case-control study

34 infants with isolated LDD482 control infants with other isolated defectsMaryland Birth Defects Reporting and Information System1984–1992

Maternal smoking during pregnancy (27.5% among all participants)

Any vs. noneEffect modification by MSX1 gene

•	 Interaction with MSX1 *rare alleles 

and risk of isolated limb deficiency

1 or 2 alleles only 2.4 (0.73

Hwang et al. 1998 Case-control study

34 infants with isolated LDD482 control infants with other isolated defectsMaryland Birth Defects Reporting and Information System1984–1992

Maternal smoking during pregnancy (27.5% among all participants)

Any vs. noneEffect modification by MSX1 gene

•	 Interaction with MSX1 *rare alleles 

and risk of isolated limb deficiency

Smoking and 1 or 2 alleles 4.8 (1.37

Reefhuis et al. 1998

Case-control study3,662 children with foot deformities7,829 control children with chromosomal or monogenic disorder26 European Surveillance of Congenital Anomalies registries1980–1994

During pregnancy

Any (18.1%) vs. none

•	 Maternal smoking during pregnancy

associated with increased risk of foot deformities

1.2 (1.1–
Table 8.5 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Akre et al. 1999 2 population-based case-control studies

2,782 boys operated on for cryptorchidism1,220 boys operated on for hypospadias (5 matched controls per case)Linkage of Inpatient and Birth RegistriesSweden birth cohort 1983–1993

Prenatal clinic record on maternal smoking

Yes (38.1%) vs. no

•	 Maternal smoking associated with

increased risk of cryptorchidism

1.19 (1.0

Akre et al. 1999 2 population-based case-control studies

2,782 boys operated on for cryptorchidism1,220 boys operated on for hypospadias (5 matched controls per case)Linkage of Inpatient and Birth RegistriesSweden birth cohort 1983–1993

Prenatal clinic record on maternal smoking

Yes (38.1%) vs. no

•	 Maternal smoking not associated with

increased risk of hypospadias

0.85 (0.7

Chen et al. 1999 Case-control study

775 children with Down syndrome7,750 control children with no malformation, matched by birth yearWashington State Birth Events Records Database1984–1994

Any maternal smoking during pregnancy vs. none (age)

<35 years (20.2%)≥35 years (14.2%)

•	 Maternal smoking during pregnancy

not associated with Down syndrome

1.00 (0.8

Källén 1999 Case-control studies

304 infants with craniosynostosis, no information available on type or number of controlsLinkages of Swedish Registry of Congenital Malformations and National Board of Health Medical Birth RegistrySweden1983–1996

Smoking at first prenatal visit 

Any (% not stated) vs. none

Categories

None<10 cigarettes/day≥10 cigarettes/day

•	 Associated with craniosynostosis 1.45 (1.1
Table 8.5 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Källén 1999 Case-control studies

304 infants with craniosynostosis, no information available on type or number of controlsLinkages of Swedish Registry of Congenital Malformations and National Board of Health Medical Birth RegistrySweden1983–1996

Smoking at first prenatal visit 

Any (% not stated) vs. none

Categories

None<10 cigarettes/day≥10 cigarettes/day

•	 Associated with isolated

craniosynostosis

1.67 (1.2

Källén 1999 Case-control studies

304 infants with craniosynostosis, no information available on type or number of controlsLinkages of Swedish Registry of Congenital Malformations and National Board of Health Medical Birth RegistrySweden1983–1996

Smoking at first prenatal visit 

Any (% not stated) vs. none

Categories

None<10 cigarettes/day≥10 cigarettes/day

•	 Not associated with syndromes 0.61 (0.2

Källén 1999 Case-control studies

304 infants with craniosynostosis, no information available on type or number of controlsLinkages of Swedish Registry of Congenital Malformations and National Board of Health Medical Birth RegistrySweden1983–1996

Smoking at first prenatal visit 

Any (% not stated) vs. none

Categories

None<10 cigarettes/day≥10 cigarettes/day

•	 Dose-response effect for isolated

craniosynostosis 

<10 cigarettes/day 1.48 (1.0

Källén 1999 Case-control studies

304 infants with craniosynostosis, no information available on type or number of controlsLinkages of Swedish Registry of Congenital Malformations and National Board of Health Medical Birth RegistrySweden1983–1996

Smoking at first prenatal visit 

Any (% not stated) vs. none

Categories

None<10 cigarettes/day≥10 cigarettes/day

•	 Dose-response effect for isolated

craniosynostosis

≥10 cigarettes/day 2.12 (1.5
Table 8.5 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Källén 1999 Case-control studies

304 infants with craniosynostosis, no information available on type or number of controlsLinkages of Swedish Registry of Congenital Malformations and National Board of Health Medical Birth RegistrySweden1983–1996

Smoking at first prenatal visit 

Any (% not stated) vs. none

Categories

None<10 cigarettes/day≥10 cigarettes/day

•	 Associated with sagittal but not other

suture synostosis

1.48 (1.0

Yang et al. 1999 Population-based case-control study

285 children with Down syndrome329 control children with no defects Cases ascertained from Metropolitan Atlanta Congenital Defects Program5 counties in Georgia1989–1996

Lifetime nonsmokers (71.0%)Ever smoked (28.9%)Current smoker (15.8%)Total pack-yearsa

<5 (16.4%)≥5 (12.2%)

Effect modification by timing and origin of meiotic error and OC use

•	 No association in presence of maternal

meiosis I nondisjunction errorCurrent smoker (age)

<35 years 0.69 (0.3

Yang et al. 1999 Population-based case-control study

285 children with Down syndrome329 control children with no defects Cases ascertained from Metropolitan Atlanta Congenital Defects Program5 counties in Georgia1989–1996

Lifetime nonsmokers (71.0%)Ever smoked (28.9%)Current smoker (15.8%)Total pack-yearsa

<5 (16.4%)≥5 (12.2%)

Effect modification by timing and origin of meiotic error and OC use

•	 No association in presence of maternal

meiosis I nondisjunction errorCurrent smoker (age)

≥35 years 0.81 (0.2
Table 8.5 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Yang et al. 1999 Population-based case-control study

285 children with Down syndrome329 control children with no defects Cases ascertained from Metropolitan Atlanta Congenital Defects Program5 counties in Georgia1989–1996

Lifetime nonsmokers (71.0%)Ever smoked (28.9%)Current smoker (15.8%)Total pack-yearsa

<5 (16.4%)≥5 (12.2%)

Effect modification by timing and origin of meiotic error and OC use

•	 Associated with Down syndrome

in young mothers with meiosis II nondisjunction errorEver smoked (age)

<35 years 2.43 (0.8

Yang et al. 1999 Population-based case-control study

285 children with Down syndrome329 control children with no defects Cases ascertained from Metropolitan Atlanta Congenital Defects Program5 counties in Georgia1989–1996

Lifetime nonsmokers (71.0%)Ever smoked (28.9%)Current smoker (15.8%)Total pack-yearsa

<5 (16.4%)≥5 (12.2%)

Effect modification by timing and origin of meiotic error and OC use

•	 Associated with Down syndrome

in young mothers with meiosis II nondisjunction errorEver smoked (age)

≥35 years 0.37 (0.0

Yang et al. 1999 Population-based case-control study

285 children with Down syndrome329 control children with no defects Cases ascertained from Metropolitan Atlanta Congenital Defects Program5 counties in Georgia1989–1996

Lifetime nonsmokers (71.0%)Ever smoked (28.9%)Current smoker (15.8%)Total pack-yearsa

<5 (16.4%)≥5 (12.2%)

Effect modification by timing and origin of meiotic error and OC use

•	 Associated with Down syndrome

in young mothers with meiosis II nondisjunction errorCurrent smoker (age)

<35 years 2.98 (1.0
Table 8.5 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Yang et al. 1999 Population-based case-control study

285 children with Down syndrome329 control children with no defects Cases ascertained from Metropolitan Atlanta Congenital Defects Program5 counties in Georgia1989–1996

Lifetime nonsmokers (71.0%)Ever smoked (28.9%)Current smoker (15.8%)Total pack-yearsa

<5 (16.4%)≥5 (12.2%)

Effect modification by timing and origin of meiotic error and OC use

•	 Associated with Down syndrome

in young mothers with OC use and maternal meiosis II nondisjunction error

OC use alone 0.38 (0.0

Yang et al. 1999 Population-based case-control study

285 children with Down syndrome329 control children with no defects Cases ascertained from Metropolitan Atlanta Congenital Defects Program5 counties in Georgia1989–1996

Lifetime nonsmokers (71.0%)Ever smoked (28.9%)Current smoker (15.8%)Total pack-yearsa

<5 (16.4%)≥5 (12.2%)

Effect modification by timing and origin of meiotic error and OC use

•	 Associated with Down syndrome

in young mothers with OC use and maternal meiosis II nondisjunction error

Smoking without OC use 1.54 (0.4

Yang et al. 1999 Population-based case-control study

285 children with Down syndrome329 control children with no defects Cases ascertained from Metropolitan Atlanta Congenital Defects Program5 counties in Georgia1989–1996

Lifetime nonsmokers (71.0%)Ever smoked (28.9%)Current smoker (15.8%)Total pack-yearsa

<5 (16.4%)≥5 (12.2%)

Effect modification by timing and origin of meiotic error and OC use

•	 Associated with Down syndrome

in young mothers with OC use and maternal meiosis II nondisjunction error

Smoking with OC use 7.92 (1.6
Table 8.5 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Honein et al. 2000 Population-based case-control study

346 infants with isolated clubfoot3,029 infants with no defectsFrequency matched to cases by year and hospital of birthAtlanta Birth Defects Case-Control Study1968–1980 

First trimester

Any (28.6%) vs. none

•	 Interaction between maternal smoking

and family history of clubfoot

Smoking only 1.32 (1.0

Honein et al. 2000 Population-based case-control study

346 infants with isolated clubfoot3,029 infants with no defectsFrequency matched to cases by year and hospital of birthAtlanta Birth Defects Case-Control Study1968–1980

First trimester

Any (28.6%) vs. none

•	 Interaction between maternal smoking

and family history of clubfoot

Family history only 6.52 (2.9

Honein et al. 2000 Population-based case-control study

346 infants with isolated clubfoot3,029 infants with no defectsFrequency matched to cases by year and hospital of birthAtlanta Birth Defects Case-Control Study1968–1980

First trimester

Any (28.6%) vs. none

•	 Interaction between maternal smoking

and family history of clubfoot

Both 20.30 (7.

Källén 2002b Case-control study

3,262 infants with hypospadias1,413,811 infants with no malformationLinkages of Swedish Registry of Congenital Malformations, National Board of Health Medical Birth Registry, and Hospital Discharge RegistrySweden1983–1996

Smokers (24.6%) vs. nonsmokers

•	 Maternal smoking negatively

associated with hypospadias

0.83 (0.7
Table 8.5 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Källén 2002b Case-control study

3,262 infants with hypospadias1,413,811 infants with no malformationLinkages of Swedish Registry of Congenital Malformations, National Board of Health Medical Birth Registry, and Hospital Discharge RegistrySweden1983–1996

Cigarettes/day

<10 (15.2%) 

Smokers vs. nonsmokers 

<10 cigarettes/day 0.84 (0.7

Källén 2002b Case-control study

3,262 infants with hypospadias1,413,811 infants with no malformationLinkages of Swedish Registry of Congenital Malformations, National Board of Health Medical Birth Registry, and Hospital Discharge RegistrySweden1983–1996

Cigarettes/day

≥10 (9.3%)

Smokers vs. nonsmokers 

≥10 cigarettes/day 0.81 (0.7

Shaw et al. 2002 Case-control study

265 infants and fetal deaths with neural tube defects165 infants with LDD734 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1989

During the periconceptional period (1 month before to 3 months after conception) (24%) vs. none

•	 Little association with LDD

Vitamins/Smoking

Yes/No 1.0

Shaw et al. 2002 Case-control study

265 infants and fetal deaths with neural tube defects165 infants with LDD734 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1989

During the periconceptional period (1 month before to 3 months after conception) (24%) vs. none

•	 Little association with LDD

Vitamins/Smoking

No/Yes 1.5 (0.8–
Table 8.5 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Shaw et al. 2002 Case-control study

265 infants and fetal deaths with neural tube defects165 infants with LDD734 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1989

During the periconceptional period (1 month before to 3 months after conception) (24%) vs. none

•	 Little association with LDD

Vitamins/Smoking

No/No 1.1 (0.7–

Shaw et al. 2002 Case-control study

265 infants and fetal deaths with neural tube defects165 infants with LDD734 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1989

During the periconceptional period (1 month before to 3 months after conception) (24%) vs. none

•	 Little association with LDD

Vitamins/Smoking

Yes/Yes 0.8 (0.5–

Skelly et al. 2002 Case-control study

239 children with clubfoot365 control children with no malformationWestern Washington State1986–1994

Average number of cigarettes/day during pregnancy 

None (81.7%)0.01–9.9 (11.2%)10–19.9 (4.8%)≥20 (2.3%)

•	 Associated with idiopathic clubfoot

 Smoking vs. none (cigarettes/day) 2.1 (1.5–

Skelly et al. 2002 Case-control study

239 children with clubfoot365 control children with no malformationWestern Washington State1986–1994

Average number of cigarettes/day during pregnancy 

None (81.7%)0.01–9.9 (11.2%)10–19.9 (4.8%)≥20 (2.3%)

•	 Associated with idiopathic clubfoot

 0.01–9.9 1.5 (0.9–

Skelly et al. 2002 Case-control study

239 children with clubfoot365 control children with no malformationWestern Washington State1986–1994

Average number of cigarettes/day during pregnancy 

None (81.7%)0.01–9.9 (11.2%)10–19.9 (4.8%)≥20 (2.3%)

•	 Associated with idiopathic clubfoot

 10–19.9 3.1 (1.7–
Table 8.5 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Skelly et al. 2002 Case-control study

239 children with clubfoot365 control children with no malformationWestern Washington State1986–1994

Average number of cigarettes/day during pregnancy 

None (81.7%)0.01–9.9 (11.2%)10–19.9 (4.8%)≥20 (2.3%)

•	 Associated with idiopathic clubfoot

 ≥20 3.9 (1.6–

Skelly et al. 2002 Case-control study

239 children with clubfoot365 control children with no malformationWestern Washington State1986–1994

Average number of cigarettes/day during pregnancy 

None (81.7%)0.01–9.9 (11.2%)10–19.9 (4.8%)≥20 (2.3%)

•	 Associated with idiopathic clubfoot

Risk (any vs. none) varied by infant gender

Boys 1.8 (1.2–

Skelly et al. 2002 Case-control study

239 children with clubfoot365 control children with no malformationWestern Washington State1986–1994

Average number of cigarettes/day during pregnancy 

None (81.7%)0.01–9.9 (11.2%)10–19.9 (4.8%)≥20 (2.3%)

•	 Associated with idiopathic clubfoot

Risk (any vs. none) varied by infant gender

Girls 2.8 (1.4–

Skelly et al. 2002 Case-control study

239 children with clubfoot365 control children with no malformationWestern Washington State1986–1994

Average number of cigarettes/day during pregnancy 

None (81.7%)0.01–9.9 (11.2%)10–19.9 (4.8%)≥20 (2.3%)

•	 Associated with isolated idiopathic

clubfoot

Any vs. none (cigarettes/day) 2.4 (1.7–

Skelly et al. 2002 Case-control study

239 children with clubfoot365 control children with no malformationWestern Washington State1986–1994

Average number of cigarettes/day during pregnancy 

None (81.7%)0.01–9.9 (11.2%)10–19.9 (4.8%)≥20 (2.3%)

•	 Associated with isolated idiopathic

clubfoot

 0.01–9.9 1.4 (0.9–
Table 8.5 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Skelly et al. 2002 Case-control study

239 children with clubfoot365 control children with no malformationWestern Washington State1986–1994

Average number of cigarettes/day during pregnancy 

None (81.7%)0.01–9.9 (11.2%)10–19.9 (4.8%)≥20 (2.3%)

•	 Associated with isolated idiopathic

clubfoot

 10–19.9 3.5 (1.8–

Skelly et al. 2002 Case-control study

239 children with clubfoot365 control children with no malformationWestern Washington State1986–1994

Average number of cigarettes/day during pregnancy 

None (81.7%)0.01–9.9 (11.2%)10–19.9 (4.8%)≥20 (2.3%)

•	 Associated with isolated idiopathic

clubfoot

 ≥20 4.6 (1.9–

van Rooij et al 2002

Case-control study45 case mothers of children with orofacial clefts39 case mothers of children with spina bifida75 control mothersThe Netherlands1997–1999

Smokers (18.1%) vs. nonsmokersCigarettes/dayEffect modification by NAT2 acetylator status

•	 Maternal smoking not associated with

spina bifida

•	 No association between maternal NAT2

acetylator status and spina bifida

•	 No interaction

Data not 

Werler et al. 2003 Population-based case-control study

Mothers of 205 case children with gastroschisis127 case children with small intestinal atresia381 malformed control children416 control children with no malformation15 cities across the United States and Canada1995–1999

Maternal smoking during first trimesterCigarettes/dayControl children with malformation

Any (34%) 1–9 (10%)10–19 (11%)>19 (13%)

Control children with no malformation

Any (34%)1–9 (9%)10–19 (9%)>19 (16%)

•	 Associated with gastroschisis

Any vs. none (cigarettes/day) 1.5 (1.1–
Table 8.5 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Werler et al. 2003 Population-based case-control study

Mothers of 205 case children with gastroschisis127 case children with small intestinal atresia381 malformed control children416 control children with no malformation15 cities across the United States and Canada1995–1999

Maternal smoking during first trimesterCigarettes/dayControl children with malformation

Any (34%) 1–9 (10%)10–19 (11%)>19 (13%)

Control children with no malformation

Any (34%)1–9 (9%)10–19 (9%)>19 (16%)

•	 Associated with gastroschisis

 1–9 1.3 (0.7–

Werler et al. 2003 Population-based case-control study

Mothers of 205 case children with gastroschisis127 case children with small intestinal atresia381 malformed control children416 control children with no malformation15 cities across the United States and Canada1995–1999

Maternal smoking during first trimesterCigarettes/dayControl children with malformation

Any (34%) 1–9 (10%)10–19 (11%)>19 (13%)

Control children with no malformation

Any (34%)1–9 (9%)10–19 (9%)>19 (16%)

•	 Associated with gastroschisis

 10–19 1.4 (0.9–
Table 8.5 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Werler et al. 2003 Population-based case-control study

Mothers of 205 case children with gastroschisis127 case children with small intestinal atresia381 malformed control children416 control children with no malformation15 cities across the United States and Canada1995–1999

Maternal smoking during first trimesterCigarettes/dayControl children with malformation

Any (34%) 1–9 (10%)10–19 (11%)>19 (13%)

Control children with no malformation

Any (34%)1–9 (9%)10–19 (9%)>19 (16%)

•	 Associated with gastroschisis

 >19 1.8 (1.1–

Werler et al. 2003 Population-based case-control study

Mothers of 205 case children with gastroschisis127 case children with small intestinal atresia381 malformed control children416 control children with no malformation15 cities across the United States and Canada1995–1999

Maternal smoking during first trimesterCigarettes/dayControl children with malformation

Any (34%) 1–9 (10%)10–19 (11%)>19 (13%)

Control children with no malformation

Any (34%)1–9 (9%)10–19 (9%)>19 (16%)

•	 Not associated with small intestinal

atresia

Any vs. none (cigarettes/day) 1.0 (1.6–
Table 8.5 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Werler et al. 2003 Population-based case-control study

Mothers of 205 case children with gastroschisis127 case children with small intestinal atresia381 malformed control children416 control children with no malformation15 cities across the United States and Canada1995–1999

Maternal smoking during first trimesterCigarettes/dayControl children with malformation

Any (34%) 1–9 (10%)10–19 (11%)>19 (13%)

Control children with no malformation

Any (34%)1–9 (9%)10–19 (9%)>19 (16%)

•	 Not associated with small intestinal

atresia

 1–9 1.4 (0.6–

Werler et al. 2003 Population-based case-control study

Mothers of 205 case children with gastroschisis127 case children with small intestinal atresia381 malformed control children416 control children with no malformation15 cities across the United States and Canada1995–1999

Maternal smoking during first trimesterCigarettes/dayControl children with malformation

Any (34%) 1–9 (10%)10–19 (11%)>19 (13%)

Control children with no malformation

Any (34%)1–9 (9%)10–19 (9%)>19 (16%)

•	 Not associated with small intestinal

atresia

 10–19 0.8 (0.3–
Table 8.5 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Werler et al. 2003 Population-based case-control study

Mothers of 205 case children with gastroschisis127 case children with small intestinal atresia381 malformed control children416 control children with no malformation15 cities across the United States and Canada1995–1999

Maternal smoking during first trimesterCigarettes/dayControl children with malformation

Any (34%) 1–9 (10%)10–19 (11%)>19 (13%)

Control children with no malformation

Any (34%)1–9 (9%)10–19 (9%)>19 (16%)

•	 Not associated with small intestinal

atresia

 >19 1.2 (0.6–

Carmichael et al. 2004

Population-based case-control study92 infants with LDD180 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1988

Maternal and paternal smoking and infant MSX1 genotype

Neither (50.0%)Mother only (11.7%)Father only (20.6%)Both (14.4%)

•	 No association of maternal smoking

and LDD risk

1.0 (0.4–

Carmichael et al. 2004

Population-based case-control study92 infants with LDD180 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1988

Maternal and paternal smoking and infant MSX1 genotype

Neither (50.0%)Mother only (11.7%)Father only (20.6%)Both (14.4%)

•	 No association of paternal smoking and

LDD risk

1.1 (0.6–

Carmichael et al. 2004

Population-based case-control study92 infants with LDD180 control infants with no malformationCalifornia Birth Defects Monitoring Program1987–1988

Maternal and paternal smoking and infant MSX1 genotype

Neither (50.0%)Mother only (11.7%)Father only (20.6%)Both (14.4%)

•	 No association between MSX1

genotype and LDD

•	 No interaction between parental

smoking, infant’s MSX1 genotype, and LDD risk
Table 8.5 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Pierik et al. 2004 Population-based nested case-control study

78 case children with cryptorchidism56 case newborns with hypospadias313 control newborns with no defects in a cohort of 8,698 male newbornsRotterdam, The Netherlands1999–2001

Current smoking (maternal 22.7%, paternal 41.5%) vs. no current smoking

•	 Maternal smoking not associated with

cryptorchidism

1.3 (0.8–

Pierik et al. 2004 Population-based nested case-control study

78 case children with cryptorchidism56 case newborns with hypospadias313 control newborns with no defects in a cohort of 8,698 male newbornsRotterdam, The Netherlands1999–2001

Current smoking (maternal 22.7%, paternal 41.5%) vs. no current smoking

•	 Maternal smoking not associated with

hypospadias

1.6 (0.8–

Pierik et al. 2004 Population-based nested case-control study

78 case children with cryptorchidism56 case newborns with hypospadias313 control newborns with no defects in a cohort of 8,698 male newbornsRotterdam, The Netherlands1999–2001

Current smoking (maternal 22.7%, paternal 41.5%) vs. no current smoking

•	 Paternal smoking not associated with

cryptorchidism

1.2 (0.6–

Pierik et al. 2004 Population-based nested case-control study

78 case children with cryptorchidism56 case newborns with hypospadias313 control newborns with no defects in a cohort of 8,698 male newbornsRotterdam, The Netherlands1999–2001

Current smoking (maternal 22.7%, paternal 41.5%) vs. no current smoking

•	 Paternal smoking associated with

hypospadias

3.8 (1.8–
Table 8.5 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Carmichael et al. 2008

Case-control study531 cases of craniosynostosis5,008 control children without malformation matched by birth cohortNational Birth Defects Prevention Study10 states1997–2003

Smoking before pregnancy, 1st, 2nd, and 3rd month of pregnancy2nd and 3rd trimesters Categories None Smoked <5 cigarettes/day Smoked 5–14 cigarettes/day Smoked ≥15 cigarettes/day

•	 Smoking during first month of

pregnancy was not associated with craniosynostosis

•	 Smoking later in pregnancy (2nd or

3rd trimester) was associated with increased risk but only among mothers who smoked at least 1 pack per day

Carmichael et al. 2008

Case-control study531 cases of craniosynostosis5,008 control children without malformation matched by birth cohortNational Birth Defects Prevention Study10 states1997–2003

Smoking before pregnancy, 1st, 2nd, and 3rd month of pregnancy2nd and 3rd trimesters Categories None Smoked <5 cigarettes/day Smoked 5–14 cigarettes/day Smoked ≥15 cigarettes/day

•	 Smoked ≥15 cigarettes/day 2nd trimester 1.6 (0.9–

Carmichael et al. 2008

Case-control study531 cases of craniosynostosis5,008 control children without malformation matched by birth cohortNational Birth Defects Prevention Study10 states1997–2003

Smoking before pregnancy, 1st, 2nd, and 3rd month of pregnancy2nd and 3rd trimesters Categories None Smoked <5 cigarettes/day Smoked 5–14 cigarettes/day Smoked ≥15 cigarettes/day

•	 Smoked ≥15 cigarettes/day 3rd trimester 1.4 (0.7–
Table 8.5 Continued

Study Design/population

Definition of smoking(prevalence of smoking) Findings by type of cardiovascular defect

Odds rat(95% co interval) 

Carmichael et al. 2008

Case-control study531 cases of craniosynostosis5,008 control children without malformation matched by birth cohortNational Birth Defects Prevention Study10 states1997–2003

Smoking before pregnancy, 1st, 2nd, and 3rd month of pregnancy2nd and 3rd trimesters Categories None Smoked <5 cigarettes/day Smoked 5–14 cigarettes/day Smoked ≥15 cigarettes/day

•	 Most confidence intervals include 1.0 

Note: Apgar = appearance, pulse, grimace, activity, respiration; BMI = body mass index; LDD = limb deficiency defects; OC = oral contraceptive.

aPack-years = the number of years of smoking multiplied by the number of packs of cigarettes smoked per day.
Table 8.6 Association between smoking and reproductive hormones in women

Study Population Sample/period

Definition of smoking(number of smokers) Findings in smokers

Estimate o(95% CI op value) 

MacMahon et al.1982b

106 White womenAged 25–49 years 

Overnight urine sampleFP (days 10–11)LP (days 21–22)

Nonsmokers: ≤100 cigarettes in lifetimeFormer smokers (n = 23)Current smokers (n = 39)

• Estrone, estradiol, and

estriol levels in FP similar to those in nonsmokers 

• All 3 decreased in LP• Little difference from

levels in former smokers

LP decreas(10–43%)

Michnovicz et al. 1986

27 nonobese women with normal cycle lengthMean age ~30 years

Blood and urine samples over 48 hours after administration of radiolabeled estradiolFP (days 1–10) in morning5 samples in LP (days 19–25)

Smokers (14) ≥15 cigarettes/day

• 2-hydroxylation increased• Urine estriol and estriol/

estrone decreased

Increased <0.001Decreased <0.01

Longcope and Johnston 1988

88 women (47 premenopausal)Mean age 50 years

Radiolabeled steroid infusionBlood and urine samples at baseline

Smokers (23) 10 cigarettes/day for ≥10 years

• Metabolic clearance rates

for testosterone, androstenedione, and estrone decreased

• Plasma testosterone,

androstenedione increased

• No difference in estrone

and estradiol or conversion from androgens

p <0.05 fometabolic clearance NS in only premenopwomen 

Zumoff et al. 1990

16 volunteers with normal ovulatory and luteal functionAged 25–35 years

Blood samples on 17 days over cycle, more frequently around midcycle (ovulation)

Smokers (8)≥20 cigarettes/day for ≥3 years

• Progesterone increased in

FP, not LP

• Estradiol increased in

early FP, slightly through FP

• Mean LH slightly decreased

Increased <0.0001)Increased <0.001) in FPIncreased (p ~0.05) through FNS
Table 8.6 Continued

Study Population Sample/period

Definition of smoking(number of smokers) Findings in smokers

Estimate o(95% CI op value) 

Key et al. 1991 147 women with cycle 

lengths of 21–35 days tested for estradiol and progesterone Aged ≥35 yearsGuernsey Breast Cancer Study105 women tested for urinary steroids

24-hour urine and 1 blood sample

Current smokers (1–10, 11–20, ≥21 cigarettes/day)69 smokers tested for estradiol and progesterone 20 smokers tested for urinary steroids

• No difference in serum

estradiol or progesterone

• No difference in 6 urinary

steroids (primarily androgens)

NS 

Berta et al. 1992 684 nonobese fertile women

Aged 25–52 years

24-hour urine sample and 3 blood samples on days 21–24 of LP

Smokers (237)>10 cigarettes/day for ≥5 years

• Plasma progesteronedecreased• Plasma prolactin decreased• No difference in estrone,

estradiol, FSH, and LH

Decreased <0.05)Decreased <0.002)

Cramer et al. 1994

224 womenAged 26–50 yearsSome with family history of ovarian cancer

1 blood sample in early FP (days 1–3)

Not defined, except “current, past, none”Current smokers (42)

• Mean FSH increased

in current and former smokers (≥10 pack-years)a

Increased (p = 0.03)

Cooper et al. 1995

290 womenAged 38–49 years

1 blood sample in early FP (days 2–4)

Self-reports on current smoking (31), former smoking, and involuntary and prenatal exposure

• Mean FSH increased in

current smokers and those exposed to SHS

• No difference in FSH in

former smokers or prenatal exposure

Increased (28–116%Increased <10 cigareIncreased 10–20 cigadayIncreased (4–86%) winvoluntarexposure
Table 8.6 Continued

Study Population Sample/period

Definition of smoking(number of smokers) Findings in smokers

Estimate o(95% CI op value) 

Key et al. 1996 167 women 

Aged ≥34 yearsGuernsey Breast Cancer Study

24-hour urine sample with timing known and periovulatory period excluded

Self-reports, not defined (53)

• Estrone and estradiol

slightly decreased

• Estriol decreased in early

FP, but less so later

0–16% for 4–15% for estradiol30% for esearly FP5–22% for later in cy

Westhoff et al. 1996

175 parous women with normal cyclesAged 21–36 years

Urine sample on day 10 to mensesBlood sample 3 times in LP

Self-reports, not defined (48)

• No difference in mean LP

progesterone in blood or urine

• Urine estradiol decreasedin LP

21% decrep = 0.04

Backer et al. 1999

3,114 womenAged 35–60 years National Health and Nutrition Examination Survey (U.S. national sample)

1 convenient blood sample

Smoking during 5 days before examination

• FSH increased p <0.001 

Lucero et al. 2001

498 women not in depressive state Aged 36–44 yearsHarvard Study of Moods and Cycles

1 blood sample in early FP (days 1–5)

Smoking not defined; current smokers (52); former smokers (172)

• FSH increased• Estradiol increased• LH increased• No difference in sex hormone binding globulin

12% increp <0.058% increap <0.0542% incre
Table 8.6 Continued

Study Population Sample/period

Definition of smoking(number of smokers) Findings in smokers

Estimate o(95% CI op value) 

Sowers et al. 2001

511 White womenAged 24–45 years

1 blood sample in FP (days 3–7) annually for 3 years

Lifetime nonsmokers, former smokers, current smokers (~20%)

• Increased serum testosterone• Intermediate effect

among former smokers

30–40% in(by year), p <0.01

Jernström et al. 2003

513 nulliparous womenAged 17–35 years

Morning blood sample on random day (timing calculated)

Current smoker (yes/no) • 2a- and 16a-hydroxyestrone slightly 

increased before adjustment, but not after adjustment 

• No effect on either metabolite alone

19% increp = 0.06 unadjustedp = 0.76 ad

Windham et al. 2005

403 women in reproductive yearsAged 18–39 years Members of Kaiser Permanente health maintenance organization

Daily urine collection through 2–7 cyclesAdjustment of hormone values for creatinine

Cigarettes/day from daily diary, averaged over cycleValidated by cotinine100–150 cycles of smokers

• Mean FSH increased in

smokers ≥10 cigarettes/day 

20–35% insignificant some days 

Windham et al. 2005

403 women in reproductive yearsAged 18–39 years Members of Kaiser Permanente health maintenance organization

Daily urine collection through 2–7 cyclesAdjustment of hormone values for creatinine

Cigarettes/day from daily diary, averaged over cycleValidated by cotinine100–150 cycles of smokers

• Estrone and progesterone

metabolites increased in early FP in smokers of ≥10 cigarettes/day

25% and 3increased, 

Windham et al. 2005

403 women in reproductive yearsAged 18–39 years Members of Kaiser Permanente health maintenance organization

Daily urine collection through 2–7 cyclesAdjustment of hormone values for creatinine

Cigarettes/day from daily diary, averaged over cycleValidated by cotinine100–150 cycles of smokers

• Progesterone decreased

in LP in smokers of ≥20 cigarettes/day

25% decrep = 0.06
Table 8.7 Association between smoking and reproductive hormones in healthy men

Study Population Study period Definition of smoking Findings

Odds ratioresponse rand 95% Cp value 

Briggs 1973 6 healthy smokers

6 healthy nonsmokers

7 days >30 cigarettes/day • Serum testosterone

lower in smokers (5.15 + 0.7 ng/mL) than in nonsmokers (7.47 + 0.53 ng/mL) 

NR 

Briggs 1973 6 healthy smokers

6 healthy nonsmokers

7 days >30 cigarettes/day • Mean increase in

testosterone after 7 days abstinence for smokers (1.65 + 0.5 ng/mL) but no change for nonsmokers

p <0.005 

Dotson et al. 1975

91 university students attending simulated party

4 hours Number of cigarettes 

smoked

• Testosterone positively

correlated with number of cigarettes smoked, r = 0.24

p <0.05 

Winternitz and Quillen 1977

17 long-term male smokers 2 days smoking followed 

by day not smoking

8 cigarettes2.8 mg of nicotine within 2 hours vs. baseline on day of abstinence

• LH, FSH, testosterone,

and thyroid-stimulating hormone showed no significant change during 4-hour study

NS 

Shaarawy and Mahmoud 1982

25 healthy smokers20 healthy nonsmokersAll fathers of ≥2 children

3 consecutive days >20 cigarettes/day • Smokers had higher

serum FSH (18.3 vs. 12.2 milli-international units per milliliter)

p <0.0025 

Shaarawy and Mahmoud 1982

25 healthy smokers20 healthy nonsmokersAll fathers of ≥2 children

3 consecutive days >20 cigarettes/day • Serum testosterone was

lower in smokers than in nonsmokers (3.6 vs. 6.2 ng/mL)

p <0.0005 

Shaarawy and Mahmoud 1982

25 healthy smokers20 healthy nonsmokersAll fathers of ≥2 children

3 consecutive days >20 cigarettes/day • LH not different between

groups
Table 8.7 Continued

Study Population Study period Definition of smoking Findings

Odds ratioresponse rand 95% Cp value 

Wilkins et al. 1982

10 long-term male smokers (≥1 pack/day of cigarettes with 1.0 mg of nicotine) 

2 days 2 cigarettes

2.0 mg vs. 0.2 mg of nicotine in 10 minutes

• Prolactin concentrations

were significantly higher with high- vs. low-nicotine cigarettes 

• 150% increase in prolactin concentrations 30 

minutes after smoking cigarette with 2 mg of nicotine and remained above baseline at 60 minutes

p <0.0001 

Deslypere and Vermeulen 1984

75 healthy smokers73 healthy nonsmokers33 former smokers

Single blood sample >5 cigarettes/day for >2 

years

• Plasma testosterone and

free testosterone levels were higher in smokers than in nonsmokers for three age groups

• LH did not differ between

smokers and nonsmokers

Aged 20–3p <0.001Aged 40–5

p <0.01

Aged 60–8

p <0.05

Klaiber et al. 1984

Group I

23 healthy smokers 18 healthy nonsmokers

Group II

18 smokers 17 nonsmokers Attending infertility clinic

Single fasting blood sample for estradiol

Not defined • Higher mean serum

estradiol levels in both groups of smokers

• Number of cigarettes

smoked/day not associated with estradiol concentrations in smokers

• Positive correlation with

number of cigarettes smoked/day in analysis of pooled data from smokers and nonsmokers

Group I: p Group II: p Group I: r p <0.03Group II: r p <0.001

Gossain et al. 1986

6 healthy smokers6 healthy nonsmokers

Experimental session with blood sample obtained 120 minutes after smoking first cigarette

2 unfiltered cigarettes smoked in 10 minutes

• Mean prolactin concentrations of 8.3 ng/mL for 

smokers and 15.4 ng/mL for nonsmokers

Integrated for 2 groups dat p <0.001
Table 8.7 Continued

Study Population Study period Definition of smoking Findings

Odds ratioresponse rand 95% Cp value 

Seyler et al. 1986 4 healthy smokers

Average 22.5 cigarettes/day

2 experimental sessions 15 hours with no 

smoking followed by 2 low-dose (0.48 mg) cigarettes smoked 5 minutes apart or 2 highdose (2.87 mg) nicotine cigarettes smoked in rapid succession

• No differences in FSH,

LH, prolactin, or thyroidstimulating hormone concentrations between baseline and either high-dose or low-dose exposures

NS 

Barrett-Connor and Khaw 1987

590 menNo history of heart disease or strokeRancho Bernardo, California

Enrollment 1972–1974 Lifetime nonsmokers, 

former smokers, or current smokers (number of cigarettes/day)

• No significant differences

between groups in concentrations of testosterone or SHBG

Barrett-Connor and Khaw 1987

590 menNo history of heart disease or strokeRancho Bernardo, California

Enrollment 1972–1974 Lifetime nonsmokers, 

former smokers, or current smokers (number of cigarettes/day)

• Androstenedione was

higher in smokers

p <0.001 

Barrett-Connor and Khaw 1987

590 menNo history of heart disease or strokeRancho Bernardo, California

Enrollment 1972–1974 Lifetime nonsmokers, 

former smokers, or current smokers (number of cigarettes/day)

• Estrone was higher in

smokers

p <0.001 

Barrett-Connor and Khaw 1987

590 menNo history of heart disease or strokeRancho Bernardo, California

Enrollment 1972–1974 Lifetime nonsmokers, 

former smokers, or current smokers (number of cigarettes/day)

• Estradiol was higher in

smokers

p <0.02 

Barrett-Connor and Khaw 1987

590 menNo history of heart disease or strokeRancho Bernardo, California

Enrollment 1972–1974 Lifetime nonsmokers, 

former smokers, or current smokers (number of cigarettes/day)

• Dose-response effect for

number of cigarettes/day for androstenedione, estrone, and estradiol, but not for testosterone and SHBG

p <0.001 
Table 8.7 Continued

Study Population Study period Definition of smoking Findings

Odds ratioresponse rand 95% Cp value 

Dai et al. 1988 121 men

Pittsburgh Multiple Risk Factor Intervention Trial

Baseline and 4 years later

Cigarettes/day 

None1–3031–70

• Testosterone positively

associated with number of cigarettes/day

p <0.05 

Dai et al. 1988 121 men

Pittsburgh Multiple Risk Factor Intervention Trial

Baseline and 4 years later

Cigarettes/day 

None1–3031–70

• Androstenedione

positively associated with number of cigarettes/day

p <0.05 

Meikle et al. 1989

75 healthy monozygotic twins85 healthy dizygotic twins1 set of healthy triplets

Nonsmokers, former smokers, current smokers Packs/day for current smokers

• Higher DHT concentrations for current smokers 

than for nonsmokers

• No adjusted, independent effect of smoking 

for estrone, estradiol, testosterone, SHBG, LH, and FSH

p = 0.03 

Michnovicz et al. 1989

20 healthy smokers16 healthy nonsmokers

48 hours Lifetime nonsmokers vs. 

≥15 cigarettes/day

• Estradiol 2-hydroxylation increased ~70% in 

smokers

p <0.001 

Michnovicz et al. 1989

20 healthy smokers16 healthy nonsmokers

48 hours Lifetime nonsmokers vs. 

≥15 cigarettes/day

• Urinary catechol estrogen

index significantly higher for smokers

p = 0.006 

Field et al. 1994 1,241 healthy men

Boston area341 male smokers

Enrollment 1987–1989 Cigarettes smoked/day • Higher androstenedione,

testosterone, DHT, and SHBG for smokers

Androstenp = 0.0001Testosterop = 0.009DHTp = 0.004SHBGp = 0.0004
Table 8.7 Continued

Study Population Study period Definition of smoking Findings

Odds ratioresponse rand 95% Cp value 

Sofikitis et al. 1995

Healthy men presenting for hernia repair

49 smokers 18 lifetime nonsmokers9 former smokers

19 monthsPresurgery and postsurgery sampling and postcessation sampling

≥20 cigarettes/day for >3 years

• Testicular androgenbinding protein lower in 

smokers

p <0.05 

Sofikitis et al. 1995

Healthy men presenting for hernia repair

49 smokers 18 lifetime nonsmokers9 former smokers

19 monthsPresurgery and postsurgery sampling and postcessation sampling

≥20 cigarettes/day for >3 years

• Testicular venous testosterone lower in smokers p <0.05 

Sofikitis et al. 1995

Healthy men presenting for hernia repair

49 smokers 18 lifetime nonsmokers9 former smokers

19 monthsPresurgery and postsurgery sampling and postcessation sampling

≥20 cigarettes/day for >3 years

• Circulating serum FSH,

LH, and testosterone concentrations not statistically different between smokers and nonsmokers

English et al. 2001

25 smokers25 lifetime nonsmokers

NR Self-reported ≥10 

cigarettes/day

• Cotinine correlated with

SHBG (r = 0.49)

p <0.05 

English et al. 2001

25 smokers25 lifetime nonsmokers

NR Self-reported ≥10 

cigarettes/day

• Free testosterone and

total testosterone higher in smokers

p = 0.03 

English et al. 2001

25 smokers25 lifetime nonsmokers

NR Self-reported ≥10 

cigarettes/day

• Bioavailable testosterone

did not differ between groups

English et al. 2001

25 smokers25 lifetime nonsmokers

NR Self-reported ≥10 

cigarettes/day

• 17-β estradiol did not 

differ between group

p = 0.01 
Table 8.7 Continued

Study Population Study period Definition of smoking Findings

Odds ratioresponse rand 95% Cp value 

Trummer et al. 2002

260 smokers70 former smokers258 lifetime nonsmokersInfertility clinic population

1993–2000 Self-reported number of 

cigarettes/day

• Increased LH and testosterone and decreased 

prolactin in smokers compared with those for nonsmokers

Increased and free teone, p <0.Increased p = 0.035Decreased prolactin, p <0.001

Note: BMI = body mass index; CI = confidence interval; DHT = dihydrotestosterone; FSH = follicle-stimulating hormone; LH = luteinizing hormone; mg = milligrams; ng/mL = nanograms per milliliter; NR = not reported; NS = no significant difference; SHBG = sex hormone 
Risk of IUGR with level of exposure to pollutant in first month

Pollutant/location Comparison by exposure AOR 95% CI

PM10         

Teplice Medium : low 1.44 1.03–2.02

Teplice High : low 2.14 1.42–3.23

Prachatice Medium : low 1.59 1.06–2.39

Prachatice High : low 1.09 0.49–2.46

PAH         

Teplice Medium : low 1.59 1.06–2.39

Teplice High : low 2.15 1.27–3.63

Prachatice Medium : low 1.49 0.81–2.73

Prachatice High : low 1.26 0.60–2.63

Increase in AOR for IUGR for each 10 μg of PM10 or 10 ng of PAH during first month*

Pollutant/location AOR 95% CI

PM10      

Teplice 1.19 1.06–1.33

Prachatice 1.04 0.86–1.27

PAH      

Teplice 1.22 1.07–1.39

Prachatice 1.17 0.92–1.89

*ORs adjusted for parity, maternal age and height, prepregnancy weight, education, marital status, season, year of study, and 

maternal smoking per month 
645

Chapter 9

A Vision for the Future

The Global Tobacco Epidemic 647

Reducing the Risks from Smoking 651

Ending the Tobacco Epidemic 652

Concluding Remarks 654

Appendix 9.1: Recommendations for Future Research 655

Nicotine Addiction 655

Biomarkers for Addiction Potential 655

Future Directions in Understanding Addiction 655

Cancer 657

Cardiovascular Diseases 657

Pulmonary Diseases 658

Reproductive and Developmental Effects 658

Epidemiologic Studies 658

Pathophysiological and Cellular/Molecular Mechanisms 659

Appendix 9.2: Ending the Tobacco Problem: A Blueprint for the Nation 660

Complete List of Recommendations 660

Strengthening Traditional Tobacco Control Measures 660

Changing the Regulatory Landscape 662

New Frontiers in Tobacco Control 664

Appendix 9.3: Promoting Healthy Lifestyles: Policy, Program, and Personal Recommendations 

for Reducing Cancer Risk 664

References 667

A Vision for the Future 647

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

The Global Tobacco Epidemic

Tobacco use remains the leading preventable cause 

of premature death in the United States, and the World 

Health Organization (WHO) has called tobacco use “the 

single most preventable cause of death in the world today” 

(WHO 2008, p. 8). Predictions based on large population 

studies indicate that one-half of all long-term smokers, 

particularly those who began smoking in adolescence, 

will eventually die from their use of tobacco. Furthermore, one-half of the deaths caused by smoking will 

occur in middle age (35 through 69 years), resulting in 

the loss of 20 to 25 years of normal life expectancy (Peto 

et al. 1992, 2006; Doll et al. 1994). In the 45 years since 

the first U.S. Surgeon General’s report on smoking and 

health was published in 1964 (U.S. Department of Health, 

Education, and Welfare [USDHEW] 1964), smoking has 

been the primary underlying cause of more than 12 million U.S. deaths. Each year since 2004, more than 430,000 

additional smoking-attributable deaths have been added to the national total (U.S. Department of Health and 

Human Services [USDHHS] 2004; Bonnie et al. 2007; 

Centers for Disease Control and Prevention [CDC] 2008a). 

It has been estimated that worldwide, tobacco use caused 

100 million deaths during the twentieth century, and that 

tobacco use may cause as many as 1 billion deaths in the 

twenty-first century, unless urgent and effective action is 

taken (WHO 2008).

Understanding the health consequences and diseases caused by tobacco use has provided the scientific 

foundation for public health actions aimed at tobacco use 

prevention, cessation, and protection from secondhand 

smoke exposure. Since the first Surgeon General’s report, 

this series has considered research findings on mechanisms of disease production in assessing the biologic plausibility of associations observed in epidemiologic studies. 

The important contribution of evidence on biologic plausibility and coherence in evaluation of causality has been 

reviewed in recent reports (USDHHS 2004, 2006). For 

example, evidence regarding the biologic plausibility of the 

observed relationship between exposure to secondhand 

smoke and coronary heart disease (CHD) has been very 

important in the evaluation of causality (USDHHS 2001, 

2006). In initial studies (e.g., Hirayama 1984; Garland 

et al. 1985), the estimated magnitude of the association 

between exposure to secondhand smoke and CHD seemed 

large compared with the association between active smoking and CHD. However, further findings on mechanisms 

linking tobacco smoke exposure to CHD risk—in particular, the impact of tobacco smoke exposure on platelet 

aggregation and acute endothelial dysfunction—provided 

plausible and quantitatively consistent mechanisms for 

the observed nonlinear relationship with exposure levels 

to tobacco smoke (Glantz and Parmley 1991, 1995; Law 

et al. 1997). More recently, the potential effect of active 

smoking and exposure to secondhand smoke on breast 

cancer risk is an area for which data on biologic plausibility and mechanisms are critically needed in the evaluation of potential causality (USDHHS 2006; International 

Agency for Research on Cancer [IARC] 2004; Miller et al. 

2007; Phillips and Garte 2008).

Despite the wealth of scientific evidence on the 

adverse health effects of exposure to tobacco smoke, many 

gaps remain in our understanding of the molecular and cellular mechanisms of tobacco-induced diseases. It has been 

suggested that “given the obvious dangers of tobacco and the 

associated imperative to eliminate it, research undertaken 

purely to unravel mechanisms of tobacco-related cancer 

is difficult to justify” (Carlsten and Burke 2006, p. 2481). 

However, as discussed in Chapter 1, research to further 

understand the biologic mechanisms by which exposure 

to tobacco smoke causes disease has several important 

applications beyond assisting in the determination of 

causal relationships, including

	 •	 developing biomarkers of injury to identify smokers

at early stages of disease development;

	 •	 providing a basis for preventive therapies that block

or reverse the underlying process of injury; 

	 •	 identifying the contribution of exposure to tobacco

smoke to causation of diseases with multiple etiologic factors; and

	 •	 assessing tobacco products for their potential to

cause injury through a particular mechanism.

Expanding our knowledge of several common 

molecular and cellular mechanisms underlying seemingly 

diverse smoking-induced diseases—such as dysregulation 

of inflammatory and immune processes (including oxidative stress, altered antibody production, endothelial cell 

dysfunction, suppression of T cells) and the dysregulation 

of inflammatory cells—could have important implications 

in the potential development of novel therapeutic targets 

for various environmentally induced diseases (Wang and 

Scott 2005). For example, with growing understanding 
Surgeon General’s Report

648 Chapter 9

of genetic and epigenetic mechanisms, opportunities are 

expanding to address the broader applications of disease 

mechanisms related to exposure to tobacco smoke (Esteller 2008; Herbst et al. 2008; Caporaso et al. 2009; Breton et 

al. 2009; National Cancer Institute [NCI] 2009). As noted 

in the 2007–2008 Annual Report of the President’s Cancer 

Panel, “...even if all current smokers cease using tobacco 

today and no new smokers take up the habit, the latency 

of tobacco-caused cancer and other diseases dictates that 

cancer and other morbidity and mortality from tobacco 

will still be affecting our population for at least another 

two decades” (Reuben 2008, p. 57). A list of research priorities identified in this report is provided in Appendix 9.1.

A key feature of tobacco use is the development of 

nicotine addiction, which often leads to chronic, daily 

exposure to tobacco that typically persists for many years. 

As reviewed in Chapter 4 of this report, addiction, or more 

technically the diseases of dependence and withdrawal, 

make it essential to ensure that effective behavioral and 

pharmacological cessation treatments are widely available 

and accessible to diverse populations of smokers (Zaza et 

al. 2005; National Institutes of Health [NIH] State-of-theScience Panel 2006). The various treatments for tobacco 

use have targeted different aspects of nicotine addiction, 

such as reinforcement, withdrawal, and cue-associated 

learning. Pharmacologic treatments have included nicotinic acetylcholine receptor ligands (nicotine replacement, and varenicline, a partial α4β2 agonist) or have 

involved alterations in signal transduction to stimulate 

the release of the same neurochemicals that are released 

by nicotine (e.g., bupropion and nortriptyline). Ideally, 

those who smoke would find it as easy to access cessation 

services as they do commercial tobacco products (Fiore et 

al. 2008). 

Effective public health and clinical approaches to 

increase smoking cessation rates have been developed 

(USDHHS 2000; Zaza et al. 2005; Bonnie et al. 2007; Reuben 2007; Fiore et al. 2008). These public health strategies 

and the clinical treatments need to be more fully implemented. 

Significant progress has been achieved in the United 

States during the last 50 years in reducing smoking initiation and increasing smoking cessation (Bonnie et al. 2007; 

Reuben 2007; Cokkinides et al. 2009). After 30 years of 

declining rates of smoking, particularly among men, the 

total U.S. cancer deaths began to decline in the late 1990s, 

driven largely by a reduction in male lung cancer deaths 

(Cokkinides et al. 2009). Moreover, the declines in lung 

cancer death rates among men and women in California declined more rapidly than in the rest of the country 

after the implementation of a comprehensive and sustained statewide tobacco control program (Barnoya and 

Glantz 2004; Jemal et al. 2008).

Today, an estimated one-half of all Americans who 

have ever smoked have quit (CDC 2008a, 2009a), and the 

benefits of cessation have been documented for smokers 

of all ages (USDHHS 1990; IARC 2007a). However, as a 

group, smokers who successfully quit early in life can 

avoid a large proportion of the excess mortality caused 

by smoking (USDHHS 1990; IARC 2007a). Data from the 

British Doctors’ Study have been used to demonstrate the 

lifetime risks of smoking and the amount of that risk that 

can be avoided by sustained cessation at various ages (Doll 

et al. 2004). Figure 9.1 contrasts the cumulative survival 

curves for all-cause mortality of continuing smokers (blue 

lines), with never smokers (red lines), and with smokers 

who quit by various ages (e.g., effect from sustained quitting at ages 35, 40, 50, and 60 years). The survival curves 

demonstrate that even at older ages, a substantial and 

important fraction of the excess all-cause mortality due to 

smoking can be averted by sustained quitting. Nonetheless, smokers who quit after the age of 44 years continue 

to have excess risk for tobacco-related diseases. 

As noted in Chapter 6, cigarette smoking is a 

major cause of cardiovascular disease (CVD) and has 

multiplicative interactions with the other major risk factors for CHD. Importantly, although there is a strong 

dose-response relationship between the number of 

cigarettes smoked per day and cardiovascular risk, 

the relationship is not linear, with those who smoke 

few cigarettes per day or who do not smoke every day 

remaining at significantly elevated risk for CVD. It has 

been estimated that one-fifth of U.S. smokers are intermittent or occasional smokers (CDC 2008a), and this 

pattern of use is more common among some racial and 

ethnic groups, including Blacks and Hispanics, and smokers living below the poverty level (Fagan and Rigotti 

2009). This emphasizes the importance of increasing our 

understanding of the process of smoking and quitting and 

of providing appropriate cessation services to this group 

of smokers.

The time course of reduction of risk after quitting 

smoking varies substantially across disease outcomes, 

with the risk of CHD declining more rapidly than the 

risk of tobacco-related cancers, particularly among those 

with a longer duration of smoking before sustained quitting (USDHHS 1990; IARC 2007a). The continued excess 

risk of lung cancer among former smokers has focused 

attention on the need to better identify those at greatest 

risk and to develop effective methods of early detection 

(Black and Baron 2007; Dubey and Powell 2008; Field and 

Duffy 2008). More than one-half of all cases of lung cancer are diagnosed at an advanced stage, and the five-year 

survival rate for lung cancer remains at about 15 percent 

(Jemal et al. 2008). At present, the efficacy of screening 

for lung cancer with low-dose computed tomography or 
A Vision for the Future 649

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

other methodologies remains controversial (Black and 

Baron 2007). A better understanding of the molecular and 

cellular pathways involved in respiratory carcinogenesis 

could increase the feasibility of chemoprevention trials or 

of more cost-effective application of lung cancer screening 

(Alberg et al. 2005; Dubey and Powell 2008; Field 2008).

Recent advances in the understanding of the molecular origins of lung cancer have focused attention on the 

possibility that molecular profiling of genes and proteins 

could lead to the development of biomarkers for defining 

cancer risk, prognosis, and potentially improved treatment for some of the even more difficult to manage 

types of lung cancer (Herbst et al. 2008). The evidence 

reviewed in Chapter 5 on the major established pathways 

of cancer causation by cigarette smoking identifies important steps along these mechanistic pathways that could 

be used in potential biomarkers for defining cancer risk, 

prognosis, and potentially improved treatment. Figure 9.2 

graphically presents how molecular profiling and assessments of genes and proteins could influence decisions 

regarding lung cancer treatment options for individual patients.

Chronic obstructive pulmonary disease (COPD) 

remains a leading cause of death in the United States, and 

in 2005, approximately 1 in 20 deaths in the United States 

had COPD as the underlying cause, with an estimated 75 

percent of these COPD deaths attributable to smoking 

(CDC 2008b). While the U.S. trend in COPD deaths has 

remained fairly stable from 2000 to 2005 (CDC 2008b), the 

global burden of COPD is increasing (Mannino and Buist 

2007; Barnes 2007). Importantly, the evidence indicates 

that in the United States, COPD could be almost completely prevented by the elimination of smoking (USDHHS 

2004). Although the risks for COPD morbidity and mortality decline with smoking cessation, they may not return to 

the levels of nonsmokers (USDHHS 2004). The U.S. Lung 

Health Study documented the benefits of substantially 

reduced mortality among individuals with asymptomatic 

airway obstruction who quit smoking (Anthonisen et al. 

2005). The U.S. Lung Health Study also documented the 

benefits of providing an intensive 10-week smoking cessation program to this at-risk population; nearly 22 percent 

of intervention participants succeeded in quitting smoking compared with only 5.4 percent of participants who 

received usual care (Anthonisen et al. 2005). These results 

emphasize that rates of smoking cessation among patients 

most at risk of COPD could be increased up to fourfold 

if current available smoking cessation treatment options 

were delivered more routinely. 

Figure 9.1 Effects on survival of stopping smoking 

cigarettes at ages 25–34 years (effect 

from age 35), ages 35–44 years (effect 

from age 40), ages 45–54 years (effect 

from age 50), and ages 55–64 years 

(effect from age 60) 

Source: Doll et al. 2004. Reprinted with permission from BMJ 

Publishing Group Ltd., © 2004.

Numerous studies have shown that COPD is associated with lung cancer risk; this association may be 
Surgeon General’s Report

650 Chapter 9

attributed to shared exposure to cigarette smoke, to 

shared genetic susceptibility, and/or to facilitation of 

tumor initiation and promotion by inflammation (Dubey 

and Powell 2008). The growing global burden of COPD 

emphasizes the need for research to develop biomarkers of injury to identify smokers at early stages of disease 

development and to provide a basis for preventive therapies that block or reverse the underlying process of 

injury, particularly among former smokers. Research 

in this area may be guided by the evidence reviewed in 

Chapter 7, which identifies the two major mechanisms 

underlying the causation of COPD by cigarette smoking, 

oxidative stress (injury) and protease-antiprotease imbalance, and the strong association between COPD occurrence and a specific genetic disorder: AAT deficiency.

As noted in Chapter 8, health professionals have 

long known that exposure to tobacco smoke during 

pregnancy poses serious risks to fetal development. 

Figure 9.2 Molecular-profiling approaches to the development of personalized therapy

Source: Herbst et al. 2008. Reprinted with permission from Massachusetts Medical Society, © 2008.

Note: Host profiling involves innate characteristics of the cancer patient. All markers that are involved in profiling lung cancer can

apply to the tumor or its local environment. Predictive markers identify groups of patients who are likely to have increased sensitivity 

or resistance to a given therapy, a critical step in personalizing treatment. It has been traditional to assess individual genetic or protein prognostic or predictive markers (e.g., HER2 for breast cancer), but emerging techniques permit global analyses of the genomic, 

gene-expression, epigenetic, and protein profiles of the host (innate), including markers in blood and in tumor or nonmalignant lung 

tissue. These methods include SNP arrays to assess genomic alterations, bisulfite sequencing, and methylation-specific PCR to assess 

epigenetic changes, microarrays for assessing gene expression or microRNA levels, and proteomic methods (such as mass spectroscopy, reverse-phase protein arrays, and multiplex beads) to assess intracellular signaling in tumor tissue and cytokines and angiogenic 

factors in blood. Blood-based profiling includes markers derived from the host (e.g., lymphocytes) and the tumor and local 

environment (e.g., circulating tumor cells and tumor-derived cytokines) (red arrows); IHC = immunohistochemical analysis; 

PCR = polymerase chain reaction; SNP = single nucleotide polymorphism.
A Vision for the Future 651

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Despite this, approximately 19 percent of women of 

reproductive age smoke cigarettes, and based on birth 

certificate data, more than 1 in 10 (11.4 percent) women reported smoking during pregnancy (CDC 2004, 

2008a). However, birth certificate data often underreport smoking during pregnancy. In survey data from 

2002 to 2005, 17.3 percent of pregnant women reported 

smoking cigarettes in the month preceding the survey 

(NSDUH Report 2007). In addition, many pregnant women who do not smoke are exposed to secondhand smoke in 

workplaces, public places, and in their own homes. Recommendations have been made regarding the types of 

smoking cessation services that should be provided to all 

pregnant smokers (Fiore et al. 2008). Despite the documented costs of poor infant outcomes caused by smoking 

during pregnancy, and the higher prevalence of prenatal 

tobacco use found among lower income women, in 2006 

only 27 states covered tobacco cessation counseling services for pregnant women in their Medicaid populations 

(CDC 2008e). 

Reducing the Risks from Smoking

The benefits of quitting have been shown for smokers of all ages (USDHHS 1990, 2004; IARC 2007a). Smokers who quit completely and permanently early in life 

have a risk of premature death very similar to lifetime 

nonsmokers (Figure 9.1) (USDHHS 1990, 2004; IARC 

2007a). However, for lung cancer, there is a persistent 

elevated risk in former smokers compared with lifetime 

nonsmokers of the same age even after a long abstinence 

(IARC 2007a). Evidence indicates that lung cancer risk 

increases far more strongly with each additional year 

of smoking than it increases for a higher average number of cigarettes smoked per day (Flanders et al. 2003; 

IARC 2007a). Although sustained smoking cessation 

at any age produces substantial reductions in risk, significant health benefits (other than for the fetus during 

pregnancy) from reducing the amount smoked or from 

short-term cessation have not been demonstrated (Benhamou et al. 1989; Godtfredsen et al. 2002; Anthonisen et 

al. 2005; Tverdal and Bjartveit 2006; IARC 2007a; Bjartveit and Tverdal 2009). The evidence presented in this 

report on the biologic mechanisms by which exposure to 

tobacco smoke causes cancers, cardiovascular and chronic obstructive pulmonary diseases, and reproductive and 

developmental effects document the importance of smokers quitting completely early in life and avoiding even 

occasional or infrequent smoking.

As reviewed in Chapter 2, in recent years a range 

of new products have been introduced and marketed to 

smokers as an alternative to conventional cigarettes, 

sometimes accompanied by messages, explicit or implied, 

that they offer reduced exposure to toxic substances or 

risk of disease. Evidence reviewed in this and previous 

reports indicates that five decades of evolving cigarette 

design have not reduced overall disease risk among smokers, and new designs can be used to undermine prevention 

and cessation efforts. It is now recognized that substantial 

risks may be associated with new tobacco products:

1. Smokers who might have otherwise stopped smoking 

may continue to smoke because of perceived reduction in risk with use of new products.

2. Former smokers may resume smoking because of 

perceived reduction in risk with use of new products.

3. Nonsmokers, particularly youth, may start to use new 

products because of their perceived safety.

The evidence reviewed in this report highlights 

many of the scientific challenges that will be faced in evaluating new cigarette products presented as alternatives to 

conventional cigarettes, because of the diversity of such 

products, the multitude of smoking-related diseases, the 

impact of these products on nonusers, and the dearth of 

empirical data on their effects. The Institute of Medicine 

(IOM) Committee to Assess the Science Base for Tobacco 

Harm Reduction (Stratton et al. 2001) and more recent 

reviews (Gray et al. 2005; Royal College of Physicians of 

London 2007; European Commission 2008) have discussed 

the potential role in tobacco control of a wider range of alternatives to the current cigarette. Several questions need 

to be carefully considered when proposing novel tobacco 

products as strategies to reducing smoking-attributable 

mortality: Do these products decrease individual risk? Do 

they increase initiation of tobacco use or promote relapse? 

Do they delay cessation? Do they lead to dual product use? 

How does their use compare to cessation? As discussed in 

Chapter 2, in the absence of a sound science base to support such alternative strategies, the primary public health 

approaches remain prevention and cessation of all forms 

of tobacco products. 

Chapter 4 in this report documents the importance of nicotine as the drug causing the addiction that 

is the fundamental reason that individuals persist in 
Surgeon General’s Report

652 Chapter 9

using tobacco products. However, other constituents in 

tobacco and tobacco smoke may also be reinforcing or may 

facilitate the reinforcing effects of nicotine. The factors 

contributing to the high addiction potential of tobacco 

products are multiple and complex. Understanding these 

relationships is critical in developing better treatments for 

cessation and for determining appropriate strategies to 

reduce use of tobacco products (Benowitz and Henningfield 1994; Henningfield et al. 1998, 2004; Gray et al. 2005; 

Benowitz et al. 2006; Royal College of Physicians of London 2007; Benowitz 2008; Zeller et al. 2009). 

The evidence on the CVD risks of low levels of 

tobacco smoke exposure in Chapter 6 of this report clearly 

demonstrate that the dose response for CVD is not linear, 

with risk rising rapidly at low doses and then plateauing 

at relatively low levels of exposure. The data on CVD also 

demonstrates the potential for dual tobacco product use 

resulting in a greater risk of disease than either product alone (Teo et al. 2006). Additional research to identify those toxicants in tobacco products that are most 

responsible for acute cardiac risks is critically needed 

(Boffetta and Straif 2009).

As reviewed in this and prior reports, the risk of 

lung and other cancers, as well as COPD, increases dramatically with greater duration of smoking. In addition, 

dual use of cigarettes along with other tobacco products 

could not only result in delays in sustained smoking cessation but may also increase the risk of disease more than 

cigarette smoking alone. If the use of alternative tobacco 

products hinders tobacco prevention and cessation efforts 

and results in longer durations of smoking among some 

smokers, the population burden of tobacco-related morbidity and mortality would be higher than for an approach 

focused on helping these smokers quit completely. In 

addition, tobacco products used in places where smoking 

is not allowed may defeat public health efforts to reduce 

smoking rates. Thus, there are continuing concerns about 

the population health impact of tobacco product modification or alternatives to cigarettes (Stratton et al. 2001; 

European Commission 2008). 

Ending the Tobacco Epidemic

Since the health risks of tobacco use were first 

identified, the public health response has focused on preventing initiation of tobacco use, encouraging cessation 

among existing users, and more recently, protecting nonsmokers from exposure to secondhand smoke. Although 

the primary focus of previous Surgeon General’s reports 

has been a review of scientific evidence related to health 

effects of tobacco use, numerous reports have provided 

specific recommendations to reduce the use of tobacco and 

exposure to secondhand smoke (Lynch and Bonnie 1994; 

USDHHS 2000; Zaza et al. 2005; NIH State-of-the-Science 

Panel 2006; Bonnie et al. 2007; Reuben 2007; Fiore et al. 

2008). Effective public health and clinical approaches to 

increase smoking cessation rates have been developed 

and need to be more fully implemented (USDHHS 2000; 

Zaza et al. 2005; Bonnie et al. 2007; Reuben 2007; Fiore et 

al. 2008). 

The IOM report, Ending the Tobacco Problem: A 

Blueprint for the Nation, concluded that the ultimate 

goal is “to reduce smoking so substantially that it is no 

longer a significant public health problem” (Bonnie et 

al. 2007, p. 1). The report proposed a two-pronged strategy to accomplish this goal: first, to strengthen and fully 

implement traditional tobacco control measures known 

to be effective, and second, to change the regulatory 

landscape to permit policy innovations such as strong federal regulation of tobacco products and their marketing 

and distribution (Bonnie et al. 2007). A complete list of 

the 42 recommendations made by the IOM report is provided in Appendix 9.2. In addition, the President’s Cancer 

Panel has highlighted the critical importance of reducing 

tobacco use stating that “ridding the nation of tobacco is 

the single most important action needed to dramatically 

reduce cancer mortality and morbidity” (Reuben 2008, p. 

iii) and that “if the population ceased smoking, this single 

behavior change would be tantamount to a vaccine against 

one-third of cancer deaths” (Reuben 2007, p. vi). 

In its 2006–2007 Annual Report, the President’s 

Cancer Panel provided a detailed review of the status of 

tobacco control efforts in this country to address tobacco use prevention and treatment (Chapter 4) and environmental tobacco smoke exposure (Chapter 5). In this 

review, the President’s Cancer Panel outlined the important roles in reducing tobacco-caused death and disease 

that could be undertaken by federal, state, and local governments; nongovernmental organizations and other 

partners; the educational system; employers, insurance, 

and the health care system; and individuals and families 

(Reuben 2007). Many of these actions are very consistent 

with the 42 recommendations made by IOM (Appendix 
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

9.2) and emphasize the evidence-based methods identified by the 2006 NIH State-of-the-Science consensus conference (NIH State-of-the-Science Panel 2006). The 15 

recommendations from the President’s Cancer Panel are 

provided in Appendix 9.3.

Since the release of the recommendations from 

IOM (Bonnie et al. 2007) and the President’s Cancer Panel 

review of the status of tobacco control in this country 

(Reuben 2007), additional actions have been taken at the 

federal, state, and local levels. Below is a summary of the 

status of tobacco control efforts in this country within the 

WHO MPOWER framework (WHO 2008):

	 •	 Monitor tobacco use and prevention policies.

	 •	 Protect people from tobacco smoke.

	 •	 Offer help to quit tobacco use.

	 •	 Warn about the dangers of tobacco use.

	 •	 Enforce comprehensive restrictions on tobacco 

advertising, promotion, and sponsorship.

	 •	 Raise taxes on tobacco.

MONITOR. The monitoring of the population pattern of tobacco use and the status of prevention and control policies and programs has been defined as essential 

in national efforts to counter the tobacco epidemic (WHO 

2008; Giovino et al. 2009). Current efforts to monitor 

the tobacco use epidemic and identify additional steps to 

optimize measurement of tobacco use and factors influencing use in the United States have been reviewed (Cruz 

2009; Delnevo and Bauer 2009; Farrelly 2009; Giovino 

et al. 2009; Stellman and Djordjevic 2009). These papers 

provide detailed analysis of national tobacco monitoring, 

research, and evaluation under the classic Agent, Host, 

Vector, and Environment framework. These reviews indicate that many of the most important basic elements of a 

national monitoring system are in place but that several 

key elements are needed to improve the system. 

PROTECT. This report provides additional scientific evidence that there is no risk-free level of exposure 

to tobacco smoke. Although progress has been made to 

increase protection of nonsmokers in the United States 

from secondhand smoke exposure since the release of 

the 2006 Surgeon General’s report on the health consequences of involuntary exposure to tobacco smoke (CDC 

2008f), biomonitoring of exposure indicates that almost 

one-half of nonsmokers, and more than 60 percent of 

young children, continue to be exposed (CDC 2008c). 

Wide geographic, occupational, and demographic disparities remain (CDC 2008c,f). It has been estimated that 

only about one in three residents of the United States live 

under state or local laws that make worksites, restaurants, 

and bars completely smoke-free (CDC 2008f).

OFFER. The U.S. Tobacco Use and Dependence 

Guideline Panel has identified the most effective interventions to assist tobacco users to successfully quit (Fiore et 

al. 2008). Moreover, a systematic review and analysis of 

recommended clinical preventive services has identified 

clinical smoking cessation services as one of the most 

successful and cost-effective recommendations (Maciosek 

et al. 2006). However, data indicate that less than 30 percent of smokers are offered assistance in quitting annually (Partnership for Prevention 2008). Both IOM and the 

President’s Cancer Panel address this issue in their recommendations (Appendices 9.2 and 9.3).

WARN. WHO recommends that national efforts to 

warn about the dangers of tobacco should create high levels of awareness of the health risks of tobacco use across 

age groups, genders, and places of residence so all people 

understand that the result of tobacco use is often suffering, disfigurement, and early death (WHO 2008). The 

President’s Cancer Panel noted that the warning labels 

on tobacco products in many other countries are larger 

and more graphic than those on U.S. cigarette packages 

(see figure 17, page 74, Reuben 2007). The Federal Cigarette Labeling and Advertising Act of 1965 (the Cigarette 

Act) and the Comprehensive Smokeless Tobacco Health 

Education Act of 1986 (the Smokeless Act), as amended 

by the Family Smoking Prevention and Tobacco Control 

Act (Tobacco Control Act) (2009), require new, stronger 

warning statements on cigarette and smokeless tobacco 

packages and advertising and require color graphics 

depicting the negative health consequences of smoking on cigarette packages and advertising. The Tobacco 

Control Act further amends the Cigarette Act and the 

Smokeless Act to give the U.S. Food and Drug Administration the authority to revise the warning label statements and the color graphics for both cigarettes and 

smokeless tobacco through rulemaking. In addition to 

potential changes in package warning labels, evidence 

supports the effectiveness of health communication and 

countermarketing strategies employing a wide range of 

efforts, including paid television, radio, billboard, print, 

and Web-based advertising at the national, state, and 

local levels; media advocacy through public relations 

efforts; and efforts to reduce or replace tobacco industry 

sponsorship and promotions (CDC 2007; NCI 2008). Recommendations 15 and 16 from IOM address the need for 

a national, youth-oriented, countermarketing campaign 

as well as increased mass media and other general and 
Surgeon General’s Report

654 Chapter 9

targeted public education programs to promote effective 

cessation programs and activities (Appendix 9.2) (Bonnie 

et al. 2007).

ENFORCE. Both the 2007 IOM and 2006–2007 President’s Cancer Panel reports have identified the sophisticated strategies used by the tobacco industry to counter 

policies and programs to reduce tobacco consumption 

(Bonnie et al. 2007; Reuben 2007). Cigarettes remain one 

of the most heavily marketed products in the United States, 

with more than $250 billion (in 2006 dollars) expended 

between 1940 and 2005 on cigarette advertising and 

promotion (NCI 2008). The influence of these tobacco 

industry efforts in shaping tobacco-related knowledge, 

opinions, attitudes, and behavior was reviewed in detail, 

and it was concluded that the total weight of evidence 

demonstrated a causal relationship between tobacco 

advertising and promotion and increased tobacco use 

(NCI 2008). The Tobacco Control Act will enable new 

actions to be taken at the federal, state, and local levels to 

counteract the influence of tobacco advertising, promotions, and sponsorship.

RAISE. With the increase in the federal excise tax 

on cigarettes from $0.24 to $1.01 on April 1, 2009, the 

combined federal and average state cigarette excise tax 

increased to $2.21 per pack (CDC 2009b). Evidence-based 

reviews have concluded that increases in the price of 

cigarettes through excise taxes or other strategies are an 

effective policy intervention to prevent smoking initiation among adolescents and young adults, reduce cigarette consumption, and increase the number of smokers 

who quit (USDHHS 2000; Zaza et al. 2005; NIH State-ofthe-Science 2006; Bonnie et al. 2007; CDC 2007; Reuben 

2007). Additionally, the WHO MPOWER recommendations 

emphasize the importance of ensuring that the tax rates 

on tobacco products are adjusted periodically to keep pace 

with inflation and rise faster than consumer purchasing 

power. WHO also stresses that implementation of effective strategies to limit smuggling and the availability of 

untaxed tobacco products is essential to maximizing the 

effectiveness of higher taxes in reducing tobacco use 

(WHO 2008). 

Concluding Remarks

In 1964, the Surgeon General’s Advisory Committee concluded: “Cigarette smoking is a health hazard of 

sufficient importance in the United States to warrant 

appropriate remedial action” (USDHEW 1964, p. 33). 

Evidence-based recommendations have helped to define 

appropriate remedial actions, including those from the 

2000 Surgeon General’s report on reducing tobacco use 

(USDHHS 2000), NIH (NIH State-of-the-Science Panel 

2006), the Task Force on Community Preventive Services (Zaza et al. 2005), IOM reports (Stratton et al. 2001; 

Bonnie et al. 2007), and President’s Cancer Panel reports 

(Reuben 2007, 2008). The specific scientific conclusions 

from this report may provide further guidance for developing additional remedial actions. 

Despite significant progress, tobacco use remains 

the single most preventable cause of death and disease 

in the United States. It is worth noting that lung cancer 

was once a very rare disease. Primary Malignant Growths 

of the Lungs and Bronchi, published in 1912, reviewed 

the worldwide scientific literature and was able to identify 

only 374 verified cases of lung cancer (Adler 1912; Spiro and Silvestri 2005). In stark contrast, lung cancer is 

today the nation’s leading cause of cancer death among 

both men and women, killing an estimated 160,000 people 

in the United States, and an estimated 1.34 million people 

worldwide each year (Jemal et al. 2008; WHO 2008). An 

estimated 90 percent of U.S. lung cancer deaths in men 

and 80 percent of U.S. lung cancer deaths in women are 

caused by smoking and exposure to secondhand smoke 

(CDC 2009c). In addition, more than 100,000 deaths from 

pulmonary diseases and more than 140,000 deaths from 

heart disease and stroke in the United States are caused 

each year by active smoking and exposure to secondhand 

smoke (CDC 2008d). 

Since the publication of the 1964 Surgeon General’s 

report on smoking and health, this series of reports has 

provided an incontrovertible body of research evidence 

documenting the burden of sickness and death caused by 

tobacco use. Faced with these facts, it is appropriate to 

restate the challenge issued by a former Director-General 

of WHO, Dr. Gro Harlem Brundtland, at the start of the 

international negotiations that led to the landmark 

Framework Convention on Tobacco Control:

If we do not act decisively today, a hundred years 

from now our grandchildren and their children 

will look back and seriously question how people 

claiming to be committed to public health and 

social justice allowed the tobacco epidemic to 

unfold unchecked (Brundtland 1999).
A Vision for the Future 655

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Appendix 9.1 

Recommendations for Future Research

The evidence reviewed within this report identified 

important gaps in our scientific knowledge that merit 

greater attention in future research. Below is a listing of 

areas of research that can substantially contribute to a 

better understanding of how tobacco use causes disease.

Nicotine Addiction

With the emerging science base for understanding the physiological, behavioral, and cognitive bases for 

addiction and for identifying the genetics and other 

host factors that may moderate the effects of nicotine, 

new types of interventions are being developed that are 

expanding the treatment armamentarium, thus providing more effective interventions for those who continue 

to have difficulty in quitting smoking. For example, pharmacologic treatments are being marketed that target 

specific nicotinic receptors responsible for the reinforcing effects of nicotine, such as varenicline (Gonzales et 

al. 2006; Jorenby et al. 2006; Nides et al. 2006; Oncken 

et al. 2006). Nicotine immunotherapies (vaccines) under 

development also offer potential treatments for nicotine 

addiction. Nicotine immunotherapies stimulate the 

immune system to develop antibodies to nicotine that 

reduce the level and speed of nicotine entering the brain, 

potentially changing the pharmacokinetics of nicotine and 

thereby reducing the reinforcing effects of nicotine (Pentel 

2004; Hatsukami et al. 2005). Another area of major development in the treatment of smokers, as with the treatment 

of other diseases, involves tailoring treatments to the phenotype and genotype of the individuals to select the most 

efficacious treatments (Lerman and Niaura 2002). All of 

these treatment developments have been aided by greatly 

expanded understanding of the mechanisms of dependence and withdrawal during the past two decades.

Valid indicators and biomarkers of addiction are 

needed to assess future “less addictive” or “less toxic” 

tobacco products and treatments and to provide a better 

understanding of the addictive process. Many subjective 

and behavioral measures and some cognitive measures 

have been developed and used to test addiction to tobacco. 

However, fundamental gaps in knowledge exist, and other 

areas need to be more vigorously pursued.

Biomarkers for Addiction Potential

Table 9.1 summarizes the methods used for animal and human testing to assess the addiction potential 

of a nicotine product. Most of these methods have been 

referred to in Chapter 4 of this report. Although there 

are many subjective and behavioral methods, researchers 

have devoted little attention to cognitive and neurophysiological measures of addiction through the use of functional magnetic resonance imaging or positron emission 

tomography. Using more precise tools to assess and better understand learning processes, decision making, and 

brain changes associated with addiction will lead to the 

development of measurements in these areas. The limitations and questions associated with the measures listed in 

Table 9.1 are similar to those concerning the diagnosis of 

tobacco addiction or, for that matter, biomarkers for disease in general. That is, other than relative terms (e.g., 

product A has a greater abuse potential than does product B) or the occurrence of addiction, the threshold or 

criterion that determines the extent of abuse potential is 

unknown. 

Future Directions in Understanding Addiction

Several areas of research that can substantially contribute to a better understanding of nicotine addiction 

include—but are not limited to—the following:

	 •	 Improve understanding of the criteria for and measures of nicotine addiction or dependence and how 

they might differ across various populations, including youth and ethnic minorities.

	 •	 Adapt commonly used measures of assessing addiction to cigarettes to other tobacco products as demonstrated by preliminary efforts to develop and 

validate scales for smokeless tobacco dependence 

and, most recently, to waterpipe smoking.

	 •	 Develop a better understanding of the contribution of the design features of tobacco products 

and of constituents other than nicotine that play 

an important role in all aspects of nicotine addiction, including initiation, maintenance, withdrawal, 

and relapse.
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656 Chapter 9

Table 9.1 Behavioral indicators of addiction potential of a drug or addiction to a drug

Animal models

•	 Conditioned place preference

•	 Drug self-administration

•	 Drug discrimination

•	 Withdrawal

− Somatic signs

− Reward threshold

Human models

•	 Choice of drug compared with other reinforcers

•	 Breakpoint on a progressive ratio task relative to other reinforcers

•	 Level of nicotine or tobacco self-administration and pattern of self-administration

•	 Compensatory tobacco use behavior

•	 Time to use drug after a period of deprivation

•	 Withdrawal symptoms

− Negative affect

− Performance

− Physiological (e.g., heart rate, weight)

− Acoustic startle response

•	 Physiological reactivity toward smoking-related stimuli

•	 Cue-induced craving

Subjective measures of addiction potential

•	 Drug liking

•	 Drug effects (e.g., good effects, bad effects, strength of effects)

•	 Visual analog scale for drug effects (e.g., high, dizzy)

•	 Amount of monetary expenditure for a drug

Biochemical measures of addiction

•	 Cotinine/nicotine level

Cognitive indications of addiction 

•	 Attentional bias toward smoking-related stimuli

Neurophysiological biomarkers of addiction potential or addiction

•	 Extent of brain activity in response to nicotine

•	 Extent of brain activity in response to cues

	 •	 Use current knowledge of the neurosystems

associated with the reinforcement, withdrawal, 

and conditioning effects of nicotine addiction to 

develop a strategic road map for future discoveries 

in this area.

	 •	 Move toward a better understanding of the role and

neurobiology of associative learning and cognitive 

processing in the development of and recovery from 

nicotine addiction.

	 •	 Foster an interdisciplinary effort to develop links

among genotypes, endophenotypes, phenotypes, 

and the neurobiologic effects of nicotine.

	 •	 Explore the differences between adolescents and

adults in their sensitivity to nicotine and to other 

factors associated with tobacco use, and find out 

which factors contribute to these differences (e.g., 

stage of neurodevelopment, sex hormones).
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	 •	 Increase understanding of the relationship between

comorbid disorders and nicotine addiction, including the common neural pathways and psychosocial 

vulnerabilities, and the mechanisms associated with 

an increased risk of nicotine addiction. 

Cancer

Even though the evidence has long been sufficient 

to infer that both active and involuntary smoking cause at 

least 15 types of cancer, the long latency of tobacco-caused 

cancers emphasizes the need for further research on the 

mechanisms by which exposure to tobacco causes cancer. 

Several areas of research that can substantially contribute 

to a better understanding of these mechanisms include—

but are not limited to—the following:

	 •	 Investigate genetic polymorphisms and phenotypic

variations among smokers in critical aspects of the 

carcinogenic process that may lead to variations in 

susceptibility to the carcinogens in tobacco smoke. 

Examples include differences in carcinogen- and 

nicotine-metabolizing enzymes and their products, DNA repair genes, and cell cycle genes. This 

research could lead to the identification of individuals who are particularly susceptible to the effects of 

tobacco smoke and who could be targeted for preventive interventions.

	 •	 Develop a panel of quantitative biomarkers of carcinogens or their metabolites in blood or urine. 

Apply this panel of biomarkers to determine carcinogen dose in smokers and its relationship to cancer. 

Such a panel could be extremely useful in determining individual risk of tobacco-induced cancer and 

potentially useful for regulation.

	 •	 Develop quantitative reproducible and reliable

methods for assessing levels of DNA adducts specific to all major carcinogens in tobacco smoke, and 

carry out biomarker studies to investigate the relationship between DNA adducts and cancer in smokers. This approach could potentially identify highly 

susceptible smokers and further define mechanisms 

of cancer induction in general, beyond the effects of 

tobacco products.

	 •	 Further study the role of nicotine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone, and other toxicants in tobacco smoke in the activation of nicotinic 

acetylcholine receptors in lung epithelial cells, as 

well as similar key intracellular proteins and related 

epigenetic events that can lead to tumor promotion, 

cocarcinogenesis, progression, and maintenance 

of cancer.

	 •	 Conduct additional studies of the potential mechanisms by which carcinogens in tobacco smoke affect 

breast tissue, and how various other effects from 

tobacco smoke exposure, including possible antiestrogenic effects, could modulate or reduce the carcinogenic effects of tobacco smoke exposure.

	 •	 Develop a predictive algorithm—including tobacco

carcinogen and DNA biomarker data and related 

parameters such as polymorphisms in DNA repair 

genes—to identify those smokers most susceptible to cancer induction by cigarette smoke. This 

algorithm would be analogous to the Gail model for 

breast cancer susceptibility.

	 •	 Investigate the mechanisms by which alcohol consumption and asbestos exposure enhance the risk 

for tobacco-related cancers.

	 •	 Study the major pathway by which tobacco smoke

induces cancer through DNA adduct formation by 

tobacco smoke carcinogens and other contributing 

factors such as tumor promotion, cocarcinogenesis, direct receptor binding effects of nicotine and 

tobacco-specific nitrosamines, and hypermethylation of tumor suppressor gene promoter regions 

that clearly contribute. Further research is necessary to elucidate the relevant mechanisms involved 

in these pathways.

Cardiovascular Diseases

Even though the evidence has long been sufficient 

to infer that both active and involuntary smoking cause 

coronary heart disease, the observed risks from exposure 

to toxicants in combustible and noncombustible tobacco 

products emphasize the need for further research on 

the mechanisms by which exposure to tobacco adversely 

affects the cardiovascular system. Several areas of research 

that can substantially contribute to a better understanding of these mechanisms include—but are not limited 

to—the following:

	 •	 Conduct further study of the role of oxidizing chemicals, nicotine, or other toxicants in tobacco smoke 

in the development of endothelial dysfunction.
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658 Chapter 9

	 •	 Promote additional study of the role of specific

toxicants in tobacco smoke in the development 

of acute and chronic inflammatory reactions and 

the development of reliable biomarkers of these 

reactions predictive of acute cardiovascular events 

and atherosclerosis.

	 •	 Identify the toxicants in tobacco smoke most responsible for the nonlinear dose response between 

exposure dose to tobacco smoke (including secondhand smoke) and indicators of acute cardiovascular 

risk and related cardiovascular events.

	 •	 Identify the toxicants in tobacco smoke most responsible for platelet activation effects.

	 •	 Analyze the toxicants in various forms of smokeless

tobacco products that could produce acute or 

chronic changes in mechanisms related to cardiovascular risk.

	 •	 Conduct further study of the differential effects of

alveolar deposition of particulate constituents from 

tobacco smoke and other ambient air sources on 

biochemical and physiological acute and chronic 

reactions related to cardiovascular risk and related 

cardiovascular events. 

	 •	 Further explore the role of nicotine and other toxicants in tobacco smoke in the development of insulin resistance.

Pulmonary Diseases

Chronic obstructive pulmonary disease (COPD) 

remains a major public health problem that is increasing, but evidence indicates that COPD could be almost 

completely prevented with the elimination of smoking 

(U.S. Department of Health and Human Services 2004). 

Although there are substantial and rapid benefits to lung 

function after smoking cessation, evidence indicates that 

morbidity related to COPD persists long after cessation of 

smoking (International Agency for Research on Cancer 

2007a). Several areas of research that can substantially 

contribute to a better understanding of the mechanisms 

by which exposure to tobacco smoke increase the risk of 

COPD include—but are not limited to—the following:

	 •	 Promote further research in characterizing the

genetic basis of susceptibility to tobacco smoke in 

the causation of COPD.

	 •	 Further explore the role of oxidative stress in the

pathogenesis of COPD and the potential to modulate 

this mechanism of disease production.

	 •	 Investigate more deeply the role of protease-antiprotease imbalance in the pathogenesis of COPD 

and the potential to modulate this mechanism of 

disease production. 

Reproductive and 

Developmental Effects

Epidemiologic Studies

Numerous adverse pregnancy outcomes or maternal 

complications have been causally associated with 

maternal smoking. Research to better define doseresponse relationships, especially for preeclampsia, preterm delivery, and premature rupture of membranes, 

would be informative. This information could be used to 

establish more accurate estimates of individual risk and 

of population-attributable risk percentage. In general, 

research is needed to better define the effects of smoking 

cessation (before or during pregnancy) on risk of pregnancy 

complications or outcomes such as spontaneous abortion, 

placenta previa, placental abruption, preterm delivery, and 

premature rupture of membranes. This information could 

be used to help refine public health strategies for decreasing the contribution of maternal smoking to adverse pregnancy outcomes.

Smoking should continue to be examined in studies 

of birth defects, particularly in geographic areas in which 

smoking during pregnancy remains prevalent, as the evidence so far is suggestive, but not conclusive. These studies would be most beneficial if they also examine interactions with genetic polymorphisms (see below), requiring 

additional subjects and funding. Animal studies that better simulate smoke exposure would also be very useful in 

this regard.

Evidence is increasing that exposures during pregnancy may have long-lasting effects on offspring. Furthermore, developmental delays and disabilities are 

increasing in the population, so additional studies of 

smoking effects (in utero and postnatal exposure) on 

neurobehavioral endpoints, including cognition and 

behavior, are needed, perhaps as large cohort studies. 

In the context of some suggestive or early studies, it is 

important to pursue examination of in utero exposure to 

smoking and later reproductive effects in the offspring, 

including pubertal development, sperm quality, and 

female fertility. Studies of in utero exposure in offspring, 
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either as children or adults, are difficult to carry out 

logistically because of long follow-up times or lack of retrospective data on parental tobacco use or secondhand 

smoke exposure during pregnancy if adults are studied. 

Such studies should also consider postnatal secondhand 

smoke exposure. Studies in adult offspring would need 

to be limited to nonsmokers, while considering secondhand smoke exposure in adults as well, requiring larger 

numbers of study subjects for stratification. In addition, 

numerous other factors may affect these endpoints after 

birth. Because of some of these methodological difficulties, further studies on mechanisms related to endocrine function would help support causal relationships 

(see below).

Research on humans would be improved with measurement of a biomarker of exposure, such as cotinine. 

Studies tend to show higher cotinine levels in young 

children exposed to secondhand smoke relative to older 

children and adults, so studying the pharmacokinetics 

of cotinine in the very young (birth to five years) would 

be of interest to determine whether this is attributable to 

slower metabolism of nicotine and cotinine or to greater 

exposure to secondhand smoke.

Pathophysiological and Cellular/Molecular 

Mechanisms

Effects on Organ Systems

1. Smoking has often been considered antiestrogenic, 

but studies measuring hormone levels in nonpregnant women or in men do not support this hypothesis. Therefore, studies of effects of smoking and 

secondhand smoke exposure on levels of other hormones in males and females would help elucidate 

the mechanism of effects of smoking on reproductive 

function and some pregnancy outcomes.

2. Research is needed to better understand mechanisms 

underlying causal relationships between maternal 

smoking and placental damage such as placenta 

previa, placental abruption, preeclampsia, preterm 

delivery, and premature rupture of membranes. Specifically needed are studies

	 •	 to better characterize the effects of maternal

smoking on physiological transformation and on 

the development of the villous capillary system of 

the placenta;

	 •	 of the effects of maternal smoking on the balance

between pro- and antiangiogenic factors; and

	 •	 of the effects of maternal smoking on nutrient transport in uteroplacental circulation and 

the potential consequences for fetal growth 

and development.

3. The possible mechanisms of smoke exposure affecting 

organogenesis that may lead to birth defects require 

more research, particularly on the histopathologic 

changes in the brain and lung.

4. Research is needed to better define effects of active 

smoking on immunoregulation in general. In addition, research is needed to better understand the 

contribution of tobacco-related dysregulation of the 

immune response to adverse pregnancy outcomes, 

such as preterm delivery and preterm premature 

rupture of membranes, and to determine what mechanisms are involved, such as increased risk of infection of the upper genital tract or modification of the 

inflammatory response.

Molecular Mechanisms and 

Specific Toxicants

1. Cigarette smoke contains thousands of toxicants, but 

more data documenting exposure to toxicants in the 

fetus of maternal active and involuntary smokers are 

necessary to link effects of smoking to specific toxic 

mechanisms or models. Some of the primary toxicants 

of interest are heavy metals (e.g., lead, mercury, cadmium, arsenic), polycyclic aromatic hydrocarbons, 

solvents, and other less studied compounds such as 

pyrazines and phenols. Additional media could be 

used as substrate, including placenta, umbilical cord, 

amniotic fluid, urine excretion in the first days, and 

meconium for metals only (atomic absorption).

2. In addition, the bioavailability and bioaccumulation 

of these compounds (particularly metals) from inhalation of smoke in adults or children should be studied, including animal studies to interpret toxicologic 

data on these compounds.

3. Research is needed to establish whether deficiencies 

of micronutrients such as vitamin C and zinc contribute to adverse pregnancy outcomes and if mechanisms exist to compensate for the deficiencies, leading to better pregnancy outcomes.

4. Research on the effects of smoking and its components on DNA damage should be conducted.
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660 Chapter 9

5. Further studies that include information on genetic 

polymorphisms affecting drug- and carcinogenmetabolizing enzymes are critical to uncovering 

mechanisms of smoking effects in many areas, including birth defects, other adverse pregnancy outcomes, and developmental effects.

6. In addition, a potential genetic basis for the population of women who have difficulty quitting smoking during pregnancy, including polymorphisms for 

nicotine-metabolizing enzymes or for central nervous 

system receptors, should be investigated to develop 

new pharmacologic treatments.

Appendix 9.2

Ending the Tobacco Problem: A Blueprint for the Nation

Committee on Reducing Tobacco Use: Strategies, Barriers, and Consequences

Institute of Medicine, 2007

Richard J. Bonnie, Kathleen Stratton, and Robert B. Wallace, editors

Complete List of 

Recommendations

Strengthening Traditional Tobacco Control 

Measures

Recommendation 1: Each state should fund state tobacco 

control activities at the level recommended by the CDC 

[Centers for Disease Control and Prevention]. A reasonable target for each state is in the range of $15 to $20 per 

capita, depending on the state’s population, demography, 

and prevalence of tobacco use. If it is constitutionally permissible, states should use a statutorily prescribed portion 

of their tobacco excise tax revenues to fund tobacco control programs.

Recommendation 2: States with excise tax rates below the 

level imposed by the top quintile of states should also substantially increase their own rates to reduce smuggling 

and tax evasion. State excise tax rates should be indexed 

to inflation.

Recommendation 3: The federal government should substantially raise federal tobacco excise taxes, currently 

set at 39 cents a pack. Federal excise tax rates should be 

indexed to inflation.

Recommendation 4: States and localities should enact 

complete bans on smoking in all nonresidential indoor 

locations, including workplaces, malls, restaurants, and 

bars. States should not preempt local governments from 

enacting bans more restrictive than the state ban.

Recommendation 5: All health care facilities, including 

nursing homes, psychiatric hospitals, and medical units 

in correctional facilities, should meet or exceed JCAHO 

[Joint Commission on the Accreditation of Healthcare 

Organizations] standards in banning smoking in all 

indoor areas.

Recommendation 6: The American Correctional Association should require through its accreditation standards 

that all correctional facilities (prisons, jails, and juvenile 

detention facilities) implement bans on indoor smoking.

Recommendation 7: States should enact legislation 

requiring leases for multiunit apartment buildings and 

condominium sales agreements to include the terms governing smoking in common areas and residential units. 

States and localities should also encourage the owners of 

multiunit apartment buildings and condominium developers to include nonsmoking clauses in these leases and 

sales agreements and to enforce them.

Recommendation 8: Colleges and universities should ban 

smoking in indoor locations, including dormitories, and 

should consider setting a smoke-free campus as a goal. 

Further, colleges and universities should ban the promotion of tobacco products on campus and at all campussponsored events. Such policies should be monitored and 

evaluated by oversight committees, such as those associated with the American College Health Association.

Recommendation 9: State health agencies, health care 

professionals, and other interested organizations should 

undertake strong efforts to encourage parents to make 

their homes and vehicles smoke free.

Recommendation 10: States should not preempt local 

governments from restricting smoking in outdoor public 

spaces, such as parks and beaches.
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Recommendation 11: All states should license retail sales 

outlets that sell tobacco products. Licensees should be 

required to (1) verify the date of birth, by means of photographic identification, of any purchaser appearing to be 

25 years of age or younger; (2) place cigarettes exclusively 

behind the counter and sell cigarettes only in a direct 

face-to-face exchange; and (3) ban the use of self-service 

displays and vending machines. Repeat violations of laws 

restricting youth access should be subject to license suspension or revocation. States should not preempt local 

governments from licensing retail outlets that sell 

tobacco products.

Recommendation 12: All states should ban the sale and 

shipment of tobacco products directly to consumers 

through mail order or the Internet or other electronic systems. Shipments of tobacco products should be permitted 

only to licensed wholesale or retail outlets.

Recommendation 13: School boards should require all 

middle schools and high schools to adopt evidence-based 

smoking prevention programs and implement them with 

fidelity. They should coordinate these in-school programs 

with public activities or mass media programming, or 

both. Such prevention programs should be conducted 

annually. State funding for these programs should be 

supplemented with funding from the U.S. Department of 

Education under the Safe and Drug-Free School Act or by 

an independent body administering funds collected from 

the tobacco industry through excise taxes, court orders, or 

litigation agreements.

Recommendation 14: All physicians, dentists, and other 

health care providers should screen and educate youth 

about tobacco use during their annual health care visits 

and any other visit in which a health screening occurs. 

Physicians should refer youth who smoke to counseling 

services or smoking cessation programs available in the 

community. Physicians should also urge parents to keep 

a smoke-free home and vehicles, to discuss tobacco use 

with their children, to convey that they expect their children to not use tobacco, and to monitor their children’s 

tobacco use. Professional societies, including the American Medical Association, the American Nursing Association, the American Academy of Family Physicians, the 

American College of Physicians, and the American Academy of Pediatrics, should encourage physicians to adopt 

these practices.

Recommendation 15: A national, youth-oriented 

media campaign should be funded on an ongoing basis 

as a permanent component of the nation’s strategy to 

reduce tobacco use. State and community tobacco control programs should supplement the national media 

campaign with coordinated youth prevention activities. 

The campaign should be implemented by an established 

public health organization with funds provided by the 

federal government, public-private partnerships, or the 

tobacco industry (voluntarily or under litigation settlement agreements or court orders) for media development, 

testing, and purchases of advertising time and space.

Recommendation 16: State tobacco control agencies 

should work with health care partners to increase the 

demand for effective cessation programs and activities 

through mass media and other general and targeted public education programs.

Recommendation 17: Congress should ensure that stable 

funding is continuously provided to the national quitline network.

Recommendation 18: The Secretary of the U.S. Department of Health and Human Services [HHS], through the 

National Cancer Institute, the Centers for Disease Control 

and Prevention, and other relevant federal health agencies, should fund a program of developmental research 

and demonstration projects combining media techniques, 

other social marketing methods, and innovative approaches to disseminating smoking cessation technologies.

Recommendation 19: Public and private health care systems should organize and provide access to comprehensive smoking cessation programs by using a variety of 

successful cessation methods and a staged disease management model (i.e. stepped care), and should specify the 

successful delivery of these programs as one criterion for 

quality assurance within those systems.

Recommendation 20: All insurance, managed care, and 

employee benefit plans, including Medicaid and Medicare, 

should cover reimbursement for effective smoking cessation programs as a lifetime benefit.

Recommendation 21: While sustaining their own valuable 

tobacco control activities, state tobacco control programs, 

CDC, philanthropic foundations, and voluntary organizations should continue to support the efforts of community 

coalitions promoting, disseminating, and advocating for 

tobacco use prevention and cessation, smoke-free environments, and other policies and programs for reducing 

tobacco use.

Recommendation 22: Tobacco control programs should 

consider populations disproportionately affected by 

tobacco addiction and tobacco-related morbidity and 

mortality when designing and implementing prevention 

and treatment programs. Particular attention should be 

paid to ensuring that health communications and other 

materials are culturally-appropriate and that special outreach efforts target all high-risk populations. Standard 
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662 Chapter 9

prevention or treatment programs that are modified 

to reach high-risk populations should be evaluated 

for effectiveness.

Changing the Regulatory Landscape

Recommendation 23: Congress should repeal the existing 

statute preempting state tobacco regulation of advertising and promotion “based on smoking and health” and 

should enact a new provision that precludes all direct state 

regulation only in relation to tobacco product characteristics and packaging while allowing complementary state 

regulation in all other domains of tobacco regulation, 

including marketing and distribution. Under this 

approach, federal regulation sets a floor while allowing 

states to be more restrictive.

Recommendation 24: Congress should confer upon the 

FDA [U. S. Food and Drug Administration] broad regulatory authority over the manufacture, distribution, marketing, and use of tobacco products.

Recommendation 25: Congress should empower the 

FDA to regulate the design and characteristics of tobacco 

products to promote the public health. Specific authority 

should be conferred

	 •	 to require tobacco manufacturers to disclose to

the agency all chemical compounds found in both 

product and the product’s smoke, whether added 

or occurring naturally, by quantity; to disclose to 

the public the amount of nicotine in the product 

and the amount delivered to the consumer based 

on standards established by the agency; to disclose 

to the public research on their product, as well as 

behavioral aspects of its use; and to notify the agency whenever there is a change in a product;

	 •	 to prescribe cigarette testing methods, including

how the cigarettes are tested and which smoke constituents must be measured;

	 • to promulgate tobacco product standards, including 

reduction of nicotine yields and reduction or elimination of other constituents, wherever such a standard is found to be appropriate for protection of the 

public health, taking into consideration the risks 

and benefits to the population as a whole, including 

users and non-users of tobacco products; and

	 • to develop specific standards for evaluating novel 

products that companies intend to promote as 

reduced-exposure or reduced-risk products, and to 

regulate reduced-exposure and reduced-risk health 

claims, assuring that there is a scientific basis for 

claims that are permitted.

Recommendation 26: Congress should strengthen the 

federally mandated warning labels for tobacco products 

immediately and should delegate authority to the FDA 

to update and revise these warnings on a regular basis 

upon finding that doing so would promote greater public understanding of the risks of using tobacco products 

or reduce tobacco consumption. Congress should require 

or authorize the FDA to require rotating color graphic 

warnings covering 50 percent of the package equivalent to 

those required in Canada.

Recommendation 27: Congress should empower the FDA 

to require manufacturers to include in or on tobacco packages information about the health effects of tobacco use 

and about products that can be used to help people quit.

Recommendation 28: Congress should ban, or empower 

the FDA to ban, terms such as “mild,” “lights,” “ultralights,” and other misleading terms mistakenly interpreted by consumers to imply reduced risk, as well as other 

techniques, such as color codes, that have the purpose or 

effect of conveying false or misleading impressions about 

the relative harmfulness of the product.

Recommendation 29: Whenever a court or administrative agency has found that a tobacco company has made 

false or misleading communications regarding the effects 

of tobacco products, or has engaged in conduct promoting tobacco use among youth or discouraging cessation 

by tobacco users of any age, the court or agency should 

consider using its remedial authority to require manufacturers to include corrective communications on or with 

the tobacco package as well as at the point of sale.

Recommendation 30: Congress and state legislatures 

should enact legislation regulating the retail point of sale 

of tobacco products for the purpose of discouraging consumption of these products and encouraging cessation. 

Specifically:

	 •	 All retail outlets choosing to carry tobacco products

should be licensed and monitored. (See also youth 

access section in Chapter 5.)

	 • Commercial displays or other activity promoting 

tobacco use by or in retail outlets should be banned, 

although text-only informational displays (e.g., price 

or health-related product characteristics) may be 

permitted within prescribed regulatory constraints.
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	 • Retail outlets choosing to carry tobacco products 

should be required to display and distribute prescribed warnings about the health consequences 

of tobacco use, information regarding products 

and services for cessation, and corrective messages designed to offset misstatements or implied 

claims regarding the health effects of tobacco use 

(e.g., that “light” cigarettes are less harmful than 

other cigarettes).

	 •	 Retail outlets choosing to carry tobacco products should be required to allocate a proportionate amount of space to cessation aids and nicotine 

replacement products and, after regulatory clearance by the FDA or a designated state agency, to 

“qualifying” exposure-reduction products. (The FDA 

or a suitable state health agency should promulgate 

a list of “qualifying” exposure-reducing products.)

Recommendation 31: Congress should explicitly and 

unmistakably include production, marketing, and distribution of tobacco products on Indian reservations by 

Indian tribes within the regulatory jurisdiction of FDA. 

Authority to investigate and enforce the Jenkins Act should 

be transferred to the Bureau of Alcohol, Tobacco, Firearms 

and Explosives. State restrictions on retail outlets should 

apply to all outlets on Indian reservations.

Recommendation 32: State governments should develop 

and, if feasible, implement and evaluate legal mechanisms 

for restructuring retail tobacco sales and restricting the 

number of tobacco outlets.

Recommendation 33: Congress should empower the FDA 

to restrict outlets in order to limit access and facilitate 

regulation of the retail environment, and thereby protect 

the public health.

Recommendation 34: If most states fail to increase 

tobacco control funding and reduce variations in tobacco 

excise tax rates as proposed in Recommendations 1 and 

2, Congress should enact a National Tobacco Control 

Funding Plan raising funds through a per-pack remedial 

assessment on cigarettes sold in the United States. Part 

of the proceeds should be used to support national 

tobacco control programs and the remainder of the funds 

should be distributed to the states to subsidize state 

tobacco control programs according to a formula based on 

the level of state tobacco control expenditures and state 

tobacco excise rates. The plan should be designed to give 

states an incentive, not only to increase state spending on 

tobacco control, but also to raise cigarette taxes, especially in low-tax states. Congress should assure that any 

federal coordination mechanism affecting the coverage and collection of state tobacco excise taxes applies 

to Indian tribes.

Recommendation 35: Congress and state legislatures 

should enact legislation limiting visually displayed tobacco advertising in all venues, including mass media and at 

the point-of-sale, to a text-only, black-and-white format.

Recommendation 36: Congress and state legislatures 

should prohibit tobacco companies from targeting youth 

under 18 for any purpose, including dissemination of messages about smoking (whether ostensibly to promote or 

discourage it) or to survey youth opinions, attitudes and 

behaviors of any kind. If a tobacco company wishes to 

support youth prevention programs, the company should 

contribute funds to an independent non-profit organization with expertise in the prevention field. The independent organization should have exclusive responsibility for 

designing, executing, and evaluating the program.

Recommendation 37: The Motion Picture Association 

of America (MPAA) should encourage and facilitate the 

showing of anti-smoking advertisements before any film 

in which smoking is depicted in more than an incidental manner. The film rating board of the MPAA should 

consider the use of tobacco in the movies as a factor in 

assigning mature film ratings (e.g., an R-rating indicating 

Restricted: no one under age 17 admitted without parent 

or guardian) to films that depict tobacco use.

Recommendation 38: Congress should appropriate the 

necessary funds to enable the U.S. Department of Health 

and Human Services to conduct a periodic review of a 

representative sample of movies, television programs, 

and videos that are offered at times or in venues in which 

there is likely to be a significant youth audience (e.g., 15 

percent) in order to ascertain the nature and frequency of 

images portraying tobacco use. The results of these 

reviews should be reported to Congress and to the public.

Recommendation 39: State tobacco control agencies 

should conduct surveillance of tobacco sales and use and 

the effects of tobacco control interventions in order to 

assess local trends in usage patterns; identify special 

groups at high risk for tobacco use; determine compliance 

with state and local tobacco-related laws, policies, and 

ordinances; and evaluate overall programmatic success.

Recommendation 40: The Secretary of HHS, through FDA 

or other agencies, should establish a national comprehensive tobacco surveillance system to collect information 

on a broad range of elements needed to understand and 

track the population impact of all tobacco products and 
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664 Chapter 9

the effects of national interventions (such as attitudes, 

beliefs, product characteristics, product distribution and 

usage patterns, and marketing messages and exposures 

to them).

New Frontiers in Tobacco Control

Recommendation 41: Congress should direct the Centers 

for Disease Control and Prevention to undertake a major 

program of tobacco control policy analysis and development and should provide sufficient funding to support 

the program. This program should develop the next generation of macro-level simulation models to project the 

likely effects of various policy innovations, taking into 

account the possible initiatives and responses of the 

tobacco industry as well as the impacts of the innovations 

on consumers.

Recommendation 42: Upon being empowered to regulate 

tobacco products, the FDA should give priority to exploring the potential effectiveness of a long-term strategy for 

reducing the amount of nicotine in cigarettes and should 

commission the studies needed to assess the feasibility of 

implementing such an approach. If such a strategy appears 

to be feasible, the agency should develop a long-term plan 

for implementing the strategy as part of a comprehensive 

plan for reducing tobacco use.

Appendix 9.3 

Promoting Healthy Lifestyles: Policy, Program, and 

Personal Recommendations for Reducing Cancer Risk

President’s Cancer Panel

2006–2007 Annual Report

Recommendations Addressing Tobacco Use Prevention and Treatment; 

Environmental Tobacco Smoke Exposure

1. Ratify and fully implement the Framework Convention for 

Tobacco Control. Key provisions include: comprehensive bans 

on tobacco advertising, promotion, and sponsorship, larger 

and stronger warning labels on tobacco product packaging, 

provision of tobacco addiction treatment, disclosure of tobacco 

product ingredients, and public protection against environmental tobacco smoke exposure.

• President

• Congress

2. Authorize the Food and Drug Administration (FDA) to strictly 

regulate tobacco products and product marketing. FDA must 

receive sufficient funding and personnel to carry out this crucial role.

• President

• Congress

3. Increase the Federal excise tax on tobacco products. • Congress

4. Require all Federal facilities to be smoke-free. • Congress

• Federal agencies
A Vision for the Future 665

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

5. Reallocate existing National Cancer Institute, Centers for Disease Control and Prevention, and other Federal resources to 

better mirror the tobacco-related disease burden and capitalize 

on opportunities for progress.

• Congress

• Department of Health and Human Services

(National Institutes of Health, Centers for 

Disease Control and Prevention, Health 

Resources and Services Administration, 

Substance Abuse and Mental Health Services Administration)

• Veterans Administration

6. Add the conduct of meaningful tobacco-related activities to 

the evaluation criteria for NCI-designated Cancer Centers.

• National Cancer Institute

7. Reduce the influence of the tobacco industry:

	 •	 U.S. political parties and individual candidates should

refuse campaign contributions from the tobacco industry 

or its subsidiaries.

	 •	 Prohibit recipients of National Cancer Institute grants and

contracts from accepting money from tobacco companies 

or their subsidiaries. Other Federal agencies should consider similar requirements.

• All U.S. political parties

• National Cancer Institute

8. Strengthen anti-tobacco efforts at the state and local levels:

	 •	 Increase state commitment of Master Settlement Agreement funds and/or tobacco tax funds for tobacco control 

programs to at least the minimum level recommended by 

the Centers for Disease Control and Prevention for each 

state.

	 •	 Pass smoke-free ordinances for all public and private workplaces and public spaces.

	 •	 Encourage state governments to further increase tobacco

excise taxes to discourage purchase of cigarettes and other 

tobacco products.

	 •	 Require all public schools and universities to be 100 percent smoke-free.

	 •	 Require state-funded programs (e.g., Medicaid, corrections,

mental health) to offer smoking cessation services.

	 •	 Ensure that all state cancer control plans include a tobacco

control component.

• State and local governments

9. Develop and provide evidence-based multimedia curricula and 

educational materials in grades K-12 on the dangers of 

tobacco use and tobacco smoke exposure and the role of 

the tobacco industry in promoting tobacco use. Encourage 

colleges and universities to disseminate tested anti-tobacco 

messages for the 18 to 24 year-old age group through campus 

radio and television stations, Web sites, and print publications.

• Department of Health and Human Services

(National Institutes of Health, Centers for 

Disease Control and Prevention, Food and 

Drug Administration)

• State and local boards of education

• Non-governmental organizations

10. Cease including images of smoking in movies, television, 

music videos, video games, and other visual media with 

child, adolescent, and young adult audiences.

• All visual media producers
Surgeon General’s Report

666 Chapter 9

11. Prohibit smoking in and around the workplace. Support 

worker efforts to quit smoking; provide incentives for cessation.

• Employers

12. Make coverage of tobacco use cessation services and medications a standard benefit in all comprehensive health benefit 

packages.

• Health insurance companies

• Centers for Medicare and Medicaid Services

• Veterans Administration

• Civilian Health and Medical Program of the 

 Uniformed Services

• Indian Health Service

13. Incorporate smoking cessation services into the comprehensive care of cancer patients, survivors, and their family 

members.

• Cancer centers

• Academic and community hospitals and

 medical centers

• Private oncology offices/practices

• All publicly-funded clinics and health

 centers

14. Adopt the Agency for Healthcare Research and Quality 

Guidelines for Clinicians Treating Tobacco Use and 

Dependence as part of the standard of care for all health care 

providers.

• Primary and other health care providers

15. Quit smoking and use of any smokeless tobacco products. 

Prohibit smoking in the home and car. Protect children from 

exposure to smoking in movies and smoking role models. 

Patronize only smoke-free restaurants and other businesses.

• Individuals and families
A Vision for the Future 667

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

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List of Abbreviations

1-HOP 1-hydroxypyrene

4-ABP 4-aminobiphenyl

4-HNE 4-hydroxy-2-nonenal

8-oxo-dG 7-hydroxy-8-oxo-2’-deoxyguanosine

8-OH-dG 8-hydroxy-2’-deoxyguanosine

8-OH-DPAT 8-hydroxy-2-dipropylaminotetralin

AAT α1-antitrypsin

ACE angiotensin-converting enzyme

ACh acetylcholine

ACTH adrenocorticotropic hormone

ADMA asymmetric dimethylarginine

AGT O6-alkylguanine–DNA alkyltransferase

AH aryl hydrocarbon

AHH aryl hydrocarbon hydroxylase

AKT protein kinase B

AOR adjusted odds ratio

AP apurinic/apyrimidinic

AP-1 activator protein-1

APA American Psychiatric Association

APO apolipoprotein

APO A-I apolipoprotein A-I

APO B apolipoprotein B

APO E apolipoprotein E

ATP adenosine triphosphate

B[a]P benzo[a]pyrene

B[b]F benzo[b]fluoranthene

B[k]F benzo[k]fluoranthene

BAL bronchoalveolar lavage

BER base excision repair

BH BCL-2 homology

BMI body mass index 

BPDE benzo[a]pyrene-7,8-diol-9,10-epoxide

BSID Bayley Scales of Infant Development 

Ca2+ calcium ion

Cal/EPA California Environmental Protection Agency

CAM chorioallantoic membrane

CaMKII Ca2+ calmodulin-dependent protein kinase II

CAN Canadian Intense

CAT chloramphenicol acetyltransferase

CB1 cannabinoid subtype 1

CDC Centers for Disease Control and Prevention

CDK cyclin-dependent kinase

CETP cholesterol ester transfer protein

CHD coronary heart disease

CI confidence interval

CNS central nervous system

CO carbon monoxide

CO2 carbon dioxide

COPD chronic obstructive pulmonary disease

CPS-I Cancer Prevention Study I

CPS-II Cancer Prevention Study II

CREB cyclic adenosine monophosphate–response 

element binding protein

CRP C-reactive protein

CS conditioned stimulus

CSE cigarette smoke extract

CT computed tomography

CUZNSOD copper zinc superoxide dismutase

CVD cardiovascular disease

DEB diepoxybutane

DHBMA dihydroxybutyl mercapturic acid

DHβE [3H]dihydro-beta-erythroidine

dL deciliter

DMBA 7,12-dimethybenz[a]anthracene

DRC DNA repair capacity

DRZ diagonal radioactive zone

DSB double-strand break

DSBR double-strand break repair

DSM-III-R Diagnostic and Statistical Manual of Mental 

Disorders, 3rd ed. (rev)

DSM-IV Diagnostic and Statistical Manual of Mental 

Disorders, 4th ed.

EB 3,4-epoxybutene

ECSOD extracellular superoxide dismutase

EF etiologic fraction

ELF epithelial lining fluid

ENOS endothelial nitric oxide synthase

EPA U.S. Environmental Protection Agency

EPC endothelial progenitor cell

EPO eosinophil-specific peroxidase

ERK extracellular signal-regulated kinase

F-344 Fischer-344
Surgeon General’s Report

672

FDA U.S. Food and Drug Administration

Fe2+ ferrous ion

Fe3+ ferric ion

FEV1 forced expiratory volume in one second

FFA free fatty acid

FR fecundability ratio

FSH follicle-stimulating hormone

FTC U.S. Federal Trade Commission

FTND Fagerström Test for Nicotine Dependence

FTQ Fagerström Tolerance Questionnaire

FVC forced vital capacity

g gram

GABA γ-aminobutyric acid

GC gas chromatography

GCL glutamate cysteine ligase

GGR global genomic nucleotide excision repair

GLu-P-1 2-amino-6-methyldipyrido[1,2-a:3’,2’-d]

imidazole

GOLD Global Initiative for Chronic Obstructive 

Lung Disease

GPX glutathione peroxidase

GRX glutathione reductase

GSH glutathione

GSSG oxidized glutathione

GST glutathione-S-transferase

GTP guanosine triphosphate

H/R hypoxia/reperfusion

H2O water

H2O2 hydrogen peroxide

H2S hydrogen sulfide

HAT histone acetyltransferase

Hb hemoglobin

HbA1c hemoglobin A1c

HBEC human bronchial epithelial cell

HCA heterocyclic amine

hCG human chorionic gonadotropin

HCN hydrogen cyanide

HCR host cell reactivation

HDAC histone deacetylase

HDL high-density lipoprotein

HDLc high-density lipoprotein cholesterol

Hg mercury

HIV human immunodeficiency virus

HONC Hooked on Nicotine Checklist

HOX hypohalous acids

HPG hypothalamic-pituitary-gonadal

HPLC high-performance liquid chromatography

HR23B homologous recombinational repair group 

23B

IARC International Agency for Research on Cancer

IBF intervillous blood flow

ICAM intercellular adhesion molecule

ICD-10 International Statistical Classification of 

Diseases and Related Health Problems, Tenth 

Revision

Ig immunoglobulin

IgM immunoglobulin M

IL interleukin

INOS inducible nitric oxide synthase

IOM Institute of Medicine

ISO International Organization for 

Standardization

IUGR intrauterine growth restriction

IVF in vitro fertilization

kcal kilocalorie

kg kilogram

L liter

LBW low birth weight

LC liquid chromotography

LDL low-density lipoprotein

LDLc low-density lipoprotein cholesterol

LH luteinizing hormone

LMPCR ligation-mediated polymerase chain reaction

LOD logarithm of the odds

LPL lipoprotein lipase

LUC luciferase

m3 cubic meter

MAO monoamine oxidase

MAPK mitogen-activated protein kinase

MDM2 murine double minute 2

MDPH Massachusetts Department of Public Health

MEK mitogen-activated protein kinase kinase

mg milligram

mGluR2/3 metabotropic glutamate receptor subtype 2/3

mGluR5 metabotropic glutamate receptor subtype 5

MHBMA monohydroxybutenyl mercapturic acid

MI myocardial infarction

mL milliliter

mm millimeter

MMP matrix metalloproteinase
673

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

MMR mismatch repair

MMS methyl methanesulfonate

MNSOD manganese superoxide dismutase

MPEP 2-methyl-6-(phenylethynyl)pyridine

MPO myeloperoxidase

mRNA messenger RNA

MRP multidrug-resistance protein

MS mass spectrometry

MSCA McCarthy Scales of Children’s Abilities

MT1 membrane-type 1

MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide

μg microgram

μm micrometer

μmol micromole

N2 nitrogen

NAB N’-nitrosoanabasine

nAChR nicotinic acetylcholine receptor

NADPH reduced nicotinamide adenine dinucleotide 

phosphate

NAT N-acetyltransferase

NATB N’-nitrosoanatabine

NCI National Cancer Institute

NDMA N-nitrosodimethylamine

NER nucleotide excision repair

NF-κB nuclear factor-kappa B

ng nanogram

NHLBI National Heart, Lung, and Blood Institute

NIH National Institutes of Health

NK natural killer

nmol nanomole

NMTCA N-nitroso-2-methylthiazolidine 4-carboxylic 

acid

NNAL 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol

NNK 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone

NNN N’-nitrosonornicotine

NO nitric oxide

NO2 nitrogen dioxide

NOS nitric oxide synthase

NPRO N-nitrosoproline

NRC National Research Council 

NRT nicotine replacement therapy

NSCLC non-small-cell lung cancer

NST nonstress test

NTCA N-nitrosothiazolidine 4-carboxylic acid

O2 oxygen

O2•− superoxide anion

OH hydroxyl radical

ONOO− peroxynitrite

ONOOH peroxynitrous acid

OR odds ratio

p short arm of chromosome

PAD peripheral arterial disease

PAF platelet-activating factor

PAH polycyclic aromatic hydrocarbon

PAI-1 plasminogen activator inhibitor-1

PARP poly (adenosine diphosphate–ribose) 

polymerase

PAT poly AT insertion/deletion polymorphism

PCASRM Practice Committee of the American Society 

for Reproductive Medicine

PCNA proliferating cell nuclear antigen

p-CREB phosphorylated CREB

PdG 1,N2-propanodeoxyguanosine

PDK1 3-phosphoinositide–dependent protein 

kinase-1

PET positron emission tomography

pg picogram

pHeff effective pH

PhIP 2-amino-1-methyl-6-phenylimidazo[4,5-b]

pyridine

PHS U.S. Public Health Service

PI protease inhibitor

PI-3K phosphatidylinositol-3 kinase

PIP3 phosphatidylinositol 3,4,5-triphosphate

PKA protein kinase A

PKB protein kinase B (also known as AKT)

PKC protein kinase C

PKcs protein kinase catalytic subunit

PlGF placental growth factor

PMN polymorphonuclear neutrophil

pmol picomole

p-MPPI 4-(2’-methoxy-phenyl)-1-[2’-(n-2’’-pyridinyl)-

p-iodobenzamido]ethyl-piperazine

POB pyridyloxobutyl

pol polymerase

ppm parts per million

PPROM preterm premature rupture of membranes
Surgeon General’s Report

674

PREP potential reduced-exposure product

PRX peroxiredoxin

q long arm of chromosome

Q•− semiquinone radical

RCT reverse cholesterol transport

REC homologous recombination

RI resistance index

RNS reactive nitrogen species

ROS reactive oxygen species

RR relative risk

S/D systolic/diastolic

SAB spontaneous abortion

SARS severe acute respiratory syndrome

SCC squamous cell carcinoma

SCE sister chromatid exchange

SCENIHR Scientific Commission on Emerging and 

Newly Identified Health Risks

SCLC small-cell lung cancer

SD standard deviation

SES socioeconomic status

sFlt-1 soluble vascular endothelial growth factor 

receptor Flt-1

SGA small for gestational age

sICAM soluble intercellular adhesion molecule

SIDS sudden infant death syndrome

SNO S-nitrosothiol

SNP single nucleotide polymorphism

SOD superoxide dismutase 

S-PMA S-phenylmercapturic acid

STR short tandem repeat

sVCAM soluble vascular cell adhesion molecule

TBARS thiobarbituric acid reactive substances

TCR transcription-coupled repair

TFIIH transcription initiation factor IIH

TGFβ transforming growth factor-beta

TGRL triglyceride-rich lipoprotein

Th1 helper T-cell subset 1

Th2 helper T-cell subset 2

TIMP tissue inhibitor of metalloproteinase

Tmax time to reach maximum blood concentrations 

of nicotine

TNFα tumor necrosis factor-alpha

tPA tissue plasminogen activator

TPM total particulate matter

trans, anti-PheT r-1,t-2,3,c-4-tetrahydroxy-1,2,3,4-tetrahydrophenanthrene

Trp-P-1 3-amino-1,4-dimethyl-5H-pyrido[4,3-b]indole

Trp-P-2 3-amino-1-methyl-5H-pyrido[4,3-b]indole

TRX thioredoxin

TSNA tobacco-specific nitrosamine

tt-MA trans,trans-muconic acid

TxB2 thromboxane B2

TxM thromboxane metabolite

UCSF University of California at San Francisco

UGT uridine-5’-diphosphate-glucuronosyltransferase

US unconditioned stimulus

USDHEW U.S. Department of Health, Education, and 

Welfare

USDHHS U.S. Department of Health and Human 

Services

USPSTF U.S. Preventive Services Task Force

UV ultraviolet

VCAM vascular cell adhesion molecule

VEGF vascular endothelial growth factor

VEGFR vascular endothelial growth factor receptor

VLDL very-low-density lipoprotein

Vmax maximum velocity

VOC volatile organic compound

VTA ventral tegmental area

WHO World Health Organization

XP (A–G) xeroderma pigmentosum (groups A–G)

γGT γ-glutamyltranspeptidase
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

List of Tables and Figures

Chapter 1

Introduction, Evaluation of Evidence on Mechanisms 

of Disease Production, and Summary

Table 1.1 Four-level hierarchy for classifying the strength 

of causal inferences from available evidence 3

Table 1.2 Causal criteria 7

Figure 1.1 The health consequences causally linked to smoking and exposure to secondhand smoke 4

Figure 1.2 General schema for the causation of disease by 

tobacco smoke 5

Figure 1.3 Potential pathways and mechanisms for cardiovascular dysfunction mediated by cigarette 

smoking 6

Chapter 3

Chemistry and Toxicology of Cigarette Smoke 

and Biomarkers of Exposure and Harm

Table 3.1 Selected chronic carcinogenicity studies in mice 

and rats with inhalation exposure to cigarette 

smoke 64

Figure 3.1 Tobacco alkaloids 32

Figure 3.2 Structures of nicotine and minor alkaloid S(-)-Nmethylanabasine in tobacco leaf 33

Figure 3.3 Three forms of nicotine 33

Figure 3.4 Tobacco-specific nitrosamines 35

Figure 3.5 Priority environmental polycyclic aromatic hydrocarbons 38

Figure 3.6 Commonly studied aromatic amines in tobacco 

smoke 42

Figure 3.7 Primary heterocyclic amines in tobacco smoke

43

Chapter 4

Nicotine Addiction: Past and Present

Table 4.1 Criteria for substance (nicotine) dependence

106

Table 4.2 Questions, answers, and scoring for Fagerström 

Test for Nicotine Dependence and Fagerström 

Tolerance Questionnaire 107

Table 4.3 Measures of nicotine addiction 109

Table 4.4 Bioavailability and amount of nicotine absorbed 

per unit dose and time to maximum venous blood 

concentration of nicotine by product 113

Table 4.5 Genetic linkage studies of smoking behavior phenotypes 139

Table 4.6 Studies of candidate genes for nicotine metabolism and smoking behavior 142

Table 4.7 Studies of candidate genes for neuronal nicotine 

receptors and smoking behavior 144

Table 4.8 Studies of candidate genes for dopamine and 

smoking behavior 146

Table 4.9 Studies of candidate genes for serotonin and 

smoking behavior 150

Table 4.10 Other studies of candidate genes for smoking 

behavior 152

Table 4.11 Lifetime and current prevalence of nicotine 

dependence in population studies in the United 

States 163

Table 4.12 Prevalence of selected symptoms of nicotine 

dependence reported in selected studies 166

Figure 4.1 Venous blood concentrations of nicotine over 

time for various nicotine delivery systems 114

Figure 4.2 Mean plasma nicotine concentrations after 

administration of each of four smokeless tobacco 

products or mint snuff 115

Figure 4.3 Associative learning processes in nicotine addiction 121

Figure 4.4 Neural pathways for γ-aminobutyric acid, glutamate, dopamine, and excitatory neurotransmitters 127

Figure 4.5 Cumulative incidence curves of daily smoking 

and nicotine dependence in the National Comorbidity Survey 165
Surgeon General’s Report

676

Figure 4.6 Individual estimated slopes in craving ratings 

over three weeks prequit, from just before to just 

after midnight on the quit date, and over three 

weeks postquit 175

Figure 4.7 Reactions for the three-week period before the 

quit date and the three-week period after the quit 

date 176

Figure 4.8 Withdrawal severity and lapse behavior among 

smokers who abstained for the first five days of a 

quit attempt 177

Figure 4.9 Negative affect in the days and hours preceding 

the first lapse for smokers who attributed their 

first lapse to a stressor or bad mood (stress trigger) or to some other type of event (other trigger) 178

Chapter 5

Cancer

Table 5.1 IARC evaluations of carcinogens in mainstream 

cigarette smoke 228

Table 5.2 DNA adducts in human lung tissue 243

Table 5.3 Selected gene polymorphisms evaluated by 

molecular epidemiology investigations for relationship to lung cancer through variation in susceptibility to carcinogens in tobacco smoke 246

Table 5.4 Human DNA glycosylases 253

Table 5.5 Factors involved in nucleotide excision repair 

activity in humans 257

Table 5.6 Select candidate genes and polymorphisms implicated in repair of tobacco-induced DNA damage 262

Table 5.7 Translesion-specialized DNA polymerases (pol) 

and activities on various DNA lesions 270

Table 5.8 Mutational specificity of selected DNA adducts 

derived from tobacco smoke 271

Table 5.9 Frequency of mutation or deletion of tumor-suppressor genes in lung cancer 274

Table 5.10 Frequency of gene amplification and increased 

expression of genes in lung cancer 276

Table 5.11 Pathways altered through gene silencing by promoter methylation 293

Table 5.12 Carcinogens and tobacco-induced cancers 299

Figure 5.1 Link between cigarette smoking and cancer 

through carcinogens in tobacco smoke 226

Figure 5.2 Chemical structures of biomarkers of carcinogen 

exposure 231

Figure 5.3 Metabolism of six carcinogens in tobacco smoke 

that produce DNA adducts identified in the lungs 

of smokers 236

Figure 5.4 Mechanism of base excision repair 255

Figure 5.5 Mechanism of nucleotide excision repair: (A) 

global genomic repair; (B) transcription-coupled 

repair 256

Figure 5.6 Mechanism of mismatch repair 258

Figure 5.7 Proposed mechanism of homologous recombination 260

Figure 5.8 Proposed mechanism of nonhomologous endjoining 261

Figure 5.9 Model of mechanism for mammalian translesion 

synthesis 270

Figure 5.10 Patterns of TP53 gene mutations and percentage 

of G→T transversion mutations in human lung 

cancers 278

Figure 5.11 Patterns of TP53 gene mutations and percentage 

of G→T transversion mutations in different histologic types of lung cancer 280

Figure 5.12 Concordance between codon distribution of 

G→T transversions along TP53 gene in lung 

cancers (top) and distribution of adducts of 

benzo[a]pyrene-7,8-diol-9,10-epoxide (BPDE)–

DNA adducts in bronchial epithelial cells (bottom) 281

Figure 5.13 Patterns of TP53 gene mutations and percentage 

of G→T transversions in smoking-associated cancers other than lung cancer 282

Figure 5.14 Tobacco-associated suppression of proapoptotic 

proteins and tumor-suppressor proteins 285

Figure 5.15 Protein-signaling pathways deregulated in lung 

cancer 286
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Chapter 6

Cardiovascular Diseases

Table 6.1 Rate ratios for coronary heart disease among 

White men, by age and duration of cigarette 

smoking 359

Table 6.2 Death rates and rate ratios for death from coronary heart disease among men, by age and duration of smoking by number of cigarettes smoked 

per day 360

Table 6.3 Biomarkers of risk for cardiovascular disease from 

exposure to cigarette smoke 392

Table 6.4 Randomized controlled trials of counseling for 

smokers hospitalized with cardiovascular disease 396

Table 6.5 Randomized controlled trials of pharmacologic 

interventions for smoking cessation in patients 

with cardiovascular disease 397

Table 6.6 Smoking reduction and cardiovascular disease endpoints: biomarkers and clinical outcomes 404

Figure 6.1 Relative and excess death rate for coronary heart 

disease among men, by age group 356

Figure 6.2 Age-specific excess death rates among male 

smokers for coronary heart disease, lung cancer, 

chronic obstructive pulmonary disease (COPD), 

and cerebrovascular disease 357

Figure 6.3 Dose-response relationship between number of 

cigarettes smoked per day and relative risk of 

ischemic heart disease 358

Figure 6.4 Plasma nicotine and carboxyhemoglobin concentrations throughout a day of cigarette smoking 364

Figure 6.5 Overview of mechanisms by which cigarette smoking causes an acute cardiovascular event 366

Figure 6.6 Potential sites of actions and mechanisms of 

effects of smoking on platelets 376

Figure 6.7 Potential sites of effects of smoking on thrombosis through oxidative stress and other mechanisms 378

Chapter 7

Pulmonary Diseases

Table 7.1 Causal conclusions on smoking and diseases 

of the respiratory tract other than lung cancer: 

the 2004 and 2006 reports of the Surgeon General 438

Table 7.2 Definitions for principal nonmalignant respiratory diseases caused by cigarette smoking 439

Table 7.3 Selected components of cigarette smoke and 

potential mechanisms of injury 439

Table 7.4 Measurements of oxidative stress 463

Table 7.5 Studies of oxidative stress in smokers 464

Table 7.6 Studies of oxidative stress in animals exposed to 

smoke 466

Table 7.7 In vitro studies of oxidative stress 468

Table 7.8 Genomewide linkage analysis studies in generalpopulation samples and in families with chronic 

obstructive pulmonary disease (COPD) 478

Table 7.9 Replicated candidate gene associations in chronic 

obstructive pulmonary disease (COPD) 480

Table 7.10 Matrix metalloproteinases in emphysema 489

Table 7.11 Mouse models of overexpression of a protein leading to emphysema 492

Table 7.12 Effects of protease inhibitors in experimental 

smoke-induced emphysema 493

Figure 7.1 Lung defenses 440

Figure 7.2 Fractional deposition of inhaled particles in the 

human respiratory tract 441

Figure 7.3 Comparison of normal bronchial gland (A) with 

enlarged bronchial glands (B and C) from a 

patient with chronic bronchitis 442

Figure 7.4 Natural history of decline in forced expiratory volume with aging measured in a group of working 

men in West London over about six years 444

Figure 7.5 Nature of an obstruction in the small conducting 

airways (<2 millimeters in diameter) 445
Surgeon General’s Report

678

Figure 7.6 Dose-response relationship between level of 

smoking and the percentage of 408 patients in the 

St. Paul’s Lung Study with morphologic evidence 

of significant emphysema in their lungs 446

Figure 7.7 Postmortem bronchogram performed on the 

lungs of a person with centrilobular emphysema 447

Figure 7.8 Details of centrilobular emphysema lesions 448

Figure 7.9 Cut surface of lungs removed from two patients 

with different forms of emphysema before receiving a lung transplant 449

Figure 7.10 Innate and adaptive immune system of the lung, 

including the mucous production and clearance 

apparatus, the epithelial barrier, and the inflammatory immune response 450

Figure 7.11 Lymphoid collections within lung tissue 452

Figure 7.12 Persistent innate and adaptive immune inflammatory response in alveolar tissue 454

Figure 7.13 Remodeling process after a single clean surgical 

wound 455

Figure 7.14 Diagram based on three-dimensional reconstructions of serial electron micrographs illustrating how inflammatory immune cells navigate 

through interstitial space of alveolar wall 456

Figure 7.15 Formation of reactive oxygen species 458

Figure 7.16 Synthesis of nitric oxide (NO) and related products 459

Figure 7.17 Oxidant and antioxidant systems in the lungs

460

Figure 7.18 Pathogenesis of smoking-induced pulmonary 

emphysema 488

Chapter 8

Reproductive and Developmental Effects

Table 8.1 Association of adult cigarette smoking and in 

utero exposure to cigarette smoke with semen 

parameters and fertility in adults 528

Table 8.2 Association between maternal smoking and spontaneous abortion (SAB), 1998–2006 532

Table 8.3 Association between maternal smoking and orofacial clefts (OFCs), 1999–2009 542

Table 8.4 Association between maternal smoking and cardiovascular malformations, by phenotype, 1999–

2008 546

Table 8.5 Association between maternal smoking and noncardiovascular congenital malformations, by type 

of malformation, 1998–2008 548

Table 8.6 Association between smoking and reproductive 

hormones in women 558

Table 8.7 Association between smoking and reproductive 

hormones in healthy men 562

Table 8.8 Basal maternal and fetal cardiovascular effects of 

smoking 569

Table 8.9 Maternal and fetal cardiovascular effects: radioisotope studies of placental intervillous blood flow 

(IBF) conducted before and after smoking 570

Table 8.10 Acute maternal and fetal cardiovascular effects of 

smoking 571

Table 8.11 Animal and in vitro studies on association 

between maternal smoking and congenital abnormalities with relevant genetic and/or molecular 

hypotheses 578

Table 8.12 Reproductive and developmental effects of polycyclic aromatic hydrocarbons (PAHs), by endpoint 590

Table 8.13 Studies of interactions between genotype and 

exposure to tobacco related to oral clefting 602

Table 8.14 Decreased birth weight, preterm delivery, intrauterine growth retardation, and neonatal oxidative damage: interactions between host genotype 

and exposure to tobacco smoke 604

Chapter 9

A Vision for the Future

Table 9.1 Behavioral indicators of addiction potential of a 

drug or addiction to a drug 656

Figure 9.1 Effects on survival of stopping smoking cigarettes 

at ages 25–34 years (effect from age 35), ages 

35–44 years (effect from age 40), ages 45–54 years 

(effect from age 50), and ages 55–64 years (effect 

from age 60) 649

Figure 9.2 Molecular-profiling approaches to the development of personalized therapy 650
679

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Definitions and Alternative Nomenclature of Genetic Symbols Used in This Report

Throughout this report, genes are represented by their abbreviations in italics. In many cases, proteins and enzymes related to these 

genes have the same abbreviation, presented in roman type. Definitions, alternative genetic symbols, related proteins and enzymes, 

and polymorphisms and variant genotypes are listed alphabetically by gene abbreviation.

Gene symbol 

used in this 

report Definition

Alternative 

gene symbol Related protein/enzyme

Polymorphism/variant 

genotype

5HTT serotonin transporter SLC6A4, 

5HTTLPR

5HTT, SERT, SLC6A4 LPR; VNTR; 5HTTLPR

ADPRT poly (ADP-ribose) polymerase 

family, member 1 

PARP1 ADPRT; PARP1 VAL762ALA; PRO882LEU; 

CYS908TYR

AGT O6-alkylguanine–DNA 

alkyltransferase 

   AGT ILE143VAL; GLY160ARG

ANKK1 ankyrin repeat and kinase 

domain containing 1 

   ANKK1, protein kinase PKK2 GLU713LYS (caused by 

DRD2 *TAQ1A system)

APAF1 apoptotic peptidase activating 

factor 1 

   APAF1   

APEX1 APEX nuclease 

(multifunctional DNA repair 

enzyme) 1 

   APEX1 GLU148ASP (T11865G)

AREG amphiregulin (schwannomaderived growth factor) SDGF AREG, SDGF, CRDGF 

(colorectum cell-derived 

growth factor)

  

ARP arginine-rich protein ARMET ARP, ARMET (argininerich mutated in early stage 

tumors)

  

ATM ataxia telangiectasia mutated TEL1 ATM; TEL1 (telomere 

maintenance 1)

  

BAX BCL2-associated X protein    BAX   

BRAF v-raf murine sarcoma viral 

onco homolog B1 

   BRAF, B-RAF proto-oncogene 

serine/threonine-protein 

kinase (p94)

  

BRCA2 breast cancer 2, early onset    BRCA2, breast cancer 

susceptibility protein 

HIS372ASN (T27113G), 

ILE3412VAL (G93268A)

C-FOS v-fos FBJ murine osteosarcoma 

viral oncogene homolog

FOS FOS, C-FOS   

C4A complement component 4A 

(Rodgers blood group) 

   C4A haplotype

C4B complement component 4B 

(Childo blood group) 

   C4B haplotype

CASPASE-3 cysteine-aspartic acid 

protease-3

   CASPASE-3   

CASPASE-8 cysteine-aspartic acid 

protease-8 

   CASPASE-8   
Surgeon General’s Report

680

Gene symbol 

used in this 

report Definition

Alternative 

gene symbol Related protein/enzyme

Polymorphism/variant 

genotype

CCK cholecystokinin    CCK C-45T promoter 

polymorphism in SP1 

binding region of CCK

gene

CCKAR cholecystokinin A receptor CCK1-R CCKAR, CCK1-R 

(cholecystokinin-1 receptor)

T779C, VAL365ILE

CCND1 G1/S-specific cyclin D1    CCND1 G870A, *A/*A, *G/*A, 

*G/*G

CCNH cyclin H    CCNH, cyclin-dependent 

kinase-activating kinase

VAL270ALA 

CD14 CD14 molecule    CD14 molecule; CD14 

antigen

C-159T (promoter 

polymorphism)

CDK4 cyclin-dependent kinase 4    CDK4, cell division kinase 4   

CDKN2A cyclin-dependent kinase 

inhibitor 2A 

   CDKN2A, P16   

C-HA-RAS v-Ha-ras Harvey rat sarcoma 

viral oncogene homolog

C-HRAS, 

HRAS

C-HRAS, HRAS1 

proto-oncoprotein

  

CHFR checkpoint with forkhead and 

ring finger domains

   CHFR, mitotic checkpoint 

protein

  

CHRNA3 cholinergic receptor, nicotinic, 

a3

   CHRNA3   

CHRNA4 cholinergic receptor, nicotinic, 

a4 

   CHRNA4, α4 nAChR, 

nicotinic acetylcholine 

receptor α4 subunit

SNP RS3746372 (*1); 

haplotype

CHRNA5 cholinergic receptor, nicotinic, 

a5 

   CHRNA5, nicotinic 

acetylcholine receptor α5 

subunit, α5 nAChR

SNP RS16969968

(CHRNA5); SNPs 

RS8023462 and RS1948

(CHRNA5/A3/B4 cluster)

CHRNA7 cholinergic receptor, nicotinic, 

a7

   CHRNA7, nicotinic 

acetylcholine receptor α7 

subunit, α7 nAChR

D15S1360 (a microsatellite 

polymorphic marker in 

INTRON 2) exhibited seven 

different dinucleotide 

repeat lengths (99, 109, 

111, 113, 115, 117, and 125 

bp), the major alleles are 

*113 and *115 (*113/*113, 

*113/*115, *115/*115)

CHRNB2 cholinergic receptor, nicotinic, 

b2 (neuronal) 

   CHRNB2, nicotinic 

acetylcholine receptor β2 

subunit, β2 nAChR

multiple SNPs; haplotype

CHRNB3 cholinergic receptor, nicotinic, 

b3

   CHRNB3   
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Gene symbol 

used in this 

report Definition

Alternative 

gene symbol Related protein/enzyme

Polymorphism/variant 

genotype

CHRNB4 cholinergic receptor, nicotinic, 

b4

   CHRNB4   

C-MYC avian myelocytomatosis viral 

oncogene homolog

MYC C-MYC, myc proto-oncogene 

protein

  

COMT catechol-O-methyltransferase    COMT A1947G, *A, *G, 

VAL158MET

COX-1 cyclooxygenase-1    COX-1   

COX-2 cyclooxygenase-2    COX-2   

CYP17A1 cytochrome P-450, family 17, 

subfamily A, polypeptide 1 

   CYP17A1   

CYP1A1 cytochrome P-450, family 1, 

subfamily A, polypeptide 1 

   CYP1A1, MSPI *MSPI (*A/*a, *a/*a), 

ILE462VAL

CYP2A13 cytochrome P-450, family 2, 

subfamily A, polypeptide 13 

   CYP2A13 ARG257CYS (C3375T, 

*C/*T, *T/*T)

CYP2A6 cytochrome P-450, family 2, 

subfamily A, polypeptide 6

   CYP2A6 *1 (wild type), *1A, *1B, 

*2, *3, *4, *4A, *4B, *4C, 

*4D, *5, *6, *7, *8, *9, 

*10, *12, *16, *NULL, 

*DEL

CYP2B6 cytochrome P-450, family 2, 

subfamily B, polypeptide 6

   CYP2B6 *5 (C1459T=ARG487CYS); 

*6 (G516T=GLN172HIS); 

*2 (C64T=ARG22CYS); 

*3 (C777A=SER259ARG); 

*4 (A785G=LYS262ARG)

CYP2D6 cytochrome P-450, family 2, 

subfamily D, polypeptide 6 

   CYP2D6 *3, *4A, *5

CYP2E1 cytochrome P-450, family 2, 

subfamily E, polypeptide 1 

   CYP2E1 *1C, *1D, *DRA1, *RSA1

DAPK1 death-associated protein 

kinase 1 

DAPK DAPK1, DAPK   

DAT dopamine transporter DAT1 DAT, DAT1 VNTR

DDC dopa decarboxylase (aromatic 

l-amino acid decarboxylase) 

AADC DDC, AADC haplotype

DLC1 deleted in liver cancer 1    DLC1   

DRD1 dopamine receptor D1    DRD1 *DDE1

DRD2 dopamine receptor D2    DRD2 *TAQ1A (*A), *TAQ1B, 

-141C *INS/*DEL, *FOK1, 

*INTRON 2, *MBO1
Surgeon General’s Report

682

Gene symbol 

used in this 

report Definition

Alternative 

gene symbol Related protein/enzyme

Polymorphism/variant 

genotype

DRD4 dopamine receptor D4    DRD4 VNTR

DRD5 dopamine receptor D5    DRD5 haplotype

DßH dopamine beta hydroxylase    DβH G1368A, C1021T, *A allele

(G444A)

E-CADHERIN cadherin 1, type 1, E-cadherin 

(epithelial) 

    E-CADHERIN, calciumdependent adhesion protein, 

epithelial

  

EGFR epidermal growth factor 

receptor (erythroblastic 

leukemia viral (v-erb-b) onco 

homolog, avian)

   EGFR   

ELA2 elastase, neutrophil expressed ELANE ELA2   

EN2 engrailed homeobox 2 EN-2 EN2   

ENOS endothelial nitric oxide 

synthase 

NOS3 ENOS, NOS3 *A allele (a quadruple 

repeat of a 27 base-pair 

sequence in INTRON 4), 

GLU298ASP (*ASP298)

EPHX1 gene of epoxide hydrolase 1, 

microsomal (xenobiotic)

MEH EPHX1, MEH microsomal 

epoxide hydrolase

EXON 3 SNP, EXON 4

SNP, EXONs 3-4 SNP 

haplotypes, (T → C) 

TYR113HIS (*H), (A → G) 

HIS139ARG

ERCC1 excision repair crosscomplementing rodent repair 

deficiency, complementation 

group 1 (includes overlapping 

antisense sequence)

   ERCC1   

ESR1 estrogen receptor 1    estrogen receptor α *XBAL (c.454-351A → G), 

*PVULL (c.454-397T → C)

FAS Fas (TNF receptor superfamily, 

member 6) 

   FAS   

FHIT fragile histidine triad    FHIT, FRA3B   

FMS colony stimulating factor 1 

receptor

CSF1R, 

C-FMS, 

CD115, FIM2, 

CSFR

CSF1R, C-FMS, CD115, 

FIM2, CSFR

  

GABARAP GABA receptor-associated 

protein 

   GABARAP   

GABAB2 γ-aminobutyric acid type B 

receptor 2 

   GABAB2 haplotype
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How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Gene symbol 

used in this 

report Definition

Alternative 

gene symbol Related protein/enzyme

Polymorphism/variant 

genotype

GC group-specific component 

(vitamin D binding protein) 

   GC *1S (416GLU, 420THR), 

*1F (416ASP, 420THR), 

*1S/*1F, *2 (416ASP, 

420LYS), haplotype

GPX glutathione peroxidase    GPX   

GSTA1 glutathione-S-transferase 1a    GSTA1   

GSTM1 glutathione-S-transferase μ1    GSTM1 *NULL, *DEL

GSTP1 glutathione-S-transferase p1    GSTP1 ILE105VAL, *ILE/*ILE, 

*ILE/*VAL, ALA114VAL, 

*ALA/*ALA, *ALA/*VAL

GSTT1 glutathione-S-transferase q1    GSTT1 *NULL, *DEL

H-CADHERIN cadherin 13, H-cadherin 

(heart) 

CDH13 H-CADHERIN, CDH13   

HER-2/NEU v-erb-b2 erythroblastic 

leukemia viral oncogene 

homolog 2, neuro/glioblastoma 

derived oncogene homolog 

(avian)

ERBB2 HER-2/NEU, erb B2 c-erb B2/

neu protein, HER-2(human 

epidermal growth factor 

receptor 2)

  

HPRT hypoxanthine 

phosphoribosyltransferase

   HPRT   

IL-1ß interleukin-1b    IL-1β C-31T (TATA Box), *-31C, 

*-31T

JUN jun oncogene    JUN   

KRAS v-Ki-ras2 Kirsten rat sarcoma 

viral oncogene homolog 

    KRAS   

LAMA3 laminin, α3    LAMA3   

LAMB3 laminin, β3    LAMB3   

LAMC2 laminin, γ2    LAMC2   

LIG1 ligase I, DNA, ATP-dependent    LIG1 ALA170ALA (A → C), 

ASP802ASP (C → T), 

ALA814ALA (C → G)

LIG4 ligase IV, DNA, ATP-dependent    LIG4 ALA3ALA (C8T, cDNA), 

THR9ILE (C27T, cDNA)

LKB1/STK11 serine/threonine kinase 11    LKB1, STK11   

LMYC v-myc myelocytomatosis viral 

onco gene homolog 1, lung 

carcinoma derived 

L-MYC, 

MYCL1

L-MYC, LMYC, MYCL1   

MAOA monoamine oxidase A    MAOA silent C1460T (EXON 14), 

VNTR
Surgeon General’s Report

684

Gene symbol 

used in this 

report Definition

Alternative 

gene symbol Related protein/enzyme

Polymorphism/variant 

genotype

MAOB monoamine oxidase B    MAOB A644G (*A,*G)

MBD4 methyl-CpG binding domain 

protein 4 

   MBD4 SER342PRO (T → C), 

GLU346LYS (G → A)

MGMT O6-methylguanine-DNA 

methyltransferase 

   MGMT LEU84PHE, ILE143VAL

MMP-1 matrix metallopeptidase 1 

(interstitial collagenase) 

   MMP-1   

MMP-12 matrix metallopeptidase 12 

(macrophage elastase)

   MMP-12   

MPO myeloperoxidase    MPO   

MSX1 msh homeobox 1    MSX1 haplotype (intronic CA

repeat), *X1.3/*X1.3, 

*X2.4/*X2.4, *2 (rare 

allele)

MUC5AC mucin 5AC, oligomeric 

mucus/gel-forming

   MUC5AC   

MUTYH mutY homolog (E. coli)    MUTYH, mutY DNA 

glycosylase, A/G-specific 

adenine DNA glycosylase

GLN335HIS (G → C)

MYO18B myosin XVIIIB    MYO18B   

NAT1 N-acetyltransferase 1    NAT1, arylamine 

N-acetyltransferase 1

1088 *A/*A (T1088A), 

1095 *A/*A (C1095A)

NAT2 N-acetyltransferase 2    NAT2, arylamine 

N-acetyltransferase 2

ILE114THR (T → C), 

LYS161LYS (C → T), 

LYS268ARG (A → G), 

ARG197GLN (G → A), 

TYR94TYR (C → T), 

GLY286GLU (G → A), 

*4/*4 (wild type)

NBS1 Nijmegen breakage syndrome 1 NBN NBS1, NBN, nibrin GLN185GLU (C → G)

N-MYC v-myc myelocytomatosis 

viral related oncogene, 

neuroblastoma derived (avian)

NMYC, MYCN N-MYC, NMYC, MYCN, 

N-myc proto-oncogene 

protein

  

NORE1A RAS association (RALGDS/AF6) domain family member 5 RASFF5 NORE1A, RASFF5   

NRXN1 neurexin 1    NRXN1   

NRXN3 neurexin 3    NRXN3   

NTRK2 neurotrophic tyrosine kinase, 

receptor, type 2 

   NTRK2   
685

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Gene symbol 

used in this 

report Definition

Alternative 

gene symbol Related protein/enzyme

Polymorphism/variant 

genotype

OGG1 8-oxoguanine DNA glycosylase    OGG1 SER326CYS (C → G), 

326*CYS/*CYS, 

326*SER/*SER 

OPRM1 opioid receptor, μ1    OPRM1 ASN40ASP (A118G), 

*ASP40, *ASN40 

P14ARF cyclin-dependent kinase 

inhibitor 2A (CDKN2A) 

P14 P14, P14ARF (the alternate 

reading frame products of 

CDKN2A gene)

  

P16 cyclin-dependent kinase 

inhibitor 2A (CDKN2A) 

P16INK4A P16, P16INK4A (the major 

product of CDKN2A gene)

  

P21 cyclin-dependent kinase 

inhibitor 1A

P21, CDNK1A, 

CIP1, WAF1, 

SDI1

P21, CDNK1A, CIP1, WAF1, 

SDI1

SER31ARG

P53 tumor suppressor    P53 ARG72PRO (G → C), 

72*ARG/*PRO, 

72*PRO/*PRO, *MSPI 

(INTRON 6), 16 bp 

insertion (INTRON 3)

P73 tumor protein gene 73 TP73 P73, TP73 *GC/*GC, *AT/*AT, 

*GC/*AT (G4A, C14T in 

EXON 2)

PARKIN Parkinson disease (autosomal 

recessive, juvenile) 2, parkin 

PARK2 PARKIN (ligase)   

PAX5 α paired box gene 5 BSAP (B-cell 

specific 

activator) α

PAX5 α (one of the products 

of PAX5 gene), BSAP (B-cell 

specific activator protein) α

  

PAX5 ß paired box gene 5 BSAP (B-cell 

specific 

activator) β

PAX β (one of the products 

of PAX5 gene), BSAP (B-cell 

specific activator protein) β

  

PCMVCAT a plasmid construct 

containing the reporter 

gene CAT (chloramphenicol 

acetyltransferase) driven 

by CMV (cytomegalovirus) 

promoter

   PCMVCAT, chloramphenicol 

acetyltransferase as a reporter

  

PLAP placental alkaline phosphatase ALPP PLAP, ALPP alkaline 

phosphatase, placental 

(Regan isozyme)

*1/*1, *2/*2

POLD1 polymerase (DNA directed), 

delta 1, catalytic subunit 

125kDa 

   POLD1 ARG19HIS (G → A), 

HIS119ARG (A → G), 

SER173ASN (A → G)
Surgeon General’s Report

686

Gene symbol 

used in this 

report Definition

Alternative 

gene symbol Related protein/enzyme

Polymorphism/variant 

genotype

PTEN phosphatase and tensin 

homolog 

   PTEN, deleted on 

chromosome 10

this gene may be deleted 

on chromosome 10 (10q23) 

with the development of 

cancers

RAD23B RAD23 homolog B 

(S. cerevisiae) 

   RAD23B, UV excision repair 

protein RAD23 homolog B, 

XP-C repair complementing 

protein

ALA249VAL (C → T)

RAD4 RAD4 gene of S. cerevisiae    RAD4, S. cerevisiae DNA 

damage recognition and 

repair protein

  

RAD50 RAD50 gene homolog 

(S. cerevisiae)

   RAD50 (human) ARG1111ILE (G3374T, 

cDNA)

RAD51 RAD51 homolog (S. cerevisiae)    RAD51   

RAD52 RAD52 homolog (S. cerevisiae)    RAD52

RAD54L RAD54 homolog (S. cerevisiae) S. cerevisiae

RAD50 gene 

homolog

RAD54L ARG374SER (G1222C, 

cDNA)

RASSF1A Ras association (RalGDS/AF-6) 

domain family member 1 (A 

isoform) 

   RASSF1A   

RASSF2 Ras association (RalGDS/AF-6) 

domain family member 2 

   RASSF2   

RASSF4 Ras association (RalGDS/AF-6) 

domain family member 4 

   RASSF4, tumor suppressor 

protein

  

RB retinoblastoma 1 tumor 

suppressor 

RB1 RB, RB1   

SERPINA1 serpin peptidase inhibitor, 

clade A (a-1 antiproteinase, 

antitrypsin), member 1 

   SERPINA1, AAT protein *M, *S, *Z, *NULL

SERPINA3 serpin peptidase inhibitor, 

clade A (a-1 antiproteinase, 

antitrypsin), member 3 

   SERPINA3, ACT protein PRO229ALA, LEU55PRO, 

MET389VAL, ALA15THR (signal peptide),

1258DELAA

SFTPB surfactant protein B    SFTPB; surfactant, 

pulmonary-associated 

protein B

A-18C (promoter), 

A1013C, C1580T, A9306G,

INTRON 4 variants, 

THR131ILE

STK11 serine/threonine kinase 11    STK11   

TDG thymine-DNA glycosylase    TDG   

TGFa transforming growth factor a    TGFa   
687

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Gene symbol 

used in this 

report Definition

Alternative 

gene symbol Related protein/enzyme

Polymorphism/variant 

genotype

TGFß1 transforming growth factor β1    TGFβ1 SNP RS1800469

(C-509T, promoter), SNP 

RS2241712 (G-10807A, 

promoter), SNP RS6957

(3’UTR), SNP RS224178

(3’UTR), SNP RS1982073

(T29C, LEU10PRO, 

EXON 1)

TGFß3 transforming growth factor β3    TGFβ3   

TH tyrosine hydroxylase    TH VNTR

TIMP-3 tissue inhibitor of 

metalloproteinase 3 

   TIMP-3   

TNFα tumor necrosis factor (TNF 

superfamily, member 2) 

TNF TNFα, TNF TNF2 ( a promoter SNP, 

G-308A), SNPs G-376A and 

G-238A (promoter),

G489A (INTRON),

SNP RS3091257 (3’UTR),

SNP RS769178 (3’UTR)

TP thymidine phosphorylase    TP   

TPH tryptophan hydroxylase TPH1 TPH, TPH1 C218A, A779C

TP53 tumor protein    TP53   

TRAIL-R1 TNF-related apoptosis inducing 

ligand receptor 1 

TNFRSF10A TRAIL-R1, TNFRSF10A, 

death receptor 4

  

UGT1A UDP glucuronosyltransferase 1 

family, polypeptide A1

   UGT1A   

XPC xeroderma pigmentosum, 

complementation group C 

XPCC, XP3 XPC, XPCC, XP3 ALA499VAL (C → T), 

LYS939GLN (A → C), 

*PAT (poly AT ins/del 

polymorphism)

XPD xeroderma pigmentosum, 

complementation group D 

ERCC2 XPD, ERCC2 ASP312ASN (G → A, 312 

*G/*A), LYS751GLN 

(A → C, 751 *A/*C)

XPF xeroderma pigmentosum, 

complementation group F

ERCC4 XPF, ERCC4 SER662PRO (T → C), 

ARG415GLN (G1244A, 

EXON 8 SNP RS1800067), 

SER835SER (T2505C,

EXON 11 SNP RS1799801)

XPG xeroderma pigmentosum, 

complementation group G 

ERCC5 XPG, ERCC5 HIS1104ASP (G3507C,

SNP RS17655), HIS46HIS 

(T335C, SNP RS1047768), 

CYS529SER (SNP 

RS2227869)
Surgeon General’s Report

688

Gene symbol 

used in this 

report Definition

Alternative 

gene symbol Related protein/enzyme

Polymorphism/variant 

genotype

XPV polymerase (DNA directed) eta POLH XPV POLH, human DNA 

polymerase h

  

XRCC1 x-ray repair complementing 

defective repair in Chinese 

hamster cells 1 

   XRCC1 ARG194TRP (C → T), 

ARG280HIS (G → A), 

ARG399GLN (G → A)

XRCC2 x-ray repair complementing 

defective repair in Chinese 

hamster cells 2

   XRCC2   

XRCC3 x-ray repair complementing 

defective repair in Chinese 

hamster cells 3 

   XRCC3 THR241MET (T → C)

XRCC4 x-ray repair complementing 

defective repair in Chinese 

hamster cells 4 

   XRCC4 ALA247SER (G → T)

XRCC5 x-ray repair complementing 

defective repair in Chinese 

hamster cells 5 (double-strandbreak rejoining)

KU80 XRCC5, KU80   

XRCC6 x-ray repair complementing 

defective repair in Chinese 

hamster cells 6

KU70 XRCC6, KU70   
689

Index

Note: t following a number refers to a Table; f following a number refers to a Figure.

A

AAT. See α1-antitrypsin deficiency

4-ABP. See 4-aminobiphenyl

Accord (smoking system), 18

ACE. See Angiotensin-converting enzyme inhibitors

Acetaldehyde

in animal studies, 181

health effects, 29, 49, 298

in tobacco smoke, 112, 229t

Acrolein

DNA adducts, 272

in Eclipse, 18

health effects, 29, 59, 72, 365, 439t

Activated charcoal filters, 39, 46–47

Acute tolerance, 116

Adaptive immunity, 450f, 454f

Addiction. See Nicotine addiction

Additives, 34, 44–45

required reporting of, 20

Adhesion molecules, 371, 378

Adolescents

chronic tolerance, 117

epidemiology of smoking among, 156

nicotine dependence measurement in, 156–161

reinforcement, 118

sensitivity to nicotine addiction, 117

Adults

hematocrit levels, 377

prevalence of smoking and nicotine dependence, 162–167

psychiatric comorbidity, 167–169

Advance cigarettes, 17

Advertising

impact of, 654

lower yield tobacco products, 19

recommendations, 662, 663, 664

regulation, 653

Aerosols, particle-size distribution in, 50

Affective dimensions of smoking recovery, 173–174

Affective symptoms of tobacco withdrawal, 175–176

A549 cell line, 60

African Americans

adolescents, 156, 181

GSTP1 gene, 249

heart disease, 361

mortality, 361

smoking behavior, 48, 159

smoking topography, 48, 137

AGT. See O6-alkylguanine-DNA alkyltransferase

Airway epithelial cells, 288–290

Airway obstruction, 444, 445f

Airway remodeling, 453–456

AKT. See Protein kinase B

Alaska Natives, 156, 162

Albany Study, 361

Alcohol abuse

baclofen and, 129

carcinogenesis and, 298

reinforcement and, 120, 121

smoking cessation and, 169, 174

Aldehydes, 38–40

Alkylating agents, products of, 234

Allergic reactions to nicotine, 74

All-trans retinoic acid, 491

α1-antitrypsin (AAT)

deficency, 70, 445, 449f, 475–476

α-tocopherol, 461

Alveolar macrophages, 300, 440f, 451, 462

American Academy of Family Physicians, 661

American Academy of Pediatrics, 661

American College of Physicians, 661

American Correctional Association, 660

American Indians, smoking prevalence among, 156, 162

American Medical Association, 661

American Nursing Association, 661

Amino acid deficiencies, 600

4-aminobiphenyl (4-ABP), 42f, 227

adducts, 243f

in bladder cancer, 299t

chemical structure, 231f

in mainstream smoke, 228t

metabolism, 236f

4-aminobiphenyl-C8-deoxyguanosine, 271t, 273

Angiogenesis, 453–454

Angiotensin-converting enzyme (ACE) inhibitors, 360

Anhedonia, 131

Animal studies

cardiovascular and cerebrovascular, 67–69

cytotoxicity, 61–62

emphysema, 466–467, 491–492

fertility, 71–72

inhalation, 63–67

oxidative stress, 465

reproductive and developmental, 71–74

respiratory, 69–71

skin-painting, 62–63
Surgeon General’s Report

690

Antidepressant drugs, 134–135

Antioxidants, 379. See also specific substance

levels in smokers, 373

in lungs, 459–461

Antiprotease-protease imbalance, 472

evidence summary, 495

Antiprotease therapy, 493

Antipsychotic drugs, 134–135

Anxiety disorders, nicotine dependence and, 160, 168

Anxiolytic effects, 126

Aortic aneurysm, 362

Apolipoprotein level, 388

Apoptosis, 284, 493–494

Apurinic/apyrimidinic sites, 273

Aromatic amines, 41–42, 227

as biomarkers, 230–232

bladder cancer and, 241, 250

in mainstream smoke, 228t

Arsenic, 229f

Asbestos, 298

in cigarette filters, 16

Asian Americans

cardiovascular disease in, 361

PI *Z alleles, 475

smoking prevalence, 156, 162

Aspirin, 375, 380

Associative learning processes, 120–121, 181

Asthma, 439t

Atherosclerosis, 362, 363, 365

Atorvastatin, 380

Attitudinal influences, 172, 176–177

B

Baclofen, 128, 129

BAL. See Bronchoalveolar lavage

Base excision repair, 253–254, 255f, 262t

polymorphisms in, 264–265

Bayley Scales of Infant Development, 541

B cells, 452f, 453

BCL-2 family proteins, 284, 285

Benzene

as biomarker, 233, 234

in cigarette smoke, 227

metabolic activation, 237

Benzo[a]pyrene

DNA adducts, 243t

in mainstream smoke, 228t

Benzo[a]pyrene-7,8-diol-9,10-epoxide-N2-deoxyguanine 

stereoisomers, 273

Beryllium, 229t

β-adrenergic receptors, 289

Beta-carotene, 461

Bidis, 361

Biomarkers. See also specific biomarkers

of addiction potential, 655, 656t

of biologically effective dose, 53–54

breath and blood, 234

cardiovascular, 391–394

conclusions, 9–10, 79

of exposure, 52–53, 78

general concepts, 51–52

of inflammation, 392t–393t, 402, 463, 471

of potential harm, 54–56, 78

of protease involvement in emphysema, 491

urinary, 230–234

Birth defects, 539–540, 542t–548t, 601, 602t–603t

Birth weight. See Low birth weight

Black tobacco, 55

Bladder cancer, 307, 324

aromatic amines and, 241, 250

black tobacco smokers and, 55

gene mutations, 282f, 283

gene promoter hypermethylation, 294

risk factors, 54–55, 250, 268

Blonde tobacco, 55

Blood

alterations in, 375–380 (See also Thrombogenic effects)

biomarkers, 234

DNA adducts in, 244–245

hyperviscosity, 585

Blood flow, 576–577

Blood pressure, 368

maternal, 575

Blood vessels, alterations in, 380–381

Body weight. See also Low birth weight

smoking and, 77, 129

Boston Early-Onset COPD Study, 477, 478t, 479

Breast cancer, 525, 606

Breath biomarkers, 234

British Doctors’ Study, 648

Bronchitis, chronic, 439t, 441–443, 477

Bronchoalveolar lavage (BAL), 516

Brundtland, Gro Harlem, 654

Bupropion, 134, 135, 154, 397t, 400–401

Bureau of Alcohol, Tobacco, Firearms and Explosives, 663

Buspirone, 135

1,3-butadiene

animal studies, 67, 297

biomarker of exposure, 52

cancer risk, 29

in lung cancer, 299t

metabolic activation, 235, 237, 238

in tobacco smoke, 79, 227, 229t
691

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

C

Cachexia, 474

Cadmium

as biomarker, 234

placental levels of, 55

pulmonary injury and, 439t

reproductive and developmental effects, 568, 583, 587, 588

in tobacco smoke, 40–41, 227, 229t, 365

California Birth Defects Monitoring Program, 601

Cambridge glass fiber filters, 30, 31

Cancer, 224–226. See also Carcinogens; specific types of cancer

cell-cycle control in, 294–296

cell-surface receptors, activation of, 288–292

conclusions, 10, 304

evidence summary, 302–303

gene mutations, 274–278

gene promoter hypermethylation, 292–294

pathway of causation, 226f

research recommendations, 657

risk reduction, 664–666

signal transduction, 284–288

Cancer Prevention Study II, 355–356

Candidate gene studies, 141–145, 182, 262t, 480t–486t

Carbon dioxide, 30, 31

Carbon filters, 60

Carbon monoxide (CO)

as biomarker, 392t

cardiovascular disease, 392t

in novel tobacco products, 18

in oxidative stress, 463t, 471

reproductive and developmental effects, 584–586

Carbonyl compounds, 39

Carboxyhemoglobin, 364f, 492

maternal, 585

Carcinogens, 227–230. See also DNA adducts; specific 

carcinogens

biomarkers, 230–235

enzymology, 237–241

gene polymorphisms, 245–251

metabolic activation and detoxification, 235–237

specific cancers caused by, 298–300

TP53 mutations and, 278–283

whole smoke and condensate, 296–297

Carcinogenesis, synergistic interactions in, 297–298

Carcinogen-metabolizing genes, 245–251

Cardiomegaly, 69

Cardiovascular disease and effects, 6f. See also Endothelium; 

Hemodynamic effects; Inflammation; Thrombogenic effects; 

specific diseases

African Americans, 361

animal studies, 67–69

biomarkers, 391–394

conclusions, 10–11, 408

in diabetics, 383

evidence summary, 407

harm reduction, 402–407

implications, 407

lower yield tobacco products and, 362

malformations, 540, 546t–547t

mechanisms, 366f, 367

mortality, 356–357, 359, 361, 362

nicotine replacement therapy and, 368, 369

pathophysiology, 363–367

risk assessment, 355–356

secondhand smoke and, 363

smoking cessation and, 394–402

sudden death from, 361

2006 Surgeon General’s report on, 355, 363

Carlton cigarettes, 50–51

Casing, tobacco, 44

Catalase, 460

Catecholamines, 76–77

Causal agents, classification of, 7–8

Causal relationships

criteria, 5, 7t

inference of, 3t

CCND1 gene, 294–295

CDC. See Centers for Disease Control and Prevention

CD4 helper T cells, 453

CDKN2A (P16) tumor-suppressor gene, 292, 680t

Cell-cycle control, 294–296

Cell-derived oxidants, 462

Cellulose-acetate filters, 36

Centers for Disease Control and Prevention (CDC)

lung cancer and COPD study, 437

Centilobular emphysema, 446–447, 448f

Cerebrovascular disease, 357f, 361

mortality, 361

Cervical cancer, 4f, 225, 300, 324

Cervical mucus biomarkers, 53

Characterized adducts, 242–244

CHD. See Coronary heart disease

Chemistry of tobacco smoke. See also specific constituents

additives, 44–45

aromatic amines, 41–42

cardiovascular disease and, 363–367

conclusions, 9–10, 79

delivery of chemicals, 45–51

heavy metals, 40–41

heterocyclic amines, 43–44

nicotine and free nicotine, 32–34

N-nitrosamines, 34–37

phases of tobacco smoke, 30–31

polycyclic aromatic hydrocarbons, 37–38

volatile and aldehyde compounds, 38–40

Chewing gum. See Nicotine gum

Children

active smoking, effects of, 438t

secondhand smoke exposure, effects of, 4f, 438t

of smokers, 57–58

Chlorisondamine, 132

Cholesterol, low-density lipoprotein (LDL), 379–380. See also

Lipid abnormalities
Surgeon General’s Report

692

CHRNA4 gene, 141, 144t, 145t, 182, 680t

CHRNA7 gene, 141, 144t, 680t

Chromium, 229t, 589

Chromosome instability and loss, 274–278

Chronic bronchitis, 439t, 441–443, 477

Chronic disease, 4f

Chronic obstructive pulmonary disease (COPD)

apoptosis, 473

evidence summary, 494–495

genetic associations, 476–486

hypersecretion of mucus, 472

lung inflammation, 472–473

oxidative stress in, 471–474

pathogenesis, 471–472

phenotypes, 476–479

protease-antiprotease imbalance, 472

pulmonary hypertension and, 447

severity classifications, 443–444

1984 Surgeon General’s report on, 437

systemic involvement, 473–474

Chronic tolerance, 116–117

Cigarettes. See also specific types or brands of cigarette

defined, 15

smoked per day, 356–357

Cigarette design

conclusions, 9, 21

history, 15–17

lower yield tobacco products, 18

novel cigarette products, 17, 18–19

product evaluation, 19

Cigarette filters. See Filters

Cigarette-like products. See Novel tobacco products

Cigarette paper, 15

Cigarette smoke. See Tobacco smoke

Cigarette substitutes. See Novel tobacco products

Cigars, 362, 363

Ciliatoxicity assays, 59

Circulating proteins, 378–379

Cleft lip and palate, 11, 538–540, 582, 601

genotype and, 602t–603t

maternal smoking and, 542t–545t

Clinical imaging studies, 134

Clonidine, 401, 607

Cloud motion, 51

Clozapine, 136

Clubfoot, 540, 577

CO. See Carbon monoxide

Cobalt, 41

Cocaine, 105

Cochrane Database of Systematic Reviews, 395

Cognitive domain, impact on, 554

Coherence, 5–7

Collagenase, overexpression of, 493

Comet assay, 263–264

Committee to Assess the Science Base for Tobacco Harm 

Reduction, 651

Compensatory smoking, 111, 403

Composite International Diagnostic Interview-Substance Abuse 

Module, 162

Conclusions

biomarkers, 9–10, 79

cancer, 10, 304

cardiovascular disease, 10–11, 408

cigarette design, 9, 21

mechanisms of disease production, 9

nicotine addiction, 10, 183

pulmonary diseases, 11, 496

reproductive and developmental effects, 11, 612

respiratory and pulmonary disease, 11, 496

secondhand smoke exposure, effects of, 9

smoking cessation, 11, 408

tobacco smoke chemistry and toxicology, 9–10, 79

Conditioned stimuli, 120–121

Conditioning, 120–124

Congenital lobar emphysema, 447

Consumer perception, 19, 662

COPD. See Chronic obstructive pulmonary disease

Copenhagen City Heart Study, 443

Coronary blood flow, 368–370

Coronary heart disease (CHD)

cigarettes smoked per day, 356–359

duration of smoking and, 359

men, 357f

mortality, 360t

race and ethnicity, 361

secondhand smoke exposure and, 647

smoking cessation, 359–360

women, 360

Cotinine, 112

as biomarker, 52

chemical structure, 32f

Counseling, smoking cessation, 396t, 398–399, 606–607

COX-1. See Cyclooxygenase-1

COX-2. See Cyclooxygenase-2

Craniosynostosis, 540, 548t–554t

Craving, 123–124, 158, 175f

C-reactive protein, 379

CREB. See Cyclic adenosine monophosphate-response element 

binding protein

Cresols, 29

Cross-complementation group 1 for excision repair (XRCC1) 

gene, 264–265, 266

Cryptorchidism, 548t–553t

Cue-provoked craving, 123–124

Curing process, 35, 78

Cyanide, 31

Cyclic adenosine monophosphate-response element binding 

protein (CREB), 134

Cyclooxygenase-1 (COX-1), 288

Cyclooxygenase-2 (COX-2), 288, 289

CYP1A1 gene, 246–247, 248–249

CYP2A6 gene, 141, 142t

CYP2A13 gene, 247

CYP2B6 gene, 154
693

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

CYP2E1 gene, 142t, 247

Cytochrome P-450 enzymes, 237–238

Cytogenic effects, 57, 58–59

Cytoplasmic kinase, activation of, 290–291

Cytotoxicity, 59–61

animal studies, 61–77

cardiovascular and cerebrovascular system, 67–69

endocrine system, 76–77

immune system, 74–76

reproductive and developmental systems, 71–74

respiratory system, 63–67, 69–71

D

Death. See Mortality

Decision-tree analyses, 173

Demographic variables, 172–173

Denicotinized tobacco, 50, 123, 129

Department of Health and Human Services, 661, 663

Depression, nicotine dependence and, 135, 173–174

Dermal application of cigarette smoke condensate, 62–63

Desmosine, 491

Developmental effects. See Reproductive and developmental 

effects

Developmental immunotoxicity, 597–598

Diabetes

cardiovascular disease and, 383

insulin resistance, 384–385

macrovascular complications, 386–387

metabolic control, 384

microvascular complications, 385–386

mortality, 386

pathophysiological mechanisms, 387

peripheral arterial disease and, 382

risk for, 383–384

Diabetes Control and Complications Trial, 386

Diagnostic and Statistical Manual, Third Edition Revised

(DSM-III-R), 162, 165

Diagnostic and Statistical Manual of Mental Disorders, Fourth 

Edition (DSM-IV), 106, 109t

Disease. See also specific diseases

causation schema, 5f

mechanisms of (See Mechanisms of disease production)

smoking causally linked to, 4f

Distal acinar emphysema, 447

Distress tolerance, 174

DNA adducts, 236f, 244–245

characterized, 242–244

conversion to mutations, 268–273

genotoxicity assessment, 273

protein adducts as surrogates for, 245

repair, 252–259

uncharacterized, 244

DNA damage, 57. See also Chromosome instability and loss

DNA repair

adducts, 252–259

base excision repair, 253–254, 255f, 262t, 264–265

comet assay, 263–264

double-strand break repair, 259, 268

8-oxoguanine DNA glycosylase activity assay, 263

functional assays, 261–263

genotype-phenotype correlations, 267–268

mismatch repair, 258–259

molecular epidemiology of, 259–268

mutagen sensitivity assays, 263

nucleotide excision repair, 254–257, 262t, 266–267

O6-alkylguanine-DNA alkyltransferase, 252, 264

OGG1 gene, 265

transcription-coupled repair, 257–258

Dopamine

candidate gene studies, 146t–149t

neural pathways, 127f

neurotransmitter and receptor systems, 141–144

nicotinic acetylcholine receptors, 126

Dopamine receptor D2 (DRD2), 141

Double-strand break repair, 259

DNA repair, 259, 268

Down syndrome, 546t–551t

DRD2. See Dopamine receptor D2

Drug dependence, 106–108

1988 Surgeon General’s report on, 106

DSM-III-R. See Diagnostic and Statistical Manual, Third 

Edition Revised

DSM-IV. See Diagnostic and Statistical Manual of Mental 

Disorders, Fourth Edition

Dual product use, 19

Dye exclusion assay, 60

E

Eclipse smoking system, 18, 19

Ectopic pregnancy, 531–534, 609

2004 Surgeon General’s report on, 531, 609

Educational status, smoking cessation and, 173

“Effective pH,” 33

EGFR gene, 276–277, 289–290, 442

8-oxoguanine DNA glycosylase activity assay, 263

Elastases, 482–483, 488–489

“Elastic” cigarettes, 49–50

Elastin-derived peptides, 401

Electronic Nicotine Delivery Systems, 17–18, 31t, 32

ELF. See Epithelial lining fluid

Emergent processes, 174–178, 179

Emphysema, 445–446, 449f

animal studies, 466–467, 491–492

antiprotease therapy, 493

centilobular, 446–447, 448f

distal acinar, 447
Surgeon General’s Report

694

mantle, 447

matrix metalloproteinases, 489t

panacinar, 446–447

paraseptal, 447

pathogenesis of, 472, 487–494

protease-antiprotease imbalance, 495

protease involvement, biomarkers of, 491

unilateral, 447

Ending the Tobacco Problem: A Blueprint for the Nation, 652, 

660–664

Endocannabinoid system, 129–130, 132

Endocrine system, 76–77, 555–565

men, 557–561, 562–564

pregnancy, 557

premenopause, 555–557

women, 555–557, 558t–560t

Endothelial progenitor cells, 370

Endothelium

dysfunction, 370, 371

nitric oxide and, 371–372

pathologic angiogenesis, 373–374

regeneration of, 370–371

vasodilation, 372–373

Endothelium-dependent vasodilation, 372–373

ENDS. See Electronic Nicotine Delivery Systems

Environmental context of learning and conditioning, 122–124

Environmental Protection Agency (EPA), 7

Environmental tobacco smoke exposure. See Secondhand 

smoke exposure

Enzyme antioxidants, 459–461. See also specific substances

Enzymology of carcinogen metabolism, 237–245

EPA. See Environmental Protection Agency

Epidermal growth factor receptor, 287

Epithelial injury, 465, 470

Epithelial lining fluid (ELF), 438

Epoxide hydrolases, 238–239

ERBB receptors, 289

ERK. See Extracellular signal-regulated kinases

Esophageal cancer, 4f, 297, 298

Estriol, birth weight and, 557

Ethnicity, 361. See also specific ethnic groups

Ethylene oxide, 227, 229t, 240

Eugenol, 44

Euglycemic hyperinsulinemic clamp technique, 384

European Americans

AAT deficiency, 475

candidate gene studies, 142t–144t

cigarette brands, popular, 49

smoking topography, 48

Evidence

description of, 8

evaluation of, 3t, 5–7

Evidence summaries

cancer, 302–303

cardiovascular disease, 407

COPD, 494–495

genetics, 302–303

genetic susceptibility to tobacco smoke, 495

harm reduction, 407

nicotine addiction, 180–182

oxidative stress, 463–465, 494–495

protease-antiprotease imbalance, 495

reproductive and developmental effects, 577–583, 608–611

Exhaled air biomarkers, 467

Exocyclic etheno adducts, 273

Expanded tobacco, 45, 62, 78

Exposure reduction, 402–406

Extracellular signal-regulated kinases (ERK), 291

F

Fagerström Test for Nicotine Dependence (FTND), 107t, 109t, 

163t

Fagerström Tolerance Questionnaire (FTQ), 106, 107t, 109t

Family Smoking Prevention and Tobacco Control Act (2009), 8, 

20, 653, 680

FDA. See Food and Drug Administration

Federal Cigarette Labeling and Advertising Act (1965), 653

Federal Trade Commission (FTC), 16, 29

Fertility. See also Reproductive and developmental effects

animal studies, 71–72

female, 525–526

male, 526–527

maternal smoking and, 526

subfertility, 525–526

2001 Surgeon General’s report on, 526

Fetal effects. See also Low birth weight

animal studies, 72–73

birth defects, 539–540, 542t–548t, 601, 602t–603t

blood flow, 576–577

carbon monoxide and, 584

cardiovascular, 569t–570t, 570–574, 575

organogenesis, 577–583

pathophysiological mechanisms, 659–660

size and growth, 538

timing and critical periods, 577

Fibrinogen, 379

Filters (cigarette), 46–47

activated charcoal, 46–47

asbestos in, 16

cellulose-acetate, 36

glass fiber, 30, 31

health risks, 16–17

Filter ventilation holes, blockage of, 16, 49

“599 list,” 44

Flavorings, 44–45

Flow-mediated arterial vasodilation, 391

Fluoxetine, 135

Fluvastatin, 380

Folate levels in smokers, 58

Food and Drug Administration (FDA), 8, 20, 653

Food intake, smoking abstinence and, 129

Formaldehyde, 227, 439t

Framework Convention on Tobacco Control, 654
695

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

Framingham Heart Study, 139–140t, 361, 478

Free fatty acids, 384

metabolism, 389–390

Free nicotine, 31–34

Free radicals, 457

FTC. See Federal Trade Commission

FTND. See Fagerström Test for Nicotine Dependence

FTQ. See Fagerström Tolerance Questionnaire

Functional assays, 261–263

Functional magnetic resonance imaging, 134

Future vision

global tobacco epidemic, 647–651, 652–654

recommendations, 655–666

reducing risk from smoking, 671–672

G

γ-aminobutyric acid (GABA), 127f

γ-glutamyltranspeptidase, 461

Gas phase of tobacco smoke, 4, 31, 462

defined, 30

Gastroschisis, 540, 552t–553t

Gefitinib, 277

Gender factors. See Men; Women

Gene mutations, 268–273. See also specific genes

chromosome instability and loss, 274–278

Gene profiling, 491

Gene promoter hypermethylation, 292–294

Gene silencing, 293

Genetics

evidence summary, 302

genetic susceptibility to tobacco smoke, 495

lung cancer, 274, 275–278, 292–293, 307

pharmacogenetics, 145–154

of smoking behavior, 10, 137–145

summary and future directions, 155

Genetic polymorphisms. See also specific genes

in base excision repair, 264–265

in double-strand break repair, 268

epidemiology, 245–251

maternal and neonatal, 600–605

in nucleotide excision repair, 266–267

in O6-alkylguanine-DNA alkyltransferase, 264

Genetic symbols, definitions and alternative nomenclature for, 

679–688

Genotoxicity

cigarette smoke condensate, 56–59

DNA adduct assessment, 273

Genotype-phenotype correlations, 267–268

Glass fiber filters, 30, 31

Global genomic nucleotide excision repair, 254–257, 258

Global Initiative for Chronic Obstructive Lung Disease (GOLD), 

443

Global tobacco epidemic, 647–651, 652–654

Glucose levels, 76

Glutamate, 126–128

Glutathione-S-transferases (GSTs), 239–240

Glutathione (GSH) system, 460–461

Glycosylases, 253–254, 263, 277t

GOLD. See Global Initiative for Chronic Obstructive Lung 

Disease

Growth control, loss of mechanisms for, 284–296

GSH. See Glutathione system

GSTM1 gene, 248–249, 482t

GSTP1 gene, 249

GSTP1 gene, 482t

GSTs. See Glutathione-S-transferases

GSTT1 gene, 249, 601, 605

G→T transversions, 278f, 279–283

Guidelines for Carcinogen Risk Assessment, 7

Gum. See Nicotine gum

H

Harm reduction, 402

evidence summary, 407

nicotine replacement therapy, 406

reduced smoking, 403–406

Head cancers, 294

Health Professionals Follow-Up Study, 383

Heart disease. See Cardiovascular disease; Coronary heart 

disease

Heart rate, 368

fetal, 569t–570t, 570–574, 575

maternal, 568–570, 574–575

Heavy metals, 40–41

Hematocrit level, 377

Hemodynamic effects, 368–370

Heritability. See Genetics

HER-2/NEU gene, 276–277, 289

Heterocyclic amine protein pyrolysate products, 56

Heterocyclic amines, 43–44

Heterocyclic aromatic amines, 227

Hispanic Americans, 156, 361, 648

Homologous DNA recombination, 259, 260f

Honolulu Heart Program, 361

Hooked on Nicotine Checklist, 110t, 156

1-HOP. See 1-hydroxypyrene

Hormones

maternal smoking and, 612

men, 557–561

Host-cell reactivation assay, 261

HPRT. See Hypoxanthine phosphoribosyl transferase mutations

5HTT gene, 679

smoking status and, 151t

Hydrogen cyanide, 31, 439t

1-hydroxypyrene (1-HOP), 230, 231f, 391

Hypercholesterolemia, 370

Hypercoagulable state, 382

Hypersecretion of mucus, 472
Surgeon General’s Report

696

Hypospadias, 540, 548t–553t

Hypoxanthine phosphoribosyl transferase (HPRT) mutations, 

57

Hypoxia, 585

I

IARC. See International Agency for Research on Cancer

ICD-10. See International Classification of Diseases, 

10th Revision

Ilomastat, 493

Imaging studies, 134

Immune system response, 74–76, 300

of the lung, 450f, 451–453

reproductive system and, 583–584

Implications

cardiovascular disease, 407

pulmonary diseases, 496

reproductive and developmental effects, 606–608

“Incentive amplification,” 121

Income level, smoking prevalence and, 162

Inductive plethysmography, 50

Infant mortality, 538–539, 607

Inflammation, 382, 456

biomarkers, 392t–393t, 463, 471

lung, 472–473

Inhalation patterns, 50

Inhalation studies, 63–67

Inhalers, nicotine, 113t

Innate immunity, 450f, 454f

Institute of Medicine (IOM)

biomarker definition, 52

cigarette substitutes, 19, 651

Ending the Tobacco Problem: A Blueprint for the Nation,

660–664

Insulin dosage, 384

Insulin resistance

diabetes and, 384–385

lipolysis inhibitors, 390

Insulin Resistance Atherosclerosis Study, 383

Intellectual abilities, prenatal exposure and, 541

INTERHEART study, 361, 367

International Agency for Research on Cancer (IARC), 7, 227, 

228t–229t

International Classification of Diseases, 10th Revision (ICD10), 106t

International Collaborative Study on Genetic Susceptibility to 

Environmental Carcinogens, 247, 249

International Organization for Standardization, 29

Intrauterine growth restriction (IUGR), 597, 604t–605t

Intrauterine growth retardation, 597, 604t–605t

In vitro studies

AGT, 252

oxidative stress, 463–465

In vivo studies, AGT, 252

IOM. See Institute of Medicine

Isoprostanes, 377

IUGR. See Intrauterine growth restriction

J

Jenkins Act, 663

Joint Commission on the Accreditation of Healthcare 

Organizations (JCAHO), 660

K

Kenacid blue binding assay, 60

Ketones, 39

Koch’s postulates, 7

KRAS gene, 59, 277

L

Lactate dehydrogenase release assay, 60

Laryngeal cancer, 225, 283, 296, 299t

LBW. See Low birth weight

LDL. See Low-density lipoprotein

Lead, 40–41, 229t

reproductive and developmental effects, 588

Learning and conditioning

associative learning, 121

environmental context, 122–124

negative reinforcement, 122

positive reinforcement, 121–122

secondary reinforcement, 120–121

Legacy Tobacco Documents Library, 16

Legislation, tobacco control, 8

Leukemia, 4f, 299t, 300

Leukocytes, 451

Lifestyle

healthy, promoting, 664–666

as relapse risk factor, 172–173

“Light” tobacco products. See Lower yield tobacco products

Limb deficiency defects, 540, 577

Linkage studies

COPD phenotypes, 477–479

smoking behavior, 139t–140t, 140–141

Lipid abnormalities

composition, 388

epidemiology, 387–388

free fatty acid metabolism, 389–390

lipid transfer enzymes, 388

oxidized lipoproteins, 388

pathogenic mechanisms, therapeutic implications of, 390

postprandial changes, 388–389
697

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

reverse cholesterol transport, 390

smoking cessation, effects of, 390

Lipid peroxides, 467

Lipid transfer enzymes, 388

Lip occlusion of filter ventilation holes, 49

Lipolysis inhibitors, 390

Lipoproteins, 388

Lipoprotein-associated lipid transfer enzymes, 388

Liver cancer, 225, 299t

Low birth weight (LBW), 4f, 55

cadmium exposure and, 588

estriol and, 557

maternal smoking and, 538, 539, 604t–605t

polycyclic aromatic hydrocarbons and, 590t–592t, 597

secondhand smoke exposure and, 538

1964 Surgeon General’s report on, 538

2001 Surgeon General’s report on, 538

2004 Surgeon General’s report on, 538

Low-density lipoprotein (LDL) cholesterol, 379–380

Lower yield tobacco products, 15, 18, 68, 73, 362

cardiovascular disease and, 362

consumer perception of, 19

risk reduction with, 16, 17, 566

Lozenges, nicotine, 114, 395

Luciferase host-cell reactivation assay, 261–263

Lung cancer, 4f

conclusions, 10

family history and, 300–302

genetics, 274, 275–278, 292–293 (See also TP53 gene)

G→T transversions, 279–283

mortality, 300

1964 Surgeon General’s report on, 5

survival, 277–278

Lung Health Study, 403, 406

Lungs

antioxidants in, 459–461

characterized adducts in, 242–244

defenses, 440f

inflammation, 456, 472–473

local oxidative stress, 467–469

lymphoid collections, 452f

tissue studies, 490–491

uncharacterized adducts in, 244

Lymphoid collections in lung tissue, 452f

M

Macular degeneration, 374

Mainstream smoke, 30–31

Major depression, 135, 168

Mantle emphysema, 447

Marlboro cigarettes, 36, 49, 51

Maternal cardiovascular effects, 569t–570t, 571t–574t

blood pressure, 575

heart rate, 568–570, 574–575

Maternal smoking. See also Fetal effects; Reproductive and 

developmental effects

hormones and, 612

later fertility or fecundability, 526

nicotine dependence in offspring, 160–161

Matrix metalloproteinases, 290, 489t

McCarthy Scales of Children’s Abilities, 541

M cells, 452

McLeod syndrome (unilateral form of emphysema), 447

Mecamylamine, 111, 119, 373

Mechanisms of disease production, 3–5. See also Evidence

conclusions, 9

mechanisms of action, 7–8

mode of action versus, 7

schema for, 5f

1964 Surgeon General’s report on, 5

Memory, nicotine and, 126

Men

coronary heart disease in, 357f

endocrine system, 557–561, 562t–564t

fertility, 526–527

hormones, 557–561

nicotine dependence prevalence in, 162

nicotine reinforcement in, 120

smoking cessation, 608

smoking topography, 48

Menarche, 525

Menopause, 525

Menstrual cycle, 524–525, 608

Mentholated smoke, 66, 69

Mercury, 40, 41

reproductive and developmental effects, 588, 589

Merit cigarettes, 50–51

Mesocorticolimbic brain system, 125–126

Mesolimbic dopamine system, 135–136

Metabolic activation of carcinogens, 235–237

Metals, 40–41, 229t. See also specific metals

biomarkers, 234

reproductive and developmental effects, 587–589

Methyllycaconitine, 126, 130, 133

4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), 231f, 

232

4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK)

chemical structure, 35f

DNA adducts, 243t, 243t

in mainstream smoke, 228t

metabolism, 236f

Methylphenidate, 119

Micronutrient deficiencies, 599–600

Microsomal epoxide hydrolase, 486, 600

Minnesota Child Development Inventory, 541

Mismatch repair, 258–259

Modeling of smoking, 179

“Mode of action,” 7

Modified tobacco products. See Lower yield tobacco products; 

Novel tobacco products

“Molecular Koch’s postulates,” 7
Surgeon General’s Report

698

Molecular profiling, 649, 650f

Monitoring the Future study, 156

Monoamine oxidase, 457

Monocytes, 378

Mortality

African Americans, 361

cardiovascular disease, 356–357, 359, 361, 362

cerebrovascular diseases, 361

cigarettes smoked per day and, 356–357

diabetes and, 386

duration of smoking and, 359

infant, 538–539, 607

lung cancer, 300

perinatal, 538–539

PI *Z alleles and, 476

preeclampsia and, 534

smoking cessation and, 360, 394–395

sudden death, 361

women, 360

Motion Picture Association of America, 663

Motivation as relapse risk factor, 177–178

MPOWER framework (WHO), 653–654

MRPs. See Multidrug-resistance proteins

Mucin, 461

Mucociliary function, impaired, 69, 439t

Mucus hypersecretion, 472

Multidrug-resistance proteins (MRPs), 461

Multinational Study of Vascular Disease in Diabetes, 386

Multiple Risk Factor Intervention Trial Research Group, 360

Mutagen sensitivity assays, 263

Myeloperoxidase, 378

Myocardial infarction, 355, 366f

Myocardial ischemia, 366f, 367

N

NAB (N’-nitrosoanabasine), 34, 35f, 232

N-acetylcysteine, 467

N-acetyltransferases (NATs), 241

Nacystelyn, 467

Naloxone, 132

Naltrexone, 129, 155

Naphthalene, 598

Nasal cancer, 297, 299t

Nasal spray, nicotine, 113–114, 120, 124, 406

NATB. See N’-nitrosoanatabine

NAT2 gene, 246t, 249–250

National Cancer Institute, 661, 665

National Comorbidity Survey, 164–165, 168

National Emphysema Treatment Trial, 486

National Health Interview Survey, 162, 477

National Institute of Mental Health Diagnostic Interview 

Survey, 162

National Institutes of Health (NIH), 665

National Longitudinal Study of Adolescent Health, 161

National Mortality Followback Survey, 361

National Survey on Drug Use & Health, 157, 158, 162

NATs. See N-acetyltransferases

NDMA. See N-nitrosodimethylamine

“Necessary” causal agents, 7–8

Neck cancer, 294

Necrosis, 60–61

Negative reinforcement, 116, 118, 122, 124

“Neither necessary nor sufficient” causal agents, 8

Neonates, hematocrit in, 377

Nephropathy, 385–386

Neurochemical correlates of nicotine withdrawal, 132

Neurodevelopment, 540–554

Neuronal nicotinic receptors, 141, 144t

Neuropathy, 386

Neurosubstrates of nicotine dependence, 131–133

Neutral red incorporation assay, 60

Next cigarettes, 18

Niacin, 390

Nickel, 229t, 587

Nicotine

allergic reactions to, 74

bioavailability, 113

chemistry of, 31–34

delivery systems, comparison of, 114

forms of, 33f

free, 31–34

metabolism, 141

pharmacokinetics, 113–116

reinforcement (See Nicotine reinforcement)

reproductive and developmental effects, 586–587

smokeless tobacco products and, 115f

structure, 33f

thrombosis and, 381–382

tolerance, 116–117

withdrawal (See Withdrawal)

Nicotine addiction. See also Relapse

adolescent sensitivity to, 117

clinical imaging studies, 134

components of, 116–124

conclusions, 10, 183

definition, 105–108

determinants of, 160–161

evidence summary, 180–182

genetics, 137–155

measures of, 109t–110t

pathophysiology of, 124–136

physiological mechanisms and indicators, 116–124

prevalence and trajectory toward dependence, 156–161

research recommendations, 655–657

summary of evidence, 180–182

1988 Surgeon General’s report on, 105–106, 180

Nicotine dependence

adolescent, measuring, 156–161

depression and, 135

by dose, duration, and subpopulations, 165–167

epidemiology of, 162–167

men, 162

neurosubstrates of, 131–133
699

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

in offspring, maternal smoking and, 160–161

prevalence, 156–167

psychiatric comorbidity, 167–169

schizophrenia and, 135–136

summary and future directions, 135

Nicotine gum, 111, 114f, 395

cardiovascular effects, 368, 369

craving cues and, 123–124

insulin resistance and, 384

nicotine bioavailability, 113t

safety, 406

for smoking cessation, 367

Nicotine inhalers, 113t

Nicotine lozenges, 114, 395

Nicotine nasal spray, 113–114, 120, 124, 406

Nicotine patches, 114f

addiction potential, 115

adolescents and, 158

cardiovascular risk, 367

cravings and, 123, 124

LH secretion, impact on, 587

nicotine bioavailability, 113t

for smoking cessation, 152–154, 389

weight gain and, 389

Nicotine reinforcement

alcohol and, 119, 121

negative, 122

neurosubstrates of, 125–130

positive, 121–122

relapse and, 172

versus smoking reinforcement, 120

Nicotine replacement therapy (NRT), 145–154, 395

cardiovascular disease and, 381, 399–400, 406

cravings, reduction in, 124

gum (See Nicotine gum)

harm reduction, 406

lozenges, 114, 395

nasal spray, 113–114, 120, 124, 406

nicotine concentration and, 113

patch (See Nicotine patches)

pregnancy and, 607

recommendations, 663

smoking reduction and, 404t

Nicotine tolerance, 116–117

Nicotine withdrawal. See Withdrawal

Nicotinic acetylcholine receptors, 125

NIH. See National Institutes of Health

Nitric oxide

as free radical, 457

generation, 375–377

oxidative stress, biomarker of, 463t

reproductive and developmental effects, 600

vascular effects, 371–372, 380, 585

Nitriles, 40

Nitrogen oxide, 39, 439t

N-nitrosamines, 34–37

as biomarkers, 232

carcinogenicity, 226, 227

Nitrosamino acids, 232–233

N’-nitrosoanabasine (NAB), 34, 35f, 232

N’-nitrosoanatabine (NATB), 34, 232

N-nitrosodimethylamine (NDMA), 235, 236f

N’-nitrosonornicotine (NNN), 34, 228t, 232

NNAL (4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol), 231f, 

232

NNK. See 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone

Nonenzymatic antioxidants, 461

Nonhomologous end-joining of DNA, 259, 261f

Non-neoplastic histopathologic changes, 71

Non-small-cell lung cancer, 292–293

Nonvolatile nitrosamines, 34

Norepinephrine, 130, 132

Normative Aging Study, 486

Nornicotine, 111–112

Nortriptyline

pregnancy and, 607

for smoking cessation, 135, 401, 402

Novel tobacco products, 17, 18–19

conclusions, 9

1,N2-propanodeoxyguanosine, 272–273

NRT. See Nicotine replacement therapy

NRXN1 gene, 141

NRXN3 gene, 141

Nuclear coronary perfusion studies, 394

Nuclear factor-kappa B, 287–288

Nucleotide excision repair, 254–257, 262t, 266–267

Nurses’ Health Study, 360, 361, 383, 386

Nutrient deficiencies, 599–600

O

O6-alkylguanine-DNA alkyltransferase (AGT)

DNA repair, 252, 264

in vitro studies, 252

Obama, Barack, 8

Office on Smoking and Health, 8

OGG1 gene, 265

Olefins, 40

O6-methyldeoxyguanosine, 272

O14-methylthymidine, 272

Omni cigarettes, 17

Oncogenes. See also specific genes

activation, 275–277

Opioid system, 129–130, 132

O16-pyridyloxobutyl-deoxyguanosine, 272

Oral cancer, 225, 282f, 323t

Oral premalignant lesions, 58

Organogenesis, 577–583

Orofacial clefts. See Cleft lip and palate

Oviduct (tubal) function, 72, 534, 566, 586

Ovum (ova), 57

Oxidants, 462

Oxidative DNA damage, 54, 233

Oxidative DNA repair lesions, 54
Surgeon General’s Report

700

Oxidative stress

animal studies, 465–467

assessment, 463

consequences, 465–470

in COPD, 471–474

evidence, 463–465, 494–495

human studies, 467

inflammation, 465, 470, 472

local, 467–469

platelet function and, 377

reactive oxygen species and, 457–459

systemic involvement, 469–470

in vitro studies, 463–465, 468t–469t

Oxidized lipoproteins, 388

Oxidized low-density lipoprotein cholesterol, 379–380

Oxidizing chemicals, 391, 407

8-oxodeoxyguanosine, 233, 272

chemical structure, 231f

mutational specificity, 271t

8-oxoguanine DNA glycosylase activity assay, 263

P

Pack-years, 267n

PAD. See Peripheral arterial disease

PAHs. See Polycyclic aromatic hydrocarbons

Panacinar emphysema, 446–447

Pancreatic cancer, 4f, 291, 298–300

Pancreatic juice biomarkers, 53

Paper, cigarette, 15

Papillomas, 62

Paracicatricial emphysema, 447

Paraseptal emphysema, 447

Particulate (tar) phase of tobacco smoke, 30

constituents in, 31, 35, 488

Patch. See Nicotine patches

Pathologic angiogenesis, 373–374

Peabody Picture Vocabulary Test, 541

Perinatal mortality, 538–539

Peripheral arterial disease (PAD), 362

Persistent innate and adaptive immune inflammatory response, 

453, 454f

Person risk factors for relapse, 172–174

P53 protein, 285–286

pH, effective, 33

Pharmacogenetic approaches to nicotine addiction, 145–154

Pharmacokinetics of nicotine, 113–116

Pharmacotherapy for smoking cessation, 401–402. See also

Nicotine replacement therapy; specific drugs

Phenotypes

COPD, 476–479

defined, 108

smoking behavior, 124, 139t–140t, 143t–145t, 146t–153t

Philip Morris (tobacco manufacturer), 16, 17, 18, 36

Phosphatidylinositol-3 kinase, 287

Phosphatidylinositol 3’-phosphatase, 287

PHS. See Public Health Service

Physicians’ Health Study, 380, 383

Pioglitazone, 390

Pipes, 362

PI* Z alleles, 475, 476

PKB. See Protein kinase B

Placental abruption, 535

Placental blood flow, 576–577

Placenta previa, 535

Plasmin, 379

Platelets, impact of smoking on, 375–377

Plausibility, 5–7

Policy recommendations, 660–664

advertising, 662, 663, 664

secondhand smoke exposure, 664–666

Polonium 210, 41, 227

Polycyclic aromatic hydrocarbons (PAHs), 11, 37–38

as biomarkers, 230

carcinogenicity, 228t

reproductive and developmental effects, 589–599

Polymorphonuclear leukocytes, 378

Positive reinforcement, 118–119, 121–122, 124

Postprandial hypertriglyceridemia, 384–385

Postprandial lipid changes, 389

PPROM. See Preterm premature rupture of membranes

Preeclampsia, 534–535, 585–586, 609–610

mortality and, 534

2004 Surgeon General’s report on, 534, 567, 609

Pregnancy. See also Maternal smoking; Reproductive and 

developmental effects

complications, 527–537

endocrine system, 557

smoking cessation during, 606–607

2001 Surgeon General’s report on, 557

Premenopause, 555–557

Premier cigarettes, 18

President’s Cancer Panel, 648, 652–653, 654

recommendations, 664–666

Preterm delivery, 11, 536–537

placenta previa and, 535

Surgeon General’s reports on, 536

vitamin deficiencies and, 55

Preterm premature rupture of membranes (PPROM), 537, 

599–600, 610–611

Prevention, smoking, 606–607

Primary Malignant Growths of the Lungs and Bronchi, 654

Progesterone, 587, 608

Prostacyclin, 380

Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial, 

302

Proteases, 489–494

Protease-antiprotease imbalance, 495

Protease inhibitors, 493t

Protein adducts, 54, 245

Protein kinase A, 226f, 291

Protein kinase B (AKT or PKB), 226, 226f, 287, 290–291

Protein kinase C, 291

Protein-signaling pathways, lung cancer, 286f
701

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

P73 gene, 296

P16 gene, 292, 293, 294

Psychiatric comorbidity, nicotine addiction and, 134–136, 

167–169

P21 protein, 295

Public Health Service (PHS), 16, 135, 395, 606, 607

Pulmonary defenses, 440f

Pulmonary disease. See also Lungs; specific diseases

conclusions, 11, 496

future research recommendations, 658

genetics of, 475–487

overview of, 437–438

oxidative stress and, 457–470

1984 Surgeon General’s report on, 440

2004 Surgeon General’s report on, 440

tissue remodeling, 453–457

Pulmonary hypertension, 447–449

Pyrolysis environment, 47

Q

Quest cigarettes, 18

Quinapril, 374

R

RAD23B gene, 262t, 267

Radioactive elements, 41

RAS/mitogen-activated protein kinase, 287

Raven Progressive Matrices Test, 541

Reactive oxygen species (ROS), 251, 254, 265, 457–459

Reboxetine, 130

Recommendations

policy (See Policy recommendations)

research (See Research recommendations)

Reconstituted tobacco, 45–46

Red blood cells, 377

Reduced exposure, methods for, 402–406

Regulation

antiapoptotic proteins, 688–690

smoking cessation during pregnancy, 607–608

tobacco products, 662–664

tumor suppressors and proapoptotic proteins, 284–286

Reinforcement. See Nicotine reinforcement

Relapse

defined, 170

lapse-relapse relationship, 171

natural history of, 170–171

prevalence, 170–171

rapidity of, 171

risk factors (See Relapse risk factors)

Relapse risk factors, 171

emergent processes, 174–178

person factors, 172–174

situational instigators, 178–179

summary and future directions, 180

transition from lapse to relapse or recovery, 179–180

Relative risk (RR), 355

coronary heart disease, 356f

Report of the Advisory Committee to the U.S. Surgeon General 

(1964), 7t

Reproductive and developmental effects. See also Fertility; Fetal 

effects; Maternal smoking; Pregnancy

animal studies, 71–74

children of smokers, 57–58

conclusions, 11, 612

developmental endpoints, 537–554

endocrine system, 555–561

evidence summaries, 577–583, 608–611

immune system, 583–584

implications, 606

overview, 523

placental effect, 566–568

regulation and policy, 607–608

reproductive endpoints, 524–527, 601–605

research recommendations, 658–660

smoking cessation and prevention, 606–607

tobacco smoke toxicants and, 584–599

tubal function, 566

Research recommendations, 655–660

cancer, 657

cardiovascular diseases, 657–658

nicotine addiction, 655–657

pulmonary diseases, 658

reproductive and developmental effects, 658–660

Respiratory defense mechanisms, 440f, 450–451

adaptive immunity, 450f, 452–453, 454f

innate immunity, 450f, 451–452, 454f

summary, 456–457

tissue remodeling, 453–456

Respiratory disease. See also Pulmonary disease; specific 

diseases

animal studies, 69–71

conclusions, 11

nonmalignant, 437–438, 439t

1964 Surgeon General’s report on, 437

2004 Surgeon General’s report on, 438t

2006 Surgeon General’s report on, 438t

Respiratory system

defense mechanisms (See Respiratory defense mechanisms)

dosimetry of tobacco smoke in, 439–440

Retail sales, regulation of, 661, 662–663

Retinoblastoma protein, 286

Retinopathy, 386

Reverse cholesterol transport, 390

Reward, 118

Rimonabant, 130

Risk assessment tools, biomarkers as, 52

R.J. Reynolds (tobacco manufacturer), 17, 18

ROS. See Reactive oxygen species

Rosiglitazone, 390

RR. See Relative risk
Surgeon General’s Report

702

S

Safe and Drug-Free School Act, 661

St. Louis Alpha-1-Antitrypsin Study, 476

Saliva biomarkers, 52

Salmonella mutagenicity assay, 56, 78

SCE. See Sister chromatid exchange

Schizophrenia, 135–136

Secondary reinforcement, 120–121

Secondhand smoke exposure, 381

cardiovascular disease and, 363

conclusions, 9

health consequences of, 4f, 9

low birth weight and, 538

during pregnancy, 659

recommendations, 664–666

Seminal fluid biomarkers, 53

Sensitization, 116

Sensory-gating deficits, 136

Serotonin, 129–130

smoking behavior and, 150t

SERPINA3 gene, 11, 475, 486, 496

Sidestream smoke, 31

SIDS. See Sudden infant death syndrome

Signaling cascades, 292

Signal transduction, 284–288

Sister chromatid exchange (SCE), 58

Situational instigators, 171, 178–179

Skin-painting studies, 62–63

Skoal smokeless tobacco products, 115f

Small airway obstruction, 444, 456

Small-cell lung cancer, 292–293

Smoke. See Tobacco smoke

Smokeless tobacco products, 113–114, 115f

cardiovascular disease and, 366–367, 381

maternal use, 539

plasma nicotine concentrations, 115f

Smoking

adolescents, 156, 158–160

duration, 359

epidemiological literature review, 524–555

frequency, 119

pathophysiological and cellular mechanisms, 555–605

reduced, 403–406

regulation and policy, 607–608

reinforcement versus nicotine reinforcement, 120

risk reduction, 651–652

Smoking behavior

African Americans, 48

blockage of filter ventilation holes, 16, 49

defined, 51

heritability of, 10, 137–138

molecular genetic research, 138–145

phenotypes, 139t–140t

Smoking cessation

cardiovascular disease and, 359–360, 390, 394–402

conclusions, 408

counseling, 396t, 398–399, 606–607

lipid abnormalities and, 390

men, 608

mortality and, 360, 394–395

pharmacotherapy for, 397t–398t, 401–402 (See also Nicotine 

replacement therapy; specific drug)

pregnancy and, 606–607

regulation and policy, 607–608

1990 Surgeon General’s report on, 395

survival curves and, 648

Smoking compensation, 16, 18, 111, 119

Smoking initiation, 137–138

in adolescents (See Adolescents)

Smoking machine conditions, 60

Smoking persistence, 138, 182

Smoking prevention, 606–607

Smoking recovery, 182. See also Relapse

Smoking topography, 33, 48

Snuff, 114f, 115f, 357, 366, 586

SOD. See Superoxide dismutase

Sperm, 526–527

genetic damage to, 599

S-phenylmercapturic acid, 233

Spontaneous abortion, 527–531, 532t–533t, 609

Surgeon General’s reports on, 530, 531

Squamous cell carcinoma, 247, 280f

Stroke, 361

Subfertility, 525–526

Sudden death, 361

Sudden infant death syndrome (SIDS), 4f, 539

“Sufficient” causal agents, 8

Sulfur-containing gases, 39

Superoxide dismutase (SOD), 251, 457

1964 Surgeon General’s Report, 5

low birth weight, 538

respiratory disease, 437

1982 Surgeon General’s Report, 5

1984 Surgeon General’s Report

COPD, 437

pulmonary diseases, 440

1988 Surgeon General’s Report

drug dependence criteria, 106

nicotine addiction, 105–106, 180

1990 Surgeon General’s Report, 395

2000 Surgeon General’s Report, 654

2001 Surgeon General’s Report, 524

fertility, 526

low birth weight, 538

menopause, 525

perinatal mortality, 539

pregnancy, estrogen levels in, 557

2004 Surgeon General’s Report

birth defects, 539

cancer, 225

ectopic pregnancy, 531, 609

evidence strength, 3, 7

low birth weight, 538

male fertility, 526
703

How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease

placental abruption, 535

placenta previa, 535

preeclampsia, 534, 567, 609

preterm delivery, 536

preterm premature rupture of membranes, 537

pulmonary diseases, 440

respiratory disease, 438t

sudden infant death syndrome, 539

spontaneous abortion, 530, 609

2006 Surgeon General’s Report

cardiovascular disease, 355, 363

low birth weight, 538

preterm delivery, 536

respiratory disease, 438t

spontaneous abortion, 531

Survival curves, 648

Sympathetic nervous system, 123, 367

Synergistic interactions in carcinogenesis, 297–298

Systemic oxidative stress, 469–470

T

Tar delivery, 15, 36, 39

Target populations, 19–20

Tar (particulate) phase of tobacco smoke, 30

Taxes, tobacco, 653, 664–665

T cells, 75–76

Test methods

FTC, 16

new products, 19

TGF-α, 600–601

TGF-β3, 600–601

Thioredoxins, 365

Third National Health and Nutrition Examination Survey, 554

Thrombogenic effects

blood alterations in, 375–380

secondhand smoke exposure and, 381

vascular alterations, 380–381

Thrombosis, 381–382

Thromboxane A/s12/s0, 534

Tissue factor, 380

Tissue plasminogen activator, 380–381

Tissue remodeling, 453–456

Tobacco

alkaloids, 31–32

processing, 45–46

reconstituted, 45–46

types of, 34, 36

Tobacco casing, 44

Tobacco control measures, 660–666

Tobacco epidemic, global, 647–651, 652–654

Tobacco industry, 15, 20. See also specific companies

marketing, 653–654

publicly released documents, 16, 33, 34, 116

Tobacco lamina, 9

Tobacco smoke

activation of cell-surface receptors in airway epithelial cells 

by, 288–292

additives, effect of, 44–45

carcinogens in (See Carcinogens)

causation of disease schema, 5f

characteristics, 438–439

chemistry of (See Chemistry of tobacco smoke)

dosimetry of, 439–440

gene promoter hypermethylation induction, 292–294

genotoxicity, 56–59

inhalation studies, 63–67

phases, 30–31

secondhand (See Secondhand smoke)

susceptibility to, 475–487

Tobacco-specific nitrosamines (TSNAs), 35f, 79, 226, 232, 252

as biomarker, 10

DNA adducts, 10

lower yield tobacco products, 17

urinary metabolites, 10

Tolerance, nicotine, 116–117

TP53 gene, 295

G→T transversions, 279–283

in lung cancer, 278–279

Transcription-coupled repair, 257–258

Transdermal system. See Nicotine patches

Translesion synthesis, 269–272

Treating Tobacco Use and Dependence: Clinical Practice 

Guidelines (PHS), 395

TSNAs. See Tobacco-specific nitrosamines

Tubal (oviduct) function, 72, 534, 566, 586

Tumor-suppressor genes, 274–275

inactivation, 277–278

U

Uncharacterized adducts, 244

Unconditioned stimuli, 120

Unilateral emphysema, 447

United Kingdom Prospective Diabetes Study, 386

University of Minnesota Transdisciplinary Tobacco Use Research 

Center, 19

Upper aerodigestive tract cancer, 58

Uridine-5’-diphosphate-glucuronosyltransferases, 240–241

Urinary biomarkers, 230, 234

U.S. Lung Health Study, 367, 403, 649

U.S. Tobacco Use and Dependence Guideline Panel, 653

Uterine blood flow, 576–577
Surgeon General’s Report

704

V

Vapor inhalers, nicotine, 113t

Varenicline, 154, 401, 402

Vascular homeostasis, 371–372

Vasoconstriction, coronary, 369

Vasodilation, endothelium-dependent, 372–373

Vigabatrin, 128

Virchow’s triad, 375

Vitamin C, 381, 461

deficiency, 599, 611

Vitamin E, 461

Volatile compounds, 38–40

Volatile nitrosamines, 34

Von Willebrand protein, 380

W

Waterpipe smoking, 655

Wechsler Preschool and Primary Scale of Intelligence - Revised, 

541

Weight. See also Low birth weight

smoking and, 77, 129

WHO. See World Health Organization

Withdrawal, 117–118. See also Relapse

animal studies, 131

behavioral signs, 132–133

molecular mechanisms, 133–134

neurochemical correlates, 132

neurosubstrates of, 131–133

psychiatric comorbidity, 134–136

receptors, 132–133

symptoms, 175–176

Women. See also Reproductive and developmental effects

cardiovascular disease, 360

endocrine system, 555–557, 558t–560t

mortality, 360

smoking behavior, 48

smoking topography, 33

2001 Surgeon General’s report on, 524

withdrawal, 118

World Health Organization (WHO)

on global tobacco epidemic, 647

MPOWER Framework, 653–654

research, 386

X

Xeroderma pigmentosum A (XPA), 266

Xeroderma pigmentosum C (XPC), 266

Xeroderma pigmentosum complementation group D (XPD), 

266–267

XPF/ERCC1 gene complex, 267

XPG/ERCC5 gene complex, 267

XRCC1 (cross-complementation group 1 for excision repair) 

gene, 264–265, 266

Y

Youth. See also Adolescents

marketing to, 19

Z

Zinc

deficiencies of, 599–600

in tobacco smoke, 390, 613

Zuckerman Sensation Seeking Scale, 159