# Presentation: 942449

##          10 Year Perspective  

- Public Health Genomics
- and its Integration into
- Cancer Control and Prevention

## Outline

- Genomics 2008: the gap between scientific excitement and health impact widens
- The four phases of genomics translation
- Public health genomics 2008: closing the gap between genome discoveries and population health
- Vision for the next decade: needs and opportunities and applications in cancer control and prevention

## A New Strategy for Cancer Control Research

- Copyright ©1999 American Association for Cancer Research

**Hiatt, R. A. et al. Cancer Epidemiol Biomarkers Prev 1999;8:957-964**

***A New Strategy for Cancer Control Research***
***Biobehavioral Model for Nicotine Addiction Allowing ***
***Interplay Among Numerous Factors***

## A Framework for Cancer Control Research 

- Copyright ©1999 American Association for Cancer Research

**Hiatt, R. A. et al. Cancer Epidemiol Biomarkers Prev 1999;8:957-964**

***A Framework for Cancer Control Research ***
***(from 1994 Advisory Committee on Cancer Control. Canada***** **

## Successes of Genome Wide Association Studies (GWAS)

- Celiac disease
- Atrial fibrillation
- Colorectal cancer
- Breast cancer
- Prostate cancer
- Diabetes
- Gallstones
- Asthma
- Multiple sclerosis
- Rheumatoid arthritis
- Crohn disease
- Age-related macular   degeneration

- GWAS articles

- HuGENavigator, Jan 2008

## What Do You Do With Genes When You Find Them?

- JAMA March 20, 2008

**“****The Year of perfect vision 2020”**
- "I predict that comprehensive, genomics-based health care will become
-  the norm with individualized preventive medicine and
-  early detection of illnesses” (Zerhouni, 2006)
**Predictive, Preventive and Personalized Medicine**

## What Do You Do With Genes When You Find Them?

- Two challenges for “translation” that need a collaborative approach with a crucial role of population sciences
- Premature Translation
- “Lost   in   Translation”

## Challenge 1: Premature Translation

***Challenge 1: Premature Translation***
***“******Genomics and Personalized Health”***

## “My Genome, Myself: Seeking Clues in DNA” A. Harmon, New York Times, Nov 17, 2007

**"I am convinced that within five years every college-educated **
**person in America is going to have a profile like this. **
**You cannot afford not having this**.“
-  Kari Stefansson, DeCode Genetics-April 1, 2008

## “Long and short: Yesterday personal genomics was an oddity. Today, it's an industry ” April 8, 2008 

**Company A**; “you notice when you get your results is how subtle the differences are between the average person's risk for disease and your own. For colorectal cancer, for instance, my results tell me that I have a .21 out of 100 chance of developing the disease, compared to a .26 out of 100 average risk. That may be scientifically valid distinction, but as a consumer it is so slight as to be no difference.”
**Company B** “uses a different method of calculating your genetic risk. It generates a “lifetime risk analysis” that results in what the company believes are stronger calls. Certainly the numbers seem more emphatic; examples I saw showed, for instance, a person with a 51 percent risk of heart disease, compared to an average 42 percent risk. That's a striking difference”

- _[http://blog.wired.com/wiredscience/2008/04/enter-navigenic.html](http://blog.wired.com/wiredscience/2008/04/enter-navigenic.html)_

## Genetic Testing as a Public Health IssueEvidence based Information Needed! 

## Challenge 2: ”Lost in Translation”C. Lenfant NEJM 2003;349:868

**< 33% of patients with**** ****coronary artery disease are prescribed aspirin**

## ”Lost in Translation”C. Lenfant NEJM 2003;349:868

**    “****About a quarter of the cases of Familial Hypercholesterolemia predicted were diagnosed routinely; most remained undiagnosed until middle age” **
**    **
**     ****HA Neil BMJ (2000) **

**“****Let's be realistic:**** ****If we didn't do it with aspirin,  how can we expect to do it**** ****with DNA?”**

## Outline

- Genomics 2008: the gap between scientific excitement and health impact widens
- The four phases of genomics translation
- Public health genomics 2008: closing the gap between genome discoveries and population health
- Vision for the next decade: needs and opportunities and applications in cancer control and prevention

##  “Translational and Clinical Science—Time for a New Vision”  NIH Roadmap: Bench to BedsideE. Zerhouni NEJM 2005;353:15  

- Discoveries
- (e.g. genetic
- risk factor)

- Promising
- Application
- (e.g. genetic test)

- T1

- Modified from Khoury et al
- Genetics in Medicine 2007

## T1Discovery to Candidate Health Application

***T1******Discovery to Candidate Health Application***

- Candidate health application

- Gene discovery

**Define health outcome & intended use**

**Evaluate**** ****gene/environment/disease associations**

**Identify potential interventions**

**Establish analytic &clinical validity **

**Describe disease biology**

- Courtesy: W. Burke
- Based on Khoury et al. Genet Med 2007

##  “Translational and Clinical Science—Time for a New Vision”  NIH Roadmap: Bench to BedsideE. Zerhouni NEJM 2005;353:15  

- Discoveries
- (e.g. genetic
- risk factor)

- Promising
- Application
- (e.g. genetic test)

- T1

- Modified from Khoury et al
- Genetics in Medicine 2007

## The Second Translation Block:The Roadmap less traveled (L Green) 

- Discoveries
- (e.g. genetic
- risk factor)

- Promising
- Application
- (e.g. genetic test)

- T1

- Evidence based
- Guideline/
- Policy

- T2

- Modified from Khoury et al
- Genetics in Medicine 2007

*Modified from IOM Clinical Research Roundtable, Sung et al JAMA, 2003*

## T2Health Application to Evidence-based Practice Guidelines

***T2******Health Application to Evidence-based Practice Guidelines***

- Practice guidelines

- Candidate health
- application

**Establish clinical utility**

**Evidence synthesis**

**Stakeholder input**

**Evidence-based process**

**Identify evidence gaps: uncertainties about benefits, costs, harms**

- Courtesy: W. Burke
- Based on Khoury et al. Genet Med 2007

## The “Third” Phase in TranslationJM Westfall et al JAMA 2007;2007;297:403.   

- Discoveries
- (e.g. genetic
- risk factor)

- Promising
- Application
- (e.g. genetic test)

- Practice &
- Control
- Programs

- T1

- Evidence based
- Guideline/
- Policy

- T2

- T3

- Modified from Khoury et al
- Genetics in Medicine 2007

## T3Practice Guidelines to Health Practice

***T3******Practice Guidelines to Health Practice***

- Health practice

- Practice guidelines

**Dissemination research**

**Implementation research**

**Phase IV clinical trials/observation**

**Diffusion research**

**Policy analysis: Identify policy options that support appropriate use**

- Courtesy: W. Burke
- Based on Khoury et al/ Genet Med 2007

## The Fourth Phase of Translation: Assessing Population Health Benefits 

- Discoveries
- (e.g. genetic
- risk factor)

- Promising
- Application
- (e.g. genetic test)

- Practice &
- Control
- Programs

- Reducing the
- Burden of
- Disease

- T1

- Evidence based
- Guideline/
- Policy

- T2

- T3

- T4

- Modified from Khoury et al
- Genetics in Medicine 2007

## T4Health Practice to Health Impact

***T4******Health Practice to Health Impact***

- Improved population health

- Health practice

**Define outcomes of interest**

**Identify/develop appropriate metrics**

**Determine benefits and harms**

**Re-evaluate guidelines and policies******** Identify needed changes**

**Implement surveillance**

- Courtesy: W. Burke
- Based on Khoury et al. Genet Med 2007

## The Genomics Translation Highway:2001-2006 

- More than 350,000 published human genetics/genomics articles
- < 3% deal with Translation Research T2 and Beyond
- Only 2 USPSTF Evidence-based recommendations
*BRCA1 (1994-2005)----Do it carefully*
*HFE*  *(1996-2006)----Don’t do it*

## Outline

- Genomics 2008: the gap between scientific excitement and health impact widens
- The four phases of genomics translation
- Public health genomics 2008: closing the gap between genome discoveries and population health
- Vision for the next decade: needs and opportunities and applications in cancer control and prevention

## A Population Health Approach:What is “Public Health Genomics?”

- A multidisciplinary field concerned with the effective and responsible translation of genome-based knowledge and technologies to improve population health
**Focus: **
- Populations
- Gene-environment Interaction
- Prevention
- Evidence-based applications
- ELSI integration
- Health disparities

## Public Health Genomics: Closing the Gap Between

- Gene
- Discovery

**PopulationHealth **

***Public Health Genomics: Closing the Gap Between***
*** ******Gene Discovery and Population Health**** *

** **

**Closing the Gap**

## Public Health Genomics: Closing the Gap Between

- Gene
- Discovery

**PopulationHealth **

***Public Health Genomics: Closing the Gap Between***
*** ******Gene Discovery and Population Health**** *

** **

**Closing the Gap**

**Population Studies**

- US Genome Profile
- Public Health Studies

## Public Health Genomics: Closing the Gap Between

- Gene
- Discovery

**Population**
**Health**

***Public Health Genomics: Closing the Gap Between***
*** ******Gene Discovery and Population Health**** *

** **

**Closing the Gap**

**Population Studies**

- US Genome Profile
- Public Health Studies

- Human
- Genome
- Epidemiology
- Network

**HuGENet**

## Human Genome Epidemiology Network (HuGENet)

**Global collaboration of individuals and organizations to assess population impact of genomics and how it can be used to improve health and prevent disease**
**4 coordinating centers**
**Dozens of networks**
**Hundreds of collaborators**
**10 collaborating journals**
**HuGE Navigator   **

## 56 Genes

- 32  with MA of
-  160 variants

- 24 No Meta
- Analyses

- 100 Not
- Significant

- 60 Significant

**Odds Ratios 0.54-0.88 for protective variants**
**Odds Ratio 1.04-3.2 for risk factor variants **

- Am J Hum Genet March 2008

- 7 Companies

- Jan 17, 2008

## Individual OR and Population Attributable Risk

| Risk factor | OR (95% CI) | Frequency in cases/controls | PAR (%) |
| --- | --- | --- | --- |
| Family history | 2.22 (1.83-2.68) | 0.19/0.09 | 9.89 |
| rs4430796 | 1.38 (1.21-1.57) | 0.38/0.30 | 10.23 |
| rs1859962 | 1.28 (1.11-1.47) | 0.30/0.25 | 6.54 |
| rs16901979 | 1.53 (1.22-1.92) | 0.10/0.07 | 3.58 |
| rs6983267 | 1.37 (1.18-1.59) | 0.82/0.77 | 22.17 |
| rs1447295 | 1.22 (1.06-1.40) | 0.31/0.26 | 5.41 |
| Total |  |  | 46.34 |

**Notes:**
Individually, the risk ratio associated with these 5 SNPs ranged from 1.22 to 1.53, which was lower than RR associated with family history. 

The cumulative population attributable risk indicates that five SNPs plus family history accounted for 46% of the cases of PCA in this study.  

## Distribution of Risk Factors

**%**

**Number of risk factors**

- 8.2

- 1.4   0.3

- 3.5

- 16.6

-  22.2

- 36.0

- 36.4

- 26.9

- 33.6

- 5.0

-  10.1

**Notes:**
This figure showed cumulative distribution of polymorphisms. About 36% of case and 36% control had 2 risk factors. 8.2% cases had 4 risk variants and 1.4% cases had 5 and more risk variants. 

To me, cumulative distribution of polymorphisms is not quite different between cases and controls 

## Comparison of 3 models

- AUC=57.7              AUC=60.8               AUC=63.3
- Model 1                  Model 2                   Model 3
- Model 1= age + region
- Model 2= Model 1 + family history
- Model 3= Model 2 + 5 SNPs

**Notes:**
In order to assess the effect of adding SNPs in distinguishing cases and controls subject, they compared 3 models by constructing receiver-operating-characteristic (ROC) curves and calculated statistics for the area under the curve (AUC).  

Model 1= age + region     
Model 2= Model 1 + family history
Model 3= Model 2 + 5 SNPs

The authors reported that AUC was 57.7 for model 1, 60.8 for model 2, and 63.3 for model 3 which was sig. higher than that for model 2.  

To me, adding test results to age and family history only marginally improved risk prediction (the area under the curve increased from 0.61 to 0.63). As shown in the last slide, the cumulative distribution of polymorphisms is not so different between cases and controls, so discriminative ability of the test is insufficient to distinguish cases and controls.  

## Public Health Genomics: Closing the Gap Between

- Gene
- Discovery

**Population Health**

***Public Health Genomics: Closing the Gap Between***
*** ******Gene Discovery and Population Health**** *

** **

**Closing the Gap**

**Population Studies**

- US Genome Profile
- Public Health Studies

- Human
- Genome
- Epidemiology
- Network

**HuGENet**

- Evaluation of
- Genomic
- Applications in
- Practice & Prevention

**EGAPP**

## EGAPP 

**E**valuation of
**G**enomic
**A**pplications in
**P**ractice and
**P**revention

- Non-regulatory
- Independent, non-federal, multidisciplinary Working Group
- Integrate existing processes for evaluation and appraisal
- Minimize conflicts of interest
- Evidence-based, transparent, and publicly accountable

**Notes:**
Add spoken comments
CDC-funded initiative intended to establish and test a systematic, evidence-based process for evaluating genetic tests and other applications of genomic technology in transition from research to practice.
Non-regulatory – focused on knowledge synthesis

## 
                         www.egappreviews.org

***                         ******www.egappreviews.org***

## CypP450 Testing in Patients with Depression Treated with SSRI’s

- Non-psychotic depression
- Major cause of disability in the US
- SSRIs are first-line choices for drug therapy
- Choice/dose is highly empirical
- SSRI’s discontinued in 12 - 15% due to side effects
- Cytochrome P450 (CYP450) enzymes metabolize many drugs e.g. _SSRI’s_
- Genetic variants result in extensive, intermediate and poor metabolizers

## What’s the Evidence?

- Analytic validity
- Does the test accurately and reliably measure CYP450 genotype?
- Accuracy and reliability appear high
- Clinical validity
- Does the test result correlate with the clinical outcomes: circulating drug levels, clinical response, side effects?
- Study quality poor
- No consistent association between CYP450 genotype and clinical response to SSRI treatment or side effects
- Clinical Utility
- Does knowledge of the test result change patient management?
- Does use of the test result in improved patient outcomes?
- No evidence to support improved clinical outcomes

## ER

| EGAPP Topics Under Review 2008   |  |  |  |
| --- | --- | --- | --- |
| Disorder/Effect | Test | Target Population | Intended Use |
| Breast Cancer | CYP2D6 | Individuals prior to treatment for BrCa | Treatment with Tamoxifen |
| Diabetes, Type II | TCF7L2 | General population | Risk assessment |
| Cardiovascular Disease | Multigene panels | General population | Risk prediction; drug or nutritional/lifestyle management  |
| Thrombophilia | F5, F2 | Individuals with family history or clinical suspicion of thrombophilia | Prevention and management |
| Breast Cancer | Gene expression profiles | Women diagnosed with breast cancer | Treatment and recurrence risk  |
| Colorectal Cancer (CRC) | UGT1A1 | Individuals diagnosed with CRC | Treatment with Irinotecan |
| Hereditary Nonpolyposis Colorectal Cancer (HNPCC) | Mismatch repair gene mutations | Individuals diagnosed with CRC and their family members | Management of individuals and early detection/prevention for family members |
| Depression | CYP450 | Individuals diagnosed with depression | Treatment with SSRI drugs |
| Ovarian Cancer | Genomic Tests | 1) General population of women and; 2) women at increased risk for ovarian cancer | Detection and management |

- ER

- 

**Sel**

**Plan**

**In prog**

**In prog**

## Public Health Genomics: Closing the Gap Between

- Gene
- Discovery

**Population Health**

***Public Health Genomics: Closing the Gap Between***
*** ******Gene Discovery and Population Health**** *

** **

**Closing the Gap**

**Population Studies**

- US Genome Profile
- Public Health Studies

- Human
- Genome
- Epidemiology
- Network

**HuGENet**

- Evaluation of
- Genomic
- Applications in
- Practice & Prevention

**EGAPP**

- Family history
- State Capacity
- Genomics Centers
- Two new Translation RFAs

**Practice**

## RFAs in Genomics Translation

- FY08: 2 CDC RFAs to fund genomics translation research and programs
- Includes genetic/genomic tests and family history
- Close the gaps identified through EGAPP
- Partnership development process (federal, state, academia,  private sector)
- Translation Network for  Genomic Applications in  Practice and Prevention (GAPPNet)

## Outline

- Genomics 2008: the gap between scientific excitement and health impact widens
- The four phases of genomics translation
- Public health genomics 2008: closing the gap between genome discoveries and population health
- Vision for the next decade: needs and opportunities and applications in cancer control and prevention

## Public Health Genomics: Needs and Opportunities for the Next Decade 

- Accelerate the process of translation to close the widening gap (with balanced investment in T1 through T4)
- Enhance knowledge synthesis and evidence based guidelines and policies for better decision making
- Engage/empower consumers and educate providers with decision support tools such as family history and genetic test information
- Expand public-private partnerships to enhance the pipeline for appropriate integration of genomics into health and health care

## A Population Health Approach to Genomics Translation: Application to Cancer  

- Discoveries
- (e.g. genetic
- risk factor)

- Promising
- Application
- (e.g. genetic test)

- Cancer
- Practice &
- Control
- Programs

- Reducing the
- Burden of
- Cancer

- T1

- Evidence based
- Guideline/
- Policy

- T2

- T3

- T4

- Modified from Khoury et al
- Genetics in Medicine 2007
- & Am J Prev Med 2007

**Population**
**Sciences**

## A Population Health Approach to Cancer Control and Prevention  

- Discoveries

- Promising
- Applications

- Cancer
- Practice &
- Control
- Programs

- Reducing the
- Burden of
- Cancer

- T1

- Evidence based
- Guideline/
- Policy

- T2

- T3

- T4

- Modified from Khoury et al
- Genetics in Medicine 2007
- & Am J Prev Med 2007

**Population**
**Sciences**

## What will I be doing at DCCPS?

- Apply what I learned to public health genomics to cancer (and learn a whole lot more)
- Work with DCCPS programs to help integrate public health genomics into research and application portfolios
- PHG Interest group
- Collaborations and new initiatives
- Training and educational programs
- Topics of high priority
- Gene-environment interaction
- Pharmacogenomics
- Family history
- Behavioral and social sciences
- Genetic, cellular and molecular tests
- Knowledge synthesis
- Connect with other parts of NCI and NIH
- Have fun!