Gene Expression Algorithm for Prevalent Coronary Artery Disease: A First Step in a Long Journey
Authors: Donna K. Arnett
Journal: Annals of Internal Medicine (2010)

Editorials5 October 2010Gene Expression Algorithm for Prevalent Coronary Artery Disease: A First Step in a Long JourneyDonna K. Arnett, MSPH, PhDDonna K. Arnett, MSPH, PhDFrom University of Alabama at Birmingham, Birmingham, AL 35294.Author, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-153-7-201010050-00011 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail The development of a noninvasive method for accurately estimating the risk for coronary artery disease (CAD) is a high clinical and public health priority; the disease is the leading cause of death in the United States and is growing in importance globally (1, 2). Coronary angiography, the gold standard for detecting CAD, is expensive and poses risks to patients (3, 4); the currently available "noninvasive" methods for classifying CAD risk are not truly noninvasive, because they expose patients to radiation and contrast agents (5); and risk algorithms, such as the Framingham risk score, misclassify risk in some patients. A truly ...References1. Lloyd-Jones D, Adams RJ, Brown TM, Carnethon M, Dai S, De Simone G, et al; Writing Group Members. Heart disease and stroke statistics—2010 update: a report from the American Heart Association. Circulation. 2010;121:46-e215. [PMID: 20019324] MedlineGoogle Scholar2. Mathers CD, Loncar D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med. 2006;3:442. [PMID: 17132052] CrossrefMedlineGoogle Scholar3. Wyman RM, Safian RD, Portway V, Skillman JJ, McKay RG, Baim DS. Current complications of diagnostic and therapeutic cardiac catheterization. J Am Coll Cardiol. 1988;12:1400-6. [PMID: 2973480] CrossrefMedlineGoogle Scholar4. Batyraliev T, Ayalp MR, Sercelik A, Karben Z, Dinler G, Besnili F, et al. Complications of cardiac catheterization: a single-center study. Angiology. 2005;56:75-80. [PMID: 15678259] CrossrefMedlineGoogle Scholar5. Wang CC, Chang SH, Chen CC, Huang HL, Hsieh IC. Severe coronary artery spasm with anaphylactoid shock caused by contrast medium—case reports. Angiology. 2006;57:225-9. [PMID: 16518532] CrossrefMedlineGoogle Scholar6. Rosenberg S, Elashoff MR, Beineke P, Daniels SE, Wingrove JA, Tingley WG, et al; PREDICT Investigators. Multicenter validation of the diagnostic accuracy of a blood-based gene expression test for assessing obstructive coronary artery disease in nondiabetic patients. Ann Intern Med. 2010;153:425-34. LinkGoogle Scholar7. Hunter DJ, Khoury MJ, Drazen JM. Letting the genome out of the bottle—will we get our wish? N Engl J Med. 2008;358:105-7. [PMID: 18184955] CrossrefMedlineGoogle Scholar8. Feero WG, Guttmacher AE, Collins FS. Genomic medicine—an updated primer. N Engl J Med. 2010;362:2001-11. [PMID: 20505179] CrossrefMedlineGoogle Scholar9. Steyerberg EW, Vickers AJ, Cook NR, Gerds T, Gonen M, Obuchowski N, et al. Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology. 2010;21:128-38. [PMID: 20010215] CrossrefMedlineGoogle Scholar10. LOC100130339 hypothetical protein LOC100130339 [Homo sapiens]. Bethesda, MD: National Center for Biotechnology Information; 2008. Accessed at www.ncbi.nlm.nih.gov/gene/?term=AF289562 on 31 August 2010. Google Scholar11. Humphries SE, Drenos F, Ken-Dror G, Talmud PJ. Coronary heart disease risk prediction in the era of genome-wide association studies: current status and what the future holds. Circulation. 2010;121:2235-48. [PMID: 20497987] CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAuthors: Donna K. Arnett, MSPH, PhDAffiliations: From University of Alabama at Birmingham, Birmingham, AL 35294.Disclosures: None disclosed. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M10-2025.Corresponding Author: Donna K. Arnett, MSPH, PhD, Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, RPHB 220E, 1530 3rd Avenue South, Birmingham, AL 35294-0022; e-mail, arnett@uab.edu. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoMulticenter Validation of the Diagnostic Accuracy of a Blood-Based Gene Expression Test for Assessing Obstructive Coronary Artery Disease in Nondiabetic Patients Steven Rosenberg , Michael R. Elashoff , Philip Beineke , Susan E. Daniels , James A. Wingrove , Whittemore G. Tingley , Philip T. Sager , Amy J. Sehnert , May Yau , William E. Kraus , L. Kristin Newby , Robert S. Schwartz , Szilard Voros , Stephen G. Ellis , Naeem Tahirkheli , Ron Waksman , John McPherson , Alexandra Lansky , Mary E. Winn , Nicholas J. Schork , and Eric J. Topol , for the PREDICT (Personalized Risk Evaluation and Diagnosis in the Coronary Tree) Investigators* Metrics Cited byThe limitations of opportunistic epidemiology, pseudopod epidemiologyA gene-expression score to predict obstructive CADA Blood-Based Gene Expression Test for Obstructive Coronary Artery Disease Tested in Symptomatic Nondiabetic Patients Referred for Myocardial Perfusion Imaging The COMPASS Study 5 October 2010Volume 153, Issue 7Page: 473-474KeywordsAlgorithmsAngiographyClinical geneticsGenetic diseasesGeneticsGenomicsMyocardial perfusion imagingPopulation statisticsPrevention, policy, and public healthStable coronary artery disease ePublished: 5 October 2010 Issue Published: 5 October 2010 Copyright & PermissionsCopyright © 2010 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...