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Personalized Genetic Prediction: Too Limited, Too Expensive, or Too Soon?

2009; American College of Physicians; Volume: 150; Issue: 2 Linguagem: Inglês

10.7326/0003-4819-150-2-200901200-00012

1539-3704

John P. A. Ioannidis,

Genomics and Rare Diseases

Editorials20 January 2009Personalized Genetic Prediction: Too Limited, Too Expensive, or Too Soon?John P.A. Ioannidis, MDJohn P.A. Ioannidis, MDFrom the University of Ioannina, Iaonnina 45110, Greece.Author, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-150-2-200901200-00012 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Genetic epidemiology has identified many common genetic variants that are associated with common diseases, and the list is growing monthly (1, 2). This success has boosted expectations for personalized genetic prediction. According to these expectations, genetic information can tell people about their risk for various diseases and which medications they should use or avoid. However, 2 articles in this issue (3, 4) suggest that this promise may be exaggerated and premature.Paynter and colleagues (3) evaluated the predictive performance of rs10757274 for cardiovascular disease (CVD) in 22 129 white women. This gene variant has emerged from genome-wide association studies, and its ...References1. McCarthy MI, Abecasis GR, Cardon LR, Goldstein DB, Little J, Ioannidis JP, et al. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat Rev Genet. 2008;9:356-69. [PMID: 18398418] CrossrefMedlineGoogle Scholar2. Manolio TA, Brooks LD, Collins FS. A HapMap harvest of insights into the genetics of common disease. J Clin Invest. 2008;118:1590-605. [PMID: 18451988] CrossrefMedlineGoogle Scholar3. Paynter NP, Chasman DI, Buring JE, Shiffman D, Cook NR, Ridker PM. Cardiovascular disease risk prediction with and without knowledge of genetic variation at chromosome 9p21.3. Ann Intern Med. 2009;150:65-72. LinkGoogle Scholar4. Eckman MH, Rosand J, Greenberg SM, Gage BF. Cost-effectiveness of using pharmacogenetic information in warfarin dosing for patients with nonvalvular atrial fibrillation. Ann Intern Med. 2009;150:73-83. LinkGoogle Scholar5. Schunkert H, Götz A, Braund P, McGinnis R, Tregouet DA, Mangino M, et al; Cardiogenics Consortium. Repeated replication and a prospective meta-analysis of the association between chromosome 9p21.3 and coronary artery disease. Circulation. 2008;117:1675-84. [PMID: 18362232] CrossrefMedlineGoogle Scholar6. Kathiresan S, Melander O, Anevski D, Guiducci C, Burtt NP, Roos C, et al. Polymorphisms associated with cholesterol and risk of cardiovascular events. N Engl J Med. 2008;358:1240-9. [PMID: 18354102] CrossrefMedlineGoogle Scholar7. Zheng SL, Sun J, Wiklund F, Smith S, Stattin P, Li G, et al. Cumulative association of five genetic variants with prostate cancer. N Engl J Med. 2008;358:910-9. [PMID: 18199855] CrossrefMedlineGoogle Scholar8. 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[PMID: 18587394] CrossrefMedlineGoogle Scholar12. 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 Scholar13. Little J, Higgins JPT, Ioannidis JPA, Moher D, Gagnon F, von Elm E, et al. Strengthening the Reporting of Genetic Association Studies (STREGA): an extension of the STROBE statement. Ann Intern Med. 2009. [Forthcoming]. Google Scholar14. Ioannidis JP. Molecular evidence-based medicine: evolution and integration of information in the genomic era. Eur J Clin Invest. 2007;37:340-9. [PMID: 17461979] CrossrefMedlineGoogle Scholar15. Ioannidis JP, Boffetta P, Little J, O'Brien TR, Uitterlinden AG, Vineis P, et al. Assessment of cumulative evidence on genetic associations: interim guidelines. Int J Epidemiol. 2008;37:120-32. [PMID: 17898028] CrossrefMedlineGoogle Scholar16. Janssens AC, Gwinn M, Bradley LA, Oostra BA, van Duijn CM, Khoury MJ. A critical appraisal of the scientific basis of commercial genomic profiles used to assess health risks and personalize health interventions. Am J Hum Genet. 2008;82:593-9. [PMID: 18319070] CrossrefMedlineGoogle Scholar17. Scheuner MT, Sieverding P, Shekelle PG. Delivery of genomic medicine for common chronic adult diseases: a systematic review. JAMA. 2008;299:1320-34. [PMID: 18349093] CrossrefMedlineGoogle Scholar18. Ioannidis JPA. Limits to forecasting in personalized medicine: an overview. Int J Forecast. [Forthcoming]. Google Scholar Author, Article, and Disclosure InformationAffiliations: From the University of Ioannina, Iaonnina 45110, Greece.Disclosures: None disclosed.Corresponding Author: John P.A. Ioannidis, MD, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, University Campus, Ioannina, 45110, Greece; e-mail, [email protected]uoi.gr. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoCardiovascular Disease Risk Prediction With and Without Knowledge of Genetic Variation at Chromosome 9p21.3 Nina P. Paynter , Daniel I. Chasman , Julie E. Buring , Dov Shiffman , Nancy R. Cook , and Paul M. Ridker Cost-Effectiveness of Using Pharmacogenetic Information in Warfarin Dosing for Patients With Nonvalvular Atrial Fibrillation Mark H. Eckman , Jonathan Rosand , Steven M. Greenberg , and Brian F. Gage Metrics Cited byA new non-invasive diagnostic tool in coronary artery disease: artificial intelligence as an essential element of predictive, preventive, and personalized medicinePersonalized Respiratory Medicine: Exploring the Horizon, Addressing the Issues. 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Brent Richards, MD, MSc, Fotini K. Kavvoura, MD, PhD, Fernando Rivadeneira, MD, PhD, Unnur Styrkársdóttir, PhD, Karol Estrada, MSc, Bjarni V. Halldórsson, PhD, Yi-Hsiang Hsu, MD, ScD, M. Carola Zillikens, MD, Scott G. Wilson, PhD, Benjamin H. Mullin, BSc, Najaf Amin, MSc, Yurii S. Aulchenko, PhD, L. Adrienne Cupples, PhD, Panagiotis Deloukas, PhD, Serkalem Demissie, PhD, Albert Hofman, MD, PhD, Augustine Kong, PhD, David Karasik, PhD, Joyce B. van Meurs, PhD, Ben A. Oostra, PhD, Huibert A.P. Pols, MD, PhD, Gunnar Sigurdsson, MD, PhD, Unnur Thorsteinsdottir, PhD, Nicole Soranzo, PhD, Frances M.K. Williams, MD, PhD, Yanhua Zhou, MSc, Stuart H. Ralston, MD, Gudmar Thorleifsson, PhD, Cornelia M. van Duijn, PhD, Douglas P. Kiel, MD, MPH, Kari Stefansson, MD, PhD, André G. Uitterlinden, PhD, John P.A. Ioannidis, MD, PhD, and Tim D. Spector, MD, MSc, for the GEFOS (Genetic Factors for Osteoporosis) ConsortiumPopulation-Wide Generalizability of Genome-Wide Discovered AssociationsComparative effectiveness research and genomic medicine: An evolving partnership for 21st century medicineExpanding the Public Health Research Agenda for Ovarian CancerEnabling personalized medicine through the use of healthcare information technologyThe Scientific Foundation for Personal Genomics: Recommendations from a National Institutes of Health–Centers for Disease Control and Prevention Multidisciplinary WorkshopReporting genetic association studies: the STREGA statementPersonalized Medicine: Reality and Reality Checks 20 January 2009Volume 150, Issue 2Page: 139-141KeywordsBreast cancerCardiovascular diseasesClinical geneticsGenetic diseasesGeneticsHemorrhageMedical risk factorsPharmacogeneticsPopulation statistics ePublished: 20 January 2009 Issue Published: 20 January 2009 Copyright & PermissionsCopyright © 2009 by American College of Physicians. 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