Article open access publication

Drug-Gene Interactions of Antihypertensive Medications and Risk of Incident Cardiovascular Disease: A Pharmacogenomics Study from the CHARGE Consortium

PLoS ONE, Public Library of Science (PLoS), ISSN 1932-6203

Volume 10, 10, 2015

DOI:10.1371/journal.pone.0140496, Dimensions: pub.1027906390, PMC: PMC4627813, PMID: 26516778,



  1. (1) University of Washington, grid.34477.33
  2. (2) University of Alabama at Birmingham, grid.265892.2
  3. (3) University of North Carolina at Chapel Hill, grid.10698.36
  4. (4) Icelandic Heart Association, grid.420802.c
  5. (5) University of Iceland, grid.14013.37
  6. (6) Boston University, grid.189504.1
  7. (7) California Pacific Medical Center, grid.17866.3e
  8. (8) University of Mississippi Medical Center, grid.410721.1
  9. (9) Harbor–UCLA Medical Center, grid.239844.0
  10. (10) Los Angeles Biomedical Research Institute, grid.279946.7
  11. (11) Leiden University Medical Center, grid.10419.3d
  12. (12) Erasmus University Medical Center, grid.5645.2
  13. (13) National Institutes of Health, grid.94365.3d
  14. (14) The University of Texas Health Science Center at Houston, grid.267308.8
  15. (15) University of California, San Francisco, grid.266102.1
  16. (16) University of Glasgow, grid.8756.c
  17. (17) University of North Carolina—GSK Center of Excellence in Pharmacoepidemiology, Chapel Hill, North Carolina, United States of America
  18. (18) The Framingham Heart Study, Framingham, Massachusetts, United States of America
  19. (19) University of Minnesota, grid.17635.36
  20. (20) Seattle Epidemiologic Research and Information Center of the Department of Veterans Affairs Office of Research and Development, Seattle, Washington, United States of America
  21. (21) Group Health Cooperative, grid.280243.f
  22. (22) Wake Forest University, grid.241167.7
  23. (23) University College Cork, grid.7872.a
  24. (24) BHF Glasgow Cardiovascular Research Centre, Faculty of Medicine, Glasgow, United Kingdom
  25. (25) University of Copenhagen, grid.5254.6, KU
  26. (26) Boston University School of Medicine, grid.475010.7
  27. (27) University of Auckland, grid.9654.e
  28. (28) Morehouse School of Medicine, grid.9001.8
  29. (29) Johns Hopkins University, grid.21107.35
  30. (30) Inspectorate for Health Care, the Hague, The Netherlands


BACKGROUND: Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals. METHODS: Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases). RESULTS: Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction > 5.0×10-8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD.


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