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PLoS One. 2015 Oct 30;10(10):e0140496. doi: 10.1371/journal.pone.0140496. eCollection 2015.

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

Author information

1
Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, United States of America.
2
Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
3
Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina, United States of America.
4
Icelandic Heart Association, Kopavogur, Iceland; Faculty of Medicine, University of Iceland, Reykjavik, Iceland.
5
Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America.
6
California Pacific Medical Center Research Institute, San Francisco, California, United States of America.
7
Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America.
8
Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America; Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California, United States of America.
9
Department of Cardiology, Leiden University Medical Center, The Netherlands; Department of Gerontology and Geriatrics, Leiden University Medical Center, The Netherlands.
10
Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.
11
Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America.
12
Collaborative Studies Coordinating Center, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina, United States of America.
13
Department of Biostatistics, University of Texas School of Public Health, Houston, Texas, United States of America.
14
California Pacific Medical Center Research Institute, San Francisco, California, United States of America; Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, United States of America.
15
Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, 27599, United States of America.
16
Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, United States of America; Cardiology Division, University of Washington, Seattle, Washington, United States of America.
17
Institute of Cardiovascular and Medical Sciences, Faculty of Medicine, University of Glasgow, Glasgow, United Kingdom.
18
Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina, United States of America; University of North Carolina-GSK Center of Excellence in Pharmacoepidemiology, Chapel Hill, North Carolina, United States of America.
19
Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America; The Framingham Heart Study, Framingham, Massachusetts, United States of America.
20
Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, United States of America.
21
Department of Epidemiology, University of Washington, Seattle, Washington, United States of America; Seattle Epidemiologic Research and Information Center of the Department of Veterans Affairs Office of Research and Development, Seattle, Washington, United States of America; Group Health Research Institute, Group Health, Seattle, Washington, United States of America.
22
Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University, Winston-Salem, North Carolina, United States of America.
23
Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, Mississippi, United States of America.
24
Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, United States of America; Department of Epidemiology, University of Washington, Seattle, Washington, United States of America; Group Health Research Institute, Group Health, Seattle, Washington, United States of America.
25
Department of Pharmacology and Therapeutics, University College Cork, Cork, Ireland.
26
Institute for Molecular Medicine, University of Texas Health Science Center, Houston, Texas, United States of America.
27
Department of Gerontology and Geriatrics, Leiden University Medical Center, The Netherlands.
28
Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands; Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands.
29
Robertson Center for Biostatistics, University of Glasgow, Glasgow, United Kingdom.
30
BHF Glasgow Cardiovascular Research Centre, Faculty of Medicine, Glasgow, United Kingdom.
31
Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
32
Faculty of Health and Medical Sciences, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.
33
The Framingham Heart Study, Framingham, Massachusetts, United States of America; Boston University School of Medicine, Boston, Massachusetts, United States of America; Boston University School of Public Health, Boston, Massachusetts, United States of America.
34
Department of Statistics, University of Auckland, Auckland, New Zealand.
35
Department of Medicine, Morehouse School of Medicine, Atlanta, Georgia, United States of America.
36
Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.
37
Department of Cardiology, Leiden University Medical Center, The Netherlands.
38
Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands; Inspectorate for Health Care, the Hague, The Netherlands.
39
Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina, United States of America; Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina United States of America.
40
Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, United States of America; Department of Epidemiology, University of Washington, Seattle, Washington, United States of America; Department of Health Services, University of Washington, Seattle, Washington, United States of America; Group Health Research Institute, Group Health, Seattle, Washington, United States of America.

Abstract

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.

PMID:
26516778
PMCID:
PMC4627813
DOI:
10.1371/journal.pone.0140496
[Indexed for MEDLINE]
Free PMC Article

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