Drug-Gene Interactions of Antihypertensive Medications and Risk of Incident Cardiovascular Disease: A Pharmacogenomics Study from the CHARGE Consortium
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Drug-Gene Interactions of Antihypertensive Medications and Risk of Incident Cardiovascular Disease : A Pharmacogenomics Study from the CHARGE Consortium. / Bis, Joshua C; Sitlani, Colleen; Irvin, Ryan; Avery, Christy L; Smith, Albert Vernon; Sun, Fangui; Evans, Daniel S; Musani, Solomon K; Li, Xiaohui; Trompet, Stella; Krijthe, Bouwe P; Harris, Tamara B; Quibrera, P Miguel; Brody, Jennifer A; Demissie, Serkalem; Davis, Barry R; Wiggins, Kerri L; Tranah, Gregory J; Lange, Leslie A; Sotoodehnia, Nona; Stott, David J; Franco, Oscar H; Launer, Lenore J; Stürmer, Til; Taylor, Kent D; Cupples, L Adrienne; Eckfeldt, John H; Smith, Nicholas L; Liu, Yongmei; Wilson, James G; Heckbert, Susan R; Buckley, Brendan M; Ikram, M Arfan; Boerwinkle, Eric; Chen, Yii-Der Ida; de Craen, Anton J M; Uitterlinden, Andre G; Rotter, Jerome I; Ford, Ian; Hofman, Albert; Sattar, Naveed; Slagboom, P Eline; Westendorp, Rudi G J; Gudnason, Vilmundur; Vasan, Ramachandran S; Lumley, Thomas; Cummings, Steven R; Taylor, Herman A; Post, Wendy; Jukema, J Wouter; Stricker, Bruno H; Whitsel, Eric A; Psaty, Bruce M; Arnett, Donna.
In: PLOS ONE, Vol. 10, No. 10, e0140496, 30.10.2015, p. 1-13.Research output: Contribution to journal › Journal article › peer-review
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TY - JOUR
T1 - Drug-Gene Interactions of Antihypertensive Medications and Risk of Incident Cardiovascular Disease
T2 - A Pharmacogenomics Study from the CHARGE Consortium
AU - Bis, Joshua C
AU - Sitlani, Colleen
AU - Irvin, Ryan
AU - Avery, Christy L
AU - Smith, Albert Vernon
AU - Sun, Fangui
AU - Evans, Daniel S
AU - Musani, Solomon K
AU - Li, Xiaohui
AU - Trompet, Stella
AU - Krijthe, Bouwe P
AU - Harris, Tamara B
AU - Quibrera, P Miguel
AU - Brody, Jennifer A
AU - Demissie, Serkalem
AU - Davis, Barry R
AU - Wiggins, Kerri L
AU - Tranah, Gregory J
AU - Lange, Leslie A
AU - Sotoodehnia, Nona
AU - Stott, David J
AU - Franco, Oscar H
AU - Launer, Lenore J
AU - Stürmer, Til
AU - Taylor, Kent D
AU - Cupples, L Adrienne
AU - Eckfeldt, John H
AU - Smith, Nicholas L
AU - Liu, Yongmei
AU - Wilson, James G
AU - Heckbert, Susan R
AU - Buckley, Brendan M
AU - Ikram, M Arfan
AU - Boerwinkle, Eric
AU - Chen, Yii-Der Ida
AU - de Craen, Anton J M
AU - Uitterlinden, Andre G
AU - Rotter, Jerome I
AU - Ford, Ian
AU - Hofman, Albert
AU - Sattar, Naveed
AU - Slagboom, P Eline
AU - Westendorp, Rudi G J
AU - Gudnason, Vilmundur
AU - Vasan, Ramachandran S
AU - Lumley, Thomas
AU - Cummings, Steven R
AU - Taylor, Herman A
AU - Post, Wendy
AU - Jukema, J Wouter
AU - Stricker, Bruno H
AU - Whitsel, Eric A
AU - Psaty, Bruce M
AU - Arnett, Donna
PY - 2015/10/30
Y1 - 2015/10/30
N2 - 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.
AB - 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.
U2 - 10.1371/journal.pone.0140496
DO - 10.1371/journal.pone.0140496
M3 - Journal article
C2 - 26516778
VL - 10
SP - 1
EP - 13
JO - PLoS ONE
JF - PLoS ONE
SN - 1932-6203
IS - 10
M1 - e0140496
ER -
ID: 147133088