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
Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, United States of America.
Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
PLoS One. 2015 Oct 30;10(10):e0140496. doi: 10.1371/journal.pone.0140496. eCollection 2015.
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.
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).
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.
高血压是一系列心血管疾病（CVD）的主要危险因素，包括心肌梗死、猝死和中风。在美国，超过6500万人患有高血压，其中很大一部分人被开了抗高血压药物。尽管过去几十年进行的大型长期临床试验已经确定了一些有效的抗高血压治疗方法，这些方法可降低未来临床并发症的风险，但个体对治疗的反应以及对心血管事件的预防存在差异。
我们在21267名接受药物治疗的高血压参与者中进行了全基因组关联研究，探讨基因变异可能影响或改变常用抗高血压治疗对主要心血管结局风险的有效性这一假设。药物治疗类别包括血管紧张素转换酶抑制剂、β受体阻滞剂、钙通道阻滞剂和利尿剂。在基因组流行病学心脏与衰老研究队列（CHARGE）联盟的背景下，每项研究都进行了基于阵列的全基因组基因分型，推算至HapMap II期参考面板，并在比例风险或逻辑回归模型中使用加性遗传模型来评估四种治疗药物类别中每种药物与基因的相互作用。我们使用荟萃分析在15375名欧洲血统参与者（3527例CVD病例）的发现分析中结合约200万个单核苷酸多态性（SNP）的研究特异性相互作用估计值，并在1751名欧洲血统GenHAT参与者以及4141名非裔美国人（1267例CVD病例）的仅病例研究中进行有针对性的随访。
尽管药物与SNP的相互作用在生物学上似乎合理，暴露和结局测量良好，且有足够的检验效能来检测适度的相互作用，但我们在四项抗高血压治疗荟萃分析中未发现任何具有统计学意义的相互作用（P相互作用>5.0×10 - 8）。同样，对于仅限于来自已发表的大型全基因组关联研究中对冠状动脉疾病或血压有显著主要影响的66个SNP的荟萃分析，结果也是阴性（P相互作用≥0.01）。我们的结果表明，常见SNP对血压药物与新发CVD风险之间的关系没有主要的药物遗传学影响。
