Prospective meta-analyses of drug-gene interactions: CHARGE GWAS consortium

描述（由申请人提供）：现代药物治疗的益处可以通过避免对遗传上易受不良反应影响的患者使用某些药物或对遗传上可能受益的患者选择其他药物来最大化。药物遗传学研究通常依赖于候选基因方法；然而，证明对健康有益的临床应用仍然很少或很遥远。近年来，全基因组关联研究（GWAS）发现了大量与复杂疾病相关的常见遗传位点。GWAS方法用于识别影响药物反应的新变异和途径，可以补充候选基因方法。该研究的背景是基因组流行病学心脏和衰老研究（CHARGE）联盟的队列，该联盟的成立是为了促进对多个大型人群前瞻性队列研究的GWAS荟萃分析，包括年龄、基因/环境易感研究、社区动脉粥样硬化风险、心血管健康研究、弗雷明汉心脏研究和鹿特丹研究。健康ABC研究、动脉粥样硬化的多种族研究、年轻人冠状动脉风险发展和杰克逊心脏研究都加入了这项工作。CHARGE数据共享模型加速了复杂疾病新基因位点的发现。利用57,000多名参与者（22.4%是非裔美国人）的全基因组数据，拟议的项目将使用GWAS方法识别基因位点，这些基因位点可以改变选定药物对各种结果的影响，重点关注药物的意外副作用。在修订后的应用程序中，主要目的是通过ECG QTc间期评估心肌复极的结果；四种主要暴露是：(1)使用高扭转风险延长qt的药物（选定的抗心律失常药、抗组胺药、抗生素和抗抑郁药）；(2)磺脲类抗糖尿病药；(3)噻嗪类利尿剂，(4)三环和四环抗抑郁药。除了这项与QTc相关的主要工作外，我们计划评估其他潜在的药物-基因相互作用，如利尿剂与血清钾水平的使用，抗抑郁药和利尿剂与ECG QRS间期的使用，β受体阻滞剂和钙拮抗剂与PR间期的使用，阿司匹林与心血管事件的使用（阿司匹林使用者中的“阿司匹林失效”），以及非甾体抗炎药的使用，血管紧张素转换酶抑制剂，血管紧张素受体阻滞剂和肾功能利尿剂。公共卫生相关性：这种广泛的发现工作可能阐明新的生物机制，影响某些药物的处方，并确定新疗法的新靶点。

DESCRIPTION (provided by applicant): The benefits of modern drug therapies can be maximized by avoiding some medications in patients who are genetically susceptible to adverse reactions or by selecting other medications for patients who are genetically likely to benefit. Pharmacogenetic studies have usually relied on candidate-gene approaches; yet clinical applications with demonstrated health benefits remain few or far off. Recently, genome-wide association studies (GWAS) have discovered a large number of common genetic loci associated with complex disorders. GWAS methods to identify novel variants and pathways that affect drug response can complement the candidate-gene approaches. The setting is the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, formed to facilitate GWAS meta-analyses among multiple large population-based prospective cohort studies, including Age, Gene/ Environment Susceptibility Study, Atherosclerosis Risk in Communities, Cardiovascular Health Study, Framingham Heart Study, and the Rotterdam Study. Health ABC Study, the Multi-Ethnic Study of Atherosclerosis, the Coronary Artery Risk Development in Young Adults, and the Jackson Heart Study have joined the effort. The CHARGE data- sharing model has accelerated the discovery of novel genetic loci for complex diseases. With genome-wide data on more than 57,000 participants (22.4% African Americans), the proposed project will use GWAS methods to identify genetic loci that modify the effects of selected drugs on a variety of outcomes with a focus on unintended adverse drug effects. In this revised application, the primary aim involves the outcome of myocardial repolarization as assessed by the ECG QTc interval; and the four primary exposures of interest are: (1) use of high-torsades-risk QT-prolonging drugs (selected antiarrhythmics, antihistamines, antibiotics, and antidepressants); (2) sulfonylurea anti-diabetic agents; (3) thiazide diuretics, and (4) tri-cyclic and tetra- cyclic anti-depressants. In addition to this primary effort related to QTc, we plan to evaluate other potential drug-gene interactions such as the use of diuretics with serum potassium levels, the use of anti-depressants and diuretics with the ECG QRS interval, the use of beta-blockers and calcium antagonists and the PR interval, the use of aspirin with cardiovascular events ("aspirin failure" among aspirin users), and use of non-steroidal anti-inflammatory drugs, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, and diuretics with renal function. Public-health relevance: This broad-based discovery effort is likely to illuminate novel biologic mechanisms, affect how some drugs are prescribed, and identify novel targets for new therapies.