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

描述(由申请人提供)：现代药物疗法的好处可以通过避免对遗传上易发生不良反应的患者使用某些药物或通过为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候选基因方法；然而，被证明对健康有益的临床应用仍然很少或遥远。近年来，全基因组关联研究发现了大量与复杂疾病相关的常见遗传位点。确定影响药物反应的新的变异体和途径的Gwas方法可以补充候选基因方法。背景是基因组流行病学中心脏和老龄化研究(CHARD)联盟的队列，该联盟的成立是为了促进在多项大型基于人群的前瞻性队列研究之间进行GWAS荟萃分析，这些研究包括年龄、基因/环境易感性研究、社区动脉粥样硬化风险、心血管健康研究、Framingham心脏病研究和鹿特丹研究。健康ABC研究、动脉粥样硬化多种族研究、青年冠状动脉风险发展和杰克逊心脏研究都加入了这一努力。电荷数据共享模式加速了复杂疾病的新遗传基因座的发现。利用超过57,000名参与者(22.4%的非裔美国人)的全基因组数据，拟议的项目将使用Gwas方法来确定遗传基因座，这些基因座可以改变选定药物对各种结果的影响，重点是意外的不良药物影响。在这一修订的应用中，主要目的涉及通过心电图QTC间期评估心肌复极的结果；感兴趣的四种主要暴露是：(1)高扭矩风险QT延长药物的使用(选定的抗心律失常药、抗组胺药、抗生素和抗抑郁药)；(2)磺脲类药物；(3)噻嗪类利尿剂；以及(4)三环和四环抗抑郁药。除了与QTC相关的这项主要工作外，我们还计划评估其他潜在的药物-基因相互作用，例如利尿剂与血钾水平的使用，抗抑郁药和利尿剂与心电图QRS间期的使用，β-受体阻滞剂和钙拮抗剂及PR间期的使用，阿司匹林与心血管事件(阿司匹林使用者的“阿司匹林衰竭”)的使用，以及非类固醇抗炎药、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的使用。与公共健康相关：这项基础广泛的发现工作可能会阐明新的生物机制，影响某些药物的处方方式，并为新疗法确定新的靶点。

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.