Genome-wide association study of coronary artery disease in individuals of African ancestry

项目摘要/摘要 冠状动脉疾病(CAD)是美国成年人死亡的主要原因。它的流行率是 在非洲血统的个体中最高。据估计，遗传因素占26%至69%。 冠心病风险的个体间差异。CAD的大规模全基因组关联研究(GWAS)主要有 在欧洲和东亚祖先的群体中进行了研究，确定了207个独立的基因座 远远的。已确定的基因座中很少有在非洲祖先群体中复制的。大规模的遗传研究 在非洲血统人群中缺乏冠心病的遗传多样性。这项提议将有效地利用现有资源 使用基因组学和流行病学联盟、百万退伍军人计划和其他项目的人口结构 建立队列，为非洲血统人口的遗传研究创造有史以来最大的样本量 冠心病和相关心脏代谢性状的综合表型。我们建议解决以下问题 明确的目标。AIM 1将使用混合作图、单变量GWAS、多变量来询问基因组 在非洲血统人群中确定与冠心病相关的基因座的方法有GWA型和跨种族GWA型。 目标2将使用全表型关联研究、变异-性状系统聚类法和整合基因组法 分析CAD基因座的特征，并深入了解表型、生理和机械影响 这是冠心病的病理生理学基础。目标3将探讨冠心病对公众健康的影响和临床意义 构建多基因冠心病风险评分和识别孟德尔病原变异的风险变异 与非洲血统人群相关的CAD基因综合征。人口结构-- 特异多基因风险评分与罕见低频率致病变异的鉴定 CAD基因的孟德尔综合征将有助于量化非洲血统个体的CAD风险 并有可能缩小跨不同领域的遗传信息临床应用的翻译差距 人口。已识别的冠心病风险基因座的全面跨性状关联将有助于发现 CAD的亚型。改进的遗传CAD风险分类和改进的CAD亚型表型都将有所帮助 随着精准医学在CAD中的实施。从新的基因座阐明的新的生物学见解 在非洲血统人群中识别的也可以推广到其他人群进行诊断， 预防和治疗冠心病。

PROJECT SUMMARY/ABSTRACT Coronary artery disease (CAD) is a leading cause of death among adults in the United States. Its prevalence is highest in individuals of African ancestry. It has been estimated that genetic factors account for 26% to 69% of interindividual variation in CAD risk. Large-scale genome-wide association studies (GWAS) of CAD have mainly been conducted in populations of European and East-Asian ancestries and identified 207 independent loci so far. Few of the identified loci have been replicated in populations of African ancestries. Large-scale genetic study of CAD in African-ancestry populations are lacking. This proposal will efficiently leverage the existing resources of the Population Architecture using Genomics and Epidemiology Consortium, Million Veteran Program and other established cohorts to create the largest-ever sample size for a genetic study of African-ancestry populations comprehensively phenotyped for CAD and related cardiometabolic traits. We propose to address the following Specific Aims. Aim 1 will interrogate the genome using admixture mapping, univariate GWAS, multi-variate GWAS and trans-ethnic GWAS approaches to identify loci associated with CAD in African-ancestry populations. Aim 2 will use phenome-wide association studies, variant-trait hierarchical clustering and integrative genomic analyses to characterize CAD loci and gain insights into phenotypic, physiologic, and mechanistic impacts that underlie the pathophysiology of CAD. Aim 3 will explore the public health impact and clinical relevance of CAD risk variants by constructing polygenic CAD risk scores and identifying pathogenic variants in Mendelian syndromes of CAD genes that are relevant to African-ancestry populations. The construction of population- specific polygenic risk scores and identification of rare and low-frequency pathogenic variants of large effect in Mendelian syndromes of CAD genes will facilitate quantification of CAD risk in individuals of African ancestry and potentially narrow the translational gap towards clinical use of genetic information across diverse populations. The comprehensive cross-trait associations of identified CAD risk loci will facilitate the discovery of subtypes of CAD. Both improved genetic CAD risk classifications and refined CAD sub-phenotyping would help with the implementation of precision medicine in CAD. The new biological insights elucidated from novel loci identified in African-ancestry populations may also be generalized to other populations for the diagnosis, prevention, and treatment of CAD.