IDENTIFICATION OF COMMON GENETIC VARIANTS FOR ATRIAL FIBRILLATION AND PR INTERVAL

摘要 心房颤动(房颤)是一个重要的公共卫生问题，因为它的发病率越来越高，寿命也越来越长。 风险、成本、发病率和死亡率。目前的房颤疗法部分有效，依从性适中，费用较高， 以及相当高的发病率。因此，有必要更全面地了解 房颤的病因学以确定房颤的风险个体，并为房颤治疗提供新的药物靶点。 2008年，我们组织了AFGen联盟(AFGen)，从那时起，我们高度合作， 国际财团在房颤遗传学领域处于领先地位。我们已经描述了绝大多数超过 已发现与房颤相关的130个遗传位点。为了补充我们的全基因组关联数据，我们 还领导了对房颤患者进行完整外显子组(WES)和基因组测序(WGS)的努力。 我们已经确定了肌瘤蛋白Titin的功能缺失变异，这些变异与 早发性房颤。 在我们的竞争性续签申请中，我们现在寻求在4个方向上扩展我们之前的工作。在目标1中，我们 建议对WES和WGS数据进行最大的基于疾病的分析之一。总的来说，我们将 包括来自NHLBI Trans-Omics for Precision Medicine计划的超过91K个房颤病例和769K个对照， NHGRI常见病基因组计划中心，英国生物库，来自TIMI的5项临床试验 学习，以及我们所有人的计划。我们的主要分析将集中在与房颤相关的识别上 基因。然后我们将利用这些多血统数据来a)精细定位基因座以识别因果变异，b) 开发多基因风险评分，以识别跨祖先的高危个体，以及c)使用孟德尔 随机评估危险因素对房颤的因果影响，以及房颤对心力衰竭和中风的因果影响。在AIM 2、我们建议使用深度学习模型来重建美国的左房(LA)的大小和功能 王国生物库10万人心脏MRI影像资料。在初步研究中，我们得出了 对7个LA性状进行了测量，确定了20多个与LA性状相关的遗传座位，并进行了共定位 左房和房颤风险基因。在目标3中，我们建议通过执行以下操作来验证前50个房颤和左房相关基因 干细胞来源的心房肌细胞的基因扰动分析。我们将进行基因敲除或超过 表达后，使用高含量成像分析心肌细胞结构和电生理学。最后， 在目标4中，我们将支持AFGen联盟的持续努力和对早期阶段的持续培训 虚拟联谊会中的调查员。 我们相信，我们的多学科团队汇集了房颤遗传学方面的非凡专业知识， 流行病学、生物信息学、生物统计学和基础心血管研究。最终，我们预计我们的 这项工作将为房颤的风险分层、预防和治疗提供新的靶点。

Abstract Atrial fibrillation (AF) is of major public health importance because of increasing prevalence, and high lifetime risk, costs, morbidity, and mortality. Current AF therapies have partial efficacy, moderate adherence, high cost, and substantial morbidity. Hence, there is a profound need to develop a more comprehensive understanding of the etiology of AF to identify individuals at risk for AF and novel drug targets for AF therapies. In 2008, we organized the AFGen Consortium (AFGen) and since that time our highly collaborative, international consortium has led the field of AF genetics. We have described the vast majority of the more than 130 genetic loci that have been associated with AF. To complement our genome wide association data, we also have led efforts to perform whole exome (WES) and genome sequencing (WGS) in individuals with AF. We have identified loss of function variants in the sarcomeric protein, titin, that are significantly associated with early-onset AF. In our competitive renewal application, we now seek to extend our prior work in 4 directions. In Aim 1, we propose to conduct one of the largest disease-based analyses of WES and WGS data. In aggregate we will include over 91K AF cases and 769K controls from the NHLBI Trans-Omics for Precision Medicine program, the NHGRI Center for Common Disease Genomics program, the UK Biobank, 5 clinical trials from the TIMI Study, and the All of Us Program. Our primary analysis will be focused on the identification of AF associated genes. We will then take advantage of this multi-ancestry data to a) fine map loci to identify causal variants, b) develop polygenic risk scores that identify individuals at high risk across ancestries, and c) use Mendelian Randomization to assess both causal effects of risk factors on AF, and AF on heart failure and stroke. In Aim 2, we propose to use deep learning models to reconstruct left atrial (LA) size and function in the United Kingdom Biobank cardiac MRI imaging data in 100K individuals. In preliminary studies, we have derived measurements for 7 LA traits, identified more than 20 genetic loci associated with LA traits, and co-localized LA and AF risk genes. In Aim 3, we propose to validate the top 50 AF and LA associated genes by performing gene perturbation assays in stem cell derived atrial cardiomyocytes. We will perform gene knockouts or over expression followed by assays of myocyte structure and electrophysiology using high content imaging. Finally, in Aim 4, we will support the ongoing efforts of the AFGen Consortium and continuing training of early-stage investigators in a virtual fellowship. We believe that our multidisciplinary team brings together extraordinary expertise in AF genetics, epidemiology, bioinformatics, biostatistics, and basic cardiovascular research. Ultimately, we anticipate that our work will provide novel targets for the risk stratification, prevention, and treatment of AF.