Genomics of Cardiac Electrical Activity and Arrhythmia

描述(申请人提供)：体表心电活动反映心肌去极化和传导(PR和QRS间期)和复极(QT间期)。心脏传导和复极异常可能导致心律失常和不良后果(房颤和心脏性猝死)，并可能需要放置心脏起搏器和/或除颤器。识别心脏电活动的分子决定因素将有助于深入了解心律失常的发生，并有可能帮助开发新的治疗方法。心脏电活动和心律失常的等位基因结构目前尚不清楚，但可能既包括影响不大的常见变异，也可能涉及影响更强的罕见变异的聚集。虽然调控区域的变化可能在心律失常中起作用，但这一点很明显 外显子区域的变异会改变蛋白质的分子结构，会导致蛋白质功能的改变，并影响下游的表型。事实上，编码区突变可导致孟德尔形式的心脏电异常，进而导致临床心律失常(如长和短QT综合征，进行性心脏传导疾病)。因此，我们假设生物功能编码区的遗传变异将与普通人群的心脏电活动和心律失常有关。首先，我们建议从基于人群的研究中系统地研究约45,000名个体的心脏电活动与编码区基因变异的关系。其次，我们将通过检查已识别的变异与临床相关性来评估它们的临床相关性 房颤和心源性猝死。最后，我们将评估其生物学机制。 确定基因，并从功能上剖析使用小鼠和斑马鱼模型确定的变体的作用。我们的最终目标是确定与临床相关和具有生物功能的基因和遗传变异，从而潜在地成为新疗法的目标。这一应用代表了多中心的合作努力，以有效地结合临床和分子心脏病学、基因组学和统计遗传学、心血管和遗传流行病学、系统生物学和生物信息学以及动物模型功能研究方面的专业知识。我们利用8项基于人群的心血管疾病研究的现有表型数据和这些研究中提供的Exome芯片的外显子全基因分型数据，以高效和经济高效的方式检查功能编码区变异与心脏电活动和心律失常风险的变化之间的关联。重要的是，我们随后将这些遗传关联转化为功能研究，以了解所识别的基因和变异在心脏电生理学和心律失常中所起的作用。

DESCRIPTION (provided by applicant): Cardiac electrical activity on the surface electrocardiogram reflects myocardial depolarization and conduction (PR and QRS intervals), and repolarization (QT interval). Abnormalities in cardiac conduction and repolarization can lead to cardiac arrhythmias and adverse outcomes (atrial fibrillation and sudden cardiac death) and can necessitate the placement of cardiac pacemakers and / or defibrillators. Identifying the molecular determinants of cardiac electrical activity will provide insight into arrhythmia generation and potentially help target the development of novel therapies. The allelic architecture of cardiac electrical activity and arrhythmias is currently unknown, but is likely to involve both common variants with modest effects and an aggregation of rare variants with stronger effects. While variation in regulatory regions may have a role in arrhythmias, it is clear that variants in exonic regions that change the molecular structure of a protein can lead to alteration in protein function and influence downstream phenotypes. Indeed, coding region mutations can lead to Mendelian forms of cardiac electrical abnormalities that then lead to clinical arrhythmias (e.g. long and short QT syndromes, progressive cardiac conduction disease). We therefore hypothesize that biologically functional coding region genetic variation will be associated with cardiac electrical activity and arrhythmia in the general population. First we propose to systematically investigate the association of cardiac electrical activity with geneti variation in coding regions in ~45,000 individuals from population-based studies. Second, we will evaluate the clinical relevance of the identified variants by examining their association with atrial fibrillation and sudden cardiac death. Finally, we will assess the biologic mechanism of the identified genes and functionally dissect the role of the variants identified using mouse and zebrafish models. Our ultimate goal is to identify genes and genetic variation that are clinically relevant and biologically functional, and therefore potentially the target of new therapies. This application represents a multi-center collaborative effort to efficiently combine expertise in clinical and molecular cardiology, genomics and statistical genetics, cardiovascular and genetic epidemiology, systems biology and bioinformatics, and animal model functional studies. We leverage existing phenotype data from eight population-based studies of cardiovascular diseases with exome-wide genotyping data from the Exome chip available in these studies, in order to efficiently and cost-effectively examine association of functional coding region variants with variation in cardiac electrical activity and risk of arrhythmias. Importantly, we then translae these genetic associations into functional studies, to understand the role in cardiac electrophysiology and arrhythmias played by the genes and variants identified.