Genomics of Cardiac Electrical Activity and Arrhythmia

描述（由申请人提供）：表面心电图上的心电活动反映心肌去极化和传导（PR和QRS间期）和复极化（QT间期）。心脏传导和复极异常可导致心律失常和不良后果（心房颤动和心源性猝死），并可能需要放置心脏起搏器和/或除颤器。确定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，并可能有助于开发新的治疗方法。心电活动和心律失常的等位基因结构目前尚不清楚，但可能涉及影响一般的常见变异和影响较强的罕见变异的聚集。虽然调节区域的变化可能在心律失常中起作用，但这是明确的

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.