Genetic Architecture of Cardiac Structure and Function and Its Impact on Heart Failure

心力衰竭(HF)随着年龄的增长而显著增加，并与50%的5年死亡率有关。不正常的 心脏结构和心功能损害先于HF和潜在的HF亚型的发展。 心脏结构和功能是可遗传的--全基因组关联研究确定了57个共同的 然而，与心脏结构和功能相关的变异基因对新的心脏功能的贡献 目前还没有探索相关措施。此外，几乎没有全面描述基因特征的数据存在 心脏结构和功能的相关性(即罕见和结构性变异)，特别是在少数群体中。完毕 在过去的十年中，我们研究了遗传对高频和横断面回声测量的影响 基因组流行病学(CHARD)联盟心脏和衰老研究的队列设置。我们现在 建议将我们的努力扩展到Trans-Omics for Precision Medicine(TOPMed)计划，将我们的RICH 具有前沿全基因组测序数据的七个群体的纵向表型数据 一群人。我们的中心假设是，特定的常见的、罕见的和结构性的遗传变异将与 心脏结构和功能以及心力衰竭；以及心脏结构的遗传易感性 功能改变将改善心力衰竭的风险预测。在目标1中，我们将描述 心脏结构和功能及其纵向变化，并评价其对心衰的影响。通知 了解高频生理，我们将评估蛋白质和代谢物对ECHO和HF的因果影响。 使用孟德尔随机化方法。在目标2中，我们将构建心脏结构的多基因风险评分。 和功能，并评估它们对心力衰竭风险预测的影响。我们将应用一种新的方法来构建PRS， 并将使用机器学习算法来评估其对心力衰竭风险的预测。随着 在这个项目中，我们的目标是深入了解进行性心脏功能障碍的生物学途径。 和HF，并为药物开发提供靶点。

Heart failure (HF) increases with age markedly and is associated with a 50% 5-year mortality. Abnormalities of cardiac structure and impairment of cardiac function precede the development of HF and underlie HF subtypes. Cardiac structure and function are heritable - genome-wide association studies have identified 57 common variants associated with cardiac structure and function, however, genetic contribution to newer cardiac function measures have not been explored. In addition, few data exist comprehensively characterizing genetic associations (i.e., rare and structural variants) of cardiac structure and function, especially in minorities. Over the past decade, we have investigated the genetic effect on HF and cross-sectional echo measures within the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. We now propose to extend our effort to the Trans-Omics for Precision Medicine (TOPMed) Program by combing our rich longitudinal phenotypic data with cutting-edge whole genome sequencing data in seven population-bases cohorts. Our central hypothesis is that specific common, rare and structural genetic variants will be associated with cardiac structure and function, as well as HF; and incorporating genetic predisposition to cardiac structure and function alterations will improve HF risk prediction. In Aim 1, we will characterize genetic architecture of cardiac structure and function and their longitudinal changes, and evaluate their effects on HF. To inform understanding of HF physiology, we will assess the causal effects of proteins and metabolites on echo and HF using Mendelian randomization approaches. In Aim 2, we will construct polygenic risk scores for cardiac structure and function and assess their impact on HF risk prediction. We will apply a new approach for PRS construction, and will use a machine learning algorithms to evaluate its prediction on the risk of HF. With the completion of this project, we aim to generate insights into the biological pathways underlying progressive cardiac dysfunction and HF, and to provide targets for drug development.