Using Genetics to Inform Mechanism of Cardiovascular Disease

利用遗传学了解心血管疾病的机制

• 批准号: 10094225
• 负责人: Cristen J Willer
• 金额: $ 90.71万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-02-01 至 2024-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10094225
• 关键词: Aortic Aneurysm; Atrial Fibrillation; Bioinformatics; Biological; Cardiovascular Diseases; Cardiovascular system; Cause of Death; Clinical; Computing Methodologies; Coronary Arteriosclerosis; Data; Development; Diagnosis; Disease; Dissection; Genes; Genetic; Genetic study; Genomics; Goals; Lipids; Myocardial Infarction; Pharmacotherapy; Phenotype; Preventive; Sampling; Signal Transduction; Statistical Methods; Technology; Testing; Therapeutic; United States; Variant; Work; cardiovascular disorder prevention; case control; epigenomics; genetic variant; genome wide association study; improved; innovation; insertion/deletion mutation; insight; loss of function; novel; novel therapeutics; targeted sequencing; trait; whole genome

PROJECT SUMMARY/ABSTRACT The goal of this R35 proposal is to uncover novel genetic discoveries and biological mechanisms underlying association with devastating cardiovascular diseases. This proposal builds on strengths in high-throughput genetics and genomics and development and application of innovative computational and statistical methods and genomics technology to maximize the benefits of genetic studies of cardiovascular disease. We will continue our discovery efforts to uncover genetic variants associated with a variety of cardiovascular diseases including atrial fibrillation, aortic aneurysm and dissection, and myocardial infarction and coronary artery disease. Building on our previous work where we identified a number of new genes for coronary artery disease and lipids, we also propose to uncover the mechanisms underlying association at known loci using genetics and epigenomics. We propose to assess the phenotypic impact of the ~19 million variants and 20k indels and SVs identified from whole genome sequenced samples by imputing them into 70,000 new GWAS samples with many cardiovascular phenotypes. We will perform integrated analyses with epigenomics data to highlight clusters of loci with related function. We also propose to perform targeted sequencing of 300 genes in 30,000 CAD cases and controls to search for loss of function variants at CAD loci that implicate CAD genes. We will continue to search for mechanistic insight by performing a PheWAS for all CAD-associated variants identified, disentangling multiple independent signals and correlated traits and clinical endpoints using conditional testing. Completion of these studies will provide new insights into disease mechanisms that have the potential to catalyze breakthroughs in cardiovascular disease prevention, treatment, and diagnosis.

项目总结/文摘