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Using Electrocardiogram Genetics to Inform Arrhythmia Risk

利用心电图遗传学来了解心律失常风险

基本信息

批准号：
10550134
负责人：
Patrick Thomas Ellinor
金额：
$ 72.02万
依托单位：
MASSACHUSETTS GENERAL HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-01-20 至 2025-12-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10550134
关键词：
Address Adverse event Affect Arrhythmia Cardiac Cardiac Myocytes Cardiovascular Diseases Cellular Assay Classification ClinVar Clinical Clinical Data Code Collection Data Diagnostic Disease EKG P Wave Electrocardiogram Electronic Health Record Electrophysiology (science)Fibroblasts Genes Genetic Genetic Variation Genomics Goals Healthcare Heart Diseases Heritability Human Genetics Individual Link Long QT Syndrome Measurement Measures Medical Genetics Methods Mission Morbidity - disease rate National Heart, Lung, and Blood Institute Outcome Pathogenicity Persons Physiological Processes Prevention Prognosis Proliferating Proxy Public Health Reproducibility Resources Risk Sampling Science Testing Trans-Omics for Precision Medicine Translations Validation Variant adjudication biobank causal variant clinical phenotype clinical practice clinically relevant cohort data submission endophenotype exome exome sequencing genetic testing genetic variant genome sequencing high throughput screening improved innovation large scale data mortality risk novel population based programs rare variant repository response risk stratification screening stem cells sudden cardiac death trait transmission process variant of unknown significance whole genome

项目摘要

Project summary Nearly one in three people will have an arrythmia during their lifetime and up to 10% may die of sudden cardiac death. Arrhythmias and sudden cardiac death are heritable and often caused by problems of cardiac conduction or repolarization. Nevertheless, the genetic causes are not well-defined. Moreover, interpretation of genetic variation is limited by the frequent discovery of variants of uncertain clinical significance. Our preliminary data suggest that using high-depth genomic sequencing data from large-scale biobanks with routinely measured electrocardiogram intervals – indicators of arrhythmia and sudden cardiac death risk – has the potential to address these challenges. Our overall goal is to minimize morbidity from cardiovascular disease. The specific objective of this proposal is to utilize high-depth whole genome and exome sequencing data to identify, functionally evaluate, and clinically characterize genetic variation that predisposes to arrhythmia risk and sudden cardiac death. To do so, we will leverage a unique and massive repository of individuals with genomic sequencing, electrocardiograms, and clinical data. The electrocardiogram is a widely utilized and inexpensive screening test. Standard electrocardiogram intervals are reliable and reproducible measurements that are associated with a variety of cardiac conditions, most notably arrhythmias and sudden cardiac death. Our overall hypothesis is that functional and clinically relevant rare genetic variation underlies population-based electrocardiographic interval variability. In Aim 1, we will identify rare coding variation associated with electrocardiographic intervals. We will use data from a unique resource of over 220,000 individuals with electrocardiograms and whole genome or exome sequence data in the National Heart Lung and Blood Institute’s Trans-Omics for Precision Medicine Program, UK Biobank, Geisinger MyCode/DiscovEHR cohort, and Mass General Brigham HealthCare Biobank. In Aim 2, we will validate and characterize the electrophysiological and structural impact of identified genes in stem cell derived cardiomyocytes. In Aim 3 we will assess whether variants with large electrocardiographic trait effect sizes are associated with arrhythmia risk using electronic health record data in nearly 400,000 sequenced individuals, and variant pathogenicity using ClinVar, a repository of clinical variant adjudications. Studying how rare genetic variants affect the electrocardiogram is an innovative approach for understanding arrhythmia and sudden cardiac death risk. We anticipate that this paradigm will be broadly applicable to other quantitative endophenotypes and heart diseases. We submit that our aims are consistent with the NHLBI’s mission of understanding the causes of disease and enabling translation of basic discoveries into clinical practice.

项目总结