Functional Genomics: A Phenome-wide Survey

功能基因组学：全表型组调查

• 批准号: 9815133
• 负责人: Eric R Gamazon
• 金额: $ 46.93万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9815133
• 关键词: Biological; Biological Assay; Catalogs; Collaborations; Computerized Medical Record; DNA; Data; Development; Electronic Health Record; Elements; Genetic; Genetic Variation; Genome; Genomics; Genotype-Tissue Expression Project; Growth; Human; Human Genetics; Human Genome; Lead; Link; Medical; Methodological Studies; Methodology; Molecular; Phenotype; Physiological; Process; Research; Statistical Methods; Surveys; Tissues; Work; biobank; cell type; computerized tools; cost effective; disorder risk; functional genomics; gene function; genetic analysis; genome wide association study; genomic data; genomic epidemiology; high throughput technology; human disease; novel; phenome; trait

Two major developments in the field of Genomics inform the aims of this proposal. Recent large-scale efforts using DNA biobanks linked to electronic health records (EHR) have demonstrated a cost-effective and rapid approach to human genetic discovery with the enormous potential to uncover trait-associated loci hitherto inaccessible because of inadequate power or difficult-to-procure phenotypes. Meanwhile, Functional Genomics is generating large catalogs of functional elements in the genome using a broad spectrum of molecular assays in diverse tissues, cell types, or conditions. This proposal will develop an integrative methodology that advances our understanding of the physiological mechanisms through which genetic variation influences disease risk or quantitative trait. Building on existing research collaborations, this work will develop a set of analytic approaches and computational tools for the analysis of the human medical phenome and present a novel framework for the study of gene function, using large-scale biobanks linked to extensive EHR data (BioVU, UK Biobank, and All of Us) and the enormous breadth of functional genomics data (from GTEx and other consortia) that are being produced. We will develop a new Phenome-Wide Association Study (PheWAS) methodology, an approach to discovery and replication with enhanced capabilities for proposing relevant mechanisms.

基因组学领域的两个主要发展为本提案的目的提供了信息。