Trans-omics Analysis to Unravel Molecular Underpinnings of Heart, Lung and Blood Disease Risk Factors

摘要

ABSTRACT Heart, lung, and blood (HLB) traits, including blood pressure, pulmonary function and measures of hemostasis, can predict morbidity and mortality. Understanding the regulation of these HLB traits is essential to decrease disease burden. Despite successful identification of genetic variants associated HLB traits over the last decade, the underlying mechanism of how genetic variants regulate these traits remains unclear. Circulating metabolites, the ultimate products of gene and environment interaction, holds promise to link genetic variants, metabolic changes to HLB traits. Multiple genetic variants that influence circulating metabolites have been identified, however, the role of these metabolic-related loci on HLB traits is understudied. Ethnic differences in the distribution of HLB traits, as well as disease risk are well-known, but current multi-omic findings are largely driven by European ancestry. Few studies have examined the metabolic influence on HLB traits in multiple ethnic groups. The overall objective of this application is to identify metabolic signatures related to HLB traits and genetic loci influencing circulating metabolites in multi-ethnic populations, and utilize these findings to identify molecular pathways that regulate HLB traits. We propose to conduct this project in five TOPMed cohorts, including the Atherosclerosis Risk in Communities (ARIC) study, the Framingham Heart Study (FHS), the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), the Jackson Heart Study (JHS), and the Multi- Ethnic Study of Atherosclerosis (MESA), with a balance of European Americans, African Americans and Hispanic Americans. We will leverage the unique resources from each study on existing whole genome sequencing (WGS) data, metabolome profiles, multiple HLB traits, and utilize the TOPMed Cloud Computing Pilot Analysis Commons for the computational engine. Our aims are: (1) to identify metabolic signatures associated with HLB traits, including blood pressure, pulmonary function and measures of hemostasis; (2) to identify genetic determinants of circulating metabolites; and (3) integrating Aims 1 and 2 omics findings to highlight causal pathways associated with the regulation of HLB traits. Our team is uniquely positioned, given our expertise in metabolome profiling, genomics, HLB traits, biostatistics and bioinformatics. The results of this research will enable continued scientific progress toward an understanding of HLB disease pathophysiology, with direct implications for prevention and potential therapies.