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

跨组学分析揭示心脏、肺和血液疾病危险因素的分子基础

• 批准号: 9524641
• 负责人: Bing Yu
• 金额: $ 49.47万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-05-01 至 2020-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9524641
• 关键词: African American; American; Atherosclerosis Risk in Communities; Bioinformatics; Biometry; Blood; Blood Pressure; Cloud Computing; Computational Biology; Data; Disease; Enhancers; Equilibrium; Ethnic Origin; Ethnic group; Etiology; European; Exons; Framingham Heart Study; Frequencies; Functional disorder; Gene Frequency; Genes; Genetic; Genetic Determinism; Genomics; Goals; Heart; Heart Diseases; Hematological Disease; Hemostatic function; Hispanic Americans; Hispanic Community Health Study/Study of Latinos; Individual; Intervention; Jackson Heart Study; Link; Lung; Lung diseases; Measures; Mediating; Mediation; Meta-Analysis; Metabolic; Metabolic Pathway; Minor; Minority; Modeling; Molecular; Molecular Target; Morbidity - disease rate; Multi-Ethnic Study of Atherosclerosis; Multivariate Analysis; National Heart, Lung, and Blood Institute; Network-based; Pathway interactions; Pattern; Population; Positioning Attribute; Prevention; Quantitative Trait Loci; Regulation; Research; Resources; Risk Factors; Role; Structure; Technology; Testing; Trans-Omics for Precision Medicine; Variant; burden of illness; cardiogenesis; cohort; disorder risk; ethnic difference; gene environment interaction; gene product; genetic variant; genome sequencing; genome-wide; insight; metabolome; metabolomics; mortality; multiple omics; novel; prevent; promoter; pulmonary function; response; secondary analysis; sex; statistics; trait; whole genome

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.

抽象的 心脏，肺和血液（HLB）特征，包括血压，肺功能和止血的度量， 可以预测发病率和死亡率。了解这些HLB特征的调节对于降低至关重要 疾病负担。尽管在过去十年中成功鉴定了与HLB特征相关的遗传变异的鉴定，但 遗传变异如何调节这些特征的基本机制尚不清楚。循环代谢物， 基因和环境相互作用的最终产物有望连接遗传变异，代谢 更改HLB特征。已经确定了影响循环代谢产物的多种遗传变异， 但是，这些与代谢相关的基因座对HLB性状的作用研究了。种族差异 HLB特征的分布以及疾病的风险是众所周知的，但是当前的多摩变发现在很大程度上是驱动的 由欧洲血统。很少有研究检查了多种种族中对HLB特征的代谢影响 组。该应用程序的总体目的是确定与HLB特征相关的代谢特征和 在多种族种群中影响循环代谢物的遗传基因座，并利用这些发现来识别 调节HLB性状的分子途径。我们建议在五个顶级队列中进行这个项目， 包括社区中的动脉粥样硬化风险（ARIC）研究，Framingham心脏研究（FHS）， 西班牙裔社区健康研究/拉丁美洲人（HCHS/SOL），杰克逊心脏研究（JHS）和多人 动脉粥样硬化的种族研究（MESA），与欧美人，非裔美国人和西班牙裔平衡 美国人。我们将利用有关现有整个基因组测序（WGS）的每项研究的独特资源 数据，代谢组轮廓，多个HLB特征，并利用了顶部的云计算试验分析 计算引擎的下议院。我们的目标是：（1）识别与HLB相关的代谢特征 特征，包括血压，肺功能和止血的措施； （2）识别遗传 循环代谢物的决定因素； （3）整合目标1和2的OMICS发现以突出因果关系 与HLB性状的调节相关的途径。鉴于我们的专业知识 代谢组分析，基因组学，HLB特征，生物统计学和生物信息学。这项研究的结果将 使持续的科学进步能够理解HLB疾病病理生理学，直接 对预防和潜在疗法的影响。