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

摘要 心、肺和血(HLB)特征，包括血压、肺功能和止血措施， 可以预测发病率和死亡率。了解这些HLB特性的调节对于减少 疾病负担。尽管在过去的十年中成功地鉴定了与HLB性状相关的遗传变异， 基因变异如何调控这些特征的潜在机制尚不清楚。循环代谢物， 基因和环境相互作用的最终产物，有望将基因变异、新陈代谢 HLB特征的变化。已经确定了多种影响循环代谢物的遗传变异， 然而，这些代谢相关的基因座在HLB性状上的作用还没有得到充分的研究。中国的种族差异 HLB性状的分布和疾病风险是众所周知的，但目前的多组学发现在很大程度上是由 有欧洲血统。很少有研究考察代谢对多种族HLB型性状的影响 组。本应用程序的总体目标是识别与HLB特性和 影响多民族人群循环代谢物的遗传位点，并利用这些发现来识别 调节HLB特性的分子途径。我们建议在五个TOPMed队列中进行这个项目， 包括社区动脉粥样硬化风险(ARIC)研究、弗雷明翰心脏研究(FHS)、 西班牙裔社区健康研究/拉丁裔社区健康研究(HCHS/SOL)，杰克逊心脏研究(JHS)，以及 动脉粥样硬化的种族研究(MESA)，平衡了欧洲裔美国人、非裔美国人和西班牙裔美国人 美国人。我们将利用来自现有全基因组测序(WGS)的每项研究的独特资源 数据、代谢组谱、多个HLB特征，并利用TOPMed云计算试点分析 计算引擎的公共点。我们的目标是：(1)确定与HLB相关的代谢特征 特征，包括血压、肺功能和止血措施；(2)确定基因 循环代谢物的决定因素；以及(3)整合AIMS 1和2的组学结果以突出因果关系 与HLB特性调节相关的途径。我们的团队处于独特的地位，考虑到我们在 代谢组谱、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 推动持续的科学进步，以了解HLB病的病理生理学，直接 对预防和潜在治疗的影响。

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.