Epigenomic and Metabolomics Determinants of Subclinical and Clinical Vascular and Myocardial Disease

项目摘要/摘要：项目3 将传统的不精确的心血管疾病(CVD)风险评估转变为更精确 风险预测和早期检测，项目3将进行一项无针对性的多组体研究 动脉粥样硬化性心血管疾病(ASCVD)亚临床和临床CVD表型的分子因素 心力衰竭(HF)途径包括保留的HF(HFpEF)和减少的射血分数(HFrEF)。 遗传和环境风险因素都有助于心血管疾病的发展。已识别的遗传变异 仅占人群中ASCVD和HF风险的一小部分。环境的影响 然而，对心血管疾病的贡献在很大程度上仍未在分子水平上得到探索。生物分子，如 表观遗传学和代谢组学标记，可以捕获互补的分子效应器 环境暴露，并在多个层面上改变生物功能。因此，研究多重 分子层(如表观基因组和代谢组)可能有助于发现新的途径和机制 通过环境暴露影响心血管疾病的发展并为预防提供新的目标 和心血管疾病的管理。这对南亚人等人来说尤其重要，他们患有 年轻时心血管疾病负担高，并有独特的心脏代谢风险特征(例如，非常高的患病率 糖尿病和血脂异常，尽管肥胖率相对较低)，但在目前 表观基因组学、代谢组学和基因组学的群体研究。检视多染色体标记的变化 关于相同个体内心血管疾病表型的自然病史，提供了一种受控和 对这些关系的公正评价。确定表观基因组和代谢相关的因子 亚临床(目标1，动脉粥样硬化和左心室收缩/舒张期功能障碍)和临床心血管疾病(目标2， 冠状动脉疾病，HFpEF，缺血性和非缺血性HFrEF)，我们将进行表观全基因组和 从Precision中信息选择的3000名参与者的代谢全组关联分析 CARRS队列中的心血管表型和病理生理途径(Precision-CARRS)， 在基线和第一次后续访问时进行测量，并在外部队列中复制研究结果。要确定 基因组、表观基因组和代谢组谱对亚临床和临床CVD和BUDY的联合影响 预测模型(目标3)，我们将应用先进的多体方法、机器学习算法和 因果推论方法。最后，我们将评估表观基因组和代谢组谱是否相关。 与亚临床和临床心血管疾病有关的环境空气污染(来自项目2)并进行调解(目标4)。 通过综合多项措施和综合分析，项目3将提高风险 南亚人心血管疾病的评估、分子理解和精确医学。

PROJECT SUMMARY / ABSTRACT: Project 3 To transform conventional imprecise cardiovascular disease (CVD) risk assessments towards more precise risk prediction and early-stage detection, Project 3 will conduct an untargeted multi-omic study to investigate molecular factors associated with subclinical and clinical CVD phenotypes along atherosclerotic CVD (ASCVD) and heart failure (HF) pathways including HF with preserved (HFpEF) and reduced ejection fraction (HFrEF). Both genetic and environmental risk factors contribute to the development of CVD. Identified genetic variations only account for a small proportion of ASCVD and HF risk in the population. Effect of environmental contributions to CVD, however, remain largely unexplored at the molecular level. Biomolecules, such as epigenetic and metabolomic markers, can capture complementary molecular effectors in response to environmental exposures, and alter biological functions at multiple levels. Therefore, studying multiple molecular layers (e.g., epigenome and metabolome) may help discover novel pathways and mechanisms through which environmental exposures influence CVD development and provide new targets for prevention and management of CVD. This is particularly important for populations, such as South Asians, who suffer a high burden of CVD at young ages and have unique cardiometabolic risk profile (e.g., very high prevalence of diabetes and dyslipidemia despite relatively low prevalence of obesity), but are underrepresented in current population studies of epigenomics, metabolomics and genomics. Examining the changes in multi-omic markers in relation to the natural history of CVD phenotypes within the same individuals provides a controlled and unbiased evaluation of these relationships. To identify epigenomic and metabolomic factors associated with subclinical (Aim 1, atherosclerosis and left ventricular systolic/diastolic dysfunction) and clinical CVD (Aim 2, coronary artery disease, HFpEF, ischemic and non-ischemic HFrEF), we will conduct epigenome-wide and metabolome-wide association analyses of 3,000 participants informatively selected from the Precision Cardiovascular Phenotyping and Pathophysiological Pathways in the CARRS cohort (Precision-CARRS), measured at baseline and the first follow-up visit, and replicate the findings in external cohorts. To determine the joint impact of genomic, epigenomic and metabolomic profiles on subclinical and clinical CVD and build prediction models (Aim 3), we will apply advanced multi-omic approaches, machine learning algorithms and causal inference methods. Lastly, we will assess whether epigenomic and metabolomic profiles are associated with, and mediate ambient air pollution (from Project 2) in relation to subclinical and clinical CVD (Aim 4). Through comprehensive multi-omic measurements and integrative analyses, Project 3 will improve the risk assessment, molecular understanding and precision medicine of CVD in South Asians.