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

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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.