Cardiovascular diseases (CVDs) are the leading cause of morbidity and mortality worldwide, with increasing evidence suggesting that both genetic and environmental factors contribute to their development. Early-life exposures may have long-lasting effects on cardiovascular health, yet the underlying mechanisms remain poorly understood. This project will leverage UK Biobank’s extensive multi-omics (genomic, epigenomic, proteomic, metabolomic) and imaging data, alongside detailed environmental and lifestyle exposure measures (including air pollution, residential environment, diet, physical activity, sleep, and socioeconomic factors), to investigate the complex interplay between these exposures and genetic susceptibility in the multifactorial etiology of CVDs and related comorbidities. Focusing on key CVD outcomes-such as hypertension, left ventricular hypertrophy, myocardial infarction, and coronary artery disease-and on multi-system comorbid conditions (cardiometabolic, cardiorenal, cardio-cerebral, and cardio-hepatic), we will apply advanced analytical approaches including Mendelian randomization, genome-wide association studies (GWAS), integrative imaging-omics, and machine learning algorithms. This multifaceted approach will facilitate the identification of underlying biological mechanisms and mediating pathways linking exposures to disease outcomes. A unique strength of the project is the integration of UK Biobank data with the Shanghai Birth Cohort study, providing a rare life-course perspective from childhood to adulthood. Incorporating early-life environmental exposures and genetic predisposition data will enable us to elucidate how early-life factors shape cardiovascular risk trajectories over the lifespan. This integrated multi-omics and life-course design aims to yield novel insights into the interplay between environment and genetics in CVD etiology and ultimately inform strategies for risk prediction and prevention.
