A multi-ancestry study of gene-lifestyle interactions and multi-omics in cardiometabolic traits - project summar/abstract cardiometabolic diseases and risk factors, including hypertension,…

A multi-ancestry study of gene-lifestyle interactions and multi-omics in cardiometabolic traits - project summar/abstract cardiometabolic diseases and risk factors, including hypertension, dyslipidemia, adiposity, and type 2 diabetes, represent a major public health burden that disproportionately affects diverse (non-european ancestry) populations. Cardiometabolic traits are influenced by both genetic and environmental (lifestyle) factors. Therefore, understanding interactions (GXE) between these factors could provide insights into intervention, prevention and therapeutic strategies to reduce the burden of disease. Many genome-wide association studies (gwas) have made important genetic discoveries for many complex traits through approaches based on "genetic main effects". However, genome-wide interaction studies (gwis) are still limited. The objective of this study is therefore to identify novel genetic loci associated with cardiometabolic traits through gwis in large samples, to investigate gene-lifestyle interactions in the cardiometabolic trait loci, and to characterize the molecular effects underlying the interactions by leveraging existing "omics" data such as DNA methylation, gene expression, and metabolites. By investigating genomic and lifestyle contributors to health outcomes through their interactions across diverse populations and between sexes, our proposal reflects the priorities of the precision medicine initiative (PMI) whose focus is the interplay between lifestyle/environment and genetics, with an emphasis on diverse populations. We propose to evaluate gene-lifestyle interactions across diverse populations (european, african, hispanic, and asian). Our recent progress with blood pressure, lipids, and dichotomized lifestyle factors (smoking, alcohol consumption, physical activity, educational attainment, psychosocial factors, and sleep) encountered limited statistical power. Therefore, we propose to vastly increase the power for gwis with an ~10-fold larger sample size and expand our focus to include other cardiometabolic traits (adiposity and diabetes traits), quantitative lifestyle exposures (e.g., cigarettes per day), and aggregate lifestyle risk scores as an overall lifestyle risk factor for cardiometabolic health; evaluate the impact of identified interactions on clinical endpoints (like coronary heart disease); assess the druggability of identified interactions; and characterize interactions using multiple omics data. Our proposal includes our recent discovery studies (n~130,000), our recent replication studies (n~252,000), and the addition of several new, substantially larger studies including the million veteran program (n~234,000), the UK biobank (n~478,000), the biobank japan (n~160,000), and the study of latinos (n~13,000), among others. The overall sample, including 912,000 european, 91,000 african, 33,000 hispanic, and 231,000 asian ancestry individuals, represents the most significant effort to date to investigate interactions with an aggregate sample size of about 1.267 million. Findings can lead to new diagnostic and therapeutic tools, contribute to precision care in the management of cardiometabolic disorders, and provide insights for the PMI with the ultimate goal of enhancing clinical practice.