Abstract
Cardiovascular disease (CVD) remains a leading cause of mortality and morbidity worldwide, influenced by complex interactions between biological, environmental, and social factors. Studies employing traditional genetic approaches are often insufficient to capture the broader context of these heterogeneous factors. We highlight an integrative framework that combines electronic health records (EHRs) with public (census) data on socio-environmental exposures, leveraging the Observational Medical Outcomes Partnership (OMOP) Common Data Model and individual's geolocations linked through ZIP Code Tabulation Area (ZCTA) codes. By incorporating the exposome, including social determinants of health (SDoH), this framework enhances privacy-preserving analysis and improves personalized CVD risk stratification. Furthermore, Precision Medicine aims to identify tailored prevention and therapeutic strategies by considering an individual's unique genetic, environmental, and lifestyle factors in which the exposome plays a pivotal role. Accordingly, in this review we will discuss a holistic precision medicine approach centered around the exposome to address health disparities, to better identify communities at high-risk for CVD, and to advance tailored prevention and intervention strategies.