Epigenomic regulatory programs reveal the latent heterogeneity of complex diseases

Complex diseases exhibit substantial variation in clinical presentation and outcome despite shared diagnoses. Current genetic models typically represent inherited risk as a single additive liability, obscuring the diverse biological mechanisms through which variants influence disease. Here, we show that disease-associated variants are organized into recurrent regulatory programs that reveal latent disease mechanisms. Using genome-scale epigenomic maps across human tissues and cell states, we identify regulatory programs that partition disease-associated variants without phenotypic or disease-specific priors. Variants assigned to different programs exert distinct biological effects that translate into divergent clinical outcomes. In type 2 diabetes, these programs reveal previously unrecognized disease subtypes with opposing cardiometabolic profiles that stratify future risk of myocardial infarction and non-alcoholic fatty liver disease. Together, our findings establish that inherited disease risk is organized into latent regulatory programs, revealing a fundamental layer of biological heterogeneity underlying complex disease.