Cross-trait genomic modeling reveals the polygenic architecture and systemic impact of MASLD

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a globally prevalent disease, yet its genetic architecture remains incompletely characterized. We integrated genome-wide association study data from multiple cohorts totaling nearly 3 million individuals of European ancestry and applied cross-trait genomic modeling of hepatic fat and seven cardiometabolic traits to construct an MASLD-specific polygenic architecture. We identified 128 risk variants across 100 loci and prioritized 55 effector genes, including established (e.g., <i>PNPLA3</i> and <i>TM6SF2</i>) and previously unreported candidates (e.g., <i>NRXN3</i> and <i>FRMD5</i>). A phenome-wide scan of the MASLD polygenic risk score revealed broad associations spanning hepatic, cardiometabolic, renal, endocrine, and neuropsychiatric systems. Using a two-step, proteome-wide Mendelian randomization across >4900 plasma proteins, we identified potential mediators linking MASLD to disease. Validation in population-based cohort pinpointed seven proteins (e.g., FURIN, aldehyde dehydrogenase 2, and apolipoprotein M) mediating up to 50.6% of the cardiometabolic risk attributable to MASLD. Our findings delineate the polygenic architecture of MASLD, highlight its multisystem consequences, and nominate translational biomarkers for precision prevention.