Subtyping metabolic dysfunction-associated steatotic liver disease using electronic health record-linked genomic cohorts reveals diverse etiologies and progression

Abstract

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a heterogeneous condition with diverse etiologies and clinical presentations. Yet, a consensus of subtypes is lacking in MASLD. Based on latent class analysis of significant MASLD-related clinical variables, we identify five subgroups with distinct genetic, clinical, and risk profiles, which are well recapitulated in an independent cohort. Polygenic risk score and genetic variant analysis reveal genetic contributions across all subgroups. In particular, two subgroups, male-predominant cardiorenal (C2) and female-predominant with obesity and mood disorders (C3), are associated with high prevalence of type 2 diabetes, obesity, and sleep apnea. The latter also has relatively high usage of antidepressant medicine. On the other hand, the polygenic MASLD (C4) is characterized by the lowest incidence of metabolic comorbidities and ischemic heart disease. Nevertheless, this subgroup overall has the highest rate of liver transplant, which is likely driven, in part, by the combinatorial genetic effects of high-prevalent risk alleles in TM6SF2 and MBOAT7 together with low-prevalent protective allele in HSD17B13. Finally, the polygenic MASH subtype C5 shows increased risk of developing advanced fibrosis and acute renal failure. Together, our study provides key insights into MASLD heterogeneity, highlighting the opportunity for personalized therapies. From multi-year Mayo Clinic records on liver disease, researchers identified five distinct patient patterns. The method for generating liver disease subtypes is robust, producing transferable subtypes across diverse patient cohorts.