Genetics of MASLD: a diabetes perspective

Metabolic dysfunction-associated steatotic liver disease (MASLD) is highly prevalent in people with type 2 diabetes and represents a major contributor to liver-related and extrahepatic morbidity and mortality. Despite this strong epidemiological overlap, the clinical course of MASLD in diabetes is highly heterogeneous and not fully explained by conventional metabolic risk factors. Human genetic studies have provided important insights into this variability by revealing that hepatic steatosis and its downstream consequences can arise through biologically distinct pathways. Genome-wide association studies have identified multiple genetic loci influencing liver fat accumulation, disease severity and progression. These loci implicate diverse mechanisms, including liver-intrinsic defects in lipid handling, enhanced hepatic lipogenesis, and systemic metabolic dysfunction related to insulin resistance and adipose tissue biology. Genetic evidence indicates that similar degrees of hepatic steatosis may therefore reflect different underlying biological processes, with differing implications for glycaemic management, cardiovascular risk and liver disease progression. In this review, we examine the genetic architecture of hepatic steatosis and MASLD in the context of diabetes. We discuss evidence from family studies, genome-wide association analyses, imaging genetics and Mendelian randomisation, with an emphasis on cautious causal interpretation. We also explore gene-diabetes and gene-environment interactions that modify disease expression and may contribute to variability in clinical outcomes and treatment response. Finally, we consider the translational implications of MASLD genetics, including risk stratification, therapeutic target discovery and emerging genotype-informed approaches to clinical management. We highlight key research gaps, particularly the need for ancestry-diverse studies, improved phenotyping in diabetes populations, and integration of genetic analyses into prospective clinical trials. Together, current genetic evidence supports a mechanism-based framework for understanding MASLD heterogeneity in diabetes and provides a foundation for more precise approaches to risk assessment and management.