Integrative Multi-Omics Analysis Elucidates the Progressive Disease Landscape and Reveals Dynamic Protein Biomarkers for MASLD Surveillance.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent chronic liver disease worldwide, encompassing a continuum ranging from simple steatosis to steatohepatitis, hepatic fibrosis, and cirrhosis. Despite the complex and heterogeneous pathogenesis, effective therapeutic targets remain elusive. In this study, we sought to identify and validate critical genes implicated in MASLD progression through multi-omics integration and machine learning algorithms. Analysis revealed considerable activation of lipid metabolism, oxidative stress, and inflammation-related pathways throughout disease progression, with notable upregulation of AKR1B10, COL1A2, and SPP1 and downregulation of CYP2C19. These expression patterns were consistently verified across in vivo and in vitro models. Functional assays indicated that AKR1B10 knockdown or CYP2C19 overexpression substantially attenuated hepatocellular lipid accumulation, alleviated oxidative stress and inflammatory responses, and suppressed key lipogenic gene expression. Collectively, these findings elucidate key molecular axes in MASLD progression and provide mechanistic insights and theoretical foundations for the development of targeted therapies.