Metabolic dysfunction-associated steatotic liver disease (MASLD) encompasses both lean and obese phenotypes with variable progression to metabolic dysfunction-associated steatohepatitis (MASH), yet the metabolic determinants of this divergence under identical dietary exposure remain unclear. Here, genetically identical male C57BL/6J mice were fed a high-fat diet (HFD) enriched in fructose, palmitate, and cholesterol for 27 weeks, resulting in two distinct phenotypes: responders and mild responders. Responders exhibited increased liver and visceral adipose indices, hypertriglyceridemia, and right-lobe-predominant steatohepatitis with pronounced collagen deposition, accompanied by upregulation of pro-fibrotic (COL1A1, ACTA2) and proinflammatory (TNF-α, TGF-β) genes, whereas mild responders showed attenuated fibrosis and preserved IL-10 expression despite elevated hepatic triglycerides. Metabolomic profiling of serum and cecal samples identified "candidate circulatory" metabolites, and principal component analysis of these features revealed clear separation of all three cohorts, supporting metabolically distinct, nonprogressive trajectories. A cosine similarity-based angular criterion in PCA was applied to identify metabolites associated with each phenotype. Comprehensive metabolomics, coupled with pathway and functional network analyses, revealed different metabolic remodeling between phenotypes. Responders were enriched in cholesterol and bile acid metabolism, with metabolites linked to fibrogenesis and mitochondrial dysfunction, consistent with severe dietary lipotoxicity. In contrast, mild responders exhibited coordinated perturbations in glycerophospholipid, tyrosine, and gluconeogenic pathways, with corticosterone-centered network features suggestive of a compensatory metabolic adaptation rather than overt lipotoxicity. Collectively, these findings suggest that identical HFDs can lead to divergent lean and obese MASH phenotypes, highlighting candidate biomarkers that may support future stratification of MASLD and inform precision nutrition strategies.
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