Abstract: Objective This study aimed to identify key genes associated with metabolic-associated steatohepatitis (MASH) and to investigate their functional pathways. Methods Liver tissues transcriptomic data and single-cell RNA sequencing (scRNA-seq) data from MASH and normal individuals were downloaded from the Gene Expression Omnibus (GEO) database. The Scissor algorithm was employed to identify cell subpopulations and genes most strongly correlated with the MASH phenotype. Functional enrichment analysis was performed on the associated genes, and key gene levels were further validated by using independent GEO datasets. Silicovirtual knockout experiments were conducted on pivotal genes to assess their potential downstream biological functional impacts. Results A strong correlation was demonstrated in macrophages and lymphocytes frum those with MASH, while certain hepatocytes and stellate cells also showed a positive associations; enrichment analysis of the differentially expressed genes revealed a characteristic cascade in MASH, e.g., the sustained activation of inflammation and stress-response pathways was accompanied by cellular metabolic reprogramming, evidenced by the activation of amino acid catabolism and organic acid synthesis pathways; this process subsequently led to abnormalities in lipid metabolism and transport pathways, collectively exacerbating hepatocellular dysfunction and abnormal lipid accumulation; validation analysis of significantly differentially expressed genes in external datasets identified HMGCS1 as a key gene involved in pathogenesis of MASH; virtual knockout of HMGCS1 demonstrated that the perturbed genes were significantly enriched in pathways related to lipid and cholesterol transport. Conclusion By integrating single-cell and bulk transcriptomic data, this study delineates key cellular subpopulations, pathogenic molecular mechanisms and critical genes associated with MASH occurrence, which might provide a potential targets for therapeutic intervention.

Key words: Metabolic-associated steatohepatitis, Single-cell RNA sequencing, Transcriptome sequencing, Gene enrichment analysis