Sex-Specific Gene Expression in MASLD: A Transcriptomic and Systems Biology Analysis Reveals Key Regulatory Modules and Immune Networks

Background Metabolic dysfunction-associated steatotic liver disease (MASLD) is a complex metabolic disorder disease characterized by significant sex-related differences in its pathogenesis and progression. Elucidating the sex-specific molecular mechanisms of MASLD is crucial for identifying novel therapeutic targets. Methods We analyzed liver gene expression profiles from MASLD patients retrieved from the Gene Expression Omnibus (GEO) database (dataset GSE159088). Sex-stratified analysis was performed to identify differentially expressed genes (DEGs) between male and female patients. Functional annotation of these DEGs was conducted through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Further mechanistic insights were explored using Gene Set Variation Analysis (GSVA) and Gene Set Enrichment Analysis (GSEA). To identify robust sex-associated gene modules in MASLD, we applied Weighted Gene Co-expression Network Analysis (WGCNA) and machine learning algorithms. Additionally, immune infiltration patterns in MASLD were assessed using the single-sample GSEA (ssGSEA) algorithm, and their correlation with sex-specific gene expression was examined. Results We identified 31 sex-specific DEGs in MASLD liver tissues. Functional enrichment revealed these DEGs were significantly involved in metabolism-related pathways such as glycine, serine, threonine, cysteine, and methionine metabolism. GSVA and GSEA further confirmed their enrichment in core sexually dimorphic biological pathways. We constructed a sex-associated gene co-expression network by WGCNA and identified a key module (purple module) highly correlated with male sex. Machine learning algorithms, including Random Forest and Support Vector Machine (SVM), prioritized hub genes (e.g., FAM224A, CPE, ASCL1, HYDIN, TSPAN8, ESPL1) within this module. Integrative analysis further demonstrated that these sex-specific hub genes were significantly correlated with altered immune infiltration landscapes (particularly involving Natural Killer T cells, Type 1 T helper cells, and Activated CD8 ⁺ T cells) and associated with epigenetic regulatory processes such as chromatin remodeling and DNA methylation. Conclusion This study delineates a multi-dimensional sex-specific molecular signature in MASLD, providing insights into mechanisms of sexual dimorphism in disease progression and highlighting potential targets for precision, sex-tailored interventions.