To investigate the potential pathogenesis of metabolic dysfunction-associated steatotic liver disease (MASLD) by using bioinformatics approaches. Data from three MASLD-related datasets (GSE89632, GSE72756 and GSE49541) were downloaded from the Gene Expression Omnibus (GEO) database and merged for analysis. Differentially expressed genes (DEGs) were identified via the limma package in R (|logFC|> 1, adjusted p value < 0.05). Functional enrichment analysis was conducted via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and gene set enrichment analysis (GSEA). Protein‒protein interaction (PPI) network analysis was used to identify hub genes related to MASLD. 1278 DEGs (1238 upregulated, 40 downregulated) related to MASLD were identified. GO analysis revealed that the DEGs were involved mainly in the regulation of membrane potential (BP), the monoatomic ion channel complex (CC) and postsynaptic neurotransmitter receptor activity (MF). KEGG analysis highlighted neuroactive ligand-receptor interactions and taste transduction pathways, which were downregulated in MASLD. PPI network analysis identified 10 hub genes: PIK3CD, PIK3R2, PIK3R1, PIK3R3, PIK3CB, PIK3CA, SRC, PIK3CG, PIK3R5 and PIK3R6. This study identified 10 hub genes associated with MASLD, primarily involved in the PI3K/AKT signaling pathway, which could serve as biomarkers for MASLD diagnosis and progression, with the pathway potentially becoming a new therapeutic target.