The study identified key lipid metabolism-related genes (LMGs) associated with nonalcoholic fatty liver disease (NAFLD) using transcriptomic and single-cell RNA sequencing (scRNA-seq) analyses. Researchers analyzed multiple datasets (GSE48452, GSE63067, GSE89632, GSE72756) alongside scRNA-seq data (GSE159977). They identified 295 differentially expressed genes (DEGs) between NAFLD and controls, with 24 LMGs linked to fatty acid metabolism, bile acid metabolism, and inflammation.
NAFLD patients were classified into two clusters based on these LMGs. Cluster 1 showed inhibited fatty acid metabolism but activated inflammatory and TNF signaling pathways, indicating disease heterogeneity. Using machine learning methods (LASSO, BSR, Boruta), three key LMGs—PRKAA2, KLF5, and ME1—were identified. ME1 and PRKAA2 were validated as core genes for diagnostic modeling, with ME1 showing stronger biological relevance. A two-gene diagnostic model integrating PRKAA2 and ME1 achieved high accuracy (AUC = 0.945).
Immune analysis revealed significant associations of ME1 and PRKAA2 with immune cells, especially NK and T cells, highlighting immune-metabolic crosstalk in NAFLD. scRNA-seq identified six cell types, with NK cells strongly correlating with ME1 expression. NAFLD samples showed reduced T-cell proportions but elevated NK-cell infiltration, indicating immune imbalance. ME1 was found to drive lipid accumulation and influence NK-cell metabolic activity, while PRKAA2's role was context-dependent.
Functional pathway analysis revealed that differential LMGs were involved in TNF, JAK–STAT, AMPK, and PPAR signaling, which regulate lipid metabolism and inflammation. The study underscores ME1’s potential as a biomarker and therapeutic target, linking lipid dysregulation and immune imbalance in NAFLD. Future studies should validate these findings and explore ME1’s therapeutic potential.