Bioinformatics Analysis Explores Potential Hub Genes in Nonalcoholic Fatty Liver Disease

Abstract

Background: Nonalcoholic fatty liver disease (NAFLD) is now recognized as the most prevalent chronic liver disease worldwide. However, the dysregulated gene expression for NAFLD is still poorly understood. Material and methods: We analyzed two public datasets (GSE48452 and GSE89632) to identify differentially expressed genes (DEGs) in NAFLD. Then, we performed a series of bioinformatics analyses to explore potential hub genes in NAFLD. Results: This study included 26 simple steatosis (SS), 34 nonalcoholic steatohepatitis (NASH), and 13 healthy controls (HC). We observed 6 up- and 19 down-regulated genes in SS, and 13 up- and 19 down-regulated genes in NASH compared with HC. Meanwhile, the overlapping pathways between SS and NASH were PI3K-Akt signaling pathway and pathways in cancer. Then, we screened out 10 hub genes by weighted Gene Co-Expression Network Analysis (WGCNA) and protein-protein interaction (PPI) networks. Eventually, we found that CYP7A1/GINS2/PDLIM3 were associated with the prognosis of hepatocellular carcinoma (HCC) in the TCGA database. Conclusion: Although further validation is still needed, we provide useful and novel information to explore the potential candidate genes for NAFLD prognosis and therapeutic options.