Identification of Key Genes in Non-Alcoholic Fatty Liver Disease Development through Bioinformatics Analysis

Objective: The prevalence of NAFLD has increased globally. We performed bioinformatics analysis to identify key biomarkers associated with NAFLD formation. Methods: and results We conducted an analysis of differential expression genes in the GSE164760 dataset from the GEO database, comparing healthy controls, NASH, and NAFLD-HCC. Subsequently, we validated the expression levels of NAFLD-HCC differential genes in TCGA liver hepatocellular carcinoma and identified 7 differential expression genes. We developed a nomogram model to predict the progression from NASH to NAFLD-HCC and found that YWHAZ and pathological stage were independent factors affecting liver cancer prognosis. Based on this, we constructed a prognostic nomogram model. We also discovered a significant positive correlation between YWHAZ expression and obesity, insulin resistance, and NAFLD histological grade. Finally, we utilized various bioinformatics tools such as GEO, Xiantao, UALCAN, and HAP to conduct in-depth research on YWHAZ expression in liver cancer. Conclusion: This study indicates that YWHAZ is closely related to the development of NAFLD disease, and these findings provide important references for the prevention and treatment of NAFLD.