Objective: Non-alcoholic fatty liver disease (NAFLD) poses significant health risks, including the potential progression to more severe liver conditions such as liver fibrosis, cirrhosis, and even hepatocellular carcinoma, but its underlying mechanisms are not well understood. This study aimed to identify potential hub genes for NAFLD and evaluate their clinical application in predicting the condition.
Methods: We conducted differential expression analysis and weighted gene co-expression network analysis (WGCNA) to identify NAFLD susceptibility modules and hub genes. We performed KEGG and GO analyses to explore the potential roles of these hub genes. We developed a nomogram model and ROC curves to assess the diagnostic efficacy of the hub genes. Additionally, we investigated the correlation between FOS and immune infiltration. Finally, we conducted a Mendelian randomization study based on genome-wide association studies to determine the causal effect of FOS on NAFLD.
Results: WGCNA analysis was conducted to construct gene co-expression networks, identify the most significant module, and identify 115 key genes derived from the overlapping results of WGCNA and differential expression analysis. GO and KEGG pathway enrichment analyses revealed that these key genes were associated with fat cell differentiation, ameboidal−type cell migration, response to lipopolysaccharide, TNF signaling pathway, MAPK signaling pathway, and AGE−RAGE signaling pathway in diabetic complications. Using Cytoscape software, we identified the top ten up-regulated genes with high scores: FOS, JUN, NR4A1, JUNB, EGR1, MYC, IL1B, CCL2, CXCL8, and PTGS2. Furthermore, our nomogram model demonstrated good performance in predicting NAFLD, and the ROC curve confirmed its diagnostic effectiveness. Finally, we focused on FOS and observed a causal association between FOS and immune cell infiltrates in NAFLD. In the inverse variance weighting analysis, we found that FOS was not associated with the risk of NAFLD, with an odds ratio of 0.997 (95% CI = 0.947-1.049, p = 0.898).
Conclusion: We identified hub genes related to NAFLD, which may provide insights into early diagnostic approaches and contribute to the understanding of molecular mechanisms underlying NAFLD risk genes.