Screening of Biomarkers in Liver Tissue after Bariatric Surgery Based on WGCNA and SVM-RFE Algorithms

Abstract

As the most common chronic liver disease around the world, nonalcoholic fatty liver disease (NAFLD) has a close connection with obesity, diabetes, and metabolic syndrome. Bariatric surgery (BS) is considered to be the most effective treatment for NAFLD. However, the regulatory mechanism of hepatic lipid metabolism after BS remains poorly elucidated. By analyzing two transcriptome datasets regarding liver tissues after BS, namely, GSE83452 and GSE106737, we acquired 110 differentially expressed genes (DEGs). By further analysis of DEGs in terms of the weighted gene coexpression network analysis (WGCNA) and support vector machine-recursive feature elimination (SVM-RFE) algorithms, we identified four crucial genes participating in the regulation of hepatic lipid metabolism: SRGN, THEMIS2, SGK1, and FPR3. In addition, the results of gene set enrichment analysis (GSEA) showed that BS can activate immune-related regulatory pathways and change immune cell infiltration levels. Finally, through cellular level studies, we found that the silencing of SRGN affects the expression of SREBP-1, SIRT1, and FAS during adipogenesis in the liver and the formation of lipid droplets in the liver. In summary, the immune system in the liver is activated after BS, and SRGN participates in the regulation of hepatic lipid metabolism.