Exploration and validation of biomarkers related to bile acid metabolism in obese patients

Background Studies have shown that bile acids can effectively improve metabolism and play an anti-obesity role. However, the mechanism of bile acid-related genes in obesity has not been fully elucidated. Methods Differential analysis was implemented to acquire differentially expressed genes (DEGs) between obesity (Obese) and Nonobese samples. The critical module genes were identified by the weighted gene co-expression network analysis (WGCNA). Overlapping genes derived from intersecting DEGs, bile acid metabolism genes, and critical module genes. Biomarkers identified using three ML algorithms and intersection process. Nomogram constructed for predicting disease probabilities. Biomarker functions and pathways determined by enrichment analysis. miRNA-mRNA and mRNA-TF networks created. Results 59 DEGs identified between Obese and Nonobese samples; yellow module deemed critical. 13 overlapping genes found via intersection analysis. PEMT, CP, and SLC27A2 identified as biomarkers via three three machine learning algorithms, used to construct a nomogram for predicting obesity disease probabilities. These biomarkers primarily involved in ER lumen, protein-lipid complex, and FA transmembrane transport activities. mRNA-miRNA network showed CP regulated by hsa-miR-592; TF-mRNA network indicated CP, PEMT, and SLC27A2 regulated by HNF4A, MLXIPL, and TCF2. RT-qPCR results showed PEMT and CP up-regulated in obese mouse tissues, while SLC27A2 expression was lower than in non-obese samples. Conclusion Three biomarkers (CP, PEMT, SLC27A2) linked to obesity, involved in bile acid synthesis/accumulation, impacting energy metabolism, glucose/lipid metabolism, etc. Study offers clinical significance for obesity diagnosis.