Bioinformatics analysis identifies key secretory protein-encoding differentially expressed genes in adipose tissue of metabolic syndrome.

The objective of this study was to identify key secretory protein-encoding differentially expressed genes (SP-DEGs) in adipose tissue in female metabolic syndrome, thus detecting potential targets in treatment. We examined gene expression profiles in 8 women with metabolic syndrome and 7 healthy, normal body weight women. A total of 143 SP-DEGs were screened, including 83 upregulated genes and 60 downregulated genes. GO analyses of these SP-DEGs included proteolysis, angiogenesis, positive regulation of endothelial cell proliferation, immune response, protein processing, positive regulation of neuroblast proliferation, cell adhesion and ER to Golgi vesicle-mediated transport. KEGG pathway analysis of the SP-DEGs were involved in the TGF-beta signalling pathway, cytokine‒cytokine receptor interactions, the hippo signalling pathway, Malaria. Two modules were identified from the PPI network, namely, Module 1 (DNMT1, KDM1A, NCoR1, and E2F1) and Module 2 (IL-7 R, IL-12A, and CSF3). The gene DNMT1 was shared between the network modules and the WGCNA brown module. According to the single-gene GSEA results, DNMT1 was significantly positively correlated with histidine metabolism and phenylalanine metabolism. This study identified 7 key SP-DEGs in adipose tissue. DNMT1 was selected as the central gene in the development of metabolic syndrome and might be a potential therapeutic target.