Abstract:

Objective By analyzing the Gene Expression Omnibus （GEO） database （GSE98895 and GSE23561） of peripheral blood mononuclear cells （PBMC） from patients with metabolic syndrome，and to identify the key genes for metabolic syndrome. Methods The differentially expressed genes of PBMC in metabolic syndrome patients and healthy subjects in the GSE98895 dataset were analyzed. Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway analysis of differentially expressed genes were carried out. Protein-protein interaction （PPI） network analysis was also performed. The top 10 hub genes with a high degree of connectivity were selected in the PPI network. The hub gene expression in PBMC of metabolic syndrome patients had been illustrated in the GSE98895 and GSE23561 datasets and human protein atlas （HPA） dataset. A circular RNA（circRNA）-microRNA（miRNA）-mRNA network for the pathogenesis of metabolic syndrome was constructed. Results A total of 155 differentially expressed genes between metabolic syndrome patients and healthy subjects were identified，among which 62 genes were up-regulated，and 93 genes were down-regulated. The results of the GO and the KEGG enrichment pathway analysis indicated that the differentially expressed genes were mainly involved in the regulation of transcription，immune response，cAMP signaling pathway and T cell receptor signaling pathway. Totally，10 genes （JUN，IFNG，MMP9，PIK3R1，LCK，NGF，PDGFRB，CD79B，CX3CR1 and ABCA1） with the highest degree scores were identified. The expressions of IFNG and LCK in PBMC of patients with metabolic syndrome were higher than those of healthy subjects （P<0.05）. HPA dataset analysis showed that IFNG and LCK were mainly expressed in T cells and natural killer（NK） cells. A circRNA-miRNA-mRNA network had been constructed for metabolic syndrome. Totally，7 miRNA and 43 circRNA associated with IFNG were identified，and 16 miRNA and 62 circRNA associated with LCK were identified. Conclusions IFNG and LCK have up-regulated expressions in PBMC of metabolic syndrome patients. An in-depth study of the circRNA-miRNA-mRNA network for IFNG and LCK may help to discover the molecular mechanism of occurrence and development and the biomarkers of metabolic syndrome.

Key words: Metabolic syndrome, Gene Expression Omnibus database, Differentially expressed gene, Biomarker