Identification of hub genes affecting gestational diabetes mellitus based on GEO database.

Abstract

This research aimed to obtain gestational diabetes mellitus (GDM) related hub genes, providing new targets for clinical diagnosis and treatment of GDM. The microarray data of GSE9984 and GSE103552 were obtained from the Gene Expression Omnibus (GEO). The dataset GSE9984 contained placental gene expression profiles of 8 GDM patients and four healthy specimens. The dataset GSE103552 contained 20 specimens from GDM patients and 17 normal specimens. The differentially expressed genes (DEGs) were identified by GEO2R online analysis. DAVID database was applied to conduct functional enrichment analysis of the DEGs. The Search Tool for the Retrieval of Interacting Genes (STRING) database was adopted to acquire protein-protein interaction (PPI) networks. A total of 195 up-regulated and 371 down-regulated DEGs were selected in the GSE9984, and total of 191 up-regulated and 229 down-regulated DEGs were selected in the GSE103552. In the two datasets, 24 common differential genes were obtained and named co-DEGs. The Gene Ontology (GO) annotation analysis indicated the DEGs participated in multi-multicellular organism process, endocrine hormone secretion, long-chain fatty acid biosynthetic process, cell division, unsaturated fatty acid biosynthetic process, cell adhesion and cell recognition. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis suggested that GSE9984 and GSE103552 were related to vitamin digestion and absorption, tryptophan metabolism, steroid hormone biosynthesis, Ras signaling pathway, protein digestion and absorption, PPAR signaling pathway, PI3K-Akt signaling pathway, p53 signaling pathway. PPI was constructed in string database, and six hub genes were selected, including CCNB1, APOA2, AHSG and IGFBP1. Four critical genes were identified to be considered as therapeutic potential biomarkers of GDM, including CCNB1, APOA2, AHSG and IGFBP1.