The Identification of Hub Genes and Pathways in type 2 Diabetes Mellitus by Bioinformatics Analysis

Abstract Background This study aimed to identify potential core genes and pathways involved in type 2 diabetes mellitus (T2DM) through exhaustive bioinformatics analysis. This study elucidated parts of the pathogenesis of T2DM and screened therapeutic targets of the treatment. Method: The original microarray data GSE25724 was downloaded from the Gene Expression Omnibus database. Data were processed by the limma package in R software and the differentially expressed genes(DEGs) were identified. Gene Ontology(GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis were carried out to identify potential biological functions and pathways of the DEGs. The STRING(Search Tool for the Retrieval of Interacting Genes ) and Cytoscape software were used to establish a protein-protein interaction(PPI) network for the DEGs.Hub genes were identified using the PPI network.Results In total, 75 DEGs were involved in T2DM, with 1 up-regulated gene, and 74 down-regulated genes. GO enrichment analysis showed that DEGs mainly enriched in the regulation of hormone levels, unfolded protein binding.KEGG pathway enrichment analysis showed that DEGs were significantly enriched in the fatty acid metabolism pathway, propionate metabolism pathway, and degradation pathway of valine, leucine, and isoleucine. Furthermore,Neuroendocrine protein 7B2(SCG5),Synaptosomal-associated protein 25 (SNAP25), Sterol Carrier Protein 2 (SCP2), Carboxypeptidase E (CPE),and Protein Convertase Subtilisin/Kexin Type 1 (PCSK1) were the core genes in the PPI network.Conclusion This study identified 5 hub genes as potential biomarkers of type 2 diabetes through bioinformatics analysis, which might increase our understanding of the potential molecular mechanisms of T2DM and provided targets for further research.