Gene Expression Profiling of Type 2 Diabetes Mellitus by Bioinformatics Analysis

Abstract

Objective. The aim of this study was to identify the candidate genes in type 2 diabetes mellitus (T2DM) and explore their potential mechanisms. Methods. The gene expression profile GSE26168 was downloaded from the Gene Expression Omnibus (GEO) database. The online tool GEO2R was used to obtain differentially expressed genes (DEGs). Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by using Metascape for annotation, visualization, and comprehensive discovery. The protein-protein interaction (PPI) network of DEGs was constructed by using Cytoscape software to find the candidate genes and key pathways. Results. A total of 981 DEGs were found in T2DM, including 301 upregulated genes and 680 downregulated genes. GO analyses from Metascape revealed that DEGs were significantly enriched in cell differentiation, cell adhesion, intracellular signal transduction, and regulation of protein kinase activity. KEGG pathway analysis revealed that DEGs were mainly enriched in the cAMP signaling pathway, Rap1 signaling pathway, regulation of lipolysis in adipocytes, PI3K-Akt signaling pathway, MAPK signaling pathway, and so on. On the basis of the PPI network of the DEGs, the following 6 candidate genes were identified: PIK3R1, RAC1, GNG3, GNAI1, CDC42, and ITGB1. Conclusion. Our data provide a comprehensive bioinformatics analysis of genes, functions, and pathways, which may be related to the pathogenesis of T2DM.

Pharmacoinformatics and UPLC-QTOF/ESI-MS-Based Phytochemical Screening of Combretum indicum against Oxidative Stress and Alloxan-Induced Diabetes in Long–Evans Rats

“…Inflammatory response—the most significant biological process—is documented to be associated with diabetes [ 31 ]. G-protein-coupled receptor signaling pathways are related with the crosstalk with insulin signaling [ 32 ], while chemokines have been found to be associated with or implicated in the pathogenesis of type 1 diabetes [ 30 ]. Type 2 diabetes has broad impact on immune responses [ 33 ].…”

[Retracted] Establishment and Verification of a Gene Signature for Diagnosing Type 2 Diabetics by WGCNA, LASSO Analysis, and In Vitro Experiments

“…The data indicated that these genes could participate in modulating inflammatory response and β cell dysfunction. In previous bioinformatic analysis, PIK3R1, RAC1, GNG3, GNAI1, CDC42, and ITGB1 have been identified as candidate genes of the pathogenesis of type 2 diabetes [ 33 ]. For instance, epidemiological studies have demonstrated that PIK3R1 exerts a critical role in insulin signal transduction during type 2 diabetes development [ 34 , 35 ].…”

ASK1-Interacting Protein 1 Acts as a Novel Predictor of Type 2 Diabetes

“…Furthermore, in vivo models of mouse obesity have demonstrated that the absence of JNK1 would improve insulin sensitivity ( 29 ). In addition, studies on Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of T2D-associated genes have revealed that MAPK signaling pathways are associated with T2D ( 30 , 31 ). An in vivo study using a p38 MAPK inhibitor to treat db/db mice showed that inhibition of the p38 MAPK pathway could reduce blood glucose level and improve the function of β-cells, thus ameliorating the pathogenesis of T2D ( 32 ).…”