Identification and analysis of hub genes of hypoxia-immunity in type 2 diabetes mellitus.

Abstract

The chronic metabolic disease named type 2 diabetes (T2D) accounts for over 90% of diabetes mellitus. An increasing number of evidences have revealed that hypoxia has a significantly suppressive effect on cell-mediated immunity, as well as the utilization of glucose in diabetics. Therefore, we aimed to screen and identify hypoxia-immune-related hub genes in T2D through bioinformatic analysis. The Gene Expression Omnibus (GEO) database was used to get T2D gene expression profile data in the peripheral blood samples (GSE184050), and hypoxia-related genes were acquired from Molecular Signatures Database (MSigDB). Differentially expressed mRNAs (DEGs) and lncRNAs (DELs) between T2D and normal samples were identified by DeSeq2 package. The clusterProfiler package was used to perform enrichment analyses for the overlapped genes of DEGs and hypoxia-related genes. Further, Hypoxia-related hub genes were discovered using two machine learning algorithms. Next, the compositional patterns of immune and stromal cells in T2D and healthy groups were estimated by using xCell algorithm. Moreover, we used the weighted correlation network analysis (WGCNA) to examine the connection between genes and immune cells to screen immune-related genes. Gene Set Enrichment Analysis (GSEA) was used to investigate the functions of the hypoxia-immune-related hub genes. Finally, two peripheral blood cohorts of T2D (GSE184050 and GSE95849) as well as the quantitative real-time PCR (qRT-PCR) experiments for clicinal peripheral blood samples with T2D were used for verification analyses of hub genes. And meanwhile, a lncRNA-TF-mRNA network was constructed. Following the differentially expressed analysis, 38 out of 3822 DEGs were screened as hypoxia-related DEGs, and 493 DELs were found. These hypoxia-related DEGs were mainly enriched in the GO terms of pyruvate metabolic process, cytoplasmic vesicle lumen and monosaccharide binding, and the KEGG pathways of glycolysis/gluconeogenesis, pentose phosphate pathway and biosynthesis of nucleotide sugars. Moreover, 7 out of hypoxia-related DEGs were identified as hub genes. There were six differentially expressed immune cell types between T2D and healthy samples, which were further used as the clinical traits for WGCNA to identify AMPD3 and IER3 as the hypoxia-immune-related hub genes. The results of the KEGG pathways of genes in high-expression groups of AMPD3 and IER3 were mainly concentrated in glycosaminoglycan degradation and vasopressin-regulated water reabsorption, while the low-expression groups of AMPD3 and IER3 were mainly associated with RNA degradation and nucleotide excision repair. Finally, when compared to normal samples, both the AMPD3 and IER3 were highly expressed in the T2D groups in the GSE184050 and GSE95849 datasets. The result of lncRNA-TF-mRNA regulatory network showed that lncRNAs such as BACH1-IT1 and SNHG15 might induce the expression of the corresponding TFs such as TFAM and THAP12 and upregulate the expression of AMPD3. This study identified AMPD3 and IER3 as hypoxia-immune-related hub genes and potential regulatory mechanism for T2D, which provided a new perspective for elucidating the upstream molecular regulatory mechanism of diabetes mellitus.