Identification of key genes involved in type 2 diabetic islet dysfunction: a bioinformatics study

Abstract

Aims: To identify the key differentially expressed genes (DEGs) in islet and investigate their potential pathway in the molecular process of type 2 diabetes. Methods: Gene Expression Omnibus (GEO) datasets (GSE20966, GSE25724, GSE38642) of type 2 diabetes patients and normal controls were downloaded from GEO database. DEGs were further assessed by enrichment analysis based on the Database for Annotation, Visualization and Integrated Discovery (DAVID) 6.8. Then, by using Search Tool for the Retrieval Interacting Genes (STRING) 10.0 and gene set enrichment analysis (GSEA), we identified hub gene and associated pathway. At last, we performed quantitative real-time PCR (qPCR) to validate the expression of hub gene. Results: Forty-five DEGs were co-expressed in the three datasets, most of which were down-regulated. DEGs are mostly involved in cell pathway, response to hormone and binding. In protein–protein interaction (PPI) network, we identified ATP-citrate lyase (ACLY) as hub gene. GSEA analysis suggests low expression of ACLY is enriched in glycine serine and threonine metabolism, drug metabolism cytochrome P450 (CYP) and NOD-like receptor (NLR) signaling pathway. qPCR showed the same expression trend of hub gene ACLY as in our bioinformatics analysis. Conclusion: Bioinformatics analysis revealed that ACLY and the pathways involved are possible target in the molecular mechanism of type 2 diabetes.

Metalloproteins and apolipoprotein C: candidate plasma biomarkers of T2DM screened by comparative proteomics and lipidomics in ZDF rats

“…The comparison method we adopted fully considered the in uence of genetics and environments. Although this comparison will overestimate the role of the genetic effects of the leptin receptor gene in T2DM and increase the di culty of comparison with other similar studies [57,58], we believe this is a simple and effective comparison strategy when the population's genetic background is not known clearly. So far, very limited studies have been performed with regard to detection of plasma proteins and lipids pro les in ZDF rats.…”

<em>In&nbsp;silico</em> prediction and validation of potential therapeutic genes in pancreatic &beta;‑cells associated with type 2 diabetes

“…Moreover, using the GSE20966 dataset, Ding et al (33) revealed DEGs that are enriched in the pancreatic secretion pathway, and that serpin family G member 1 and alanyl aminopeptidase membrane are associated with the development of T2D. In addition, Zhong et al (34) reported that ATP-citrate lyase is hub gene involved in the molecular mechanism of T2D. Based on previous studies, the characteristic of the PPI network were further analyzed in the present study, which identified additional hub genes, including ALB, IL-8, CD44, CCL2, HGF, CFTR, HIST1H2BN, MAPK11 and NTRK2.…”

Antagonistic epistasis of Hnf4α and FoxO1 networks through enhancer interactions in β-cell function

“…We found alterations of Arhgef9, encoding Rho guanine nucleotide exchange factor 9, a guanine exchange factor for Cdc42. This is one of the few genes consistently identified in multiple surveys of diabetic islet gene expression (Zhong et al, 2019). Small G-proteins, such as Rho, Rac1, Cdc42, and Arf6 play important roles in cytoskeletal remodeling, vesicle fusion, and insulin exocytosis (Kowluru, 2017).…”

“…S4). The latter included ARHGEF9, one of only 20 genes concordantly decreased in three independent RNA profiling datasets of type 2 diabetes patients (Zhong et al, 2019). 12 genes (Ttc22,Sel1l3,Rspo4,Pla2g4b,Nr1h4,Lad1,Jmjd7,Fut1,Elovl2,Dll4,Cacnb3,and Baiap2l2) were shared in common between the two comparisons (Table S7 and S8).…”