Dataset Information

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.

SUBMITTER: Zhong M

PROVIDER: S-EPMC6542763 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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

Zhong Ming M Wu Yilong Y Ou Weijie W Huang Linjing L Yang Liyong L

Bioscience reports 20190531 5

<b>Aims</b>: To identify the key differentially expressed genes (DEGs) in islet and investigate their potential pathway in the molecular process of type 2 diabetes.<b>Methods</b>: 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 ...[more]

PMID: 31088900

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Dataset Information

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

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

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