Open Access

In silico prediction and validation of potential therapeutic genes in pancreatic β‑cells associated with type 2 diabetes

  • Authors:
    • Di Yi Zhou
    • Xin Mou
    • Kaiyuan Liu
    • Wen Hong Liu
    • Ya Qing Xu
    • Danyang Zhou
  • View Affiliations

  • Published online on: September 4, 2020     https://doi.org/10.3892/etm.2020.9188
  • Article Number: 60
  • Copyright: © Zhou et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Diabetes mellitus is becoming a major health burden worldwide. Pancreatic β‑cell death is a characteristic of type 2 diabetes (T2D), but the underlying mechanisms of pancreatic β‑cell death remain unknown. Therefore, the aim of the present study was to identify potential targets in the pancreatic islet of T2D. The GSE20966 dataset was obtained from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were identified by using the GEO2R tool. The Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes Pathway enrichment analysis of DEGs were further assessed using the Database for Annotation, Visualization and Integrated Discovery. Furthermore, protein‑protein interaction (PPI) networks were constructed for the up‑ and downregulated genes using STRING databases and were then visualized with Cytoscape. The body weight, fasting blood glucose (FBG), pancreatic index and biochemistry parameters were measured in db/db mice. Moreover, the morphology of the pancreas was detected by hematoxylin and eosin staining, and hub genes were assessed using reverse transcription‑quantitative PCR (RT‑qPCR) and western blot analysis. In total, 570 DEGs were screened, including 376 upregulated and 194 downregulated genes, which were associated with ‘complement activation, classical pathway’, ‘proteolysis’, ‘complement activation’ and ‘pancreatic secretion pathway’. It was found that the body weight, FBG, alanine aminotransferase, aspartate aminotransferase, total cholesterol, triglycerides, blood urea nitrogen, creatinine, fasting serum insulin, glucagon and low‑density lipoprotein cholesterol levels were significantly higher in db/db mice, while high‑density lipoprotein cholesterol levels and the pancreatic index were significantly decreased. Furthermore, albumin, interleukin‑8, CD44, C‑C motif chemokine ligand 2, hepatocyte growth factor, cystic fibrosis transmembrane conductance regulator, histone cluster 1 H2B family member n, mitogen‑activated protein kinase 11 and neurotrophic receptor tyrosine kinase 2 were identified as hub genes in PPI network. RT‑qPCR and western blotting results demonstrated the same expression trend in hub genes as found by the bioinformatics analysis. Therefore, the present study identified a series of hub genes involved in the progression of pancreatic β‑cell, which may help to develop effective therapeutic strategy for T2D.
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November-2020
Volume 20 Issue 5

Print ISSN: 1792-0981
Online ISSN:1792-1015

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Spandidos Publications style
Zhou DY, Mou X, Liu K, Liu WH, Xu YQ and Zhou D: <em>In&nbsp;silico</em> prediction and validation of potential therapeutic genes in pancreatic &beta;‑cells associated with type 2 diabetes. Exp Ther Med 20: 60, 2020
APA
Zhou, D.Y., Mou, X., Liu, K., Liu, W.H., Xu, Y.Q., & Zhou, D. (2020). <em>In&nbsp;silico</em> prediction and validation of potential therapeutic genes in pancreatic &beta;‑cells associated with type 2 diabetes. Experimental and Therapeutic Medicine, 20, 60. https://doi.org/10.3892/etm.2020.9188
MLA
Zhou, D. Y., Mou, X., Liu, K., Liu, W. H., Xu, Y. Q., Zhou, D."<em>In&nbsp;silico</em> prediction and validation of potential therapeutic genes in pancreatic &beta;‑cells associated with type 2 diabetes". Experimental and Therapeutic Medicine 20.5 (2020): 60.
Chicago
Zhou, D. Y., Mou, X., Liu, K., Liu, W. H., Xu, Y. Q., Zhou, D."<em>In&nbsp;silico</em> prediction and validation of potential therapeutic genes in pancreatic &beta;‑cells associated with type 2 diabetes". Experimental and Therapeutic Medicine 20, no. 5 (2020): 60. https://doi.org/10.3892/etm.2020.9188