Exploring the molecular targets for Type 2 diabetes-induced Alzheimer's disease through bioinformatics analysis

Epigenomics. 2023 Jun;15(11):619-633. doi: 10.2217/epi-2023-0149. Epub 2023 Aug 9.

Abstract

Aim: The purpose of this study was to elucidate the potential mechanisms of Alzheimer's disease (AD) induced by Type 2 diabetes mellitus (T2DM) through bioinformatics analysis, to provide new treatment targets for this disease. Methods: We used weighted gene coexpression network analysis and differentially expressed genes analysis to identify significantly differentially expressed genes shared by T2DM and AD. Molecular docking was used to predict possible protein targets for T2DM-induced AD. Results: The direct interaction of CD44 and STAT3 may play a significant role in the development of T2DM-induced AD. Conclusion: A new approach to treating T2DM-associated AD may be provided by these hub genes and their predicted molecular targets.

Keywords: Alzheimer’s disease; CD44; STAT3; Type 2 diabetes mellitus; bioinformatics analysis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alzheimer Disease* / genetics
  • Alzheimer Disease* / metabolism
  • Computational Biology
  • Diabetes Mellitus, Type 2* / genetics
  • Gene Regulatory Networks
  • Humans
  • Molecular Docking Simulation