ArticlePeerJ2025
Bioinformatic analysis and experimental validation of hub autophagy-related genes as novel biomarkers for type 2 diabetes mellitus and Alzheimer's disease.
Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Ochratoxin A and Clear Cell Renal Cell Carcinoma: Exploring Potential Molecular Links Through Network Toxicology and Machine Learning.International journal of molecular sciences · 2026Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background & Objectives: Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM) share considerable similarities in their proposed patho mechanisms. Autophagy, an intrinsic cellular process involved in the degradation of dysfunctional organelles and abnormal proteins, has been implicated in the pathogenesis of both AD and T2DM. This study aims to identify potential shared biomarkers related to autophagy in AD and T2DM by analyzing hub differentially expressed autophagy-related genes (DEARGs) and examining their potential functions. Methods: Gene expression profiles for AD and T2DM were acquired from the Gene Expression Omnibus (GEO) database (training sets: GSE109887 for AD and GSE104674 for T2DM; validation sets: GSE122063 for AD and GSE64998 for T2DM). Autophagy-related genes (ARGs) were extracted from multiple databases. DEARGs were identified and integrated with module genes derived from weighted gene co-expression network analysis (WGCNA) to determine key shared ARGs. Then, the STRING database was used to construct a protein-protein interaction (PPI) network, from which hub genes were identified. These hub genes were validated using independent microarray datasets through differential expression analysis, and ROC curves were generated to assess their diagnostic value. Moreover, the expression of the hub genes was validated in brain tissues of T2DM mouse models using qRT-PCR. Results: A total of 33 shared DEARGs were identified, among which 12 were designated as hub genes (A Conclusions: Our integrated bioinformatics analyses, supported by preliminary experimental validations, identified several hub ARGs shared between AD and T2DM. Among these,
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