ORIGINAL RESEARCH article
Front. Endocrinol.
Sec. Diabetes: Molecular Mechanisms
Volume 16 - 2025 | doi: 10.3389/fendo.2025.1487007
This article is part of the Research TopicTargeting early-stage Diabetic Retinopathy and Age-related Macular Degeneration: Diagnosis and management.View all 5 articles
MAPK8 and HDAC6: Potential Biomarkers Related To Autophagy In Diabetic Retinopathy Based On Bioinformatics Analysis
Provisionally acceptedSelect one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Introduction: One of the most common vascular diseases of the retina is diabetic retinopathy (DR), a microvascular condition caused by diabetes. The autophagy system transports and degrades cytoplasmic substances to lysosomes as part of the intracellular degradation process. Autophagy appears to be an important regulator in the development and progression of DR, but its mechanism and potential role are unclear. The purpose of this study is to identify autophagy-related genes in DR and find potential biomarkers associated with DR through bioinformatics analysis.We retrieved the dataset GSE102485 from the Gene Expression Omnibus (GEO) database and compiled a list of 344 autophagy-related genes. Using the R software, bioinformatics analysis was used to identify the differentially expressed autophagy-related genes (ARGs). Then, we identified the autophagy-related hub genes (ARHGs) through a series of analyses including Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, correlation analysis, and protein-protein interaction (PPI) network. In addition, the miRNAgene-TF interaction network was generated using the NetworkAnalyst platform. Potential therapeutic drugs were predicted utilizing the Drug-Gene Interaction Database (DGIdb). Ultimately, DR was simulated through the high glucose incubation of the retinal pigment epithelium cell line (ARPE-19), and employing quantitative real-time polymerase chain reaction (qRT-PCR) to verify ARHG expression. The effectiveness of ARHGs in diagnosing DR was assessed by measuring the area under the receiver operating characteristic (ROC) curve.Results: Differential expression analysis identified 26 ARGs, of which 6 were upregulated and 20 were downregulated. Through GO and KEGG enrichment analysis, it was found that ARGs showed significant enrichment in autophagy-related pathways. Using PPI network analysis, 7 ARHGs were identified. The expression of MAPK8, HDAC6, DNAJB1 and TARDBP, in a model of DR were confirmed by qRT-PCR. The ROC curve results showed that MAPK8, HDAC6, DNAJB1 and TSC2 had high predictive accuracy and could be used as biomarkers for DR.Through bioinformatics analysis, we identified 26 genes that may be associated with autophagy in DR. We suggest that the hub genes MAPK8 and HDAC6 as biomarkers may be involved in autophagy in DR.
Keywords: Diabetic retinopathy1, Autophagy2, biomarker3, MAPK84, HDAC65
Received: 05 Sep 2024; Accepted: 05 May 2025.
Copyright: © 2025 . This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.