ArticleDiabetology & metabolic syndrome2025
Multi-omics and experimental validation studies reveal key biomarkers of cellular senescence in diabetic retinopathy.
Article in Diabetology & metabolic syndrome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Hypothalamic Inflammaging: A Central Driver of Type 2 Diabetes Mellitus and Metabolic Disease in Aging.Diabetes & metabolism journal · 2026Review
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Abstract
objectiveDiabetic retinopathy (DR) is a prevalent microvascular complication of diabetes, contributing to vision impairment and related retinal diseases. Growing evidence indicates that cellular senescence (CS) under high-glucose conditions plays a role in the pathogenesis of DR. This study aims to identify key biomarkers of CS in DR by integrating transcriptomics, single-cell sequencing data, and experimental validation, thereby offering insights for understanding the disease mechanism and developing novel therapeutic strategies.
methodsDR-related datasets and CS-related genes (CSRGs) were retrieved from the Gene Expression Omnibus (GEO) and CellAge databases. The characteristic gene set for DR-CS was obtained by intersecting differentially expressed genes (DEGs), Weighted Gene Co-expression Network Analysis (WGCNA) results, and CSRGs. Subsequent analyses involved constructing protein-protein interaction (PPI) network, cytoHubba screening, enrichment analysis, and immune infiltration analysis. Machine learning methods were used to identify key biomarkers from the DR-CS characteristic gene set, which were then validated using external datasets. Single-cell sequencing and gene set enrichment analysis (GSEA) were employed to determine the cellular location and biological functions of DR-CS key biomarkers, and animal experiments further validated these biomarkers.
resultsA total of 67 DR-CS-related characteristic genes were identified. Enrichment analysis highlighted pathways like cellular senescence and the Advanced Glycation Endproducts-Receptor for Advanced Glycation Endproducts (AGE-RAGE) signaling pathway in diabetic complications as being closely related to DR development. A set of 13 characteristic genes was selected through a combination of PPI network and six cytoHubba algorithms. Further analysis using machine learning, expression analysis, and Receiver Operating Characteristic (ROC) analysis revealed MYC and LOX as key biomarkers of DR-CS. The expression characteristics of MYC and LOX in various cells were examined using single-cell RNA sequencing. Animal experiments demonstrated that the expression levels of MYC and LOX in the retina were significantly higher in DR group than in the control group (P < 0.05).
conclusionMYC and LOX were identified as key biomarkers of DR-CS. Thus, investigating these genes may provide new therapeutic targets for DR treatment by targeting cellular senescence.
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