Transcriptomic profiling of diabetic retinopathy: insights into RPL11 and bisphenol A

Diabetic retinopathy (DR) is a leading microvascular complication of diabetes mellitus, causing irreversible vision loss in adults worldwide. However, the molecular mechanisms underlying DR pathogenesis-especially the crosstalk between core genes, immune microenvironment, and environmental factors remains incompletely elucidated. This knowledge gap hinders the development of effective preventive and therapeutic strategies for DR, making it urgent to identify key molecular targets and regulatory pathways.

To elucidate the molecular mechanisms underlying DR through transcriptomic analysis, and explore the potential interaction between ribosomal protein L11 (RPL11) and bisphenol A (BPA) using in silico approaches.

The gene expression dataset associated with DR (GSE221521, Platform: GPL24676) was preprocessed and statistically evaluated via R (version 4.5.1). Differentially expressed genes (DEGs) were identified using linear models with empirical Bayes moderation (limma R package, version 3.65.7), and weighted gene co-expression network analysis (WGCNA) was applied via the WGCNA R package (version 1.73) to detect co-expressed gene modules. Functional annotations were performed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses (clusterProfiler R package, version 4.17.0). To validate the core gene, we conducted Gene Set Enrichment Analysis (GSEA, fgsea R package, version 1.35.8), immune cell infiltration profiling (CIBERSORT algorithm, version 1.03), molecular docking (AutoDock Vina, version 1.2.0), and molecular dynamics simulations (GROMACS, version 2022.4).

Differential expression analysis (thresholds: |log₂-fold change (FC)| ≥ 0.585 [1.5-fold change] and Benjamini-Hochberg (BH)-adjusted P < 0.05) identified 341 DR-specific DEGs (intersection of DEGs from DR vs. healthy controls [Nor] and DR vs. diabetes mellitus [DM] without retinopathy). Additionally, WGCNA (soft threshold power β=3, scale-free R²=0.8) identified 38 co-expressed gene modules, with the "black and brown" modules showing the strongest correlation with DR (Spearman correlation coefficient > 0.6, adjusted P < 0.001). Venn analysis of 341 DR-specific DEGs and WGCNA core genes (gene significance [GS] > 0.5, module membership [MM] > 0.8) revealed 201 co-expressed genes, and GO and KEGG pathway enrichment analyses were performed (P < 0.05). RPL11 was identified as a core gene with high diagnostic potential in peripheral blood (area under the curve [AUC] = 0.796, 95% Confidence Interval (CI):0.716-0.875), with significantly downregulated expression (log₂FC = -0.67, adjusted P = 4.19×10^-5) observed in the DR cohort. It also exhibited significant binding affinity with BPA in molecular docking simulations (binding energy = -5.491 kcal/mol, and molecular dynamics simulations confirmed the BPA-RPL11 complex's stability (backbone RMSD: 0.45-0.55 nm after 60 ns, persistent hydrogen bonds: 2-5 throughout the simulation), providing hypothesis-generating clues for DR-related molecular research.

This research analyzed molecular associations related to DR using peripheral blood transcriptomic data, identifying RPL11 as a hypothesis-generating molecule with potential associations with DR in peripheral blood-this finding serves as a hypothesis-generating candidate for subsequent DR-related molecular research. Environmental BPA exposure was found to be associated with RPL11 dysregulation in peripheral blood (in silico evidence: BPA-RPL11 specific binding and stable complex formation), suggesting a potential correlative link to DR progression that requires further empirical validation. These findings highlight the need for additional research to explore the possibility of minimizing BPA contamination as a potential DR risk mitigation strategy, rooted in hypothesis-generating insights.