BMC Medical Genomics · 7 authors, 4 centres
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This study constructed a miRNA-mRNA regulatory network in trabecular meshwork and aqueous humor of primary open-angle glaucoma patients, identifying 2 miRNAs (miR-106b-5p, miR-15a-5p) and 3 genes (CREB1, CAPZA2, SLC2A3) as potential biomarkers. These biomarkers may aid in early diagnosis and provide insights into the pathogenesis of POAG.
**Background:** Primary open-angle glaucoma (POAG) is the most common glaucoma subtype, characterized by trabecular meshwork (TM) dysfunction leading to elevated intraocular pressure (IOP) and optic nerve damage. MicroRNAs (miRNAs) are post-transcriptional regulators implicated in POAG pathogenesis, but the miRNA-mRNA regulatory network in TM and aqueous humor (AH) remains incompletely understood. This study aimed to construct a miRNA-mRNA regulatory network and identify potential biomarkers for POAG.
**Methods:** TM tissues from 23 POAG patients and 12 healthy controls (corneal donors) were collected at the Second Xiangya Hospital. Due to small tissue size, samples were pooled (5-6 POAG tissues per test, 3 control tissues per test) to yield 4 tests per group. Microarray analysis (GSE138125 for mRNA, GSE231760 for miRNA) identified differentially expressed miRNAs (DEmiRNAs) and mRNAs (DEmRNAs) using thresholds |logFC|>2 for miRNAs and |logFC|>1 for mRNAs, adjusted P<0.05. Target genes of DEmiRNAs were predicted using miEAA and miRNet databases, and overlapping targets with DEmRNAs were identified. GO and KEGG enrichment analyses were performed. A protein-protein interaction (PPI) network of target genes was constructed using STRING, and the top 30 hub genes were selected via CytoHubba. A miRNA-mRNA regulatory network was built using Cytoscape. Hub gene expression was validated in the GSE27276 dataset (TM from 19 controls, 17 POAG). Receiver operating characteristic (ROC) curves were used to assess biomarker potential in TM (from GSE27276) and in AH (from GSE105269, 11 controls, 12 POAG). Gene set enrichment analysis (GSEA) was performed for key genes.
**Key Results:** A total of 29 up-regulated and 7 down-regulated miRNAs, and 923 up-regulated and 887 down-regulated mRNAs were identified in POAG TM vs. controls. Target genes and DEmRNAs were enriched in nitric oxide biosynthetic process, vasopressin-regulated water reabsorption, and other pathways. The PPI network identified top 30 hub genes regulated by 24 DEmiRNAs. Validation in GSE27276 showed 8 hub genes were significantly differentially expressed: CAPZA2, CREB1, HSP90AB1, RCOR3, SLC6A4 (up-regulated); SCAMP2, SEMA4B, SLC2A3 (down-regulated). ROC analysis in TM identified CAPZA2 (AUC>0.8), CREB1 (AUC>0.8), SEMA4B (AUC>0.8), and SLC2A3 (AUC>0.8) as good biomarkers. In AH, miR-106b-5p (AUC=0.727) and miR-15a-5p (AUC=0.705) showed moderate accuracy. Combining miRNA-mRNA axes (miR-106b-5p-CAPZA2/CREB1, miR-15a-5p-SLC2A3) yielded AUC>0.9. GSEA revealed that CREB1 up-regulation was associated with chaperone mediated autophagy and Rho GTPase signaling; CAPZA2 up-regulation with ECM organization, TCA cycle, and oxidative phosphorylation; SLC2A3 down-regulation with glycosaminoglycan metabolism and intestinal immune network for IgA production.
**Clinical Implications:** This study identifies miR-106b-5p and miR-15a-5p in AH as promising non-invasive biomarkers for POAG diagnosis, especially when combined with their target genes (CAPZA2, CREB1, SLC2A3). The miRNA-mRNA network provides insights into POAG pathogenesis, highlighting pathways such as ECM remodeling, autophagy, and oxidative phosphorylation. These findings may facilitate early diagnosis and development of targeted therapies for POAG. Limitations include small sample size, lack of experimental validation (e.g., PCR, luciferase assays), and potential confounding by disease stage and medication use.