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Updated: Jul 8, 2026
Optimization of the Retinal Vein Occlusion Mouse Model to Limit Variability
Published on: August 6, 2021
Integrated Bioinformatics Analysis of a TF-miRNA-mRNA Regulatory Network in Retinal Vein Occlusion with Metabolic
Chunlan Liang1, Haixia Xie1, Qi Shi1
1Department of Ophthalmology, The First Affiliated Hospital of Jinan University, Guangzhou, China.
Purpose:
Metabolic syndrome (MetS) is a known risk factor for retinal vein occlusion (RVO); however, the molecular mechanisms linking their comorbidity and their relationship with previously established clinical predictors of RVO are not fully elucidated. This study aimed to identify a shared TF-miRNA-mRNA regulatory network in RVO and MetS, and to examine its correlation with key clinical predictors.
Methods:
Common genes for RVO and MetS were identified from CTD, GeneCards, DisGeNET, and the GEO dataset GSE98895. Functional enrichment, protein‑protein interaction (PPI), and TF-miRNA-mRNA network analyses were conducted. Key molecules were validated by qRT‑PCR in peripheral blood mononuclear cells from 21 subjects (7 with MetS-RVO, 7 with RVO only, and 7 controls). Spearman and Kendall correlation analyses were used to assess relationships between network components and clinical predictors (hypertension, BMI, HDL‑C, PDW, etc.).
Results:
Six overlapping genes (CHD7, IFNG, ABCA1, THBS1, PDGFRB, JUN) were enriched in pathways related to vascular remodeling, lipid metabolism, and inflammation. The regulatory network comprised 20 nodes and 28 edges. qRT‑PCR confirmed up‑regulation of hsa‑miR‑192‑5p and down‑regulation of ABCA1 in the MetS-RVO group. Correlation analysis revealed 27 significant associations (FDR < 0.05), with notable correlations between RELA and PDW (r = 0.759) and between RELA and HDL‑C (r = -0.688). HDL‑C was inversely correlated with several inflammatory markers (RELA, IFNG, STAT3).
Conclusion:
This study proposes a TF-miRNA-mRNA network associated with RVO-MetS comorbidity and offers molecular support for previously reported clinical predictors. ABCA1 and hsa‑miR‑192‑5p may serve as potential biomarkers. The limited sample size warrants cautious interpretation, and these findings provide a hypothesis‑generating foundation for future targeted investigations.
