Exploring miRNA Associations Using a Biomarker Database: a Diabetic Retinopathy Sub-Analysis
Abstract
Abstract Objective: MicroRNAs are emerging as biomarkers for ophthalmic conditions, yet their distribution across diseases and confidence in their associations remain unevenly described. To evaluate miRNA biomarkers associated with eye diseases especially with diabetic retinopathy by ranking them according to confidence scores and by analyzing their disease-specific distributions. Material Method: A dataset of 43 unique biomarker entries related to eye diseases was analyzed. “Confidence” scores, originally presented as strings such as “10/11”, were converted to numeric values and biomarkers were ranked in descending order of confidence. Disease frequency was assessed to determine which ocular conditions are most extensively represented in biomarker studies. A subset focused on Diabetic Retinopathy and associated miRNAs. Results: The highest ranked miRNAs by confidence included hsa miR 210 3p, miR 21, miR 4667 5p, miR 3173 3p and miR 4490. Glaucoma was the most frequently studied disease, followed by DR and Diabetic Macular Edema. Within the DR subset (8 of 43 entries), eight distinct miRNAs were identified: miR 126 (2 occurrences), and miR 21, miR 211, miR 320a, hsa miR 495 3p, hsa miR 23a 3p, hsa miR 15a 5p and miRNA 126 each occurring once. Conclusion: The analysis highlights a small number of miRNAs with strong evidence linking them to eye diseases, particularly glaucoma and DR contexts. miR-126 emerges as the most frequently observed in DR. These findings underscore the need for more extensive biomarker profiling across less-studied ophthalmic diseases and more robust validation of candidate miRNAs.
Keywords
References
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Details
Primary Language
English
Subjects
Biological Network Analysis
Journal Section
Research Article
Authors
Publication Date
September 4, 2026
Submission Date
November 17, 2025
Acceptance Date
April 13, 2026
Published in Issue
Year 2026 Volume: 3 Number: 1