A 3-miRNA Risk Scoring Signature in Early Diabetic Retinopathy

Abstract

Purpose: The aim of our study was to investigate a comprehensive profile of streptozotocin (STZ)-induced early diabetic retinopathy (DR) mice to identify a risk scoring signature based on micorRNAs (miRNAs) for early DR diagnosis. Methods: RNA sequencing was performed to obtain the gene expression profile of retinal pigment epithelium (RPE) in early STZ-induced mice. Differentially expressed genes (DEGs) were determined with log2|fold change (FC)| > 1 and p value < 0.05. Functional analysis was carried out based on gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and the protein–protein interaction (PPI) network. We predicted the potential miRNAs via online tools and ROC curves were then conducted. Three potential miRNAs with AUC > 0.7 were explored via public datasets and a formula was further established to evaluate DR severity. Results: In total, 298 DEGs (200 up-regulating and 98 down-regulating) were obtained through RNA sequencing. Hsa-miR-26a-5p, hsa-miR-129-2-3p and hsa-miR-217 were three predicted miRNAs with AUC > 0.7, suggesting their potential to distinguish healthy controls from early DR. The formula of DR severity score = 19.257 − 0.004 × hsa-miR-217 + 5.09 × 10−5 × hsa-miR-26a-5p − 0.003 × hsa-miR-129-2-3p was established based on regression analysis. Conclusions: In the present study, we investigated the candidate genes and molecular mechanisms based on RPE sequencing in early DR mice models. Hsa-miR-26a-5p, hsa-miR-129-2-3p and hsa-miR-217 could work as biomarkers for early DR diagnosis and DR severity prediction, which was beneficial for DR early intervention and treatment.