Integrated Bioinformatics and Explainable Machine Learning Analyses Reveal Mesenchymal Stem Cell Exosome-Related Biomarkers for Diabetic Retinopathy

Abstract

Purpose:

This study aims to identify potential biomarkers for diabetic retinopathy (DR) by focusing on genes associated with mesenchymal stem cell-derived exosomes (MSCs-Exo).

Methods:

By integrating DR transcriptome data with the protein dataset of MSCs-Exo, we utilized a comprehensive array of bioinformatics techniques, including weighted gene coexpression network analysis, Mfuzz clustering, and machine learning algorithms such as least absolute shrinkage and selection operator regression and random forest to pinpoint key genes. Functional mechanisms were explored through functional enrichment analysis, immune infiltration, and single-cell RNA sequencing. The immunohistochemistry and Western blotting were used for validation on DR mice models.

Results:

Our comprehensive analysis identified 16 hub genes associated with MSCs-Exo. Through the application of interpretable machine learning techniques, YBX1 and PSMA7 were further identified as central genes within this network. A predictive diagnostic model for DR was developed and validated using receiver operating characteristic curve analysis, which demonstrated modest diagnostic efficacy, as indicated by an area under the curve exceeding 0.7. Importantly, experimental validation showed that the protein expression levels of YBX1 and PSMA7 were significantly reduced in the retinal tissues of DR mice compared with the control group (P < 0.05). Functional enrichment analysis suggested that YBX1 and PSMA7 are involved in critical biological processes, specifically the regulation of protein and amino acid metabolism. In addition, immune infiltration results show that they are significantly associated with the immune dysregulation of DR, especially in CD4T memory cells. Single-cell analysis also supported the above finding.

Conclusion:

These findings suggest that YBX1 and PSMA7, derived from MSCs-Exo, may serve as potential biomarkers for DR. Further studies are needed to confirm their clinical utility and therapeutic relevance.