Urinary extracellular vesicle miRNA signature reflects pancreatic islet stress in type 2 diabetes

Introduction: Type 2 diabetes (T2D) is a progressive metabolic disorder characterized by insulin resistance and progressive β-cell dysfunction. Early detection remains critical to prevent long-term complications. Urinary extracellular vesicle (ECV) microRNAs (miRNAs) have emerged as stable, non-invasive biomarkers with the potential to reflect systemic molecular alterations associated with metabolic disease. Methods: We analyzed previously generated urinary ECV miRNA sequencing data from a well-characterized cohort of 68 adults (40 T2D and 28 healthy controls). Differentially expressed miRNAs were identified and evaluated for diagnostic performance using receiver operating characteristic (ROC) analysis and supervised machine learning models with 10-fold cross-validation. Independent external validation was performed to assess generalizability. Cross-tissue validation was conducted using publicly available datasets from pancreatic islets, blood, liver, and adipose tissue. Predicted target genes were examined across tissues, and miRNA–mRNA interaction networks with pathway enrichment analyses were performed to explore functional relevance. Results: Forty-six miRNAs were significantly dysregulated in urinary ECVs from T2D patients compared with controls. Network bottleneck centrality analysis prioritized five key miRNAs (miR-320a, miR-16-5p, miR-125b-5p, miR-26a-5p, and miR-30c-5p). Individual miRNAs demonstrated moderate discriminatory capacity (AUC 0.73–0.81), while the combined panel improved performance (internal AUC = 0.87; external AUC = 0.86). Dysregulated urinary miRNA patterns partially mirrored expression changes in pancreatic islets and other metabolic tissues. Target gene analysis revealed tissue-specific alterations in key metabolic regulators, including PTEN, IGF1R, HMGA1, VEGFA, MCL1, CCND2, BTG2, and SMAD4. Conclusion: Urinary ECV miRNAs reflect molecular alterations associated with T2D and represent promising complementary, non-invasive biomarkers with mechanistic relevance to disease progression.