Urinary Extracellular Vesicles as Molecular Fingerprints of Kidney Injury and Disease Progression

Abstract

Urinary extracellular vesicles (uEVs) have emerged as promising non-invasive indicators of kidney injury and disease progression because they carry proteins, nucleic acids, lipids, metabolites, and signaling molecules derived from renal and urinary tract cells. Their molecular composition can reflect pathological alterations across glomerular, tubular, inflammatory, metabolic, and fibrotic pathways, supporting their potential use as dynamic molecular fingerprints of renal disease. This review examines the biological origin, molecular cargo, disease-associated alterations, and translational relevance of uEVs across acute kidney injury, chronic kidney disease, diabetic kidney disease, glomerular disorders, rare renal diseases, and kidney transplantation. Current evidence suggests that uEV-based signatures may support early detection, disease stratification, prognostic assessment, and longitudinal monitoring of renal dysfunction. Advances in proteomics, transcriptomics, metabolomics, mass spectrometry, Raman spectroscopy, and machine learning have further improved the characterization of multidimensional uEV profiles. However, variability in urine collection, vesicle isolation, normalization, analytical platforms, and biomarker validation continues to limit clinical implementation. Standardized workflows, larger multicenter cohorts, longitudinal validation, and integration of multi-omics data with clinical and histopathological findings are therefore required. Overall, uEV molecular fingerprinting represents a promising strategy for precision nephrology and for improving non-invasive assessment of kidney injury and disease progression.