Urinary Extracellular Vesicle Metabolomic Profiling Reveals a Distinct Molecular Signature for the Non-Invasive Diagnosis of Lupus Nephritis

Background: Lupus nephritis (LN) is a severe complication of systemic lupus erythematosus (SLE), underscoring an urgent need for non-invasive diagnostic biomarkers. 
Objective: This study aimed to define the metabolomic signature of urinary extracellular vesicles (uEVs) in LN and to identify novel biomarkers for precision diagnosis.
Methods: We isolated uEVs from 29 patients with LN, 22 SLE patients without nephritis, and 20 healthy controls. uEVs were characterized according to MISEV guidelines, and their metabolomes were profiled using untargeted liquid chromatography–tandem mass spectrometry (LC–MS/MS). Differential metabolites were analyzed through bioinformatics and a random forest machine-learning algorithm to construct a diagnostic model. 
Results: Among 897 identified metabolites, 284 were significantly dysregulated in LN. A random forest model prioritized a ten-metabolite panel. Three metabolites—Glucosylsphingosine, PE-NMe, and PC(20:5/TXB2)—exhibited outstanding diagnostic performance, with area under the curve (AUC) values of 0.912, 0.906, and 0.897, respectively, for distinguishing LN from non-renal SLE. 
Conclusion: We identified a distinct uEV metabolic signature in LN and developed a robust, non-invasive biomarker panel. This strategy holds significant promise for the early detection and personalized management of LN, offering a compelling alternative to invasive renal biopsy.