Proteomic Analysis of Urinary Microvesicles Reveal Biomarkers for Neurologic Disease

Background: Extracellular vesicles (EVs) harbor thousands of proteins that hold promise for biomarker development. Usually difficult to purify, EVs in urine are relatively easily obtained and have demonstrated efficacy for kidney disease prediction. Herein, we further characterize the proteome of urinary EVs to explore the potential for biomarkers unrelated to kidney dysfunction, focusing on Parkinson's disease (PD).   Methods: Using a quantitative mass spectrometry approach, we measured urinary EV proteins from a discovery cohort of 50 subjects. EVs in urine were classified into subgroups and EV proteins were ranked by abundance and variability over time. Enriched pathways and ontologies in stable EV proteins were identified and proteins that predict PD were further measured in a cohort of 108 subjects. Findings: Hundreds of commonly expressed urinary EV proteins with stable expression over time were distinguished from proteins expressed in few individual with high variability over time.  Bioinformatic analyses reveal a striking enrichment of endolysosomal proteins linked to Parkinson's, Alzheimer's, Huntington's disease, and other neurologic disorders. Tissue and biofluid enrichment analyses show broad representation of EVs from across the body without bias towards kidney or urine proteins. Among the proteins linked to neurological diseases, SNAP23 and calbindin were the most elevated in PD cases with 86% prediction success for disease diagnosis in the discovery cohort and 76% prediction success in the replication cohort.   Interpretation: Urinary EVs are an underutilized but highly accessible resource for biomarker discovery with particular promise for neurological diseases like PD.    Funding Statement: Research support was provided by NIH/NINDS U01 NS097028 and R01 NS064934. The authors acknowledge core resources provided by the UAB Comprehensive Cancer Center, UAB Institutional Core Funding Mechanism, and core resources made possible through NCI P30 CA013148. Declaration of Interests: The authors have no competing conflicts of interests to declare. Ethics Approval Statement: All protocols were approved by an institutional review board.