Temporal Dynamics of Urinary Extracellular Vesicle Excretion and Cargo in Healthy Subjects over 24 Hours

Abstract

Urinary extracellular vesicles (uEVs) are promising non-invasive biomarkers of renal physiology and pathology, yet little is known about their temporal excretion patterns or optimal normalization strategies as urine concentrations vary significantly during the day. In this basic physiology study, we used a uniquely designed processing protocol of urine collection to characterize the variation of uEV excretion and cargo throughout a 24 hour period in healthy subjects. Thirteen healthy adults collected every individual void over 24 hours and these voids were independently analyzed along with a composite sample intended to recreate a 24 hour collection sample. uEVs were enriched by low-speed centrifugation with three low-ionic-strength washes to minimize uromodulin contamination. Size, concentration, morphology and cargo of uEVs were characterized with nanoparticle tracking analysis, cryo-electron microscopy, immunoblotting and single EV flow cytometry. We observed a stable urine creatinine excretion into the urine over the day. uEV concentrations varied up to 100-fold across the day between individuals with a decreasing trend over time with the result close to reaching statistical significance (p=0.06). uEV concentration was positively associated with urine creatinine, specific gravity, and TSG101, an EV marker. The association between urine flow and uEV excretion varied across the day. Most tested uEV cargo markers exhibited substantial within individual variation over the day without consistent trends in our healthy cohort. When grouped into predefined time periods to visualize temporal patterns, a transient dip at noon was observed, followed by a significant increase in the subsequent period, consistent with a pattern previously reported. These findings offer foundational insights into uEV excretion patterns over the course of a day in a healthy cohort and emphasize key methodological considerations essential for advancing uEV biomarker research.