Normalization of urinary extracellular vesicles

Background: Urinary extracellular vesicles (uEVs) have emerged as a powerful non-invasive tool to study renal epithelial transport in humans. However, the optimal method to quantify and normalize uEVs remains unclear, especially for spot urines. Methods: Four healthy subjects were subjected to overn...

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Bibliographic Details
Published in:Journal of extracellular vesicles 2018-01, Vol.7, p.145-145
Main Authors: Blijdorp, Charles J, Hartjes, Thomas A, van Royen, Martin E, Jenster, Guido W, Zietse, Robert, Hoorn, Ewout J
Format: Article
Language:English
Subjects:
Bias
CD63 antigen
CD81 antigen
CD9 antigen
Creatinine
Excretion
Extracellular vesicles
Immobilization
Immunoblotting
Nanoparticles
Proteins
Ultracentrifugation
Urine
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Summary:Background: Urinary extracellular vesicles (uEVs) have emerged as a powerful non-invasive tool to study renal epithelial transport in humans. However, the optimal method to quantify and normalize uEVs remains unclear, especially for spot urines. Methods: Four healthy subjects were subjected to overnight thirsting (10 pm-noon) followed by water loading (20 ml/kg in 30 min). Spot urines were collected during thirsting (T1-2) and after water loading (WL1-4, noon-7 pm). Subsequently, 4 uEV quantification techniques were compared: (1) nanoparticle tracking analysis (NTA), (2) uEV isolation by ultracentrifugation followed by immunoblotting of CD9, CD63, CD81, ALIX, and TSG101, (3) a timeresolved fluorescence immunoassay (TRFIA) that captures CD9+ uEVs, and (4) EVQuant, a novel technique which counts individual fluorescently labeled EVs after immobilization in a matrix. A Bland-Altman analysis was used to compare methods using NTA as reference. Methods: As expected, urine osmolality was near-maximal during thirsting, decreased after water loading and then increased again. The results of the 4 uEV quantification methods showed similar dynamics as urine osmolality suggesting that uEV number changes in proportion to urinary concentration. Of interest, EVQuant identified 2.4 ± 0.5 times more uEVs than NTA. Using NTA as reference, the Bland-Altman analysis showed that EVQuant had the best agreement (SD of bias 16%) followed by TRFIA (SD of bias 22%). Of the uEV-markers, CD9 agreed best with NTA (SD of bias 28%). uEV number correlated strongly with urine creatinine (R2 0.9, P
ISSN:2001-3078