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Benchmarking blood collection tubes and processing intervals for extracellular vesicle performance metrics

The analysis of extracellular vesicles (EV) in blood samples is under intense investigation and holds the potential to deliver clinically meaningful biomarkers for health and disease. Technical variation must be minimized to confidently assess EV‐associated biomarkers, but the impact of pre‐analytic...

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Detalles Bibliográficos
Autores principales: Dhondt, Bert, Pinheiro, Cláudio, Geeurickx, Edward, Tulkens, Joeri, Vergauwen, Glenn, Van Der Pol, Edwin, Nieuwland, Rienk, Decock, Anneleen, Miinalainen, Ilkka, Rappu, Pekka, Schroth, Gary, Kuersten, Scott, Vandesompele, Jo, Mestdagh, Pieter, Lumen, Nicolaas, De Wever, Olivier, Hendrix, An
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196222/
https://www.ncbi.nlm.nih.gov/pubmed/37202906
http://dx.doi.org/10.1002/jev2.12315
Descripción
Sumario:The analysis of extracellular vesicles (EV) in blood samples is under intense investigation and holds the potential to deliver clinically meaningful biomarkers for health and disease. Technical variation must be minimized to confidently assess EV‐associated biomarkers, but the impact of pre‐analytics on EV characteristics in blood samples remains minimally explored. We present the results from the first large‐scale EV Blood Benchmarking (EVBB) study in which we systematically compared 11 blood collection tubes (BCT; six preservation and five non‐preservation) and three blood processing intervals (BPI; 1, 8 and 72 h) on defined performance metrics (n = 9). The EVBB study identifies a significant impact of multiple BCT and BPI on a diverse set of metrics reflecting blood sample quality, ex‐vivo generation of blood‐cell derived EV, EV recovery and EV‐associated molecular signatures. The results assist the informed selection of the optimal BCT and BPI for EV analysis. The proposed metrics serve as a framework to guide future research on pre‐analytics and further support methodological standardization of EV studies.