Proteomic analysis of plasma-derived extracellular vesicles: Insights into acute stroke pathophysiology

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Institut Català de la Salut

[Reymond S, Gruaz L, Sanchez JC] Department of Medicine, University of Geneva, Geneva, Switzerland. [Schvartz D] Bioinformatic Support Platform, Faculty of Medicine, University of Geneva, Geneva, Switzerland. [Penalba A] Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain. Universitat Autònoma de Barcelona, Barcelona, Spain. [Montaner J] Vall d’Hebron Institut de Recerca (VHIR), Barcelona, Spain. Universitat Autònoma de Barcelona, Barcelona, Spain. Institute de Biomedicine of Seville (IBiS), Hospital Universitario Virgen del Rocío, CSIC, Universidad de Sevilla, Sevilla, Spain. Department of Neurology, Hospital Universitario Virgen Macarena, Sevilla, Spain

Vall d'Hebron Barcelona Hospital Campus

Data de publicació

2025-08-25T09:25:43Z

2025-08-25T09:25:43Z

2025-08-15



Resum

Extracellular vesicles; Proteomics; Stroke


Vesículas extracelulares; Proteómica; Ictus


Vesícules extracel·lulars; Proteòmica; Ictus


Managing acute stroke is challenging and requires the differentiation of stroke subtypes while excluding stroke mimics. Understanding the biological processes underlying the different stroke subtypes could help improve acute stroke care and patient outcomes. Plasma-derived extracellular vesicles (EVs) have emerged as promising tools for investigating these processes through their unique cargo. Therefore, we aimed at exploring the protein content of plasma-derived EVs in a cohort composed of patients with hemorrhagic stroke (n = 10), ischemic stroke with large-vessel occlusion (LVO) (n = 10) and without LVO (n = 10), transient ischemic attack (n = 10), stroke mimics (n = 10) and healthy controls (n = 10). EVs were isolated by size exclusion chromatography from 150 μL of plasma. Characterization was performed by transmission electron microscopy, western blotting and nanoparticle tracking analysis, and confirmed an efficient EV enrichment. Proteomics analysis was conducted using data-independent acquisition mass spectrometry and a supervised partial least squares discriminant analysis (PLS-DA) model was applied on proteomics data. The PLS-DA model successfully distinguished healthy controls, severe stroke subtypes (LVO ischemic and hemorrhagic stroke), and non LVO ischemic stroke, identifying key proteins influencing these patterns. These findings suggest that EVs and their protein cargo may play a role in critical processes like inflammation and coagulation in acute stroke pathology.

Tipus de document

Article


Versió publicada

Llengua

Anglès

Publicat per

Elsevier

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Attribution 4.0 International

http://creativecommons.org/licenses/by/4.0/

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