Extracellular Vesicle Surface Markers as a Diagnostic Tool in Transient Ischemic Attacks

Area of Science:

• Neuroscience
• Biomarker Discovery
• Vascular Neurology

Background:

• Extracellular vesicles (EVs) are emerging biomarkers for neurological conditions.
• Systematic evaluation of EVs in transient ischemic attack (TIA) diagnosis is lacking.

Purpose of the Study:

• Investigate EV-surface antigen profiles in patients with TIA-suspicious symptoms.
• Develop and validate a predictive model for TIA diagnosis using EV-surface antigens.

Main Methods:

• Analyzed serum EVs from TIA-suspicious patients and healthy controls.
• Quantified EVs using nanoparticle tracking analysis and characterized surface antigens via multiplex flow cytometry.
• Developed a predictive model using a random forest algorithm.

Main Results:

• Increased EV concentration observed in patients with high likelihood of TIA.
• Identified specific EV-surface antigens (e.g., CD8, CD31) as discriminants.
• Achieved 96% accuracy in the training cohort and 78.9% in the validation cohort for TIA prediction.

Conclusions:

• Distinct EV-surface antigen profiles differentiate TIA patients from controls.
• An EV-based algorithm shows potential for aiding TIA recognition.