Brain-Derived Extracellular Vesicle Subpopulations: from Bulk Measurements to Single-Entity Assays.
Brain-Derived Extracellular Vesicle Subpopulations: from Bulk Measurements to Single-Entity Assays.
Where did the research take place?
The study site has not been established. Author addresses may differ from where the research occurred.
Hong Kong, HK · Author affiliation
Department of Biomedical Engineering, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China.Location evidence
Shanghai, CN · Author affiliation
Institute of Translational Medicine, Shanghai University, Shanghai 200444, China.Location evidence
Jinan, CN · Author affiliation
Institute of Brain Science and Brain-Inspired Research, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 250000, China.Location evidence
CN · Author affiliation · country only
State Key Laboratory of Biomedical Imaging Science and Systems, Suzhou 215163, China.Location evidence
Shantou, CN · Author affiliation
Hospital of Stomatology, Shantou University Medical College, Shantou 515041, China.Location evidence
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Original abstract
Neurodegenerative diseases (NDs), such as Alzheimer's disease (AD) and Parkinson's disease (PD), pose a significant global health challenge, currently affecting over 40 million individuals and placing a heavy burden on healthcare systems. Existing diagnostic methods, such as neuroimaging and cognitive assessments, often lack sufficient sensitivity and specificity, especially in the early stages of disease. This underscores the need for novel biomarkers. Extracellular vesicles (EVs), particularly those derived from the brain, i.e., brain-derived extracellular vesicles (BDEVs), hold great potential as noninvasive diagnostic tools due to their ability to reflect the physiological and pathological states of their cells of origin. However, isolation and detection of such EV subpopulations from accessible body fluids such as blood remain a technical challenge due to their low abundance and overlapping physical properties compared to other EVs. This review discusses rationally designed isolation and detection technologies for EVs from major brain cell subpopulations and their integration with emerging fields like AI and big data analysis. We specifically contrast traditional ensemble-averaged bulk measurements with emerging single-entity assays, highlighting how the latter bypass biological noise to resolve rare BDEV subpopulations. It highlights the potential of these EV subpopulations as biomarkers, addresses EV isolation challenges and proposes standardized methodologies, and emphasizes the need for comprehensive profiling of EV markers at single-entity level, and point-of-care testing (POCT) development.