Brain‐derived extracellular vesicles: Potential diagnostic biomarkers for central nervous system diseases
Open accessAbstract
Extracellular vesicles (EVs) are membrane‐enclosed nanovesicles secreted by cells into the extracellular space and contain functional biomolecules, e.g. signaling receptors, bioactive lipids, nucleic acids, and proteins, which can serve as biomarkers. Neurons and glial cells secrete EVs, contributing to various physiological and pathological aspects of brain diseases. EVs confer their role in the bidirectional crosstalk between the central nervous system (CNS) and the periphery owing to their distinctive ability to cross the unique blood–brain barrier (BBB). Thus, EVs in the blood, cerebrospinal fluid (CSF), and urine can be intriguing biomarkers, enabling the minimally invasive diagnosis of CNS diseases. Although there has been an enormous interest in evaluating EVs as promising biomarkers, the lack of ultra‐sensitive approaches for isolating and detecting brain‐derived EVs (BDEVs) has hindered the development of efficient biomarkers. This review presents the recent salient findings of exosomal biomarkers, focusing on brain disorders. We summarize highly sensitive sensors for EV detection and state‐of‐the‐art methods for single EV detection. Finally, the prospect of developing advanced EV analysis approaches for the non‐invasive diagnosis of brain diseases is presented.
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EVs are naturally occurring nanoscale entities that can cross the BBB.
“These naturally occurring nanoscale entities can cross the BBB and have the inherent capability to transport a wide array of therapeutic and diagnostic agents [118].”
From Extracellular vesicles as nanotheranostic platforms for targeted neurological disorder interventions (2024) · cites this paper as [118]
EVs have the inherent capability to transport a wide array of therapeutic and diagnostic agents.
“These naturally occurring nanoscale entities can cross the BBB and have the inherent capability to transport a wide array of therapeutic and diagnostic agents [118].”
From Extracellular vesicles as nanotheranostic platforms for targeted neurological disorder interventions (2024) · cites this paper as [118]
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- Authors
- Xu, X., Iqbal, Z., Xu, L., Wen, C., Duan, L., Xia, J., Yang, N., Zhang, Y., & Liang, Y.
- Affiliations
- Affiliated Hospital of Jining Medical University (CN)
- Shenzhen University (CN)
- Chinese University of Hong Kong (HK)
- Lake Erie College of Osteopathic Medicine (US)
- Corresponding author
- Zhang, Yuanmin
- Liang, Yujie
- ORCID
- Venue
- Psychiatry and Clinical Neurosciences
- Publisher
- Wiley
- Published
- 2023-11-14
- Volume
- 78
- Issue
- 2
- Pages
- 83-96
- ISSN
- 1323-1316 (ISSN-L)
- 1440-1819
- OpenAlex
- W4387931644
- Cited by
- 68
- References
- 110
- Citations by year
- 2026: 22 · 2025: 23 · 2024: 23
- FWCI
- 1.80
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Psychiatry and Clinical Neurosciences (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Basic and Applied Basic Research Foundation of Guangdong Province (2023A1515011936)
- Natural Science Foundation of Shandong Province (ZR2019MH100, ZR2023QH148)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Extracellular vesicles in disease
- Physical Sciences › Materials Science › Biomaterials › Nanoparticle-Based Drug Delivery
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Cellular transport and secretion
- Keywords
- brain-derived extracellular vesicles, exosomes, diagnostic biomarkers, central nervous system disorders, blood-brain barrier, cerebrospinal fluid, urinary biomarkers, non-invasive diagnosis, neurodegenerative diseases, neuroinflammation
- MeSH terms
- Extracellular Vesicles, Brain, Brain Diseases, Central Nervous System Diseases, Humans, Biomarkers
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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