ArticleCell communication and signaling : CCS2025
Transmission Electron Microscopy-based characterization of Extracellular Vesicles from plasma and serum from Parkinson´s Disease patients.
Article in Cell communication and signaling : CCS, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Protocol for SEC-based isolation and characterization of human plasma-derived extracellular vesicles.STAR protocols · 2026Article
- Outer membrane vesicles secreted byInfection and immunity · 2026Article
- The recent progression of extracellular vesicles application in osteoporosis.Frontiers in pharmacology · 2026Review
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Authors and funding
8 authors.
Funding
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Abstract
Parkinson's disease is a neurodegenerative disorder with no curative treatment option and objective biomarker profile. Extracellular Vesicles (EVs) are membrane-enclosed biological nanoparticles released from all cells of the human body. In this pilot study we compare plasma- and serum-derived EVs from Parkinson's disease (PD) patients and healthy controls (HC) utilizing a precipitation-based method. Additionally, we employ an L1CAM antibody to selectively enrich for L1CAM-positive EVs from the total plasma-/serum-derived EV fractions. Successful EV enrichment was shown in western blot experiments for CD63 and for L1CAM as well as in metabolomic analysis for a HC sample. In a side-by-side quantification,. which we based on transmission electron microscopic images from negative stain samples, we identify small but significant differences between EV diameter from PD patients and HC. To streamline the quantification process, we introduce an ImageJ-based computer algorithm for (semi-)automated quantification of EVs from negative stain electron micrographs. We observe that this (semi-)automated quantification determines a smaller diameter than manual quantification. However, the difference between PD and HC group is systematic and reveals the same relative differences calculated from manually measured total plasma-derived EV particles. In this pilot study, we introduce a new workflow implemented into an ImageJ plugin enabling to determine differences in EV size within TEM images. For our data set of plasma-derived EVs from PD patients and HC, we find small, yet consistent differences. We feel that this study contributes to the search of a clinical biomarker for PD.
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