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Parkinson’s disease affects millions worldwide, yet doctors still lack reliable biomarkers that could help diagnose or track the condition. Researchers are increasingly turning to tiny messengers called extracellular vesicles, which are small particles released by nearly every cell in the body, as potential sources of these biomarkers.
Researchers at the Friedrich-Alexander-University explored differences in extracellular vesicles found in the blood of people with Parkinson’s disease compared to healthy individuals. Using advanced imaging with transmission electron microscopy, the team measured the size and characteristics of these vesicles. They also developed a computer algorithm in ImageJ to automate the analysis, making the process faster and more consistent.
EV finder: semi-automated ImageJ script to analyse TEM images and quantify EVs
A) Schematic overview and exemplary data flow (for details see suppl. data). After input of a folder containing TEM images, the script will identify maxima that in size and circularity represent EV particles. The identified areas will be transformed into ellipses and the area and location of each ellipse will be stored in a CVS.txt file. All images from the same folder will be analysed in a loop like manner. CVS like.txt files can then be opened with other programs for subsequent analyses. B Comparative analysis of serum derived EV using manual and EV finder-based analysis. Statistical analysis using One-way ANOVA with *** p < 0.001 and **** p < 0.0001. C Quantitative comparison of the mean diameter for the different groups and analysis tools. D Comparison of EV finder areas (red and yellow ellipses) and manually added circles and diameters (white circles and arrows). E Quotient between mean particle diameter from manual and EV finder determined EV mean diameter size
The researchers found that vesicles from Parkinson’s patients showed small but consistent size differences compared to those from healthy controls. While subtle, these findings are promising because even small variations in extracellular vesicles could eventually point to useful biomarkers. By refining tools for measurement and enrichment, this work takes a step toward better ways of diagnosing and monitoring Parkinson’s disease in the future.
