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March 30, 2021
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Extracellular vesicles in CSF show promise as diagnostic tool for Parkinson’s disease

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The total and aggregated numbers of alpha-synuclein-positive extracellular vesicles in cerebrospinal fluid successfully identified Parkinson’s disease in a cross-sectional, multicenter study that used nanoscale flow cytometry assays.

The results indicated that these types of extracellular vesicles in CSF represent “a helpful tool” for diagnosing PD, according to the researchers.

Brain illustration
Extracellular vesicles in cerebrospinal fluid successfully identified Parkinson’s disease in a cross-sectional, multicenter study. Source: Adobe Stock

“[PD] is frequently misdiagnosed, particularly during early stages. Because usage of neuroimaging measurements (the most accurate markers available) is limited by relatively high cost and poor accessibility, simple, accurate and reliable biochemical markers are urgently needed,” the researchers wrote. “Extracellular vesicles (EVs), including exosomes and microvesicles, are membrane-bound vesicles important in cell-to-cell communication and signaling. EVs and their cargo, which include lipids, proteins (eg, alpha-synuclein) and nucleic acids, are thought to play critical roles in normal central nervous system function and neurological disorders, including PD and have been suggested as an ideal source of biomarkers for PD and other neurodegenerative diseases.”

Zhen Hong, MD, PhD, of the department of pathology at the University of Washington School of Medicine and the department of neurology at West China Medical School, Sichuan University, and colleagues aimed to develop “a reliable and fast” assay capable of calculating the number of alpha-synuclein-containing EVs in CSF and to determine their value in diagnosing PD. The researchers conducted a cross-sectional, multicenter study that included 170 patients with PD and 131 healthy controls with comparable age and sex distributions. They determined the number of CSF EVs carrying alpha-synuclein or aggregated alpha-synuclein with antibodies against total or aggregated alpha-synuclein and “highly specific, sensitive and rapid assays” based on nanoscale flow cytometry technology.

The results showed no significant differences in the number of or size distribution of total EVs in CSF in patients with PD compared with controls. However, Hong and colleagues found that the numbers of both total alpha-synuclein-positive and aggregated alpha-synuclein-positive EV subpopulations among all detected CSF EVs were significantly lower in patients with PD compared with controls (P < .0001). While each EV subpopulation

demonstrated greater diagnostic sensitivity and specificity than total CSF alpha-synuclein when measured with an immunoassay, a combination of the two EV subpopulations resulted in diagnostic accuracy that reached clinical relevance (area under the curve = 0.819; sensitivity = 80%; specificity = 71%).

Immunoassay measures of alpha-synuclein as PD biomarkers “have been largely disappointing,” according to the researchers, noting a few exceptions that measure CSF alpha-synuclein oligomers/aggregates — or “seeds” — that can promote synthetic alpha-synuclein monomers to aggregate in vitro and have shown high sensitivity and specificity to distinguish patients with PD from controls.

“Measuring CSF aggregated [alpha-synuclein]-carrying EVs in our study also showed promising results, suggesting the potential of alpha-synuclein oligomers/aggregates, which may represent more pathologically relevant disease isoforms, as PD biomarkers,” Hong and colleagues wrote.

They also noted that their assay “rapidly” calculated alpha-synuclein-carrying EVs in CSF and compared that timeframe with the “days” other immunoassay measures may take to provide results.

“If the performance on PD diagnosis and differential diagnosis can be improved/confirmed and validated in further independent studies, our assay could be useful to improve diagnostic accuracy of PD in clinical practice and to increase power and reduce costs in clinical trials by lowering the misclassification rate during subject recruitment,” Hong and colleagues wrote.