ArticleMolecular neurobiology2025
Neurofilament Light Chain from Neuronally Derived Extracellular Vesicles in Differentiating Parkinson's Disease from Essential Tremor with Resting Tremor.
Article in Molecular neurobiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Parkinson's disease (PD) and essential tremor with resting tremor (rET) show a remarkable symptom overlap that complicates the clinical differentiation and highlights the need for easily assessable diagnostic biomarkers. Neuronally derived extracellular vesicles (NDEVs) have been suggested as a peripheral substrate providing insights on the central nervous system pathology. Here, we assessed the accuracy of NDEV neurofilament light chain (Nf-L) levels in discriminating between PD and rET patients. Thirty-three PD and 13 rET patients and 30 healthy controls (HC) were consecutively enrolled in the study. NDEVs were obtained from serum through size exclusion chromatography followed by immunocapture based on L1CAM expression. NDEV Nf-L levels were quantified by ELISA on Ella Platform. Receiver operator characteristic (ROC) analysis was performed to investigate the NDEV Nf-L classification performance. Associations between NDEV Nf-L and demographical or clinical variables were investigated with Spearman's method. NDEV Nf-L levels were significantly higher in PD compared to rET patients and HC, and achieved an excellent classification performance in distinguishing PD from both rET and HC (AUC: 0.902 and 0.987, respectively). No differences were observed between rET and HC. A significant negative association between NDEV Nf-L and sex was detected in rET patients. Our pilot study suggests that NDEV Nf-L might be a useful blood-derived biomarker helping the differential diagnosis between PD and rET patients. Future studies are needed to validate these findings in larger independent cohorts.
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