Background: Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by the accumulation of misfolded alpha-synuclein (α-Syn) and the subsequent loss of dopaminergic neurons. Identifying reliable and non-invasive biomarkers is crucial for accelerating early diagnosis and monitoring disease progression. To this aim, we longitudinally investigated α-Syn in salivary extracellular vesicles (SEVs) in PD patients and the correlation with clinical outcomes. Methods: SEVs were isolated from PD patients and healthy controls (HCs) saliva using differential ultracentrifugation followed by morphological and molecular characterization. The levels of both total (α-SynTot) and oligomeric (α-SynOlig) α-Syn were quantified by ELISA. Results: We found a significant increase in both α-SynTot and α-SynOlig in PD-derived SEVs compared to HCs, and receiver operating characteristic analysis revealed that α-SynOlig displayed higher sensitivity (65%) for discriminating PD from HCs compared to α-SynTot (59%). Moreover, α-SynOlig levels correlated negatively with Mini-Mental State Examination scores and were higher in patients with motor fluctuations. Finally, we found that α-SynOlig levels did not change after one-year follow-up in patients when also the clinical parameters remained unaltered. Conclusions: These results establish for the first time that SEVs-associated α-SynOlig is a promising, sensitive and non-invasive biomarker for PD diagnosis and clinical correlation studies, bearing higher sensitivity than α-SynTot. Moreover, α-SynOlig levels closely followed the clinical outcomes in PD patients. Finally, these findings strengthen the rationale for the further exploration of SEVs to disclose still unavailable accessible biomarkers for multiple neurological diseases.
Clinical Validation of α-Synuclein in Salivary Extracellular Vesicles as a Biomarker for Parkinson's Disease: A Longitudinal Study
Gurgone, AntoniaCo-first
;Cardinale, VitaCo-first
;Tangari, Marta M;Budicin, Serena;Comai, Debora;Ledda, Claudia;Lopiano, Leonardo;Camussi, Giovanni;Zibetti, Maurizio
Co-last
;Giustetto, Maurizio
Co-last
2026-01-01
Abstract
Background: Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by the accumulation of misfolded alpha-synuclein (α-Syn) and the subsequent loss of dopaminergic neurons. Identifying reliable and non-invasive biomarkers is crucial for accelerating early diagnosis and monitoring disease progression. To this aim, we longitudinally investigated α-Syn in salivary extracellular vesicles (SEVs) in PD patients and the correlation with clinical outcomes. Methods: SEVs were isolated from PD patients and healthy controls (HCs) saliva using differential ultracentrifugation followed by morphological and molecular characterization. The levels of both total (α-SynTot) and oligomeric (α-SynOlig) α-Syn were quantified by ELISA. Results: We found a significant increase in both α-SynTot and α-SynOlig in PD-derived SEVs compared to HCs, and receiver operating characteristic analysis revealed that α-SynOlig displayed higher sensitivity (65%) for discriminating PD from HCs compared to α-SynTot (59%). Moreover, α-SynOlig levels correlated negatively with Mini-Mental State Examination scores and were higher in patients with motor fluctuations. Finally, we found that α-SynOlig levels did not change after one-year follow-up in patients when also the clinical parameters remained unaltered. Conclusions: These results establish for the first time that SEVs-associated α-SynOlig is a promising, sensitive and non-invasive biomarker for PD diagnosis and clinical correlation studies, bearing higher sensitivity than α-SynTot. Moreover, α-SynOlig levels closely followed the clinical outcomes in PD patients. Finally, these findings strengthen the rationale for the further exploration of SEVs to disclose still unavailable accessible biomarkers for multiple neurological diseases.| File | Dimensione | Formato | |
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Euro J of Neurology - 2026 - Gurgone - Clinical Validation of ‐Synuclein in Salivary Extracellular Vesicles as a Biomarker.pdf
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