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Staging Disease Progression from Prodromal to Overt Stage of Alpha-synucleinopathies

D. Arnaldi, M. Roascio, E. Antelmi, F. Biscarini, L. Baldelli, V. Brunetti, E. Capriglia, E. Casaglia, A. Castelnuovo, G. Della Marca, L. Ferini-Strambi, R. Ferri, M. Figorilli, A. Galbiati, B. Guarnieri, D. Hoxhaj, F. Di Laudo, C. Liguori, S. Marelli, P. Mattioli, M. Mulas, B. Orso, M. Pardini, F. Pizza, F. Placidi, G. Plazzi, F. Provini, L. Sambati, M. Puligheddu, G. Arnulfo (Genova, Italy)

Meeting: 2025 International Congress

Keywords: Electroencephalogram(EEG), Parkinson’s, Presynaptic dopaminergic system

Category: Parkinson's disease: Biomarkers (non-Neuroimaging)

Objective: To compute a disease progression model of the prodromal to overt synucleinopathy continuum, usable at single subject level.

Background: Progression milestones to stage patients along the synucleinopathy continuum are needed.

Method: Longitudinal cognitive and motor scores of isolated REM sleep behavior disorder (iRBD) patients were extracted from (i) FarPReSto (N=322, https://clinicaltrials.gov/study/NCT05262543) and (ii) Parkinson’s Progression Markers Initiative (N=112, https://www.ppmi-info.org). Ninety-four iRBD patients developed parkinsonism/dementia over time. A Disease Course Mapping (DCM) model was trained on clinical scores on a learning set (N=378; 68.7±6.63 yo; 79% males) and tested  on a blind set (N=50; 68.77±7.26 yo; 86% males) to estimate individual parameters (acceleration factor ɑ, time-shift τ, [DA1] and inter-marker spacing ⍵) and these parameters were then used to predict phenoconversion (Support Vector Machine). The blind set also included baseline dopamine transporter SPECT (DaT-SPECT), as a biomarker of dopaminergic nigro-striatal function, and high-density EEG (hdEEG), as a biomarker of cortical function. DaT-SPECT and hdEEG data were correlated with DCM parameters using Spearman’s rank correlation coefficient (Benjamini–Hochberg with ɑ=5%).

Results: Converter iRBD patients showed faster and an earlier onset of clinical dysfunctions than non-converter patients (pα=0.045 and pτ[DA1] =0.0002, Wilcoxon test, BH corrected). DCM model individual parameters predicted phenoconversion with an accuracy of 78% (f1-score: 78%, specificity: 72%, sensitivity: 79%). Lower DaT levels correlated with worse clinical performances (𝜌DaT,⍵=-0.44, p=0.04). Earlier onset of motor dysfunctions (𝜌wpli,⍵=-0.38, p=0.02) was related to higher synchronization in theta band. Hyperexcitability in theta band (𝜌fEI,ɑ=0.35, p=0.01, BH uncorrected) tended to correlate with faster disease progression.

Conclusion: The DCM model, trained on a large dataset of prodromal to overt alpha-synucleinopathy patients, provided individual progression parameters that correctly predicted phenoconversion with 78% accuracy. These parameters were significantly correlated with both dopaminergic nigro-striatal and cortical functions, and they could be used at single subject level to stage progression in the alpha-synucleinopathy continuum.

To cite this abstract in AMA style:

D. Arnaldi, M. Roascio, E. Antelmi, F. Biscarini, L. Baldelli, V. Brunetti, E. Capriglia, E. Casaglia, A. Castelnuovo, G. Della Marca, L. Ferini-Strambi, R. Ferri, M. Figorilli, A. Galbiati, B. Guarnieri, D. Hoxhaj, F. Di Laudo, C. Liguori, S. Marelli, P. Mattioli, M. Mulas, B. Orso, M. Pardini, F. Pizza, F. Placidi, G. Plazzi, F. Provini, L. Sambati, M. Puligheddu, G. Arnulfo. Staging Disease Progression from Prodromal to Overt Stage of Alpha-synucleinopathies [abstract]. Mov Disord. 2025; 40 (suppl 1). https://www.mdsabstracts.org/abstract/staging-disease-progression-from-prodromal-to-overt-stage-of-alpha-synucleinopathies/. Accessed October 5, 2025.
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MDS Abstracts - https://www.mdsabstracts.org/abstract/staging-disease-progression-from-prodromal-to-overt-stage-of-alpha-synucleinopathies/

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