Objective: To characterize multi-domain progression over the course of Neuronal alpha-Synuclein Disease (NSD), in both treatment-naive and treated individuals.

Background: Neuronal alpha-Synuclein Disease (NSD), a proposed nomenclature to designate people with evidence of neuronal-predominant alpha-synuclein aggregation with or without symptoms, begins years prior to clinical diagnosis of Parkinson’s disease or Dementia with Lewy Bodies. Characterizing progression from early through late NSD is challenging due to symptom progression across multiple domains and variability in age of onset.

Method: Data were obtained from the Parkinson’s Progression Markers Initiative (PPMI) and restricted to individuals with NSD confirmed by positive CSF α‑synuclein SAA. We developed a data‑driven framework to construct multi‑dimensional disease‑progression curves spanning imaging, clinical, and biomarker domains. A key feature of our approach is that individual trajectories are explicitly modeled before and after treatment initiation. Using a functional‑data framework, we estimate subject‑specific smooth trajectories and their derivatives, apply functional linearization, and aggregate these into population‑level progression curves. We compare progression patterns between treatment‑naive and treated participants to explore treatment‑associated deviations from the underlying natural‑history trajectories.

Results: We applied a statistical framework that combines multimodal clinical, imaging, and biomarker measures into a unified NSD progression timeline, capturing both levels and rates of change in early and late disease. Dopamine transporter binding decreased prior to motor findings (MDS-UPDRS III) followed by motor-related functional impairment (MDS-UPDRS II). Distinct patterns of clinical and biological progression were observed between individuals with early and advanced disease. We observed heterogeneous treatment-associated deviations across imaging, clinical, and biomarker trajectories.

Conclusion: The proposed framework offers a principled way to integrate heterogeneous, multidomain measures into a unified disease progression timeline. Modeling trajectories before and after treatment initiation provides a foundation that could be extended to evaluate treatment-related deviations from natural history in future studies or clinical trials.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/novel-modeling-approach-for-comparing-treatment-naive-and-post-treatment-neuronal-synucleinopathy-progression-using-multi-modal-ppmi-data/