Non-motor symptom subtypes in early Parkinson's disease.

Abstract

Background: Parkinson's disease (PD) is a clinically heterogeneous disorder characterized by a broad spectrum of non-motor symptoms. Defining non-motor subtypes may help clarify early pathophysiological mechanisms, predict disease progression, and guide personalized care.

Objective: To identify non-motor PD subtypes through an unsupervised approach, evaluate their consistency with proposed models of PD pathology, and assess their prognostic value.

Methods: Data from 824 newly diagnosed, drug-naïve PD patients enrolled in the Parkinson's Progression Markers Initiative were analyzed. Five core non-motor features at baseline-REM sleep behavior disorder (RBD), hyposmia, dysautonomia, anxiety, and cognitive impairment-were used for two-step cluster analysis. Cluster-wise progression to Hoehn and Yahr stage 3, motor complications, and dementia was assessed using Kaplan-Meier and Cox regression analyses.

Results: Three non-motor clusters emerged. Cluster 1 (RBD-/hyposmia+, n = 474) included patients with mild anxiety and selective cognitive deficits. Cluster 2 (RBD+, n = 219) exhibited the greatest non-motor burden, including dysautonomia, psychiatric symptoms, and global cognitive impairment. These patients were older at diagnosis and showed more symmetric and axial motor signs, faster progression to Hoehn and Yahr stage 3, and a higher risk of dementia. Cluster 3 (RBD-/hyposmia-, n = 131) displayed minimal non-motor involvement. No differences were found in time to motor complications across clusters.

Conclusions: This is the first study to identify PD subtypes based exclusively on early non-motor symptoms in a large, untreated cohort. The resulting data-driven clusters aligned with some proposed models of PD pathology and demonstrated clear, independent prognostic value for progression to Hoehn and Yahr stage 3 and dementia risk.