Objective: To characterize autonomic dysfunction in early Parkinson’s disease (PD) in order to improve early PD diagnosis.

Background: Parkinson’s disease (PD) is a progressive neurodegenerative disorder associated with cardinal motor symptoms such as tremor, bradykinesia and rigidity [1]. However, non-motor symptoms, particularly autonomic dysfunction, can appear up to 10 years before motor symptom onset, offering a window for early detection [2]. Notably, approximate 71% of patients report experiencing autonomic dysfunction in the early stages of PD [3]. Autonomic dysfunction spans multiple domains, including cardiovascular, gastrointestinal, urinary, thermoregulatory, sexual, and pupillomotor systems. As a key non-motor symptom in PD, autonomic dysfunction shows potential as a diagnostic biomarker for identifying individuals at risk of developing PD.

Method: We conducted a retrospective analysis using data from the Parkinson’s Progression Markers Initiative (PPMI). We extracted autonomic dysfunction measures, including SCOPA-AUT scores, from the baseline PPMI study visit along with clinical demographics and motor outcomes via the Movement Disorders Society Unified Parkinson’s Disease Rating Scale. We addressed the imbalanced and skewed dataset by first applying a log transformation and then normalizing the dataset. We then applied Principal Component Analysis (PCA) followed by Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to identify distinct autonomic dysfunction profiles. A spider plot was generated to visualize and compare mean values across dysfunction domains.

Results: DBSCAN clustering identified four subgroups with distinct autonomic dysfunction profiles (see Figure 1). Cluster 0 displayed moderate dysfunction across most domains, with elevated sexual scores. Cluster 1 exhibited the most widespread dysfunction, with the highest scores in urinary, cardiovascular, thermoregulatory, and sexual domains. Cluster 2 had minimal dysfunction across all domains, suggesting a mild symptom profile. Cluster 3 showed elevated pupillomotor and thermoregulatory scores, with minimal sexual dysfunction.

Conclusion: We identified four distinct autonomic profiles in early PD. These profiles could provide valuable insights for earlier diagnosis and help predict the progression of the disease.

Figure 1 Spider Plot

References: [1] Postuma RB, Berg D, Stern M, et al. MDS clinical diagnostic criteria for Parkinson’s disease. Mov Disord. 2015;30(12):1591-1601. doi:10.1002/mds.26424

[2] Pont-Sunyer C, Hotter A, Gaig C, et al. The onset of nonmotor symptoms in Parkinson’s disease (the ONSET PD study). Mov Disord. 2015;30(2):229-237. doi:10.1002/mds.26077

[3] Stanković I, Petrović I, Pekmezović T, et al. Longitudinal assessment of autonomic dysfunction in early Parkinson’s disease. Parkinsonism Relat Disord. 2019;66:74-79. doi:10.1016/j.parkreldis.2019.07.008

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MDS Abstracts - https://www.mdsabstracts.org/abstract/characterization-of-autonomic-dysfunction-profiles-in-early-parkinsons-disease/