Differential gait features across Parkinson's disease clinical subtypes
- PMID: 39903964
- PMCID: PMC11847565
- DOI: 10.1016/j.clinbiomech.2025.106445
Differential gait features across Parkinson's disease clinical subtypes
Abstract
Background: Clinical subtypes in Parkinson's disease including non-motor manifestations may be more beneficial than subtypes based upon motor manifestations alone. Inclusion of gait metrics may help identity targets for rehabilitation and potentially predict development of non-motor symptoms for individuals with Parkinson's disease. This study aims to characterize gait differences across established multi-domain subtypes.
Methods: "Motor Only", "Psychiatric & Motor" and "Cognitive & Motor" clinical subtypes were established through motor, cognitive, and psychiatric assessment. Walking was assessed in the "OFF" medication state. Multivariate analysis of variance identified differences in gait domains across clinical subtypes.
Findings: The "Motor Only" subtype exhibited the fastest velocity, longest step length, and least timing variability (swing, step, stance), compared to "Psychiatric & Motor" and "Cognitive & Motor" subtypes. Stance time differed across subtypes; "Psychiatric & Motor" subtype had the longest stance time, followed by "Cognitive & Motor", then "Motor only". The "Psychiatric & Motor" group had different asymmetry from the "Cognitive & Motor" subtype, as "Psychiatric & Motor" walked with longer steps on their less-affected side while the "Cognitive & Motor" subtype displayed the opposite pattern. No differences were observed for swing time, step velocity variability, step length variability, width measures, or other asymmetry measures.
Interpretation: Cognitive and Psychiatric subtypes displayed worse gait performance than the "Motor only" group. Stance time and step length asymmetry were different between Psychiatric and Cognitive subtypes, indicating gait deficits may be related to distinct aspects of non-motor manifestations. Gait signatures may help clinicians distinguish between non-motor subtypes, guiding personalized treatment.
Keywords: Gait; Neuropsychology; Parkinson's disease; Walking.
Copyright © 2025 The Authors. Published by Elsevier Ltd.. All rights reserved.
Conflict of interest statement
Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Christina S. Lessov-Schlaggar, Baijayanta Maiti, Paul T. Kotzbauer, Joel S. Perlmutter, Gammon M. Earhart, Meghan C. Campbell reports financial support was provided by National Institute of Neurological Disorders and Stroke. Sidney T Baudendistel, Kerri S. Rawson, Joel S. Perlmutter, Gammon M. Earhart, Meghan C. Campbell reports financial support was provided by National Institute of Child Health and Human Development. Sidney T. Baudendistel reports administrative support was provided by National Institute of Child Health and Human Development National Center for Medical Rehabilitation Research. Joel S. Perlmutter reports financial support was provided by American Parkinson Disease Association. Joel S. Perlmutter reports financial support was provided by Saint Louis American Parkinson Disease Association. Joel S. Perlmutter reports financial support was provided by Oertli Fund. Joel S. Perlmutter reports financial support was provided by Paula & Rodger Riney Fund. Joel S. Perlmutter reports financial support was provided by Barnes Jewish Hospital Foundation (BJHF). If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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References
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- Amboni M, Iuppariello L, Iavarone A, Fasano A, Palladino R, Rucco R, Picillo M, Lista I, Varriale P, Vitale C, Cesarelli M, Sorrentino G, Barone P, 2018. Step length predicts executive dysfunction in Parkinson’s disease: a 3-year prospective study. J. Neurol. 265, 2211–2220. 10.1007/s00415-018-8973-x - DOI - PubMed
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