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Translational methods to detect asymmetries in temporal and spatial walking metrics in parkinsonian mouse models and human subjects with Parkinson’s disease

Clinical signs in Parkinson’s disease (PD), including parkinsonian gait, are often asymmetric, but mechanisms underlying gait asymmetries in PD remain poorly understood. A translational toolkit, a set of standardized measures to capture gait asymmetries in relevant mouse models and patients, would g...

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Autores principales: Broom, Lauren, Worley, Audrey, Gao, Fay, Hernandez, Laura D., Ashton, Christine E., Shih, Ludy C., VanderHorst, Veronique G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6385183/
https://www.ncbi.nlm.nih.gov/pubmed/30792396
http://dx.doi.org/10.1038/s41598-019-38623-6
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author Broom, Lauren
Worley, Audrey
Gao, Fay
Hernandez, Laura D.
Ashton, Christine E.
Shih, Ludy C.
VanderHorst, Veronique G.
author_facet Broom, Lauren
Worley, Audrey
Gao, Fay
Hernandez, Laura D.
Ashton, Christine E.
Shih, Ludy C.
VanderHorst, Veronique G.
author_sort Broom, Lauren
collection PubMed
description Clinical signs in Parkinson’s disease (PD), including parkinsonian gait, are often asymmetric, but mechanisms underlying gait asymmetries in PD remain poorly understood. A translational toolkit, a set of standardized measures to capture gait asymmetries in relevant mouse models and patients, would greatly facilitate research efforts. We validated approaches to quantify asymmetries in placement and timing of limbs in mouse models of parkinsonism and human PD subjects at speeds that are relevant for human walking. In mice, we applied regression analysis to compare left and right gait metrics within a condition. To compare alternation ratios of left and right limbs before and after induction of parkinsonism, we used circular statistics. Both approaches revealed asymmetries in hind- and forelimb step length in a unilateral PD model, but not in bilateral or control models. In human subjects, a similar regression approach showed a step length asymmetry in the PD but not control group. Sub-analysis of cohorts with predominant postural instability-gait impairment and with predominant tremor revealed asymmetries for step length in both cohorts and for swing time only in the former cohort. This translational approach captures asymmetries of gait in mice and patients. Application revealed striking differences between models, and that spatial and temporal asymmetries may occur independently. This approach will be useful to investigate circuit mechanisms underlying the heterogeneity between models.
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spelling pubmed-63851832019-02-26 Translational methods to detect asymmetries in temporal and spatial walking metrics in parkinsonian mouse models and human subjects with Parkinson’s disease Broom, Lauren Worley, Audrey Gao, Fay Hernandez, Laura D. Ashton, Christine E. Shih, Ludy C. VanderHorst, Veronique G. Sci Rep Article Clinical signs in Parkinson’s disease (PD), including parkinsonian gait, are often asymmetric, but mechanisms underlying gait asymmetries in PD remain poorly understood. A translational toolkit, a set of standardized measures to capture gait asymmetries in relevant mouse models and patients, would greatly facilitate research efforts. We validated approaches to quantify asymmetries in placement and timing of limbs in mouse models of parkinsonism and human PD subjects at speeds that are relevant for human walking. In mice, we applied regression analysis to compare left and right gait metrics within a condition. To compare alternation ratios of left and right limbs before and after induction of parkinsonism, we used circular statistics. Both approaches revealed asymmetries in hind- and forelimb step length in a unilateral PD model, but not in bilateral or control models. In human subjects, a similar regression approach showed a step length asymmetry in the PD but not control group. Sub-analysis of cohorts with predominant postural instability-gait impairment and with predominant tremor revealed asymmetries for step length in both cohorts and for swing time only in the former cohort. This translational approach captures asymmetries of gait in mice and patients. Application revealed striking differences between models, and that spatial and temporal asymmetries may occur independently. This approach will be useful to investigate circuit mechanisms underlying the heterogeneity between models. Nature Publishing Group UK 2019-02-21 /pmc/articles/PMC6385183/ /pubmed/30792396 http://dx.doi.org/10.1038/s41598-019-38623-6 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Broom, Lauren
Worley, Audrey
Gao, Fay
Hernandez, Laura D.
Ashton, Christine E.
Shih, Ludy C.
VanderHorst, Veronique G.
Translational methods to detect asymmetries in temporal and spatial walking metrics in parkinsonian mouse models and human subjects with Parkinson’s disease
title Translational methods to detect asymmetries in temporal and spatial walking metrics in parkinsonian mouse models and human subjects with Parkinson’s disease
title_full Translational methods to detect asymmetries in temporal and spatial walking metrics in parkinsonian mouse models and human subjects with Parkinson’s disease
title_fullStr Translational methods to detect asymmetries in temporal and spatial walking metrics in parkinsonian mouse models and human subjects with Parkinson’s disease
title_full_unstemmed Translational methods to detect asymmetries in temporal and spatial walking metrics in parkinsonian mouse models and human subjects with Parkinson’s disease
title_short Translational methods to detect asymmetries in temporal and spatial walking metrics in parkinsonian mouse models and human subjects with Parkinson’s disease
title_sort translational methods to detect asymmetries in temporal and spatial walking metrics in parkinsonian mouse models and human subjects with parkinson’s disease
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6385183/
https://www.ncbi.nlm.nih.gov/pubmed/30792396
http://dx.doi.org/10.1038/s41598-019-38623-6
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