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Subtyping of early-onset Parkinson’s disease using cluster analysis: A large cohort study
BACKGROUND: Increasing evidence suggests that early-onset Parkinson’s disease (EOPD) is heterogeneous in its clinical presentation and progression. Defining subtypes of EOPD is needed to better understand underlying mechanisms, predict disease course, and eventually design more efficient personalize...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9692000/ https://www.ncbi.nlm.nih.gov/pubmed/36437996 http://dx.doi.org/10.3389/fnagi.2022.1040293 |
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author | Zhou, Zhou Zhou, Xiaoxia Xiang, Yaqin Zhao, Yuwen Pan, Hongxu Wu, Juan Xu, Qian Chen, Yase Sun, Qiying Wu, Xinyin Zhu, Jianping Wu, Xuehong Li, Jianhua Yan, Xinxiang Guo, Jifeng Tang, Beisha Lei, Lifang Liu, Zhenhua |
author_facet | Zhou, Zhou Zhou, Xiaoxia Xiang, Yaqin Zhao, Yuwen Pan, Hongxu Wu, Juan Xu, Qian Chen, Yase Sun, Qiying Wu, Xinyin Zhu, Jianping Wu, Xuehong Li, Jianhua Yan, Xinxiang Guo, Jifeng Tang, Beisha Lei, Lifang Liu, Zhenhua |
author_sort | Zhou, Zhou |
collection | PubMed |
description | BACKGROUND: Increasing evidence suggests that early-onset Parkinson’s disease (EOPD) is heterogeneous in its clinical presentation and progression. Defining subtypes of EOPD is needed to better understand underlying mechanisms, predict disease course, and eventually design more efficient personalized management strategies. OBJECTIVE: To identify clinical subtypes of EOPD, assess the clinical characteristics of each EOPD subtype, and compare the progression between EOPD subtypes. MATERIALS AND METHODS: A total of 1,217 patients were enrolled from a large EOPD cohort of the Parkinson’s Disease & Movement Disorders Multicenter Database and Collaborative Network in China (PD-MDCNC) between January 2017 and September 2021. A comprehensive spectrum of motor and non-motor features were assessed at baseline. Cluster analysis was performed using data on demographics, motor symptoms and signs, and other non-motor manifestations. In 454 out of total patients were reassessed after a mean follow-up time of 1.5 years to compare progression between different subtypes. RESULTS: Three subtypes were defined: mild motor and non-motor dysfunction/slow progression, intermediate and severe motor and non-motor dysfunction/malignant. Compared to patients with mild subtype, patients with the severe subtype were more likely to have rapid eye movement sleep behavior disorder, wearing-off, and dyskinesia, after adjusting for age and disease duration at baseline, and showed a more rapid progression in Unified Parkinson’s Disease Rating Scale (UPDRS) total score (P = 0.002), UPDRS part II (P = 0.014), and III (P = 0.001) scores, Hoehn and Yahr stage (P = 0.001), and Parkinson’s disease questionnaire-39 item version score (P = 0.012) at prospective follow-up. CONCLUSION: We identified three different clinical subtypes (mild, intermediate, and severe) using cluster analysis in a large EOPD cohort for the first time, which is important for tailoring therapy to individuals with EOPD. |
format | Online Article Text |
id | pubmed-9692000 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96920002022-11-26 Subtyping of early-onset Parkinson’s disease using cluster analysis: A large cohort study Zhou, Zhou Zhou, Xiaoxia Xiang, Yaqin Zhao, Yuwen Pan, Hongxu Wu, Juan Xu, Qian Chen, Yase Sun, Qiying Wu, Xinyin Zhu, Jianping Wu, Xuehong Li, Jianhua Yan, Xinxiang Guo, Jifeng Tang, Beisha Lei, Lifang Liu, Zhenhua Front Aging Neurosci Neuroscience BACKGROUND: Increasing evidence suggests that early-onset Parkinson’s disease (EOPD) is heterogeneous in its clinical presentation and progression. Defining subtypes of EOPD is needed to better understand underlying mechanisms, predict disease course, and eventually design more efficient personalized management strategies. OBJECTIVE: To identify clinical subtypes of EOPD, assess the clinical characteristics of each EOPD subtype, and compare the progression between EOPD subtypes. MATERIALS AND METHODS: A total of 1,217 patients were enrolled from a large EOPD cohort of the Parkinson’s Disease & Movement Disorders Multicenter Database and Collaborative Network in China (PD-MDCNC) between January 2017 and September 2021. A comprehensive spectrum of motor and non-motor features were assessed at baseline. Cluster analysis was performed using data on demographics, motor symptoms and signs, and other non-motor manifestations. In 454 out of total patients were reassessed after a mean follow-up time of 1.5 years to compare progression between different subtypes. RESULTS: Three subtypes were defined: mild motor and non-motor dysfunction/slow progression, intermediate and severe motor and non-motor dysfunction/malignant. Compared to patients with mild subtype, patients with the severe subtype were more likely to have rapid eye movement sleep behavior disorder, wearing-off, and dyskinesia, after adjusting for age and disease duration at baseline, and showed a more rapid progression in Unified Parkinson’s Disease Rating Scale (UPDRS) total score (P = 0.002), UPDRS part II (P = 0.014), and III (P = 0.001) scores, Hoehn and Yahr stage (P = 0.001), and Parkinson’s disease questionnaire-39 item version score (P = 0.012) at prospective follow-up. CONCLUSION: We identified three different clinical subtypes (mild, intermediate, and severe) using cluster analysis in a large EOPD cohort for the first time, which is important for tailoring therapy to individuals with EOPD. Frontiers Media S.A. 2022-11-11 /pmc/articles/PMC9692000/ /pubmed/36437996 http://dx.doi.org/10.3389/fnagi.2022.1040293 Text en Copyright © 2022 Zhou, Zhou, Xiang, Zhao, Pan, Wu, Xu, Chen, Sun, Wu, Zhu, Wu, Li, Yan, Guo, Tang, Lei and Liu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Zhou, Zhou Zhou, Xiaoxia Xiang, Yaqin Zhao, Yuwen Pan, Hongxu Wu, Juan Xu, Qian Chen, Yase Sun, Qiying Wu, Xinyin Zhu, Jianping Wu, Xuehong Li, Jianhua Yan, Xinxiang Guo, Jifeng Tang, Beisha Lei, Lifang Liu, Zhenhua Subtyping of early-onset Parkinson’s disease using cluster analysis: A large cohort study |
title | Subtyping of early-onset Parkinson’s disease using cluster analysis: A large cohort study |
title_full | Subtyping of early-onset Parkinson’s disease using cluster analysis: A large cohort study |
title_fullStr | Subtyping of early-onset Parkinson’s disease using cluster analysis: A large cohort study |
title_full_unstemmed | Subtyping of early-onset Parkinson’s disease using cluster analysis: A large cohort study |
title_short | Subtyping of early-onset Parkinson’s disease using cluster analysis: A large cohort study |
title_sort | subtyping of early-onset parkinson’s disease using cluster analysis: a large cohort study |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9692000/ https://www.ncbi.nlm.nih.gov/pubmed/36437996 http://dx.doi.org/10.3389/fnagi.2022.1040293 |
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