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Clinically relevant connectivity features define three subtypes of Parkinson's disease patients.


ABSTRACT: Parkinson's disease (PD) is characterized by complex clinical symptoms, including classic motor and nonmotor disturbances. Patients with PD vary in clinical manifestations and prognosis, which point to the existence of subtypes. This study aimed to find the fiber connectivity correlations with several crucial clinical symptoms and identify PD subtypes using unsupervised clustering analysis. One hundred and thirty-four PD patients and 77 normal controls were enrolled. Canonical correlation analysis (CCA) was performed to define the clinically relevant connectivity features, which were then used in the hierarchical clustering analysis to identify the distinct subtypes of PD patients. Multimodal neuroimaging analyses were further used to explore the neurophysiological basis of these subtypes. The methodology was validated in an independent data set. CCA revealed two significant clinically relevant patterns (motor-related pattern and depression-related pattern; r = .94, p?

SUBMITTER: Guo T 

PROVIDER: S-EPMC7469787 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Clinically relevant connectivity features define three subtypes of Parkinson's disease patients.

Guo Tao T   Guan Xiaojun X   Zhou Cheng C   Gao Ting T   Wu Jingjing J   Song Zhe Z   Xuan Min M   Gu Quanquan Q   Huang Peiyu P   Pu Jiali J   Zhang Baorong B   Cui Feng F   Xia Shunren S   Xu Xiaojun X   Zhang Minming M  

Human brain mapping 20200626 14


Parkinson's disease (PD) is characterized by complex clinical symptoms, including classic motor and nonmotor disturbances. Patients with PD vary in clinical manifestations and prognosis, which point to the existence of subtypes. This study aimed to find the fiber connectivity correlations with several crucial clinical symptoms and identify PD subtypes using unsupervised clustering analysis. One hundred and thirty-four PD patients and 77 normal controls were enrolled. Canonical correlation analys  ...[more]

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