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Brain Functional and Structural Signatures in Parkinson’s Disease

The aim of this study is to explore functional and structural properties of abnormal brain networks associated with Parkinson’s disease (PD). (18)F-Fluorodeoxyglucose positron emission tomography ((18)F-FDG PET) and T1-weighted magnetic resonance imaging from 20 patients with moderate-stage PD and 2...

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Autores principales: Liu, Chunhua, Jiang, Jiehui, Zhou, Hucheng, Zhang, Huiwei, Wang, Min, Jiang, Juanjuan, Wu, Ping, Ge, Jingjie, Wang, Jian, Ma, Yilong, Zuo, Chuantao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7264099/
https://www.ncbi.nlm.nih.gov/pubmed/32528272
http://dx.doi.org/10.3389/fnagi.2020.00125
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author Liu, Chunhua
Jiang, Jiehui
Zhou, Hucheng
Zhang, Huiwei
Wang, Min
Jiang, Juanjuan
Wu, Ping
Ge, Jingjie
Wang, Jian
Ma, Yilong
Zuo, Chuantao
author_facet Liu, Chunhua
Jiang, Jiehui
Zhou, Hucheng
Zhang, Huiwei
Wang, Min
Jiang, Juanjuan
Wu, Ping
Ge, Jingjie
Wang, Jian
Ma, Yilong
Zuo, Chuantao
author_sort Liu, Chunhua
collection PubMed
description The aim of this study is to explore functional and structural properties of abnormal brain networks associated with Parkinson’s disease (PD). (18)F-Fluorodeoxyglucose positron emission tomography ((18)F-FDG PET) and T1-weighted magnetic resonance imaging from 20 patients with moderate-stage PD and 20 age-matched healthy controls were acquired to identify disease-related patterns in functional and structural networks. Dual-modal images from another prospective subject of 15 PD patients were used as the validation group. Scaled Subprofile Modeling based on principal component analysis method was applied to determine disease-related patterns in both modalities, and brain connectome analysis based on graph theory was applied to verify these patterns. The results showed that the expressions of the metabolic and structural patterns in PD patients were significantly higher than healthy controls (PD1-HC, p = 0.0039, p = 0.0058; PD2-HC, p < 0.001, p = 0.044). The metabolic pattern was characterized by relative increased metabolic activity in pallidothalamic, pons, putamen, and cerebellum, associated with metabolic decreased in parietal–occipital areas. The structural pattern was characterized by relative decreased gray matter (GM) volume in pons, transverse temporal gyrus, left cuneus, right superior occipital gyrus, and right superior parietal lobule, associated with preservation in GM volume in pallidum and putamen. In addition, both patterns were verified in the connectome analysis. The findings suggest that significant overlaps between metabolic and structural patterns provide new evidence for elucidating the neuropathological mechanisms of PD.
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spelling pubmed-72640992020-06-10 Brain Functional and Structural Signatures in Parkinson’s Disease Liu, Chunhua Jiang, Jiehui Zhou, Hucheng Zhang, Huiwei Wang, Min Jiang, Juanjuan Wu, Ping Ge, Jingjie Wang, Jian Ma, Yilong Zuo, Chuantao Front Aging Neurosci Neuroscience The aim of this study is to explore functional and structural properties of abnormal brain networks associated with Parkinson’s disease (PD). (18)F-Fluorodeoxyglucose positron emission tomography ((18)F-FDG PET) and T1-weighted magnetic resonance imaging from 20 patients with moderate-stage PD and 20 age-matched healthy controls were acquired to identify disease-related patterns in functional and structural networks. Dual-modal images from another prospective subject of 15 PD patients were used as the validation group. Scaled Subprofile Modeling based on principal component analysis method was applied to determine disease-related patterns in both modalities, and brain connectome analysis based on graph theory was applied to verify these patterns. The results showed that the expressions of the metabolic and structural patterns in PD patients were significantly higher than healthy controls (PD1-HC, p = 0.0039, p = 0.0058; PD2-HC, p < 0.001, p = 0.044). The metabolic pattern was characterized by relative increased metabolic activity in pallidothalamic, pons, putamen, and cerebellum, associated with metabolic decreased in parietal–occipital areas. The structural pattern was characterized by relative decreased gray matter (GM) volume in pons, transverse temporal gyrus, left cuneus, right superior occipital gyrus, and right superior parietal lobule, associated with preservation in GM volume in pallidum and putamen. In addition, both patterns were verified in the connectome analysis. The findings suggest that significant overlaps between metabolic and structural patterns provide new evidence for elucidating the neuropathological mechanisms of PD. Frontiers Media S.A. 2020-05-26 /pmc/articles/PMC7264099/ /pubmed/32528272 http://dx.doi.org/10.3389/fnagi.2020.00125 Text en Copyright © 2020 Liu, Jiang, Zhou, Zhang, Wang, Jiang, Wu, Ge, Wang, Ma and Zuo. http://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
Liu, Chunhua
Jiang, Jiehui
Zhou, Hucheng
Zhang, Huiwei
Wang, Min
Jiang, Juanjuan
Wu, Ping
Ge, Jingjie
Wang, Jian
Ma, Yilong
Zuo, Chuantao
Brain Functional and Structural Signatures in Parkinson’s Disease
title Brain Functional and Structural Signatures in Parkinson’s Disease
title_full Brain Functional and Structural Signatures in Parkinson’s Disease
title_fullStr Brain Functional and Structural Signatures in Parkinson’s Disease
title_full_unstemmed Brain Functional and Structural Signatures in Parkinson’s Disease
title_short Brain Functional and Structural Signatures in Parkinson’s Disease
title_sort brain functional and structural signatures in parkinson’s disease
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7264099/
https://www.ncbi.nlm.nih.gov/pubmed/32528272
http://dx.doi.org/10.3389/fnagi.2020.00125
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