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Different Dynamic Nodal Properties Contribute to Cognitive Impairment in Patients with White Matter Hyperintensities

White matter hyperintensities (WMHs) are commonly observed in older adults and are associated with cognitive impairment. Although previous studies have found abnormal functional connectivities in patients with WMHs based on static functional magnetic resonance imaging (fMRI), the topological propert...

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Autores principales: Liu, Yuanyuan, Cao, Shanshan, Du, Baogen, Zhang, Jun, Chen, Chen, Hu, Panpan, Tian, Yanghua, Wang, Kai, Ji, Gong-Jun, Wei, Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9688268/
https://www.ncbi.nlm.nih.gov/pubmed/36421852
http://dx.doi.org/10.3390/brainsci12111527
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author Liu, Yuanyuan
Cao, Shanshan
Du, Baogen
Zhang, Jun
Chen, Chen
Hu, Panpan
Tian, Yanghua
Wang, Kai
Ji, Gong-Jun
Wei, Qiang
author_facet Liu, Yuanyuan
Cao, Shanshan
Du, Baogen
Zhang, Jun
Chen, Chen
Hu, Panpan
Tian, Yanghua
Wang, Kai
Ji, Gong-Jun
Wei, Qiang
author_sort Liu, Yuanyuan
collection PubMed
description White matter hyperintensities (WMHs) are commonly observed in older adults and are associated with cognitive impairment. Although previous studies have found abnormal functional connectivities in patients with WMHs based on static functional magnetic resonance imaging (fMRI), the topological properties in the context of brain dynamics remain relatively unexplored. Herein, we explored disrupted dynamic topological properties of functional network connectivity in patients with WMHs and its relationship with cognitive impairment. We included 36 healthy controls (HC) and 104 patients with mild WMHs (n = 39), moderate WMHs (n = 37), and severe (n = 28) WMHs. The fMRI data of all participants were analyzed using Anatomical Automatic Labeling (AAL) and a sliding-window approach to generate dynamic functional connectivity matrics. Then, graph theory methods were applied to calculate the topological properties. Comprehensive neuropsychological scales were used to assess cognitive functions. Relationships between cognitive functions and abnormal dynamic topological properties were evaluated by Pearson’s correlation. We found that the patients with WMHs had higher temporal variability in regional properties, including betweenness centrality, nodal efficiencies, and nodal clustering coefficient. Furthermore, we found that the degree of centrality was related to executive function and memory, and the local coefficient correlated to executive function. Our results indicate that patients with WMHs have higher temporal variabilities in regional properties and are associated with executive and memory function.
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spelling pubmed-96882682022-11-25 Different Dynamic Nodal Properties Contribute to Cognitive Impairment in Patients with White Matter Hyperintensities Liu, Yuanyuan Cao, Shanshan Du, Baogen Zhang, Jun Chen, Chen Hu, Panpan Tian, Yanghua Wang, Kai Ji, Gong-Jun Wei, Qiang Brain Sci Article White matter hyperintensities (WMHs) are commonly observed in older adults and are associated with cognitive impairment. Although previous studies have found abnormal functional connectivities in patients with WMHs based on static functional magnetic resonance imaging (fMRI), the topological properties in the context of brain dynamics remain relatively unexplored. Herein, we explored disrupted dynamic topological properties of functional network connectivity in patients with WMHs and its relationship with cognitive impairment. We included 36 healthy controls (HC) and 104 patients with mild WMHs (n = 39), moderate WMHs (n = 37), and severe (n = 28) WMHs. The fMRI data of all participants were analyzed using Anatomical Automatic Labeling (AAL) and a sliding-window approach to generate dynamic functional connectivity matrics. Then, graph theory methods were applied to calculate the topological properties. Comprehensive neuropsychological scales were used to assess cognitive functions. Relationships between cognitive functions and abnormal dynamic topological properties were evaluated by Pearson’s correlation. We found that the patients with WMHs had higher temporal variability in regional properties, including betweenness centrality, nodal efficiencies, and nodal clustering coefficient. Furthermore, we found that the degree of centrality was related to executive function and memory, and the local coefficient correlated to executive function. Our results indicate that patients with WMHs have higher temporal variabilities in regional properties and are associated with executive and memory function. MDPI 2022-11-10 /pmc/articles/PMC9688268/ /pubmed/36421852 http://dx.doi.org/10.3390/brainsci12111527 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liu, Yuanyuan
Cao, Shanshan
Du, Baogen
Zhang, Jun
Chen, Chen
Hu, Panpan
Tian, Yanghua
Wang, Kai
Ji, Gong-Jun
Wei, Qiang
Different Dynamic Nodal Properties Contribute to Cognitive Impairment in Patients with White Matter Hyperintensities
title Different Dynamic Nodal Properties Contribute to Cognitive Impairment in Patients with White Matter Hyperintensities
title_full Different Dynamic Nodal Properties Contribute to Cognitive Impairment in Patients with White Matter Hyperintensities
title_fullStr Different Dynamic Nodal Properties Contribute to Cognitive Impairment in Patients with White Matter Hyperintensities
title_full_unstemmed Different Dynamic Nodal Properties Contribute to Cognitive Impairment in Patients with White Matter Hyperintensities
title_short Different Dynamic Nodal Properties Contribute to Cognitive Impairment in Patients with White Matter Hyperintensities
title_sort different dynamic nodal properties contribute to cognitive impairment in patients with white matter hyperintensities
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9688268/
https://www.ncbi.nlm.nih.gov/pubmed/36421852
http://dx.doi.org/10.3390/brainsci12111527
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