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Altered Topology of the Structural Brain Network in Patients With Post-stroke Depression

There is a pressing need to further our understanding of the mechanisms underlying the depression symptoms in patients with post-stroke depression (PSD) in order to inform targeted therapeutic approaches. While previous research has demonstrated a reorganization in the functional brain network of PS...

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Autores principales: Xu, Xiaopei, Tang, Rui, Zhang, Luping, Cao, Zhijian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6668487/
https://www.ncbi.nlm.nih.gov/pubmed/31396046
http://dx.doi.org/10.3389/fnins.2019.00776
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author Xu, Xiaopei
Tang, Rui
Zhang, Luping
Cao, Zhijian
author_facet Xu, Xiaopei
Tang, Rui
Zhang, Luping
Cao, Zhijian
author_sort Xu, Xiaopei
collection PubMed
description There is a pressing need to further our understanding of the mechanisms underlying the depression symptoms in patients with post-stroke depression (PSD) in order to inform targeted therapeutic approaches. While previous research has demonstrated a reorganization in the functional brain network of PSD, it remains uncertain whether, or not it also occurs in the structural brain network. We therefore aim to investigate the structural brain network of patients with PSD as compared to post-stroke non-depression (PSND) patients. In addition, our research considers the relationship between network metrics and functional measurements. Thirty-one PSD patients and twenty-three PSND patients were recruited. All patients underwent MRI and functional assessments, including the Barthel index, mini-mental state examination (MMSE), and Hamilton depression rating scale (HAMD). Diffusion tensor imaging was used to construct the structural brain network and to conduct the subsequent graph theoretical analysis. Network measures were computed and compared between PSD and PSND patients. Associations between functional assessments and network measures were studied as well. We successfully detected increased global and local efficiency in patients with PSD. Regions with disrupted local connections were located primarily in the cognitive and limbic systems. More importantly, PSD patients’ global and regional network measures were associated with depression severity, as measured by HAMD. These findings suggest that disrupted global and local network topologies might contribute to PSD patients’ depression symptoms. Therefore, connectome-based network measures could be potential bio-markers for evaluating stroke patients’ depression levels.
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spelling pubmed-66684872019-08-08 Altered Topology of the Structural Brain Network in Patients With Post-stroke Depression Xu, Xiaopei Tang, Rui Zhang, Luping Cao, Zhijian Front Neurosci Neuroscience There is a pressing need to further our understanding of the mechanisms underlying the depression symptoms in patients with post-stroke depression (PSD) in order to inform targeted therapeutic approaches. While previous research has demonstrated a reorganization in the functional brain network of PSD, it remains uncertain whether, or not it also occurs in the structural brain network. We therefore aim to investigate the structural brain network of patients with PSD as compared to post-stroke non-depression (PSND) patients. In addition, our research considers the relationship between network metrics and functional measurements. Thirty-one PSD patients and twenty-three PSND patients were recruited. All patients underwent MRI and functional assessments, including the Barthel index, mini-mental state examination (MMSE), and Hamilton depression rating scale (HAMD). Diffusion tensor imaging was used to construct the structural brain network and to conduct the subsequent graph theoretical analysis. Network measures were computed and compared between PSD and PSND patients. Associations between functional assessments and network measures were studied as well. We successfully detected increased global and local efficiency in patients with PSD. Regions with disrupted local connections were located primarily in the cognitive and limbic systems. More importantly, PSD patients’ global and regional network measures were associated with depression severity, as measured by HAMD. These findings suggest that disrupted global and local network topologies might contribute to PSD patients’ depression symptoms. Therefore, connectome-based network measures could be potential bio-markers for evaluating stroke patients’ depression levels. Frontiers Media S.A. 2019-07-24 /pmc/articles/PMC6668487/ /pubmed/31396046 http://dx.doi.org/10.3389/fnins.2019.00776 Text en Copyright © 2019 Xu, Tang, Zhang and Cao. 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
Xu, Xiaopei
Tang, Rui
Zhang, Luping
Cao, Zhijian
Altered Topology of the Structural Brain Network in Patients With Post-stroke Depression
title Altered Topology of the Structural Brain Network in Patients With Post-stroke Depression
title_full Altered Topology of the Structural Brain Network in Patients With Post-stroke Depression
title_fullStr Altered Topology of the Structural Brain Network in Patients With Post-stroke Depression
title_full_unstemmed Altered Topology of the Structural Brain Network in Patients With Post-stroke Depression
title_short Altered Topology of the Structural Brain Network in Patients With Post-stroke Depression
title_sort altered topology of the structural brain network in patients with post-stroke depression
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6668487/
https://www.ncbi.nlm.nih.gov/pubmed/31396046
http://dx.doi.org/10.3389/fnins.2019.00776
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