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Disrupted grey matter network morphology in pediatric posttraumatic stress disorder

INTRODUCTION: Disrupted topological organization of brain functional networks has been widely observed in posttraumatic stress disorder (PTSD). However, the topological organization of the brain grey matter (GM) network has not yet been investigated in pediatric PTSD who was more vulnerable to devel...

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Autores principales: Niu, Running, Lei, Du, Chen, Fuqin, Chen, Ying, Suo, Xueling, Li, Lingjiang, Lui, Su, Huang, Xiaoqi, Sweeney, John A., Gong, Qiyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5988464/
https://www.ncbi.nlm.nih.gov/pubmed/29876279
http://dx.doi.org/10.1016/j.nicl.2018.03.030
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author Niu, Running
Lei, Du
Chen, Fuqin
Chen, Ying
Suo, Xueling
Li, Lingjiang
Lui, Su
Huang, Xiaoqi
Sweeney, John A.
Gong, Qiyong
author_facet Niu, Running
Lei, Du
Chen, Fuqin
Chen, Ying
Suo, Xueling
Li, Lingjiang
Lui, Su
Huang, Xiaoqi
Sweeney, John A.
Gong, Qiyong
author_sort Niu, Running
collection PubMed
description INTRODUCTION: Disrupted topological organization of brain functional networks has been widely observed in posttraumatic stress disorder (PTSD). However, the topological organization of the brain grey matter (GM) network has not yet been investigated in pediatric PTSD who was more vulnerable to develop PTSD when exposed to stress. MATERIALS AND METHODS: Twenty two pediatric PTSD patients and 22 matched trauma-exposed controls who survived a massive earthquake (8.0 magnitude on Richter scale) in Sichuan Province of western China in 2008 underwent structural brain imaging with MRI 8–15 months after the earthquake. Brain networks were constructed based on the morphological similarity of GM across regions, and analyzed using graph theory approaches. Nonparametric permutation testing was performed to assess group differences in each topological metric. RESULTS: Compared with controls, brain networks of PTSD patients were characterized by decreased characteristic path length (P = 0.0060) and increased clustering coefficient (P = 0.0227), global efficiency (P = 0.0085) and local efficiency (P = 0.0024). Locally, patients with PTSD exhibited increased centrality in nodes of the default-mode (DMN), central executive (CEN) and salience networks (SN), involving medial prefrontal (mPFC), parietal, anterior cingulate (ACC), occipital and olfactory cortex and hippocampus. CONCLUSIONS: Our analyses of topological brain networks in children with PTSD indicate a significantly more segregated and integrated organization. The associations and disassociations between these grey matter findings and white matter (WM) and functional changes previously reported in this sample may be important for diagnostic purposes and understanding the brain maturational effects of pediatric PTSD.
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spelling pubmed-59884642018-06-06 Disrupted grey matter network morphology in pediatric posttraumatic stress disorder Niu, Running Lei, Du Chen, Fuqin Chen, Ying Suo, Xueling Li, Lingjiang Lui, Su Huang, Xiaoqi Sweeney, John A. Gong, Qiyong Neuroimage Clin Regular Article INTRODUCTION: Disrupted topological organization of brain functional networks has been widely observed in posttraumatic stress disorder (PTSD). However, the topological organization of the brain grey matter (GM) network has not yet been investigated in pediatric PTSD who was more vulnerable to develop PTSD when exposed to stress. MATERIALS AND METHODS: Twenty two pediatric PTSD patients and 22 matched trauma-exposed controls who survived a massive earthquake (8.0 magnitude on Richter scale) in Sichuan Province of western China in 2008 underwent structural brain imaging with MRI 8–15 months after the earthquake. Brain networks were constructed based on the morphological similarity of GM across regions, and analyzed using graph theory approaches. Nonparametric permutation testing was performed to assess group differences in each topological metric. RESULTS: Compared with controls, brain networks of PTSD patients were characterized by decreased characteristic path length (P = 0.0060) and increased clustering coefficient (P = 0.0227), global efficiency (P = 0.0085) and local efficiency (P = 0.0024). Locally, patients with PTSD exhibited increased centrality in nodes of the default-mode (DMN), central executive (CEN) and salience networks (SN), involving medial prefrontal (mPFC), parietal, anterior cingulate (ACC), occipital and olfactory cortex and hippocampus. CONCLUSIONS: Our analyses of topological brain networks in children with PTSD indicate a significantly more segregated and integrated organization. The associations and disassociations between these grey matter findings and white matter (WM) and functional changes previously reported in this sample may be important for diagnostic purposes and understanding the brain maturational effects of pediatric PTSD. Elsevier 2018-03-23 /pmc/articles/PMC5988464/ /pubmed/29876279 http://dx.doi.org/10.1016/j.nicl.2018.03.030 Text en © 2018 The Authors. Published by Elsevier Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
Niu, Running
Lei, Du
Chen, Fuqin
Chen, Ying
Suo, Xueling
Li, Lingjiang
Lui, Su
Huang, Xiaoqi
Sweeney, John A.
Gong, Qiyong
Disrupted grey matter network morphology in pediatric posttraumatic stress disorder
title Disrupted grey matter network morphology in pediatric posttraumatic stress disorder
title_full Disrupted grey matter network morphology in pediatric posttraumatic stress disorder
title_fullStr Disrupted grey matter network morphology in pediatric posttraumatic stress disorder
title_full_unstemmed Disrupted grey matter network morphology in pediatric posttraumatic stress disorder
title_short Disrupted grey matter network morphology in pediatric posttraumatic stress disorder
title_sort disrupted grey matter network morphology in pediatric posttraumatic stress disorder
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5988464/
https://www.ncbi.nlm.nih.gov/pubmed/29876279
http://dx.doi.org/10.1016/j.nicl.2018.03.030
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