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Large-scale network dysfunction in the acute state compared to the remitted state of bipolar disorder: A meta-analysis of resting-state functional connectivity

BACKGROUND: Bipolar disorder (BD) is a mental disorder characterized by mood fluctuations between an acute episodic state of either mania or depression and a clinically remitted state. Dysfunction of large-scale intrinsic brain networks has been demonstrated in this disorder, but it remains unknown...

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Autores principales: Wang, Yanlin, Gao, Yingxue, Tang, Shi, Lu, Lu, Zhang, Lianqing, Bu, Xuan, Li, Hailong, Hu, Xiaoxiao, Hu, Xinyu, Jiang, Ping, Jia, Zhiyun, Gong, Qiyong, Sweeney, John A., Huang, Xiaoqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7136605/
https://www.ncbi.nlm.nih.gov/pubmed/32259712
http://dx.doi.org/10.1016/j.ebiom.2020.102742
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author Wang, Yanlin
Gao, Yingxue
Tang, Shi
Lu, Lu
Zhang, Lianqing
Bu, Xuan
Li, Hailong
Hu, Xiaoxiao
Hu, Xinyu
Jiang, Ping
Jia, Zhiyun
Gong, Qiyong
Sweeney, John A.
Huang, Xiaoqi
author_facet Wang, Yanlin
Gao, Yingxue
Tang, Shi
Lu, Lu
Zhang, Lianqing
Bu, Xuan
Li, Hailong
Hu, Xiaoxiao
Hu, Xinyu
Jiang, Ping
Jia, Zhiyun
Gong, Qiyong
Sweeney, John A.
Huang, Xiaoqi
author_sort Wang, Yanlin
collection PubMed
description BACKGROUND: Bipolar disorder (BD) is a mental disorder characterized by mood fluctuations between an acute episodic state of either mania or depression and a clinically remitted state. Dysfunction of large-scale intrinsic brain networks has been demonstrated in this disorder, but it remains unknown whether those network alterations are related to different states. METHODS: In the present study, we performed a meta-analysis of whole-brain seed-based resting-state functional connectivity (rsFC) studies in BD patients to compare the intrinsic function of brain networks between episodic and remitted states. Thirty-nine seed-based voxel-wise rsFC datasets from thirty publications (1047 BD patients vs 1081 controls) were included in the meta-analysis. Seeds were categorized into networks by their locations within a priori functional networks. Seed-based d mapping analysis of between-state effects identified brain systems in which different states were associated with increased connectivity or decreased connectivity within and between each seed network. FINDINGS: We found that BD patients presented decreased connectivity within the affective network (AN) in acute episodes but not in the remitted state of the illness. Similar decreased connectivity within the default-mode network (DMN) was also found in the acute state, but it was replaced by increased connectivity in the remitted state. In addition, different patterns of between-network dysconnectivity were observed between the acute and remitted states. INTERPRETATION: This study is the first to identify different patterns of intrinsic function in large-scale brain networks between the acute and remitted states of BD through meta-analysis. The findings suggest that a shift in network function between the acute and remitted states may be related to distinct emotional and cognitive dysfunctions in BD, which may have important implications for identifying clinically relevant biomarkers to guide alternative treatment strategies for BD patients during active episodes or remission. FUNDING: This study was supported by grants from the National Natural Science Foundation of China (81171488, 81671669 and 81820108018) and by a Sichuan Provincial Youth Grant (2017JQ0001).
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spelling pubmed-71366052020-04-10 Large-scale network dysfunction in the acute state compared to the remitted state of bipolar disorder: A meta-analysis of resting-state functional connectivity Wang, Yanlin Gao, Yingxue Tang, Shi Lu, Lu Zhang, Lianqing Bu, Xuan Li, Hailong Hu, Xiaoxiao Hu, Xinyu Jiang, Ping Jia, Zhiyun Gong, Qiyong Sweeney, John A. Huang, Xiaoqi EBioMedicine Research paper BACKGROUND: Bipolar disorder (BD) is a mental disorder characterized by mood fluctuations between an acute episodic state of either mania or depression and a clinically remitted state. Dysfunction of large-scale intrinsic brain networks has been demonstrated in this disorder, but it remains unknown whether those network alterations are related to different states. METHODS: In the present study, we performed a meta-analysis of whole-brain seed-based resting-state functional connectivity (rsFC) studies in BD patients to compare the intrinsic function of brain networks between episodic and remitted states. Thirty-nine seed-based voxel-wise rsFC datasets from thirty publications (1047 BD patients vs 1081 controls) were included in the meta-analysis. Seeds were categorized into networks by their locations within a priori functional networks. Seed-based d mapping analysis of between-state effects identified brain systems in which different states were associated with increased connectivity or decreased connectivity within and between each seed network. FINDINGS: We found that BD patients presented decreased connectivity within the affective network (AN) in acute episodes but not in the remitted state of the illness. Similar decreased connectivity within the default-mode network (DMN) was also found in the acute state, but it was replaced by increased connectivity in the remitted state. In addition, different patterns of between-network dysconnectivity were observed between the acute and remitted states. INTERPRETATION: This study is the first to identify different patterns of intrinsic function in large-scale brain networks between the acute and remitted states of BD through meta-analysis. The findings suggest that a shift in network function between the acute and remitted states may be related to distinct emotional and cognitive dysfunctions in BD, which may have important implications for identifying clinically relevant biomarkers to guide alternative treatment strategies for BD patients during active episodes or remission. FUNDING: This study was supported by grants from the National Natural Science Foundation of China (81171488, 81671669 and 81820108018) and by a Sichuan Provincial Youth Grant (2017JQ0001). Elsevier 2020-04-04 /pmc/articles/PMC7136605/ /pubmed/32259712 http://dx.doi.org/10.1016/j.ebiom.2020.102742 Text en © 2020 The Authors 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 Research paper
Wang, Yanlin
Gao, Yingxue
Tang, Shi
Lu, Lu
Zhang, Lianqing
Bu, Xuan
Li, Hailong
Hu, Xiaoxiao
Hu, Xinyu
Jiang, Ping
Jia, Zhiyun
Gong, Qiyong
Sweeney, John A.
Huang, Xiaoqi
Large-scale network dysfunction in the acute state compared to the remitted state of bipolar disorder: A meta-analysis of resting-state functional connectivity
title Large-scale network dysfunction in the acute state compared to the remitted state of bipolar disorder: A meta-analysis of resting-state functional connectivity
title_full Large-scale network dysfunction in the acute state compared to the remitted state of bipolar disorder: A meta-analysis of resting-state functional connectivity
title_fullStr Large-scale network dysfunction in the acute state compared to the remitted state of bipolar disorder: A meta-analysis of resting-state functional connectivity
title_full_unstemmed Large-scale network dysfunction in the acute state compared to the remitted state of bipolar disorder: A meta-analysis of resting-state functional connectivity
title_short Large-scale network dysfunction in the acute state compared to the remitted state of bipolar disorder: A meta-analysis of resting-state functional connectivity
title_sort large-scale network dysfunction in the acute state compared to the remitted state of bipolar disorder: a meta-analysis of resting-state functional connectivity
topic Research paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7136605/
https://www.ncbi.nlm.nih.gov/pubmed/32259712
http://dx.doi.org/10.1016/j.ebiom.2020.102742
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