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Main Authors: Nanfang Pan, Kun Qin, Luis R. Patino, Maxwell J. Tallman, Du Lei, Lu Lu, Wenbin Li, Thomas J. Blom, Kaitlyn M. Bruns, Jeffrey A. Welge, Jeffrey R. Strawn, Qiyong Gong, John A. Sweeney, Manpreet K. Singh, Melissa P. DelBello
Format: Artículo Open Access
Published: Wiley 2024
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Online Access:https://acamh.onlinelibrary.wiley.com/doi/10.1111/jcpp.13946
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author Nanfang Pan
Kun Qin
Luis R. Patino
Maxwell J. Tallman
Du Lei
Lu Lu
Wenbin Li
Thomas J. Blom
Kaitlyn M. Bruns
Jeffrey A. Welge
Jeffrey R. Strawn
Qiyong Gong
John A. Sweeney
Manpreet K. Singh
Melissa P. DelBello
author_facet Nanfang Pan
Kun Qin
Luis R. Patino
Maxwell J. Tallman
Du Lei
Lu Lu
Wenbin Li
Thomas J. Blom
Kaitlyn M. Bruns
Jeffrey A. Welge
Jeffrey R. Strawn
Qiyong Gong
John A. Sweeney
Manpreet K. Singh
Melissa P. DelBello
Nanfang Pan
Kun Qin
Luis R. Patino
Maxwell J. Tallman
Du Lei
Lu Lu
Wenbin Li
Thomas J. Blom
Kaitlyn M. Bruns
Jeffrey A. Welge
Jeffrey R. Strawn
Qiyong Gong
John A. Sweeney
Manpreet K. Singh
Melissa P. DelBello
collection Wiley Open Access
contents Aberrant brain network topology in youth with a familial risk for bipolar disorder: a task‐based fMRI connectome study Nanfang Pan Kun Qin Luis R. Patino Maxwell J. Tallman Du Lei Lu Lu Wenbin Li Thomas J. Blom Kaitlyn M. Bruns Jeffrey A. Welge Jeffrey R. Strawn Qiyong Gong John A. Sweeney Manpreet K. Singh Melissa P. DelBello Journal of Child Psychology and Psychiatry Background Youth with a family history of bipolar disorder (BD) may be at increased risk for mood disorders and for developing side effects after antidepressant exposure. The neurobiological basis of these risks remains poorly understood. We aimed to identify biomarkers underlying risk by characterizing abnormalities in the brain connectome of symptomatic youth at familial risk for BD. Methods Depressed and/or anxious youth ( n  = 119, age = 14.9 ± 1.6 years) with a family history of BD but no prior antidepressant exposure and typically developing controls ( n  = 57, age = 14.8 ± 1.7 years) received functional magnetic resonance imaging (fMRI) during an emotional continuous performance task. A generalized psychophysiological interaction (gPPI) analysis was performed to compare their brain connectome patterns, followed by machine learning of topological metrics. Results High‐risk youth showed weaker connectivity patterns that were mainly located in the default mode network (DMN) (network weight = 50.1%) relative to controls, and connectivity patterns derived from the visual network (VN) constituted the largest proportion of aberrant stronger pairs (network weight = 54.9%). Global local efficiency ( E local , p  = .022) and clustering coefficient ( C p , p  = .029) and nodal metrics of the right superior frontal gyrus (SFG) ( E local : p  < .001; C p : p  = .001) in the high‐risk group were significantly higher than those in healthy subjects, and similar patterns were also found in the left insula (degree: p  = .004; betweenness: p  = .005; age‐by‐group interaction, p  = .038) and right hippocampus (degree: p  = .003; betweenness: p  = .003). The case–control classifier achieved a cross‐validation accuracy of 78.4%. Conclusions Our findings of abnormal connectome organization in the DMN and VN may advance mechanistic understanding of risk for BD. Neuroimaging biomarkers of increased network segregation in the SFG and altered topological centrality in the insula and hippocampus in broader limbic systems may be used to target interventions tailored to mitigate the underlying risk of brain abnormalities in these at‐risk youth. 10.1111/jcpp.13946 http://creativecommons.org/licenses/by-nc/4.0/
doi_str_mv 10.1111/jcpp.13946
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institution Wiley Open Access
license_str_mv http://creativecommons.org/licenses/by-nc/4.0/
publishDate 2024
publisher Wiley
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spellingShingle Aberrant brain network topology in youth with a familial risk for bipolar disorder: a task‐based fMRI connectome study
Nanfang Pan
Kun Qin
Luis R. Patino
Maxwell J. Tallman
Du Lei
Lu Lu
Wenbin Li
Thomas J. Blom
Kaitlyn M. Bruns
Jeffrey A. Welge
Jeffrey R. Strawn
Qiyong Gong
John A. Sweeney
Manpreet K. Singh
Melissa P. DelBello
Journal of Child Psychology and Psychiatry
Aberrant brain network topology in youth with a familial risk for bipolar disorder: a task‐based fMRI connectome study Nanfang Pan Kun Qin Luis R. Patino Maxwell J. Tallman Du Lei Lu Lu Wenbin Li Thomas J. Blom Kaitlyn M. Bruns Jeffrey A. Welge Jeffrey R. Strawn Qiyong Gong John A. Sweeney Manpreet K. Singh Melissa P. DelBello Journal of Child Psychology and Psychiatry Background Youth with a family history of bipolar disorder (BD) may be at increased risk for mood disorders and for developing side effects after antidepressant exposure. The neurobiological basis of these risks remains poorly understood. We aimed to identify biomarkers underlying risk by characterizing abnormalities in the brain connectome of symptomatic youth at familial risk for BD. Methods Depressed and/or anxious youth ( n  = 119, age = 14.9 ± 1.6 years) with a family history of BD but no prior antidepressant exposure and typically developing controls ( n  = 57, age = 14.8 ± 1.7 years) received functional magnetic resonance imaging (fMRI) during an emotional continuous performance task. A generalized psychophysiological interaction (gPPI) analysis was performed to compare their brain connectome patterns, followed by machine learning of topological metrics. Results High‐risk youth showed weaker connectivity patterns that were mainly located in the default mode network (DMN) (network weight = 50.1%) relative to controls, and connectivity patterns derived from the visual network (VN) constituted the largest proportion of aberrant stronger pairs (network weight = 54.9%). Global local efficiency ( E local , p  = .022) and clustering coefficient ( C p , p  = .029) and nodal metrics of the right superior frontal gyrus (SFG) ( E local : p  < .001; C p : p  = .001) in the high‐risk group were significantly higher than those in healthy subjects, and similar patterns were also found in the left insula (degree: p  = .004; betweenness: p  = .005; age‐by‐group interaction, p  = .038) and right hippocampus (degree: p  = .003; betweenness: p  = .003). The case–control classifier achieved a cross‐validation accuracy of 78.4%. Conclusions Our findings of abnormal connectome organization in the DMN and VN may advance mechanistic understanding of risk for BD. Neuroimaging biomarkers of increased network segregation in the SFG and altered topological centrality in the insula and hippocampus in broader limbic systems may be used to target interventions tailored to mitigate the underlying risk of brain abnormalities in these at‐risk youth. 10.1111/jcpp.13946 http://creativecommons.org/licenses/by-nc/4.0/
title Aberrant brain network topology in youth with a familial risk for bipolar disorder: a task‐based fMRI connectome study
topic Journal of Child Psychology and Psychiatry
url https://acamh.onlinelibrary.wiley.com/doi/10.1111/jcpp.13946