A magnetic resonance imaging-based morphometric and structural covariance network study of Brazilian adolescents stratified by depression risk

Fernanda Rohrsetzer; Joana Bisol Balardin; Felipe Almeida Picon; João Ricardo Sato; Lucas Battel; Anna Viduani; Pedro H.  Manfro; Leehyun Yoon; Brandon A Kohrt; Helen Fisher; Valeria Mondelli; Johnna Swartz; Christian Kieling

doi:10.47626/1516-4446-2023-3037

A magnetic resonance imaging-based morphometric and structural covariance network study of Brazilian adolescents stratified by depression risk

Fernanda Rohrsetzer, Joana Bisol Balardin, Felipe Almeida Picon, João Ricardo Sato, Lucas Battel, Anna Viduani, Pedro H. Manfro, Leehyun Yoon, Brandon A Kohrt, Helen Fisher, Valeria Mondelli, Johnna Swartz, Christian Kieling

Research output: Contribution to journal › Article › peer-review

Abstract

Objectives: To explore differences in regional cortical morphometric structure between adolescents at risk for depression or with current depression. Methods: We analyzed cross-sectional structural neuroimaging data from a sample of 150 Brazilian adolescents classified as low-risk (LR) (n=50) or high-risk (HR) for depression (n=50) or with current depression (n=50) through a vertex-based approach with measurements of cortical volume (CV), surface area (SA), and cortical thickness (CT). Differences between groups in subcortical volume and in the organization of networks of structural covariance were also explored. Results: No significant differences in brain structure between groups were observed in whole-brain vertex-wise CV, SA, or CT. Also, no significant differences in subcortical volume were observed between risk groups. In relation to the structural covariance network, there was an indication of an increase in the hippocampus betweenness centrality index in the HR group network compared to the LR and current depression group networks. However, this result was only statistically significant when applying false discovery rate correction for nodes within the affective network. Conclusion: In an adolescent sample recruited using an empirically based composite risk score, no major differences in brain structure were detected according to the risk and presence of depression.

Original language	English
Pages (from-to)	318-326
Number of pages	9
Journal	Brazilian Journal of Psychiatry
Volume	45
Issue number	4
Early online date	13 May 2023
DOIs	https://doi.org/10.47626/1516-4446-2023-3037
Publication status	Published - 1 Jul 2023

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10.47626/1516-4446-2023-3037Licence: CC BY-NC

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Rohrsetzer, F., Balardin, J. B., Picon, F. A., Sato, J. R., Battel, L., Viduani, A., Manfro, P. H., Yoon, L., Kohrt, B. A., Fisher, H., Mondelli, V., Swartz, J., & Kieling, C. (2023). A magnetic resonance imaging-based morphometric and structural covariance network study of Brazilian adolescents stratified by depression risk. Brazilian Journal of Psychiatry, 45(4), 318-326. https://doi.org/10.47626/1516-4446-2023-3037

@article{503e50764b47408e854e136401dbb568,

title = "A magnetic resonance imaging-based morphometric and structural covariance network study of Brazilian adolescents stratified by depression risk",

abstract = "Objectives: To explore differences in regional cortical morphometric structure between adolescents at risk for depression or with current depression. Methods: We analyzed cross-sectional structural neuroimaging data from a sample of 150 Brazilian adolescents classified as low-risk (LR) (n=50) or high-risk (HR) for depression (n=50) or with current depression (n=50) through a vertex-based approach with measurements of cortical volume (CV), surface area (SA), and cortical thickness (CT). Differences between groups in subcortical volume and in the organization of networks of structural covariance were also explored. Results: No significant differences in brain structure between groups were observed in whole-brain vertex-wise CV, SA, or CT. Also, no significant differences in subcortical volume were observed between risk groups. In relation to the structural covariance network, there was an indication of an increase in the hippocampus betweenness centrality index in the HR group network compared to the LR and current depression group networks. However, this result was only statistically significant when applying false discovery rate correction for nodes within the affective network. Conclusion: In an adolescent sample recruited using an empirically based composite risk score, no major differences in brain structure were detected according to the risk and presence of depression.",

author = "Fernanda Rohrsetzer and Balardin, {Joana Bisol} and Picon, {Felipe Almeida} and Sato, {Jo{\~a}o Ricardo} and Lucas Battel and Anna Viduani and Manfro, {Pedro H.} and Leehyun Yoon and Kohrt, {Brandon A} and Helen Fisher and Valeria Mondelli and Johnna Swartz and Christian Kieling",

note = "Funding Information: HLF was partly supported by the Economic and Social Research Council (ESRC) Centre for Society and Mental Health at King{\textquoteright}s College London (ES/S012567/1). VM was supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London, Maudsley National Health Service (NHS) Foundation Trust, and King{\textquoteright}s College London. CK is a CNPq researcher and an Academy of Medical Sciences Newton Advanced fellow. The views expressed are those of the authors and do not necessarily reflect the views of the NHS, the NIHR, the Department of Health and Social Care, the ESRC, or King{\textquoteright}s College London. Funding Information: The Identifying Depression Early in Adolescence (IDEA) project was funded by an MQ Brighter Futures grant (MQBF/1 IDEA). Additional support was provided by the UK Medical Research Council (MC_PC_MR/R019460/1) and the Academy of Medical Sciences (GCRFNG_ 100281) under the Global Challenges Research Fund. This work is also supported by research grants from Brazilian public funding agencies Conselho Nacional de Desenvolvimento Cient{\'i}fico e Tecnol{\'o}gico (CNPq; 477129/2012-9 and 445828/2014-5), Coordenac¸{\~a}o de Aperfeic¸oamento de Pessoal de N{\'i}vel Superior (CAPES; 62/2014), and Fundac¸{\~a}o de Amparo {\`a} Pesquisa do Estado do Rio Grande do Sul (FAPERGS; 17/2551-0001009-4). Funding Information: JRS receives financial support from Fundac¸{\~a}o de Amparo {\`a} Pesquisa do Estado de S{\~a}o Paulo (FAPESP; grants 2021/05332-8, 2018/04654-9, and 2018/21934-5). JRS, BAK, and CK are supported by the U.S. National Institute of Mental Health (NIMH; R21MH124072). Funding Information: The Identifying Depression Early in Adolescence (IDEA) project was funded by an MQ Brighter Futures grant (MQBF/1 IDEA). Additional support was provided by the UK Medical Research Council (MC_PC_MR/R019460/1) and the Academy of Medical Sciences (GCRFNG_ 100281) under the Global Challenges Research Fund. This work is also supported by research grants from Brazilian public funding agencies Conselho Nacional de Desenvolvimento Cient{\'i}fico e Tecnol{\'o}gico (CNPq; 477129/2012-9 and 445828/2014-5), Coordenac¸{\~a}o de Aperfeic¸oamento de Pessoal de N{\'i}vel Superior (CAPES; 62/2014), and Fundac¸{\~a}o de Amparo {\`a} Pesquisa do Estado do Rio Grande do Sul (FAPERGS; 17/2551-0001009-4). JRS receives financial support from Fundac¸{\~a}o de Amparo {\`a} Pesquisa do Estado de S{\~a}o Paulo (FAPESP; grants 2021/05332-8, 2018/04654-9, and 2018/21934-5). JRS, BAK, and CK are supported by the U.S. National Institute of Mental Health (NIMH; R21MH124072). HLF was partly supported by the Economic and Social Research Council (ESRC) Centre for Society and Mental Health at King{\textquoteright}s College London (ES/S012567/1). VM was supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London, Maudsley National Health Service (NHS) Foundation Trust, and King{\textquoteright}s College London. CK is a CNPq researcher and an Academy of Medical Sciences Newton Advanced fellow. The views expressed are those of the authors and do not necessarily reflect the views of the NHS, the NIHR, the Department of Health and Social Care, the ESRC, or King{\textquoteright}s College London. We are extremely grateful to the schools and individuals who participated in this study, and to all members of the IDEA team for their dedication, hard work, and insights. Publisher Copyright: {\textcopyright} 2023, Associacao Brasileira de Psiquiatria. All rights reserved.",

year = "2023",

month = jul,

day = "1",

doi = "10.47626/1516-4446-2023-3037",

language = "English",

volume = "45",

pages = "318--326",

journal = "Brazilian Journal of Psychiatry",

number = "4",

}

Rohrsetzer, F, Balardin, JB, Picon, FA, Sato, JR, Battel, L, Viduani, A, Manfro, PH, Yoon, L, Kohrt, BA, Fisher, H , Mondelli, V, Swartz, J & Kieling, C 2023, 'A magnetic resonance imaging-based morphometric and structural covariance network study of Brazilian adolescents stratified by depression risk', Brazilian Journal of Psychiatry, vol. 45, no. 4, pp. 318-326. https://doi.org/10.47626/1516-4446-2023-3037

TY - JOUR

T1 - A magnetic resonance imaging-based morphometric and structural covariance network study of Brazilian adolescents stratified by depression risk

AU - Rohrsetzer, Fernanda

AU - Balardin, Joana Bisol

AU - Picon, Felipe Almeida

AU - Sato, João Ricardo

AU - Battel, Lucas

AU - Viduani, Anna

AU - Manfro, Pedro H.

AU - Yoon, Leehyun

AU - Kohrt, Brandon A

AU - Fisher, Helen

AU - Mondelli, Valeria

AU - Swartz, Johnna

AU - Kieling, Christian

N1 - Funding Information: HLF was partly supported by the Economic and Social Research Council (ESRC) Centre for Society and Mental Health at King’s College London (ES/S012567/1). VM was supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London, Maudsley National Health Service (NHS) Foundation Trust, and King’s College London. CK is a CNPq researcher and an Academy of Medical Sciences Newton Advanced fellow. The views expressed are those of the authors and do not necessarily reflect the views of the NHS, the NIHR, the Department of Health and Social Care, the ESRC, or King’s College London. Funding Information: The Identifying Depression Early in Adolescence (IDEA) project was funded by an MQ Brighter Futures grant (MQBF/1 IDEA). Additional support was provided by the UK Medical Research Council (MC_PC_MR/R019460/1) and the Academy of Medical Sciences (GCRFNG_ 100281) under the Global Challenges Research Fund. This work is also supported by research grants from Brazilian public funding agencies Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq; 477129/2012-9 and 445828/2014-5), Coordenac¸ão de Aperfeic¸oamento de Pessoal de Nível Superior (CAPES; 62/2014), and Fundac¸ão de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS; 17/2551-0001009-4). Funding Information: JRS receives financial support from Fundac¸ão de Amparo à Pesquisa do Estado de São Paulo (FAPESP; grants 2021/05332-8, 2018/04654-9, and 2018/21934-5). JRS, BAK, and CK are supported by the U.S. National Institute of Mental Health (NIMH; R21MH124072). Funding Information: The Identifying Depression Early in Adolescence (IDEA) project was funded by an MQ Brighter Futures grant (MQBF/1 IDEA). Additional support was provided by the UK Medical Research Council (MC_PC_MR/R019460/1) and the Academy of Medical Sciences (GCRFNG_ 100281) under the Global Challenges Research Fund. This work is also supported by research grants from Brazilian public funding agencies Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq; 477129/2012-9 and 445828/2014-5), Coordenac¸ão de Aperfeic¸oamento de Pessoal de Nível Superior (CAPES; 62/2014), and Fundac¸ão de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS; 17/2551-0001009-4). JRS receives financial support from Fundac¸ão de Amparo à Pesquisa do Estado de São Paulo (FAPESP; grants 2021/05332-8, 2018/04654-9, and 2018/21934-5). JRS, BAK, and CK are supported by the U.S. National Institute of Mental Health (NIMH; R21MH124072). HLF was partly supported by the Economic and Social Research Council (ESRC) Centre for Society and Mental Health at King’s College London (ES/S012567/1). VM was supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London, Maudsley National Health Service (NHS) Foundation Trust, and King’s College London. CK is a CNPq researcher and an Academy of Medical Sciences Newton Advanced fellow. The views expressed are those of the authors and do not necessarily reflect the views of the NHS, the NIHR, the Department of Health and Social Care, the ESRC, or King’s College London. We are extremely grateful to the schools and individuals who participated in this study, and to all members of the IDEA team for their dedication, hard work, and insights. Publisher Copyright: © 2023, Associacao Brasileira de Psiquiatria. All rights reserved.

PY - 2023/7/1

Y1 - 2023/7/1

N2 - Objectives: To explore differences in regional cortical morphometric structure between adolescents at risk for depression or with current depression. Methods: We analyzed cross-sectional structural neuroimaging data from a sample of 150 Brazilian adolescents classified as low-risk (LR) (n=50) or high-risk (HR) for depression (n=50) or with current depression (n=50) through a vertex-based approach with measurements of cortical volume (CV), surface area (SA), and cortical thickness (CT). Differences between groups in subcortical volume and in the organization of networks of structural covariance were also explored. Results: No significant differences in brain structure between groups were observed in whole-brain vertex-wise CV, SA, or CT. Also, no significant differences in subcortical volume were observed between risk groups. In relation to the structural covariance network, there was an indication of an increase in the hippocampus betweenness centrality index in the HR group network compared to the LR and current depression group networks. However, this result was only statistically significant when applying false discovery rate correction for nodes within the affective network. Conclusion: In an adolescent sample recruited using an empirically based composite risk score, no major differences in brain structure were detected according to the risk and presence of depression.

AB - Objectives: To explore differences in regional cortical morphometric structure between adolescents at risk for depression or with current depression. Methods: We analyzed cross-sectional structural neuroimaging data from a sample of 150 Brazilian adolescents classified as low-risk (LR) (n=50) or high-risk (HR) for depression (n=50) or with current depression (n=50) through a vertex-based approach with measurements of cortical volume (CV), surface area (SA), and cortical thickness (CT). Differences between groups in subcortical volume and in the organization of networks of structural covariance were also explored. Results: No significant differences in brain structure between groups were observed in whole-brain vertex-wise CV, SA, or CT. Also, no significant differences in subcortical volume were observed between risk groups. In relation to the structural covariance network, there was an indication of an increase in the hippocampus betweenness centrality index in the HR group network compared to the LR and current depression group networks. However, this result was only statistically significant when applying false discovery rate correction for nodes within the affective network. Conclusion: In an adolescent sample recruited using an empirically based composite risk score, no major differences in brain structure were detected according to the risk and presence of depression.

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U2 - 10.47626/1516-4446-2023-3037

DO - 10.47626/1516-4446-2023-3037

M3 - Article

VL - 45

SP - 318

EP - 326

JO - Brazilian Journal of Psychiatry

JF - Brazilian Journal of Psychiatry

IS - 4

ER -

A magnetic resonance imaging-based morphometric and structural covariance network study of Brazilian adolescents stratified by depression risk

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