An MRI-based morphometric and structural covariance network study of Brazilian adolescents stratified by depression risk

Fernanda Rohrsetzer, Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil. Child and Adolescent Psychiatry Division, Hospital de Clínicas de Porto Alegre (HCPA), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Joana Bisol Balardin, Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil. Child and Adolescent Psychiatry Division, Hospital de Clínicas de Porto Alegre (HCPA), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Felipe Picon, Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil. Child and Adolescent Psychiatry Division, Hospital de Clínicas de Porto Alegre (HCPA), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
João Ricardo Sato, Center of Mathematics, Computing and Cognition - Universidade Federal do ABC, São Paulo, Brazil.
Lucas Battel, Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil. Child and Adolescent Psychiatry Division, Hospital de Clínicas de Porto Alegre (HCPA), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Anna Viduani, Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil. Child and Adolescent Psychiatry Division, Hospital de Clínicas de Porto Alegre (HCPA), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Pedro Henrique Manfro, Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil. Child and Adolescent Psychiatry Division, Hospital de Clínicas de Porto Alegre (HCPA), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Leehyun Yoon, Department of Human Ecology, University of California, Davis, Davis, CA, United States.
Brandon A. Kohrt, Division of Global Mental Health, Department of Psychiatry, School of Medicine and Health Sciences, The George Washington University, Washington, DC, United States.
Helen L. Fisher, King's College London, Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom. ESRC Centre for Society and Mental Health, King's College London, United Kingdom.
Valeria Mondelli, King's College London, Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom. National Institute for Health Research Mental Health Biomedical Research Centre, South London and Maudsley NHS Foundation Trust and King's College London, London, United Kingdom.
Johnna R. Swartz, Department of Human Ecology, University of California, Davis, Davis, CA, United States.
Christian Kieling, Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil. Child and Adolescent Psychiatry Division, Hospital de Clínicas de Porto Alegre (HCPA), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.

Document Type

Journal Article

Publication Date

5-27-2023

Journal

Revista brasileira de psiquiatria (Sao Paulo, Brazil : 1999)

DOI

10.47626/1516-4446-2023-3037

Keywords

Adolescent; depression; methods; neuroimaging/structural; risk factors

Abstract

OBJECTIVE: 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 (n=50) or high-risk for depression (n=50) or with current depression (n=50) through a vertex-based approach with measurements of cortical volume, surface area and thickness. Differences between groups in subcortical volumes 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 cortical volume, surface area or thickness. 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 high-risk group network compared to the low-risk 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.

Department

Psychiatry and Behavioral Sciences

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