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Identification of structural brain alterations in adolescents with depressive symptomatology

INTRODUCTION: Depressive symptoms can emerge as early as childhood and may lead to adverse situations in adulthood. Studies have examined structural brain alternations in individuals with depressive symptoms, but findings remain inconclusive. Furthermore, previous studies have focused on adults or u...

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Autores principales: Bashford-Largo, Johannah, R. Blair, R. James, Blair, Karina S., Dobbertin, Matthew, Dominguez, Ahria, Hatch, Melissa, Bajaj, Sahil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10451038/
https://www.ncbi.nlm.nih.gov/pubmed/37536609
http://dx.doi.org/10.1016/j.brainresbull.2023.110723
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author Bashford-Largo, Johannah
R. Blair, R. James
Blair, Karina S.
Dobbertin, Matthew
Dominguez, Ahria
Hatch, Melissa
Bajaj, Sahil
author_facet Bashford-Largo, Johannah
R. Blair, R. James
Blair, Karina S.
Dobbertin, Matthew
Dominguez, Ahria
Hatch, Melissa
Bajaj, Sahil
author_sort Bashford-Largo, Johannah
collection PubMed
description INTRODUCTION: Depressive symptoms can emerge as early as childhood and may lead to adverse situations in adulthood. Studies have examined structural brain alternations in individuals with depressive symptoms, but findings remain inconclusive. Furthermore, previous studies have focused on adults or used a categorical approach to assess depression. The current study looks to identify grey matter volumes (GMV) that predict depressive symptomatology across a clinically concerning sample of adolescents. METHODS: Structural MRI data were collected from 338 clinically concerning adolescents (mean age = 15.30 SD=2.07; mean IQ = 101.01 SD=12.43; 132 F). Depression symptoms were indexed via the Mood and Feelings Questionnaire (MFQ). Freesurfer was used to parcellate the brain into 68 cortical regions and 14 subcortical regions. GMV was extracted from all 82 brain areas. Multiple linear regression was used to look at the relationship between MFQ scores and region-specific GMV parameter. Follow up regressions were conducted to look at potential effects of psychiatric diagnoses and medication intake. RESULTS: Our regression analysis produced a significant model (R(2) = 0.446, F(86, 251) = 2.348, p < 0.001). Specifically, there was a negative association between GMV of the left parahippocampal (B = −0.203, p = 0.005), right rostral anterior cingulate (B = −0.162, p = 0.049), and right frontal pole (B = −0.147, p = 0.039) and a positive association between GMV of the left bank of the superior temporal sulcus (B = 0.173, p = 0.029). Follow up analyses produced results proximal to the main analysis. CONCLUSIONS: Altered regional brain volumes may serve as biomarkers for the development of depressive symptoms during adolescence. These findings suggest a homogeneity of altered cortical structures in adolescents with depressive symptoms.
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spelling pubmed-104510382023-09-01 Identification of structural brain alterations in adolescents with depressive symptomatology Bashford-Largo, Johannah R. Blair, R. James Blair, Karina S. Dobbertin, Matthew Dominguez, Ahria Hatch, Melissa Bajaj, Sahil Brain Res Bull Article INTRODUCTION: Depressive symptoms can emerge as early as childhood and may lead to adverse situations in adulthood. Studies have examined structural brain alternations in individuals with depressive symptoms, but findings remain inconclusive. Furthermore, previous studies have focused on adults or used a categorical approach to assess depression. The current study looks to identify grey matter volumes (GMV) that predict depressive symptomatology across a clinically concerning sample of adolescents. METHODS: Structural MRI data were collected from 338 clinically concerning adolescents (mean age = 15.30 SD=2.07; mean IQ = 101.01 SD=12.43; 132 F). Depression symptoms were indexed via the Mood and Feelings Questionnaire (MFQ). Freesurfer was used to parcellate the brain into 68 cortical regions and 14 subcortical regions. GMV was extracted from all 82 brain areas. Multiple linear regression was used to look at the relationship between MFQ scores and region-specific GMV parameter. Follow up regressions were conducted to look at potential effects of psychiatric diagnoses and medication intake. RESULTS: Our regression analysis produced a significant model (R(2) = 0.446, F(86, 251) = 2.348, p < 0.001). Specifically, there was a negative association between GMV of the left parahippocampal (B = −0.203, p = 0.005), right rostral anterior cingulate (B = −0.162, p = 0.049), and right frontal pole (B = −0.147, p = 0.039) and a positive association between GMV of the left bank of the superior temporal sulcus (B = 0.173, p = 0.029). Follow up analyses produced results proximal to the main analysis. CONCLUSIONS: Altered regional brain volumes may serve as biomarkers for the development of depressive symptoms during adolescence. These findings suggest a homogeneity of altered cortical structures in adolescents with depressive symptoms. 2023-09 2023-08-01 /pmc/articles/PMC10451038/ /pubmed/37536609 http://dx.doi.org/10.1016/j.brainresbull.2023.110723 Text en https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Bashford-Largo, Johannah
R. Blair, R. James
Blair, Karina S.
Dobbertin, Matthew
Dominguez, Ahria
Hatch, Melissa
Bajaj, Sahil
Identification of structural brain alterations in adolescents with depressive symptomatology
title Identification of structural brain alterations in adolescents with depressive symptomatology
title_full Identification of structural brain alterations in adolescents with depressive symptomatology
title_fullStr Identification of structural brain alterations in adolescents with depressive symptomatology
title_full_unstemmed Identification of structural brain alterations in adolescents with depressive symptomatology
title_short Identification of structural brain alterations in adolescents with depressive symptomatology
title_sort identification of structural brain alterations in adolescents with depressive symptomatology
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10451038/
https://www.ncbi.nlm.nih.gov/pubmed/37536609
http://dx.doi.org/10.1016/j.brainresbull.2023.110723
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