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Age-dependent brain morphometry in Major Depressive disorder
BACKGROUND: Major depressive disorder (MDD) is a complex disorder that affects nearly 264 million people worldwide. Structural brain abnormalities in multiple neuroanatomical networks have been implicated in the etiology of MDD, but the degree to which MDD affects brain structure during early to lat...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8718744/ https://www.ncbi.nlm.nih.gov/pubmed/34959051 http://dx.doi.org/10.1016/j.nicl.2021.102924 |
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author | Myoraku, Alison Lang, Adam Taylor, Charles T. Scott Mackin, R. Meyerhoff, Dieter J. Mueller, Susanne Strigo, Irina A. Tosun, Duygu |
author_facet | Myoraku, Alison Lang, Adam Taylor, Charles T. Scott Mackin, R. Meyerhoff, Dieter J. Mueller, Susanne Strigo, Irina A. Tosun, Duygu |
author_sort | Myoraku, Alison |
collection | PubMed |
description | BACKGROUND: Major depressive disorder (MDD) is a complex disorder that affects nearly 264 million people worldwide. Structural brain abnormalities in multiple neuroanatomical networks have been implicated in the etiology of MDD, but the degree to which MDD affects brain structure during early to late adulthood is unclear. METHODS: We examined morphometry of brain regions commonly implicated in MDD, including the amygdala, hippocampus, anterior cingulate gyrus, lateral orbitofrontal gyrus, subgenual cortex, and insular cortex subregions, from early to late adulthood. Harmonized measures for gray matter (GM) volume and cortical thickness of each region were estimated cross-sectionally for 305 healthy controls (CTLs) and 247 individuals with MDD (MDDs), collated from four research cohorts. We modeled the nonlinear associations of age with GM volume and cortical thickness using generalized additive modeling and tested for age-dependent group differences. RESULTS: Overall, all investigated regions exhibited smaller GM volume and thinner cortical measures with increasing age. Compared to age matched CTLs, MDDs had thicker cortices and greater GM volume from early adulthood until early middle age (average 35 years), but thinner cortices and smaller GM volume during and after middle age in the lateral orbital gyrus and all insular subregions. Deviations of the MDD and CTL models for both GM volume and cortical thickness in these regions started as early as age 18. CONCLUSIONS: The analyses revealed that brain morphometry differences between MDDs and CTLs are dependent on age and brain region. The significant age-by-group interactions in the lateral orbital frontal gyrus and insular subregions make these regions potential targets for future longitudinal studies of MDD. |
format | Online Article Text |
id | pubmed-8718744 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-87187442022-01-06 Age-dependent brain morphometry in Major Depressive disorder Myoraku, Alison Lang, Adam Taylor, Charles T. Scott Mackin, R. Meyerhoff, Dieter J. Mueller, Susanne Strigo, Irina A. Tosun, Duygu Neuroimage Clin Regular Article BACKGROUND: Major depressive disorder (MDD) is a complex disorder that affects nearly 264 million people worldwide. Structural brain abnormalities in multiple neuroanatomical networks have been implicated in the etiology of MDD, but the degree to which MDD affects brain structure during early to late adulthood is unclear. METHODS: We examined morphometry of brain regions commonly implicated in MDD, including the amygdala, hippocampus, anterior cingulate gyrus, lateral orbitofrontal gyrus, subgenual cortex, and insular cortex subregions, from early to late adulthood. Harmonized measures for gray matter (GM) volume and cortical thickness of each region were estimated cross-sectionally for 305 healthy controls (CTLs) and 247 individuals with MDD (MDDs), collated from four research cohorts. We modeled the nonlinear associations of age with GM volume and cortical thickness using generalized additive modeling and tested for age-dependent group differences. RESULTS: Overall, all investigated regions exhibited smaller GM volume and thinner cortical measures with increasing age. Compared to age matched CTLs, MDDs had thicker cortices and greater GM volume from early adulthood until early middle age (average 35 years), but thinner cortices and smaller GM volume during and after middle age in the lateral orbital gyrus and all insular subregions. Deviations of the MDD and CTL models for both GM volume and cortical thickness in these regions started as early as age 18. CONCLUSIONS: The analyses revealed that brain morphometry differences between MDDs and CTLs are dependent on age and brain region. The significant age-by-group interactions in the lateral orbital frontal gyrus and insular subregions make these regions potential targets for future longitudinal studies of MDD. Elsevier 2021-12-23 /pmc/articles/PMC8718744/ /pubmed/34959051 http://dx.doi.org/10.1016/j.nicl.2021.102924 Text en © 2021 Published by Elsevier Inc. https://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 | Regular Article Myoraku, Alison Lang, Adam Taylor, Charles T. Scott Mackin, R. Meyerhoff, Dieter J. Mueller, Susanne Strigo, Irina A. Tosun, Duygu Age-dependent brain morphometry in Major Depressive disorder |
title | Age-dependent brain morphometry in Major Depressive disorder |
title_full | Age-dependent brain morphometry in Major Depressive disorder |
title_fullStr | Age-dependent brain morphometry in Major Depressive disorder |
title_full_unstemmed | Age-dependent brain morphometry in Major Depressive disorder |
title_short | Age-dependent brain morphometry in Major Depressive disorder |
title_sort | age-dependent brain morphometry in major depressive disorder |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8718744/ https://www.ncbi.nlm.nih.gov/pubmed/34959051 http://dx.doi.org/10.1016/j.nicl.2021.102924 |
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