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Calendar age and puberty-related development of regional gray matter volume and white matter tracts during adolescence
BACKGROUND: Adolescence is a critical time for brain development. Findings from previous studies have been inconsistent, failing to distinguish the influence of pubertal status and aging on brain maturation. The current study sought to address these inconsistencies, addressing the trajectories of pu...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7981330/ https://www.ncbi.nlm.nih.gov/pubmed/33471191 http://dx.doi.org/10.1007/s00429-020-02208-1 |
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author | Ando, Ayaka Parzer, Peter Kaess, Michael Schell, Susanne Henze, Romy Delorme, Stefan Stieltjes, Bram Resch, Franz Brunner, Romuald Koenig, Julian |
author_facet | Ando, Ayaka Parzer, Peter Kaess, Michael Schell, Susanne Henze, Romy Delorme, Stefan Stieltjes, Bram Resch, Franz Brunner, Romuald Koenig, Julian |
author_sort | Ando, Ayaka |
collection | PubMed |
description | BACKGROUND: Adolescence is a critical time for brain development. Findings from previous studies have been inconsistent, failing to distinguish the influence of pubertal status and aging on brain maturation. The current study sought to address these inconsistencies, addressing the trajectories of pubertal development and aging by longitudinally tracking structural brain development during adolescence. METHODS: Two cohorts of healthy children were recruited (cohort 1: 9–10 years old; cohort 2: 12–13 years old at baseline). MRI data were acquired for gray matter volume and white matter tract measures. To determine whether age, pubertal status, both or their interaction best modelled longitudinal data, we compared four multi-level linear regression models to the null model (general brain growth indexed by total segmented volume) using Bayesian model selection. RESULTS: Data were collected at baseline (n = 116), 12 months (n = 97) and 24 months (n = 84) after baseline. Findings demonstrated that the development of most regional gray matter volume, and white matter tract measures, were best modelled by age. Interestingly, precentral and paracentral regions of the cortex, as well as the accumbens demonstrated significant preference for the pubertal status model. None of the white matter tract measures were better modelled by pubertal status. Limitations: The major limitation of this study is the two-cohort recruitment. Although this allowed a faster coverage of the age span, a complete per person trajectory over 6 years of development (9–15 years) could not be investigated. CONCLUSIONS: Comparing the impact of age and pubertal status on regional gray matter volume and white matter tract measures, we found age to best predict longitudinal changes. Further longitudinal studies investigating the differential influence of puberty status and age on brain development in more diverse samples are needed to replicate the present results and address mechanisms underlying norm-variants in brain development. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00429-020-02208-1. |
format | Online Article Text |
id | pubmed-7981330 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-79813302021-04-12 Calendar age and puberty-related development of regional gray matter volume and white matter tracts during adolescence Ando, Ayaka Parzer, Peter Kaess, Michael Schell, Susanne Henze, Romy Delorme, Stefan Stieltjes, Bram Resch, Franz Brunner, Romuald Koenig, Julian Brain Struct Funct Short Communication BACKGROUND: Adolescence is a critical time for brain development. Findings from previous studies have been inconsistent, failing to distinguish the influence of pubertal status and aging on brain maturation. The current study sought to address these inconsistencies, addressing the trajectories of pubertal development and aging by longitudinally tracking structural brain development during adolescence. METHODS: Two cohorts of healthy children were recruited (cohort 1: 9–10 years old; cohort 2: 12–13 years old at baseline). MRI data were acquired for gray matter volume and white matter tract measures. To determine whether age, pubertal status, both or their interaction best modelled longitudinal data, we compared four multi-level linear regression models to the null model (general brain growth indexed by total segmented volume) using Bayesian model selection. RESULTS: Data were collected at baseline (n = 116), 12 months (n = 97) and 24 months (n = 84) after baseline. Findings demonstrated that the development of most regional gray matter volume, and white matter tract measures, were best modelled by age. Interestingly, precentral and paracentral regions of the cortex, as well as the accumbens demonstrated significant preference for the pubertal status model. None of the white matter tract measures were better modelled by pubertal status. Limitations: The major limitation of this study is the two-cohort recruitment. Although this allowed a faster coverage of the age span, a complete per person trajectory over 6 years of development (9–15 years) could not be investigated. CONCLUSIONS: Comparing the impact of age and pubertal status on regional gray matter volume and white matter tract measures, we found age to best predict longitudinal changes. Further longitudinal studies investigating the differential influence of puberty status and age on brain development in more diverse samples are needed to replicate the present results and address mechanisms underlying norm-variants in brain development. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00429-020-02208-1. Springer Berlin Heidelberg 2021-01-20 2021 /pmc/articles/PMC7981330/ /pubmed/33471191 http://dx.doi.org/10.1007/s00429-020-02208-1 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Short Communication Ando, Ayaka Parzer, Peter Kaess, Michael Schell, Susanne Henze, Romy Delorme, Stefan Stieltjes, Bram Resch, Franz Brunner, Romuald Koenig, Julian Calendar age and puberty-related development of regional gray matter volume and white matter tracts during adolescence |
title | Calendar age and puberty-related development of regional gray matter volume and white matter tracts during adolescence |
title_full | Calendar age and puberty-related development of regional gray matter volume and white matter tracts during adolescence |
title_fullStr | Calendar age and puberty-related development of regional gray matter volume and white matter tracts during adolescence |
title_full_unstemmed | Calendar age and puberty-related development of regional gray matter volume and white matter tracts during adolescence |
title_short | Calendar age and puberty-related development of regional gray matter volume and white matter tracts during adolescence |
title_sort | calendar age and puberty-related development of regional gray matter volume and white matter tracts during adolescence |
topic | Short Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7981330/ https://www.ncbi.nlm.nih.gov/pubmed/33471191 http://dx.doi.org/10.1007/s00429-020-02208-1 |
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