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Associations between age and gray matter volume in anatomical brain networks in middle-aged to older adults

Aging is associated with cognitive decline, diminished brain function, regional brain atrophy, and disrupted structural and functional brain connectivity. Understanding brain networks in aging is essential, as brain function depends on large-scale distributed networks. Little is known of structural...

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Autores principales: Hafkemeijer, Anne, Altmann-Schneider, Irmhild, de Craen, Anton J M, Slagboom, P Eline, van der Grond, Jeroen, Rombouts, Serge A R B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BlackWell Publishing Ltd 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4326918/
https://www.ncbi.nlm.nih.gov/pubmed/25257192
http://dx.doi.org/10.1111/acel.12271
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author Hafkemeijer, Anne
Altmann-Schneider, Irmhild
de Craen, Anton J M
Slagboom, P Eline
van der Grond, Jeroen
Rombouts, Serge A R B
author_facet Hafkemeijer, Anne
Altmann-Schneider, Irmhild
de Craen, Anton J M
Slagboom, P Eline
van der Grond, Jeroen
Rombouts, Serge A R B
author_sort Hafkemeijer, Anne
collection PubMed
description Aging is associated with cognitive decline, diminished brain function, regional brain atrophy, and disrupted structural and functional brain connectivity. Understanding brain networks in aging is essential, as brain function depends on large-scale distributed networks. Little is known of structural covariance networks to study inter-regional gray matter anatomical associations in aging. Here, we investigate anatomical brain networks based on structural covariance of gray matter volume among 370 middle-aged to older adults of 45–85 years. For each of 370 subjects, we acquired a T1-weighted anatomical MRI scan. After segmentation of structural MRI scans, nine anatomical networks were defined based on structural covariance of gray matter volume among subjects. We analyzed associations between age and gray matter volume in anatomical networks using linear regression analyses. Age was negatively associated with gray matter volume in four anatomical networks (P < 0.001, corrected): a subcortical network, sensorimotor network, posterior cingulate network, and an anterior cingulate network. Age was not significantly associated with gray matter volume in five networks: temporal network, auditory network, and three cerebellar networks. These results were independent of gender and white matter hyperintensities. Gray matter volume decreases with age in networks containing subcortical structures, sensorimotor structures, posterior, and anterior cingulate cortices. Gray matter volume in temporal, auditory, and cerebellar networks remains relatively unaffected with advancing age.
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spelling pubmed-43269182015-02-19 Associations between age and gray matter volume in anatomical brain networks in middle-aged to older adults Hafkemeijer, Anne Altmann-Schneider, Irmhild de Craen, Anton J M Slagboom, P Eline van der Grond, Jeroen Rombouts, Serge A R B Aging Cell Original Articles Aging is associated with cognitive decline, diminished brain function, regional brain atrophy, and disrupted structural and functional brain connectivity. Understanding brain networks in aging is essential, as brain function depends on large-scale distributed networks. Little is known of structural covariance networks to study inter-regional gray matter anatomical associations in aging. Here, we investigate anatomical brain networks based on structural covariance of gray matter volume among 370 middle-aged to older adults of 45–85 years. For each of 370 subjects, we acquired a T1-weighted anatomical MRI scan. After segmentation of structural MRI scans, nine anatomical networks were defined based on structural covariance of gray matter volume among subjects. We analyzed associations between age and gray matter volume in anatomical networks using linear regression analyses. Age was negatively associated with gray matter volume in four anatomical networks (P < 0.001, corrected): a subcortical network, sensorimotor network, posterior cingulate network, and an anterior cingulate network. Age was not significantly associated with gray matter volume in five networks: temporal network, auditory network, and three cerebellar networks. These results were independent of gender and white matter hyperintensities. Gray matter volume decreases with age in networks containing subcortical structures, sensorimotor structures, posterior, and anterior cingulate cortices. Gray matter volume in temporal, auditory, and cerebellar networks remains relatively unaffected with advancing age. BlackWell Publishing Ltd 2014-12 2014-09-25 /pmc/articles/PMC4326918/ /pubmed/25257192 http://dx.doi.org/10.1111/acel.12271 Text en © 2014 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd. http://creativecommons.org/licenses/by/3.0/ This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Hafkemeijer, Anne
Altmann-Schneider, Irmhild
de Craen, Anton J M
Slagboom, P Eline
van der Grond, Jeroen
Rombouts, Serge A R B
Associations between age and gray matter volume in anatomical brain networks in middle-aged to older adults
title Associations between age and gray matter volume in anatomical brain networks in middle-aged to older adults
title_full Associations between age and gray matter volume in anatomical brain networks in middle-aged to older adults
title_fullStr Associations between age and gray matter volume in anatomical brain networks in middle-aged to older adults
title_full_unstemmed Associations between age and gray matter volume in anatomical brain networks in middle-aged to older adults
title_short Associations between age and gray matter volume in anatomical brain networks in middle-aged to older adults
title_sort associations between age and gray matter volume in anatomical brain networks in middle-aged to older adults
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4326918/
https://www.ncbi.nlm.nih.gov/pubmed/25257192
http://dx.doi.org/10.1111/acel.12271
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