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Three major dimensions of human brain cortical ageing in relation to cognitive decline across the eighth decade of life
Different brain regions can be grouped together, based on cross-sectional correlations among their cortical characteristics; this patterning has been used to make inferences about ageing processes. However, cross-sectional brain data conflate information on ageing with patterns that are present thro...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8254824/ https://www.ncbi.nlm.nih.gov/pubmed/33398085 http://dx.doi.org/10.1038/s41380-020-00975-1 |
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author | Cox, S. R. Harris, M. A. Ritchie, S. J. Buchanan, C. R. Valdés Hernández, M. C. Corley, J. Taylor, A. M. Madole, J. W. Harris, S. E. Whalley, H. C. McIntosh, A. M. Russ, T. C. Bastin, M. E. Wardlaw, J. M. Deary, I. J. Tucker-Drob, E. M. |
author_facet | Cox, S. R. Harris, M. A. Ritchie, S. J. Buchanan, C. R. Valdés Hernández, M. C. Corley, J. Taylor, A. M. Madole, J. W. Harris, S. E. Whalley, H. C. McIntosh, A. M. Russ, T. C. Bastin, M. E. Wardlaw, J. M. Deary, I. J. Tucker-Drob, E. M. |
author_sort | Cox, S. R. |
collection | PubMed |
description | Different brain regions can be grouped together, based on cross-sectional correlations among their cortical characteristics; this patterning has been used to make inferences about ageing processes. However, cross-sectional brain data conflate information on ageing with patterns that are present throughout life. We characterised brain cortical ageing across the eighth decade of life in a longitudinal ageing cohort, at ages ~73, ~76, and ~79 years, with a total of 1376 MRI scans. Volumetric changes among cortical regions of interest (ROIs) were more strongly correlated (average r = 0.805, SD = 0.252) than were cross-sectional volumes of the same ROIs (average r = 0.350, SD = 0.178). We identified a broad, cortex-wide, dimension of atrophy that explained 66% of the variance in longitudinal changes across the cortex. Our modelling also discovered more specific fronto-temporal and occipito-parietal dimensions that were orthogonal to the general factor and together explained an additional 20% of the variance. The general factor was associated with declines in general cognitive ability (r = 0.431, p < 0.001) and in the domains of visuospatial ability (r = 0.415, p = 0.002), processing speed (r = 0.383, p < 0.001) and memory (r = 0.372, p < 0.001). Individual differences in brain cortical atrophy with ageing are manifest across three broad dimensions of the cerebral cortex, the most general of which is linked with cognitive declines across domains. Longitudinal approaches are invaluable for distinguishing lifelong patterns of brain-behaviour associations from patterns that are specific to aging. |
format | Online Article Text |
id | pubmed-8254824 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-82548242021-09-16 Three major dimensions of human brain cortical ageing in relation to cognitive decline across the eighth decade of life Cox, S. R. Harris, M. A. Ritchie, S. J. Buchanan, C. R. Valdés Hernández, M. C. Corley, J. Taylor, A. M. Madole, J. W. Harris, S. E. Whalley, H. C. McIntosh, A. M. Russ, T. C. Bastin, M. E. Wardlaw, J. M. Deary, I. J. Tucker-Drob, E. M. Mol Psychiatry Article Different brain regions can be grouped together, based on cross-sectional correlations among their cortical characteristics; this patterning has been used to make inferences about ageing processes. However, cross-sectional brain data conflate information on ageing with patterns that are present throughout life. We characterised brain cortical ageing across the eighth decade of life in a longitudinal ageing cohort, at ages ~73, ~76, and ~79 years, with a total of 1376 MRI scans. Volumetric changes among cortical regions of interest (ROIs) were more strongly correlated (average r = 0.805, SD = 0.252) than were cross-sectional volumes of the same ROIs (average r = 0.350, SD = 0.178). We identified a broad, cortex-wide, dimension of atrophy that explained 66% of the variance in longitudinal changes across the cortex. Our modelling also discovered more specific fronto-temporal and occipito-parietal dimensions that were orthogonal to the general factor and together explained an additional 20% of the variance. The general factor was associated with declines in general cognitive ability (r = 0.431, p < 0.001) and in the domains of visuospatial ability (r = 0.415, p = 0.002), processing speed (r = 0.383, p < 0.001) and memory (r = 0.372, p < 0.001). Individual differences in brain cortical atrophy with ageing are manifest across three broad dimensions of the cerebral cortex, the most general of which is linked with cognitive declines across domains. Longitudinal approaches are invaluable for distinguishing lifelong patterns of brain-behaviour associations from patterns that are specific to aging. Nature Publishing Group UK 2021-01-04 2021 /pmc/articles/PMC8254824/ /pubmed/33398085 http://dx.doi.org/10.1038/s41380-020-00975-1 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Cox, S. R. Harris, M. A. Ritchie, S. J. Buchanan, C. R. Valdés Hernández, M. C. Corley, J. Taylor, A. M. Madole, J. W. Harris, S. E. Whalley, H. C. McIntosh, A. M. Russ, T. C. Bastin, M. E. Wardlaw, J. M. Deary, I. J. Tucker-Drob, E. M. Three major dimensions of human brain cortical ageing in relation to cognitive decline across the eighth decade of life |
title | Three major dimensions of human brain cortical ageing in relation to cognitive decline across the eighth decade of life |
title_full | Three major dimensions of human brain cortical ageing in relation to cognitive decline across the eighth decade of life |
title_fullStr | Three major dimensions of human brain cortical ageing in relation to cognitive decline across the eighth decade of life |
title_full_unstemmed | Three major dimensions of human brain cortical ageing in relation to cognitive decline across the eighth decade of life |
title_short | Three major dimensions of human brain cortical ageing in relation to cognitive decline across the eighth decade of life |
title_sort | three major dimensions of human brain cortical ageing in relation to cognitive decline across the eighth decade of life |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8254824/ https://www.ncbi.nlm.nih.gov/pubmed/33398085 http://dx.doi.org/10.1038/s41380-020-00975-1 |
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