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Individual variations in ‘brain age’ relate to early-life factors more than to longitudinal brain change
Brain age is a widely used index for quantifying individuals’ brain health as deviation from a normative brain aging trajectory. Higher-than-expected brain age is thought partially to reflect above-average rate of brain aging. Here, we explicitly tested this assumption in two independent large test...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8580481/ https://www.ncbi.nlm.nih.gov/pubmed/34756163 http://dx.doi.org/10.7554/eLife.69995 |
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author | Vidal-Pineiro, Didac Wang, Yunpeng Krogsrud, Stine K Amlien, Inge K Baaré, William FC Bartres-Faz, David Bertram, Lars Brandmaier, Andreas M Drevon, Christian A Düzel, Sandra Ebmeier, Klaus Henson, Richard N Junqué, Carme Kievit, Rogier Andrew Kühn, Simone Leonardsen, Esten Lindenberger, Ulman Madsen, Kathrine S Magnussen, Fredrik Mowinckel, Athanasia Monika Nyberg, Lars Roe, James M Segura, Barbara Smith, Stephen M Sørensen, Øystein Suri, Sana Westerhausen, Rene Zalesky, Andrew Zsoldos, Enikő Walhovd, Kristine Beate Fjell, Anders |
author_facet | Vidal-Pineiro, Didac Wang, Yunpeng Krogsrud, Stine K Amlien, Inge K Baaré, William FC Bartres-Faz, David Bertram, Lars Brandmaier, Andreas M Drevon, Christian A Düzel, Sandra Ebmeier, Klaus Henson, Richard N Junqué, Carme Kievit, Rogier Andrew Kühn, Simone Leonardsen, Esten Lindenberger, Ulman Madsen, Kathrine S Magnussen, Fredrik Mowinckel, Athanasia Monika Nyberg, Lars Roe, James M Segura, Barbara Smith, Stephen M Sørensen, Øystein Suri, Sana Westerhausen, Rene Zalesky, Andrew Zsoldos, Enikő Walhovd, Kristine Beate Fjell, Anders |
author_sort | Vidal-Pineiro, Didac |
collection | PubMed |
description | Brain age is a widely used index for quantifying individuals’ brain health as deviation from a normative brain aging trajectory. Higher-than-expected brain age is thought partially to reflect above-average rate of brain aging. Here, we explicitly tested this assumption in two independent large test datasets (UK Biobank [main] and Lifebrain [replication]; longitudinal observations ≈ 2750 and 4200) by assessing the relationship between cross-sectional and longitudinal estimates of brain age. Brain age models were estimated in two different training datasets (n ≈ 38,000 [main] and 1800 individuals [replication]) based on brain structural features. The results showed no association between cross-sectional brain age and the rate of brain change measured longitudinally. Rather, brain age in adulthood was associated with the congenital factors of birth weight and polygenic scores of brain age, assumed to reflect a constant, lifelong influence on brain structure from early life. The results call for nuanced interpretations of cross-sectional indices of the aging brain and question their validity as markers of ongoing within-person changes of the aging brain. Longitudinal imaging data should be preferred whenever the goal is to understand individual change trajectories of brain and cognition in aging. |
format | Online Article Text |
id | pubmed-8580481 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-85804812021-11-12 Individual variations in ‘brain age’ relate to early-life factors more than to longitudinal brain change Vidal-Pineiro, Didac Wang, Yunpeng Krogsrud, Stine K Amlien, Inge K Baaré, William FC Bartres-Faz, David Bertram, Lars Brandmaier, Andreas M Drevon, Christian A Düzel, Sandra Ebmeier, Klaus Henson, Richard N Junqué, Carme Kievit, Rogier Andrew Kühn, Simone Leonardsen, Esten Lindenberger, Ulman Madsen, Kathrine S Magnussen, Fredrik Mowinckel, Athanasia Monika Nyberg, Lars Roe, James M Segura, Barbara Smith, Stephen M Sørensen, Øystein Suri, Sana Westerhausen, Rene Zalesky, Andrew Zsoldos, Enikő Walhovd, Kristine Beate Fjell, Anders eLife Neuroscience Brain age is a widely used index for quantifying individuals’ brain health as deviation from a normative brain aging trajectory. Higher-than-expected brain age is thought partially to reflect above-average rate of brain aging. Here, we explicitly tested this assumption in two independent large test datasets (UK Biobank [main] and Lifebrain [replication]; longitudinal observations ≈ 2750 and 4200) by assessing the relationship between cross-sectional and longitudinal estimates of brain age. Brain age models were estimated in two different training datasets (n ≈ 38,000 [main] and 1800 individuals [replication]) based on brain structural features. The results showed no association between cross-sectional brain age and the rate of brain change measured longitudinally. Rather, brain age in adulthood was associated with the congenital factors of birth weight and polygenic scores of brain age, assumed to reflect a constant, lifelong influence on brain structure from early life. The results call for nuanced interpretations of cross-sectional indices of the aging brain and question their validity as markers of ongoing within-person changes of the aging brain. Longitudinal imaging data should be preferred whenever the goal is to understand individual change trajectories of brain and cognition in aging. eLife Sciences Publications, Ltd 2021-11-10 /pmc/articles/PMC8580481/ /pubmed/34756163 http://dx.doi.org/10.7554/eLife.69995 Text en © 2021, Vidal-Pineiro et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Neuroscience Vidal-Pineiro, Didac Wang, Yunpeng Krogsrud, Stine K Amlien, Inge K Baaré, William FC Bartres-Faz, David Bertram, Lars Brandmaier, Andreas M Drevon, Christian A Düzel, Sandra Ebmeier, Klaus Henson, Richard N Junqué, Carme Kievit, Rogier Andrew Kühn, Simone Leonardsen, Esten Lindenberger, Ulman Madsen, Kathrine S Magnussen, Fredrik Mowinckel, Athanasia Monika Nyberg, Lars Roe, James M Segura, Barbara Smith, Stephen M Sørensen, Øystein Suri, Sana Westerhausen, Rene Zalesky, Andrew Zsoldos, Enikő Walhovd, Kristine Beate Fjell, Anders Individual variations in ‘brain age’ relate to early-life factors more than to longitudinal brain change |
title | Individual variations in ‘brain age’ relate to early-life factors more than to longitudinal brain change |
title_full | Individual variations in ‘brain age’ relate to early-life factors more than to longitudinal brain change |
title_fullStr | Individual variations in ‘brain age’ relate to early-life factors more than to longitudinal brain change |
title_full_unstemmed | Individual variations in ‘brain age’ relate to early-life factors more than to longitudinal brain change |
title_short | Individual variations in ‘brain age’ relate to early-life factors more than to longitudinal brain change |
title_sort | individual variations in ‘brain age’ relate to early-life factors more than to longitudinal brain change |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8580481/ https://www.ncbi.nlm.nih.gov/pubmed/34756163 http://dx.doi.org/10.7554/eLife.69995 |
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