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http://hdl.handle.net/2445/184155
Title: | Individual variations in 'brain age' relate to early-life factors more than to longitudinal brain change |
Author: | Vidal Piñeiro, Dídac Wang, Yunpeng Krogsrud, Stine K. Amlien, Inge K. Baaré, William F. C. Bartrés Faz, David Bertram, Lars Brandmaier, Andreas M. Drevon, Christian A Düzel, Sandra Ebmeier, Klaus P. Henson, Richard N. Junqué i Plaja, Carme, 1955- Kievit, Rogier A. Kühn, Simone Leonardsen, Esten Lindenberger, Ulman Madsen, Kathrine Skak Magnussen, Fredrik Mowinckel, Athanasia Monika Nyberg, Lars Roe, James M. Segura i Fàbregas, Bàrbara Smith, Stephen M. Sørensen, Øystein Suri, Sana Westerhausen, René Zalesky, Andrew Zsoldos, Enikő Walhovd, Kristine Beate Fjell, Anders Martin |
Keywords: | Diferències individuals Envelliment cerebral Individual differences Aging brain |
Issue Date: | 10-Nov-2021 |
Publisher: | eLife Sciences |
Abstract: | 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. |
Note: | Reproducció del document publicat a: https://doi.org/10.7554/eLife.69995 |
It is part of: | eLife, 2021, vol. 10, num. e69995 |
URI: | http://hdl.handle.net/2445/184155 |
Related resource: | https://doi.org/10.7554/eLife.69995 https://doi.org/10.7554/eLife.79475 |
ISSN: | 2050-084X |
Appears in Collections: | Articles publicats en revistes (Medicina) Articles publicats en revistes (IDIBAPS: Institut d'investigacions Biomèdiques August Pi i Sunyer) Articles publicats en revistes (Institut de Neurociències (UBNeuro)) Publicacions de projectes de recerca finançats per la UE |
Files in This Item:
File | Description | Size | Format | |
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Original article.pdf | 1.07 MB | Adobe PDF | View/Open | |
Correction.pdf | 2.69 MB | Adobe PDF | View/Open |
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