Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations.
Journal
Nature medicine
ISSN: 1546-170X
Titre abrégé: Nat Med
Pays: United States
ID NLM: 9502015
Informations de publication
Date de publication:
26 Aug 2024
26 Aug 2024
Historique:
received:
22
03
2024
accepted:
22
07
2024
medline:
27
8
2024
pubmed:
27
8
2024
entrez:
26
8
2024
Statut:
aheadofprint
Résumé
Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex and neurodegeneration) on the brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American and Caribbean countries (LAC) and 8 non-LAC countries). Based on higher-order interactions, we developed a brain-age gap deep learning architecture for functional magnetic resonance imaging (2,953) and electroencephalography (2,353). The datasets comprised healthy controls and individuals with mild cognitive impairment, Alzheimer disease and behavioral variant frontotemporal dementia. LAC models evidenced older brain ages (functional magnetic resonance imaging: mean directional error = 5.60, root mean square error (r.m.s.e.) = 11.91; electroencephalography: mean directional error = 5.34, r.m.s.e. = 9.82) associated with frontoposterior networks compared with non-LAC models. Structural socioeconomic inequality, pollution and health disparities were influential predictors of increased brain-age gaps, especially in LAC (R² = 0.37, F² = 0.59, r.m.s.e. = 6.9). An ascending brain-age gap from healthy controls to mild cognitive impairment to Alzheimer disease was found. In LAC, we observed larger brain-age gaps in females in control and Alzheimer disease groups compared with the respective males. The results were not explained by variations in signal quality, demographics or acquisition methods. These findings provide a quantitative framework capturing the diversity of accelerated brain aging.
Identifiants
pubmed: 39187698
doi: 10.1038/s41591-024-03209-x
pii: 10.1038/s41591-024-03209-x
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : NIA NIH HHS
ID : R01 AG057234
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG075775
Pays : United States
Organisme : John E. Fogarty Foundation for Persons with Intellectual and Developmental Disabilities
ID : R01AG083799
Organisme : Alzheimer's Association
ID : SG-20-725707
Pays : United States
Informations de copyright
© 2024. The Author(s).
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