A hematology-based clock derived from the Study of Longitudinal Aging in Mice to estimate biological age.
Journal
Nature aging
ISSN: 2662-8465
Titre abrégé: Nat Aging
Pays: United States
ID NLM: 101773306
Informations de publication
Date de publication:
18 Oct 2024
18 Oct 2024
Historique:
received:
03
06
2023
accepted:
24
09
2024
medline:
19
10
2024
pubmed:
19
10
2024
entrez:
18
10
2024
Statut:
aheadofprint
Résumé
Biological clocks and other molecular biomarkers of aging are difficult to implement widely in a clinical setting. In this study, we used routinely collected hematological markers to develop an aging clock to predict blood age and determine whether the difference between predicted age and chronologic age (aging gap) is associated with advanced aging in mice. Data from 2,562 mice of both sexes and three strains were drawn from two longitudinal studies of aging. Eight hematological variables and two metabolic indices were collected longitudinally (12,010 observations). Blood age was predicted using a deep neural network. Blood age was significantly correlated with chronological age, and aging gap was positively associated with mortality risk and frailty. Platelets were identified as the strongest age predictor by the deep neural network. An aging clock based on routinely collected blood measures has the potential to provide a practical clinical tool to better understand individual variability in the aging process.
Identifiants
pubmed: 39424993
doi: 10.1038/s43587-024-00728-7
pii: 10.1038/s43587-024-00728-7
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.
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