There are multiple clocks that time us: Cross-sectional and longitudinal associations among 14 alternative indicators of age and aging.

BASE–II age indicator ageing biological age epigenetic clock

Journal

The journals of gerontology. Series A, Biological sciences and medical sciences
ISSN: 1758-535X
Titre abrégé: J Gerontol A Biol Sci Med Sci
Pays: United States
ID NLM: 9502837

Informations de publication

Date de publication:
09 Oct 2024
Historique:
received: 19 11 2023
medline: 9 10 2024
pubmed: 9 10 2024
entrez: 9 10 2024
Statut: aheadofprint

Résumé

Aging is a complex process influenced by mechanisms operating at numerous levels of functioning. Multiple biomarkers of age have been identified, yet we know little about how the different alternative age indicators are intertwined. In the Berlin Aging Study II (nmin= 328; nmax= 1,517, women = 51%; 14.27 years of education), we examined how levels and seven-year changes in indicators derived from blood assays, MRI brain scans, other-ratings, and self-reports converge among older adults. We included eight epigenetic biomarkers (incl. five epigenetic "clocks"), a BioAge composite from clinical laboratory parameters, brain age, skin age, subjective age, subjective life expectancy, and future health horizon. We found moderate associations within aging domains, both cross-sectionally and longitudinally over seven years. However, associations across different domains were infrequent and modest. Notably, participants with older BioAge had correspondingly older epigenetic ages. Our results suggest that different aging clocks are only loosely interconnected and that more specific measures are needed to differentiate healthy from unhealthy aging.

Identifiants

pubmed: 39383103
pii: 7816222
doi: 10.1093/gerona/glae244
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press on behalf of The Gerontological Society of America.

Auteurs

Johanna Drewelies (J)

Max Planck Institute for Human Development Berlin.

Jan Homann (J)

Institute of Epidemiology and Social Medicine, University of Münster.

Valentin Max Vetter (VM)

Charite - Universitätsmedizin Berlin.

Sandra Duezel (S)

Charite - Universitätsmedizin Berlin.

Simone Kühn (S)

Max Planck Institute for Human Development Berlin.
Max Planck UCL Centre for Computational Psychiatry and Ageing Research.

Laura Deecke (L)

Institute of Epidemiology and Social Medicine, University of Münster.

Elisabeth Steinhagen-Thiessen (E)

Charite - Universitätsmedizin Berlin.

Philippe Jawinski (P)

Humboldt Universität zu Berlin.

Sebastian Markett (S)

Humboldt Universität zu Berlin.

Ulman Lindenberger (U)

Max Planck Institute for Human Development Berlin.
Max Planck UCL Centre for Computational Psychiatry and Ageing Research.

Christina M Lill (CM)

Institute of Epidemiology and Social Medicine, University of Münster.
Ageing Epidemiology Unit, School of Public Health, Imperial College London.

Ilja Demuth (I)

Charite - Universitätsmedizin Berlin.

Denis Gerstorf (D)

Humboldt Universität zu Berlin.
German Institute for Economic Research, DIW Berlin.

Classifications MeSH