Abstract
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 7-year changes in indicators derived from blood assays, magnetic resonance imaging brain scans, other-ratings, and self-reports converge among older adults. We included 8 epigenetic biomarkers (incl. 5 epigenetic “clocks”), a BioAge composite from clinical laboratory parameters, brain age, skin age, subjective age, subjective life expectancy, and subjective health horizon. We found moderate associations within aging domains, both cross-sectionally and longitudinally over 7 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.
| Originalsprache | Englisch |
|---|---|
| Aufsatznummer | glae244 |
| Zeitschrift | Journals of Gerontology - Series A Biological Sciences and Medical Sciences |
| Jahrgang | 80 |
| Ausgabenummer | 6 |
| ISSN | 1079-5006 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - 01.06.2025 |
Fördermittel
This article reports data from the Berlin Aging Study II (BASE-II; https://www.base2.mpg.de/en ). The BASE-II research project (Co-PIs are Lars Bertram, Ilja Demuth, Johanna Drewelies, Sandra Düzel, Denis Gerstorf, Ulman Lindenberger, Graham Pawelec, Elisabeth Steinhagen-Thiessen, and Gert G. Wagner) is supported by the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung, BMBF) under grant numbers #16SV5536K, #16SV5537, #16SV5538, #16SV5837, #01UW0808, #01GL1716A, and #01GL1716B. Another source of funding is the Max Planck Institute for Human Development, Berlin, Germany. Additional contributions (eg, equipment, logistics, and personnel) are made from each of the other participating sites. This work was also funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – 460683900. C.M.L. was supported by the Heisenberg program of the German Research Foundation (DFG; LI 2654/4-1).
| Träger | Trägernummer |
|---|---|
| Max-Planck-Gesellschaft | |
| Bundesministerium für Bildung und Forschung | 16SV5536K, 01GL1716B, 01UW0808, 01GL1716A, 16SV5538, 16SV5537, 16SV5837 |
| Deutsche Forschungsgemeinschaft | 460683900, LI 2654/4-1 |
UN SDGs
Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung
-
SDG 3 – Gesundheit und Wohlergehen
Strategische Forschungsbereiche und Zentren
- Querschnittsbereich: Medizinische Genetik
DFG-Fachsystematik
- 2.23-06 Molekulare und zelluläre Neurologie und Neuropathologie
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