Marioni, RE;
Suderman, M;
Chen, BH;
Horvath, S;
Bandinelli, S;
Morris, T;
Beck, S;
... Hägg, S; + view all
(2019)
Tracking the Epigenetic Clock Across the Human Life Course: A Meta-analysis of Longitudinal Cohort Data.
The Journals of Gerontology: Series A
, 74
(1)
pp. 57-61.
10.1093/gerona/gly060.
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Abstract
Background: Epigenetic clocks based on DNA methylation yield high correlations with chronological age in cross-sectional data. Due to a paucity of longitudinal data, it is not known how Δage (epigenetic age - chronological age) changes over time or if it remains constant from childhood to old age. Here, we investigate this using longitudinal DNA methylation data from five datasets, covering most of the human life course. Methods: Two measures of the epigenetic clock (Hannum and Horvath) are used to calculate Δage in the following cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC) offspring (n = 986, total age-range 7-19 years, 2 waves), ALSPAC mothers (n = 982, 16-60 years, 2 waves), InCHIANTI (n = 460, 21-100 years, 2 waves), SATSA (n = 373, 48-99 years, 5 waves), Lothian Birth Cohort 1936 (n = 1,054, 70-76 years, 3 waves), and Lothian Birth Cohort 1921 (n = 476, 79-90 years, 3 waves). Linear mixed models were used to track longitudinal change in Δage within each cohort. Results: For both epigenetic age measures, Δage showed a declining trend in almost all of the cohorts. The correlation between Δage across waves ranged from 0.22 to 0.82 for Horvath and 0.25 to 0.71 for Hannum, with stronger associations in samples collected closer in time. Conclusions: Epigenetic age increases at a slower rate than chronological age across the life course, especially in the oldest population. Some of the effect is likely driven by survival bias, where healthy individuals are those maintained within a longitudinal study, although other factors like the age distribution of the underlying training population may also have influenced this trend.
Type: | Article |
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Title: | Tracking the Epigenetic Clock Across the Human Life Course: A Meta-analysis of Longitudinal Cohort Data |
Location: | United States |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1093/gerona/gly060 |
Publisher version: | https://doi.org/10.1093/gerona/gly060 |
Language: | English |
Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute > Research Department of Cancer Bio |
URI: | https://discovery.ucl.ac.uk/id/eprint/10049345 |
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