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BackgroundTelomere length and DNA methylation have been proposed as biological clock measures that track chronological age. Whether they change in tandem, or contribute independently to the prediction of chronological age, is not known.MethodsWe address these points using data from two Scottish cohorts: the Lothian Birth Cohorts of 1921 (LBC1921) and 1936 (LBC1936). Telomere length and epigenetic clock estimates from DNA methylation were measured in 920 LBC1936 participants (ages 70, 73 and 76 years) and in 414 LBC1921 participants (ages 79, 87 and 90 years).ResultsThe epigenetic clock changed over time at roughly the same rate as chronological age in both cohorts. Telomere length decreased at 48-67 base pairs per year on average. Weak, non-significant correlations were found between epigenetic clock estimates and telomere length. Telomere length explained 6.6% of the variance in age in LBC1921, the epigenetic clock explained 10.0%, and combined they explained 17.3% (allP< 1 × 10-7). Corresponding figures for the LBC1936 cohort were 14.3%, 11.7% and 19.5% (allP< 1 × 10-12). In a combined cohorts analysis, the respective estimates were 2.8%, 28.5% and 29.5%. Also in a combined cohorts analysis, a one standard deviation increase in baseline epigenetic age was linked to a 22% increased mortality risk (P= 2.6 × 10-4) whereas, in the same model, a one standard deviation increase in baseline telomere length was independently linked to an 11% decreased mortality risk (P= 0.06).ConclusionsThese results suggest that telomere length and epigenetic clock estimates are independent predictors of chronological age and mortality risk.

Original publication

DOI

10.1093/ije/dyw041

Type

Journal article

Journal

International journal of epidemiology

Publication Date

02/2018

Volume

45

Pages

424 - 432

Addresses

Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK riccardo.marioni@ed.ac.uk.