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The epigenetic clock and physical development during childhood and adolescence: longitudinal analysis from a UK birth cohort

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)549-558
Number of pages10
JournalInternational Journal of Epidemiology
Issue number2
Early online date15 Jan 2017
DateAccepted/In press - 23 Sep 2016
DateE-pub ahead of print - 15 Jan 2017
DatePublished (current) - Apr 2017


Background: Statistical models that use an individual’s DNA methylation levels to estimate their age (known as epigenetic clocks) have recently been developed, with 96% correlation found between epigenetic and chronological age. We postulate that differences between estimated and actual age (age acceleration, AA), can be used as a measure of developmental age in early life.

Methods: We obtained DNA methylation measures at three timepoints (birth, age seven and 17) in 1018 children from the Avon Longitudinal Study of Parents and Children (ALSPAC). Using an online calculator, we estimated epigenetic age, and thus AA, for each child at each timepoint. We then investigated whether AA was prospectively associated with repeated measures of height, weight, BMI, bone mineral density, bone mass, fat mass, lean mass and Tanner stage.

Results: Positive AA at birth was associated with higher average fat mass (1321g per year of AA, 95% CI 386, 2256g) from birth to adolescence (i.e. from age 0-17) and AA at age 7 was associated with higher average height (0.23cm per year of AA, 95% CI 0.04, 0.41cm). Conflicting evidence for the role of AA (at birth and in childhood) on changes during development was also found, with higher AA being positively associated with changes in weight, BMI and Tanner stage but negatively with changes in height and fat mass.

Conclusions: We found evidence that being ahead of one’s epigenetic age is related to developmental characteristics during childhood and adolescence. This demonstrates the potential for using AA as a measure of development in future research.

    Research areas

  • ALSPAC, ARIES, DNA methylation, Epigenetic age, Longitudinal data, Analysis, Physical development

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