Dataset Information

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

ABSTRACT:

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 time points (birth, age 7 years and age 17 years) 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 time point. We then investigated whether AA was prospectively associated with repeated measures of height, weight, body mass index (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 [1321?g per year of AA, 95% confidence interval (CI) 386, 2256?g] from birth to adolescence (i.e. from age 0-17 years) and AA at age 7 was associated with higher average height (0.23?cm per year of AA, 95% CI 0.04, 0.41?cm). 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 acceleration is related to developmental characteristics during childhood and adolescence. This demonstrates the potential for using AA as a measure of development in future research.

SUBMITTER: Simpkin AJ

PROVIDER: S-EPMC5722033 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Publications

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

Simpkin Andrew J AJ Howe Laura D LD Tilling Kate K Gaunt Tom R TR Lyttleton Oliver O McArdle Wendy L WL Ring Susan M SM Horvath Steve S Smith George Davey GD Relton Caroline L CL

International journal of epidemiology 20170401 2

<h4>Background</h4>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.<h4>Methods</h4>We obtained DNA methylation measures at three time points (birth, age 7 years and age 17 years) in 10 ...[more]

PMID: 28089957

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Dataset Information

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

Background

Methods

Results

Conclusions

Publications

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

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