Improved prediction of chronological age from DNA methylation limits it as a biomarker of ageing
Costanza L. Vallerga,
Rosie M. Walker,
Anjali K Henders,
Grant W. Montgomery,
Glenda M. Halliday,
J. B. Kwok,
Peter A. Silburn,
George D. Mellick,
Sarah E. Harris,
Alison D Murray,
David J. Porteous,
Christopher S. Haley,
Kathryn L Evans,
Andrew M. McIntosh,
Riccardo E. Marioni,
Naomi R Wray,
Allan F. McRae,
Peter M Visscher
Posted 23 May 2018
bioRxiv DOI: 10.1101/327890
Posted 23 May 2018
DNA methylation is associated with age. The deviation of age predicted from DNA methylation from actual age has been proposed as a biomarker for ageing. However, a better prediction of chronological age implies less opportunity for biological age. Here we used 13,661 samples in the age range of 2 to 104 years from 14 cohorts measured on Illumina HumanMethylation450/EPIC arrays to perform prediction analyses using Elastic Net and Best Linear Unbiased Prediction. We show that increasing the sample size achieves a smaller prediction error and higher correlations in test datasets. Our predictors achieved prediction errors of about 4.5 years across cohorts, in contrast to >7 years for the widely-used Horvath and Hannum predictors. We demonstrate that smaller prediction errors provide a limit to how much variation in biological ageing can be captured by methylation and provide evidence that age predictors from small samples are prone to confounding by cell composition.
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