A computational solution for bolstering reliability of epigenetic clocks: Implications for clinical trials and longitudinal tracking

By A. Higgins-Chen, Kyra L. Thrush, Yunzhang Wang, Christopher J Minteer, Pei-lun Kuo, Meng Wang, Peter Niimi, Gabriel Sturm, Jue Lin, A. Moore and 17 more. Nature Aging, 2021

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Epigenetic clocks are widely used aging biomarkers calculated from DNA methylation data, but this data can be surprisingly unreliable. Here we show that technical noise produces deviations up to 9 years between replicates for six prominent epigenetic clocks, limiting their utility. We present a computational solution to bolster reliability, calculating principal components (PCs) from CpG-level data as input for biological age prediction. Our retrained PC versions of six clocks show agreement between most replicates within 1.5 years, improved detection of clock associations and intervention effects, and reliable longitudinal trajectories in vivo and in vitro. This method entails only one additional step compared to traditional clocks, requires no replicates or previous knowledge of CpG reliabilities for training, and can be applied to any existing or future epigenetic biomarker. The high reliability of PC-based clocks is critical for applications to personalized medicine, longitudinal tracking, in vitro studies and clinical trials of aging interventions. Epigenetic clocks are widely used aging biomarkers, but their utility is limited by technical noise. The authors report a method for producing high-reliability clocks for applications such as longitudinal studies and intervention trials.

Subfields: Genetics, Health, Toxicology and Mutagenesis, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/42877366d88b5c48c0e3b7e1b68869ead1f505a6

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