Eight epigenetic clocks differed by an average of 17 years when applied to the same blood sample

Eight epigenetic clocks differed by an average of 17 years when applied to the same blood sample

In a paper published on July 24, Adiv Johnson and Maksim Shokhirev applied eight epigenetic clocks to a single publicly available whole blood dataset. For each sample, the difference between the lowest and highest estimates averaged 17 years. Across individual samples, this difference ranged from 4 to 45 years.

Epigenetic clocks use DNA methylation profiles to calculate age estimates in years. Methylation consists of chemical marks on DNA that affect gene activity. Researchers use these profiles to compare groups of people, track changes over time, and evaluate interventions in studies of aging.

The eight formulas analyzed the same blood data but produced substantially different estimates. The clocks are trained on different datasets and for different purposes, so each model translates methylation patterns into age in its own way. Whole blood introduces another source of variation because it contains several cell types, and their relative proportions affect the methylation profile.

In this type of report, age does not describe the sample alone. It describes the combination of the sample and the selected model. Johnson and Shokhirev demonstrated this numerically: for one person, the lowest and highest estimates could differ by decades.

This result allows more precise discussion of interventions. The statement “epigenetic age decreased” becomes meaningful when the researcher identifies the specific clock, tissue, and method of comparison. This information shows which model converted the methylation changes into years and what that model was designed to predict. Some clocks are trained to estimate age in years, while others estimate the risk of death or disease. Although both results may be described as “rejuvenation,” they represent different measurements.