Eight blood-trained epigenetic clocks often disagree on the same sample
In a public whole-blood dataset, eight blood-trained epigenetic clocks gave different age estimates for the same samples; the average gap between the youngest and oldest clock was 17 years. The authors say this misalignment is often overlooked outside clock research. [1]
Automatic summary · not editorially reviewed
The key findings
Epigenetic clock output can vary with training method, cell type composition, training dataset, methylomic technology, acute stressors and other factors. [1]
In a public whole-blood dataset, eight blood-trained clocks differed by an average of 17 years between youngest and oldest predicted age per sample. [1]
The authors say clock misalignment matters for choosing a clock, interpreting intervention effects, personalized tracking and relating epigenetic to biological age. [1]
The source at a glance
- Study type / format
- Abstract of a commentary-style illustrative analysis
- Population / context
- Samples in a publicly available whole-blood dataset, assessed with eight blood-trained epigenetic clocks
- Summary based on
- Study abstract
- Original publication
- July 24, 2026
Why one sample can get different clock ages
The authors explain that the output of an epigenetic aging clock can vary with the training method, cell type composition, the nature of the training dataset, the technology used to generate the methylomic data, acute stressors and other factors. On an individual level, epigenetic age can therefore fluctuate across clocks purely because of differences in model training. Researchers working on clocks know that the epigenetic age of a single sample can vary across models, but the authors say this is often underappreciated among non-experts.
Supporting source [1]
17-year average gap across eight clocks
As an illustrative example, the authors used eight blood-trained clocks on a publicly available whole-blood dataset. Their simple analysis found that the average sample difference between the youngest and oldest predicted ages across these clocks was 17 years. The smallest and largest individual-level differences observed were 4 and 45 years, respectively. These are differences between clock predictions for the same samples, not measured changes in health or lifespan.
Supporting source [1]
What clock misalignment means for interpretation
The authors state that clock misalignment has implications for choosing which clock to use, for interpreting the impact of an intervention on epigenetic age, for personalized tracking, and for relating epigenetic age to the abstract concept of biological age. The abstract presents this as a topic to raise awareness of, supported by key literature and one illustrative analysis; it does not report an intervention or a health outcome.
Supporting source [1]
How to interpret this
Abstract only; the full text was not reviewed. The analysis is described as simple and illustrative, using one publicly available whole-blood dataset and eight blood-trained clocks. No intervention, health outcome or causal claim is reported.
Based on the study abstract; the full paper, tables and supplementary data were not reviewed.
Source & supporting passages
Johnson AA, Shokhirev MN. · europepmc.org · July 24, 2026