Authors
Thomas H Jonkman, Anne Richmond, BIOS Consortium, Riccardo E Marioni, Erik W van Zwet, Bastiaan T Heijmans
Published in
Genome medicine. Volume 18. Issue 1. Oct 02, 2026. Epub Oct 02, 2026.
Abstract
Epigenetic clocks are widely applied biomarkers of biological age, but their biological underpinnings remain unclear. We previously showed that epigenetic clocks are affected by naïve and memory T cell proportions, suggesting blood cell composition as a potential driver. However, analysis of cell composition is complicated by collinearity between cell fractions.
We first develop a principal component analysis (PCA) method that is robust to collinearity of blood cell counts and show that this approach provides biologically meaningful insights. Next, we quantify the contribution of cell composition to DNA methylation age and age acceleration estimated by six 1st - or 2nd -generation epigenetic clocks in an analysis of 4,058 samples. Finally, we test the influence of cell composition on the association between age acceleration and 176 incident health outcomes using a study of 18,859 individuals.
We find that up to 53% of the variation in DNA methylation age can be attributed to cell counts, with a particularly strong contribution of the balance between naïve and memory T cells. Associations between age acceleration and cell counts are weaker (up to 21% variance explained) and, for 2nd -generation clocks, primarily involve neutrophils. We validate the contribution of cell counts to epigenetic clocks using artificial cell mixtures. Interestingly, cell composition significantly attenuates the association of age acceleration investigated with 176 incident health outcomes, although this effect remains modest.
DNAmAge and AgeAccel are markedly different in their associations with cell composition, indicating that they - at least in part - reflect different biological processes. Surprisingly, the variation in age acceleration that can be attributed to blood cell composition only has a minor contribution to its association with mortality and incident disease outcomes.
PMID:
42823742
Bibliographic data and abstract were imported from PubMed on 02 Oct 2026.
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