Evidence map›Paper›PMID 42823742›Full record

ArticleGenome medicine2026

Blood cell composition reveals distinct biological interpretation of DNA methylation age and age acceleration.

Thomas H Jonkman, Anne Richmond, BIOS Consortium, Riccardo E Marioni, Erik W van Zwet, Bastiaan T Heijmans

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Article in Genome medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Thomas H JonkmanBiomedical Data Sciences, Leiden University Medical Center, Einthovenweg 20, Leiden, 2333 ZC, The Netherlands.ORCID http://orcid.org/0000-0003-0307-6011
Anne RichmondInstitute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH42XU, UK.
BIOS Consortium
Riccardo E MarioniInstitute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH42XU, UK.
Erik W van ZwetBiomedical Data Sciences, Leiden University Medical Center, Einthovenweg 20, Leiden, 2333 ZC, The Netherlands.
Bastiaan T HeijmansBiomedical Data Sciences, Leiden University Medical Center, Einthovenweg 20, Leiden, 2333 ZC, The Netherlands. b.t.heijmans@lumc.nl.

Funding

Genetic analysis of the Dutch Hunger Winter Families Study to Boost Rigor and Robustness for Testing In-Utero Famine Effects on Aging-Related Health Conditions and Biological AgingR01AG066887 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BELSKY, DANIEL WALKER, LUMEY, L H · 2020 to 2024
$3.5M
NIH HHS R01AG066887
6 · The paper itself

Abstract

backgroundEpigenetic 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.

methodsWe 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.

resultsWe 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.

conclusionsDNAmAge 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.

Indexed as

AgingBlood CellsDNA MethylationEpigenesis, GeneticFemaleHumansMalePrincipal Component AnalysisBiological ageBlood cell countsEpigenetic clocksEpigeneticsImmunology

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.