Functional genomics analysis identifies T and NK cell activation as a driver of epigenetic clock progression

Abstract

Background Epigenetic clocks use DNA methylation (DNAm) levels of specific sets of CpG dinucleotides to accurately predict individual chronological age. A popular application of these clocks is to explore whether the deviation of predicted age from chronological age is associated with disease phenotypes, where this deviation is interpreted as a potential biomarker of biological age. This wide application, however, contrasts with the limited insight in the processes that may drive the running of epigenetic clocks. Results We perform a functional genomics analysis on four epigenetic clocks, including Hannum’s blood predictor and Horvath’s multi-tissue predictor, using blood DNA methylome and transcriptome data from 3132 individuals. The four clocks result in similar predictions of individual chronological age, and their constituting CpGs are correlated in DNAm level and are enriched for similar histone modifications and chromatin states. Interestingly, DNAm levels of CpGs from the clocks are commonly associated with gene expression in trans. The gene sets involved are highly overlapping and enriched for T cell processes. Further analysis of the transcriptome and methylome of sorted blood cell types identifies differences in DNAm between naive and activated T and NK cells as a probable contributor to the clocks. Indeed, within the same donor, the four epigenetic clocks predict naive cells to be up to 40 years younger than activated cells. Conclusions The ability of epigenetic clocks to predict chronological age involves their ability to detect changes in proportions of naive and activated immune blood cells, an established feature of immuno-senescence. This finding may contribute to the interpretation of associations between clock-derived measures and age-related health outcomes.

Recalibrating the cerebellum DNA methylation clock: implications for ageing rates comparison

“…However, we still lack sufficient evidence to confidently compare the biological ages between samples from different tissues. For example, as recently reported by Jonkman and colleagues, the Horvath’s multi-tissue clock predicts naive T cells to be up to 30 years younger than activated T cells from the same donor [41]. Can we conclude the naive T cells are biologically 30 years younger than activated T cells?…”

Dynamic epigenetic age mosaicism in the human atherosclerotic artery

“…A few studies support that notion. Peripheral blood cell profiling of six cohorts spanning a wide range of chronological age and pathological conditions, revealed that a minority of Horvath clock CpG correlate with expression of genes in cis that are not significantly enriched in any Gene Ontology term [ 21 ]. Epigenetic ageing was weakly associated with classical cardiovascular risk factors in the large MESA and HRS cohorts [ 22 ].…”

“…The results of the latter two studies agree with our observation that epigenetic ageing was not associated with asymptomatic/symptomatic status in the carotid atheroma. As caveat , Horvath clock CpG are associated with gene expression in trans in loci that regulate T cell function and may therefore be relevant for atherosclerosis [ 21 , 24 , 25 ]. As the atheroma discontinuously expands by bursts in macrophage infiltration and cellular proliferation, it is possible that the epigenetic clock is a readout of mitotic age in atherosclerosis [ 26 ].…”

Epigenetic Age and Lung Cancer Risk in the CLUE II Prospective Cohort Study

“…Recent studies have begun to elucidate the biological processes that explain age acceleration associations detected using epigenetic clocks [40]. In a functional genomics study, changes in proportions of naive and activated immune blood cells were strongly associated with the Hannum and Horvath age acceleration measures [40].…”