5 research outputs found

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

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    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.Molecular Epidemiolog

    IgG glycosylation and DNA methylation are interconnected with smoking

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    Background: Glycosylation is one of the most common post-translation modifications with large influences on protein structure and function. The effector function of immunoglobulin G (IgG) alters between pro- and anti-inflammatory, based on its glycosylation. IgG glycan synthesis is highly complex and dynamic. Methods: With the use of two different analytical methods for assessing IgG glycosylation, we aim to elucidate the link between DNA methylation and glycosylation of IgG by means of epigenome-wide association studies. In total, 3000 individuals from 4 cohorts were analyzed. Results: The overlap of the results from the two glycan measurement panels yielded DNA methylation of 7 CpG-sites on 5 genomic locations to be associated with IgG glycosylation: cg25189904 (chr.1, GNG12); cg05951221, cg21566642 and cg01940273 (chr.2, ALPPL2); cg05575921 (chr.5, AHRR); cg06126421 (6p21.33); and cg03636183 (chr.19, F2RL3). Mediation analyses with respect to smoking revealed that the effect of smoking on IgG glycosylation may be at least partially mediated via DNA methylation levels at these 7 CpG-sites. Conclusion: Our results suggest the presence of an indirect link between DNA methylation and IgG glycosylation that may in part capture environmental exposures. General significance: An epigenome-wide analysis conducted in four population-based cohorts revealed an association between DNA methylation and IgG glycosylation patterns. Presumably, DNA methylation mediates the effect of smoking on IgG glycosylation
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