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

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 pheno...

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Autores principales: Jonkman, Thomas H., Dekkers, Koen F., Slieker, Roderick C., Grant, Crystal D., Ikram, M. Arfan, van Greevenbroek, Marleen M. J., Franke, Lude, Veldink, Jan H., Boomsma, Dorret I., Slagboom, P. Eline, Consortium, B. I. O. S., Heijmans, Bastiaan T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8759260/
https://www.ncbi.nlm.nih.gov/pubmed/35031073
http://dx.doi.org/10.1186/s13059-021-02585-8
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author Jonkman, Thomas H.
Dekkers, Koen F.
Slieker, Roderick C.
Grant, Crystal D.
Ikram, M. Arfan
van Greevenbroek, Marleen M. J.
Franke, Lude
Veldink, Jan H.
Boomsma, Dorret I.
Slagboom, P. Eline
Consortium, B. I. O. S.
Heijmans, Bastiaan T.
author_facet Jonkman, Thomas H.
Dekkers, Koen F.
Slieker, Roderick C.
Grant, Crystal D.
Ikram, M. Arfan
van Greevenbroek, Marleen M. J.
Franke, Lude
Veldink, Jan H.
Boomsma, Dorret I.
Slagboom, P. Eline
Consortium, B. I. O. S.
Heijmans, Bastiaan T.
author_sort Jonkman, Thomas H.
collection PubMed
description 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-021-02585-8.
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spelling pubmed-87592602022-01-18 Functional genomics analysis identifies T and NK cell activation as a driver of epigenetic clock progression Jonkman, Thomas H. Dekkers, Koen F. Slieker, Roderick C. Grant, Crystal D. Ikram, M. Arfan van Greevenbroek, Marleen M. J. Franke, Lude Veldink, Jan H. Boomsma, Dorret I. Slagboom, P. Eline Consortium, B. I. O. S. Heijmans, Bastiaan T. Genome Biol Research 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-021-02585-8. BioMed Central 2022-01-14 /pmc/articles/PMC8759260/ /pubmed/35031073 http://dx.doi.org/10.1186/s13059-021-02585-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Jonkman, Thomas H.
Dekkers, Koen F.
Slieker, Roderick C.
Grant, Crystal D.
Ikram, M. Arfan
van Greevenbroek, Marleen M. J.
Franke, Lude
Veldink, Jan H.
Boomsma, Dorret I.
Slagboom, P. Eline
Consortium, B. I. O. S.
Heijmans, Bastiaan T.
Functional genomics analysis identifies T and NK cell activation as a driver of epigenetic clock progression
title Functional genomics analysis identifies T and NK cell activation as a driver of epigenetic clock progression
title_full Functional genomics analysis identifies T and NK cell activation as a driver of epigenetic clock progression
title_fullStr Functional genomics analysis identifies T and NK cell activation as a driver of epigenetic clock progression
title_full_unstemmed Functional genomics analysis identifies T and NK cell activation as a driver of epigenetic clock progression
title_short Functional genomics analysis identifies T and NK cell activation as a driver of epigenetic clock progression
title_sort functional genomics analysis identifies t and nk cell activation as a driver of epigenetic clock progression
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8759260/
https://www.ncbi.nlm.nih.gov/pubmed/35031073
http://dx.doi.org/10.1186/s13059-021-02585-8
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