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Local CpG density affects the trajectory and variance of age-associated DNA methylation changes
BACKGROUND: DNA methylation is an epigenetic mark associated with the repression of gene promoters. Its pattern in the genome is disrupted with age and these changes can be used to statistically predict age with epigenetic clocks. Altered rates of aging inferred from these clocks are observed in hum...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9575273/ https://www.ncbi.nlm.nih.gov/pubmed/36253871 http://dx.doi.org/10.1186/s13059-022-02787-8 |
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author | Higham, Jonathan Kerr, Lyndsay Zhang, Qian Walker, Rosie M. Harris, Sarah E. Howard, David M. Hawkins, Emma L. Sandu, Anca-Larisa Steele, J. Douglas Waiter, Gordon D. Murray, Alison D. Evans, Kathryn L. McIntosh, Andrew M. Visscher, Peter M. Deary, Ian J. Cox, Simon R. Sproul, Duncan |
author_facet | Higham, Jonathan Kerr, Lyndsay Zhang, Qian Walker, Rosie M. Harris, Sarah E. Howard, David M. Hawkins, Emma L. Sandu, Anca-Larisa Steele, J. Douglas Waiter, Gordon D. Murray, Alison D. Evans, Kathryn L. McIntosh, Andrew M. Visscher, Peter M. Deary, Ian J. Cox, Simon R. Sproul, Duncan |
author_sort | Higham, Jonathan |
collection | PubMed |
description | BACKGROUND: DNA methylation is an epigenetic mark associated with the repression of gene promoters. Its pattern in the genome is disrupted with age and these changes can be used to statistically predict age with epigenetic clocks. Altered rates of aging inferred from these clocks are observed in human disease. However, the molecular mechanisms underpinning age-associated DNA methylation changes remain unknown. Local DNA sequence can program steady-state DNA methylation levels, but how it influences age-associated methylation changes is unknown. RESULTS: We analyze longitudinal human DNA methylation trajectories at 345,895 CpGs from 600 individuals aged between 67 and 80 to understand the factors responsible for age-associated epigenetic changes at individual CpGs. We show that changes in methylation with age occur at 182,760 loci largely independently of variation in cell type proportions. These changes are especially apparent at 8322 low CpG density loci. Using SNP data from the same individuals, we demonstrate that methylation trajectories are affected by local sequence polymorphisms at 1487 low CpG density loci. More generally, we find that low CpG density regions are particularly prone to change and do so variably between individuals in people aged over 65. This differs from the behavior of these regions in younger individuals where they predominantly lose methylation. CONCLUSIONS: Our results, which we reproduce in two independent groups of individuals, demonstrate that local DNA sequence influences age-associated DNA methylation changes in humans in vivo. We suggest that this occurs because interactions between CpGs reinforce maintenance of methylation patterns in CpG dense regions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-022-02787-8. |
format | Online Article Text |
id | pubmed-9575273 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-95752732022-10-18 Local CpG density affects the trajectory and variance of age-associated DNA methylation changes Higham, Jonathan Kerr, Lyndsay Zhang, Qian Walker, Rosie M. Harris, Sarah E. Howard, David M. Hawkins, Emma L. Sandu, Anca-Larisa Steele, J. Douglas Waiter, Gordon D. Murray, Alison D. Evans, Kathryn L. McIntosh, Andrew M. Visscher, Peter M. Deary, Ian J. Cox, Simon R. Sproul, Duncan Genome Biol Research BACKGROUND: DNA methylation is an epigenetic mark associated with the repression of gene promoters. Its pattern in the genome is disrupted with age and these changes can be used to statistically predict age with epigenetic clocks. Altered rates of aging inferred from these clocks are observed in human disease. However, the molecular mechanisms underpinning age-associated DNA methylation changes remain unknown. Local DNA sequence can program steady-state DNA methylation levels, but how it influences age-associated methylation changes is unknown. RESULTS: We analyze longitudinal human DNA methylation trajectories at 345,895 CpGs from 600 individuals aged between 67 and 80 to understand the factors responsible for age-associated epigenetic changes at individual CpGs. We show that changes in methylation with age occur at 182,760 loci largely independently of variation in cell type proportions. These changes are especially apparent at 8322 low CpG density loci. Using SNP data from the same individuals, we demonstrate that methylation trajectories are affected by local sequence polymorphisms at 1487 low CpG density loci. More generally, we find that low CpG density regions are particularly prone to change and do so variably between individuals in people aged over 65. This differs from the behavior of these regions in younger individuals where they predominantly lose methylation. CONCLUSIONS: Our results, which we reproduce in two independent groups of individuals, demonstrate that local DNA sequence influences age-associated DNA methylation changes in humans in vivo. We suggest that this occurs because interactions between CpGs reinforce maintenance of methylation patterns in CpG dense regions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-022-02787-8. BioMed Central 2022-10-17 /pmc/articles/PMC9575273/ /pubmed/36253871 http://dx.doi.org/10.1186/s13059-022-02787-8 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 Higham, Jonathan Kerr, Lyndsay Zhang, Qian Walker, Rosie M. Harris, Sarah E. Howard, David M. Hawkins, Emma L. Sandu, Anca-Larisa Steele, J. Douglas Waiter, Gordon D. Murray, Alison D. Evans, Kathryn L. McIntosh, Andrew M. Visscher, Peter M. Deary, Ian J. Cox, Simon R. Sproul, Duncan Local CpG density affects the trajectory and variance of age-associated DNA methylation changes |
title | Local CpG density affects the trajectory and variance of age-associated DNA methylation changes |
title_full | Local CpG density affects the trajectory and variance of age-associated DNA methylation changes |
title_fullStr | Local CpG density affects the trajectory and variance of age-associated DNA methylation changes |
title_full_unstemmed | Local CpG density affects the trajectory and variance of age-associated DNA methylation changes |
title_short | Local CpG density affects the trajectory and variance of age-associated DNA methylation changes |
title_sort | local cpg density affects the trajectory and variance of age-associated dna methylation changes |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9575273/ https://www.ncbi.nlm.nih.gov/pubmed/36253871 http://dx.doi.org/10.1186/s13059-022-02787-8 |
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