Exploratory analysis of age and sex dependent DNA methylation patterns on the X-chromosome in whole blood samples

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Abstract

Background

Large numbers of autosomal sites are found differentially methylated in the aging genome. Due to analytical difficulties in dealing with sex differences in X-chromosome content and X-inactivation (XCI) in females, this has not been explored for the X chromosome.

Methods

Using data from middle age to elderly individuals (age 55+ years) from two Danish cohorts of monozygotic twins and the Scottish Lothian Birth Cohort 1921, we conducted an X-chromosome-wide analysis of age-associated DNA methylation patterns with consideration of stably inferred XCI status.

Results

Through analysing and comparing sex-specific X-linked DNA methylation changes over age late in life, we identified 123, 293 and 55 CpG sites significant (FDR < 0.05) only in males, only in females and in both sexes of Danish twins. All findings were significantly replicated in the two Danish twin cohorts. CpG sites escaping XCI are predominantly de-methylated with increasing age across cohorts. In contrast, CpGs highly methylated in both sexes are methylated even further with increasing age. Among the replicated sites in Danish samples, 16 (13%), 24 (8.2%) and 3 (5.5%) CpGs were further validated in LBC1921 (FDR < 0.05).

Conclusions

The X-chromosome of whole blood leukocytes displays age- and sex-dependent DNA methylation patterns in relation to XCI across cohorts.

Electronic supplementary material

The online version of this article (10.1186/s13073-020-00736-3) contains supplementary material, which is available to authorized users.

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Most cited references 37

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Gene action in the X-chromosome of the mouse (Mus musculus L.).

MARY LYON (1961)

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DNA methylation age of blood predicts all-cause mortality in later life

Riccardo E Marioni, Sonia Shah, Allan McRae … (2015)

Background DNA methylation levels change with age. Recent studies have identified biomarkers of chronological age based on DNA methylation levels. It is not yet known whether DNA methylation age captures aspects of biological age. Results Here we test whether differences between people’s chronological ages and estimated ages, DNA methylation age, predict all-cause mortality in later life. The difference between DNA methylation age and chronological age (Δage) was calculated in four longitudinal cohorts of older people. Meta-analysis of proportional hazards models from the four cohorts was used to determine the association between Δage and mortality. A 5-year higher Δage is associated with a 21% higher mortality risk, adjusting for age and sex. After further adjustments for childhood IQ, education, social class, hypertension, diabetes, cardiovascular disease, and APOE e4 status, there is a 16% increased mortality risk for those with a 5-year higher Δage. A pedigree-based heritability analysis of Δage was conducted in a separate cohort. The heritability of Δage was 0.43. Conclusions DNA methylation-derived measures of accelerated aging are heritable traits that predict mortality independently of health status, lifestyle factors, and known genetic factors. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0584-6) contains supplementary material, which is available to authorized users.

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Gene body methylation can alter gene expression and is a therapeutic target in cancer.

Xiaojing Yang, Han Han, Daniel De Carvalho … (2014)

DNA methylation in promoters is well known to silence genes and is the presumed therapeutic target of methylation inhibitors. Gene body methylation is positively correlated with expression, yet its function is unknown. We show that 5-aza-2'-deoxycytidine treatment not only reactivates genes but decreases the overexpression of genes, many of which are involved in metabolic processes regulated by c-MYC. Downregulation is caused by DNA demethylation of the gene bodies and restoration of high levels of expression requires remethylation by DNMT3B. Gene body methylation may, therefore, be an unexpected therapeutic target for DNA methylation inhibitors, resulting in the normalization of gene overexpression induced during carcinogenesis. Our results provide direct evidence for a causal relationship between gene body methylation and transcription. Copyright © 2014 Elsevier Inc. All rights reserved.

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Author and article information

Contributors

Shuxia Li:

ORCID: https://orcid.org/0000-0001-8095-3175

sli@health.sdu.dk

Jesper B. Lund:

ORCID: https://orcid.org/0000-0001-9483-1603

jlund@health.sdu.dk

Kaare Christensen:

ORCID: https://orcid.org/0000-0002-5429-5292

kchristensen@health.sdu.dk

Jan Baumbach: jan.baumbach@wzw.tum.de

Jonas Mengel-From: jmengel-from@health.sdu.dk

Torben Kruse: torben.kruse@rsyd.dk

Weilong Li: wli@health.sdu.dk

Afsaneh Mohammadnejad: amohammadnejad@health.sdu.dk

Alison Pattie: alison.pattie@gmail.com

Riccardo E. Marioni:

ORCID: https://orcid.org/0000-0003-4430-4260

riccardo.marioni@ed.ac.uk

Ian J. Deary: i.deary@ed.ac.uk

Qihua Tan:

ORCID: https://orcid.org/0000-0003-3194-0030

qtan@health.sdu.dk

Journal

Journal ID (nlm-ta): Genome Med

Journal ID (iso-abbrev): Genome Med

Title: Genome Medicine

Publisher: BioMed Central (London )

ISSN (Electronic): 1756-994X

Publication date (Electronic): 28 April 2020

Publication date PMC-release: 28 April 2020

Publication date Collection: 2020

Volume: 12

Electronic Location Identifier: 39

Affiliations

[1 ]GRID grid.10825.3e, ISNI 0000 0001 0728 0170, Epidemiology and Biostatistics, Department of Public Health, Faculty of Health Science, , University of Southern Denmark, ; J. B. Winsløws Vej 9B, DK-5000 Odense C, Denmark

[2 ]GRID grid.10825.3e, ISNI 0000 0001 0728 0170, Unit of Human Genetics, Department of Clinical Research, , University of Southern Denmark, ; Odense, Denmark

[3 ]GRID grid.6936.a, ISNI 0000000123222966, Chair of Experimental Bioinformatics, TUM School of Life Sciences Weihenstephan, , Technical University of Munich, ; Freising, Germany

[4 ]GRID grid.4305.2, ISNI 0000 0004 1936 7988, Department of Psychology, , University of Edinburgh, ; Edinburgh, Scotland UK

[5 ]GRID grid.4305.2, ISNI 0000 0004 1936 7988, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, , University of Edinburgh, ; Edinburgh, Scotland, UK

[6 ]GRID grid.4305.2, ISNI 0000 0004 1936 7988, Lothian Birth Cohorts, , University of Edinburgh, ; Edinburgh, Scotland, UK

Author information

Shuxia Li https://orcid.org/0000-0001-8095-3175

Jesper B. Lund https://orcid.org/0000-0001-9483-1603

Kaare Christensen https://orcid.org/0000-0002-5429-5292

Riccardo E. Marioni https://orcid.org/0000-0003-4430-4260

Qihua Tan https://orcid.org/0000-0003-3194-0030

Article

Publisher ID: 736

DOI: 10.1186/s13073-020-00736-3

PMC ID: 7189689

PubMed ID: 32345361

SO-VID: e25023bd-845f-4619-b78a-33b0604d7738

License:

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/. The Creative Commons Public Domain Dedication waiver ( http://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.

History

Date received : 14 October 2019

Date accepted : 7 April 2020

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100008397, Velux Fonden;

Award ID: 000121540

Award Recipient : Qihua Tan

Custom metadata

ScienceOpen disciplines: Molecular medicine

Keywords: x-chromosome,dna methylation,x-inactivation,whole blood,aging,twins

Data availability:

ScienceOpen disciplines: Molecular medicine

Keywords: x-chromosome, dna methylation, x-inactivation, whole blood, aging, twins

Exploratory analysis of age and sex dependent DNA methylation patterns on the X-chromosome in whole blood samples

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Abstract

Background

Methods

Results

Conclusions

Electronic supplementary material

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REPO-TRIAL

Most cited references 37

Gene action in the X-chromosome of the mouse (Mus musculus L.).

DNA methylation age of blood predicts all-cause mortality in later life

Gene body methylation can alter gene expression and is a therapeutic target in cancer.

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