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Differential DNA methylation with age displays both common and dynamic features across human tissues that are influenced by CpG landscape

Kenneth Day1, Lindsay L Waite1, Anna Thalacker-Mercer24, Andrew West35, Marcas M Bamman245, James D Brooks6, Richard M Myers1 and Devin Absher1*

Author Affiliations

1 HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA

2 Departments Cell, Developmental, and Integrative Biology, the University of Alabama at Birmingham, Birmingham, AL 35294, USA

3 Department of Neurology, the University of Alabama at Birmingham, Birmingham, AL 35294, USA

4 The Center for Exercise Medicine, Birmingham, AL 35294, USA

5 The School of Medicine, Birmingham, AL 35294, USA

6 Stanford School of Medicine, Cancer Institute, Stanford, CA 94305, USA

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Genome Biology 2013, 14:R102  doi:10.1186/gb-2013-14-9-r102

Published: 13 September 2013

Abstract

Background

DNA methylation is an epigenetic modification that changes with age in human tissues, although the mechanisms and specificity of this process are still poorly understood. We compared CpG methylation changes with age across 283 human blood, brain, kidney, and skeletal muscle samples using methylation arrays to identify tissue-specific age effects.

Results

We found age-associated CpGs (ageCGs) that are both tissue-specific and common across tissues. Tissue-specific ageCGs are frequently located outside CpG islands with decreased methylation, and common ageCGs show the opposite trend. AgeCGs are significantly associated with poorly expressed genes, but those with decreasing methylation are linked with higher tissue-specific expression levels compared with increasing methylation. Therefore, tissue-specific gene expression may protect against common age-dependent methylation. Distinguished from other tissues, skeletal muscle ageCGs are more associated with expression, enriched near genes related to myofiber contraction, and closer to muscle-specific CTCF binding sites. Kidney-specific ageCGs are more increasingly methylated compared to other tissues as measured by affiliation with kidney-specific expressed genes. Underlying chromatin features also mark common and tissue-specific age effects reflective of poised and active chromatin states, respectively. In contrast with decreasingly methylated ageCGs, increasingly methylated ageCGs are also generally further from CTCF binding sites and enriched within lamina associated domains.

Conclusions

Our data identified common and tissue-specific DNA methylation changes with age that are reflective of CpG landscape and suggests both common and unique alterations within human tissues. Our findings also indicate that a simple epigenetic drift model is insufficient to explain all age-related changes in DNA methylation.

Keywords:
Aging; Methylation; Muscle; Kidney; Blood; Brain; LADs; Chromatin; H3K27Me3; Sequencing