2013
DOI: 10.1186/gb-2013-14-9-r102
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Differential DNA methylation with age displays both common and dynamic features across human tissues that are influenced by CpG landscape

Abstract: BackgroundDNA 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.ResultsWe found age-associated CpGs (ageCGs) that are both tissue-specific and common across tissues. Tissue-specific ageCGs are frequently located outside C… Show more

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Cited by 303 publications
(270 citation statements)
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“…Genes affected by this process are associated with developmental regulation (Easwaran et al., 2012), implying a possible stem cell origin of cancer whereby aberrant hypermethylation could promote a continuously self‐renewing embryonic‐like state in cancer cells (Teschendorff et al., 2010). Interestingly, promoter hypermethylation of polycomb‐target genes was later described in aging blood (Rakyan et al., 2010; Teschendorff et al., 2010) and other tissue types such as mesenchymal stem cells (Fernández et al., 2015), ovary (Teschendorff et al., 2010), brain, kidney, and skeletal muscle (Day et al., 2013), findings which were also confirmed using whole‐genome bisulfite sequencing (Heyn et al., 2012). …”
Section: Introductionmentioning
confidence: 52%
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“…Genes affected by this process are associated with developmental regulation (Easwaran et al., 2012), implying a possible stem cell origin of cancer whereby aberrant hypermethylation could promote a continuously self‐renewing embryonic‐like state in cancer cells (Teschendorff et al., 2010). Interestingly, promoter hypermethylation of polycomb‐target genes was later described in aging blood (Rakyan et al., 2010; Teschendorff et al., 2010) and other tissue types such as mesenchymal stem cells (Fernández et al., 2015), ovary (Teschendorff et al., 2010), brain, kidney, and skeletal muscle (Day et al., 2013), findings which were also confirmed using whole‐genome bisulfite sequencing (Heyn et al., 2012). …”
Section: Introductionmentioning
confidence: 52%
“…The distribution of hypermethylated CpGs was found to be similar to that of the array, which is to a certain extent to be expected because it was designed to interrogate a promoter‐ and CpG dense‐biased portion of the genome. Nonetheless, hypermethylation changes always occurred in far more CpG‐dense regions than hypomethylation changes (Day et al., 2013; Yuan et al., 2015), and this observed effect was especially noticeable for aging dmCpGs.…”
Section: Discussionmentioning
confidence: 99%
“…Some evidence show that age-related hypermethylation are more conserved across different tissues than hypomethylation [5,26]. However, we only studied blood samples and adjusted methylation data using estimated cellular compositions [20].…”
Section: Discussionmentioning
confidence: 99%
“…When tracked in a large population, the distribution of DNA methylation levels suggests that these sites change rapidly with age until adulthood, at which point the rate of change slows considerably (Horvath, 2013; Lister et al ., 2013). An important characteristic of the epigenetic clock is that it can be tissue specific, meaning that different sites may be better correlated with age in specific tissues, although pan‐tissue epigenetic clocks have also been identified (Teschendorff et al ., 2010; Horvath et al ., 2012; Day et al ., 2013). In one study, an analysis examining 20 different tissues using a multitissue‐derived age predictor found that tissues differ in their apparent epigenetic ages, with some reflecting chronological age more accurately than others (Horvath, 2013).…”
Section: Epigenetic Drift Vs the Epigenetic Clock: Two Phenomena Undmentioning
confidence: 99%