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. 2018 May 30;11(1):25.
doi: 10.1186/s13072-018-0191-3.

Age-related DNA methylation changes are tissue-specific with ELOVL2 promoter methylation as exception

Roderick C Slieker  1 , Caroline L Relton  2 , Tom R Gaunt  2 , P Eline Slagboom  3 , Bastiaan T Heijmans  3
Affiliations

Age-related DNA methylation changes are tissue-specific with ELOVL2 promoter methylation as exception

Roderick C Slieker et al. Epigenetics Chromatin. .

Abstract

Background: The well-established association of chronological age with changes in DNA methylation is primarily founded on the analysis of large sets of blood samples, while conclusions regarding tissue-specificity are typically based on small number of samples, tissues and CpGs. Here, we systematically investigate the tissue-specific character of age-related DNA methylation changes at the level of the CpG, functional genomic region and nearest gene in a large dataset.

Results: We assembled a compendium of public data, encompassing genome-wide DNA methylation data (Illumina 450k array) on 8092 samples from 16 different tissues, including 7 tissues with moderate to high sample numbers (Dataset size range 96-1202, Ntotal = 2858). In the 7 tissues (brain, buccal, liver, kidney, subcutaneous fat, monocytes and T-helper cells), we identified 7850 differentially methylated positions that gained (gain-aDMPs; cut-offs: Pbonf ≤ 0.05, effect size ≥ 2%/10 years) and 4,287 that lost DNA methylation with age (loss-aDMPs), 92% of which had not previously been reported for whole blood. The majority of all aDMPs identified occurred in one tissue only (gain-aDMPs: 85.2%; loss-aDMPs: 97.4%), an effect independent of statistical power. This striking tissue-specificity extended to both the functional genomic regions (defined by chromatin state segmentation) and the nearest gene. However, aDMPs did accumulate in regions with the same functional annotation across tissues, namely polycomb-repressed CpG islands for gain-aDMPs and regions marked by active histone modifications for loss-aDMPs.

Conclusion: Our analysis shows that age-related DNA methylation changes are highly tissue-specific. These results may guide the development of improved tissue-specific markers of chronological and, perhaps, biological age.

Keywords: 450 k; Ageing; DNA methylation; Tissue-specific.

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Figures

Fig. 1
Fig. 1
Age-related change in DNA methylation in ELOVL2. a DNA methylation (y axis) against age (x axis) in blood for the ELOVL2 CpG (cg16867657). b DNA methylation (y axis) against age (x axis) in other tissues for the ELOVL2 CpG (cg16867657)
Fig. 2
Fig. 2
Identification of aDMPs. a Number of identified gain- and loss-aDMPs (y axis) in this study for each tissue (x axis). b Slopes of identified gain- and loss-aDMPs (y axis) for each tissue (x axis). c Overlap between tissues in identified gain- and loss-aDMPs. In the diagonal cells the number of aDMPs unique for that tissue, the upper number represents the percentage, the lower number the number of overlapping aDMPs. Blue—gain-aDMPs; Purple—loss-aDMPs
Fig. 3
Fig. 3
Characterization of gain-aDMPs. a Frequency of aDMPs (y axis) against the number of tissues the aDMPs was identified in (x axis). b Enrichment of gain-aDMPs in chromatin segmentations expressed as an odds ratio, grey non-significant. c Percentage (top) and odds ratios (bottom) of aDMPs in CGIs, shores and non-CGIs. Blue enriched, red depleted, grey non-significant. d Percentage (top) and odds ratios (bottom) of aDMPs in EZH2 binding sites (ChIP-seq, any cell type, ENCODE). Blue enriched, red depleted, grey non-significant. e Frequency of CpG islands (y axis) against the number of tissues a CpG island was identified in (x axis). f Frequency of genes (y axis) against the number of tissues a gene was identified in (x axis). g Expression (y axis, RPKM) of genes near gain-aDMPs per tissue (x axis). Abbreviations: TssA active TSS, TssAFlnk flanking active TSS, TxFlnk transcr. at gene 5′ and 3′, Tx strong transcription, TxWk weak transcription, EnhG genic enhancers, Enh enhancers, ZNF/Rpts ZNF genes + repeats, Het heterochromatin, TssBiv bivalent/poised TSS, BivFlnk flanking bivalent TSS/Enh, EnhBiv bivalent enhancer, ReprPC repressed polycomb, ReprPCWk weak repressed polycomb, Quies quiescent/low
Fig. 4
Fig. 4
Characterization of loss-aDMPs. a Percentage and odds ratios of aDMPs in CGIs, shores and non-CGIs. Blue enriched, red depleted, grey non-significant. b Number of tissues an aDMPs was identified in. c Enrichment of gain-aDMPs in chromatin segmentations expressed as an odds ratio, grey non-significant enrichment. d Frequency of genes (y axis) against the number of tissues genes were identified in (x axis). e Expression of genes (y axis, RPKM) near loss-aDMPs per tissue (x axis). Abbreviations: TssA active TSS, TssAFlnk flanking active TSS, TxFlnk transcr. at gene 5′ and 3′, Tx strong transcription, TxWk weak transcription, EnhG genic enhancers, Enh enhancers, ZNF/Rpts ZNF genes + repeats, Het heterochromatin, TssBiv bivalent/poised TSS, BivFlnk flanking bivalent TSS/Enh, EnhBiv bivalent enhancer, ReprPC repressed polycomb, ReprPCWk weak repressed polycomb, Quies quiescent/low
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