Epigenome-wide scans identify differentially methylated regions for age and age-related phenotypes in a healthy ageing population

Jordana T Bell, Pei-Chien Tsai, Tsun-Po Yang, Ruth Pidsley, James Nisbet, Daniel Glass, Massimo Mangino, Guangju Zhai, Feng Zhang, Ana Valdes, So-Youn Shin, Emma L Dempster, Robin M Murray, Elin Grundberg, Asa K Hedman, Alexandra Nica, Kerrin S Small, MuTHER Consortium, Emmanouil T Dermitzakis, Mark I McCarthy, Jonathan Mill, Tim D Spector, Panos Deloukas, Kourosh R Ahmadi, Chrysanthi Ainali, Amy Barrett, Veronique Bataille, Jordana T Bell, Alfonso Buil, Panos Deloukas, Emmanoil T Dermitzakis, Antigone S Dimas, Richard Durbin, Daniel Glass, Elin Grundberg, Neelam Hassanali, Åsa K Hedman, Catherine Ingle, David Knowles, Maria Krestyaninova, Cecilia M Lindgren, Christopher E Lowe, Mark I McCarthy, Eshwar Meduri, Paola di Meglio, Josine L Min, Stephen B Montgomery, Frank O Nestle, Alexandra C Nica, James Nisbet, Stephen O'Rahilly, Leopold Parts, Simon Potter, Magdalena Sekowska, So-Youn Shin, Kerrin S Small, Nicole Soranzo, Tim D Spector, Gabriela Surdulescu, Mary E Travers, Loukia Tsaprouni, Sophia Tsoka, Alicja Wilk, Tsun-Po Yang, Krina T Zondervan, Jordana T Bell, Pei-Chien Tsai, Tsun-Po Yang, Ruth Pidsley, James Nisbet, Daniel Glass, Massimo Mangino, Guangju Zhai, Feng Zhang, Ana Valdes, So-Youn Shin, Emma L Dempster, Robin M Murray, Elin Grundberg, Asa K Hedman, Alexandra Nica, Kerrin S Small, MuTHER Consortium, Emmanouil T Dermitzakis, Mark I McCarthy, Jonathan Mill, Tim D Spector, Panos Deloukas, Kourosh R Ahmadi, Chrysanthi Ainali, Amy Barrett, Veronique Bataille, Jordana T Bell, Alfonso Buil, Panos Deloukas, Emmanoil T Dermitzakis, Antigone S Dimas, Richard Durbin, Daniel Glass, Elin Grundberg, Neelam Hassanali, Åsa K Hedman, Catherine Ingle, David Knowles, Maria Krestyaninova, Cecilia M Lindgren, Christopher E Lowe, Mark I McCarthy, Eshwar Meduri, Paola di Meglio, Josine L Min, Stephen B Montgomery, Frank O Nestle, Alexandra C Nica, James Nisbet, Stephen O'Rahilly, Leopold Parts, Simon Potter, Magdalena Sekowska, So-Youn Shin, Kerrin S Small, Nicole Soranzo, Tim D Spector, Gabriela Surdulescu, Mary E Travers, Loukia Tsaprouni, Sophia Tsoka, Alicja Wilk, Tsun-Po Yang, Krina T Zondervan

Abstract

Age-related changes in DNA methylation have been implicated in cellular senescence and longevity, yet the causes and functional consequences of these variants remain unclear. To elucidate the role of age-related epigenetic changes in healthy ageing and potential longevity, we tested for association between whole-blood DNA methylation patterns in 172 female twins aged 32 to 80 with age and age-related phenotypes. Twin-based DNA methylation levels at 26,690 CpG-sites showed evidence for mean genome-wide heritability of 18%, which was supported by the identification of 1,537 CpG-sites with methylation QTLs in cis at FDR 5%. We performed genome-wide analyses to discover differentially methylated regions (DMRs) for sixteen age-related phenotypes (ap-DMRs) and chronological age (a-DMRs). Epigenome-wide association scans (EWAS) identified age-related phenotype DMRs (ap-DMRs) associated with LDL (STAT5A), lung function (WT1), and maternal longevity (ARL4A, TBX20). In contrast, EWAS for chronological age identified hundreds of predominantly hyper-methylated age DMRs (490 a-DMRs at FDR 5%), of which only one (TBX20) was also associated with an age-related phenotype. Therefore, the majority of age-related changes in DNA methylation are not associated with phenotypic measures of healthy ageing in later life. We replicated a large proportion of a-DMRs in a sample of 44 younger adult MZ twins aged 20 to 61, suggesting that a-DMRs may initiate at an earlier age. We next explored potential genetic and environmental mechanisms underlying a-DMRs and ap-DMRs. Genome-wide overlap across cis-meQTLs, genotype-phenotype associations, and EWAS ap-DMRs identified CpG-sites that had cis-meQTLs with evidence for genotype-phenotype association, where the CpG-site was also an ap-DMR for the same phenotype. Monozygotic twin methylation difference analyses identified one potential environmentally-mediated ap-DMR associated with total cholesterol and LDL (CSMD1). Our results suggest that in a small set of genes DNA methylation may be a candidate mechanism of mediating not only environmental, but also genetic effects on age-related phenotypes.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1. DNA methylation variation associates with…
Figure 1. DNA methylation variation associates with genetic variation.
A. Genome-wide pair-wise correlation coefficients in 21 pairs of MZ twins, 31 pairs of DZ twins, and 1091 pairs of unrelated individuals. B. Histogram of the observed distribution of P-values (black bars) and the expected distribution (red area indicates 90% confidence region) obtained from ten permutations of the data. C. Majority of SNPs that are cis-meQTLs are located within few kb of the methylation probe. D. Overlap of probes that have cis-meQTLs from the current study (red) with probes reported to have meQTLs in brain tissues (blue, [3]) and in LCLs (grey, [1]), not accounting for SNP overlap.
Figure 2. Epigenome-wide association scans of age…
Figure 2. Epigenome-wide association scans of age and age-related phenotypes.
(A) Genome-wide results for chronological age at FDR = 5% (a-DMRs). Red dashed line corresponds to FDR 5% significance level threshold. (B–E) Peak ap-DMRs were obtained for (B) LDL-DMR cg03001305, (C) lung function (FVC) DMR cg16463460, and maternal longevity (MLONG) DMRs cg09259772 (D) and cg13870866 (E); grey lines correspond to fitted linear regression models on these data.
Figure 3. Examples of age and age-related…
Figure 3. Examples of age and age-related phenotype DMRs in the discovery and replication samples.
(A) Example of an a-DMR probe (cg00468146 in ID4), which also has cis-meQTLs. Individuals are coloured according to cis-meQTL rs12660828 genotype (AG = red, GG = blue). (B) MZ twin methylation difference analyses identify potential environmentally-triggered DMR cg01136458 in CSMD1 associated with LDL. MZ co-twins are linked by dark blue (positive DMR effect) or light blue (negative DMR effect) dashed lines. (C,D) The two most associated a-DMRs (in NHLRC1 (C) and IRX5 (D)) in the discovery sample of 172 individuals (black dots) also replicate in the sample of 44 younger individuals (red triangles). Dashed lines represent estimated effects within the discovery (black) and replication (red) sample.
Figure 4. Functional characterization of a-DMRs.
Figure 4. Functional characterization of a-DMRs.
A. Enrichment and depletion of a-DMRs in functional genomic categories. Enrichment is calculated as the proportion of a-DMRs in each functional category (CpG islands (green) or HapMap CEPH LCL histone peaks (blue, black)) over the proportion of 26,690 probe in that functional category. Bars represent the 95% bootstrap percentile confidence intervals. B. Whole blood methylation and LCL gene expression estimates in the age DMR genes show significant negative correlation (histogram shows the distribution of gene-based rank correlation coefficients between methylation and gene expression).

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