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Hatton, A. A.

Publications and source records attributed to Hatton, A. A..

2 recordsLinked to original sources

Age-related dynamics of DNA co-methylation modules in humans

Age-related changes in the mean or variance of DNA methylation (DNAm) at individual CpG sites are well established. However, CpGs that share biological functions often exhibit coordinated regulation. Here, we analysed whole-blood DNAm data from over 7,500 individuals and identified modules of co-methylated CpGs that either maintain consistent correlations with age (age-stable modules) or undergo age-related remodelling (age-variable modules). We show that co-methylation modules are largely preserved during healthy aging, with only a small subset (~15%) showing substantial age-related reorganisation. Age-stable modules are enriched for CpG loci within promoters, transcription start sites, and CpG islands, whereas age-variable modules harbour loci that are depleted in these genomic domains and enriched for repressive chromatin marks. Age-stable co-methylation modules are also associated with long-range genetic regulation (trans-meQTLs), promoter-associated chromatin states, and higher-order chromatin interactions. While both age-stable and age-variable modules are enriched for developmental pathways, immune-related processes are distinctly associated with age-stable modules. Overall, our findings suggest that epigenetic aging is characterised by a spectrum of co-methylation network trajectories, ranging from stability to disruption, shaped by underlying genomic regulatory architecture.

systems biology↗

Blood-based genome-wide DNA methylation correlations across body fat and adiposity-related biochemical traits

The recent increase in obesity levels across many countries is likely to be driven by nongenetic factors. The epigenetic modification DNA methylation (DNAm) may help to explore this as it is sensitive to both genetic and environmental exposures. While the relationship between DNAm and body fat traits has been extensively studied [1-9], there is limited literature on the shared associations of DNAm variation across such traits. Akin to genetic correlation estimates, which measure the degree of common genetic control between two traits, here we introduce an approach to evaluate the similarities in DNAm associations between traits, DNAm correlations. As DNAm can be both a cause and consequence of complex traits [5, 10, 11], DNAm correlations have the potential to provide novel insights into trait relationships above that currently obtained from genetic and phenotypic correlations. Utilising 7,519 unrelated individuals from Generation Scotland (GS), we calculated DNAm correlations using the bivariate OREML framework in the OSCA software [12] to investigate the shared associations of DNAm variation between traits. For each trait we also estimated the shared contribution of DNAm between sexes. We identified strong, positive DNAm correlations between each of the body fat traits (BMI, body fat % and waist to hip ratio; ranging from 0.96 to 1.00), finding larger associations than those identified by genetic and phenotypic correlations. We identified a significant deviation from 1 in the rDNAm for BMI between males and females, with sex-specific DNAm changes associated with BMI identified at eight DNAm probes. Employing genome-wide DNAm correlations to evaluate the similarities in the associations of DNAm with complex traits has provided novel insight into obesity related traits beyond that provided by genetic correlations.

genomics↗