bioRxivGeneticsPreprint
Characterizing the human methylome across the life course: findings from eight UK-based studies
Esther WaltoniD, Riccardo Emilio MarioniiD, Hannah R. ElliottiD, Simon R Cox, Ian J. DearyiD, Alun David HughesiD, Therese TilliniD, Meena Kumari BiD, Tom WoofendeniD, Juan Castillo FernandeziD, Jordana T. BelliD, Alissa T. Goodman, George B. PloubidisiD, Kate M. TillingiD, Matthew J SudermaniD, Tom R. GauntiD, Erin C. DunniD, Andrew D A C SmithiD, Caroline Laura ReltoniD
Abstract
Variation in DNA methylation (DNAm) is associated with multiple biological processes that track growth and development, ageing and age-related diseases. However, there is little understanding of what constitutes typical patterns of DNAm variation and how these patterns change across the life course. In this study, we synthesised a map of the human methylome across the life course, focussing on changes in variability and mean DNAm. Harmonizing DNAm datasets across eight longitudinal and cross-sectional UK-based studies, we meta-analysed n=13,215 blood samples from n=7,037 unique individuals from birth to 98 years of age. Changes in CpG-specific variability and means were described across the life course using a meta-regression framework. CpG-specific associations of variability or mean DNAm in relation to the likelihood of association with 100 traits linked to environmental exposures, health and disease were tested within and across ten developmental age bins across the life course. Age was linked to DNAm variability at 29,212 CpG sites. On average, we observed a 1.26 fold increase in DNAm variability per year across the life course. 33,730 CpGs displayed changes in mean DNAm, with 64% of these loci showing decreases in DNAm over time. CpG sites linked to traits were in general more variable across the life course. Our study provides, for the first time, a map of the human methylome across the life course, which is publicly accessible through a searchable online database. This resource allows researchers to query CpG-specific trajectories from birth to old age and link these to health and disease.
- organism: human
- assay: DNA methylation
- research focus: differential expression
- approach: statistical model
- Citations
- 5
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