Journal
AMERICAN JOURNAL OF HUMAN GENETICS
Volume 101, Issue 4, Pages 590-602Publisher
CELL PRESS
DOI: 10.1016/j.ajhg.2017.09.003
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Funding
- Wellcome Trust [102215/2/13/2]
- 23andMe
- UK BBSRC [BB/I025751/1, BB/I025263/1]
- UK Medical Research Council (MRC Integrative Epidemiology Unit) [MC UU 12013/1, MC UU 12013/2, MC UU 12013/3, MC UU 12013/8]
- Elizabeth Blackwell Institute [EBI 424]
- UK Medical Research Council [102215/2/13/2]
- BBSRC [BB/I025751/1, BB/I025263/1] Funding Source: UKRI
- MRC [MC_PC_16067, MC_UU_12013/8, MC_UU_12013/1, MC_UU_12013/3, MC_UU_12013/2, MC_PC_15049] Funding Source: UKRI
- Biotechnology and Biological Sciences Research Council [BB/I025751/1, BB/I025263/1] Funding Source: researchfish
- Medical Research Council [G9815508, MC_UU_12013/2, MC_UU_12013/8, MC_UU_12013/1, MC_PC_15018, MC_UU_12013/3, MC_PC_16067, MC_PC_15049] Funding Source: researchfish
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The extent to which genetic influences on cardiovascular disease risk are mediated by changes in DNA methylation levels has not been systematically explored. We developed an analytical framework that integrates genetic fine mapping and Mendelian randomization with epigenome-wide association studies to evaluate the causal relationships between methylation levels and 14 cardiovascular disease traits. We identified ten genetic loci known to influence proximal DNA methylation which were also associated with cardiovascular traits after multiple-testing correction. Bivariate fine mapping provided evidence that the individual variants responsible for the observed effects on cardiovascular traits at the ADCY3 and ADIPOQ loci were potentially mediated through changes in DNA methylation, although we highlight that we are unable to reliably separate causality from horizontal pleiotropy. Estimates of causal effects were replicated with results from large-scale consortia. Genetic variants and CpG sites identified in this study were enriched for histone mark peaks in relevant tissue types and gene promoter regions. Integrating our results with expression quantitative trait loci data, we provide evidence that variation at these regulatory regions is likely to also influence gene expression levels at these loci.
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