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Genetic contribution to variation in DNA methylation at maternal smoking-sensitive loci in exposed neonates

Version 2 2016-08-25, 23:02
Version 1 2016-07-13, 07:00
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posted on 2016-08-25, 23:02 authored by Semira Gonseth, Adam J. de Smith, Ritu Roy, Mi Zhou, Seung-Tae Lee, Xiaorong Shao, Juhi Ohja, Margaret R. Wrensch, Kyle M. Walsh, Catherine Metayer, Joseph L. Wiemels

Epigenome-wide DNA methylation association studies have identified highly replicable genomic loci sensitive to maternal smoking during gestation. The role of inter-individual genetic variation in influencing DNA methylation, leading to the possibility of confounding or bias of such associations, has not been assessed. We investigated whether the DNA methylation levels at the top 10 CpG sites previously associated with exposure to maternal smoking during gestation were associated with individual genetic variation at the genome-wide level. Genome-wide association tests between DNA methylation at the top 10 candidate CpG and genome-wide SNPs were performed in 736 case and control participants of the California Childhood Leukemia Study. Three of the strongest maternal-smoking sensitive CpG sites in newborns were significantly associated with SNPs located proximal to each gene: cg18146737 in the GFI1 gene with rs141819830 (P = 8.2×10−44), cg05575921 in the AHRR gene with rs148405299 (P = 5.3×10−10), and cg12803068 in the MYO1G gene with rs61087368 (P = 1.3×10−18). For the GFI1 CpG cg18146737, the underlying genetic variation at rs141819830 confounded the association between maternal smoking and DNA methylation in our data (the regression coefficient changed from −0.02 [P = 0.139] to −0.03 [P = 0.015] after including the genotype). Our results suggest that further studies using DNA methylation at cg18146737, cg05575921, or cg12803068 that aim to assess exposure to maternal smoking during gestation should include genotype at the corresponding SNP. New methods are required for adequate and routine inclusion of genotypic influence on DNA methylation in epigenome-wide association studies to control for potential confounding.

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