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. 2015;10(11):1064-73.
doi: 10.1080/15592294.2015.1106672.

The impact of genetic variation and cigarette smoke on DNA methylation in current and former smokers from the COPDGene study

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The impact of genetic variation and cigarette smoke on DNA methylation in current and former smokers from the COPDGene study

Weiliang Qiu et al. Epigenetics. 2015.

Abstract

DNA methylation can be affected by systemic exposures, such as cigarette smoking and genetic sequence variation; however, the relative impact of each on the epigenome is unknown. We aimed to assess if cigarette smoking and genetic variation are associated with overlapping or distinct sets of DNA methylation marks and pathways. We selected 85 Caucasian current and former smokers with genome-wide single nucleotide polymorphism (SNP) genotyping available from the COPDGene study. Genome-wide methylation was obtained on DNA from whole blood using the Illumina HumanMethylation27 platform. To determine the impact of local sequence variation on DNA methylation (mQTL), we examined the association between methylation and SNPs within 50 kb of each CpG site. To examine the impact of cigarette smoking on DNA methylation, we examined the differences in methylation by current cigarette smoking status. We detected 770 CpG sites annotated to 708 genes associated at an FDR < 0.05 in the cis-mQTL analysis and 1,287 CpG sites annotated to 1,242 genes, which were nominally associated in the smoking-CpG association analysis (P(unadjusted) < 0.05). Forty-three CpG sites annotated to 40 genes were associated with both SNP variation and current smoking; this overlap was not greater than that expected by chance. Our results suggest that cigarette smoking and genetic variants impact distinct sets of DNA methylation marks, the further elucidation of which may partially explain the variable susceptibility to the health effects of cigarette smoking. Ascertaining how genetic variation and systemic exposures differentially impact the human epigenome has relevance for both biomarker identification and therapeutic target development for smoking-related diseases.

Keywords: CpG site; cis-mQTL; environmental factor; epigenetics; genetic variant.

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Figures

Figure 1.
Figure 1.
Volcano plot of the cis-mQTL analysis. Dashed red line represents an FDR<0 .05. Gene symbols for the top 20 cis-mQTL tests are shown in the volcano plot.
Figure 2.
Figure 2.
Manhattan plot of cis-mQTL analysis.
Figure 3.
Figure 3.
Top-left panel: Proportions of unique significant SNPs (i.e., SNPs in significant cis-mQTL tests) across the 22 chromosomes; Top-right panel: Proportions of unique significant CpG sites (i.e., CpG sites in significant cis-mQTL tests) across the 22 chromosomes; Bottom-left panel: Proportions of unique significant genes (i.e., genes corresponding to CpG sites in significant cis-mQTL tests) across the 22 chromosomes; Bottom-right panel: Proportions of significant cis-mQTL tests across the 22 chromosomes.
Figure 4.
Figure 4.
Distribution of mQTLs with p-value < 0.001 by distance from CpG site. For panel (a), each bin has a width of 5KB [range ≤ +45KB to ≥ −45KB from the CpG site]. For panel (b), each bin has a width of 0.5KB [range ≤ +5KB to ≥ −5KB from the CpG site].
Figure 5.
Figure 5.
Parallel boxplots of CpG site methylation level vs. SNP genotype for the top 2 significant cis-mQTL tests.
Figure 6.
Figure 6.
Parallel boxplots of CpG site methylation level vs. smoking status for the top 2 significant smoking-CpG-association tests.
Figure 7.
Figure 7.
Proportional Venn diagram of CpG sites associated with cigarette smoking (blue) at an unadjusted P < 0.05 and genetic variants (red) at a FDR < 0.05. A total of 43 sites were significant in both analyses.

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