Loss of Cardioprotective Effects at the ADAMTS7 Locus as a Result of Gene-Smoking Interactions

BACKGROUND: Common diseases such as coronary heart disease (CHD) are complex in etiology. The interaction of genetic susceptibility with lifestyle factors may play a prominent role. However, gene-lifestyle interactions for CHD have been difficult to identify. Here, we investigate interaction of smoking behavior, a potent lifestyle factor, with genotypes that have been shown to associate with CHD risk. METHODS: We analyzed data on 60 919 CHD cases and 80 243 controls from 29 studies for gene-smoking interactions for genetic variants at 45 loci previously reported to be associated with CHD risk. We also studied 5 loci associated with smoking behavior. Study-specific gene-smoking interaction effects were calculated and pooled using fixed-effects meta-analyses. Interaction analyses were declared to be significant at a P value of <1.0x10(-3) (Bonferroni correction for 50 tests). RESULTS: We identified novel gene-smoking interaction for a variant upstream of the ADAMTS7 gene. Every T allele of rs7178051 was associated with lower CHD risk by 12% in never-smokers (P= 1.3x10(-16)) in comparison with 5% in ever-smokers (P= 2.5x10(-4)), translating to a 60% loss of CHD protection conferred by this allelic variation in people who smoked tobacco (interaction P value= 8.7x10(-5)). The protective T allele at rs7178051 was also associated with reduced ADAMTS7 expression in human aortic endothelial cells and lymphoblastoid cell lines. Exposure of human coronary artery smooth muscle cells to cigarette smoke extract led to induction of ADAMTS7. CONCLUSIONS: Allelic variation at rs7178051 that associates with reduced ADAMTS7 expression confers stronger CHD protection in never-smokers than in ever-smokers. Increased vascular ADAMTS7 expression may contribute to the loss of CHD protection in smokers.Peer reviewe

Empirical type- 1 error rates and power to detect an outlier study for <i>M</i> at threshold α = 0.05.

<p>Empirical type- 1 error rates and power to detect an outlier study for <i>M</i> at threshold α = 0.05.</p

A comparative power analysis of <i>M</i> and Cochran’s Q to detect systematic heterogeneity.

<p>The nine panels show (from left to right) simulations for 10, 15 and 30 studies, examined at 50, 25 and l0 variants; Data points for the <i>M</i> statistic are represented by filled circles whilst those for Cochran’s Q are denoted by filled triangles. Each data point represents a meta-analysis scenario where effect sizes for the non-outlier studies were held constant (log_e(odds ratio) = 0.182 i.e. odds ratio = 1.2) to model homogeneous effects. The effect sizes of variants in the outlier study were the product of the non-outlier effect size (i.e. log_e(odds ratio) = 0.182) and a parameter (fold-change) to model a continuous series of systematic heterogeneity patterns. All studies were equally weighted (standard error of log_e(odds ratio) = 0.1).</p

Forest plot of <i>M</i> statistics summarizing systematic patterns of heterogeneity among studies in the CARDIOGRAMplusC4D GWAS meta-analysis.

<p>Sorted <i>M</i> statistics are presented for individual studies represented by filled squares with their 95% confidence intervals shown by horizontal lines; the sizes of the squares are proportional to each studies’ inverse-variance weighting. Studies showing weaker (<i>M</i> < 0) than average genetic effects can be distinguished from those showing stronger (<i>M</i> > 0) than average effects.</p

The power of the <i>M</i> statistic to detect systematic outlier studies.

<p>A power analysis of the <i>M</i> statistics for meta-analysis scenarios with varying numbers of studies and variants. The three panels show (from left to right) simulations for 10, 15 and 30 studies; 50, 25 and 10 variant simulations are shown by filled diamonds, filled circles, or open squares respectively. Each data point represents a meta-analysis simulation with 1,000 replicates, where an outlier study was assigned genetic effects that are x-fold stronger than the effects assigned to the remaining studies showing typical effects. Effect sizes for variants in the studies showing typical effects were allocated from an L—shaped distribution (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006755#pgen.1006755.s011" target="_blank">S2 Table</a>) whilst effect sizes for variants in the outlier study were calculated as a multiple of the typical effect size. For example, effect sizes for variants in an outlier study 2-fold-stronger than studies showing typical effects would be computed as (2 x ({0.04, 0.12, 0.2, 0.28, 0.4}, σ = 0.10).</p

Heterogeneity in the CARDIoGRAMplusC4D meta-analysis can be explained by differences in age of CAD onset, family history and ancestry.

<p><i>M</i> statistics for each study in the CARDIoGRAMplusC4D meta-analysis (Y- axis) are plotted against the average variant effect size (expressed as odds ratios) (X-axis) in each study. Panel A shows the ancestry of each study, panel B distinguishes early-onset from late-onset studies and panel C identifies studies ascertained with a positive family history of coronary artery disease. Panel D is a composite plot showing the degree of genetic enrichment among the studies in the meta-analysis, which ranged from non-enriched (late-onset studies without a positive family history of coronary artery disease) to doubly enriched (early-onset studies with a positive family history of coronary artery disease). The dashed lines indicate the Bonferroni corrected 5% significance threshold (<i>M</i> = ±0.483) to allow for multiple testing of 48 studies.</p

Mendelian Randomization (MR) estimates of the association of decreased 25-hydroxyvitamin D (25OHD) on the risk of asthma, atopic dermatitis, and elevated Immunoglobulin E (IgE) levels.

<p>Mendelian Randomization (MR) estimates of the association of decreased 25-hydroxyvitamin D (25OHD) on the risk of asthma, atopic dermatitis, and elevated Immunoglobulin E (IgE) levels.</p

Mendelian randomization estimate of the association of 25-hydroxyvitamin D (25OHD) levels with risk of asthma.

<p>Estimates obtained from using a fixed-effects model. 95% CI, 95% confidence interval; chr, chromosome, OR, odds ratio; SD, standard deviation; SNP, single-nucleotide polymorphism.</p

Characteristics of Single-Nucleotide Polymorphisms (SNPs) used as instrumental variables and their association with asthma, atopic dermatitis, and Immunoglobulin E (IgE) levels.

<p>Characteristics of Single-Nucleotide Polymorphisms (SNPs) used as instrumental variables and their association with asthma, atopic dermatitis, and Immunoglobulin E (IgE) levels.</p

Direct Acyclic Graph (DAG) of the Mendelian randomization analysis for atopic dermatitis.

<p>The effect of single-nucleotide polymorphisms (SNPs) on the change in natural log-transformed 25-hydroxyvitamin D (25OHD) levels. SUNLIGHT, Study of Underlying Genetic Determinants of Vitamin D and Highly Related Traits.</p