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

Additional file 1: of DNA methylation patterns associated with oxidative stress in an ageing population

Supplementary Data. Figure S1. Plot showing the first two PC components of the PIVUS genotype data with the 1000G multi population reference panel. Figure S3. Comparison of regression coefficients from the primary and secondary models (additionally adjusted for BMI) for oxidative marker BCD-LDL. Table S9. Enrichment in JASPAR transcription factor binding site motifs in genes annotated to oxidative stress associated CpGs (Bonferroni-adjusted p-value < 0.05). Table S10. Enriched biological process among genes annotated to oxidative marker associated CpGs (adjusted p-value < 0.05). Table S11. Enriched annotation clusters among genes annotated to oxidative marker CpGs (enrichment score > 1). Table S12. Significant lead cis-meQTL SNPs of oxidative marker CpGs (FDR <0.05). Table S13. Overlap across genotype-CpG (FDR <0.05), genotype-phenotype (p-value <0.001), and CpG-phenotype (FDR <0.05) results. (DOCX 135 kb

Additional file 3: of DNA methylation patterns associated with oxidative stress in an ageing population

Supplemental Tables. Table S1. Methylation sites associated with TGSH (FDR <0.05). Table S2. Methylation sites associated with GSH (FDR <0.05. Table S3. Methylation sites associated with GSSG (FDR <0.05). Table S4. Methylation sites associated with ratio of GSSG-to-GSH (FDR <0.05). Table S5. Methylation sites associated with levels of HCY (FDR <0.05). Table S6. Methylation sites associated with levels of oxLDL (FDR <0.05). Table S7. Methylation sites associated with levels of CD (FDR <0.05). Table S8: Methylation sites associated with BCD-LDL (FDR <0.05). (XLS 185 kb

Anomaly detection.

<p>The anomaly detection was performed by comparing intensities of one male subject with high liver fat content to a preliminary whole body imaging atlas, of subjects with normal liver fat, that holds pointwise distributions of fat content of 50 male subjects. The whole-body imaging atlas is visualized by the mean value and standard deviation.</p

Additional file 5: Table S14. of DNA methylation patterns associated with oxidative stress in an ageing population

Nominal significant associations (p-value <0.05) for significant meQTL SNPs in GWAS data from the CARDIOGRAMplusC4D and DIAGRAM consortia. (XLSX 59 kb

Group comparisons.

<p>The point-by-point P-values (P-maps) of local tissue volume were obtained by two-tailed t-tests between low weight subjects and high weight subjects (20 men and 23 women).</p

Illustration of Imiomics compared to a standard analysis approach.

<p>The standard approach analyses only a small amount of the collected imaging information using explicit measurements. Imiomics uses all collected imaging information and allows analyses of relationships to non-imaging data. In addition to more efficient data usage this allows both untargeted and targeted statistical analysis in the whole-body region, i.e. completely new types of imaging studies.</p

Dice values.

<p>Dice values obtained by composition of deformation fields for MRI scans from the POEM cohort (n = 68 for female and n = 60 for male) for the bodyparts shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0169966#pone.0169966.g003" target="_blank">Fig 3</a>. The fat and water (wat) content images are thresholded at 50% before and after the composed deformation. The Dice coefficient values are computed on these thresholded binary images. The table holds the mean and standard deviation Dice values.</p

Additional file 2: Figure S2. of DNA methylation patterns associated with oxidative stress in an ageing population

DNA methylation sites associated with oxidative markers at a Bonferroni-corrected alpha threshold 0.05 (p-value <1.1E-07). CpG sites are ordered by chromosomal position from bottom (chr. 1) to top (chr. 22). (EPS 14 kb

Longitudinal analysis.

<p>One coronal slice of the moving, deformed moving and fixed images of absolute fat content is shown together with a difference image between the fixed and deformed moving images. The subject underwent low calorie diet (LCD) and gastric bypass (GBP) between the moving and fixed MRI-scans. The total weight loss was 14 kg.</p