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

Summary of leading SNPs from the 19 loci showing strong or suggestive association with IA in a multinational GWAS containing Finnish patients [12].

<p>Association results with intracranial aneurysm (IA) by Yasuno and colleagues are followed by our meta-analysis association results with systolic blood pressure (SBP), with the ROBUST and the ADVANCED models, respectively.</p><p>Table first shows association p-values with IA for the Finnish sub-group from the multinational GWAS (IA GWAS), followed by results from our meta-analysis of association with systolic blood pressure (SBP) with the ROBUST and ADVANCED models. In the ROBUST model of association we corrected for gender and age and in the ADVANCED model we further corrected for BMI, smoking habits and alcohol consumption.</p><p>Genomic positions are based on the human genome build 36. Alleles are reported on the forward strand of the reference genome. The effects are reported for the alleles increasing risk for IA in the Yasuno et al. studies <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002563#pgen.1002563-Yasuno1" target="_blank">[12]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002563#pgen.1002563-Yasuno2" target="_blank">[13]</a>. If SNP is intergenic, Gene represents the nearest gene. SNPs are directly genotyped unless otherwise marked (* HM2 imputed SNP, ** 1000G+HM3 imputed SNP). Yasuno et al (2011) at 8q24.23 followed-up with rs1554349 instead of the lead SNP, rs6577930.</p><p><b>In bold:</b> locus showing strongest association with SBP in meta-analysis.</p>#<p>‘IA GWAS’ triplet column shows the Finnish sub-group (n_{FINN-IA-CASES} = 912, n_{FINN-CONTROLS} = 8180) association results on IA of the GWAS by Yasuno and colleagues, except for the PPA results, which is not Finnish sub-group specific, but counted for the whole multinational cohort.</p>##<p>PPA: posterior probability of association with IA as calculated by Yasuno and colleagues for the multinational IA GWAS.</p>$<p>‘SBP meta-analysis with ROBUST model’ and ‘with ADVANCED model’ twin-columns show results of our candidate locus meta-analysis with SBP as the outcome variable. SBP meta-analysis beta values are given for IA risk alleles.</p><p>OR: odds ratio, CI: confidence interval, SE: standard error.</p

2q33.1 and 5q23.2 loci cohort-wise ADVANCED model effect estimates and meta-analysis results with systolic blood pressure (SBP).^$

<p>Genomic positions are based on the human genome build 36. Alleles are reported on the forward strand of the reference genome. The effects are reported for the alleles increasing risk for IA in the Yasuno et al. studies <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002563#pgen.1002563-Yasuno1" target="_blank">[12]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002563#pgen.1002563-Yasuno2" target="_blank">[13]</a>. Risk alleles are aligned according to the forward strand of the reference genome. Minor allele frequencies (MAF) are based on from the HapMap Phase II CEU population data.</p>$<p>Diastolic blood pressure (DBP) and mean arterial pressure (MAP) association results from 2q33.1 and 5q23.2 SNP are in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002563#pgen.1002563.s005" target="_blank">Table S2</a>.</p>*<p>Meta SBP: meta-analysis of discovery and replication cohort p-values and beta for systolic blood pressure (SBP) with the ADVANCED model. Association analyses were corrected for gender, age, BMI, smoking habits and alcohol consumption.</p><p>SE: standard error.</p

Cohort-wise effects of risk allele count on SBP.

<p>The higher median age in HBCS is reflected as higher systolic blood pressure (SBP) and less consistent association. Error bars show standard error.</p

Meta-analysis results of 5q23.2 SNPs with systolic blood pressure from all four Finnish cohorts and ICBP-GWAS combined.

<p>Genomic positions are based on the human genome build 36. Risk alleles are aligned according to the forward strand of the reference genome. SE: standard error.</p

Summary of cohort characteristics.

<p>WG: whole-genome, QC: quality control, BP: blood pressure, SBP: systolic blood pressure, DBP: diastolic blood pressure, MAP: mean arterial pressure, PP: pulse pressure, BMI: body-mass index, SD: 1 standard deviation.</p

Multiplicative interaction between Chr. 22q12 (rs2412971) and Chr. 1q32 (rs6677604) loci.

<p>The allelic effects of rs2412971-A by genotype class of rs9275596 (top signal in the HLA, no interaction) and rs6677604 (top signal in at <i>CFHR1/R3</i> locus on Chr. 1q32, significant interaction). The protective effect of rs2412971-A allele is reversed in homozygotes for the rs6677604-A allele, which tags a deletion in <i>CFHR3/R1</i>. The allelic effects are expressed on the log-odds scale and correspond to beta coefficients of the logistic regression model. Error bars correspond to 95% confidence intervals.</p

Conditional analysis of the <i>HLA-DQB1, HLA-DQA1, HLA-DRB1</i> locus.

<p>Conditional analysis of the <i>HLA-DQB1, HLA-DQA1, HLA-DRB1</i> locus.</p

Haplotype analysis of rs9275224, rs2856717, rs9275424, and rs9275596 at the HLA-DQB1/DRB1 locus.

<p>The most common haplotype of 4 major alleles (GCAT) is used as a reference to derive odds ratios for all other haplotypes. Only common haplotypes (frequency >1%) are tested for association.</p

The best predictive model for IgAN based on all the genotyped SNPs and their pairwise interaction terms.

<p>This model represents the solution of a stepwise logistic regression algorithm (BIC-based stepwise model selection). The coefficients from this model are used to refine the risk score for IgAN.</p