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: Supplemental Information. of A null mutation in ANGPTL8 does not associate with either plasma glucose or type 2 diabetes in humans

Figure S1. In-silico predictions of the impact of premature termination codon p.Q121X suggests that the variant would trigger nonsensemediated decay. Table S1. ANGPTL8 p.Q121X and type 2 diabetes status by study. (PDF 145 kb

Systematic Cell-Based Phenotyping of Missense Alleles Empowers Rare Variant Association Studies: A Case for <i>LDLR</i> and Myocardial Infarction

<div><p>A fundamental challenge to contemporary genetics is to distinguish rare missense alleles that disrupt protein functions from the majority of alleles neutral on protein activities. High-throughput experimental tools to securely discriminate between disruptive and non-disruptive missense alleles are currently missing. Here we establish a scalable cell-based strategy to profile the biological effects and likely disease relevance of rare missense variants <i>in vitro</i>. We apply this strategy to systematically characterize missense alleles in the low-density lipoprotein receptor (<i>LDLR</i>) gene identified through exome sequencing of 3,235 individuals and exome-chip profiling of 39,186 individuals. Our strategy reliably identifies disruptive missense alleles, and disruptive-allele carriers have higher plasma LDL-cholesterol (LDL-C). Importantly, considering experimental data refined the risk of rare <i>LDLR</i> allele carriers from 4.5- to 25.3-fold for high LDL-C, and from 2.1- to 20-fold for early-onset myocardial infarction. Our study generates proof-of-concept that systematic functional variant profiling may empower rare variant-association studies by orders of magnitude.</p></div

A schematic illustration of SNP selection process for the primary analysis.

<p>A schematic illustration of SNP selection process for the primary analysis.</p

SNP selection process for the secondary analysis.

<p>SNP selection process for the secondary analysis.</p

Summary of subjects, methods and analyses.

<p>a. Number of SNP pairs for which interaction testing was performed - may not equal the number of possible pair-wise tests [n*(n−1)/2] because some pairs were captured in previous Analyses (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041730#pone.0041730.s001" target="_blank">File S1</a> Supporting <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041730#pone-0041730-g002" target="_blank">Figure 2</a>), and some tests were not feasible due to low allele frequencies (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041730#pone.0041730.s001" target="_blank">File S1</a> Section 3.3). b. Significance threshold computed using permutations under the null hypothesis (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041730#pone.0041730.s001" target="_blank">File S1</a> Section 3.4) c. SNP pairs with p-value for interaction within 3 orders of magnitude of the significance threshold for each Analysis were brought forward for validation in the WTCCC sample; the numbers of SNP pairs for which data were available in the WTCCC study are shown. <i>LDL</i>, concentration of LDL cholesterol; <i>HDL</i>, concentration of HDL cholesterol; <i>TG</i>, triglyceride concentration; <i>BP</i>, blood pressure; <i>CH</i>, carbohydrate metabolism (loci associated with risk of Type II diabetes and related phenotypes, such as fasting glucose concentration); <i>SMK</i>, smoking; <i>OB</i>, obesity; <i>small LDL</i>, concentration of small atherogenic LDL particles; <i>Lp(a)</i>, plasma levels of lipoprotein(a); <i>CHD</i>, risk of coronary heart disease; <i>MI</i>, risk of myocardial infarction.</p

Suggestive SNP-SNP interactions—primary analysis.

<p>SNP: single nucleotide polymorphism, Chr: chromosome; MAF: minor allele frequency; BHF-FHS: British Heart Foundation Family Heart Study; MIGen: Myocardial Infarction Genetics Consortium; SNPA Pvalue: level of nominal statistical significance for single marker association with coronary artery disease for SNP A; SNPB Pvalue: level of nominal statistical significance for single marker association with coronary artery disease for SNP B; Int. Pvalue BHF-FHS: interaction P value in BHF-FHS; Int. Pvalue MIGen: interaction P value in MIGen; N/A: replication not available. PDE11A: phosphodiesterase 11A; SEC1P: secretory blood group 1, pseudogene; SERPINA12: serpin peptidase inhibitor, clade A; SRI: sorcin; ZHX2: zinc fingers and homeoboxes 2; NR5A2: nuclear receptor subfamily 5, group A, member 2; ANGPTL4: angiopoietin-like 4; NRG3: neuregulin 3; RPSAP15: ribosomal protein SA pseudogene 15; CSRP3: cysteine and glycine-rich protein 3; GSTM3: glutathione S-transferase mu 3; RYR2: ryanodine receptor 2; TBXAS1: thromboxane A synthase 1; TAC1: tachykinin, precursor 1; P2RX4: purinergic receptor P2X, ligand-gated ion channel, 4; SCARB2: scavenger receptor class B, member 2; NOD1: nucleotide-binding oligomerization domain containing 1; PDGFD: platelet derived growth factor D.</p><p>Suggestive SNP-SNP interactions—primary analysis.</p

Functions and distribution of <i>LDLR</i> rare missense alleles identified through exome sequencing of 3,235 individuals.

<p><b>(A)</b> Plasma LDL-C (in mg/dl) in <i>LDLR</i> missense allele carriers (dots) from the ATVB cohort according to functional category (for classification, see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004855#sec004" target="_blank">Methods</a>). LoF, loss-of-function. Means are indicated by horizontal bars. p-value was determined by 2-sided, 2-tailed Student’s t-test. <b>(B, C)</b> Individual <i>LDLR</i> missense variants identified through exome sequencing of indicated number of individuals are depicted according to genomic position starting at the 5’end (top). The numbers next to each variant represent the number of times the respective variant was observed in cases and controls, respectively, with regard to plasma LDL-C levels (b) and early-onset myocardial infarction (MI; c). Colors in circles represent indicated functional classes as determined either by an overlap of four bioinformatic prediction tools (PolyPhen-2, SIFT, MutationAssessor and MutationTaster; see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004855#sec004" target="_blank">Methods</a>) (“prediction”) or cell-based experimental studies of LDL-uptake. Variants in bold have been observed in both, cases and controls. <b>(D)</b> Power calculations for the number of sequenced individuals needed to reach exome-wide significance (p<2.5×10^-6, reflected by power = 1) for association with MI-risk when the indicated classes of rare <i>LDLR</i> alleles are taken into account. For details, see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004855#sec004" target="_blank">Methods</a>.</p

Baseline Characteristics of cases in the British Heart Foundation-Family Heart Study and the Myocardial Infarction Genetics studies.

<p>Data are means and standard deviations or counts and percentages, BHF-FHS: British Heart Foundation Family Heart Study; MIGen: Myocardial Infarction Genetics Consortium; MI: myocardial infarction; BMI: body mass index.</p><p>Baseline Characteristics of cases in the British Heart Foundation-Family Heart Study and the Myocardial Infarction Genetics studies.</p

Results of gene-gene interaction search among CVRF SNPs (Analysis 1).

<p><i>Panel A</i>. Plot of the top result (arrow) from Analysis 1 against the distribution of the top results from 10,000 permutations under the null hypothesis (dotted line). The permuted top results are expected to follow a beta-distribution (solid line, parameters obtained from permuted top results), the 95^th percentile of which was taken as the significance level required to obtain a Type II error of 0.05 (arrow). <i>Inset</i>: While the significance level computed in Analysis 1 (dashed black line) was estimated using 10,000 null permutations, this estimate was found to stabilize rapidly with increasing number of permutations (black points) and to change little after 100–200 permutations. Consequently, we progressively reduced the number of permutations used to estimate the significance level in subsequent Analyses. <i>Panel B</i>. Quantile-quantile plot showing rank-ordered observed results (black points) from 29,161 tests in Analysis 1 (<i>y-axis</i>) against expected results (<i>x-axis</i>) estimated from 10,000 permutations under the null hypothesis (randomized phenotype). See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041730#pone.0041730.s001" target="_blank">File S1</a> Section 3.5 for computation methods. The shaded area corresponds to the 95%CI of the permuted expected results. The 95%CI of a normal distribution is indicated by the dotted lines. <i>Panel C</i>. Estimation of the interaction effect sizes this analysis has 80% power to detect across a range of MAF under an additive × additive interaction model. The heights of the vertical bars correspond to the effect size (OR) detectable for a typical pair of SNPs whose MAFs are as indicated on the horizontal axes.</p