Identification of ADAMTS7 as a novel locus for coronary atherosclerosis and association of ABO with myocardial infarction in the presence of coronary atherosclerosis: two genome-wide association studies.

BACKGROUND: We tested whether genetic factors distinctly contribute to either development of coronary atherosclerosis or, specifically, to myocardial infarction in existing coronary atherosclerosis. METHODS: We did two genome-wide association studies (GWAS) with coronary angiographic phenotyping in participants of European ancestry. To identify loci that predispose to angiographic coronary artery disease (CAD), we compared individuals who had this disorder (n=12,393) with those who did not (controls, n=7383). To identify loci that predispose to myocardial infarction, we compared patients who had angiographic CAD and myocardial infarction (n=5783) with those who had angiographic CAD but no myocardial infarction (n=3644). FINDINGS: In the comparison of patients with angiographic CAD versus controls, we identified a novel locus, ADAMTS7 (p=4·98×10(-13)). In the comparison of patients with angiographic CAD who had myocardial infarction versus those with angiographic CAD but no myocardial infarction, we identified a novel association at the ABO locus (p=7·62×10(-9)). The ABO association was attributable to the glycotransferase-deficient enzyme that encodes the ABO blood group O phenotype previously proposed to protect against myocardial infarction. INTERPRETATION: Our findings indicate that specific genetic predispositions promote the development of coronary atherosclerosis whereas others lead to myocardial infarction in the presence of coronary atherosclerosis. The relation to specific CAD phenotypes might modify how novel loci are applied in personalised risk assessment and used in the development of novel therapies for CAD. FUNDING: The PennCath and MedStar studies were supported by the Cardiovascular Institute of the University of Pennsylvania, by the MedStar Health Research Institute at Washington Hospital Center and by a research grant from GlaxoSmithKline. The funding and support for the other cohorts contributing to the paper are described in the webappendix.

Meta-analysis and imputation refines the association of 15q25 with smoking quantity.

Smoking is a leading global cause of disease and mortality. We established the Oxford-GlaxoSmithKline study (Ox-GSK) to perform a genome-wide meta-analysis of SNP association with smoking-related behavioral traits. Our final data set included 41,150 individuals drawn from 20 disease, population and control cohorts. Our analysis confirmed an effect on smoking quantity at a locus on 15q25 (P = 9.45 x 10(-19)) that includes CHRNA5, CHRNA3 and CHRNB4, three genes encoding neuronal nicotinic acetylcholine receptor subunits. We used data from the 1000 Genomes project to investigate the region using imputation, which allowed for analysis of virtually all common SNPs in the region and offered a fivefold increase in marker density over HapMap2 (ref. 2) as an imputation reference panel. Our fine-mapping approach identified a SNP showing the highest significance, rs55853698, located within the promoter region of CHRNA5. Conditional analysis also identified a secondary locus (rs6495308) in CHRNA3.

A genome-wide meta-analysis identifies 22 loci associated with eight hematological parameters in the HaemGen consortium.

The number and volume of cells in the blood affect a wide range of disorders including cancer and cardiovascular, metabolic, infectious and immune conditions. We consider here the genetic variation in eight clinically relevant hematological parameters, including hemoglobin levels, red and white blood cell counts and platelet counts and volume. We describe common variants within 22 genetic loci reproducibly associated with these hematological parameters in 13,943 samples from six European population-based studies, including 6 associated with red blood cell parameters, 15 associated with platelet parameters and 1 associated with total white blood cell count. We further identified a long-range haplotype at 12q24 associated with coronary artery disease and myocardial infarction in 9,479 cases and 10,527 controls. We show that this haplotype demonstrates extensive disease pleiotropy, as it contains known risk loci for type 1 diabetes, hypertension and celiac disease and has been spread by a selective sweep specific to European and geographically nearby populations.

Pharmacological effects of lipid-lowering drugs recapitulate with a larger amplitude the phenotypic effects of common variants within their target genes.

BACKGROUND: A major expectation underlying the search for novel susceptibility genes for common diseases using genome-wide association studies (GWAS) is that these discoveries will lead to new drug targets. This claim has not been verified yet. Here, we tested the hypothesis that common single nucleotide polymorphisms (SNPs) within drug target genes are associated with the corresponding phenotypes, using a population-based GWAS dataset and lipid-lowering drugs as a test case. METHODS: We examined the association between 36 genotyped and 193 imputed SNPs within four lipid-lowering drug target genes (HMGCR, PPARA, HM74A/GPR109A and CETP) and four non-lipid drug target genes (ACE, AGTR1, P2RY12, and ATP4B) and lipid phenotypes, blood pressure, and coronary artery disease in 5635 adult participants of the Lausanne, Switzerland, CoLaus study, genotyped using the Affymetrix 500K SNP chip technology. RESULTS: The phenotypes associated with SNPs within drug target genes recapitulated to a certain extent the pharmacological effects of the drug. The amplitude of the SNP effect was about 10 times smaller than the pharmacological effect of the corresponding drug. In particular, several CETP SNPs were associated with an elevation in HDL-cholesterol levels, yet a lower diastolic blood pressure, providing evidence that the blood pressure elevation induced by the CETP inhibitor torcetrapib is more likely compound specific than class specific. CONCLUSION: Pharmacological modulation of lipid-lowering drug targets recapitulates, and markedly amplifies, the phenotypic effects of common SNPs within these target genes. This data provides indirect evidence that, with certain limitations, large-scale GWAS represent a new tool for the discovery and the development of innovative drugs.