Influence of ABO locus on PFA-100 collagen-ADP closure time is not totally dependent on the von willebrand factor. Results of a GWAS on gait-2 project phenotypes

(1) Background: In a previous study, we found that two phenotypes related to platelet reactivity, measured with the PFA-100 system, were highly heritable. The aim of the present study was to identify genetic determinants that influence the variability of these phenotypes: Closure time of collagen-ADP (Col-ADP) and of collagen-epinephrine (Col-Epi). (2) Methods: As part of the GAIT-2 (Genetic Analysis of Idiopathic Thrombophilia (2) Project, 935 individuals from 35 large Spanish families were studied. A genome-wide association study (GWAS) with ≈ 10 M single nucleotide polymorphisms (SNPs) was carried out with Col-ADP and Col-Epi phenotypes. (3) Results: The study yielded significant genetic signals that mapped to the ABO locus. After adjusting both phenotypes for the ABO genotype, these signals disappeared. After adjusting for von Willebrand factor (VWF) or for coagulation factor VIII (FVIII), the significant signals disappeared totally for Col-Epi phenotype but only partially for Col-ADP phenotype. (4) Conclusion: Our results suggest that the ABO locus exerts the main genetic influence on PFA-100 phenotypes. However, while the effect of the ABO locus on Col-Epi phenotype is mediated through VWF and/or FVIII, the effect of the ABO locus on Col-ADP phenotype is partly produced through VWF and/or FVIII, and partly through other mechanisms

Association of Plasminogen Activator Inhibitor (PAI)-1 (SERPINE1) SNPs With Myocardial Infarction, Plasma PAI-1, and Metabolic Parameters

Objective— The purpose of this study was to investigate the effects of plasminogen activator inhibitor-1 (PAI-1) gene (SERPINE1) single nucleotide polymorphisms (SNPs) on the risk of myocardial infarction (MI), on PAI-1 levels, and factors related to the metabolic syndrome. Methods and Results— Eleven SNPs capturing the common genetic variation of the SERPINE1 gene were genotyped in the HIFMECH study. In the 510 male cases and their 543 age-matched controls, a significant gene-smoking interaction was observed. In nonsmokers, the rs7242-G allele was more frequent in cases than in controls (0.486 versus 0.382, P =0.013) whereas the haplotype derived from the rs2227631 (−844A>G)-G and rs2227683-A alleles was ≈3-fold lower in cases than in controls (0.042 versus 0.115, P =0.006). SERPINE1 haplotypes explained 3.5% ( P =0.007) of the variability of PAI-1 levels, which was attributable to the combined effects of 3 SNPs, −844A>G, rs2227666, and rs2227694. The rs6092 (Ala15Thr) and rs7242 SNPs acted additively to explain 4.4% of the variability of plasma insulin levels and 1.6% of the variability of BMI ( P <10 −3 and P =0.023, respectively). Conclusions— SERPINE1 haplotypes are mildly associated with plasma levels of PAI-1 and with the risk of MI in nonsmokers. They are also associated with insulin levels and BMI

Human neuropeptide Y signal peptide gain-of-function polymorphism is associated with increased body mass index: possible mode of function

Neuropeptide Y (NPY) has been implicated in the control of food intake and energy balance based on many observations in animals. We have studied single nucleotide polymorphisms (SNPs) within the regulatory and coding sequences of the human NPY gene. One variant (1128 T>C), which causes an amino acid change from leucine to proline at codon 7 in the signal peptide of NPY, was associated with increased body mass index (BMI) in two separate Swedish populations of normal and overweight individuals. In vitro transcription and translation studies indicated the unlikelihood that this signal peptide variation affects the site of cleavage and targeting or uptake of NPY into the endoplasmic reticulum (ER). However, the mutant, and to a lesser extent the wild-type, signal peptide by themselves markedly potentiated NPY-induced food intake, as well as hypothalamic NPY receptor signaling. Our findings in humans strongly indicate that the NPY signaling system is implicated in body weight regulation and suggest a new and unexpected functional role of a signal peptide

Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution.

To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11)) and MSRA (WC, P = 8.9x10(-9)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity

Peripheral Sensory Neuropathy Associates With Micro- or Macroangiopathy: Results from a population-based study of type 2 diabetic patients in Sweden

OBJECTIVE—To assess associations between peripheral sensory neuropathy (PSN) and other diabetes-related complications

Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

OBJECTIVE Glycated hemoglobin (HbA1c), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA1c. We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA1c levels. RESEARCH DESIGN AND METHODS We studied associations with HbA1c in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA1c loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening. RESULTS Ten loci reached genome-wide significant association with HbA1c, including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10−26), HFE (rs1800562/P = 2.6 × 10−20), TMPRSS6 (rs855791/P = 2.7 × 10−14), ANK1 (rs4737009/P = 6.1 × 10−12), SPTA1 (rs2779116/P = 2.8 × 10−9) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10−9), and four known HbA1c loci: HK1 (rs16926246/P = 3.1 × 10−54), MTNR1B (rs1387153/P = 4.0 × 10−11), GCK (rs1799884/P = 1.5 × 10−20) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10−18). We show that associations with HbA1c are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA1c) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA1c. CONCLUSIONS GWAS identified 10 genetic loci reproducibly associated with HbA1c. Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA1c levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA1c

A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease

Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association studies (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of 185 thousand CAD cases and controls, interrogating 6.7 million common (MAF>0.05) as well as 2.7 million low frequency (0.005<MAF<0.05) variants. In addition to confirmation of most known CAD loci, we identified 10 novel loci, eight additive and two recessive, that contain candidate genes that newly implicate biological processes in vessel walls. We observed intra-locus allelic heterogeneity but little evidence of low frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect siz