David-Alexandre Trégouët

Genome-wide haplotype association study identifies the SLC22A3-LPAL2-LPA gene cluster as a risk locus for coronary artery disease

We identify the SLC22A3-LPAL2-LPA gene cluster as a strong susceptibility locus for coronary artery disease (CAD) through a genome-wide haplotype association (GWHA) study. This locus was not identified from previous genome-wide association (GWA) studies focused on univariate analyses of SNPs. The proposed approach may have wide utility for analyzing GWA data for other complex traits.

A new algorithm for haplotype‐based association analysis: the Stochastic‐EM algorithm

It is now widely accepted that haplotypic information can be of great interest for investigating the role of a candidate gene in the etiology of complex diseases. In the absence of family data, haplotypes cannot be deduced from genotypes, except for individuals who are homozygous at all loci or heterozygous at only one site. Statistical methodologies are therefore required for inferring haplotypes from genotypic data and testing their association with a phenotype of interest. Two maximum likelihood algorithms are often used in the context of haplotype‐based association studies, the Newton‐Raphson (NR) and the Expectation‐Maximisation (EM) algorithms. In order to circumvent the limitations of both algorithms, including convergence to local minima and saddle points, we here described how a stochastic version of the EM algorithm, referred to as SEM, could be used for testing haplotype‐phenotype association. Statistical properties of the SEM algorithm were investigated through a simulation study for a large range of practical situations, including small/large samples and rare/frequent haplotypes, and results were compared to those obtained by use of the standard NR algorithm. Our simulation study indicated that the SEM algorithm provides results similar to those of the NR algorithm, making the SEM algorithm of great interest for haplotype‐based association analysis, especially when the number of polymorphisms is quite large.

Human herpesvirus 8 transmission from mother to child and between siblings in an endemic population.

BACKGROUND Transmission of human herpesvirus 8 (HHV-8), the aetiological agent of Kaposis sarcoma, is known to occur during sex among homosexual men. However, other modes of HHV-8 transmission remain to be elucidated in endemic populations. METHODS We did a population-based seroepidemiological survey in a village in French Guiana among 1337 individuals of African origin (age 2-91 years) who had reliable genealogical data. Plasma samples were taken and tested for HHV-specific IgG by immunofluorescence assay. Risk factors and familial correlations for HHV-8 seropositivity were modelled by logistic regression analysis by use of the estimating equations approach, which expresses familial dependences in terms of odds ratios. Familial odds ratios were also acquired by use of the distribution of all possible pairs of a given familial dependence. FINDINGS The overall HHV-8 seroprevalence was 13.2% with no difference according to sex. HHV-8 seropositivity was strongly age dependent: at 1.2% under 5 years, HHV-8 seroprevalence rose up to a plateau around 15% between 15 and 40 years, and showed a seroprevalence of more than 27% in individuals older than 40 years. Strong familial aggregation in HHV-8 seroprevalence was found with high mother-child (odd ratio 2.8 [95% CI 1.6-5.0]) and sib-sib (3.8 [1.6-9.5]) correlations. By contrast, no significant correlation between spouses (0.6 [0.2-1.9]) was seen. INTERPRETATION This pattern of familial aggregation, together with the variation of HHV-8 seroprevalence with age, indicate that, in endemic populations, HHV-8 transmission mainly occurs from mother to child and between siblings during childhood and adolescence.

Genetic Markers Enhance Coronary Risk Prediction in Men: The MORGAM Prospective Cohorts

Background More accurate coronary heart disease (CHD) prediction, specifically in middle-aged men, is needed to reduce the burden of disease more effectively. We hypothesised that a multilocus genetic risk score could refine CHD prediction beyond classic risk scores and obtain more precise risk estimates using a prospective cohort design. Methods Using data from nine prospective European cohorts, including 26,221 men, we selected in a case-cohort setting 4,818 healthy men at baseline, and used Cox proportional hazards models to examine associations between CHD and risk scores based on genetic variants representing 13 genomic regions. Over follow-up (range: 5–18 years), 1,736 incident CHD events occurred. Genetic risk scores were validated in men with at least 10 years of follow-up (632 cases, 1361 non-cases). Genetic risk score 1 (GRS1) combined 11 SNPs and two haplotypes, with effect estimates from previous genome-wide association studies. GRS2 combined 11 SNPs plus 4 SNPs from the haplotypes with coefficients estimated from these prospective cohorts using 10-fold cross-validation. Scores were added to a model adjusted for classic risk factors comprising the Framingham risk score and 10-year risks were derived. Results Both scores improved net reclassification (NRI) over the Framingham score (7.5%, p = 0.017 for GRS1, 6.5%, p = 0.044 for GRS2) but GRS2 also improved discrimination (c-index improvement 1.11%, p = 0.048). Subgroup analysis on men aged 50–59 (436 cases, 603 non-cases) improved net reclassification for GRS1 (13.8%) and GRS2 (12.5%). Net reclassification improvement remained significant for both scores when family history of CHD was added to the baseline model for this male subgroup improving prediction of early onset CHD events. Conclusions Genetic risk scores add precision to risk estimates for CHD and improve prediction beyond classic risk factors, particularly for middle aged men.

Testing association between candidate-gene markers and phenotype in related individuals, by use of estimating equations

Association studies are one of the major strategies for identifying genetic factors underlying complex traits. In samples of related individuals, conventional statistical procedures are not valid for testing association, and maximum likelihood (ML) methods have to be used, but they are computationally demanding and are not necessarily robust to violations of their assumptions. Estimating equations (EE) offer an alternative to ML methods, for estimating association parameters in correlated data. We studied through simulations the behavior of EE in a large range of practical situations, including samples of nuclear families of varying sizes and mixtures of related and unrelated individuals. For a quantitative phenotype, the power of the EE test was comparable to that of a conventional ML test and close to the power expected in a sample of unrelated individuals. For a binary phenotype, the power of the EE test decreased with the degree of clustering, as did the power of the ML test. This result might be partly explained by a modeling of the correlations between responses that is less efficient than that in the quantitative case. In small samples (< 50 families), the variance of the EE association parameter tended to be underestimated, leading to an inflation of the type I error. The heterogeneity of cluster size induced a slight loss of efficiency of the EE estimator, by comparison with balanced samples. The major advantages of the EE technique are its computational simplicity and its great flexibility, easily allowing investigation of gene-gene and gene-environment interactions. It constitutes a powerful tool for testing genotype-phenotype association in related individuals.

Activated thrombin activatable fibrinolysis inhibitor levels are associated with the risk of cardiovascular death in patients with coronary artery disease: the AtheroGene study

Summary.  Background: Thrombin activatable fibrinolysis inhibitor (TAFI) attenuates fibrinolysis. Results on the association between TAFI levels and the risk of coronary artery disease (CAD) are inconsistent. Objectives: We investigated the association between TAFI levels and the risk of cardiovascular events in CAD. Patients/Methods: 1668 individuals with angiographically proven CAD at baseline were followed for a median of 2.3 years, as part of the prospective AtheroGene cohort. Fifty‐six deaths from cardiovascular (CV) causes and 35 non‐fatal CV events were observed. Results: At baseline, three TAFI measurements were available: one evaluating the total amount of TAFI (t‐TAFI), one measuring the TAFIa/TAFIai amount, and the last the released activated peptide (TAFI‐AP). TAFIa/TAFIai levels were associated with increased risk of CV death [hazard ratio (HR) for one tertile increase, 2.38 (1.56–3.63); P < 10−4]. This association remained significant after adjustment for conventional risk factors, CRP levels, white blood count and markers of thrombin generation and fibrinolysis [HR = 1.69 (1.07–2.67); P = 0.01]. In addition, CPB2 gene polymorphisms explained 12%, 6%, and 3% of t‐TAFI, TAFIa/TAFIai and TAFI‐AP levels, respectively, but none was associated with CV events. Conclusions: The amount of activated TAFI, measured by TAFIa/TAFIai ELISA, but not of the t‐TAFI is independently associated with the risk of CV death.

Biological and genetic factors influencing plasma factor VIII levels in a healthy family population: results from the Stanislas cohort

The mechanisms underlying the variability of factor VIII (FVIII) levels are still poorly understood. The only receptor of FVIII identified so far is the lipoprotein receptor‐related protein (LRP), which is thought to be involved in FVIII degradation. We aimed to characterize biological and genetic factors related to FVIII variability, focusing on coding polymorphisms of the LRP gene and polymorphisms potentially detected by molecular screening of the LRP‐binding domains of the FVIII gene. Plasma FVIII coagulant activity (FVIII:C) and von Willebrand factor (VWF:Ag) antigen levels were measured in a sample of 100 healthy nuclear families (200 parents and 224 offspring). The ABO blood group and the three coding polymorphisms of the LRP gene (A217V, D2080N and C766T) were genotyped. Lipids and anthropometric factors poorly contributed to the variability of FVIII:C (<5%). A strong effect of ABO blood groups on FVIII:C levels was observed that remained significant after adjustment for VWF:Ag levels (P = 0·02). These two factors explained more than 50% of FVIII:C variability. After adjustment for VWF:Ag and ABO blood groups, a residual resemblance for FVIII:C persisted between biological relatives (ρ = 0·13 ± 0·06 between parents and offspring, ρ = 0·24 ± 0·09 between siblings) compatible with an additional genetic influence. The N allele of the LRP/D2080N polymorphism was associated with decreased levels of FVIII:C (90·4 ± 8·7 vs. 102·2 ± 3·5 IU/dl, P = 0·03) and VWF:Ag levels (109·1 ± 11·2 vs. 125·4 ± 4·4 IU/dl, P = 0·02). No polymorphism was detected in the LRP‐binding domains of the FVIII gene. This study reinforces the hypothesis of a genetic influence of FVIII levels beyond the influence of VWF:Ag and ABO blood groups. The D2080N polymorphism of the LRP gene weakly contributed to the variability of FVIII:C levels in this healthy population.

Genome-wide haplotype association study identifies the FRMD4A gene as a risk locus for Alzheimer's disease

Recently, several genome-wide association studies (GWASs) have led to the discovery of nine new loci of genetic susceptibility in Alzheimers disease (AD). However, the landscape of the AD genetic susceptibility is far away to be complete and in addition to single-SNP (single-nucleotide polymorphism) analyses as performed in conventional GWAS, complementary strategies need to be applied to overcome limitations inherent to this type of approaches. We performed a genome-wide haplotype association (GWHA) study in the EADI1 study (n=2025 AD cases and 5328 controls) by applying a sliding-windows approach. After exclusion of loci already known to be involved in AD (APOE, BIN1 and CR1), 91 regions with suggestive haplotype effects were identified. In a second step, we attempted to replicate the best suggestive haplotype associations in the GERAD1 consortium (2820 AD cases and 6356 controls) and observed that 9 of them showed nominal association. In a third step, we tested relevant haplotype associations in a combined analysis of five additional case–control studies (5093 AD cases and 4061 controls). We consistently replicated the association of a haplotype within FRMD4A on Chr.10p13 in all the data set analyzed (OR: 1.68; 95% CI: (1.43–1.96); P=1.1 × 10−10). We finally searched for association between SNPs within the FRMD4A locus and Aβ plasma concentrations in three independent non-demented populations (n=2579). We reported that polymorphisms were associated with plasma Aβ42/Aβ40 ratio (best signal, P=5.4 × 10−7). In conclusion, combining both GWHA study and a conservative three-stage replication approach, we characterised FRMD4A as a new genetic risk factor of AD.

TAFI gene haplotypes, TAFI plasma levels and future risk of coronary heart disease: the PRIME Study

Summary.  Objectives: To evaluate the association of thrombin‐activatable fibrinolysis inhibitor (TAFI) gene polymorphisms with the risk of coronary heart disease (CHD) and with TAFI levels measured by a newly developed enzyme‐linked immunosorbent assay (ELISA) (TAFI‐1B1), shown to be a reliable method for detecting quantitative variations in circulating TAFI. Patients/Methods: Six polymorphisms (C‐2599G, G‐438A, Ala147Thr, Thr325Ile, C + 1542G and T + 1583A) were genotyped and baseline plasma concentrations of TAFI were measured in a nested case–control design as part of the Prospective Epidemiological Study of Myocardial Infarction (PRIME) Study. Participants from France and Northern Ireland who had developed a CHD event during a 5‐year follow‐up (n = 321) were compared with 645 population‐ and age‐matched control subjects. Results: In France, the Thr147 allele was more frequent in cases than in controls (0.41 vs. 0.32; P = 0.02), whereas the reverse was observed in Northern Ireland (0.33 vs. 0.38; P = 0.19) (P = 0.01 for interaction). No other polymorphism was associated with CHD risk. Consistent with the results derived from the single‐locus analysis, haplotype analysis revealed that the haplotype carrying the Thr147 allele was associated with increased risk of CHD in France while the reverse tended to hold in the Northern Ireland population. Single‐locus and haplotype analyses revealed that two polymorphisms, C‐2599G and Ala147Thr (or T + 1583A that is in nearly complete association with it), had additive effects on TAFI levels and explained >18% of TAFI variability. This effect was homogeneous in France and Northern Ireland, and in cases and controls who exhibited similar TAFI levels. Conclusions: Thrombin‐activatable fibrinolysis inhibitor gene polymorphisms are strongly associated to plasma TAFI levels, but the relation to CHD risk is less clear.

miR-421 and miR-30c inhibit SERPINE 1 gene expression in human endothelial cells.

In this work, we assessed whether SERPINE1 expression could be under the influence of microRNAs (miRNAs) predicted to bind the SERPINE1 3′UTR region. We specifically focused on the 3′UTR region harboring a common polymorphism, rs1050955, that have been found associated to SERPINE1 monocyte expression, and investigated whether the presence of different alleles at rs1050955 could modify the miRNAs binding efficiency and affect PAI-1 protein levels. We demonstrated that, in human umbilical vein endothelial cells, both miR-421 and miR-30c directly interacted with PAI-1 mRNA to inhibit the expression of the associated protein. However, these inhibitory mechanisms were independent on the allele present at the rs1050955 locus. We further showed that miR-421 levels correlated with PAI-1 activity in the plasma sample of 40 patients with venous thrombosis. Our results strongly suggest that the regulation of PAI-1 molecule could be under the influence of several miRNAs whose measurement in the plasma of patients could be envisaged as a biomarker for inflammatory and thrombotic disorders.