The COL5A3 and MMP9 genes interact in eczema susceptibility.

BACKGROUND: Genetic studies of eczema have identified many genes, which explain only 14% of the heritability. Missing heritability may be partly due to ignored gene-gene (G-G) interactions. OBJECTIVE: Our aim was to detect new interacting genes involved in eczema. METHODS: The search for G-G interaction in eczema was conducted using a two-step approach, which included as a first step, a biological selection of genes, which are involved either in the skin or epidermis development or in the collagen metabolism, and as a second step, an interaction analysis of the selected genes. Analyses were carried out at both SNP and gene levels in three asthma-ascertained family samples: the discovery dataset of 388 EGEA (Epidemiological study on the Genetics and Environment of Asthma) families and the two replication datasets of 253 SLSJ (Saguenay-Lac-Saint-Jean) families and 207 MRCA (Medical Research Council) families. RESULTS: One pair of SNPs, rs2287807 in COL5A3 and rs17576 in MMP9, that were detected in EGEA at P ≤ 10-5 showed significant interaction by meta-analysis of EGEA, SLSJ and MRCA samples (P = 1.1 × 10-8 under the significant threshold of 10-7 ). Gene-based analysis confirmed strong interaction between COL5A3 and MMP9 (P = 4 × 10-8 under the significant threshold of 4 × 10-6 ) by meta-analysis of the three datasets. When stratifying the data on asthma, this interaction remained in both groups of asthmatic and non-asthmatic subjects. CONCLUSION: This study identified significant interaction between two new genes, COL5A3 and MMP9, which may be accounted for by a degradation of COL5A3 by MMP9 influencing eczema susceptibility. Further confirmation of this interaction as well as functional studies is needed to better understand the role of these genes in eczema.

Network-assisted analysis of GWAS data identifies a functionally-relevant gene module for childhood-onset asthma.

The number of genetic factors associated with asthma remains limited. To identify new genes with an undetected individual effect but collectively influencing asthma risk, we conducted a network-assisted analysis that integrates outcomes of genome-wide association studies (GWAS) and protein-protein interaction networks. We used two GWAS datasets, each consisting of the results of a meta-analysis of nine childhood-onset asthma GWASs (5,924 and 6,043 subjects, respectively). We developed a novel method to compute gene-level P-values (fastCGP), and proposed a parallel dense-module search and cross-selection strategy to identify an asthma-associated gene module. We identified a module of 91 genes with a significant joint effect on childhood-onset asthma (P < 10-5). This module contained a core subnetwork including genes at known asthma loci and five peripheral subnetworks including relevant candidates. Notably, the core genes were connected to APP (encoding amyloid beta precursor protein), a major player in Alzheimer's disease that is known to have immune and inflammatory components. Functional analysis of the module genes revealed four gene clusters involved in innate and adaptive immunity, chemotaxis, cell-adhesion and transcription regulation, which are biologically meaningful processes that may underlie asthma risk. Our findings provide important clues for future research into asthma aetiology.

[Genetic and environmental factors of asthma and allergy: Results of the EGEA study]. / Facteurs génétiques et environnementaux de l'asthme et de l'allergie: synthèse des résultats de l'étude EGEA.

INTRODUCTION AND METHODS: The EGEA study (epidemiological study on the genetics and environment of asthma, bronchial hyperresponsiveness and atopy), which combines a case-control and a family-based study of asthma case (n=2120 subjects) with three surveys over 20 years, aims to identify environmental and genetic factors associated with asthma and asthma-related phenotypes. We summarize the results of the phenotypic characterization and the investigation of environmental and genetic factors of asthma and asthma-related phenotypes obtained since 2007 in the EGEA study (42 articles). RESULTS: Both epidemiological and genetic results confirm the heterogeneity of asthma. These results strengthen the role of the age of disease onset, the allergic status and the level of disease activity in the identification of the different phenotypes of asthma. The deleterious role of active smoking, exposure to air pollution, occupational asthmogenic agents and cleaning products on the prevalence and/or activity of asthma has been confirmed. Accounting for gene-environment interactions allowed the identification of new genetic factors underlying asthma and asthma-related traits and better understanding of their mode of action. CONCLUSION: The EGEA study is contributing to the advances in respiratory research at the international level. The new phenotypic, environmental and biological data available in EGEA study will help characterizing the long-term evolution of asthma and the factors associated to this evolution.

HLA-DQ relative risks for coeliac disease in European populations: a study of the European Genetics Cluster on Coeliac Disease.

Coeliac disease is an enteropathy due to an intolerance to gluten. The association between HLA-DQ genes and CD is well established. The majority of patients carry the HLA-DQ heterodimer encoded by DQA1*05/DQB1*02, either in cis or in trans. The remaining patients carry either part of the DQ heterodimer or DQA1*03-DQB1*0302. The aim of the study was to estimate the risks associated with different DQ genotypes in European populations. HLA information was available for 470 trio families from four countries: France (117), Italy (128), and Norway and Sweden (225). Five DQA1-DQB1 haplotypes were considered and control haplotype frequencies were estimated from the set of parental haplotypes not transmitted to the affected child. The possible genotypes were grouped into five genotype groups, based on the hierarchy of risk reported in the literature. A north-south gradient in the genotype group frequencies is observed in probands: homogeneity is strongly rejected between all country pairs. For each country, the relative risks associated with each genotype group were computed taking into account the control haplotype frequencies. Homogeneity of relative risks between countries was tested pairwise by maximum likelihood ratio statistics. The hypothesis of homogeneity of relative risks is rejected (P is approximately 10(-6)) for all country pairs. In conclusion, the gradient in the genotype group frequencies in probands is not only due to differences in haplotype frequencies but also due to differences in genotype relative risks in the studied populations; the relative risks associated with each DQ genotype group are different between northern and southern European countries; neither are they ordered in the same way.

Maximum identity length contrast: a powerful method for susceptibility gene detection in isolated populations.

We report the results of our analysis of the Genetic Analysis Workshop 12 simulated data set. Focusing on the isolated populations, we compare the efficiency of a new method, the maximum identity length contrast statistic (MILC) with the maximum likelihood score (MLS) in a genome screen strategy. MILC is a method based on the contrast of haplotype identity between transmitted and nontransmitted haplotypes in trios. It uses information on linkage and association. We found that MILC allows the detection of a risk factor corresponding to candidate gene 1 where the MLS fails, though the same population replicates were used. Interestingly, the association between this risk factor and the disease could not have been detected with the TDT at a genome-wide level.

Strategies for detecting susceptibility genes in a complex disease.

One of the current issues in genetic epidemiology is detecting susceptibility genes on the genome. It is common now to undertake systematic screening of the genome using approaches based on a measure of the haplotype sharing in sib pairs. Here, we compare the efficiency of two statistics, the maximum likelihood score (MLS) and the nonparametric linkage score (NPLa) on the simulated data provided for GAW11. A question often raised is whether it is better to perform a single-step or a two-step strategy. For the simulated model, and whatever the strategy used, we show here that the answer is not unequivocal. In both cases, the power to detect susceptibility genes in a single replicate with MLS or NPL is extremely low. With two replicates, only one of the four simulated loci could be detected with reasonable power. When gametic disequilibrium is suspected, methods testing for both linkage and association might be more powerful.

Detection and modeling of disease susceptibility locus effects: how much can be learned from contrast of populations?

We report the results of our analyses of the GAW11 Problem 2 data set, using information from three different populations. In the first part of the paper, we used classical population genetic tests to compare affected individuals from the different populations, stratifying on the environmental factors. Thanks to existing linkage disequilibrium in one population, we found one of the disease susceptibility loci. In the second part of the paper, we used the marker association segregation chi 2 method to model the role of this disease susceptibility locus in the different populations and draw some inferences regarding the model used at that locus to generate the data.

An extension of the admixture test for the study of genetic heterogeneity in hereditary multiple exostoses.

Hereditary multiple exostoses (EXT) is an autosomal dominant disorder characterized by the presence of multiple cartilage-capped exostoses in the juxta-epiphyseal regions of the long bones. EXT is heterogeneous with at least three different locations currently having been identified on chromosomes 8, 11 and 19. We have tested a series of 29 EXT families for possible linkage to the three disease loci and estimated the probability of linkage of the disease to each locus in our series, by using an extension of the admixture test, which makes modelling of heterogeneous monogenic disease feasible. The maximum likelihood was obtained for proportions of 44%, 28% and 28% of families being linked to chromosome 8, 11 and 19, respectively. The a posteriori probability of linkage of the disease to EXT1, EXT2 and EXT3 was greater than 80% for 8/29, 5/29 and 3/29 families, respectively, and did not give evidence of a fourth locus for the disease. The present approach can be generalized to the investigation of genetic heterogeneity in other monogenic diseases, as it simultaneously estimates the location of each disease gene and the proportion of families linked to each locus.

Heterogeneity of marker allele frequencies hinders interpretation of linkage analysis: illustration on chromosome 18 markers.

In the first part of our study we tested linkage with chromosome 18 markers in a sample of bipolar I sib pairs. We did not obtain evidence for linkage but showed that we could not exclude the presence of a disease locus (having even a non-negligible effect). The limitation of the sib-pair sample size, and consequently of the conclusions, was a result of our care in assuring that the linkage analysis was free of possible errors in the marker allele frequencies. In the second part, we illustrated the possible impact of such heterogeneity in a single data set when applying the multipoint (APM) method. An Amish pedigree included in the study of Berrettini et al. was analyzed under two sets of marker allele frequencies. One set corresponds to estimates from the entire data set and the second to estimates from the Amish pedigree only. Very different values for the APM statistics were obtained. Although the real frequencies are unknown for this family belonging to an isolated population, this example illustrates that heterogeneity in the populations from which familial data are collected may artificially increase evidence for linkage and hinder interpretation of the analysis.

Caution in the interpretation of MLS.

We study the statistical properties of the maximum likelihood score (MLS) test. We show that the criteria for reaching conclusions about linkage are not the same for single point analysis as for multipoint, where the maximization is performed over an additional parameter, the position in the marker interval where the MLS is computed. In addition, this test is shown to be very sensitive to errors in allele frequencies and recombination fraction.

A gene for FG syndrome maps in the Xq12-q21.31 region.

FG syndrome is an X-linked recessive condition in which mental retardation is associated with congenital hypotonia, macrocephaly, characteristic face, and constipation. This syndrome was mapped by Zhu et al. [Cytogenet Cell Genet 1991;58:2091A] to Xq21.31-q22 by linkage analysis with a max lod score of 1.2 for the DXYS1X, DXS178, DXS101, and DXS94 loci and crossovers at DXS16 (Xp22.31) and DXS287 (Xq22.3). However, this mapping was only provisional and needed to be refined. In this paper, we report the results of a new linkage analysis performed on 10 families including that studied by Zhu et al. [1991]. Two-point analysis demonstrated linkage with DXS441 (Zmax = 3.39 at theta = 0.12) at Xq13. In addition, separate analysis of the lod scores obtained for the Xq13 markers suggested linkage exclusion for three families. Genetic heterogeneity was confirmed by analysis of the linkage results with the HOMOG program (max logL = 4.07, theta = 0, alpha = 0.65). Localization of one FG gene between DXS135 and DXS1066 was suggested by analysis of crossovers found in those three families which were assumed to be linked to Xq13 with a probability of 0.95 or more. This region could be reduced to the DXS135-DXS72 interval after combining our data with those from deletions previously described in males in the Xq13-q21 region.

Testing parental imprinting in insulin-dependent diabetes mellitus by the marker-association-segregation-chi 2 method.

Among patients with insulin-dependent diabetes mellitus (IDDM), an excess of DR3 and DR4 alleles is classically described when compared with the general population. In addition, an excess of maternal DR3 and paternal DR4 alleles among patients (DR3DR4) is observed. In order to explain these observations, two alternative hypotheses can be tested: maternal effect and parental imprinting. Maternal effect has been tested and not rejected on a sample of 416 caucasians affected with IDDM. Under this hypothesis, the children of a DR3 mother are expected to have an earlier exposure and, hence, an earlier age at onset. However, we did not observe such a difference in age at onset in this data set. Using the marker-association-segregation-chi 2 method, we have tested four hypotheses with different parental effects of two susceptibility alleles, alpha 0 and beta 0, at two different closely linked loci. Under the hypothesis that best fitted the data, the probability of being affected depended on the parental inheritance of the susceptibility alleles, suggesting parental imprinting (i.e., differential role of maternal and paternal allele), without evidence for a cis-trans effect. We conclude that parental imprinting on a specific allelic combination may explain the observations on the HLA genotypes of the patients and their relatives.

Genetic counselling in breast cancer: sensitivity to parameter values and to available information.

Most segregation analyses have concluded that breast cancer results from a mixture of sporadic and genetic cases. Genetic cases are probably due to a rare inherited mutation with autosomal dominant transmission. The lifetime risk for female mutation carriers is close to 1, ten fold greater than for noncarriers. Beyond these accepted results, studies differ in the estimated parameters specifying the correspondence between phenotypes and genotypes. We show here that these differences have an impact on the estimation of the probability that a woman is carrying a mutation given her disease status and also given the information on the disease status of her family members. We illustrate this problem by computing the probability of being a mutation carrier for 16 women (9 affected, 7 unaffected) belonging to one pedigree, using three sets of parameter values. For two of the women, the probability that they inherited the mutation is low, but it varies considerably according to the set of parameter values. For one woman, the probability varies from 20 to 60% if familial information is taken into account. Segregation of 17q markers in families may provide additional information depending on the posterior probability of linkage. Indeed in the pedigree studied here, the segregation of 17q markers provided additional information which moreover decreased the sensitivity to the parameters values. However, the decrease in sensitivity will only be observed if the posterior probability of linkage of the family to the studied markers is high.

Systematic search of susceptibility loci with methods using gametic disequilibrium.

Susceptibility genes are identified for a simulated complex trait by a systematic genome search for linkage between disease and a genetic marker in the presence of gametic disequilibrium. The transmission/disequilibrium tests TDTa or TDTg for multiallelic markers compare transmitted and nontransmitted alleles or the genotypes formed by the two transmitted alleles and the genotypes formed by the two nontransmitted alleles, respectively. With these two tests we were able to identify the two markers D1G31 and D5G23. Under the simulating model these are in fact two susceptibility genes involved in the disease.