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BACKGROUND: Numerous genes have been associated with the three most common allergic diseases (asthma, allergic rhinitis or eczema) but these genes explain only a part of the heritability. In the vast majority of genetic studies, complex phenotypes such as co-morbidity of two of these diseases, have not been considered. This may partly explain missing heritability.OBJECTIVE: To identify genetic variants specifically associated with the co-morbidity of asthma-plus-eczema.METHODS: We first conducted a meta-analysis of four GWAS (Genome-Wide Association Study) of the combined asthma-plus-eczema phenotype (total of 8807 European-ancestry subjects of whom 1208 subjects had both asthma and eczema). To assess whether the association with SNP(s) was specific to the co-morbidity, we also conducted a meta-analysis of homogeneity test of association according to disease status ("asthma-plus-eczema" vs. the presence of only one disease "asthma only or eczema only"). We then used a joint test by combining the two test statistics from the co-morbidity-SNP association and the phenotypic heterogeneity of SNP effect meta-analyses.RESULTS: Seven SNPs were detected for specific association to the asthma-plus-eczema co-morbidity, two with significant and five with suggestive evidence using the joint test after correction for multiple testing. The two significant SNPs are located in the OCA2 gene (Oculocutaneous Albinism II), a new locus never detected for significant evidence of association with any allergic disease. This gene is a promising candidate gene, because of its link to skin and lung diseases, and to epithelial barrier and immune mechanisms.CONCLUSION: Our study underlines the importance of studying sub-phenotypes as co-morbidities to detect new susceptibility genes.

Eosinophils play a key role in the asthma allergic response by releasing cytotoxic molecules such as eosinophil cationic protein (ECP) and eosinophil-derived neurotoxin (EDN) that generate epithelium damages.We sought to identify genetic variants influencing ECP and EDN levels in asthma-ascertained families.We performed univariate and bivariate genome-wide association analyses of ECP and EDN levels in 1018 subjects from the EGEA study with follow-up in 153 subjects from the Saguenay-Lac-Saint-Jean study and combined the results of these 2 studies through meta-analysis. We then conducted Bayesian statistical fine mapping together with quantitative trait locus and functional annotation analyses to identify the most likely functional genetic variants and candidate genes.We identified 5 genome-wide significant loci (P amp;lt; 5 × 10lt;supgt;-8lt;/supgt;) including 7 distinct signals associated with ECP and/or EDN levels. The genes targeted by our fine mapping and functional search include RNASE2 and RNASE3 (14q11), which encode EDN and ECP, respectively, and 4 other genes that regulate ECP and EDN levels. These 4 genes were JAK1 (1p31), a transcription factor that plays a key role in the immune response and acts as a potential therapeutic target for eosinophilic asthma; ARHGAP25 (2p13), which is involved in leukocyte recruitment to inflammatory sites; NDUFA4 (7p21), which encodes a component of the mitochondrial respiratory chain and is involved in cellular response to stress; and CTSL (9q22), which is involved in immune response, extracellular remodeling, and allergic inflammation.Analysis of specific phenotypes produced by eosinophils allows the identification of genes that play a major role in allergic response and inflammation, and offers potential therapeutic targets for asthma.

International audience; Background: Studying associations between genes and asthma endotypes and interactions with environment could help to identify new susceptibility genes. We used a previously identified asthma endotype characterized by adult-onset asthma, poor lung function, and high level of Fluorescent oxidation products, a marker of damages due to oxidative stress. This endotype was associated with high occupational exposure to irritants. We aimed to investigate the associations between genes related to oxidative stress and this endotype, and if the associations differed according to irritants exposure. Methods: We conducted association analyses between the asthma endotype and genetic variants (4715 SNPs) located in 422 genes involved in the “response to oxidative stress” in adults from the Epidemiological study on the Genetic and Environment of Asthma. Analyses using logistic regression were conducted first in all participants, and then separately among high vs. non-exposed participants to assess whether association differs according to irritants exposure. Results: An association was found between the SNP rs1419958 located in PID1 gene and the endotype (P = 2.2E-05), reaching significance level after correction for multiple testing. This association was even more significant in non-exposed participants (P = 1.06E-06) while there was no association in participants with high exposure to occupational irritants. Conclusion: This study showed a significant association between an asthma endotype and PID1, a promising candidate gene, the association being different according to the exposure to irritants. These results highlight the interest of studying asthma endotypes in association with genes from candidate pathways and their link with occupational irritants to decipher asthma etiology.

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.

Background: Eosinophils play a key role in the allergic response in asthma by the release of cytotoxic molecules such as eosinophil cationic protein (ECP) and eosinophil-derived neurotoxin (EDN) that generate epithelium damages. Objective: Our goal was to identify genetic variants influencing ECP and EDN levels. Methods: We conducted univariate and bivariate genome-wide association analyses of ECP and EDN levels measured in plasma in 1018 adults (451 with asthma) from the EGEA cohort using 1000-Genomes imputed SNPs. Results: The univariate analyses detected two genome-wide significant loci associated with ECP on chromosomes 14q11 (rs7141958 located between RNASE3 and RNASE2, P=3.9x10-13) and 18q21 near MC4R (rs9959588, P=1.7x10-9) and one significant locus at 14q11 associated with EDN near RNASE2 (rs67049014, P=1.6x10-12). The bivariate analysis detected the two previous loci plus a third one on 1p31 (rs57716204 in AK4, P=1.6x10-8). Fine-mapping of these regions, based on bivariate conditional analysis, showed that the 14q11 region contained three distinct signals located 76kb apart: the lead SNP rs67049014 and two other SNPs, rs76185655 and rs28525131. Interrogation of eQTL databases showed that the lead SNP was associated with the expression of RNASE2, RNASE3 and METTL17 (P Conclusion: The joint analysis of biomarkers involved in the same pathway can increase power to detect new loci and can help refining associated regions. Replication of these results is ongoing.

BACKGROUND: Asthma, a heterogeneous disease with variable age of onset, results from the interplay between genetic and environmental factors. Early-life tobacco smoke (ELTS) exposure is a major asthma risk factor. Only a few genetic loci have been reported to interact with ELTS exposure in asthma. OBJECTIVE: Our aim was to identify new loci interacting with ELTS exposure on time-to-asthma onset (TAO) in childhood. METHODS: We conducted genome-wide interaction analyses of ELTS exposure on time-to-asthma onset in childhood in five European-ancestry studies (totaling 8,273 subjects) using Cox proportional-hazard model. The results of all five genome-wide analyses were meta-analyzed. RESULTS: The 13q21 locus showed genome-wide significant interaction with ELTS exposure (P=4.3x10-8 for rs7334050 within KLHL1 with consistent results across the five studies). Suggestive interactions (P

BackgroundA positional cloning study of bronchial hyper-responsiveness (BHR) at the 17p11 locus in the French Epidemiological study on the Genetics and Environment of Asthma (EGEA) families showed significant interaction between early-life environmental tobacco smoke (ETS) exposure and genetic variants located in DNAH9. This gene encodes the heavy chain subunit of axonemal dynein, which is involved with ATP in the motile cilia function.Our goal was to identify genetic variants at other genes interacting with ETS in BHR by investigating all genes belonging to the ‘ATP-binding’ and ‘ATPase activity’ pathways which include DNAH9, are targets of cigarette smoke and play a crucial role in the airway inflammation.MethodsFamily-based interaction tests between ETS-exposed and unexposed BHR siblings were conducted in 388 EGEA families. Twenty single-nucleotide polymorphisms (SNP) showing interaction signals (p≤5.10−3) were tested in the 253 Saguenay-Lac-Saint-Jean (SLSJ) families.ResultsOne of these SNPs was significantly replicated for interaction with ETS in SLSJ families (p=0.003). Another SNP reached the significance threshold after correction for multiple testing in the combined analysis of the two samples (p=10−5). Results were confirmed using both a robust log-linear test and a gene-based interaction test.ConclusionThe SNPs showing interaction with ETS belong to the ATP8A1 and ABCA1 genes, which play a role in the maintenance of asymmetry and homeostasis of lung membrane lipids.

Purpose Interleukin-1 (IL-1) plays a key role in inflammation and immunity and its decoy receptor, IL-1R2, has been implicated in transcriptomic and genetic studies of asthma. Methods Two large asthma family collections, the French-Canadian Saguenay—Lac-St-Jean (SLSJ) study and the French Epidemiological Study on the Genetics and Environment of Asthma (EGEA), were used to investigate the association of SNPs in 10 genes that modulate IL-1R2 activities with asthma, allergic asthma, and atopy. Gene-gene interactions were also tested. Results One SNP in BACE2 was associated with allergic asthma in the SLSJ study and replicated in the EGEA study before statistical correction for multiple testing. Additionally, two SNPs in the MMP2 gene were replicated in both studies prior to statistical correction and reached significance in the combined analysis. Moreover, three gene-gene interactions also survived statistical correction in the combined analyses (BACE1-IL1RAP in asthma and allergic asthma and IL1R1-IL1RAP in atopy). Conclusions Our results highlight the relevance of genes involved in the IL-1R2 activity in the context of asthma and asthma-related traits.

Most genome-wide association studies used genetic-model-based tests assuming an additive mode of inheritance, leading to underpowered association tests in case of departure from additivity. The general regression model (GRM) association test proposed by Fisher and Wilson in 1980 makes no assumption on the genetic model. Interestingly, it also allows formal testing of the underlying genetic model. We conducted a simulation study of quantitative traits to compare the power of the GRM test to the classical linear regression tests, the maximum of the three statistics (MAX), and the allele-based (allelic) tests. Simulations were performed on two samples sizes, using a large panel of genetic models, varying genetic models, minor allele frequencies, and the percentage of explained variance. In case of departure from additivity, the GRM was more powerful than the additive regression tests (power gain reaching 80%) and had similar power when the true model is additive. GRM was also as or more powerful than the MAX or allelic tests. The true simulated model was mostly retained by the GRM test. Application of GRM to HbA1c illustrates its gain in power. To conclude, GRM increases power to detect association for quantitative traits, allows determining the genetic model and is easily applicable.

Summary A major problem in gene–gene interaction studies in large marker panels is how to correct for multiple testing while accounting for the dependence between marker pairs due to the presence of linkage disequilibrium. The “gold standard” approach is to perform permutations of case/control labels. However, this is often not feasible in practice, due to computational demands. Here, we propose a correction based on the effective number of independent tests of interaction between marker pairs. This number depends on the effective number of independent single-marker tests. We tested its validity using simulated samples, as well as that of another correction of marker pair tests. We showed that our approach was valid while the other correction strongly underestimated the effective number of independent tests. Our method provides estimates of the effective number of independent tests close to those reported in the literature for a Genome-Wide Interaction Study on a 550K chip. Our correction method is quick and simple, and can be applied whatever the marker panel and the underlying linkage disequilibrium pattern.

Figure S1. reported the proportion of replicates rejecting the additive model using a threshold P-value of 1.0E-5. Figure S1. Proportion of replicates rejecting the additive model (P = 0.01) among replicates showing significant association (P-value threshold =1.0E-5). (PDF 189 kb)

Background Atopy, an endotype underlying allergic diseases, has a substantial genetic component. Objective Our goal was to identify novel genes associated with atopy in asthma-ascertained families. Methods We implemented a 3-step analysis strategy in 3 data sets: the Epidemiological Study on the Genetics and Environment of Asthma (EGEA) data set (1660 subjects), the Saguenay-Lac-Saint-Jean study data set (1138 subjects), and the Medical Research Council (MRC) data set (446 subjects). This strategy included a single nucleotide polymorphism (SNP) genome-wide association study (GWAS), the selection of related gene pairs based on statistical filtering of GWAS results, and text-mining filtering using Gene Relationships Across Implicated Loci and SNP-SNP interaction analysis of selected gene pairs. Results We identified the 5q14 locus, harboring the adhesion G protein–coupled receptor V1 (ADGRV1) gene, which showed genome-wide significant association with atopy (rs4916831, meta-analysis P value = 6.8 × 10−9). Statistical filtering of GWAS results followed by text-mining filtering revealed relationships between ADGRV1 and 3 genes showing suggestive association with atopy (P ≤ 10−4). SNP-SNP interaction analysis between ADGRV1 and these 3 genes showed significant interaction between ADGRV1 rs17554723 and 2 correlated SNPs (rs2134256 and rs1354187) within the dynein axonemal heavy chain 5 (DNAH5) gene (Pmeta-int = 3.6 × 10−5 and 6.1 × 10−5, which met the multiple-testing corrected threshold of 7.3 × 10−5). Further conditional analysis indicated that rs2134256 alone accounted for the interaction signal with rs17554723. Conclusion Because both DNAH5 and ADGRV1 contribute to ciliary function, this study suggests that ciliary dysfunction might represent a novel mechanism underlying atopy. Combining GWAS and epistasis analysis driven by statistical and knowledge-based evidence represents a promising approach for identifying new genes involved in complex traits.

International audience; BACKGROUND:Asthma and allergic rhinitis (AR) are common allergic comorbidities with a strong genetic component in which epigenetic mechanisms might be involved.OBJECTIVE:We aimed to identify novel risk loci for asthma and AR while accounting for parent-of-origin effect.METHODS:We performed a series of genetic analyses, taking into account the parent-of-origin effect in families ascertained through asthma: (1) genome-wide linkage scan of asthma and AR in 615 European families, (2) association analysis with 1233 single nucleotide polymorphisms (SNPs) covering the significant linkage region in 162 French Epidemiological Study on the Genetics and Environment of Asthma families with replication in 154 Canadian Saguenay-Lac-Saint-Jean asthma study families, and (3) association analysis of disease and significant SNPs with DNA methylation (DNAm) at CpG sites in 40 Saguenay-Lac-Saint-Jean asthma study families.RESULTS:We detected a significant paternal linkage of the 4q35 region to asthma and allergic rhinitis comorbidity (AAR; P = 7.2 × 10(-5)). Association analysis in this region showed strong evidence for the effect of the paternally inherited G allele of rs10009104 on AAR (P = 1.1 × 10(-5), reaching the multiple-testing corrected threshold). This paternally inherited allele was also significantly associated with DNAm levels at the cg02303933 site (P = 1.7 × 10(-4)). Differential DNAm at this site was found to mediate the identified SNP-AAR association.CONCLUSION:By integrating genetic and epigenetic data, we identified that a differentially methylated CpG site within the melatonin receptor 1A (MTNR1A) gene mediates the effect of a paternally transmitted genetic variant on the comorbidity of asthma and AR. This study provides a novel insight into the role of epigenetic mechanisms in patients with allergic respiratory diseases.

Background: The number of genetic factors identified for asthma remains limited. The study of gene-by-environment interactions may facilitate the discovery of new genes. Early environmental tobacco smoke (ETS) exposure (in utero or during infancy) is a known risk factor for childhood-onset and late-onset asthma. Objective: Our goal was to identify genetic variants interacting with early ETS exposure that influence time-to-asthma onset (TAO). Methods: We conducted a large-scale meta-analysis of five genome-wide interaction studies (GEWIS) of TAO (totaling 3,643 exposed (ETS+) and 5,275 non-exposed (ETS-) individuals of European ancestry) using survival analysis methodologies. Two tests were performed: 1) a joint test of SNP effect and GxETS interaction and 2) a test of GxETS interaction alone. Results: While the joint test confirmed two asthma regions (9p24 & 17q12-q21) interacting with ETS on TAO at the genome-wide significant level (P Conclusion: This study suggests an important role of early ETS exposure and 9p24 genetic variants in asthma age-of-onset.

A previous genome-wide linkage scan of bronchial hyperresponsiveness (BHR) in the French Epidemiological study on the Genetics and Environment of Asthma (EGEA) families, performed in the presence of a gene×early-life environmental tobacco smoke (ETS) exposure interaction, showed the strongest interaction in the 17p11 region where linkage was detected only among unexposed siblings. Our goal was to conduct fine-scale mapping of 17p11 to identify single nucleotide polymorphisms (SNPs) interacting with ETS that influence BHR.Analyses were performed in 388 French EGEA asthmatic families, using a two-step strategy: 1) selection of SNPs displaying family-based association test (FBAT) association signals (p≤0.01) with BHR in unexposed siblings, and 2) a FBAT homogeneity test between exposed and unexposed siblings plus a robust log-linear interaction test.A single SNP reached the threshold (p≤3×10−3) for significant interaction with ETS using both interaction tests, after accounting for multiple testing. Results were replicated in 253 French-Canadian families, but not in 341 UK families, probably due in part to differences in phenotypic features between datasets.The SNP showing significant interaction with ETS belongs to DNAH9 (dynein, axonemal, heavy chain 9), a promising candidate gene involved in respiratory cilia mobility and associated with primary ciliary dyskinesia, a disease associated with abnormalities of pulmonary function.

Background Asthma is a heterogeneous disease in which age of onset plays an important role. Objective We sought to identify the genetic variants associated with time to asthma onset (TAO). Methods We conducted a large-scale meta-analysis of 9 genome-wide association studies of TAO (total of 5462 asthmatic patients with a broad range of age of asthma onset and 8424 control subjects of European ancestry) performed by using survival analysis techniques. Results We detected 5 regions associated with TAO at the genome-wide significant level (P < 5 × 10−8). We evidenced a new locus in the 16q12 region (near cylindromatosis turban tumor syndrome gene [CYLD]) and confirmed 4 asthma risk regions: 2q12 (IL-1 receptor–like 1 [IL1RL1]), 6p21 (HLA-DQA1), 9p24 (IL33), and 17q12-q21 (zona pellucida binding protein 2 [ZPBP2]–gasdermin A [GSDMA]). Conditional analyses identified 2 distinct signals at 9p24 (both upstream of IL33) and 17q12-q21 (near ZPBP2 and within GSDMA). Together, these 7 distinct loci explained 6.0% of the variance in TAO. In addition, we showed that genetic variants at 9p24 and 17q12-q21 were strongly associated with an earlier onset of childhood asthma (P ≤ .002), whereas the 16q12 single nucleotide polymorphism was associated with later asthma onset (P = .04). A high burden of disease risk alleles at these loci was associated with earlier age of asthma onset (4 vs 9-12 years, P = 10−4). Conclusion The new susceptibility region for TAO at 16q12 harbors variants that correlate with the expression of CYLD and nucleotide-binding oligomerization domain 2 (NOD2), 2 strong candidates for asthma. This study demonstrates that incorporating the variability of age of asthma onset in asthma modeling is a helpful approach in the search for disease susceptibility genes.

BACKGROUND: The biological mechanisms by which cleaning products and disinfectants-an emerging risk factor-affect respiratory health remain incompletely evaluated. Studying genes by environment interactions (G × E) may help identify new genes related to adult-onset asthma. OBJECTIVES: We identified interactions between genetic polymorphisms of a large set of genes involved in the response to oxidative stress and occupational exposures to low molecular weight (LMW) agents or irritants on adult-onset asthma. METHODS: Our data came from three large European cohorts: Epidemiological Family-based Study of the Genetics and Environment of Asthma (EGEA), Swiss Cohort Study on Air Pollution and Lung and Heart Disease in Adults (SAPALDIA), and European Community Respiratory Health Survey in Adults (ECRHS). A candidate pathway-based strategy identified 163 genes involved in the response to oxidative stress and potentially related to exposures to LMW agents/irritants. Occupational exposures were evaluated using an asthma job-exposure matrix and job-specific questionnaires for cleaners and healthcare workers. Logistic regression models were used to detect G × E interactions, adjusted for age, sex, and population ancestry, in 2,599 adults (mean age, 47 years; 60% women, 36% exposed, 18% asthmatics). p-Values were corrected for multiple comparisons. RESULTS: Ever exposure to LMW agents/irritants was associated with current adult-onset asthma [OR = 1.28 (95% CI: 1.04, 1.58)]. Eight single nucleotide polymorphism (SNP) by exposure interactions at five loci were found at p < 0.005: PLA2G4A (rs932476, chromosome 1), near PLA2R1 (rs2667026, chromosome 2), near RELA (rs931127, rs7949980, chromosome 11), PRKD1 (rs1958980, rs11847351, rs1958987, chromosome 14), and PRKCA (rs6504453, chromosome 17). Results were consistent across the three studies and after accounting for smoking. CONCLUSIONS: Using a pathway-based selection process, we identified novel genes potentially involved in adult asthma by interaction with occupational exposure. These genes play a role in the NF-κB pathway, which is involved in inflammation. Citation: Rava M, Ahmed I, Kogevinas M, Le Moual N, Bouzigon E, Curjuric I, Dizier MH, Dumas O, Gonzalez JR, Imboden M, Mehta AJ, Tubert-Bitter P, Zock JP, Jarvis D, Probst-Hensch NM, Demenais F, Nadif R. 2017. Genes interacting with occupational exposures to low molecular weight agents and irritants on adult-onset asthma in three European studies. Environ Health Perspect 125:207-214; http://dx.doi.org/10.1289/EHP376. We thank all study members and staff involved in data collections in each cohort: EGEA: We thank the Epidemiological Study on Genetics and Environment of Asthma (EGEA) cooperative group members as follows. Coordination: V. Siroux [epidemiology, principal investigator (PI) since 2013]; F. Demenais (genetics); I. Pin (clinical aspects); R. Nadif (biology); F. Kauffmann (PI 1992–2012). Respiratory epidemiology: Inserm U 700, Paris: M. Korobaeff (EGEA1), F. Neukirch (EGEA1); Inserm U 707, Paris: I. Annesi-Maesano (EGEA1–2); Inserm U1168 (ex-CESP/U 1018), Villejuif: F. Kauffmann, N. Le Moual, R. Nadif, M.P. Oryszczyn (EGEA1–2), R. Varraso; Inserm U 823, Grenoble: V. Siroux. Genetics: Inserm U 393, Paris: J. Feingold; Inserm U 946, Paris: E. Bouzigon, F. Demenais, M.H. Dizier; CNG, Evry: I. Gut (now CNAG, Barcelona, Spain), M. Lathrop (now McGill University, Montreal, Canada). Clinical centers: Grenoble: I. Pin, C. Pison; Lyon: D. Ecochard (EGEA1), F. Gormand, Y. Pacheco; Marseille: D. Charpin (EGEA1), D. Vervloet (EGEA1–2); Montpellier: J. Bousquet; Paris Cochin: A. Lockhart (EGEA1), R. Matran (now in Lille); Paris Necker: E. Paty (EGEA1–2), P. Scheinmann (EGEA1–2); Paris Trousseau: A. Grimfeld (EGEA1–2), J. Just. Data and quality management: Inserm ex-U155 (EGEA1): J. Hochez; Inserm U1168 (ex-CESP/U 1018), Villejuif: N. Le Moual; Inserm ex-U780: C. Ravault (EGEA1–2); Inserm ex-U794: N. Chateigner (EGEA1–2); Grenoble: J. Quentin-Ferran (EGEA1–2). SAPALDIA: We thank the team of the Swiss study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA). Study directorate: N.M. Probst-Hensch (PI; e/g); T. Rochat (p), C. Schindler (s), N. Künzli (e/exp), J.M. Gaspoz (c). Scientific team: J.C. Barthélémy (c), W. Berger (g), R. Bettschart (p), A. Bircher (a), C. Brombach (n), P.O. Bridevaux (p), L. Burdet (p), D. Felber Dietrich (e), M. Frey (p), U. Frey (pd), M.W. Gerbase (p), D. Gold (e), E. de Groot (c), W. Karrer (p), F. Kronenberg (g), B. Martin (pa), A. Mehta (e), D. Miedinger (o), M. Pons (p), F. Roche (c), T. Rothe (p), P. Schmid- Grendelmeyer (a), D. Stolz (p), A. Schmidt-Trucksäss (pa), J. Schwartz (e), A. Turk (p), A. von Eckardstein (cc), E. Zemp Stutz (e). Scientific team at coordinating centers: M. Adam (e), I. Aguilera (exp), S. Brunner (s), D. Carballo (c), S. Caviezel (pa), I. Curjuric (e), A. Di Pascale (s), J. Dratva (e), R. Ducret (s), E. Dupuis Lozeron (s), M. Eeftens (exp), I. Eze (e), E. Fischer (g), M. Foraster (e), M. Germond (s), L. Grize (s), S. Hansen (e), A. Hensel (s), M. Imboden (g), A. Ineichen (exp), A. Jeong (g), D. Keidel (s), A. Kumar (g), N. Maire (s), A. Mehta (e), R. Meier (exp), E. Schaffner (s), T. Schikowski (e), M. Tsai (exp). Abbreviations: (a) allergology, (c) cardiology, (cc) clinical chemistry, (e) epide - miology, (exp) exposure, (g) genetic and molecular biology, (m) meteorology, (n) nutrition, (o) occupational health, (p) pneumology, (pa) physical activity, (pd) pediatrics, (s) statistics. The study could not have been done without the help of the study partici - pants, technical and administrative support and the medical teams and field workers at the local study sites. Local fieldworkers: Aarau: S. Brun, G. Giger, M. Sperisen, M. Stahel; Basel: C. Bürli, C. Dahler, N. Oertli, I. Harreh, F. Karrer, G. Novicic, N. Wyttenbacher; Davos: A. Saner, P. Senn, R. Winzeler; Geneva: F. Bonfils, B. Blicharz, C. Landolt, J. Rochat; Lugano: S. Boccia, E. Gehrig, M.T. Mandia, G. Solari, B. Viscardi; Montana: A.P. Bieri, C. Darioly, M. Maire; Payerne: F. Ding, P. Danieli, A. Vonnez; Wald: D. Bodmer, E. Hochs, R. Kunz, C. Meier, J. Rakic, U. Schafroth, A. Walder. Administrative staff: N. Bauer Ott, C. Gabriel, R. Gutknecht. ECRHS: The ECRHS data incorporated in this analysis would not have been available without the collaboration of the following individuals and their research teams. ECRHS Co-ordinating Centre. P. Burney, D. Jarvis, S. Chinn, J. Knox (ECRHS II), C. Luczynska†, J. Potts. Steering Committee for ECRHS II. P. Burney, D. Jarvis, S. Chinn, U. Ackermann-Liebrich, J.M. Anto, I. Cerveri, R. deMarco†, T. Gislason, J. Heinrich, C. Janson, N. Kunzli, B. Leynaert, F. Neukirch, J. Schouten, J. Sunyer; C. Svanes, P. Vermeire†, M. Wjst. Principal Investigators and Senior Scientific Teams for ECRHS II centers within this analysis: Estonia: Tartu (R. Jogi, A. Soon); France: Paris (F. Neukirch, B. Leynaert, R. Liard, M. Zureik), Grenoble (I. Pin, J. Ferran-Quentin); Germany: Erfurt (J. Heinrich, M. Wjst, C. Frye, I. Meyer), Hamburg (K. Richter, D. Nowak); Norway: Bergen (A. Gulsvik, E. Omenaas, C. Svanes, B. Laerum); Spain: Barcelona (J.M. Anto, J. Sunyer, M. Kogevinas, J.P. Zock, X. Basagana, A. Jaen, F. Burgos), Huelva (J. Maldonado, A. Pereira, J.L. Sanchez), Albacete (J. Martinez-Moratalla Rovira, E. Almar), Galdakao (N. Muniozguren, I. Urritia), Oviedo (F. Payo); Sweden: Uppsala (C. Janson, G. Boman, D. Norback, M. Gunnbjornsdottir), Umeå (E. Norrman, M. Soderberg, K. Franklin, B. Lundback, B. Forsberg, L. Nystrom); Switzerland: Basel (N. Kunzli, B. Dibbert, M. Hazenkamp, M. Brutsche, U. Ackermann-Liebrich); United Kingdom: Norwich (D. Jarvis, B. Harrison), Ipswich (D. Jarvis, R. Hall, D. Seaton). Sí

This study is the first that formally tests for genetic heterogeneity of bipolar disorder (BD) according to age at onset (AAO) sub-groups by combining positional cloning and candidate gene approaches. Our previous genome-wide linkage-scan identified five genomic regions linked to early-onset form of BD. The present study uses association analysis to test genetic heterogeneity of candidate genes located in these five regions in a sample of 443 unrelated bipolar patients and 1,731 controls. The study involved the following steps: (1) test of heterogeneity by comparing early-onset BD patients versus later-onset BD patients; and (2) for significant results in step 1, comparison of early-onset BD patients and later-onset BD patients separately to controls. Two types of analyses were used: the single SNP test and the gene-based association test. We provide evidence for genetic heterogeneity within the ADRB2 (beta-2adrenoreceptor) gene region that is specifically associated with the early onset form of BD with an OR of 1.8. Unfortunately, the genotyping coverage of ADRB2 in the Wellcome Trust Case Control Consortium sample meant undermined our efforts to undertake a replication. However, as the ADRB2 gene product directly interacts with the CACNA1C gene product, and is known to be implicated in BD susceptibility, we conclude that further exploration of the relationships between ADRB2 and BD needs to be undertaken.

Plaque psoriasis is a chronic inflammatory disorder of the skin. It is inherited as a multifactorial trait, with a strong genetic component. Linkage studies have identified a large number of disease loci, but very few could be replicated in independent family sets. In this study, we present the results of a genome-wide scan carried out in 14 French extended families. Candidate regions were then tested in a second set of 32 families. Analysis of the pooled samples confirmed linkage to chromosomes 6p21 ( Z MLB score=3.5, P =0.0002) and 20p13 ( Z MLB score=2.9, P =0.002), although there was little contribution of the second family set to the 20p13 linkage signal. Moreover, we identified four additional loci potentially linked to psoriasis. The major histocompatibility complex region on 6p21 is a major susceptibility locus, referred to as PSORS1 , which has been found in most of the studies published to date. The 20p13 locus segregates independently of PSORS1 in psoriasis families. It has previously been thought to be involved in the predisposition to psoriasis and other inflammatory disorders such as atopic dermatitis (AD) and asthma. Although psoriasis and AD rarely occur together, this reinforces the hypothesis that psoriasis is influenced by genes with general effects on inflammation and immunity.

Resume Introduction et methode L’etude francaise EGEA (etude epidemiologique des facteurs genetiques et environnementaux de l’asthme, l’hyperactivite bronchique et l’atopie) combine une etude cas-temoins et une etude familiale de cas (n = 2120) avec trois enquetes sur 20 ans. Cet article de synthese presente les travaux realises depuis 2007 (42 articles) sur la caracterisation phenotypique et l’etude de facteurs environnementaux et genetiques de l’asthme et des phenotypes associes. Resultats Les resultats epidemiologiques et genetiques confirment le caractere heterogene de l’asthme. L’âge de debut, le statut allergique et le niveau d’activite de la maladie jouent un role preponderant dans l’identification des differents phenotypes et des facteurs genetiques sous-jacents. Le role nefaste du tabagisme, des expositions a la pollution atmospherique, aux asthmogenes professionnels et aux produits de nettoyage sur la prevalence et/ou l’activite de l’asthme est etaye. La prise en compte d’interactions gene–environnement a permis d’identifier de nouveaux facteurs genetiques de susceptibilite et de preciser leur mode d’action. Conclusion L’etude EGEA participe aux avancees de la recherche en pneumologie au niveau international. Les nouvelles donnees phenotypiques, environnementales et biologiques permettront de caracteriser l’evolution a long terme de l’asthme et les facteurs associes a cette evolution.

Background Emotional reactivity has been proposed as a relevant intermediate phenotype of bipolar disorder (BD). Our goal was to identify genetic factors underlying emotional reactivity in a sample of bipolar patients. Methods Affect intensity (a proxy measure of emotional reactivity) was measured in a sample of 281 euthymic patients meeting DSM-IV criteria for BD. We use a validated dimensional tool, the 40-item self-report Affect Intensity Measure scale developed by Larsen and Diener. Patients with BD were genotyped for 475. 740 SNPs (using Illumina HumanHap550 Beadchips or HumanHap610 Quad chip). Association was investigated with a general mixed regression model of the continuous trait against genotypes, including gender as covariate. Results Four regions (1p31.3, 3q13.11, 11p15.1 and 11q14.4) with a p -value lower or equal to 5×10 −6 were identified. In these regions, the joint effect of the four variants accounted for 24.5% of the variance of AIM score. Epistasis analysis did not detect interaction between these variants. In the 11p15.1 region, the rs10766743 located in the intron of the NELL1 gene remained significant after correction for multiple testing ( p =2×10 −7 ). Conclusions These findings illustrate that focusing on quantitative intermediate phenotypes can facilitate the identification of genetic susceptibility variants in BD.

Asthma is a complex disease, associated with biological and physiological phenotypes including immunoglobulin E (IgE) levels, sum of positive skin prick tests to allergens (SPTQ), eosinophil counts (EOS) and percent predicted forced expiratory volume in 1 s (%FEV1). We investigated the patterns of familial correlations and the inter-relationships of these four quantitative phenotypes, using the general class D regressive model, in 320 French EGEA nuclear families ascertained through 204 offspring (set A) and 116 parents (set B). Familial correlations of IgE and SPTQ were consistent with a model including no spouse correlation and equal parent-offspring and sib-sib correlations (rhoPO = rhoSS = 0.25 for IgE and 0.15 for SPTQ), this model being compatible with an additive polygenic model in the whole sample and the two family subsets A and B. Different patterns of familial correlations of EOS and %FEV1 were observed in these two sets. In set A, the best fitting model included no spouse correlation and equality of parent-offspring and sib-sib correlations (rhoPO = rhoSS = 0.14 for EOS and 0.23 for %FEV1). In set B, EOS had only a significant rhoSS of 0.28, while %FEV1 had significant rhoMO of 0.28 and rhoSS of 0.16. Analysis of shared familial determinants between these phenotypes indicated an overlap of at most 30% in rhoFO for IgE and SPTQ and in both rhoFO and rhoMO for IgE and EOS, while determinants of %FEV1 and atopy-related phenotypes appear distinct. These results may have implications for further linkage and association studies with genetic markers.

The purpose of our study was to detect genetic heterogeneity (i.e., different genotype relative risks of genetic factor) between atopic and non-atopic asthma and between atopy associated or independent of asthma. Genetic heterogeneity was tested in the Caucasian Collaborative Study on the Genetics of Asthma families using the TTS (triangle test statistic) and the predivided sample test. The TTS was proposed to detect both linkage and intra-sib-pair genetic heterogeneity; such heterogeneity may exist if the sibs differ for a factor on which the penetrances of the putative linked gene depend. The TTS has been applied to asthmatic pairs discordant for atopy and atopic sib pairs discordant for asthma. To confirm genetic heterogeneity detected by the TTS, the predivided sample test was also applied among concordant and discordant sib pairs. The analyses detected a genetic factor on chromosome 8p that could be involved in atopy with different genotype relative risks according to whether asthma is present. This would suggest a pleiotropic effect of this genetic factor in asthma and atopy. Two other regions located on chromosomes 8q and 20p were detected for genetic heterogeneity with asthma and atopy, respectively, but the factor of heterogeneity could be independent from the presence of atopy or asthma, respectively. It could be a characteristic of the disease such as the severity or the presence of an environmental factor.

The main objective of this study was to search for a major gene controlling total serum immunoglobulin E (IgE) levels, an intermediate phenotype for asthma and allergy. We studied 335 French nuclear families of the EGEA study (Epidemiological study of the Genetics and Environment of Asthma), ascertained through asthmatic probands (123 are parents in the family, 212 children). Segregation analyses were performed by regressive models, which can take into account a major gene effect, various sources of familial covariation (genetic and/or environmental) as well as measured risk factors (i.e., age, sex, smoking habits). Different strategies were considered to account for the mode of ascertainment of the families through a correlated trait (asthma): the ascertainment mode was either ignored (strategy A) or taken into account by adjusting IgE levels for the position in the family, i.e., probands, blood relatives, spouses (strategy B) or excluding the asthmatic children-probands and computing the likelihood of each family conditionally on parents' IgE levels (strategy C). Whereas a major gene effect could not be detected with strategy A, strategies B and C showed evidence for the transmission of a dominant major gene for high IgE levels, which was more significant with strategy B. This gene does not interact with any of the covariates and is responsible for ≈15% of IgE variation (the allele frequency is 0.65). Genet. Epidemiol. 18:128–142, 2000. © 2000 Wiley-Liss, Inc.

Previous segregation analysis of a sample of 234 randomly selected Australian families showed evidence for a recessive major gene controlling serum immunoglobulin E (IgE) levels independently of the specific response to allergens (SRA). Since linkage has been recently reported between serum IgE levels and the 5q candidate region spanning the interleukin-4 (IL-4) gene, we investigated whether the recessive major gene detected by segregation analysis was linked to the IL-4 region and whether polymorphisms within the IL-4 gene were associated with IgE levels. Both sib-pair method and combined segregation and linkage analysis using the regressive models were applied to our data. Whereas there was no evidence of linkage of total IgE levels to the IL-4 region, an indication of linkage (P values ranging between 0.01 and 0.03) was found between IgE levels adjusted for SRA and two IL-4 polymorphisms: one dinucleotide repeat in intron 2 of the IL-4 gene and a single nucleotide (-590 C to T) polymorphism in the IL-4 promoter. However, the putative IL-4 linked gene did not appear to be in linkage disequilibrium with either of these two polymorphisms. A contribution of the IL-4 promoter polymorphism, presumed to be a potential functional variant influencing IgE variation, was also excluded.

For any genetic model, Holmans showed that the proportions of affected sibs sharing 2, 1, or 0 identical-by-descent parental marker alleles are constrained to belong to a specific triangle. The triangle constraints do not hold when the sib phenotypes are determined by different models. We test the rejection of triangle constraints on affected sib pairs discordant for severity, to determine whether different models control the severe and mild forms of the disease in the simulated data. With this method we show that a locus on chromosome 5 plays a different role in the two forms of the disease.

Segregation analysis of the specific response to allergens (SRA) was performed in a sample of 234 randomly selected Australian families using the regressive models. Various SRA phenotypes were considered using broad and narrow definitions of these phenotypes, according to the type of test used, skin test or RAST test, and the specificity of the response to allergen. Strong evidence for familial dependencies among blood relatives was shown for most SRA phenotypes, especially when using a broad definition. There was no evidence for a Mendelian factor accounting for the familial transmission of these broadest phenotypes, which may involve multiple factors preventing the clear detection of a major effect with Mendelian transmission. However, segregation of a Mendelian recessive major gene was detected for one SRA sub-phenotype, the IgE response to a single allergen, Timothy grass pollen, measured by the RAST test. Identification of a specific SRA phenotype controlled by a major gene may have important implications for further linkage studies.

Background A previous genome-wide linkage scan in 295 families of the French Epidemiological Study on the Genetics and Environment of Asthma (EGEA) showed strong evidence of linkage of the 1p31 region to the combined asthma plus allergic rhinitis (AR) phenotype. Objective Our purpose was to conduct fine-scale mapping of the 1p31 linkage region to identify the genetic variants associated with asthma plus AR. Methods Association analyses with the asthma plus rhinitis phenotype were first conducted in the EGEA family sample using the family-based association method (FBAT) and logistic regression. The test of homogeneity of association between asthma plus AR versus asthma alone or AR alone was also applied. Replication of EGEA findings was sought in French-Canadian and United Kingdom family samples. Results We found a significant association between asthma plus rhinitis and a 1p31 genetic variant ( P = 2 × 10 −5 for rs12122228, which reached the multiple testing–corrected threshold) in EGEA using FBAT. There was evidence of heterogeneity of association between asthma plus AR versus asthma alone or AR alone ( P = .03). A Meta-analysis of FBAT results from EGEA and French-Canadian families improved evidence for both association and heterogeneity ( P = 5 × 10 −6 and P = .008, respectively), whereas a meta-analysis of EGEA, French-Canadian, and United Kingdom samples based on logistic regression slightly increased the evidence for heterogeneity. Conclusion The single nucleotide polymorphism specifically associated to asthma plus rhinitis is located in the flanking 5′ untranslated region of the nuclear factor I/A (NFIA) gene, a strong candidate gene for asthma and AR.

Two susceptibility genes, in linkage disequilibrium with alleles of the markers D1G31 and D5G23, have been identified for the disease in the simulated data set of Problem 1. Here we apply the MASC (marker association segregation chi-square) method to model the joint effect of these two genes, by testing two-locus models. The model we obtain, that is the most parsimonious and that best fits the data, corresponds to a direct involvement of the alleles D1G31-8 and D5G23-7, with a nonmultiplicative effect of the two alleles. This was indeed assumed in the true model used for simulating the data. ©1995 Wiley-Liss, Inc.

Not accounting for interaction in association analyses may reduce the power to detect the variants involved. We investigate the powers of different designs to detect under two-locus models the effect of disease-causing variants among several hundreds of markers using family-based association tests by simulation. This setting reflects realistic situations of exploration of linkage regions or of biological pathways. We define four strategies: (S1) single-marker analysis of all Single Nucleotide Polymorphisms (SNPs), (S2) two-marker analysis of all possible SNPs pairs, (S3) lax preliminary selection of SNPs followed by a two-marker analysis of all selected SNP pairs, (S4) stringent preliminary selection of SNPs, each being later paired with all the SNPs for two-marker analysis. Strategy S2 is never the best design, except when there is an inversion of the gene effect (flip-flop model). Testing individual SNPs (S1) is the most efficient when the two genes act multiplicatively. Designs S3 and S4 are the most powerful for nonmultiplicative models. Their respective powers depend on the level of symmetry of the model. Because the true genetic model is unknown, we cannot conclude that one design outperforms another. The optimal approach would be the two-step strategy (S3 or S4) as it is often the most powerful, or the second best. Genet.

Not accounting for interaction in association analyses may reduce the power to detect the variants involved. We investigate the powers of different designs to detect under two-locus models the effect of disease-causing variants among several hundreds of markers using family-based association tests by simulation. This setting reflects realistic situations of exploration of linkage regions or of biological pathways. We define four strategies: (S1) single-marker analysis of all Single Nucleotide Polymorphisms (SNPs), (S2) two-marker analysis of all possible SNPs pairs, (S3) lax preliminary selection of SNPs followed by a two-marker analysis of all selected SNP pairs, (S4) stringent preliminary selection of SNPs, each being later paired with all the SNPs for two-marker analysis. Strategy S2 is never the best design, except when there is an inversion of the gene effect (flip-flop model). Testing individual SNPs (S1) is the most efficient when the two genes act multiplicatively. Designs S3 and S4 are the most powerful for nonmultiplicative models. Their respective powers depend on the level of symmetry of the model. Because the true genetic model is unknown, we cannot conclude that one design outperforms another. The optimal approach would be the two-step strategy (S3 or S4) as it is often the most powerful, or the second best.

Background A previous genome-wide linkage scan in 295 families of the French Epidemiological Study on the Genetics and Environment of Asthma (EGEA) reported strong evidence of linkage of 11p14 to eczema. Objective Our purpose was to conduct fine-scale mapping of the 11p14 region to identify the genetic variants associated with eczema. Methods Association analyses were first conducted in the family sample from the French EGEA by using 2 methods: the family-based association method and logistic regression. Replication of the EGEA findings was sought in French Canadian and United Kingdom family samples, which, similarly to EGEA samples, were ascertained through asthma. We also tested for association in 2 German samples ascertained through eczema. Results We found significant association of eczema with 11p14 genetic variants in the vicinity of the linkage peak in EGEA ( P = 10 −4 for rs1050153 by using the family-based association method, which reached the multiple testing–corrected threshold of 10 −4 ; P = .003 with logistic regression). Pooled analysis of the 3 asthma-ascertained samples showed strong improvement in the evidence for association ( P = 6 × 10 −6 for rs293974, P = 3 × 10 −5 for rs1050153, and P = 8 × 10 −5 for rs15783). No association was observed in the eczema-ascertained samples. Conclusion The significant single nucleotide polymorphisms are located within the overlapping anoctamin 3 (ANO3) and mucin 15 (MUC15) genes. Several lines of evidence suggest that MUC15 is a strong candidate for eczema. Further investigation is needed to confirm our findings and to better understand the role of the ANO3/MUC15 locus in eczema and its relationship with respect to asthma.

BACKGROUND: Susceptibility to asthma is influenced by genes and environment; implicated genes may indicate pathways for therapeutic intervention. Genetic risk factors may be useful in identifying subtypes of asthma and determining whether intermediate phenotypes, such as elevation of the total serum IgE level, are causally linked to disease. METHODS: We carried out a genomewide association study by genotyping 10,365 persons with physician-diagnosed asthma and 16,110 unaffected persons, all of whom were matched for ancestry. We used random-effects pooled analysis to test for association in the overall study population and in subgroups of subjects with childhood-onset asthma (defined as asthma developing before 16 years of age), later-onset asthma, severe asthma, and occupational asthma. RESULTS: We observed associations of genomewide significance between asthma and the following single-nucleotide polymorphisms: rs3771166 on chromosome 2, implicating IL1RL1/IL18R1 (P=3×10(−9)); rs9273349 on chromosome 6, implicating HLA-DQ (P=7×10(−14)); rs1342326 on chromosome 9, flanking IL33 (P=9×10(−10)); rs744910 on chromosome 15 in SMAD3 (P=4×10(−9)); and rs2284033 on chromosome 22 in IL2RB (P=1.1×10(−8)). Association with the ORMDL3/GSDMB locus on chromosome 17q21 was specific to childhood-onset disease (rs2305480, P=6×10(−23)). Only HLA-DR showed a significant genomewide association with the total serum IgE concentration, and loci strongly associated with IgE levels were not associated with asthma. CONCLUSIONS: Asthma is genetically heterogeneous. A few common alleles are associated with disease risk at all ages. Implicated genes suggest a role for communication of epithelial damage to the adaptive immune system and activation of airway inflammation. Variants at the ORMDL3/GSDMB locus are associated only with childhood-onset disease. Elevation of total serum IgE levels has a minor role in the development of asthma. (Funded by the European Commission and others.)

Asthma is caused by a heterogeneous combination of environmental and genetic factors. In the context of GA2LEN (Global Allergy and Asthma European Network), we carried out meta-analyses of almost all genome-wide linkage screens conducted to date in 20 independent populations from different ethnic origins (>= 3024 families with >= 10 027 subjects) for asthma, atopic asthma, bronchial hyper-responsiveness and five atopy-related traits (total immunoglobulin E level, positive skin test response (SPT) to at least one allergen or to House Dust Mite, quantitative score of SPT (SPTQ) and eosinophils (EOS)). We used the genome scan meta-analysis method to assess evidence for linkage within bins of traditionally 30-cM width, and explored the manner in which these results were affected by bin definition. Meta-analyses were conducted in all studies and repeated in families of European ancestry. Genome-wide evidence for linkage was detected for asthma in two regions (2p21-p14 and 6p21) in European families ascertained through two asthmatic sibs. With regard to atopy phenotypes, four regions reached genome-wide significance: 3p25.3-q24 in all families for SPT and three other regions in European families (2q32-q34 for EOS, 5q23-q33 for SPTQ and 17q12-q24 for SPT). Tests of heterogeneity showed consistent evidence of linkage of SPTQ to 3p11-3q21, whereas between-study heterogeneity was detected for asthma in 2p22-p13 and 6p21, and for atopic asthma in 1q23-q25. This large-scale meta-analysis provides an important resource of information that can be used to prioritize further fine-mapping studies and also be integrated with genome-wide association studies to increase power and better interpret the outcomes of these studies. European Journal of Human Genetics (2010) 18, 700-706; doi: 10.1038/ejhg.2009.224; published online 13 January 2010

International audience; Bipolar disorder has a genetic component, but the mode of inheritance remains unclear. A previous genome scan conducted in 70 European families led to detect eight regions linked to bipolar disease. Here, we present an investigation of whether the phenotypic heterogeneity of the disorder corresponds to genetic heterogeneity in these regions using additional markers and an extended sample of families. The MLS statistic was used for linkage analyses. The predivided sample test and the maximum likelihood binomial methods were used to test genetic homogeneity between early-onset bipolar type I (cut-off of 22 years) and other types of the disorder (later onset of bipolar type I and early-onset bipolar type II), using a total of 138 independent bipolar-affected sib-pairs. Analysis of the extended sample of families supports linkage in four regions (2q14, 3p14, 16p23, and 20p12) of the eight regions of linkage suggested by our previous genome scan. Heterogeneity testing revealed genetic heterogeneity between early and late-onset bipolar type I in the 2q14 region (P = 0.0001). Only the early form of the bipolar disorder but not the late form appeared to be linked to this region. This region may therefore include a genetic factor either specifically involved in the early-onset bipolar type I or only influencing the age at onset (AAO). Our findings illustrate that stratification according to AAO may be valuable for the identification of genetic vulnerability polymorphisms. © 2010 Wiley-Liss, Inc.

International audience; ABSTRACT : Identifying gene-environment (G x E) interactions has become a crucial issue in the past decades. Different methods have been proposed to test for G x E interactions in the framework of linkage or association testing. However, their respective performances have rarely been compared. Using Genetic Analysis Workshop 15 simulated data, we compared the power of four methods: one based on affected sib pairs that tests for linkage and interaction (the mean interaction test) and three methods that test for association and/or interaction: a case-control test, a case-only test, and a log-linear approach based on case-parent trios. Results show that for the particular model of interaction between tobacco use and Locus B simulated here, the mean interaction test has poor power to detect either the genetic effect or the interaction. The association studies, i.e., the log-linear-modeling approach and the case-control method, are more powerful to detect the genetic effect (power of 78% and 95%, respectively) and taking into account interaction moderately increases the power (increase of 9% and 3%, respectively). The case-only design exhibits a 95% power to detect G x E interaction but the type I error rate is increased.

Asthma and bronchial hyper-responsiveness (BHR), an asthma-related phenotype, result from many genetic (G) and environmental (E) factors. Passive exposure to tobacco smoke (ETS) in early life is one of these risk factors. Following a genome scan for asthma and associated phenotypes conducted in 295 French Epidemiological study on the Genetics and Environment of Asthma, our present aim was to investigate interactions between genetic susceptibility to asthma and to BHR with passive ETS using two different methods: the predivided sample test (PST) and the mean interaction test (MIT). PST and MIT consider the identical by descent (identity by descent) distribution at all markers in affected sib-pairs with 2, 1 or 0 sib(s) exposed to ETS. While the PST allows detection of both linkage and G x E interaction, the MIT tests for linkage by taking into account a possible interaction. Among the six regions detected at P

International audience; Asthma, allergic rhinitis (AR) and atopic dermatitis also called eczema are allergic co-morbidites, which are likely to depend on pleiotropic genetic effects as well as on specific genetic factors. After a previous genome-wide linkage screen conducted for asthma and AR in a sample of 295 French EGEA families ascertained through asthmatic subjects, the aim here was to search for genetic factors involved in eczema and more particularly the ones shared by the three allergic diseases using the same EGEA data. In this sake, eczema and phenotypes of "allergic disease" accounting for the joint information on the presence/absence of the three diseases were examined by linkage analyses using the maximum likelihood binomial method. A fine mapping was carried out in regions detected for potential linkage, followed by association studies using the family-based association test (FBAT). Evidence for linkage to 11p14 region was shown for "allergic disease" and eczema. Linkage was also indicated between eczema and 5q13 and between "allergic disease" and both 5p15 and 17q21 regions. Fine mapping supported the evidence of linkage to 11p14 and FBAT analyses showed the association between "allergic disease" and a marker located at the linkage peak on 11p14. Further investigations in this region will allow identifying genetic factor(s) which could have pleiotropic effect in the three allergic diseases.

Objective: A recent genome scan conducted in French EGEA families led to detect linkage of 1p31 to either asthma or allergic rhinitis (AR) and more significantly to asthma associated with AR. The goal of the present study was to assess formally whether 1p31 is a linkage region shared by two different diseases, asthma and AR, or whether it is specific to the co-morbidity asthma plus AR. Methods: We used two different statistical approaches: the Triangle Test Statistic (TTS) and the Predivided Sample Test (PST), to search for heterogeneity of linkage to 1p31 according to the affection status being defined by either the presence of the two diseases (asthma plus AR) or the presence of only one disease (‘asthma only’ or ‘AR only’ or ‘asthma only or AR only’). Results: While no heterogeneity between the ‘two diseases’ phenotype and the ‘one disease’ phenotype was detected by the TTS, there was significant evidence for heterogeneity (p = 0.00007/0.002 after correction for multiple testing) using the PST. There was no indication of linkage in sib-pairs with ‘one disease’ only, while there was significant evidence for linkage in sib-pairs displaying asthma plus AR (p = 0.0002/0.0016 after correction). Conclusion: The present analysis shows that the co-morbidity, asthma plus AR, represents a phenotypic entity, distinct from asthma only or AR only, controlled by a genetic factor located on 1p31.

Although many genome screens have been conducted for asthma as a binary trait, there is limited information regarding the genetic factors underlying variation of asthma expression. Phenotypes related to variable disease expression include time to asthma onset and variation in clinical expression as measured by an asthma score built from EGEA data. A recent genome scan conducted for this score led to detection of a new region (18p11) not revealed by analysis of dichotomous asthma. Our goal was to characterize chromosomal regions harboring genes underlying time to asthma onset and to search for pleiotropic QTL influencing both time to asthma onset and the asthma score. We conducted a genome-wide linkage screen for time to asthma onset, modeled by martingale residuals from Cox survival model, in EGEA families with at least two asthmatic sibs. This was followed by a bivariate linkage scan of these residuals and asthma score. Univariate linkage analysis was performed using the Maximum Likelihood Binomial method that we extended to bivariate analysis. This screen revealed two regions potentially linked to time to asthma onset, 1p31 (LOD = 1.70, P = 0.003) and 5q13 (LOD = 1.87, P = 0.002). Bivariate linkage analysis led to a substantial improvement of the linkage signal on 5q13 (P = 0.00007), providing evidence for a pleiotropic QTL influencing both variation of time to asthma onset and of clinical expression. Use of quantitative phenotypes of variable disease expression and suitable statistical methodology can improve the power to detect new regions harboring genes which may play an important role in onset and course of disease.

Previous genome scan linkage analyses of the disease Kofendrerd Personality Disorder (KPD) with microsatellites led to detect some regions on chromosomes 1, 3, 5, and 9 that were identical for the three populations AI, KA, and DA but with large differences in significance levels. These differences in results may be explained by the different diagnosis definitions depending on the presence/absence of 12 traits that were used in the 3 populations AI, KA, and DA. Heterogeneity of linkage was thus investigated here according to the absence/presence of each of the 12 traits in the 3 populations. For this purpose, two methods, the triangle test statistic and the predivided sample test were applied to search for genetic heterogeneity. Three regions with a strong heterogeneity of linkage were detected: the region on chromosome 1 according to the presence/absence of the traits a and b, the region on chromosome 3 for the trait b, and the region on chromosome 9 for the traits k and l. These 3 regions were the same as those detected by linkage analyses. No novel region was detected by the heterogeneity tests. Concerning chromosome 1, linkage analyses showed a much stronger evidence of linkage for traits a and b and for a combination of these traits than for KPD. Moreover, there was no indication of linkage to any of the other traits used to define the diagnosis of KPD. A genetic factor located on the chromosome 1 may have been detected here which would be involved specifically in traits a and b or in a combination of these traits.

A genome-wide scan for asthma phenotypes was conducted in the whole sample of 295 EGEA families selected through at least one asthmatic subject. In addition to asthma, seven phenotypes involved in the main asthma physiopathological pathways were considered: SPT (positive skin prick test response to at least one of 11 allergens), SPTQ score being the number of positive skin test responses to 11 allergens, Phadiatop (positive specific IgE response to a mixture of allergens), total IgE levels, eosinophils, bronchial responsiveness (BR) to methacholine challenge and %predicted FEV(1). Four regions showed evidence for linkage (P/=0.001): 6q14 for %FEV(1), 12p13 for IgE, 17q22-q24 for SPT and 21q21 for both SPTQ and %FEV(1). Nine other regions indicated smaller linkage signals (0.001P/=0.005). While most of these regions have been reported by previous asthma and lung function screens, 6q14 appears to be a new region potentially linked to %FEV(1). To determine which of these various asthma phenotypes are more likely to share common genetic determinants, a principal component analysis was applied to the genome-wide LOD scores. This analysis revealed clustering of LODs for asthma, SPT and Phadiatop on one axis and clustering of LODs for %FEV(1), BR and SPTQ on the other, while LODs for IgE and eosinophils appeared to be independent from all other LODs. These results provide new insights into the potential sharing of genetic determinants by asthma-related phenotypes.

Three different samples of families with asthmatic patients, the German data set and the CSGA data set subdivided into Caucasian and African American groups, were analyzed using the maximum lod score statistic. Although different scores were obtained in each sample, the Wald's likelihood homogeneity test did not reveal any significant genetic heterogeneity. This may be due to the very large variance of the model-free linkage statistics.

International audience; Familial resemblance of asthma is well known but epidemiological research focused on familial resemblance of asthma severity is scanty. We studied whether asthma and asthma severity in first-degree relatives of cases with asthma were related to asthma severity of the index case. The analysis was based upon the examination of 944 subjects (348 cases, 239 relatives with asthma, and 357 subjects without asthma) and upon the information on 3467 first- degree relatives of probands. The risks of asthma in relatives of adult and pediatric cases were significantly higher than in relatives of subjects without asthma (OR 3.4 [95% CI 2.5-4.7] and 4.5 [2.6- 8.1], respectively). Proportions of asthma in relatives were not related to the asthma severity of cases for the three severity criteria studied (clinical score, FEV(1) % predicted, and inhaled corticosteroid use). Using both regression models and intraclass correlation coefficients, there was a significant familial resemblance for the clinical severity score (ICC = 0.23 and 0.23) and for FEV(1) (ICC = 0.19 and 0.25) among families of pediatric and adult probands, respectively. In conclusion, asthma occurrence in relatives may be independent of the severity of the cases with asthma, but results suggest familial resemblance in the severity of asthma when it occurs.

It is generally believed that an early age at the onset of disease is associated with a stronger genetic component. Our aim here was to investigate both linkage and genetic heterogeneity of asthma, the latter corresponding to different genotype relative risks of a putative linked gene according to age at onset of asthma. This analysis was conducted in 107 French EGEA families with at least two asthmatic siblings, considering 157 markers that were part of our previous genome screen, using the TTS (the Triangle Test Statistic) which has been developed to detect both linkage and intra-sibpair genetic heterogeneity. This test has been applied to 38 asthmatic sib-pairs discordant for age at the onset of asthma. To confirm the existence of genetic heterogeneity, we also used the predivided sample test (PST) which compares the IBD (identity by descent) distribution of marker alleles between asthmatic sib-pairs concordant (67) and discordant (38) for the age at onset. The cutoff point used for the age at onset was 4 years, the median age at onset in our sample of asthmatic sibs. Linkage and genetic heterogeneity for a region located on chromosome 7q (at 109 cM from pter) were indicated by both tests, TTS (P=0.005, P>0.5 after correction for multiple testing) and PST (P=0.0001, 0.015 after correction). These results suggest a genetic factor on 7q involved in asthma with genotype relative risks differing according to age at onset of disease.