AllerGen / Vancouver - 01/03//2009 Meta-Analysis of GABRIEL GWAS Asthma & IgE F. Demenais, M. Farrall, D. Strachan GABRIEL Statistical Group

AllerGen / Vancouver - 01/03//2009 GABRIEL Phase I GWAS GWAS (Illumina 300K) of UK & German data → 17q21 locus (ORMDL3) associated with asthma Moffat et al, Nature, 2007 Replication of this association by several studies Genetic heterogeneity at 17q21 locus (French EGEA data) → Effect of 17q21 variants restricted to early-onset asthma and enhanced by early-life exposure to ETS Bouzigon et al, New Engl J Med, 2008

AllerGen / Vancouver - 01/03//2009 Aim of Phase II Gabriel GWAS To identify associations of genetic variants with: - susceptibility to asthma (childhood onset, adult onset, industrial) - total IgE levels across populations of European ancestry using Illumina Human 610-Quad beadchip by conducting a meta-analysis of all studies

AllerGen – Vancouver – 01/03/2009 DATA AVAILABLE for Phase II GWAS - Most datasets are cases/controls - A few datasets include families: MRC (UK), EGEA (French), Canadian, Russian, GSK… Childhood onset Asthma subjects Adult onset Asthma Industrial Asthma1356 subjects

GWAS Phase II DATA

Genotyping at CNG (Y. Gut, M. Lathrop, Evry, France) Using Illumina Human 610-Quad beadchip Initial QC processing at CNG (S.Heath, CNG) % genotype calls - by individuals (< 95%: individuals excluded) Relationship analysis to confirm known & identify cryptic relationships Sex checks based on X-chromosome SNPs Principal components analysis to identify cryptic non-European ancestry Phase II GWAS: Overall Strategy Analysis study by study (M Farrall, Oxford) From Phenotypic data (each group) & Genotypic Data (CNG) Meta-analysis of all studies: Phase II + Phase I (imputation) Asthma (F Demenais, Paris) IgE (D Strachan, London) childhood onset, adult onset, all controls & cases separately industrial asthma

AllerGen – Vancouver – 01/03/2009 Phenotypes Asthma : Cases : doctor-diagnosed asthma or self-reported + age onset of asthma Controls: unaffecteds (not selected as « hypernormal » and may include other forms of wheezing) → Childhood Onset / Adult Onset Asthma using a cutoff of 16yrs Controls drawn at random for childhood onset/ adult onset cases IgE (log 10 ) IgE wadjusted on sex and age-at-measurement by study and by case-control status

AllerGen – Vancouver – 01/03/2009 Method used for Study by Study Analysis Single SNP analysis based on logistic regression models (linear regression for IgE) allowing for familial clustering using STATA Different models considered: - additive model (1df) - additive and non-additive effects ( 2 x 1 df) - genotype association model (2 df) Population Stratification: Eigenvectors from PCA included in regression model PCA uses HapMap data + CNG data (European controls)

AllerGen – Vancouver – 01/03/2009 Population stratification PCA on European controls from French National Genotyping Center Heath et al, Eur J Hum Genet, 2008

AllerGen – Vancouver – 01/03/2009 Meta-Analysis for Asthma & IgE From the study-by-study analysis, tables generated including for each SNP: QC metrics (MAF, SNP Call Rate, HW..) Number of cases / controls by genotype Regression coefficients & Standard errors Various test statistics QC Filtering based on MAF (1% or 5%), SNP Call Rate (≥ 97%) HW (p > ) Meta-analysis using different methods

AllerGen – Vancouver – 01/03/2009 Methods used for Primary Meta-Analysis Fixed-effect (inverse variance weighted) models assumes that observed effects are estimates of a single effect average effect computed by weighting each study’s log OR according to the inverse of their sampling variance → Test of homogeneity for SNP effect across studies using Cochran Q test Random-effect models (DerSimonian & Laird, 1986) allows for effects to vary across studies variance = between study variation + intra-study variation preferred if # of study-specific estimates ≥ 5

AllerGen / Vancouver - 01/03//2009 Fixed vs Random effect Models Example: Type 2 Diabetes (Ionnadis et al, PLoS one, 2007) Meta-analysis of FUSION, DGI, WTCC GeneSNPQ (p)I 2 (95% CI) Random pFixed p rs % (0-90) x10-7 FTO rs % (0-91) x10-12 CDKAL1 rs % (0-84)3.2x x10-11 PPARG rs % (0-84) x10-6 CDKN2Brs % (0-73)1.2x10-7 HHEXrs % (0-73)5.7x10-10

AllerGen / Vancouver - 01/03//2009 Other Methods of Meta-analysis: Meta-Regression Bag & Nikolopoulos, Stat Appl Mol Biol, 2007 Study i = 1, 2..k Cases yij = 1 Controls yij =0 Genotype j =1,2,..r Logit (pij) =  i +  2 z i2 +  3 z i3 if genotype effect cst between studies Logit (pij) =  i +  2 z i2 +  3 z i3 +  i2  i z i2 +  i3  i z i3 if gentoypexstudy int → Test for heterogeneity between studies using Multivariate Wald test Possible to include random effect + various covariates

AllerGen / Vancouver - 01/03//2009 Other Approaches of Meta-Analysis ● Combining p-values or Z scores ● Local Score method (Guedj et al, 2006; Aschard et al, 2007) can detect aggregation of association signals flexible approach which can use any test statistic

Outcome of Meta-Analysis Identify Top SNPs (genome-wide significant) Phase III Gabriel Genotype top SNPs in individuals

AllerGen / Vancouver - 01/03//2009 Gene-Gene Interactions

AllerGen / Vancouver - 01/03//2009 Various Methods to investigate GxG -Regression-based methods (one stage, 2 stages…) -Bayesian based approaches -Data Reduction based-methods / Machine Learning ‘Combinatorial Partitioning Method (CPM), MDR) - Pattern recognition models (neural networks) -Combination of test statistics (meta-statistics)  Gabriel provides opportunity to compare these methods by pooling data or in the context of meta-analysis

AllerGen / Vancouver - 01/03//2009 Gene-Environment Interactions

AllerGen / Vancouver - 01/03// Step-Analysis to identify genes involved in GxE Murcray et al, Am J Epidemiol, 2008 Step 1: Screening test: case only analysis (combined case/control sample ) For each of N SNPs: LR Test for association between G and E → Select m SNPs with P <  1 Step 2 : Case- Control analysis LR Test for GxE applied to m SNPs selected at step 1 → Significance based on P <  /m Comparison with classical one-step approach applied to case-controls → Significance based on P <  /N

AllerGen / Vancouver - 01/03//2009 Power for one-step and two-step analyses to detect GxE for varying levels of interaction effect size 10,000 markers and 500 cases/500 controls

AllerGen / Vancouver - 01/03//2009 GABRIEL Working Groups GW search for G X smoking in asthma M Boezen, D Postma, The Netherlands Childood Asthma (M Kabesch) & Adult Asthma (D. Jarvis) to summarize data available in each study (phenotypes, environment) Main areas of interest for collaborations : Phenotypes Environmental exposures : GxE Pathways: GxG Other types of variation: CNVs Methodological issues  New opportunities that are going to emerge from the AllerGen meeting