PhD,* a,b Medea Imboden

MD Emmanuelle Bouzigon

MD Ivan Curjuric

PhD, f Adaikalavan Ramasamy

MSc Ashish Kumar

PhD, h,i , Jemma B Wilk, DSc, j , Dana B Hancock

Jemma B Wilk

PhD, k Judith M Vonk

MSc Gian A Thun

PhD Valerie Siroux

PhD Rachel Nadif

MSc Florent Monier

PhD Juan R Gonzalez

MD, MD r Matthias Wjst

PhD, r , Joachim Heinrich

MD Laura R Loehr

PhD, s , Nora Franceschini

MD, MPH s , Kari E North

PhD, t , Janine Altmüller

MD, PhD Gerard H Koppelman

MD Stefano Guerra

MD Florian Kronenberg

PhD Mark Lathrop

Miriam F Moffatt

D Phil

MD, MSc George T O'connor

MD David P Strachan

MD, PhD k , Dirkje S Postma

MD, DrPH Stephanie J London

PhD Christian Schindler

MD Manolis Kogevinas

MD Francine Kauffmann

MD Debbie L Jarvis

MD Florence Demenais

PhD Nicole M Probst-Hensch

Genome-wide association study of lung function decline in

Keywords: Asthma, cohort studies, genome-wide association, lung function decline, heterogeneity ARIC, Atherosclerosis Risk in Communities Study chromosome COPD, chronic obstructive pulmonary disease ECRHS, European Community Respiratory Health Survey

Genotyping of the discovery cohort and part of B58C

INTRODUCTION

Low lung function is a feature of both asthma and chronic obstructive pulmonary disease (COPD), with twin studies demonstrating strong heritability (0.51 to 0.77) for forced expiratory volume in the first second (FEV1) [START_REF] Hankins | Pulmonary function in identical twins raised apart[END_REF][START_REF] Redline | Genotypic and phenotypic similarities in pulmonary function among family members of adult monozygotic and dizygotic twins[END_REF] . The two respiratory diseases and lung function itself share predisposing and phenotypic features, including increased airway responsiveness and atopy as well as exogenous risk factors [START_REF] Guerra | Asthma and chronic obstructive pulmonary disease[END_REF][START_REF] Postma | Rationale for the Dutch hypothesis. Allergy and airway hyperresponsiveness as genetic factors and their interaction with environment in the development of asthma and COPD[END_REF] . Genome-wide association studies (GWAS) have identified novel genetic loci for asthma [START_REF] Moffatt | Genetic variants regulating ORMDL3 expression contribute to the risk of childhood asthma[END_REF][START_REF] Himes | Genome-wide association analysis identifies PDE4D as an asthma-susceptibility gene[END_REF][START_REF] Moffatt | A largescale, consortium-based genomewide association study of asthma[END_REF][START_REF] Sleiman | Variants of DENND1B associated with asthma in children[END_REF][START_REF] Dewan | PDE11A associations with asthma: results of a genome-wide association scan[END_REF][START_REF] Hancock | Genome-wide association study implicates chromosome 9q21.31 as a susceptibility locus for asthma in mexican children[END_REF] , COPD [START_REF] Pillai | A genome-wide association study in chronic obstructive pulmonary disease (COPD): identification of two major susceptibility loci[END_REF][START_REF] Pillai | Loci Identified by Genome-wide Association Studies Influence Different Disease-related Phenotypes in COPD[END_REF][START_REF] Cho | Variants in FAM13A are associated with chronic obstructive pulmonary disease[END_REF][START_REF] Kong | Genome-wide Association Study Identifies BICD1 as a Susceptibility Gene for Emphysema[END_REF] , and lung function [START_REF] Wilk | A genomewide association study of pulmonary function measures in the Framingham Heart Study[END_REF][START_REF] Hancock | Metaanalyses of genome-wide association studies identify multiple loci associated with pulmonary function[END_REF][START_REF] Repapi | Genome-wide association study identifies five loci associated with lung function[END_REF][START_REF] Artigas | Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function[END_REF] and provide the opportunity to study agnostically their overlap in genetic background [START_REF] Weiss | Lung function and airway diseases[END_REF] . Some of the implicated genes, such as PDE4D, support a link between asthma and COPD which may be rooted in shared pathways during lung development [START_REF] Weiss | What genes tell us about the pathogenesis of asthma and chronic obstructive pulmonary disease[END_REF] . However, the majority of the genes implicated in asthma or COPD GWAS analyses have not been identified as top association signals in GWAS for lung function in the general population [START_REF] Wilk | A genomewide association study of pulmonary function measures in the Framingham Heart Study[END_REF][START_REF] Hancock | Metaanalyses of genome-wide association studies identify multiple loci associated with pulmonary function[END_REF][START_REF] Repapi | Genome-wide association study identifies five loci associated with lung function[END_REF][START_REF] Artigas | Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function[END_REF] , with the exception of HHIP and FAM13A being associated with both lung function [START_REF] Wilk | A genomewide association study of pulmonary function measures in the Framingham Heart Study[END_REF][START_REF] Hancock | Metaanalyses of genome-wide association studies identify multiple loci associated with pulmonary function[END_REF][START_REF] Repapi | Genome-wide association study identifies five loci associated with lung function[END_REF][START_REF] Artigas | Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function[END_REF] and COPD [START_REF] Pillai | A genome-wide association study in chronic obstructive pulmonary disease (COPD): identification of two major susceptibility loci[END_REF][START_REF] Pillai | Loci Identified by Genome-wide Association Studies Influence Different Disease-related Phenotypes in COPD[END_REF][START_REF] Cho | Variants in FAM13A are associated with chronic obstructive pulmonary disease[END_REF][START_REF] Kong | Genome-wide Association Study Identifies BICD1 as a Susceptibility Gene for Emphysema[END_REF] . Several lines of evidence suggest that different genes influence lung function in asthmatics and in non-asthmatics.

Genome-scans in family based linkage studies identified some, but overall limited overlap between chromosomal regions linked to lung function in asthmatics [START_REF] Postma | Genomewide screen for pulmonary function in 200 families ascertained for asthma[END_REF] , COPD patients [START_REF] Silverman | Genomewide linkage analysis of quantitative spirometric phenotypes in severe early-onset chronic obstructive pulmonary disease[END_REF] and in the general population [START_REF] Wilk | A genomewide scan of pulmonary function measures in the National Heart, Lung, and Blood Institute Family Heart Study[END_REF] and it has been suggested that genetic variation may be more important for lung function in asthma after adjusting for smoking and body size differences [START_REF] Postma | Genomewide screen for pulmonary function in 200 families ascertained for asthma[END_REF][START_REF] Holberg | Differences in familial segregation of FEV1 between asthmatic and nonasthmatic families. Role of a maternal component[END_REF][START_REF] Palmer | Familial aggregation and heritability of adult lung function: results from the Busselton Health Study[END_REF] .

Here, we present results from the first lung function GWAS conducted separately for asthmatics and non-asthmatics. This current study also focuses on the rate of lung function decline in adults instead of cross-sectional lung function parameters tested in previous GWAS [START_REF] Wilk | A genomewide association study of pulmonary function measures in the Framingham Heart Study[END_REF][START_REF] Hancock | Metaanalyses of genome-wide association studies identify multiple loci associated with pulmonary function[END_REF][START_REF] Repapi | Genome-wide association study identifies five loci associated with lung function[END_REF][START_REF] Artigas | Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function[END_REF] . The discovery cohorts included two population-based studies (SAPALDIA and ECRHS) and one asthma family-based study (EGEA), all of European ancestry with highly comparable and standardized assessment of respiratory health parameters including spirometry from two time points ten years apart. These three studies had been included in the GWAS for asthma conducted by the GABRIEL consortium [START_REF] Moffatt | A largescale, consortium-based genomewide association study of asthma[END_REF] . Replication cohorts included three population-based cohorts (FHS, ARIC, B58C) and one family-based asthma study (the Dutch Asthma Study).

METHODS

-Discovery cohorts and study population: Three large multi-centric cohorts EGEA [START_REF] Kauffmann | Epidemiological study of the genetics and environment of asthma, bronchial hyperresponsiveness, and atopy: phenotype issues[END_REF] , SAPALDIA [START_REF] Downs | Reduced exposure to PM10 and attenuated age-related decline in lung function[END_REF] and ECRHS [START_REF]The European Community Respiratory Health Survey II[END_REF] -Replication Cohorts: Four cohorts of European ancestry with available genome-wide data, ARIC [START_REF]The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. The ARIC investigators[END_REF] , FHS [START_REF] Wilk | A genomewide association study of pulmonary function measures in the Framingham Heart Study[END_REF] ; B58C [START_REF] Marossy | Childhood chest illness and the rate of decline of adult lung function between ages 35 and 45 years[END_REF] ; Dutch asthma study [START_REF] Dijkstra | Estrogen receptor 1 polymorphisms are associated with airway hyperresponsiveness and lung function decline, particularly in female subjects with asthma[END_REF] were used for replication. Subjects included in the current analysis were older than 24 years, had complete information on covariates (age, height, and sex) and valid lung function measures from at least two time-points. The lung function measurements were conducted at least ten years apart, except three years apart for ARIC (Table I). Distinct genotype data platforms and imputation software were used (Table EII, Online Repository).

-Statistical analysis: Annual decline in FEV1 and FEV1/FVC was calculated as difference between follow-up and baseline spirometric measurements (mL for FEV1 and % for FEV1/FVC) divided by the duration of follow-up in years. Standardized residuals were derived from sex-specific linear regression models adjusted for age, height and study centre in asthmatics and non-asthmatics separately. Comparability between studies of standardized residuals was tested using Wilcoxon-Mann-Whitney test (P>0.94). The standardized residuals were used as dependent variable and regressed on genome-wide single nucleotide polymorphisms (SNPs) adjusted for study-specific principal components capturing population ancestry (see online supplement for details).

Study-specific SNP effect estimates were combined through meta-analysis using fixed and random effects models. We used a threshold of P<5x10 -8 (the Bonferroni adjustment for one million independent tests) to declare a pooled effect as genomewide significant. Selection criteria for replication loci are described in the methods section of the online repository. SNPs with suggestive evidence of association with decline in FEV1 or FEV1/FVC were chosen for in silico replication (

RESULTS

Characteristics of the study populations

The cohorts included in this study differed by age and type of recruitment, and accordingly in lung function and the proportion of subjects with FEV1/FVC below 70%

(Table I

Main findings from meta-analyses of discovery and replication phase

In the discovery phase, GWAS meta-analysis of decline in FEV1 and FEV1/FVC was conducted in 2677 non-asthmatics and in 1441 asthmatics. Genomic inflation factors were low for both lung function parameters (λ<1.047, Table EIX, Online Repository)

suggesting minimal unaccounted population stratification. The replication panel included a total of 10'858 non-asthmatics and 1'138 asthmatics. Thirty lead SNPs belonging to 30 loci (5x10 -8 < P discovery <6x10 -5 ) were chosen for replication.

The four lung function parameter-and asthma-specific meta-analyses identified one association signal that almost reached the genome-wide significance level (P = 5.3x10 -

8

) at the locus 8p22 containing the TUSC3 gene for FEV1/FVC decline in asthmatics while all other signals had P<5x10 -7 (Figure I), but this signal was not associated with FEV1/FVC decline in asthmatics in the replication sample. The only locus of the selected replication candidate loci that formally replicated was 13q14.3, containing the DLEU7 gene, associated with decline in FEV1 in the non-asthmatics (P discovery =4.8x10 -6 and P replication =0.03).

In the global post hoc analysis combining both asthmatics and non-asthmatics (N=4118), a striking finding was the absence of any pronounced association signals (P >1x10 -6 ) despite increased statistical power. This was in agreement with the minimal overlap of association signals observed in asthmatics and non-asthmatics separately.

Most signals at P<10 -5 from the asthma-stratified analysis in the discovery phase exhibited statistically significant heterogeneity of effects between the two groups (Table II). At the replication stage, none of the replication SNPs was associated with lung function decline in asthmatics and non-asthmatics combined.

Association signals for annual decline in FEV1 in non-asthmatics

Of fifteen SNPs associated at P<10 -5 with decline in FEV1 in non-asthmatics ten were II) replicated. The G-allele of SNP rs9316500 near the DLEU7 gene was positively associated with annual FEV1 decline in the discovery cohorts (P=4.8x10 -6 ) and in the replication cohorts (P=0.026). Although heterogeneity between studies was not significant (P=0.61), the combined P value did not reach the genome-wide level (P=5.7x10 -5 ).

Association signals for annual decline in FEV1 in asthmatics

Eighteen SNPs in nine distinct chromosomal locations were associated with decline in FEV1 in asthmatics at P<10 -5 . None of the loci selected for in silico replication was confirmed (Table II).

Association signals for annual decline in FEV1/FVC in non-asthmatics

Seven loci showed association with FEV1/FVC decline in non-asthmatics at 10 -6 <P<10 -

5

, but no locus selected for replication was confirmed (Table II).

Association signals for annual decline in FEV1/FVC in asthmatics

Twelve SNPs at the locus 8p22 containing the gene TUSC3 at 15.68Mb were associated with FEV1/FVC decline at P<10 II). However this association was not replicated (P=0.80). In the meta-analysis combining discovery and replication samples the resulting P-value for rs4831760 was 2.8x10 -5 . All but the Dutch asthma study, exhibited effect estimates in the same direction as the discovery panel. Two other candidate loci (MPP7 and SYNE2) also failed replication testing.

SNPs previously associated in GWAS meta-analyses on cross-sectional lung function

The associations of top hit SNPs from previous GWAS meta-analyses on crosssectional lung function [START_REF] Pillai | A genome-wide association study in chronic obstructive pulmonary disease (COPD): identification of two major susceptibility loci[END_REF][START_REF] Wilk | A genomewide association study of pulmonary function measures in the Framingham Heart Study[END_REF][START_REF] Hancock | Metaanalyses of genome-wide association studies identify multiple loci associated with pulmonary function[END_REF][START_REF] Repapi | Genome-wide association study identifies five loci associated with lung function[END_REF][START_REF] Artigas | Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function[END_REF] and a replication study in asthmatics [START_REF] Li | Importance of hedgehog interacting protein and other lung function genes in asthma[END_REF] were assessed separately for asthmatics and non-asthmatics in the discovery cohorts. Associations were assessed for both, lung function parameters of decline (annual decline and percent change) and cross-sectional lung function level. Overall, a subset of variants and loci showed replication of association with cross-sectional lung function in either non-asthmatics or asthmatics. Few of the loci showed strong association with decline in lung function. We present associations at P<0.05 in For baseline FEV1, we observed associations for SNPs belonging to 4q24 (GSTCD, rs11731417, P=1.3x10 -4 ) and 15q23 (THSD4, rs1913768, P=0.003). Associations with baseline FEV1 were mainly restricted to non-asthmatics. For baseline FEV1/FVC, associations of SNPs of THSD4 were prominent (e.g. rs12899618, P=3.3x10 -4 ) and again restricted to non-asthmatics.

For decline phenotypes of FEV1, we observed associations for SNPs in regions 6p21 (DAAM2, 0.003<P<0.02) and 4q28 (HHIP, 0.02<P<0.05) among asthmatics and in THSD4 (0.003<P<0.04) among non-asthmatics. The strongest associations observed for decline phenotypes of FEV1/FVC were two SNPs in MMP15 (16q13, 0.003<P<0.002) in non-asthmatics, only. Association in the combined sample of asthmatics and non-asthmatics did not substantially alter the results.

Summary of findings from sensitivity analyses

We observed in non-asthmatics, aged 30 years and more, that MUSK and DLEU7 were no longer prominently associated with FEV1 decline, but SNPs in other genes remained strongly associated (ZIC1, rs6785065, P=2.3x10 -5 ; UBL3, rs278037, P=4.8x10 -5 ).

Results of the GWAS on percent change in lung function showed that the FEV1 association signal for DLEU7 in the non-asthmatics was no longer significant; however the signals for MUSK (rs1889321, P=2.92x10 -7 ) and other loci remained unaltered (ZIC1, rs6785065, P=2.0x10 -5 ; KIRREL3, rs11604082, P=4.1x10 -6 ; KIAA2117, rs10082549, P=2.7x10 -6 ). Top signals associated with decline in FEV1/FVC in asthmatics remained unaltered for TUSC3 (rs4831760, P=5.2x10 -8 ) and for SYNE2 (rs7144584, P=6.4x10 -7 ) after taking baseline lung function into account.

Smoking stratified analyses of the replication SNPs revealed no substantial difference in association between ever and never smokers except for a few SNPs belonging to loci containing SYNE2, RORA, BCAS1, or PLXNA4 genes.

Replication meta-analysis excluding the ARIC data substantially reduced sample size in non-asthmatics and the association of DLEU7 with decline of FEV1 was no longer significant. Instead two loci for association with decline in FEV1 in asthmatics (PLXNA4, rs10808265, P discovery =1.7x10 -6 , P replication =0.02 and SLC45A3, rs16856186, P discovery =8.9x10 -6 , P replication =0.04) and one locus, FLJ25393, for decline in FEV1/FVC in non-asthmatics (rs2658782, P discovery =4.3x10 -6 , P replication =0.03) gained statistical significance.

DISCUSSION

A main result of this study is the observed genetic heterogeneity of lung function decline between asthmatics and non-asthmatics. When we combined the two groups in the discovery phase we observed no genome-wide significant association signal despite larger sample size. All top hit association signals detected by the asthma stratified analysis showed significant heterogeneity according to the disease status. In the replication phase, this heterogeneity was also confirmed for the DLEU7 locus which was associated with FEV1 decline in non-asthmatics only. Finally, many of the SNPs identified by previous GWAS on lung function exhibited associations specific to asthma status.

The finding of genetic heterogeneity in lung function reported here is consistent with available evidence. Differences in familial segregation of FEV1 in asthmatic and nonasthmatic families previously suggested genetic heterogeneity between these two groups [START_REF] Holberg | Differences in familial segregation of FEV1 between asthmatic and nonasthmatic families. Role of a maternal component[END_REF] . Agnostic studies investigating genetic determinants of lung function in both, family-based [START_REF] Postma | Genomewide screen for pulmonary function in 200 families ascertained for asthma[END_REF][START_REF] Silverman | Genomewide linkage analysis of quantitative spirometric phenotypes in severe early-onset chronic obstructive pulmonary disease[END_REF][START_REF] Malhotra | Further evidence for the role of genes on chromosome 2 and chromosome 5 in the inheritance of pulmonary function[END_REF][START_REF] Ober | The genetic dissection of complex traits in a founder population[END_REF][START_REF] Bouzigon | Clustering patterns of LOD scores for asthma-related phenotypes revealed by a genome-wide screen in 295 French EGEA families[END_REF][START_REF] Barton | PLAUR polymorphisms are associated with asthma, PLAUR levels, and lung function decline[END_REF] and population-based samples 15-18, 23, 25 produced little overlap in chromosomal regions. Genome-wide scans on lung function in asthma [START_REF] Postma | Genomewide screen for pulmonary function in 200 families ascertained for asthma[END_REF][START_REF] Xu | A genomewide search for quantitative-trait loci underlying asthma[END_REF] or COPD [START_REF] Silverman | Genomewide linkage analysis of quantitative spirometric phenotypes in severe early-onset chronic obstructive pulmonary disease[END_REF] families also suggested a heterogeneous genetic architecture of lung function.

Nevertheless, some previously reported overlapping linkage regions for the ratio of FEV1 over vital capacity (FEV1/VC) and FEV1 over the forced vital capacity (FEV1/FVC) in families with asthma and COPD [START_REF] Postma | Genomewide screen for pulmonary function in 200 families ascertained for asthma[END_REF][START_REF] Silverman | Genomewide linkage analysis of quantitative spirometric phenotypes in severe early-onset chronic obstructive pulmonary disease[END_REF] suggest that at least some gene(s) could be important in the development of airway obstruction in both diseases.

Furthermore, genetic polymorphisms in glutathione S-transferases [START_REF] Gilliland | Effects of glutathione-Stransferase M1, T1, and P1 on childhood lung function growth[END_REF][START_REF] Flamant | Glutathione-S-transferase M1, M3, P1 and T1 polymorphisms and severity of lung disease in children with cystic fibrosis[END_REF][START_REF] Romieu | Genetic polymorphism of GSTM1 and antioxidant supplementation influence lung function in relation to ozone exposure in asthmatic children in Mexico City[END_REF][START_REF] Imboden | Glutathione Stransferase genotypes modify lung function decline in the general population: SAPALDIA cohort study[END_REF] as well as ADAM-33 [START_REF] Jongepier | Polymorphisms of the ADAM33 gene are associated with accelerated lung function decline in asthma[END_REF][START_REF] Simpson | Polymorphisms in a disintegrin and metalloprotease 33 (ADAM33) predict impaired early-life lung function[END_REF][START_REF] Sadeghnejad | Adam33 polymorphisms are associated with COPD and lung function in long-term tobacco smokers[END_REF][START_REF] Van Diemen | A disintegrin and metalloprotease 33 polymorphisms and lung function decline in the general population[END_REF] were associated with lower lung function at all ages and in different subgroups of the population (general population, patients with COPD and asthma).

Gene-lung function associations that are of relevance to several population and patient strata may be determined specifically by complex gene-gene and gene-environment interactions, as suggested for lung function decline and its complex association with estrogen receptor 1 polymorphisms, smoking, steroid use, and gender [START_REF] Dijkstra | Estrogen receptor 1 polymorphisms are associated with airway hyperresponsiveness and lung function decline, particularly in female subjects with asthma[END_REF][START_REF] Dijkstra | Lung function decline in asthma: association with inhaled corticosteroids, smoking and sex[END_REF] . While ignored in ours as well as previous GWAS, such effect modifications should be considered in the future [START_REF] Cornelis | The Gene, Environment Association Studies consortium (GENEVA): maximizing the knowledge obtained from GWAS by collaboration across studies of multiple conditions[END_REF] .

Results from the Busselton Health Study on familial aggregation and heritability of adult lung function previously suggested the existence of genetic determinants of adult lung function independent of asthma, atopy, cigarette smoking, height, age or sex [START_REF] Palmer | Familial aggregation and heritability of adult lung function: results from the Busselton Health Study[END_REF] .

Consistent with these results, neither asthma, atopy and COPD genes previously identified in large GWAS [START_REF] Moffatt | Genetic variants regulating ORMDL3 expression contribute to the risk of childhood asthma[END_REF][START_REF] Himes | Genome-wide association analysis identifies PDE4D as an asthma-susceptibility gene[END_REF][START_REF] Moffatt | A largescale, consortium-based genomewide association study of asthma[END_REF][START_REF] Sleiman | Variants of DENND1B associated with asthma in children[END_REF][START_REF] Dewan | PDE11A associations with asthma: results of a genome-wide association scan[END_REF][START_REF] Pillai | A genome-wide association study in chronic obstructive pulmonary disease (COPD): identification of two major susceptibility loci[END_REF] nor genes related to smoking behavior [START_REF] Caporaso | Genome-wide and candidate gene association study of cigarette smoking behaviors[END_REF] were associated with lung function decline in our study. The association of FEV1 decline with a gene related to height, DLEU7, was ranking high, but only in subjects without asthma (rs9316500, P discovery =4.8x 10 -6 ; P replication =0.03). DLEU7 gene product and expression remain poorly characterized, but its mRNA has been detected in the lung. The DLEU7 locus was identified as a determinant of adult height in previous GWAS metaanalyses [START_REF] Weedon | Genome-wide association analysis identifies 20 loci that influence adult height[END_REF][START_REF] Sovio | Genetic determinants of height growth assessed longitudinally from infancy to adulthood in the northern Finland birth cohort 1966[END_REF][START_REF] Kang | Genome-wide association of anthropometric traits in African-and African-derived populations[END_REF] . Three other height genes, HHIP, GPR126 and PTCH, were associated with cross-sectional lung function [START_REF] Wilk | A genomewide association study of pulmonary function measures in the Framingham Heart Study[END_REF][START_REF] Hancock | Metaanalyses of genome-wide association studies identify multiple loci associated with pulmonary function[END_REF][START_REF] Repapi | Genome-wide association study identifies five loci associated with lung function[END_REF] . All of these lung function models including ours were adjusted for adult height. The observed association, related to both HHIP and DLEU7 being associated with peak height velocity in infancy [START_REF] Sovio | Genetic determinants of height growth assessed longitudinally from infancy to adulthood in the northern Finland birth cohort 1966[END_REF] , suggests that aspects beyond adult height influence lung function and possibly its response to non-genetic determinants. Several genes implicated in respiratory diseases indicate that early lung development impacts respiratory health later in life [START_REF] Weiss | What genes tell us about the pathogenesis of asthma and chronic obstructive pulmonary disease[END_REF] . Sensitivity analyses are supportive for a growth-specific role of DLEU7. The association of genetic variants in DLEU7 with decline in FEV1 disappeared in analyses considering baseline lung function or restricted to subjects above age 30 with no remaining physiologic lung growth. There might be a link between physiologic growth and unregulated cell differentiation as the DLEU7 gene is also a proposed tumor suppressor gene in chronic lymphocytic leukemia [START_REF] Palamarchuk | 13q14 deletions in CLL involve cooperating tumor suppressors[END_REF][START_REF] Hammarsund | Characterization of a novel B-CLL candidate gene--DLEU7--located in the 13q14 tumor suppressor locus[END_REF][START_REF] Rahmatpanah | Large-scale analysis of DNA methylation in chronic lymphocytic leukemia[END_REF] .

Evidence emerges for a role of DLEU7 in counterbalancing the proliferative impact of NF-kB on various cell types [START_REF] Pekarsky | Molecular basis of CLL[END_REF] . The potential role of the gene product of TUSC3, a proposed tumor suppressor gene [START_REF] Cooke | High-resolution array CGH clarifies events occurring on 8p in carcinogenesis[END_REF] , in lung physiology is discussed in the Online Repository.

None of the SNPs identified in GWAS of cross-sectional lung function [START_REF] Wilk | A genomewide association study of pulmonary function measures in the Framingham Heart Study[END_REF][START_REF] Hancock | Metaanalyses of genome-wide association studies identify multiple loci associated with pulmonary function[END_REF][START_REF] Repapi | Genome-wide association study identifies five loci associated with lung function[END_REF][START_REF] Artigas | Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function[END_REF] ranked high in this current GWAS on lung function decline. A strong risk factor for accelerated lung function decline in adulthood is cigarette smoking, but our study was too small to assess gene smoking interaction at the GWAS level. We had decided a priori against smoking adjustment as it is not a confounder, and any link between genotype and smoking is likely to be, at least in part, in the same causal pathway (e.g. gene products metabolizing tobacco constituents or influencing smoking behavior). Their identification as determinants of lung function decline is of public health importance. Consistent with previous GWAS on cross-sectional lung function [START_REF] Wilk | A genomewide association study of pulmonary function measures in the Framingham Heart Study[END_REF][START_REF] Hancock | Metaanalyses of genome-wide association studies identify multiple loci associated with pulmonary function[END_REF][START_REF] Repapi | Genome-wide association study identifies five loci associated with lung function[END_REF][START_REF] Artigas | Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function[END_REF] , neither the TUSC3 (heterogeneity between ever/never smokers P=0.98) nor other top hit signals were modified by smoking except for SNPs in SYNE2, RORA, BCAS1 and PLXN4. Arguments for biologic plausibility are mentioned in the Online Repository.

The strength of the present study is the longitudinal design of all cohorts included.

Repeated spirometric assessments within the same subject is thought to capture more precisely exogenous factors and genes leading to accelerated loss of lung function in adulthood [START_REF] Wang | Pulmonary function between 6 and 18 years of age[END_REF] . The discovery cohorts shared comparable questionnaire and spirometry protocols and they were specifically designed to investigate environmental and genetic causes of lung function decline and asthma in a standardized way. Each study has two measures of pre-bronchodilator lung function about ten years apart, but clearly our findings would be more robust if further lung function measures were available over an even longer period of follow-up. All discovery cohorts have used the same genotyping platform and stringent quality control criteria have been applied.

Sample size is a limitation of this study, and remains a general challenge in lung function studies with a need for high phenotypic comparability as spirometry results are sensitive to technicians and devices used [START_REF] Kunzli | Variability of FVC and FEV1 due to technician, team, device and subject in an eight centre study: three quality control studies in SAPALDIA. Swiss Study on Air Pollution and Lung Disease in Adults[END_REF] . The pre-bronchodilation lung function measurements in our and previous lung function GWAS do not allow to differentiate reversible from non-reversible obstruction to airflow. Populations included in this study differed by age which is also reflected by the diverging proportion of subjects with FEV1/FVC <0.7 at follow-up between the discovery cohorts. Discovery and replication populations also differ by time spacing between the spirometry assessments. We can only speculate of on the overall impact of such differences. We do note that replication results were sensitive to the exclusion of ARIC data (the study with highest mean age, largest annual decline, and shortest follow-up time).

Other limitations are shared with any GWAS meta-analyses investigating complex phenotypes such as lack in power for investigating gene-environment interactions or studying subgroups of diseases. As the sample size of our study was comparatively small, especially for the asthmatic sample in the replication phase, we had limited ability to address differences in asthma sub-phenotypes or the impact of asthma medication intake. It is also likely that a substantial part of complex disease may be explained by rare mutations not considered by current GWAS. Finally, assessing the joint effect of SNPs having small effects individually and potentially interacting with each other remains another challenge.

In conclusion, this first GWAS meta-analysis on lung function decline provides suggestive evidence for genetic heterogeneity between persons with and without asthma and between cross-sectionally and longitudinally measured lung function.

Consistent with cross-sectional GWAS, our results are also suggestive of height related genes playing a role. Further studies in this area would be enhanced by greater comparability of age range, spacing of lung function assessments, and asthma sub-

  n -Inserm, U1018, CESP Centre for research in Epidemiology and Population Health, Respiratory and environmental epidemiology Team, F-94807, Villejuif, France o -Université Paris Sud, UMRS 1018, F-94807, Villejuif, France p -Centre for Research in Environmental Epidemiology, Barcelona, Spain q -CIBER Epidemiologia y Salúd Publica, Barcelona, Spain r -Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany s -Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina, USA t -Department of Epidemiology and Carolina Center for Genome Sciences, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina, USA u -Cologne Center for Genomics (CCG), University of Cologne, Cologne, Germany. v -Arizona Respiratory Center, University of Arizona, Tucson, AZ, USA w -Department of Medical Genetics, Molecular and Clinical Pharmacology, Division of Genetic Epidemiology, Innsbruck Medical University, Austria x -Commissariat à l'Energie Atomique, Institut de Génomique, Centre National de Génotypage, Evry, France y -National Heart and Lung Institute, Imperial College, London, United Kingdom z -Pulmonary Center, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, USA 1 -The National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, Massachusetts, USA 2 -Division of Population Health Sciences and Education, St George's, University of London, London, United Kingdom 3 -IMIM (Municipal Institute of Medical Research), Barcelona, Spain 4 -National School of Public Health, Athens, Greece Disclosure of potential conflict of interest: Authors declare no conflict of interest. Sources of support: Discovery cohorts: ESE (EGEA-SAPALDIA-ECRHS) EGEA: INSERM-Ministry of Research 'Cohortes et Collections' grant (4CH06G). French Ministry of Higher Education and Research, University Paris Diderot-Paris 7, grants from the French Agency for Environmental and Occupational Health Safety (grant AFSSETAPR-SE-2004), the French National Agency for Research (grants ANR 05-SEST-020-02/05-9-97 and ANR 06-CEBS), PHRC-Paris, Merck Sharp & Dohme (MSD)) SAPALDIA: Swiss National Science Foundation (grants no 4026-28099,3347CO-108796, 3247BO-104283, 3247BO-104288, 3247BO-104284, 32-65896.01,32-59302.99, 32-52720.97, 32-4253.94); the Federal Office for Forest, Environment and Landscape; the Federal Office of Public Health; the Federal Office of Roads and Transport; the canton's government of Aargau, Basel-Stadt, Basel-Land, Geneva, Luzern, Ticino, Zurich; the Swiss Lung League; the canton's Lung League of Basel Stadt/ Basel Landschaft, Geneva, Ticino and Zurich; Freie Akademische Gesellschaft (FAG); UBS Wealth Foundation. ECRHS: The co-ordination of ECRHS II was supported by the European Commission, as part of their Quality of Life programme. The following bodies funded the local studies in ECRHS II: Albacete: Fondo de Investigaciones Santarias (FIS) (grant code: 97/0035-01, 99/0034-01 and 99/0034-02), Hospital Universitario de Albacete, Consejeria de Sanidad; Barcelona: SEPAR, Public Health Service (grant code: R01 HL62633-01), Fondo de Investigaciones Santarias (FIS) (grant code: 97/0035-01, 99/0034-01 and 99/0034-02) CIRIT (grant code: 1999SGR 00241) Red Respira ISCII; CIBER Epidemiologia y Salud Pública (CIBERESP), Spain Basel: Swiss National Science Foundation, Swiss Federal Office for Education & Science, Swiss National Accident Insurance Fund (SUVA), USC NIEHS Center grant 5P30 ES07048; Bergen: Norwegian Research Council, Norwegian Asthma & Allergy Association (NAAF), Glaxo Wellcome AS, Norway Research Fund; Erfurt: GSF-National Research Centre for Environment & Health, Deutsche Forschungsgemeinschaft (DFG) (grant code FR 1526/1-1); Galdakao: Basque Health Dept; Grenoble: Programme Hospitalier de Recherche Clinique-DRC de Grenoble 2000 no. 2610, Ministry of Health, Direction de la Recherche Clinique, CHU de Grenoble, Ministere de l'Emploi et de la Solidarite, Direction Generale de la Sante, Comite des Maladies Respiratoires de l'Isere; Hamburg: GSF-National Reasearch Centre for Environment & Health, Deutsche Forschungsgemeinschaft (DFG) (grant code MA 711/4-1); Ipswich and Norwich: Asthma UK (formerly known as National Asthma Campaign); Huelva: Fondo de Investigaciones Santarias (FIS) (grant code: 97/0035-01, 99/0034-01 and 99/0034-02); Oviedo: Fondo de Investigaciones Santarias (FIS) (grant code: 97/0035-01, 99/0034-01 and 99/0034-02) ; Paris: Ministere de l'Emploi et de la Solidarite, Direction Generale de la Sante, UCB-Pharma (France), Aventis (France), Glaxo France, Programme Hospitalier de Recherche Clinique-DRC de Grenoble 2000 no. 2610, Ministry of Health, Direction de la Recherche Clinique, CHU de Grenoble; Tartu: Estonian Science Foundation; Umeå: Swedish Heart Lung Foundation, Swedish Foundation for Health Care Sciences & Allergy Research, Swedish Asthma & Allergy Foundation, Swedish Cancer & Allergy Foundation; Uppsala: Swedish Heart Lung Foundation, Swedish Foundation for Health Care Sciences & Allergy Research, Swedish Asthma & Allergy Foundation, Swedish Cancer & Allergy Foundation; Financial support for ECRHS I for centres in ECRHS II was provided by: Ministère de la Santé, Glaxo France, Insitut Pneumologique d'Aquitaine, Contrat de Plan Etat-Région Languedoc-Rousillon, CNMATS, CNMRT (90MR/10, 91AF/6), Ministre delegué de la santé, RNSP, France; GSF, and the Bundesminister für Forschung und Technologie, Bonn, Germany; Norwegian Research Council project no. 101422/310; Ministero Sanidad y Consumo FIS (grants #91/0016060/00E-05E and #93/0393), and grants from Hospital General de Albacete, Hospital General Juan Ramón Jiménenz, Consejeria de Sanidad Principado de Asturias, Spain; The Swedish Medical Research Council, the Swedish Heart Lung Foundation, the Swedish Association against Asthma and Allergy; Swiss National Science Foundation grant 4026-28099; National Asthma Campaign, British Lung Foundation, Department of Health, South Thames Regional Health Authority, UK. A.R. was supported by the Department of Health, UK and the European Commission as part of GABRIEL contract number 018996 under the Integrated Program LSH-2004-1.2.5-1.

France) 7 .

 7 constitute the ESE-consortium. Personal factors of relevance to lung function decline were assessed by interview and anthropometric measurements at baseline and follow-up. Participants included in discovery phase were derived from the nested asthma case/control samples (SAPALDIA and ECRHS) or from the entire study population (EGEA) subjected to genome-wide genotyping in the context of the GABRIEL asthma GWAS[START_REF] Moffatt | A largescale, consortium-based genomewide association study of asthma[END_REF] . Baseline and follow-up examination were roughly 10 years apart. The analysis was restricted to adult participants (age ≥18 years at the time of the baseline spirometry) with complete information on age, height and sex as well as valid lung function measure from both surveys. Cohort study protocols were in agreement with the Declaration of Helsinki and obtained ethical approval from their respective regional and/or national review boards.-Lung function assessments, asthma status and genotypes: At each visit, a minimum of two acceptable forced expiratory flows, forced vital capacity (FVC) and forced expiratory volume in the first second (FEV1) complying with American Thoracic Society criteria were obtained[START_REF] Kauffmann | Epidemiological study of the genetics and environment of asthma, bronchial hyperresponsiveness, and atopy: phenotype issues[END_REF][START_REF] Downs | Reduced exposure to PM10 and attenuated age-related decline in lung function[END_REF][START_REF]The European Community Respiratory Health Survey II[END_REF][START_REF]Standardization of Spirometry, 1994 Update[END_REF] . No bronchodilator was administered. Based on questionnaire data, asthmatics were defined as asthma self-report at any of the completed surveys and family-based studies considered additional clinical asthma criteria (see online repository). Genotyping for discovery cohorts was centrally performed on the Illumina Human 610quad BeadChip at the Centre National de Génotypage (CNG, Evry, Imputation of genotypes based on Hapmap2 reference panel, investigation of population stratification and quality control criteria are described in FigureEIand Table EI in the Online Repository.

clustered at position 112. 3

 3 Mb on chromosome 9, containing genes TXN, MUSK and SVEP1. Two of the 15 SNPs were located at 13q14.3 in a locus containing the DLEU7 gene; three SNPs belonged to three distinct loci. The association of lead and proxy SNPs in DLEU7 (Figure II), but not TXN/MUSK/SVEP1 (Figure EII) or the other SNPs (Table

  -7 in asthmatics (Figure I). Regional locus plot and forest plot are presented in the online repository (FigureEIII). The top association signals in this locus were conferred by distinct SNPs in each cohort, though apparently they were located in the same putative haplotype segment in SAPALDIA and in EGEA (Figure EIV, Online Repository). There was no statistically significant association in ECRHS. Meta-analysis of the discovery samples identified SNP rs4831760 as top signal in TUSC3 gene, but heterogeneity between discovery studies was borderline significant (P=0.07). The C-allele (P=5.3x10 -8 ) was positively associated with annual decline in FEV1/FVC in asthmatics (Beta=0.22 ±0.04 (standard error); Table

Figure I :

 I FIGURE LEGENDS:

Figure II :

 II Figure II: Association of the DLEU7 locus with decline in FEV1 in non-asthmatics. A)

Figure 1 Figure 2

 12 Figure 1

  was funded by the GABRIEL asthma genetic consortium supported by a contract from the European Commission (018996) and grants from the French Ministry of Research, the Wellcome Trust (WT084703MA), and Asthma UK.

	Replication cohorts:
	ARIC: The Atherosclerosis Risk in Communities Study is carried out as a collaborative
	study supported by National Heart, Lung, and Blood Institute contracts
	(HHSN268201100005C,	HHSN268201100006C,	HHSN268201100007C,
	HHSN268201100008C,	HHSN268201100009C,	HHSN268201100010C,
	HHSN268201100011C, and HHSN268201100012C), R01HL087641, R01HL59367 and
	R01HL086694; National Human Genome Research Institute contract U01HG004402;
	and National Institutes of Health contract HHSN268200625226C. Infrastructure was
	partly supported by Grant Number UL1RR025005, a component of the National
	Institutes of Health and NIH Roadmap for Medical Research. Work for this manuscript
	was supported, in part, by the Intramural Research Program of the National Institutes of
	Health (NIH), National Institute of Environmental Health Sciences (NIEHS,
	Z01ES043012).
	FHS: National Heart, Lung and Blood Institute's Framingham Heart Study (Contract No.
	N01-HC-25195) and its contract with Affymetrix, Inc for genotyping services (Contract
	No. N02-HL-6-4278). Dr. Wilk by a Young Clinical Scientist Award from the Flight
	Attendant Medical Research Institute (FAMRI). A portion of this research utilized the
	Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans
	Endowment of the Department of Medicine at Boston University School of Medicine and
	Boston Medical Center.

Table EIII ,

 EIII OnlineRepository). Study-specific regression models and meta-analyses across replication cohorts were as described for the discovery phase. Replication cohorts with spirometry data from more than two different time points modelled the lung function decline phenotype by fitting a least-squares slope using the available data (FHS, Dutch asthma study). P≤0.05 was considered as statistically significant at the replication level.The results of the main meta-analyses for the top 1000 SNPs are available in the online

repository (Table

EIV

A to D, Online Repository). We also conducted a meta-analysis by combining non-asthmatic and asthmatic samples and tested for heterogeneity between these samples (Table EV, Online Repository). Additional sensitivity analyses were done by: a) restricting the GWAS sample to subjects aged 30 and older for FEV1 decline (Table

EIV

E and F, Online Repository); b) conducting GWAS analyses on percent change instead of absolute annual decline in lung function (Table EIV G to J, Online Repository); c) investigating smoking stratified joint effects for replications SNPs (Table EVI, Online Repository); d) excluding ARIC, a cohort having substantially shorter followup time that the other cohorts (three years instead of ten years) from replication analyses (Table

EVII

, Online Repository). Methods and results of these additional analyses are described in the online repository.

  , Table EVIII, Online Repository). Baseline lung function parameters, but not their annual changes were lower in asthmatics when compared to non-asthmatics in each study. The proportion of never smokers was comparable among asthmatics, but

varied among non-asthmatics (ranging from 28.5% in B58C to 46.5% in EGEA). No substantial differences in the smoking prevalence between people with and without asthma were observed within each study. Comparing the discovery cohorts in more detail (Table EVIII, Online Repository), atopy (total IgE ≥100kU/ml) and hay fever were more prevalent in both asthmatics and non-asthmatics from EGEA when compared to ECRHS and SAPALDIA. Current asthma was more prevalent (84.4%) in EGEA than in SAPALDIA (25.5%) or ECRHS (43.3%) and the prevalence of a positive family history for asthma was also highest in EGEA, in agreement with the study design. Asthmatics from EGEA had a younger age of disease onset due to the mode of recruitment of the proband.

  Table III and those at P≥0.05 in Table EX in the online repository.

Table II :

 II Association of (lead) SNPs subjected to replication with A) decline in FEV1 and B) decline in FEV1/FVC; stratified by asthma status.

	A -decline in FEV1				Discovery phase			Replication phase
	dbSNP ID	chr	position (build 36.3)	gene nearby	Maximal frequency of coding allele	Estimate of joint analysis	P for joint analysis	P for heterogeneity between studies	P for heterogeneity between asthmatics and non-asthmatics	Estimate of joint analysis in replication cohorts	P for joint analysis	P for heterogeneity between between studies	P for heterogeneity between asthmatics and non-asthmatics
	Non-Asthmatics
	rs1889321	9 112340656	MUSK*	0.287	-0.150	6.95E-07	0.814	0.0187	-0.011	0.480	0.713	0.053
	rs9316500	13		DLEU7	0.336	0.135	4.81E-06	0.613	0.0255	0.033	0.026	0.124	0.075
	rs6785065	3 149016533	ZIC1	0.274	-0.136	0.00001	0.234	0.1700	-0.006	0.686	0.525	0.55
	rs278037	13		UBL3	0.178	-0.151	0.00002	0.364	0.0058	-0.006	0.734	0.231	0.50
	rs7641198	3 117396577	LSAMP	0.147	0.164	0.00003	0.669	0.1997	-0.002	0.939	0.690	0.15
	rs421847	21		PRSS7	0.281	0.128	0.00003	0.831	0.0350	-0.016	0.310	0.247	0.86
	rs496809	18		SALL3	0.078	-0.236	0.00004	0.412	0.0041	0.022	0.443	0.373	0.60
	rs10933964	3 110021881	TRAT1	0.499	-0.117	0.00006	0.345	0.0022	-0.015	0.265	0.869	0.041
	Asthmatics
	rs10808265	7 131840229 PLXNA4B	0.484	-0.175	1.66E-06	0.844	0.0020	0.069	0.105	0.258	0.16
	rs1902618	15		RORA	0.234	-0.220	1.72E-06	0.449	0.0043	0.029	0.590	0.777	0.58
	rs3843306	1		BARHL2	0.460	0.176	5.11E-06	0.042	8.33E-06	0.047	0.270	0.883	0.24
	rs7006290	8		ANK1	0.319	0.185	5.19E-06	0.058	0.0003	0.038	0.456	0.574	0.45
	rs12436689 14		FLRT2	0.244	-0.212	6.87E-06	0.420	0.0010	-0.017	0.759	0.051	0.95
	rs12615721	2		CTNNA2	0.104	-0.303	7.65E-06	0.853	0.0020	-0.127	0.129	0.824	0.08
	rs10516809	4		HERC5	0.101	0.306	8.67E-06	0.790	3.60E-05	-0.060	0.446	0.200	0.41
	rs16856186	1 203944749 SLC45A3	0.098	0.268	8.92E-06	0.510	0.0034	-0.079	0.350	0.094	0.46
	rs158536	20		BCAS1	0.408	0.162	0.00002	0.948	0.0001	0.075	0.100	0.917	0.09
	rs477725	19		ZNF345	0.158	0.223	0.00003	0.821	0.0031	-0.069	0.273	0.255	0.14
	rs9662589	1 230344234	DISC1	0.221	0.188	0.00005	0.868	0.0002	-0.020	0.706	0.153	0.76

Table III :

 III Association* of SNPs previously identified in GWAS on cross-sectional lung function with percent predicted lung function at baseline, as well as percent change and annual decline in lung function for A) FEV1 and B) FEV1/FVC in ESE-discovery cohorts by asthma status.

						Non-Asthmatics			Asthmatics
	B					FEV1 percent predicted	FEV1 percent change	FEV1 decline [%/y]	FEV1 percent predicted	FEV1 percent change	FEV1 decline [%/y]
					Maximal
			position		frequency of
	dbSNP ID	chr	(build 36.3) refs	gene nearby	coding allele	P-value	P-value	P-value	P-value	P-value	P-value
	rs918949		218382942 2,3	TNS1	0.384	0.010	0.133	0.089	0.076	0.241	0.256
	rs1035672 rs929937		218383444 2,3 218417460 2,4	TNS1 TNS1	0.384 0.386	Non-Asthmatics 0.010 0.623	0.133 0.017	0.089 0.016	0.093 Asthmatics 0.004	0.243 0.915	0.258 0.888
	A rs3845823 rs12477314 ‡ 239542085 5 229611365 4	PID1 HDAC4	0.432 0.215	FEV1 percent predicted 0.039 0.023	FEV1 percent change 0.963 0.727	FEV1 decline [%/y] 0.852 0.655	FEV1 percent predicted 0.393 0.125	FEV1 percent change 0.997 0.361	0.987 FEV1 decline [%/y] 0.278
	rs1529672		25495586 5	RARB	Maximal 0.159	0.012	0.329	0.337	0.605	0.716	0.860
	rs1828591		position 145700230 2,3	HHIP	frequency of 0.394	0.031	0.470	0.345	0.254	0.138	0.139
	dbSNP ID rs1435867 rs13118928 145705839 2,3 chr (build 36.3) refs 229219173 2 rs17035917 106740191 2,3 rs3995090 147826008 2,3 rs17035960 106751295 2,3 rs2395730 39892343 3 rs11727735 106851319 2,3 rs2798641 109374743 5 rs10516526 106908353 2,3 rs9496346 142711031 2 rs11731417 106965461 2,3 rs6570507 142721265 2 rs1032295 145654034 2 rs11155242 142733242 2 rs1512285 145670409 rs7753012 142787576 2 rs720485 145682038 2,3 rs3748069 142809326 2 rs1512288 145710731 2,3 rs171891 142892305 2,4 rs6817273 145711453 2,3 rs10512249 97296130 2 rs3008798 39887840 3 rs11172113 12 55813550 5 rs1318002 39892112 3 rs1036429 12 94795559 5 rs2395730 39892343 3 rs2456526 15 50876734 1 rs12899618 15 69432174 3 rs12899618 15 69432174 3 rs1913768 15 69436598 3 rs1913768 15 69436598 3,4 rs1568010 15 69455566 4 rs2304488 16 56631711 1 rs2304488 16 56631711 1 rs12447804 ‡ 16 56632783 5 rs12447804 ‡ 16 56632783 5 rs2865531 ‡ 16 73947817 5	gene nearby PID1 HHIP INTS12-GSTCD-NPNT HTR4 INTS12-GSTCD-NPNT DAAM2 INTS12-GSTCD-NPNT ARMC2 INTS12-GSTCD-NPNT GPR126 INTS12-GSTCD-NPNT GPR126 HHIP GPR126 HHIP GPR126 HHIP GPR126 HHIP GPR126 HHIP PTCH1 DAAM2 LRP1 DAAM2 CCDC38 DAAM2 ONECUT1 THSD4 THSD4 THSD4 THSD4 THSD4 MMP15 MMP15 MMP15 MMP15 CFDP1	coding allele 0.065 0.393 0.071 0.394 0.071 0.442 0.076 0.209 0.072 0.316 0.073 0.314 0.397 0.210 0.462 0.337 0.391 0.319 0.401 0.198 0.400 0.089 0.464 0.384 0.480 0.217 0.442 0.136 0.158 0.158 0.159 0.159 0.372 0.186 0.186 0.179 0.179 0.428	P-value 0.021 0.043 0.011 0.006 0.004 0.277 2.14E-04 0.315 1.96E-04 0.053 1.32E-04 0.035 0.173 0.008 0.032 0.051 0.159 0.043 0.188 0.013 0.179 0.435 0.326 0.005 0.649 0.765 0.522 0.011 0.003 3.25E-04 0.003 4.78E-04 0.535 0.121 0.033 0.121 0.033 0.035	P-value 0.845 0.500 0.785 0.135 0.093 0.554 0.361 0.444 0.327 0.378 0.335 0.356 0.096 0.785 0.029 0.477 0.510 0.407 0.533 0.884 0.535 0.922 0.960 0.602 0.725 0.322 0.716 0.524 0.003 0.253 0.002 0.221 0.042 0.002 0.101 0.003 0.111 0.621	P-value 0.418 0.371 0.699 0.077 0.054 0.685 0.198 0.530 0.177 0.368 0.177 0.342 0.306 0.670 0.141 0.487 0.786 0.401 0.813 0.741 0.816 0.999 0.850 0.530 0.902 0.356 0.513 0.500 0.014 0.390 0.011 0.344 0.067 0.002 0.147 0.003 0.161 0.736	P-value 0.824 0.271 0.029 0.073 0.067 0.979 0.057 0.006 0.062 0.098 0.048 0.080 0.274 0.268 0.152 0.065 0.943 0.134 0.781 0.129 0.866 0.807 0.755 0.809 0.782 0.295 0.619 0.451 0.424 0.328 0.393 0.365 0.413 0.085 0.112 0.085 0.112 0.377	P-value 0.321 0.132 0.649 0.056 0.056 0.036 0.114 0.188 0.120 0.777 0.146 0.804 0.042 0.857 0.033 0.566 0.044 0.604 0.046 0.830 0.046 0.032 0.009 0.114 0.015 0.047 0.003 0.230 0.137 0.596 0.162 0.617 0.241 0.760 0.344 0.719 0.382 0.840	P-value 0.132 0.377 0.456 0.061 0.039 0.063 0.158 0.074 0.788 0.078 0.821 0.090 0.807 0.033 0.637 0.024 0.628 0.058 0.815 0.057 0.028 0.057 0.125 0.017 0.031 0.023 0.250 0.007 0.668 0.131 0.695 0.152 0.515 0.111 0.487 0.506 0.482 0.603

ACKNOWLEDGMENTS

EGEA: We thank the EGEA cooperative group: Coordination: F Kauffmann; F Demenais (genetics); I Pin (clinical aspects). Respiratory epidemiology : Inserm U 700, Paris M Korobaeff (Egea1), F Neukirch (Egea1); Inserm U707, Paris : I Annesi-Maesano ; Inserm CESP/U 1018, Villejuif : F Kauffmann, N LeMoual, R Nadif, MP Oryszczyn ; Inserm U 823, Grenoble : V Siroux Genetics : Inserm U 393, Paris : J Feingold ; Inserm U 946, Paris : E Bouzigon , F Demenais, MH Dizier ; CNG, Evry : I Gut , M Lathrop. Clinical centers : Grenoble : I Pin, C Pison; Lyon : D Ecochard Juvenile Diabetes Research Foundation International, the Wellcome Trust and the National Institute for Health Research Cambridge Biomedical Research Centre; the CIMR is in receipt of a Wellcome Trust Strategic Award (079895). The B58C-GABRIEL genotyping was supported by a contract from the European Commission Framework Programme 6 (018996) and grants from the French Ministry of Research.

British 1958 Birth Cohort was funded by the Medical Research Council grant G0000934 and the Wellcome Trust grant 068545/Z/02 (http://www.b58cgene.sgul.ac.uk/). Genotyping was funded by the Wellcome Trust grant 076113/B/04/Z, by the United States National Institutes of Health and the Juvenile Diabetes Research Foundation U01 DK062418 and by the European Commission Framework Programme 6 (018996). Dutch Asthma Study: The Dutch Asthma study has been funded by the Netherlands Asthma Foundation grants AF 3.2.07.015; and AF 98.48 and a grant from the University Medical Center Groningen

FOOTNOTES

Footnotes to Table I:

* N comprises the maximal number of subjects who contributed to at least one GWAS analysis (either decline in FEV1 or in FEV1/FVC). †Time spacing between the first and the second spirometry assessment.

Footnote to Table II:

* MUSK refers to TXN/MUSK/SVEP1 locus.

Footnote to