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Description of studies in discovery and replication study
Methodological consideration related to genome-wide interaction studies
In utero smoke exposure GWIS - Details on the 27 SNPs in the discovery sample with a Pvalue<10-4
Childhood tobacco smoke exposure GWIS - details on the 31 SNPs in the discovery sample with a
Data from nine individual studies were included in two meta-analyses: a meta-analysis on the
interaction between single nucleotide polymorphisms (SNPs) and in utero smoke exposure and a
meta-analysis on the interaction between SNPs and childhood smoke exposure (Table E1, Online
Repository). All cases and controls were of European descent and two studies had a family structure.
We focused on childhood onset asthma, because this disease has a strong genetic background
interacting with environmental exposures. Childhood onset asthma was defined as asthma diagnosed
by a doctor before the age of 16 years, which is consistent with the definition in the GABRIEL
consortiumE1. In utero tobacco smoke exposure was defined as ‘exposure to maternal tobacco
smoking at any time during pregnancy’. Childhood tobacco smoke exposure was defined as ‘exposure
to passive tobacco smoking at any time from birth until 16 years of age’. Details on the outcome and
exposure definition for the individual studies are provided in the Tables E1 to E4 (Online Repository).
Genotyping and quality control
Genotyping was carried out using the Illumina Human610 quad array ( at CEACentre National de Génotypage, Evry, France. Details on the genotyping method have been described
previously.E1 We restricted our meta-analyses to SNPs fulfilling the following quality control criteria in
each study: genotype missing rate <3% in cases and controls, minor allele frequency >5% in controls
and consistency with Hardy-Weinberg equilibrium in controls (P-value>10-4). Samples were
considered with >95% genotyping success rate. We excluded putative non-European samples,
identified using EIGENSTRAT2.0 software.
Statistical analyses
The effects of in utero tobacco smoke exposure and childhood tobacco smoke exposure were
analyzed separately. All individual studies were analyzed using a logistic regression model containing
the genetic effect, the effect of tobacco smoke exposure and an interaction term indicating the
interaction between the genetic effect and tobacco smoke exposure. This way deviation from a
multiplicative model is tested. Gender, age and informative principal components for within-Europe
diversity were included as covariates. For the studies containing family data, a cluster variable
indicating the family relations was included. An additive genetic model was fitted to the data. For the
discovery meta-analysis, we meta-analyzed the estimate of the interaction term of the individual
studies. We calculated pooled interaction odds ratios (ORint) and 95% confidence intervals (CI)
assuming a fixed effect model and a random effect model. A test for heterogeneity between studies
was based on the Cochran’s Q statistic. We selected SNPs with an interaction P-value <10-4 based on
the fixed effect model, and without heterogeneity (P-value Q-statistic <0.05) for follow-up in a
replication set. Genome-wide significance would be reached at a P-value <9.3*10-8 with the number of
SNPs tested. Our threshold for further follow-up was an arbitrary chosen P-value of <10-4 based on
the number of SNPs meeting that threshold to select SNPs for the replication study. The selected
SNPs were tested in a replication study consisting of four independent studies (Description of studies
see Tables E1 to E4, Online Repository) and we meta-analyzed these in the combined set of
discovery and replication cohorts as well. The effect of the selected SNPs among exposed and
unexposed separately was also calculated in a stratified analysis. Analyses were conducted using
Plink 1.07E2 and RE3. For annotation and inspection of linkage disequilibrium (LD) patterns
WGAviewerE4 was used. A network analyses was performed for the SNPs with the largest interaction
effect using GeneMANIA algorithm ( to inspect a possible common pathway.
Description of studies in discovery and replication study
British 1958 birth cohort (B58C)
The 1958 British birth cohort is an ongoing follow-up of persons born in Britain during one week in
1958 ( At age 44-45, a full biomedical examination was performed
from which DNA samples were prepared for use as a nationally representative reference series for
genetic case-control studies.E5 About half of the cohort members with a history of asthma ascertained
at any age up to 42 years, and a similar number of non-asthmatic controls, were included in the
GABRIEL meta-analysisE1. For the purpose of this interaction analysis, childhood asthmatics were
defined as persons reporting asthma ever at any follow-up whose parents also reported that they had
asthma and/or wheezy bronchitis at any age up to and including 16 years. Maternal smoking after the
fourth month of pregnancy was ascertained by interview with a midwife shortly after birth. Postnatal
smoke exposure was ascertained from interview questions about maternal smoking and paternal
smoking, administered at the 16-year follow-up.
The Avon Longitudinal Study of Parents and Children (ALSPAC) is a population-based, birth cohort
recruited during pregnancy. Pregnant women resident in Avon, United Kingdom with estimated dates
of delivery between 1st April 1991 and 31st December 1992 were recruited through antenatal clinics. E6
From 14,451 women recruited, there were 14,072 live births and 13,988 children were alive at age one
year. Children were followed from birth using self-completion questionnaires sent to their mothers at
approximately annual intervals and, from 7 years of age, in yearly dedicated research clinics. Asthma
is defined as an affirmative answer to a question at 91 months (approximately 7½ years), “Has a
doctor ever told you that your child had asthma?” Data on passive smoke exposure in utero was
collected from questionnaires sent to mothers during pregnancy at 18 weeks gestation. Postnatal
exposure was derived from two questionnaires sent to mothers 5 or 6 times between 6 months and 78
months after birth. In utero smoke exposure was defined as “The mother smoked regularly in first 3
months of pregnancy (>1 cig/day)”. Childhood smoke exposure was defined as a positive response at
any time to “The mother smokes regularly (>1 cigs/day currently smoked)” or “The child is exposed to
a room or enclosed place where people are smoking during weekdays or weekends”. A total of 3,030
children had DNA available for genotyping and data on asthma at 91 months as well as other asthma
related phenotypes. Of these, 625 (20.6%) had asthma and an equal number of controls was selected
at random from the remainder. After ALSPAC-QC a total of 1,139 subjects were retained in the GWI
study analysis on in utero smoke exposure and 1,025 subjects were retained in the GWI study
analysis on childhood smoke exposure.
Between 1994 and 1996, 4,089 newborn infants were recruited in the BAMSE study, and
questionnaire data on baseline study characteristics were obtained.E7The catchment area included
central and north-western parts of Stockholm. At approximately one, two, four, and eight years of age,
parents completed questionnaires on their children’s symptoms related to asthma and other allergic
diseases. The response rates were 96%, 94%, 92% and 84%, respectively. At eight years of age, all
children of the BAMSE study were invited to clinical testing where blood samples were obtained from
2,480 children. DNA was extracted from 2,033 samples after exclusion of samples with too little blood,
lack of questionnaire data, or if parental consent to genetic analysis of the sample was not obtained.
From these samples, all children with a doctor’s diagnosis of asthma (ever) were selected as cases
and children with no history of asthma or other allergic diseases were selected as controls. Data on
passive smoke exposure was collected from repeated questionnaires filled out by parents. In utero
smoke exposure was defined as “The mother smoked at least one cigarette per day in any point of
time during the pregnancy” as reported in the baseline questionnaire at approximately 2 months.
Childhood smoke exposure was defined as “Any of the parents smoked at least one cigarette per day”
at the time of any questionnaire, distributed at 2 months, 1, 2, 4 and 8 years. After genome-wide data
QC and exclusion of subjects with missing values on smoke exposure a total of 484 subjects were
retained in the GWI study analyses.
Sixteen centres (eight countries) in the European Community Respiratory Health Survey (ECRHS)
have contributed samples to GABRIEL (,E9 In each centre, a representative
community-based sample of at least 3000 adults aged 20-44 years were invited to complete a brief
postal questionnaire asking about respiratory symptoms (ECRHS I - Stage 1) between 1991-1993. A
random sample of these (600 per centre) underwent intensive further investigation (ECRHS I - Stage 2
– random sample). Participants who had symptoms highly suggestive of asthma but who had not been
selected at random to take part in Stage 2, were also invited to undergo intensive investigations
(ECRHS I - Stage 2- enriched sample). About ten years later all adults who had taken part in Stage 2
were recontacted (ECRHS II) and again asked about respiratory symptoms. Samples suitable for DNA
extraction were collected. For the GABRIEL initiative all cases of asthma were identified (participants
from the random or enriched sample who said yes to the question „Have you ever had asthma? at
either ECRHS I or ECRHS II). Controls were a random sample who answered “no to the same
question in both surveys”. In utero smoke exposure was defined as any smoking by the mother during
pregnancy. Childhood smoke exposure was defined as either mother or father smoked regularly
during childhood (ECRHS1 main questionnaire).
EGEA is a 12-year longitudinal survey which combines a case-control study and a family study
( The first survey (EGEA1) took place between 1992 and 1995.E10
The study population included 388 asthmatics recruited in chest clinics and their 1,244 family
members plus 415 population-based controls (total of 2,047 subjects). The probands (asthmatics and
controls) were between 7 and 70 years old at time of study. All probands and their two parents were of
European ancestry and were born in France. The second survey (EGEA2) was conducted between
2003 and 2007 and included follow-up data in 1,543 subjects from the initial cohort and 58 new family
members.E11 Data collected through face-to-face interviews and examination included extensive
phenotypic characterization (detailed clinical data based on standardized questionnaire, skin prick
tests, lung function tests, bronchial responsiveness, blood samples, white blood cell counts, total IgE),
data on risk factors (environmental exposures, diet, physical activity, hormone-related events) and
drug consumption. For the GABRIEL initiative, asthma was defined by a positive answer to the
question "Have you ever had asthma attack "at EGEA1 (or at EGEA2 if not examined at EGEA1). In
utero smoke exposure was defined in adults as an affirmative answer on the question “When your
mother was pregnant, in particular with you, did she stop smoking during pregnancy?” Childhood
smoke exposure was defined as an affirmative answer on either question “Did your mother ever
smoke during your childhood (before 16 years old)?” or “Did your father ever smoke during your
childhood?” (for adults) and “Did his/her mother ever smoke when he/she was younger than 2 years?”
or “Did his/her father ever smoke when he/she was younger than 2 years?” or “Did his/her father or
mother or someone smoke in the household at the time of the questionnaire in EGEA1?” (for children).
The GABRIELA study was carried out as a population survey in five rural regions of Europe: BadenWürttemberg and Bavaria in Germany, North/Central Switzerland, Tyrol in Austria, and Lower Silesia
in Poland. The Polish center was not included in the GWI study analysis. Children aged 5-13 years
were recruited through primary schools. A recruitment questionnaire was sent out to 132,366 children,
of whom 79,888 (60.4%) returned their completed questionnaires (phase 1), containing questions on
asthma. Of these children, 34,491 were eligible for phase 2 as defined by a documented parental
consent to dust sampling, blood sampling, and genetic analyses and nationality of their study country.
To enrich informative observations a stratified random selection process was applied in two steps. In a
first step, 9,668 children were selected for phase 2 within the three exposure strata per center. In the
second step, 1,708 children were selected for genotyping within exposure and outcome strata per
center. In utero smoke exposure was defined as any smoking by the mother during pregnancy.
Childhood smoke exposure was defined as current smoking by the father or the mother. Details on the
study design are described in: Genuneit J et al., The GABRIEL Advanced Surveys: study design,
participation, and evaluation of bias.E12
The PIAMA study is a birth cohort study of children born between 1996-1997. Details of the study
design have been published previously.E13 10,232 pregnant women completed a validated screening
questionnaire at their prenatal health care clinic (n=52). Based on this screening, 7,862 women were
invited to participate, of whom 4,146 women agreed and gave informed consent. Mothers reporting a
history of asthma, current hay fever or allergy to pets or house dust mite were defined as allergic.
Children were recruited during the first trimester of pregnancy. Follow-up of the children took place at
3 months of age and yearly from 1 to 8 years of age. At eight years of age, all children were invited to
clinical testing including collection of blood samples for DNA extraction. The Medical Ethical
Committees of the participating institutes approved the study, and all participants gave written
informed consent. The response rates to the annual questionnaires ranged from 3764 at age 1 to
3269 at age 8 years. For the GWI study, DNA from childhood asthma cases (children who have ever
had a doctor’s diagnosis of asthma at age 8 years) and a set of non-asthmatic controls (children who
never had a doctor’s diagnosis of asthma and who have never wheezed at age 8 years) were
provided. In utero smoke exposure was defined as any smoking by the mother during pregnancy from
week 4 of pregnancy. Childhood smoke exposure was defined as any smoking by the father or the
mother inside the house between the child’s birth and 8 years of age.
SAPALDIA contributed all self-reported asthma cases as well as a random sample of controls. These
subjects were obtained from among 6,055 SAPALDIA cohort subjects that participated in both, the
baseline (1991) and follow-up (2002) examinations and agreed to providing blood for genetic analysis.
SAPALDIA is a population-based cohort that originally recruited subjects aged 18 to 60 from
population registries in eight Swiss communities representing the three largest language groups
(German, French, Italian) as well as different levels of air pollution, altitude and degrees of
urbanization. At both baseline and follow-up examination subjects underwent spirometry as well as a
detailed interview on respiratory health, smoking history and lifestyle factors. At follow-up, 8,047 of
9,651 baseline subjects re-participated in at least one part of the study and a formal biobank was
established. SAPALDIA questions about smoking and asthma status were equivalent to those used by
the ECRHS. Asthma status was defined by an affirmative answer to the question “Have you ever had
asthma” at baseline and/or follow-up interview. Childhood smoke exposure was defined as positive
answer to either of the questions “Did your father regularly smoke when you were a child?” or “Did
your mother regularly smoke when you were a child?”. In utero smoke exposure was present when the
person’s mother either continuously smoked, or reduced or stopped smoking during pregnancy.
Exposure during pregnancy was asked upon affirmatively answering the question on regular smoking
of the mother during the person’s childhood.
TOMSK is a population-based family study conducted by the Research Institute of Medical Genetics
and Siberian State Medical University (Tomsk, Russia) from 1998 onwards. E14 Both nuclear families
and extended pedigrees were recruited through atopic bronchial asthmatic probands. All participants
were Russians or of a mixed ethnic origin due to marriages between Russians and major East
Slavonic populations (Ukrainians, Byelorussians). Altogether, 196 families were studied, out of which
150 families were recruited in Tomsk Region Children Hospital and Tomsk Region Hospital (Tomsk,
Russia), and 46 families were recruited in the city of Irkutsk hospitals by the staff of the Irkutsk State
Institute of Doctors Advanced Training (Irkutsk, Russia). Both probands and their relatives were
clinically examined to establish diagnosis of asthma and atopy by the GINA criteria (Global Initiative
for Asthma: Global Strategy for Asthma Management and Prevention.
Besides the clinical examination, laboratory and functional testing were conducted to assess common
IgE levels (solid-phase immune-enzyme assay), specific sensitization (skin-prick tests), lung volumes
(spirometry), and airway responsiveness (bronchoprovocative tests with methacholine). For the GWI
study analysis, only children were included. Childhood smoke exposure was defined as an affirmative
answer to the question “Are you currently exposed to passive smoking?”.
Canadian Childhood Cohorts: CAPPS & SAGE
CAPPS was initiated in 1995 to assess the effectiveness of a multifaceted intervention program on the
primary prevention of asthma in high-risk infants. Full details have been previously publishedE15 and
are available at Infants at high risk for developing asthma and other allergic
disorders were identified and their mothers were recruited during their third trimester of pregnancy.
Infants at high risk were defined as those who had a parent with asthma or two first-degree relatives
with allergies or atopic disorders. The study had two recruitment centers in Canada, (Vancouver and
Winnipeg). In total, there were 545 families recruited into the study (549 infants, 4 sets of twins). Loss
to follow-up was minimal, with 86% of the families completing the questionnaire at the 7-year time
point. For genetic analysis blood samples have been obtained from the children, and both parents.
The Ethics Committees of the University of British Columbia and the University of Manitoba approved
the study and parents provided written informed consent for participation.
Childhood smoking exposure was measured in prospective manner by questionnaires administered to
both parents (mother and father) at 7 time-points (prenatally, 2 weeks, 4, 8, and 12 months of life, and
at age 2 and 7 years), home visits were conducted and exposure was confirmed by urine cotinine.
Specific questions, full questionnaires, and timeline for administration of questionnaires can be found
at, smoking questions were asked of
both parents and parents were asked if visitors were allowed to smoke in the home. If a child was
exposed during pregnancy they were considered exposed prenatally, if they were exposed at anytime
during the follow-up period (first 7 years of life) they were considered exposed during childhood for this
SAGE is a population-based sample of 16,320 children, born in the province of Manitoba, Canada in
the year of 1995. The SAGE study design has been previously described in detail. E16 In 2002, a onepage survey was mailed to families to enquire about their health and home environment exposure.
Questions included several chronic conditions in childhood, including hay fever, food allergy and
asthma. Parents were asked for permission to be contacted for further study and to link the survey
data to their child’s health care database records. Children were stratified according to the presence of
asthma (n=392), to the presence of hay fever or food allergy (n=192) and neither (n=3,002). Children
with neither condition were further grouped by rural and urban location; the latter were further stratified
by low and high income neighborhoods. All children in the asthma and allergy strata were invited to
participate in the case-control study, as were a random sample (n=200) from the strata of children with
neither condition. Childhood smoking exposure was measured retrospectively by questionnaires to
both parents (mother and father) when the child was age 7 to 9 (depending on enrollment date).
Questions were asked about smoking exposure during pregnancy and after birth to current age (7 to 9
depending on enrollment date) Specific questions, full questionnaires, and timeline for administration
of questionnaires can be found at If a
child was exposed during pregnancy they were considered exposed for the prenatal analysis, if they
were exposed at any time after birth they were considered exposed during childhood for this analysis.
The LifeLines cohort is a three-generation cohort that is designed to investigate universal risk factors
and their modifiers for multifactorial diseases.E17 It is an observational follow-up study in a large
representative sample of the population of the northern provinces of the Netherlands. Firstly, a random
sample of persons aged between 25 and 50 years are contacted through their general practitioner and
are invited to participate. Subsequently these probands invite their family members if present to take
part as well (parents, partner, parents in law, children), resulting in a three-generation study. At
enrollment subjects undergo a medical examination where blood sample is collected for DNA
extraction. Participants filled in a questionnaire at baseline containing a question on whether they ever
had asthma, whether the diagnosis has been confirmed by a physician and what was the age of onset.
Exposure to maternal smoking during pregnancy was defined as any smoking by the mother during
pregnancy. Exposure to passive smoking was defined as any regular smoking by the father or the
mother during childhood. Genotyping of 301,232 SNPs was performed with using Illumina
HumanCytoSNP-12v2 array. Samples for 13,301 individuals were genotyped and passed QC. The
data was imputed by BEAGLE 3.0. For the analyses on exposure to maternal smoking during
pregnancy, 22 of 27 SNPs were successfully imputed and included in the replication study. For the
analyses on passive smoking, 25 of 31 SNPs were successfully imputed and included in the
replication study.
The MAS/ISAAC study is a combination of the MAS cohort, which contained only asthma cases and
the ISAAC cohort, from which we only included the controls. The MAS and ISAAC cohort are both
multi centre studies and consist of subjects from Germany. We inspected MDS plots for these cohorts
and did not observe population stratification. Not all SNPs selected for the replication study could be
included in the replication study, because ISAAC subjects were genotyped using a different platform
(GABRIEL phase I) than the other GABRIEL cohorts (GABRIEL phase II). For the GWI study on
exposure to maternal smoking during pregnancy, 16 of the 27 SNPs selected for replication could be
included in the replication study. For the GWI study on exposure to passive smoking during childhood,
16 of the 31 SNPs selected for replication could be in the replication study. MAS consists of 1,314
healthy mature children born in 5 German cities in the year 1990.E18 All children were followed at the
age of 1, 3, 6, 12, 18, and 24 months and at yearly intervals thereafter until age 15 years. Clinical and
environmental assessment included standardized interviews, questionnaires, physical examinations,
and environmental studies. DNAs from all children with a doctor diagnosis of asthma (ever) or with
wheezing/whistling in the chest and the use of asthma medication in the previous 12 months at any
time point during follow-up were provided for the GWIS. In utero smoke exposure was defined as any
smoking by the mother during pregnancy. Childhood smoke exposure was defined as any smoking at
the child’s home or as the child’s exposure to a smoky room elsewhere up to 9 years of age.
The ISAAC study assessed the prevalence of asthma and allergies in schoolchildren and the asthma
status was based on the parent’s report of a physician’s diagnosis of asthma at least once, or of
spastic or asthmatic bronchitis more than once in self-administered questionnaires. Written informed
consent was obtained from all parents of children included in these studies and study methods were
approved by the respective ethics committees. All children were of German origin to control for
population admixture. We only used control subjects from the ISAAC study. Data on smoke exposure
was collected when the children were between 8 and 12 years of age. In utero smoke exposure was
defined as an affirmative answer to the category “during pregnancy” in the question “Does or did the
mother of the child smoke?”. Childhood smoke exposure was defined as an affirmative answer to one
of the following questions “Is there smoking in the dwelling your child lives in?” or “Did/does the
mother smoke?”.
Methodological consideration related to genome-wide interaction studies
A general problem in GWI studies is their limited power, due to often a small number of subjects with
overlapping exposures and genotypes. In our study, only about 15% of the asthma cases were
exposed to tobacco smoke in utero resulting in less than 100 exposed cases in most individual studies
(Table E1, Online Repository). A way to increase the power to detect an interaction is to assess the
association between exposure and genotype in a case-only design or a two-step design.E19, E20 These
designs assume that exposure and genotype are independent. We chose not to use these designs
given the known strong genetic component for smoking addiction. Relative modest violations of this
assumption can have a substantial impact on bias relating to the interaction parameters, E21 and lead
to false positive or false negative findings. E22 In a two-step design the interaction is tested among a
selection of SNPs. This selection is based on the same assumption that exposure and genotype are
independent. The method we used to detect interactions between exposure and genotype did not
assume exposure and genotype independence nor did we a priori select SNPs. To increase the power
of our analysis we first selected the most promising SNPs using an arbitrary threshold for interaction
<10-4 and included them in a replication study. A similar approach has been used recently in a GWI
study on interaction between genetic markers and waist hip ratio on total serum cholesterol. E23
Another difficulty with combining multiple studies by meta-analysis is the difference in exposure and
outcome definition between studies. The studies included in this GWI study differed in definition of
smoke exposure and childhood asthma, the timing of the ascertainment of exposure and outcome (for
instance prenatal or postnatal data collection on maternal smoking) and methods (questionnaire or
interview). These differences between individual studies are inevitable in a meta-analysis and
although they may not bias the results, they could create random error which makes it harder to detect
a significant interaction. E24 In addition, due to retrospectively self-reported or parental reported
passive smoke exposure children may have been misclassified according to their passive smoke
exposure leading to an underestimation of the exposure effect.
A GWI study has the advantage that it is specifically suited to identify novel SNPs that interact with an
environmental exposure in an unbiased way. In contrast to a GWI approach, a GWA approach will not
identify modest genetic effects that evolve into disease expression only in the presence of a given
exposure, or even after overriding a specific threshold of this exposure. Large interaction effect
estimates, as observed in our GWI study, are due to the fact that the genetic effect in exposed versus
non-exposed subjects is often in opposite direction. As a result, the effect of the genetic variant is
attenuated in the total population when exposed and non-exposed subjects are analyzed together, like
in a regular GWA study. Thus genetic effects may be missed in GWA studies because exposed and
non-exposed subjects level out their opposite genetic effects.
In utero smoke exposure GWIS - Details on the 27 SNPs in the discovery sample with a Pvalue<10-4
We included 27 SNPs in the replication study. None of the interaction of SNPs with in utero tobacco
smoke exposure reached statistical significance in the replication study after Bonferroni correction for
multiple testing (0.05/27). Three SNPs had a P-value <0.05 based on the fixed effect model, but for
rs14398 the interaction was in opposite direction in the replication study as in the discovery study. The
largest interaction effect was observed for rs8094633 (discovery meta-analysis: ORint=2.13,
95%CI=1.48;3.06, P-value=4.29*10-5; replication meta-analysis: ORint=2.87, 95%CI=1.09;7.58, Pvalue=0.03) (Table 1). There was no sign of heterogeneity of effects for this SNP and the overall
interaction estimate (when all studies were combined) was: ORint=2.21, P-value=4.67*10-6 (Table E5,
Online Repository). In subjects with in utero tobacco smoke exposure, carriers of the minor allele C
had an increased risk for asthma (OR=1.72, P-value=0.001) while in non-exposed subjects, carriers of
the C allele had no increased asthma risk (OR=0.89, P-value=0.05) (Table E5, Online Repository).
Leukocytes of smoking subjects express higher EPB41L3 mRNA levels than non-smoking subjectsE25
and modest evidence for association of EPB41L3 gene variants with tobacco smoking habits has been
reported.E26 In our data, this SNP was not associated with in utero tobacco smoke exposure or
childhood tobacco smoke exposure itself. Therefore the observed interaction is not likely to be
explained by smoking addiction of the mother (data not shown). Another interesting SNP that
interacted with in utero tobacco smoke exposure in the discovery meta-analysis, but could not be
replicated is the SNP near IL5RA (interleukin 5 receptor subunit alpha). IL5Ralpha and IL5Rbeta
together constitute the receptor for IL5. IL5RA is amongst others expressed on eosinophils and B-cells
and plays an important role in the pathogenesis of allergy and asthma. E27,E28 Polymorphisms in IL5RA
have been associated with allergy.E29,E30 The latter studies investigated different SNPs which are not
in LD with the marker we found.
Childhood tobacco smoke exposure GWIS - details on the 31 SNPs in the discovery sample
with a P-value<10-4
We included 31 SNPs in the replication study. None of the interactions of SNPs with childhood
tobacco smoke exposure reached statistical significance in the replication study after Bonferroni
correction for multiple testing (0.05/31). The largest interaction effect was found for rs1575472
(discovery meta-analysis: ORint=1.78, 95%CI=1.37;2.31, P=1.37*10-5; replication meta-analysis:
ORint=1.51, 95%CI=0.99;2.31, P=0.06) (Table 2). The overall interaction estimate (when all studies
were combined) was: ORint=1.70, P-value=2.52*10-6 (Table E6, Online Repository). In subjects with
childhood tobacco smoke exposure, carriers of the minor allele G had an increased risk for asthma
(OR=1.21, P-value=2.72*10-3), while in non-exposed subjects, carriers of the G allele had a decreased
asthma risk (OR=0.73, P-value=1.46*10-4) (Table E6, Online Repository). The SNP rs1575472 is
located on chromosome 6, intronic of PACRG, parkin co-regulated gene.
Moffatt MF, Gut IG, Demenais F, et al. A large-scale, consortium-based genomewide
association study of asthma. N Engl J Med 2010; 363(13): 1211-21.
Purcell S, Neale B, Todd-Brown K, et al. PLINK: a tool set for whole-genome association and
population-based linkage analyses. Am J Hum Genet 2007;
81(3): 559-75.
R Development Core Team. R Foundation for Statistical Computing. R: A Language and
Environment for Statistical Computing. 2011; .
Ge D, Zhang K, Need AC, et al. WGAViewer: software for genomic annotation of whole genome
association studies. WGAviewer Dongliang Ge & David B. Goldstein Genome Res 2008; 18(4): 640-3.
Strachan DP, Rudnicka AR, Power C, et al. Lifecourse influences on health among British
adults: effects of region of residence in childhood and adulthood. Int J Epidemiol 2007; 36(3): 522-31.
Golding J, Pembrey M, Jones R. ALSPAC--the Avon Longitudinal Study of Parents and
Children. I. Study methodology. Paediatr Perinat Epidemiol 2001; 15(0269-5022; 1): 74-87.
Kull I, Melen E, Alm J, et al. Breast-feeding in relation to asthma, lung function, and
sensitization in young schoolchildren. J Allergy Clin Immunol 2010; 125(5): 1013-9.
Burney PG, Luczynska C, Chinn S, Jarvis D. The European Community Respiratory Health
Survey. Eur Respir J 1994; 7(5): 954-60.
The European Community Respiratory Health Survey II. Eur.Respir.J. 2002; 20(5): 1071-9.
Kauffmann F, Dizier MH, Annesi-Maesano I, et al. EGEA (Epidemiological study on the
Genetics and Environment of Asthma, bronchial hyperresponsiveness and atopy)-- descriptive
characteristics. Clin Exp Allergy 1999; 29 Suppl 4: 17-21.
Siroux V, Boudier A, Bousquet J, et al. Phenotypic determinants of uncontrolled asthma. J
Allergy Clin Immunol 2009; 124(4): 681,7.e3.
Genuneit J, Buchele G, Waser M, et al. The GABRIEL Advanced Surveys: study design,
participation and evaluation of bias. Paediatr Perinat Epidemiol 2011; 25(5): 436-47.
Brunekreef B, Smit J, de Jongste J, et al. The prevention and incidence of asthma and mite
allergy (PIAMA) birth cohort study: design and first results. Pediatr Allergy Immunol 2002; 13 Suppl
15(0905-6157): 55-60.
Freidin MB, Kobyakova OS, Ogorodova LM, Puzyrev VP. Association of polymorphisms in the
human IL4 and IL5 genes with atopic bronchial asthma and severity of the disease. Comp Funct
Genomics 2003; 4(3): 346-50.
Daley D, Lemire M, Akhabir L, et al. Analyses of associations with asthma in four asthma
population samples from Canada and Australia. Hum Genet 2009; 125(4): 445-59.
Kozyrskyj AL, HayGlass KT, Sandford AJ, Pare PD, Chan-Yeung M, Becker AB. A novel study
design to investigate the early-life origins of asthma in children (SAGE study). Allergy 2009; 64(8):
Stolk RP, Rosmalen JG, Postma DS, et al. Universal risk factors for multifactorial diseases:
LifeLines: a three-generation population-based study. Eur J Epidemiol 2008; 23(1): 67-74.
Lau S, Nickel R, Niggemann B, et al. The development of childhood asthma: lessons from the
German Multicentre Allergy Study (MAS). Paediatr Respir Rev 2002; 3(3): 265-72.
Mukherjee B, Ahn J, Gruber SB, Chatterjee N. Testing gene-environment interaction in large-
scale case-control association studies: possible choices and comparisons. Am J Epidemiol 2012;
175(3): 177-90.
Ege MJ, Strachan DP, Cookson WO, et al. Gene-environment interaction for childhood asthma
and exposure to farming in Central Europe. J Allergy Clin Immunol 2011; 127(1): 138,44, 144.e1-4.
Hunter DJ. Gene-environment interactions in human diseases. Nat Rev Genet 2005; 6(4):
Liu X, Fallin MD, Kao WH. Genetic dissection methods: designs used for tests of gene-
environment interaction. Curr Opin Genet Dev 2004; 14(3): 241-5.
Surakka I, Isaacs A, Karssen LC, et al. A genome-wide screen for interactions reveals a new
locus on 4p15 modifying the effect of waist-to-hip ratio on total cholesterol. PLoS Genet 2011; 7(10):
Bookman EB, McAllister K, Gillanders E, et al. Gene-environment interplay in common
complex diseases: forging an integrative model-recommendations from an NIH workshop. Genet
Epidemiol 2011; .
Charlesworth JC, Curran JE, Johnson MP, et al. Transcriptomic epidemiology of smoking: the
effect of smoking on gene expression in lymphocytes. BMC Med Genomics 2010; 3: 29.
Uhl GR, Drgon T, Johnson C, Ramoni MF, Behm FM, Rose JE. Genome-wide association for
smoking cessation success in a trial of precessation nicotine replacement. Mol Med 2010; 16(11-12):
Gorski P, Wittczak T, Walusiak J, Palczynski C, Ruta U, Kuna P, Alam R. Eotaxin but not
MCP-3 induces eosinophil influx into nasal fluid in allergic patients. Allergy 2002; 57(6): 519-28.
Yasruel Z, Humbert M, Kotsimbos TC, et al. Membrane-bound and soluble alpha IL-5 receptor
mRNA in the bronchial mucosa of atopic and nonatopic asthmatics. Am J Respir Crit Care Med 1997;
155(4): 1413-8.
Cheong HS, Kim LH, Park BL, et al. Association analysis of interleukin 5 receptor alpha
subunit (IL5RA) polymorphisms and asthma. J Hum Genet 2005; 50(12): 628-34.
Kabesch M, Depner M, Dahmen I, et al. Polymorphisms in eosinophil pathway genes, asthma
and atopy. Allergy 2007; 62(4): 423-8.
We are extremely grateful to all the families who took part in the study, the midwives for their help in
recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory
technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. The
UK Medical Research Council and the Wellcome Trust (Grant ref: 093731) and the University of
Bristol provide core support for ALSPAC.
The BAMSE Study was supported by the Swedish Research Council, Stockholm County Council,
Centre for Allergy Research, Karolinska Institutet and the Swedish Heart Lung Foundation. Erik Melén
is supported by a post doc grant from the Swedish Heart Lung Foundation, the Swedish Fulbright
Commission and Riksbankens Jubileumsfond, Erik Rönnberg’s scholarship for research on early
childhood diseases.
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 (Egea1), F Gormand, Y
Pacheco ; Marseille : D Charpin (Egea1), D Vervloet ; Montpellier : J Bousquet ; Paris Cochin : A
Lockhart (Egea1), R Matran (now in Lille) ; Paris Necker : E Paty, P Scheinmann ; Paris-Trousseau : A
Grimfeld, J Just. Data and quality management : Inserm ex-U155 (Egea1) : J Hochez ; Inserm
CESP/U 1018, Villejuif : N Le Moual, Inserm ex-U780 : C Ravault ; Inserm ex-U794 : N Chateigner ;
Grenoble : J Ferran. The authors thank all those who participated to the setting of the study and on the
various aspects of the examinations involved: interviewers, technicians for lung function testing,
coders, those involved in quality control, data management and all those who supervised the study in
all centers. The authors are grateful to the three CIC-Inserm of Necker, Grenoble and Marseille who
supported the study and in which subjects were examined. They are indebted to all the individuals
who participated without whom that study would not have been possible.
EGEA sources of funding: 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)). For the genotyping (as for all Gabriel groups): The
GABRIEL genotyping was supported by a contract from the European Commission Framework
Programme 6 (018996) and grants from the French Ministry of Research.
The members of the GABRIELA study group are in alphabetical order: Silvia Apprich PhDG, Andrzej
Boznanski MD, PhDK, Charlotte Braun-Fahrländer MDD,E, Gisela Büchele PhDC, William Cookson MD,
DPhilA, Paul Cullinan MDA, Hanna Danielewicz MDK, Anna DębińskaK, Martin Depner PhDB, Markus
Ege MDB, Urs Frey MD, PhDR , Oliver Fuchs MDL, Jon Genuneit MDC, Dick Heederik PhDF, Elisabeth
Horak MDM, Anne Hyvärinen PhDH, Sabina Illi PhDB, Michael Kabesch MDN, Katalin KovacsM,
Aleksandra Kosmęda PhDK, Wolfgang Kneifel PhDG, Philipp Latzin MD, PhDL, Roger Lauener MDP,
Georg Loss MScD,E, Stephanie MacNeill MScA, Bernhard Morass MDM, Anne-Cécile Normand PhDQ,
Ilka Noss PhDF, Renaud Piarroux MD, PhDQ, Helena Rintala PhDH, Mascha K Rochat MDB, Nikolaos
SitaridisC, Barbara Sozanska MDK, David Strachan MDO, Christine Strunz-Lehner MPHB, Bertrand
Sudre MD, PhDI, Erika von Mutius MD, MScB, Marco Waser PhDD,E, Juliane Weber MDB, Inge
Wouters PhDF
Imperial College London, National Heart and Lung Institute, South Kensington Campus, London
SW7 2AZ, United Kingdom. B LMU Munich, University Children’s Hospital, Lindwurmstrasse 4, D
80337, Munich, Germany. C Ulm University, Institute of Epidemiology and Medical Biometry,
Helmholtzstraße 22, D-89081 Ulm, Germany. D Swiss Tropical and Public Health Institute, Socinstr.
57, P.O. Box, 4002 Basel, Switzerland. E University of Basel, Petersplatz 1, 4003 Basel, Switzerland
Utrecht University, Institute for Risk Assessment Sciences (IRAS), Division of Environmental
Epidemiology, PO Box 80178, 3508TD, Utrecht, The Netherlands.
BOKU Vienna, University of
Natural Resources and Life Sciences, Department of Food Science and Technology, Muthgasse 18,
A-1190 Vienna, Austria. H THL Kuopio, National Institute for Health and Welfare, PL 95 70701 Kuopio,
Finland. I Université de Franche-Comté, UMR 6249 Chrono-Environnement, Département de
Parasitologie/Mycologie, UFR SMP, 19 rue A. Paré, 25000 Besançon, France.
Wroclaw Medical
University, 1st Department of Paediatrics, Allergology and Cardiology, ul. J.M. Hoene-Wronskiego
13C, 53-376 Wroclaw, Poland. L Division of Pulmonology, Department of Paediatrics, Bern University
Hospital, Switzerland. M Department of Pediatrics and Adolescents, Division of Cardiology and
Pulmonology, Innsbruck Medical University, Anichstr. 35, A-6020, Innsbruck, Austria. N Hannover
Medical School, Clinic for Paediatric Pneumology and Neonatology, Carl-Neuberg-Str. 1, D-30625
Hannover, Germany. O St George’s, University of London, Cranmer Terrace, London SW17 0RE,
United Kingdom. P High Mountain Hospital Davos, Herman-Burchard-Str. 1, CH-7265 DavosWolfgang. Q Department of Parasitology and Mycology, Hôpital de la Timone, Assistance PubliqueHôpitaux de Marseille, 13385 Marseille, France. R University Children’s Hospital (UKBB), Spitalstrasse
33, 4056 Basel, Switzerland.
The PIAMA study was funded by grants from the Dutch Asthma Fonds, the ZON-MW Netherlands
Organization for Health Research and Development, the Stichting Astmabestrijding and the Ministry of
the Environment and the Netherlands Ministry of Health, Welfare and Sport.
Research support: the Swiss National Science Foundation (grants no 33CS30_134276/1, 33CSCO108796, 3247BO-104283, 3247BO-104288, 3247BO-104284, 3247-065896, 3100-059302, 3200052720, 3200-042532, 4026-028099, 3233-054996, PDFMP3-123171), 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, SUVA, Freiwillige Akademische Gesellschaft, UBS Wealth Foundation, Talecris
Biotherapeutics GmbH, Abbott Diagnostics, European Commission 018996 (GABRIEL), Wellcome
Trust WT 084703MA.
Current SAPALDIA Team: Study directorate: T Rochat (p), JM Gaspoz (c), N Künzli (e/exp), LJS Liu
(exp), NM Probst Hensch (e/g), C Schindler (s). Scientific team: JC Barthélémy (c), W Berger (g), R
Bettschart (p), A Bircher (a), G Bolognini (p), O Brändli (p), C Brombach (n), M Brutsche (p), L Burdet
(p), M Frey (p), U Frey (pd), MW Gerbase (p), D Gold (e/c/p), E de Groot (c), W Karrer (p), R Keller
(p), B Knöpfli (p), B Martin (pa), D Miedinger (o), U Neu (exp), L Nicod (p), M Pons (p), F Roche (c), T
Rothe (p), E Russi (p), P Schmid-Grendelmeyer (a), A Schmidt-Trucksäss (pa), A Turk (p), J Schwartz
(e), D. Stolz (p), P Straehl (exp), JM Tschopp (p), A von Eckardstein (cc), E Zemp Stutz (e). Scientific
team at coordinating centers: M Adam (e/g), E Boes (g), PO Bridevaux (p), D Carballo (c), E Corradi
(e), I Curjuric (e), J Dratva (e), A Di Pasquale (s), L Grize (s), D Keidel (s), S Kriemler (pa), A Kumar
(g), M Imboden (g), N Maire (s), A Mehta (e), F Meier (e), H Phuleria (exp), E Schaffner (s), GA Thun
(g) A Ineichen (exp), M Ragettli (e), M Ritter (exp), T Schikowski (e), G Stern (pd), M Tarantino (s), M
Tsai (e), M Wanner (pa) (a) allergology, (c) cardiology, (cc) clinical chemistry, (e) epidemiology, (exp)
exposure, (g) genetic and molecular biology, (m) meteorology, (n) nutrition, (o) occupational health, (p)
pneumology, (pa) physical activity, (pd) pediatrics, (s) statistics.
Acknowledgements: The study could not have been done without the help of the study participants,
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, MT Mandia, G Solari, B
Viscardi, Montana: AP Bieri, C Darioly, M Maire, Payerne: F Ding, P Danieli A Vonnez, Wald: D
Bodmer, E Hochstrasser, R Kunz, C Meier, J Rakic, U Schafroth, A Walder. Administrative staff: C
Gabriel, R Gutknecht.
Canadian Childhood Cohorts: CAPPS & SAGE
CAPPS and SAGE were funded by the Canadian Institutes for Health Research and by AllerGen NCE
Inc. (the Allergy, Genes and Environment Network), a member of the Networks of Centres of
Excellence Canada program. DD is the recipient of a Michael Smith Foundation for Health Research
(MSFHR) Career Scholar Award and holds a Tier II Canadian Research Chair appointment
The LifeLines Cohort Study, and generation and management of GWAS genotype data for the
LifeLines Cohort Study is supported by the Netherlands Organization of Scientific Research NWO
(grant 175.010.2007.006), the Economic Structure Enhancing Fund (FES) of the Dutch government,
the Ministry of Economic Affairs, the Ministry of Education, Culture and Science, the Ministry for
Health, Welfare and Sports, the Northern Netherlands Collaboration of Provinces (SNN), the Province
of Groningen, University Medical Center Groningen, the University of Groningen, Dutch Kidney
Foundation and Dutch Diabetes Research Foundation. The authors are grateful to the study
participants, the staff from the LifeLines Cohort Study and Medical Biobank Northern Netherlands, and
the participating general practitioners and pharmacists.