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The interaction of genetic variants and DNA methylation of the interleukin-4
receptor gene increase the risk of asthma at age 18 years
Clinical Epigenetics 2013, 5:1 doi:10.1186/1868-7083-5-1
Nelís Soto-Ramírez (firstname.lastname@example.org)
Syed Hasan Arshad (S.H.Arshad@soton.ac.uk)
John Holloway (J.W.Holloway@soton.ac.uk)
Hongmei Zhang (HZHANG@mailbox.sc.edu)
Eric Schauberger (email@example.com)
Susan Ewart (firstname.lastname@example.org)
Veeresh Patil (email@example.com)
Wilfried Karmaus (KARMAUS@mailbox.sc.edu)
18 August 2012
5 December 2012
3 January 2013
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The interaction of genetic variants and DNA
methylation of the interleukin-4 receptor gene
increase the risk of asthma at age 18 years
Syed Hasan Arshad2,6
* Corresponding author
1 Department of Epidemiology and Biostatistics, Arnold School of Public Health,
University of South Carolina, 800 Sumter Street, Columbia, SC 29208, USA
2 Clinical and Experimental Sciences, Faculty of Medicine, University of
Southampton, University Road, Southampton SO17 1BJ, UK
3 Human Development and Health, Faculty of Medicine, University of
Southampton, University Road, Southampton SO17 1BJ, UK
4 Department of Pediatrics, Medical College of Wisconsin, 8701 W Watertown
Plank Road, Milwaukee, WI 53226, USA
5 Department of Large Animal Clinical Sciences, Michigan State University,
3700 East Gull Lake Drive, East Lansing, MI 48824, USA
6 The David Hide Asthma and Allergy Research Centre, St Mary’s, Hospital,
Parkhurst Road, Newport, Isle of Wight PO30 5TG, UK
The occurrence of asthma is weakly explained by known genetic variants. Epigenetic marks,
DNA methylation (DNA-M) in particular, are considered to add to the explanation of asthma.
However, no etiological model has yet been developed that integrates genetic variants and
DNA-M. To explore a new model, we focused on one asthma candidate gene, the IL-4
receptor (IL4R). We hypothesized that genetic variants of IL4R in interaction with DNA-M at
cytosine-phosphate-guanine (CpG) sites jointly alter the risk of asthma during adolescence.
Blood samples were collected at age 18 years from 245 female cohort participants randomly
selected for methylation analysis from a birth cohort (n = 1,456, Isle of Wight, UK).
Genome-wide DNA-M was assessed using the Illumina Infinium HumanMethylation450
Thirteen single nucleotide polymorphisms (SNPs) and twelve CpG sites of IL4R gene were
analyzed. Based on linkage disequilibrium and association with asthma, eight SNPs and one
CpG site were selected for further analyses. Of the twelve CpG sites in the IL4R gene, only
methylation levels of cg09791102 showed an association with asthma at age 18 years
(Wilcoxon test: P = 0.01). Log-linear models were used to estimate risk ratios (RRs) for
asthma adjusting for uncorrelated SNPs within the IL4R gene and covariates. Testing for
interaction between the eight SNPs and the methylation levels of cg09791102 on the risk for
asthma at age 18 years, we identified the statistically significant interaction term of SNP
rs3024685 × methylation levels of cg09791102 (P = 0.002; after adjusting for false discovery
rate). A total of 84 participants had methylation levels ≤0.88, 112 participants between 0.89
and 0.90, and 35 between 0.91 and 0.92. For the SNP rs3024685 (‘CC’ vs. ‘TT’) at
methylation levels of ≤0.85, 0.86, 0.90, 0.91, and 0.92, the RRs were 0.01, 0.04, 4.65, 14.76,
14.90, respectively (interaction effect, P = 0.0003).
Adjusting for multiple testing, our results suggest that DNA-M modulates the risk of asthma
related to genetic variants in the IL4R gene. The strong interaction of one SNP and DNA-M
is encouraging and provides a novel model of how a joint effect of genetic variants and DNA-
M can explain occurrence of asthma.
Interleukin-4 receptor gene, DNA methylation, genetic variants, asthma, epigenetics
Asthma is a common chronic disease that affects around 235 million people around the world
and 5.4 million in the United Kingdom (UK) . The burden of disease affects 1.1 million
children between ages 0 to 17 years in the UK. Asthma is characterized clinically by
shortness of breath, wheezing episodes, chest tightness, and acute episodes of coughing .
The disease etiology is poorly understood and the postnatal development is not well
established. Genetic susceptibility, environmental factors, and gene × environment interaction
are believed to play a critical role in the development of asthma. Over 200 genes have been
suggested to contribute to asthma occurrence [3-5]. The high heritability (35% to 95%) and
the co-occurrence of asthma within families highlight the importance of a genetic component
in disease pathogenesis . In this work we focus on the interleukin receptor (IL4R) gene
which has been clearly established as an asthma susceptibility gene in multiple candidate
gene association studies [3-5].
There is evidence that interleukin-4 (IL-4) and its receptor (IL-4R) are involved in the
pathogenesis of asthma [6-8]. A recent meta-analysis indicated a modest risk associated with
IL4R single nucleotide polymorphisms (SNPs) on occurrence of asthma, but other
investigators found conflicting results . Analysis of asthma candidate genes in a genome-
wide association study population showed that SNPs in IL4R were significant related to
asthma with significance level between P = 0.05 and P = 0.0035  despite IL4R not being
identified in genome-wide association study (GWAS) analysis suggesting that IL4R variation
is not well captured in current GWAS platforms. Other genetic regulatory mechanisms
beyond DNA sequence variation may aid in explaining the role of IL4R in asthma. It has been
suggested that epigenetic mechanisms play a role in T-cell differentiation and regulation, a
crucial event in the onset of atopic diseases such as asthma . Epigenetic regulatory
mechanisms, such as DNA-methylation (DNA-M), may alter gene expression and protein
production without changing the DNA sequence. No etiological model has yet been
developed that integrates genetic variants and DNA-M. We will explore the idea that an
increase of DNA-M may silence or a decrease of DNA-M may activate the effect of specific
SNPs. To test this new model, we focus on one asthma candidate gene, the IL4R gene. We
hypothesized that SNPs in interaction with cytosine-phosphate-guanine (CpG) sites jointly
predispose to asthma at age 18 years. To test vertical transmission of DNA-M to offspring in
future steps, this work focuses on women.
Study design and population
A whole-population birth cohort was established on the Isle of Wight in 1989 to
prospectively study the natural history of asthma and allergic conditions. After exclusion of
adoptions, perinatal deaths and refusal, 1,456 children (95%) were enrolled. The local
research ethics committee approved the study and informed written parental consent was
obtained for all participants at recruitment and subsequently at follow-ups, which were
conducted at ages 1, 2, 4, 10, and 18 years of age. The birth cohort has been described in
detail elsewhere [10,11]. In this study we focused on blood samples collected at 18 years of
age from 245 female cohort participants who were randomly selected for genomic sequencing
Clinical data collection and outcome
Maternal history of asthma and smoking during pregnancy was ascertained at birth. Birth
weight was obtained from birth records. At ages 1, 2, 4, 10, and 18 years, the original
questionnaire-based information was updated, and weight and height of the child were
measured. Breastfeeding duration was assessed at follow-up visits at ages 1 and 2 years. At
age 18 years, the questionnaire-based information was updated using the International Study
of Asthma and Allergies in Childhood (ISAAC) questionnaire . Asthma at age 18 years
was defined as subjects with a physician diagnosis of asthma plus current symptoms and/or
SNP selection for the IL4R gene
An efficient genotype tagging scheme was developed that gave priority to variants that 1)
showed strong association with asthma in the Isle of Wight birth cohort, and/or 2) have been
reported by others to be associated with asthma/allergy, and/or 3) have functional importance.
A literature search for IL4R gene plus asthma and allergy was used to identify associated
variants (SNPs, indels). Functional variants included those that were non-synonymous,
located in conserved DNA, and/or present in DNA regions with gene regulatory potential.
Tagger implemented in Haploview 3.2 using Caucasian Hapmap data was used to develop a
tagging scheme for the IL4R gene region, including 10 kb upstream and downstream of the
gene . An r2 value of 0.85 was the threshold for tagging and one, two and three SNP
marker combination tests were used. The result was an efficient number of genotyped
variants (n = 13) that would provide the needed information to statistically support or exclude
the gene in its association with asthma outcomes.
DNA methylation protocol
DNA was extracted from whole blood using a standard salting out procedure . DNA
concentration was determined by PicoGreen quantitation. One microgram DNA was
bisulfite-treated for cytosine to thymine conversion using the EZ 96-DNA methylation kit
(Zymo Research, Irvine, CA, USA), following the manufacturer’s standard protocol.
Genome-wide DNA methylation was
HumanMethylation450 BeadChip (Illumina, Inc., San Diego, CA, USA), which interrogates
>484,000 CpG sites associated with approximately 24,000 genes. Arrays were processed
using a standard protocol as described elsewhere , with multiple identical control samples
assigned to each bisulphite conversion batch to assess assay variability and samples randomly
distributed on microarrays to control against batch effects. The BeadChips were scanned
using a BeadStation, and the methylation level (beta value) calculated for each queried CpG
locus using the Methylation Module of BeadStudio software.
assessed using the Illumina Infinium
The main exposures are SNPs and the methylation levels at CpG sites in the IL4R gene
(Table 1). The following SNPs were included in the analysis: rs3024622, rs3024685,
rs6498012, rs12102586, rs16976728, rs4787423, rs3024676, and rs2057768.
Table 1 Location, position, and distance between the SNPs and the CpG sites in the IL4R gene
Median, IQR (5%, 95%)
09791102 01165142 05903710
Body Body 5′UTR 3′UTR
27353414 27367172 27375732
27322095 −2246 −2858 −2905 −3142 −3159 −3577 −3959 −16296 −23796 −31319 −45077 −53637
27331974 7633 7021 6974 6737 6720 6302 5920 −6417 −13917 −21440 −35198 −43758
27365453 41112 40500 40453 40216 40199 39781 39399 27062 19562 12039 −1719 −10279
27367334 42993 42381 42334 42097 42080 41662 41280 28943 21443 13920 162 −8398
27373558 49217 48605 48558 48321 48304 47886 47504 35167 27667 20144 6386 −2174
27376910 52569 51957 51910 51673 51656 51238 50856 38519 31019 23496 9738 1178
27378053 53712 53100 53053 52816 52799 52381 51999 39662 32162 24639 10881 2321
#The location is based on Build 37, also known as GRCh37. The distance was calculated by subtracting the location of the SNP to the CpG site
in the IL4R gene. For instance, the distance between the SNP rs6498012 and the CpG site cg08932316 is 7633 (27331974–27324341)
56759 56712 56475 56458 56040 55658 43321 35821 28298 14540 5980
To assess whether our analytic sample (245 DNA samples) was representative of the total
cohort available at age 18 years, we compared the characteristics of these two subsets by
using the chi-square test. After cleaning the DNA-M data, beta (β) values presented as the
proportion of intensity of methylated (M) over the sum of methylated (M) and unmethylated
(U) sites (β = M/[c + M + U] with c being a constant to prevent dividing by zero) were used
to estimate the effect of DNA methylation . The methylation levels of 12 CpG sites
spanning the genomic region of the IL4R gene (Table 1) were tested for association with
asthma at age 18 years using Wilcoxon tests. Of these CpG sites, only methylation levels of
cg09791102 showed a statistically significant association with asthma at age 18 years
(Wilcoxon test: P = 0.01).
The 13 SNPs shown in Figure 1 were tested for Hardy-Weinberg equilibrium using
Haploview 3.2 software  and estimates of linkage disequilibrium (LD) between SNPs
were calculated using D’ and r2 , to select one SNP that represents each LD block or an
Figure 1 IL4R LD plot; standard (D’/LOD) color scheme; D’ LD values displayed.
After identifying eight uncorrelated IL4R SNPs (Figure 1; Table 1) and identifying which
CpG site was significantly associated with asthma, we ran eight independent models to
estimate statistical interactions between these SNPs and the methylation level of cg09791102
on the risk for asthma at age 18 years. We assessed the interaction on a multiplicative scale in
log-linear models using an overall chi-square test as a cutoff P value = 0.05 for each. Only
one interaction (SNP rs3024685 × cg09791102) showed a significant effect on asthma at age
18. This interaction and those SNPs and four covariates that confounded the association
between the SNP and CpG interaction with asthma at age 18 years were included in the final
log-linear model. We then inspected which genotype (CC, CT, or TT) explains the overall
effect. Confounders include child’s BMI at age 18 (kg/m2), maternal history of asthma,
maternal smoking during pregnancy, and breastfeeding duration (weeks). All confounders
were simultaneously entered as indicator variables into the log-linear model. A backward
elimination process was used to identify confounders, those that changed the association of
interest by 10% or more were retained in the final model. For the reduced model, we
estimated risk ratios (RR) and their 95% confidence intervals (CI).
Since we tested a total of eight crude SNP × methylation interactions before selecting the full
model, we adjusted for multiple testing by applying false discovery rate (P = 0.05) . All
statistical analyses were performed using the SAS statistical package, Version 9.2 (SAS
Institute, Cary, NC, USA), except for cleaning the DNA methylation data, which was done
using R statistical computing package .
Blood samples from a subset of 245 of 750 female birth cohort participants were used to
determine DNA-M at CpG sites. There were no substantial differences in prevalence of low
birth weight, asthma at 18, BMI at 18, breastfeeding duration, maternal BMI, maternal
history of asthma, nor maternal smoking between the female participants of the cohort and
the subset included in this analysis (Table 2). For the subgroup with available methylation
data 12% had maternal history of asthma, 19% had mothers that smoked during pregnancy,
and 14.3% (35/245) had asthma at age 18 years.
Table 2 Subject characteristics with available methylation data compared to the female
participants of the total cohort
participants n (%)
n = 750
Maternal history of asthma
Yes 80 (10.8)
No 662 (89.2)
Maternal smoking during pregnancy
Yes 188 (25.3)
No 555 (74.7)
Maternal body mass index (kg/m2)
Underweight (<18.5) 10 (1.7)
Normal (18.5- <25) 355(61.5)
Overweight (≥25.00) 212 (36.7)
Low birth weight
Yes 35 (4.8)
No 699 (95.2)
Asthma at age 18 years
Yes 128 (19.4)
No 531 (80.6)
Median (5%, 95% value); n
Body mass index at age
Female with DNA methylation
data, n (%)
n = 245
8.0 (0, 40); 664 10.5 (0, 40); 222 0.16
22.2 (18, 32); 499 22.9 (19.05, 32.93); 240 0.56
Of the thirteen SNPs genotyped in the IL4R gene, eight SNPs were analyzed since they were
uncorrelated (D’ <0.95) (Figure 1, Table 1). A total of 12 CpG sites spanning the genomic
region of the IL4R gene were analyzed for association with asthma at age 18 years. Only
methylation levels of cg09791102 showed an association with asthma at age 18 years
(Wilcoxon test: P = 0.01). Testing for interaction between the eight SNPs and the methylation
levels of cg09791102 on the risk for asthma at age 18 years, we identified that the interaction
term of SNP rs3024685 × methylation levels of cg09791102 was statistically significant (P =
0.0003; FDR adjusted P value = 0.002; Table 3). In other words, the genetic risk of asthma
associated with rs3024685 increases as the methylation level of cg09791102 rises (Figure 2).
Table 3 Adjusted log-linear regression model of the interaction of genetic variants and
DNA methylation of the IL4R gene on asthma at age 18 years
rs3024685 CC −102.45
rs3024622 CC −1.24
rs12102586 TT 2.41
rs16976728 TT −0.53
Maternal smoking during pregnancy 0.43
Maternal history of asthma 0.53
Body mass index at age 18 years
Breastfeeding duration (weeks) 0.02
177.91 CC 115.54
−0.004 0.04 0.11
Figure 2 Risk Ratio of asthma at age 18 years versus methylation score at different
genotypes of IL4Rrs3024685. The blue bars present the relative frequency of the DNA
methylation levels. For instance, 87% methylation is found in 10% of the participants. The
reference genotype is ‘TT’. The solid horizontal line that indicates a risk ratio value of ‘1’
shows the risk ratio of the reference ‘TT’ genotype. The black dot represents the ‘CC’
genotype, and the diamond is ‘CT’ genotype.
The DNA-M level range for cg09791102 was 0.48 to 0.92 (blue bars in Figure 2). Since the
number of participants at methylation levels of 0.85 or less were low, we grouped these
methylation levels into ≤0.85 (n = 9). For descriptive purposes, 84 participants had
methylation levels of 0.88 and less, 112 participants of 0.89 to 0.90, and 35 of 0.91 to 0.92.
Since the mode of inheritance is additive, we compared participants who had the ‘CC’ and
‘CT’ genotypes with those who were ‘TT’ genotype at rs3024685. For the genotype ‘CC’,
compared to ‘TT’, we found that at methylation levels of 0.85, 0.86, 0.90, 0.91, and 0.92, the
RRs of asthma were 0.01, 0.04, 4.65, 14.76, and 46.90 (Figure 2; FDR adjusted P value =
0.002), respectively. Similar results were found with ‘CT’ genotype, however the interaction
term did not achieve statistical significance (P = 0.06).
Descriptively, 13.2% and 14.3% of the participants had asthma at a methylation level of 0.88
at the genotype ‘CT’ and ‘TT’, respectively; and none of the ‘CC’ genotype had asthma.
Between 0.89 and 0.90 methylation levels, 15.0% of the ‘CC’, 16.7% of the ‘CT’, and 7.9%
of the ‘TT’ genotype had asthma. At methylation levels larger than 0.90, 54.6% of the ‘CC’
and 16.7% of the ‘CT’ genotype had asthma, and none of the ‘TT’ genotype had asthma.
This is the first study to determine the role of both genetic and epigenetic factors within the
genomic region of the IL4R gene on the risk for asthma. Although the CpG site cg09791102
is located 23,496 base pairs away from SNP rs3024685 in the intragenic region of the IL4R
gene, we found that the risk of asthma is modulated by this CpG site even after adjusting for
multiple testing. The distance between the SNP and the CpG sites is large. However, Bell et
al. have demonstrated that for a regulation in cis even larger distances can show statistically
significant effects . Hence, these two factors (SNP and CpG site) may jointly contribute
to gene expression or alternative splicing.
The SNP rs3024685 in the 3′UTR region has no independent effect on asthma at age 18
years; however in interaction with the CpG site cg09791102 (gene body, Table 1) it is
strongly associated with asthma in female participants. At 92% methylation level, rs3024685
(‘CC’ genotype compared to ‘TT’) showed a 46.9-fold increase risk for asthma. Our
observation of a role of gene-body methylation is further supported by the emerging
evidence, which shows that methylation in intragenic regions can be positively correlated
with gene expression levels and phenotype variation [21,22]. Intragenic DNA methylation
has been linked to ‘exon definition’ through interaction with auxiliary proteins, by which
DNA methylation in the body may result in alternative pre-mRNA splicing regulation (for
example, inclusion or exclusion of exons) [23-25]. We assume that a higher DNA-M may
mask an otherwise protective effect of rs3024685 and thus increases the risk of asthma .
Our results indicate that considering both genetic variants and DNA methylation will
significantly improve the explanation of asthma. Replication of these findings in an
independent study population is needed to validate the interplay of DNA methylation with
genetic polymorphism, which results in an increased asthma risk. However, currently there
are only few studies that can provide both genetic and DNA methylation data.
A limitation of our study is that the RRs at methylation levels larger than 90% are high,
which is due to the limited number of individuals (n = 36) with methylation levels larger than
90%. Evidence of selection bias is absent since prevalence of asthma and IL4R SNPs is
comparable between those analyzed in this study and those from the original cohort. Multiple
testing was a concern since we tested the joint effect of differential DNA methylation of
cg09791102 and eight IL4R SNPs separately (a total of eight tests). Nevertheless, the
observed increased risk remained statistically significant after penalizing its P value for false
discovery rate. Regarding reliability and specificity of methylation status of CpG sites, a
recent report demonstrated that the Infinium HumanMethylation450 array, which was used to
obtained DNA methylation profiles in this study, had strong reproducibility and high validity
. The extent to which DNA methylation measured in blood relate to other tissues and
whether can be used as a biomarker for phenotype variation is unclear and is an area of
current scientific dispute [28-30].
The strong interaction of one SNP and DNA-M is encouraging and provides a novel model
how a joint effect of genetic variants and DNA-M can explain asthma. Although the sample
size is limited and focused on female participants, our results should generally motivate other
studies to replicate the interaction we found, while also searching for new interactions
between genetic variants and DNA methylation, in particular for the IL4R gene and asthma.
CI, confidence interval; CpG, cytosine-phosphate-guanine; DNA-M, DNA methylation;
GWAS, genome-wide association study; IL4R, interleukin-4 receptor; ISAAC, International
Study of Asthma and Allergies in Childhood; LD, linkage disequilibrium; RR, risk ratio;
SNP, single nucleotide polymorphisms; UTR, untranslated region.
The authors declare that they have no competing interests.
NSR conducted the statistical analysis, interpreted the data, and drafted the manuscript. SHA
and VP contributed to the clinical interpretation and helped with the manuscript. JH
supervised the assessment of the DNA methylation and revised the manuscript. HZ directed
the statistical analysis and aided in their interpretation and the final editing. SE and ES
selected and measured the single nucleotide polymorphisms. SE and SHA contributed to
funding acquisition and the manuscript. WK designed the study, reviewed the data quality,
helped with statistical analyses, and revised the manuscript. All authors read and approved
the final manuscript.
Research reported in this publication was supported by the National Institute of Allergy and
Infectious Diseases under Award Number R01 AI091905-01 (PI: Wilfried Karmaus) and R01
AI061471 (PI: Susan Ewart). The 10-year follow-up of this study was funded by National
Asthma Campaign, UK (Grant No 364) and the 18-year follow-up by NIH/NHLBI R01
HL082925-01 (PI: S. Hasan Arshad). The content is solely the responsibility of the authors
and does not necessarily represent the official views of the National Institutes of Health.
The authors gratefully acknowledge the cooperation of the children and parents who
participated in this study, and appreciate the hard work of Mrs. Sharon Matthews and the Isle
of Wight research team in collecting data and Nikki Graham for technical support. We thank
the High-Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics
(funded by Wellcome Trust grant reference 090532/Z/09/Z and MRC Hub grant G0900747
91070) for the generation of the methylation data.
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