The Journal of Allergy and Clinical Immunology
Volume 124, Issue 6 , Pages 1204-1209.e9, December 2009

Sequencing the IL4 locus in African Americans implicates rare noncoding variants in asthma susceptibility

  • Gabe Haller, BA

      Affiliations

    • G. Haller is currently affiliated with Washington University, Division of Biology and Biomedical Sciences, St Louis, Mo.
  • ,
  • Dara G. Torgerson, PhD
  • ,
  • Carole Ober, PhD
  • ,
  • Emma E. Thompson, PhD

      Affiliations

    • Corresponding Author InformationReprint requests: Emma E. Thompson, PhD, University of Chicago, Department of Human Genetics, 920 E. 58th Street, Chicago, IL 60637.

Department of Human Genetics, University of Chicago, Chicago, Ill

Received 20 July 2009; received in revised form 9 September 2009; accepted 10 September 2009. published online 12 November 2009.

Article Outline

Background

Common genetic variations in the IL4 gene have been associated with asthma and atopy in European and Asian populations, but not in African Americans.

Objective

Because populations of African descent have increased levels of genetic variation compared with other populations, particularly with respect to low frequency or rare variants, we hypothesized that rare variants in the IL4 gene contribute to the development of asthma in African Americans.

Methods

To test this hypothesis, we sequenced the IL4 locus in 72 African Americans with asthma and 70 African American controls without asthma to identify novel and rare polymorphisms in the IL4 gene that may be contributing to asthma susceptibility.

Results

We report an excess of private noncoding single nucleotide polymorphisms (SNPs) in the subjects with asthma compared with control subjects without asthma (P = .031). Tajima's D is significantly more negative in subjects with asthma (–0.375) than controls (–0.073; P = .04), reflecting an excess of rare variants in the subjects with asthma.

Conclusion

Our findings indicate that SNPs at the IL4 locus that are potentially exclusive to African Americans are associated with susceptibility to asthma. Only 3 of the 26 private SNPs (ie, SNPs present only in the subjects with asthma or only in the controls) are tagged by single SNPs on one of the common genotyping platforms used in genome-wide association studies. We also find that most of the private SNPs cannot be reliably imputed, highlighting the importance of sequencing to identify genetic variants contributing to common diseases in African Americans.

Key words: Rare variants, private alleles, asthma, IL4, IgE, African Americans

Abbreviations used: MAF, Minor allele frequency, SNP, Single nucleotide polymorphism

 

IL-4 is the major TH2 cytokine that induces the isotype switch to IgE in B lymphocytes1, 2 and is involved in host response to both parasitic infection and allergens.3 Genetic variations in the IL4 gene have been associated with expression levels of IL-44 as well as susceptibility to atopic diseases, including asthma (see review5), and to parasitic infections.6, 7 Even though IL4 is among the most replicated asthma/atopy susceptibility loci,5 only 2 studies have included individuals of African descent.8, 9 To date, all or part of the IL4 gene has been sequenced in 78 European and 50 non-European individuals (38 African American, 6 Asian, 6 Hispanic).8, 10, 11 Together, 5 single nucleotide polymorphisms (SNPs) have been identified in the coding region of the gene (3 of which are rare nonsynonymous SNPs).12 On the other hand, an abundance of noncoding SNPs have been identified at the IL4 locus, several of which have been implicated in disease risk. For example, 2 common SNPs have been associated with allergic disease (including asthma) in many studies.5 These polymorphisms, a functional promoter SNP (-589C/T; rs2243250) and an SNP of unknown function in the 5′ untranslated region (-33C/T; rs2070874), are in linkage disequilibrium in European and Asian HapMap samples (Europeans, r2 = 1; Asians, r2 = 1; Africans, r2 = 0.18). Other variations in intron 2 (3017 T/G, rs2227284, and 2 repeat polymorphisms) have also been associated with asthma and IgE in diverse populations. However, none of these common polymorphisms or any of the other tested variants in the IL4 gene has been associated with disease risk in African Americans when P values are corrected for multiple testing.8, 9

Because populations of African descent have increased levels of genetic variation compared with other populations, particularly with respect to low-frequency or rare variants,13, 14 we hypothesized that rare variants in the IL4 gene contribute to the development of asthma in African Americans. To test this hypothesis, we sequenced nearly the entire IL4 gene in 72 African American subjects with asthma and 70 African American control subjects. We report a significant excess of private SNPs (ie, SNPs present only in subjects with asthma or only in controls) and rare noncoding SNPs (minor allele frequency [MAF] < 5%) in subjects with asthma compared with control subjects, supporting the hypothesis that rare variants in the IL4 gene play an important role in disease susceptibility in African Americans.

Back to Article Outline

Methods 

Study samples 

DNA from 142 unrelated African Americans who participate in the Chicago Asthma Genetics study were included in this study. The 72 subjects with asthma met the following criteria: (1) a physician's diagnosis of asthma (with no conflicting diagnosis); (2) the presence of at least 2 self-reported symptoms (cough, wheeze, shortness of breath); (3) current use of asthma medications; (4) either bronchial hyperresponsiveness, defined as a ≥20% decrease in FEV1 after inhalation of ≤25 mg/mL methacholine, or reversibility to inhaled bronchodilator, defined as a ≥15% increase in baseline FEV1 after inhalation of a bronchodilator (albuterol) or after treatment; (5) birth weight <4.4 lb; and (6) <3 pack-years of cigarette smoking. The 70 control subjects had no personal or family history of asthma among first-degree relatives and were ≥18 years of age. All subjects with asthma and control subjects reported at least 3 grandparents of African or African American descent. Total serum IgE measurements were available for all but 19 subjects with asthma and 11 controls without asthma; allergen skin prick testing was not performed in the control subjects, and those data therefore were not included in this study.

Sequencing studies 

The consensus sequence AF395008 (Genbank) was used to design overlapping primer sets to cover the entire IL4 gene, including 1743 bp upstream of the ATG start site, and 1724 bp downstream of the last exon (exon 4; see this article's Table E1 in the Online Repository at www.jacionline.org). Nucleotide positions throughout this article are given with respect to the ATG start site unless otherwise noted. PCR was performed in a total volume of 23 μL, with 5 mmol/L deoxyribonucleotide triphosphates (dNTPs), 37.5 mmol/L MgCl2, 12.5 μmol/L each primer, 5 μL 5x Taq Buffer, 0.2 μL GoTaq Flexi DNA polymerase (Promega, Madison, Wis), and 20 ng genomic DNA. Unincorporated nucleotides and excess primers were removed from PCR products by using Exonuclease (New England Biolabs, Ipswich, Mass)/Shrimp Alkaline Phosphatase (USBio, Marblehead, Mass). All amplifications were sequenced in both directions by using BigDye Terminator Sequencing Kits (Applied Biosystems, Foster City, Calif). The chimpanzee consensus sequence (GeneID: 449565) was aligned to the human reference sequence with ClustalW15 and used to determine ancestral alleles.

SNP identification 

The Phred-Phrap-Consed-PolyPhred package was used to assemble the sequences and identify SNPs.16 All sequences were visually inspected. Because of the sequence overlap, more than 1 call for each genotype was often obtained for each position in a sample.

Genotyping a variable element in intron 3 

The genotypes for a variable element in intron 3 (VE6566),10 a 70-bp copy number variant, were determined by size separation on 3% agarose gels (1-3 copies). DNA was amplified by using PCR primers (Table E1) that flanked the variable element. Genotypes at a TG dinucleotide repeat in the second intron of IL417, 18 were not included in this study because we could not discern genotypes by sequencing or by an electrophoretic gel assay.

Data analysis 

Polymorphisms were tested for Hardy-Weinberg equilibrium in the subjects with asthma, the controls, and the combined sample by using Haploview.19 Single SNPs were tested for association with asthma status using a χ2 test as implemented in PLINK (http://pngu.mgh.harvard.edu/purcell/plink/).20 The proportion of private SNPs in subjects with asthma compared with controls was evaluated by permutation test, in which case/control status was permuted 100,000 times in the subjects with asthma and controls (combined), holding the genotypes constant and preserving the pattern of missing data, to build an empirical distribution of the differences in the proportion of private SNPs. As a second test, a weighted-sum statistic was calculated to test for association of the locus as a whole with case status, using the method of Madsen and Browning.21 In this method, each variant was weighted by its MAF in unaffected individuals, and then individuals were given a score consisting of the sum of their weighted alleles (with rarer alleles given greater weight). Individuals were ranked on the basis of their score, and a sum of ranks for affected individuals was calculated. Significance was determined by permuting case/control status 100,000 times to produce an empirical distribution of summed ranks, and to preserve the pattern of missing data. For all permutation tests, a threshold for statistical significance was set at P <.05 (ie, less than 5000 of the 100,000 permutations were greater than the observed sum of ranks for affected individuals).

Two measures of nucleotide diversity are commonly used to compare SNP frequencies among samples of varying size and DNA fragment length: the average number of pairwise differences in a given set of chromosomes (π),22 and nucleotide diversity estimated from the allele frequency of the polymorphic sites (θw).23 The difference between these 2 estimates (relative to their SE) is expressed as Tajima's D, which is expected to be 0 under neutrality. A positive Tajima's D reflects a larger π than θw and indicates an excess of intermediate-frequency variants, whereas a negative value (larger θw than π) indicates an excess of rare variants. Significant deviations from 0 in either direction indicate a skew in the allele frequency spectrum, which can be a sign of nonneutral evolution (ie, selection) or demographic events (ie, population history). Permutation tests were used to assess whether Tajima's D was significantly more negative in subjects with asthma compared with controls. A total of 100,000 permutations were conducted by randomly sampling 72 individuals without replacement to represent subjects with asthma from the pooled set of cases and controls. The remaining sample of 70 individuals was then taken to represent controls. For each permutation, Tajima's D was calculated for the sampled subjects with asthma and controls, and the difference between their values was calculated to assess the probability that we have observed a larger difference between the values of Tajima's D for subjects with asthma and controls than expected by chance.

Admixture estimates 

European admixture in 112 African American subjects (54 cases, 58 controls) was estimated at both the genomic and local scales by using genotypes from more than 1 million SNPs on the Illumina Human 1 M array. Genomic European admixture was estimated from the first principal component in a principal component analysis including the HapMap CEU and YRI as reference populations in EIGENSTRAT.24 Local European admixture at the IL4 locus was estimated using 63,598 SNPs on chromosome 5 with the program Local Ancestry in adMixed Populations (LAMP)25 by assuming 20 generations of European admixture, a constant recombination rate of 10−7, and a population admixture rate of 81% obtained from genomic admixture estimates. Wilcoxon rank sum tests (WRSTs) with continuity corrections were used to compare percent European ancestry in subjects with asthma and controls, and between individuals who harbored private SNPs and those who did not. Genomic European admixture did not differ between subjects with asthma and controls (P = .64; see this article's Fig E1 in the Online Repository at www.jacionline.org) or between individuals who carried private polymorphisms and those who did not (Wilcoxon rank-sum test; P = .83). At the local scale, there was also no significant difference in European admixture between subjects with asthma and controls (P = .28; see this article's Fig E2 in the Online Repository at www.jacionline.org), or between individuals who carried private polymorphisms and those who did not (P = .49).

Estimates of linkage disequilibrium and SNP imputation 

Linkage disequilibrium between SNPs identified from the sequencing of IL4 and SNPs genotyped on the Illumina 1 M genotyping platform in 112 African American individuals (54 cases, 58 controls), was estimated by using Haploview 4.1.19 The IL4 SNPs from sequencing were considered to be tagged by SNPs on the Illumina 1 M if they demonstrated an r2 value >0.5 and were within 500 kb of the IL4 locus. To evaluate the potential for imputing the IL4 SNPs identified by sequencing, we generated 2 datasets (a query and reference panel) including the same 112 African American individuals who were typed on the Illumina 1 M platform. The query dataset included only the 588 SNPs typed on the Illumina 1 M platform that were within 500 kb of the IL4 transcription start and stop site. The reference panel included both the 588 SNPs from the Illumina 1 M and the IL4 SNPs from the sequencing of the same individuals. The IL4 SNPs in the query dataset were imputed with Mach 1.026 by using 50 iterations of the Markov sampler and considering 200 haplotype states when updating each individual. The accuracy in imputing the minor allele for each SNP was defined as the number of times the minor allele was correctly imputed/the number of minor alleles observed in the data.

Back to Article Outline

Results 

Sequence variation 

We identified 92 genetic polymorphisms in the 12.4 kb of DNA encompassing the IL4 gene in 142 African Americans (see this article's Table E2 in the Online Repository at www.jacionline.org). Of these, 86 were SNPs and 6 were insertion/deletion polymorphisms. More than half of the SNPs (N = 57) had MAFs <0.05. One SNP was in the coding region of exon 1 (44A/G; Leu33Leu; rs2070874), 17 were in the 3′ downstream region, 13 were in the 5′ upstream region, and 61 were intronic. All SNPs were in Hardy-Weinberg equilibrium in the combined sample, in subjects with asthma, and in controls without asthma after applying a Bonferroni correction for multiple testing. Only a single SNP (4400A/G; rs2243270) had a Hardy-Weinberg uncorrected P value <.05 in both the control (P = .02) and combined (P = .008) samples. The MAFs for each of the 92 polymorphisms in subjects with asthma and controls and in atopic cases and atopic controls are shown in Table E2. Consistent with our previous report, which included the subjects in this study,9 the -589C/T (rs2243250), -33C/T (rs2070874), and 3017 T/G (rs2227284) SNPs had similar minor allele frequencies in subjects with asthma and controls (P > .15).

Private SNPs and the allele frequency spectrum in subjects with asthma and controls 

We identified 26 private SNPs: 18 occurred only in subjects with asthma and 8 occurred only in controls, all with MAF ≤0.02. Only 2 of these SNPs were present in dbSNP (4614/rs2243272 and 5342/rs2243277), each of which had been identified by sequencing a single heterozygous individual in an African American sample (N = 46 chromosomes).11 Two of the private SNPs (-996 and -593) in our study occurred together in 2 subjects with asthma (CA4748 and CA9994) and presumably reside on the same haplotype in these individuals; 2 additional private SNPs (612, 8982) were each present in 2 subjects with asthma, 1 private SNP (4614) was present in 3 subjects with asthma, and 1 private SNP (-1621) was present in 2 controls (Fig 1).

  • View full-size image.
  • Fig 1. 

    Private SNP haplotypes in subjects with asthma and controls. A schematic of the IL4 gene is shown at the top of the figure, with relative SNP positions (with respect to ATG start site) marked. SNPs present only in asthma cases (CA) or only in asthma controls (CO; ie, private SNPs) are shown. SNPs present in asthma cases are connected to the gene figure by solid lines, and SNPs present in controls are connected by hatched lines. Individual haplotypes appear in rows, with nucleotides against a dark background representing the derived (private) allele.

The proportion of private SNPs (among all SNPs detected) was higher in subjects with asthma than controls (P = .031; permutation test; Table I). The sex ratios among individuals carrying private SNPs (16 females, 10 males) and among individuals not carrying private SNPs (73 females, 30 males) were not different (P = .358). Private SNPs were not associated with European admixture in either subjects with asthma (Fisher exact test; P = 1.0) or controls (P = .710; see this article's Table E3 in the Online Repository at www.jacionline.org), indicating that an excess of private SNPs in the subjects with asthma is not a result of differences in the number of admixed individuals or the proportion of European admixture between the groups. In addition, the weighted sum method21 revealed an association between variation at the IL4 locus and asthma status (P = .017; permutation test). Last, we investigated whether individuals with private SNPs had higher IgE levels than individuals without private SNPs. Seventeen of 23 (77%) subjects with private SNPs had IgE levels above the median value (72 IU/mL), whereas only 39 of 80 (49%) subjects without private SNPs had IgE levels above the median (P = .004), indicating that increased IgE levels are associated with rare, private SNPs and suggesting that at least some of these SNPs may be regulatory in function.

Table I. Descriptive statistics for SNPs at the IL4 locus
Proportion of private SNPsPermutation
P value
θWπTajima DPermutation
P value
Combined sample (n = 142)12.53 × 10−411.09 × 10−4−0.356
Controls without asthma (n = 70)0.076.03111.26 × 10−411.00 × 10−4−0.073.041
Subjects with asthma (n = 72)0.21112.71 × 10−411.20 × 10−4−0.375

The Watterson23 estimate of the population mutation rate (θ = 4Neμ, where Ne is the effective population size and μ is the per generation mutation rate).

Average number of pairwise differences between samples.22

We next calculated Tajima's D to identify differences in the allele frequency spectrum between subjects with asthma and controls. Tajima's D22 considers the difference between 2 measures of nucleotide diversity, θW and π, and is positive when there is an excess of intermediate frequency variants, negative when there is an excess of rare variants (at either high-frequency or low-frequency derived SNPs), and 0 under neutral expectations (where θW = π). The value for Tajima's D in the control sample is –0.073, which is in the 78th percentile of values from an empirical distribution based on 327 autosomal loci in African Americans (Seattle SNPs). However, Tajima's D is more negative in subjects with asthma (–0.375) than in controls (–0.073; P = .041; permutation test; Table I), reflecting the increased number of low-frequency variants in the subjects with asthma.

Imputing rare and private SNPs 

None of the private SNPs and only a single rare variant identified in this study were present on the Illumina 1 M genotyping array. Furthermore, only 3 of the private SNPs in IL4 were tagged by SNPs on that platform (r2 > 0.5, 2 private to controls and 1 private to a subject with asthma; see this article's Table E4 in the Online Repository at www.jacionline.org). As expected, a greater proportion of private SNPs failed to be correctly imputed at even a single minor allele compared with SNPs that were shared between subjects with asthma and controls (57% vs 1.7%; Fisher exact test; P < 10−6; see this article's Table E5 and Fig E3 in the Online Repository at www.jacionline.org). This is similarly true for rare SNPs (57% vs 3.1%; P = 9 × 10−6).

Back to Article Outline

Discussion 

The prevalence of asthma in the United States has risen in recent decades,27 and the disease burden disproportionately affects African Americans.28 In addition, the clinical presentation of asthma with respect to associations with and severity of atopy and bronchial hyperresponsiveness differs between African Americans and European Americans.28 Yet relatively few studies have investigated the genetics of asthma in African American populations, in whom associations are less often replicated,29, 30 as is the case at the IL4 locus.8, 9 One explanation for this finding could be differences in haplotype structure and patterns of linkage disequilibrium between individuals of European or Asian ancestry and those of African ancestry (see review14), as suggested in a recent genome-wide association study for asthma genes.29 An alternative explanation is that rare alleles present in African-derived populations, but not in European or Asian populations, contribute to disease susceptibility, possibly even masking the effects of other variants. Because of their unique demographic history, African-derived populations harbor more nucleotide diversity in general, and more rare alleles in particular, than populations of European or Asian descent.13, 14, 31 It is possible, therefore, that rare alleles account for more of the genetic risk for common diseases in African-derived populations. Our sequencing study revealed an excess of private and rare SNPs in African Americans with asthma compared with African American control subjects without asthma, suggesting that this may indeed be the case at some loci.

The idea that rare SNPs contribute to common diseases is not new,32, 33, 34 and a number of recent studies have reported excesses of rare, highly penetrant coding SNPs in individuals with cardiovascular disease phenotypes, tuberculosis, colorectal cancer, pancreatitis, folate response, type 1 diabetes, trichotillomania, and obsessive compulsive disorder.35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48 In contrast, we present here for the first time an association between a common disease and rare, noncoding variants. Because relatively few sequencing studies have been conducted in disease susceptibility genes, and because most of those studies focus on coding regions, it is not known whether this is an unusual finding or reflects a shared genetic architecture among asthma or other common disease susceptibility genes in African Americans. Regardless, the finding of an excess of private and rare variants in African American subjects with asthma compared with controls is consistent with the hypothesis that multiple rare variants at disease susceptibility loci contribute to complex disease risk and, if generalizable to other loci, could explain the relatively poor replicability of disease susceptibility loci in African Americans.29, 30, 49, 50, 51 In that case, characterizing the genetic architecture of common diseases in populations of African descent may be particularly challenging.

Currently, the relative contribution of rare genetic variants to asthma risk is unknown. Future resequencing studies of IL4 and additional genes in larger samples of well characterized subjects with asthma and controls are required to address this important question. Our study was limited with respect to sample size and the corresponding low power to detect clinical differences between individuals with and without private or rare SNPs. As a result, we were not able to address the possibility that rare variants in the IL4 gene are markers for clinical subtypes of asthma, such as atopic asthma (based on allergen skin prick tests), steroid-resistant asthma, or childhood versus adult onset. However, resquencing studies in large samples are becoming more feasible with the availability of high-throughput Next Generation sequencing technologies,52 which will enable more comprehensive surveys of rare variations in asthma and other common diseases. A final caveat is that sequencing artifacts caused by the misincorporation of bases during PCR can bias studies of rare variations. We have attempted to minimize this possibility by sequencing each amplicon in both directions and by designing overlapping PCR fragments that would allow the identification of the same variant in independent amplicons. However, even if some were a result of PCR artifacts, we would not expect this to occur more commonly in the subjects with asthma than in the controls. Therefore, we are confident that the excess of rare or private SNPs in subjects with asthma compared with controls in our study is not a result of PCR or sequencing artifacts.

Last, we note that only 2 of the 26 private variants present in our sample (Fig 1) have been reported previously (rs2243272 and rs2243277), and none of the private variants are present on the Affymetrix 6.0 or Illumina 1 M genotyping platforms. Furthermore, only 3 of the 26 private variants are tagged by SNPs on the Illumina 1 M genotyping platform (Table E4). We also find that a greater proportion of private SNPs failed to be correctly imputed at even a single minor allele compared with SNPs that are shared between subjects with asthma and controls, which reflects the challenges of imputing rare alleles in general (Fig E3). Given that our reference and query panels for imputation are perfectly matched (ie, identical samples used in both), our findings represent the best case scenario for a reference panel similar in size to the HapMap CEU and YRI samples. Thus, if an excess of rare or private variation reflects a common mechanism of disease susceptibility in African Americans, genome-wide association studies with 1 million or more SNP genotypes may still miss the majority of susceptibility alleles for common diseases in populations of African descent.

Clinical implications

Rare, noncoding SNPs in IL4 may play an important role in asthma susceptibility in African Americans. This study highlights the importance of resequencing for discovering risk variants in African populations.

Back to Article Outline

Fig E1. 

  • View full-size image.
  • Distribution of genomic European admixture in African American subjects with asthma (n = 54) and controls (n = 58) as estimated from the first principal component (PC) in EIGENSTRAT by using SNPs from the Illumina 1 M genotyping array.

Back to Article Outline

Fig E2. 

  • View full-size image.
  • Local ancestry in African American subjects with asthma (n = 54) and controls (n = 58) at the IL4 locus. The proportion of African ancestry (red) and European ancestry (blue) was estimated using SNPs from the Illumina 1 M genotyping array with the program LAMP.

Back to Article Outline

Fig E3. 

  • View full-size image.
  • Accuracy in imputing the minor allele for SNPs identified from sequencing studies of 112 African American individuals (54 subjects with asthma, 58 controls) as it relates to the MAF in the sample. Accuracy, Number of correctly inferred minor alleles/number of observed minor alleles; Private, SNPs that are unique to either subjects with asthma or controls; Shared, SNPs present in both subjects with asthma and controls; Tagged, IL4 SNPs that are tagged by a SNP on the Illumina 1 M genotyping array with an r2 > 0.5.

Back to Article Outline

Table E1. 

IL4 primer information
NamePrimer sequenceReference positionTm (°C)
IL4_Promoter_Fggcaaaaccttagcaacaca1074958.4
IL4_Promoter_Rgccaatcagcacctctcttc12302
IL4_Exon1_Ftgtggcctctcccttctatg1210958.4
IL4_Exon1_Rattctcagccgtgtgtttcc13722
IL4_Intron1.1_Fcccccacccctctatctgta1360158.4
IL4_Intron1.1_Rggctggattttggaaagatg15261
IL4_Intron2.2_Fbccctgaacttcatcctcctg1508061.8
IL4_Intron2.2_Rbtggcagatttttgcttctgt16663
IL4_Intron2.2_Fccaaaggtggtatgcagaggaa1521161.8
IL4_Intron2.2_Rcaaacgcattgcacagtggta16707
IL4_Intron2.3_Fattctggtgcctcagtctgg1653061.8
IL4_Intron2.3_Rcatttggaggatgggagaga18130
IL4_Exon3_Fcagccttccttcagtggaat1803361.8
IL4_Exon3_Rttgcaagttctgacctctcc19570
IL4_Intron3.1_Faatgaagcaagatggcctgt1912655.5
IL4_Intron3.1_Rtttgcctattttgggtgcat20779
IL4_Exon4_Ftcaagttccaccctctgagc2064761.8
IL4_Exon4_Ratggaaagccgaaagtctcc22177
IL4_Exon4_Fagctgtgacacacctctccag2067661.8
IL4_Exon4_Ratttcacccctccttagtcca22150
IL4_Intron4.1_Fgggttccctctcgagttagg2129555.5
IL4_Intron4.1_Rtacagcagcgcagtcatagc22786
IL4_VE_Facgagtatggcagggaacac1893461.8
IL4_VE_Raccgatctgtcagcaaatcc19321
IL4_Promoter_Finternalgggaaggttctgggagaaaa1114755.5

Reference position is with respect to the start of the reference sequence.

Back to Article Outline

Table E2. 

IL4 polymorphisms
SNP IDPosition with respect to ATGAncestral alleleDerived alleleDerived allele frequency in the total sampleDerived allele frequency in subjects with asthmaDerived allele frequency in controls without asthma
−1665GA0.0540.0700.037
−1621GA0.0070.0000.014
rs10080170−1608TG0.8790.9100.848
-1603CG0.0040.0070.000
−1587GA0.0350.0350.036
−1543GA0.0140.0070.022
rs10065221−1535AG0.0850.0560.116
rs10058157−1532TC0.1670.1320.203
rs2243242−1508G0.3770.3550.400
rs2243247−1137GA0.1760.1760.177
rs2243248−1099TG0.1580.1550.162
rs2243249−1046TC0.0260.0210.030
-996TC0.0070.0140.000
−869AC0.0040.0000.008
-593TC0.0070.0140.000
rs2243250−589CT0.6910.7040.677
rs2070874−33TC0.5800.5420.619
rs224325144AG0.1830.1900.176
240GA0.0040.0000.007
612CT0.0070.0140.000
708CT0.0040.0070.000
rs2243252845TC0.0220.0210.023
856GA0.0040.0070.000
969CT0.0040.0070.000
rs734244983CT0.4190.4580.377
rs22432531018CT0.1390.1340.144
1113CT0.0110.0070.015
1304CT0.0140.0140.014
1420GC0.0040.0070.000
rs114791981424C0.4260.4410.410
2187TC0.0150.0230.008
2307AG0.0190.0220.015
rs22432582401CT0.0300.0360.024
rs22432592402CT0.0190.0210.016
2992CA0.0140.0220.007
rs22272843017TG0.1310.1160.147
rs22432603041AT0.0150.0140.015
rs22432613097GT0.1640.1670.162
3150TC0.0260.0360.015
3212GA0.0040.0000.007
3261GC0.0040.0000.008
3384GA0.0040.0070.000
3407TC0.0040.0070.000
3444GA0.0040.0070.000
rs22272823470CG0.1180.1140.121
rs22432633590GC0.1740.1670.182
3675CT0.0080.0070.008
3726CA0.0370.0500.023
rs22432643938AG0.0180.0210.015
rs22432654000CA0.0190.0140.023
rs22432664080GA0.3430.3710.313
4142TA0.0040.0070.000
rs22432674177GC0.3530.3710.333
rs22432684254AC0.2750.2970.254
rs92827454291TA0.0470.0510.043
rs92827464294GA0.0510.0430.058
rs22432694303AA0.2740.2840.265
rs22432704400AG0.6730.6570.689
4470TC0.0110.0150.007
rs22432714590GA0.0370.0430.030
rs22432724614GT0.0110.0230.000
rs22432735051CT0.0510.0430.058
rs22432745123AG0.4040.3680.441
rs22432755212TC0.0220.0290.014
rs22432765262TC0.0070.0070.007
rs22432775342CT0.0040.0070.000
5976CG0.0040.0070.000
rs22432786058ACTAAAGACACGCAGGCCGAGTC0.0180.0210.014
65661 copy2 or 3 copies0.6500.6320.669
rs22432816686TC0.0670.0450.088
rs22432857284GT0.1640.1440.184
7767CT0.0040.0070.000
7999GC0.0110.0140.007
rs22432868043CT0.0290.0290.029
rs22432878082GC0.0140.0140.014
8214CG0.0040.0000.007
rs22432888235AG0.6380.6790.596
rs22432898423AG0.2700.3010.239
rs22432908460CA0.3390.3750.304
8968CT0.0360.0500.022
8982TC0.0070.0140.000
9040CT0.0370.0500.023
9226TC0.0110.0140.008
9274CG0.4040.3570.455
9332TC0.0040.0000.008
9512TC0.0410.0430.039
9874CT0.0110.0140.007
10082AG0.6220.6430.601
10098GA0.3310.3000.362
10099TC0.0040.0070.000
10173AC0.0290.0430.015
10238CT0.0040.0000.007

Private SNPs found only in subjects with asthma appear in boldface. RS numbers are given for polymorphisms previously reported in dbSNP.

The variable element is triallelic in the general population. Only 2 and 3 copies of the variable element were found in our population. The 2-copy allele is taken as the derived allele in this table.

Back to Article Outline

Table E3. 

Number of individuals with private SNPs in admixed and nonadmixed African Americans at the IL4 locus
AdmixedNonadmixed
Controls (P = .71)
With private SNP35
Without private SNP2624
Subjects with asthma (P = 1.0)
With private SNP69
Without private SNP1621

Admixed individuals are those inferred as having <2 African chromosomes at the IL4 locus.

Back to Article Outline

Table E4. 

Number of IL4 SNPs identified from sequencing studies of 112 African Americans that are tagged by a SNP on the Illumina 1 M genotyping array (r2 > 0.5; within 500 kb upstream and downstream of the transcription start and stop site)
PrivateShared (rare)
Subjects with asthma (rare)Controls (rare)
Tagged, r2 > 0.51 (1)2 (2)16 (3)
Untagged13 (13)5 (5)43 (31)

The number in parentheses represents the subset of rare SNPs in the cell counts (MAF < 5%).

Back to Article Outline

Table E5. 

Number of IL4 SNPs identified from sequencing studies of 112 African Americans that failed to be correctly imputed at even a single minor allele by using genotypes from the Illumina 1 M genotyping platform (accuracy = 0)
Private: subjects with asthma (rare)Private: controls (rare)Shared (rare)
Accuracy = 07 (7)5 (5)1 (1)
Accuracy > 07 (7)2 (2)58 (32)

Accuracy was defined as the number of times the minor allele was correctly imputed/the number of minor alleles observed in the data. The number in parentheses represents the subset of rare SNPs in the sample (MAF < 5%).

Back to Article Outline

References 

  1. Finkelman FD, Holmes J, Katona IM, Urban JF, Beckmann MP, Park LS, et al. Lymphokine control of in vivo immunoglobulin isotype selection. Annu Rev Immunol. 1990;8:303–333
  2. Murphy KM, Reiner SL. The lineage decisions of helper T cells. Nat Rev Immunol. 2002;2:933–944
  3. Lynch NR, Hagel IA, Palenque ME, Di Prisco MC, Escudero JE, Corao LA, et al. Relationship between helminthic infection and IgE response in atopic and nonatopic children in a tropical environment. J Allergy Clin Immunol. 1998;101:217–221
  4. Rosenwasser LJ, Klemm DJ, Dresback JK, Inamura H, Mascali JJ, Klinnert M, et al. Promoter polymorphisms in the chromosome-5 gene-cluster in asthma and atopy. Clin Exp Allergy. 1995;25:74–78
  5. Ober C, Hoffjan S. Asthma genetics 2006: the long and winding road to gene discovery. Genes Immun. 2006;7:95–100
  6. Blackwell JM, Mohamed HS, Ibrahim ME. Genetics and visceral leishmaniasis in the Sudan: seeking a link. Trends Parasitol. 2004;20:268–274
  7. Gatlin MR, Black CL, Mwinzi PN, Secor WE, Karanja DM, Colley DG. Association of the gene polymorphisms IFN-gamma +874, IL-13-1055 and IL-4 -590 with patterns of reinfection with Schistosoma mansoni. PLoS Negl Trop Dis. 2009;3:e375
  8. Basehore MJ, Howard TD, Lange LA, Moore WC, Hawkins GA, Marshik PL, et al. A comprehensive evaluation of IL4 variants in ethnically diverse populations: association of total serum IgE levels and asthma in white subjects. J Allergy Clin Immunol. 2004;114:80–87
  9. Donfack J, Schneider DH, Tan Z, Kurz T, Dubchak I, Frazer KA, et al. Variation in conserved non-coding sequences on chromosome 5q and susceptibility to asthma and atopy. Respir Res. 2005;6:145
  10. Kabesch M, Tzotcheva I, Carr D, Hofler C, Weiland SK, Fritzsch C, et al. A complete screening of the IL4 gene: novel polymorphisms and their association with asthma and IgE in childhood. J Allergy Clin Immunol. 2003;112:893–898
  11. SeattleSNPs. NHLBI HL66682 Program for Genomic Applications, UW-FHCRC, Seattle, WA (URL: http://pga.gs.washington.edu) Accessed June 2009.
  12. Sherry ST, Ward MH, Kholodov M, Baker J, Phan L, Smigielski EM, et al. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 2001;29:308–311
  13. Lohmueller KE, Indap AR, Schmidt S, Boyko AR, Hernandez RD, Hubisz MJ, et al. Proportionally more deleterious genetic variation in European than in African populations. Nature. 2008;451:994–997
  14. Tishkoff SA, Williams SM. Genetic analysis of African populations: human evolution and complex disease. Nat Rev Genet. 2002;3:611–621
  15. Thompson JD, Higgins DG, Gibson TJ. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 1994;22:4673–4680
  16. Nickerson DA, Tobe VO, Taylor SL. PolyPhred: automating the detection and genotyping of single nucleotide substitutions using fluorescence-based resequencing. Nucleic Acids Res. 1997;25:2745–2751
  17. Chouchane L, Sfar I, Bousaffara R, El Kamel A, Sfar MT, Ismail A. A repeat polymorphism in interleukin-4 gene is highly associated with specific clinical phenotypes of asthma. Int Arch Allergy Immunol. 1999;120:50–55
  18. Nagarkatti R, Kumar R, Sharma SK, Ghosh B. Association of IL4 gene polymorphisms with asthma in North Indians. Int Arch Allergy Immunol. 2004;134:206–212
  19. Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21:263–265
  20. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81:559–575
  21. Madsen BE, Browning SR. A groupwise association test for rare mutations using a weighted sum statistic. PLoS Genet. 2009;5:e1000384
  22. Tajima F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics. 1989;123:585–595
  23. Watterson GA. On the number of segregating sites in genetical models without recombination. Theor Popul Biol. 1975;7:256–276
  24. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38:904–909
  25. Sankararaman S, Sridhar S, Kimmel G, Halperin E. Estimating local ancestry in admixed populations. Am J Hum Genet. 2008;82:290–303
  26. Li Y, Willer CJ, Sanna S, Abecasis GR. Genotype Imputation. Annu Rev Genomics Hum Genet. 2009;10:387–406
  27. Centers for Disease Control and Prevention. National Center for Health Statistics. Available at: http://www.cdc.gov/asthma/asthmadata.htm. Accessed June 2, 2009.
  28. Barnes KC, Grant AV, Hansel NN, Gao P, Dunston GM. African Americans with asthma: genetic insights. Proc Am Thorac Soc. 2007;4:58–68
  29. Himes BE, Hunninghake GM, Baurley JW, Rafaels NM, Sleiman P, Strachan DP, et al. Genome-wide association analysis identifies PDE4D as an asthma-susceptibility gene. Am J Hum Genet. 2009;84:581–593
  30. Xu X, Fang Z, Wang B, Chen C, Guang W, Jin Y, et al. A genomewide search for quantitative-trait loci underlying asthma. Am J Hum Genet. 2001;69:1271–1277
  31. Carlson CS, Thomas DJ, Eberle MA, Swanson JE, Livingston RJ, Rieder MJ, et al. Genomic regions exhibiting positive selection identified from dense genotype data. Genome Res. 2005;15:1553–1565
  32. Bodmer W, Bonilla C. Common and rare variants in multifactorial susceptibility to common diseases. Nat Genet. 2008;40:695–701
  33. Iyengar SK, Elston RC. The genetic basis of complex traits: rare variants or “common gene, common disease”?. Methods Mol Biol. 2007;376:71–84
  34. Pritchard JK. Are rare variants responsible for susceptibility to complex diseases?. Am J Hum Genet. 2001;69:124–137
  35. Ahituv N, Kavaslar N, Schackwitz W, Ustaszewska A, Martin J, Hebert S, et al. Medical sequencing at the extremes of human body mass. Am J Hum Genet. 2007;80:779–791
  36. Azzopardi D, Dallosso AR, Eliason K, Hendrickson BC, Jones N, Rawstorne E, et al. Multiple rare nonsynonymous variants in the adenomatous polyposis coli gene predispose to colorectal adenomas. Cancer Res. 2008;68:358–363
  37. Cohen J, Pertsemlidis A, Kotowski IK, Graham R, Garcia CK, Hobbs HH. Low LDL cholesterol in individuals of African descent resulting from frequent nonsense mutations in PCSK9. Nat Genet. 2005;37:161–165
  38. Cohen JC, Boerwinkle E, Mosley TH, Hobbs HH. Sequence variations in PCSK9, low LDL, and protection against coronary heart disease. N Engl J Med. 2006;354:1264–1272
  39. Cohen JC, Kiss RS, Pertsemlidis A, Marcel YL, McPherson R, Hobbs HH. Multiple rare alleles contribute to low plasma levels of HDL cholesterol. Science. 2004;305:869–872
  40. Cohen JC, Pertsemlidis A, Fahmi S, Esmail S, Vega GL, Grundy SM, et al. Multiple rare variants in NPC1L1 associated with reduced sterol absorption and plasma low-density lipoprotein levels. Proc Natl Acad Sci U S A. 2006;103:1810–1815
  41. Ji W, Foo JN, O'Roak BJ, Zhao H, Larson MG, Simon DB, et al. Rare independent mutations in renal salt handling genes contribute to blood pressure variation. Nat Genet. 2008;40:592–599
  42. Kotowski IK, Pertsemlidis A, Luke A, Cooper RS, Vega GL, Cohen JC, et al. A spectrum of PCSK9 alleles contributes to plasma levels of low-density lipoprotein cholesterol. Am J Hum Genet. 2006;78:410–422
  43. Ma X, Liu Y, Gowen BB, Graviss EA, Clark AG, Musser JM. Full-exon resequencing reveals toll-like receptor variants contribute to human susceptibility to tuberculosis disease. PLoS ONE. 2007;2:e1318
  44. Marini NJ, Gin J, Ziegle J, Keho KH, Ginzinger D, Gilbert DA, et al. The prevalence of folate-remedial MTHFR enzyme variants in humans. Proc Natl Acad Sci U S A. 2008;105:8055–8060
  45. Masson E, Chen JM, Scotet V, Le Marechal C, Ferec C. Association of rare chymotrypsinogen C (CTRC) gene variations in patients with idiopathic chronic pancreatitis. Hum Genet. 2008;123:83–91
  46. Nejentsev S, Walker N, Riches D, Egholm M, Todd JA. Rare variants of IFIH1, a gene implicated in antiviral responses, protect against type 1 diabetes. Science. 2009;324:387–389
  47. Romeo S, Pennacchio LA, Fu Y, Boerwinkle E, Tybjaerg-Hansen A, Hobbs HH, et al. Population-based resequencing of ANGPTL4 uncovers variations that reduce triglycerides and increase HDL. Nat Genet. 2007;39:513–516
  48. Zuchner S, Wendland JR, Ashley-Koch AE, Collins AL, Tran-Viet KN, Quinn K, et al. Multiple rare SAPAP3 missense variants in trichotillomania and OCD. Mol Psychiatry. 2009;14:6–9
  49. Gudbjartsson DF, Walters GB, Thorleifsson G, Stefansson H, Halldorsson BV, Zusmanovich P, et al. Many sequence variants affecting diversity of adult human height. Nat Genet. 2008;40:609–615
  50. Gudmundsson J, Sulem P, Manolescu A, Amundadottir LT, Gudbjartsson D, Helgason A, et al. Genome-wide association study identifies a second prostate cancer susceptibility variant at 8q24. Nat Genet. 2007;39:631–637
  51. Thorleifsson G, Walters GB, Gudbjartsson DF, Steinthorsdottir V, Sulem P, Helgadottir A, et al. Genome-wide association yields new sequence variants at seven loci that associate with measures of obesity. Nat Genet. 2009;41:18–24
  52. Mardis ER. The impact of next-generation sequencing technology on genetics. Trends Genet. 2008;24:133–141

 Supported by R01 HL72414, U01 HL049596, and M01 RR00055. D.G.T. is supported by R01 HL087665 and U10 HL064313. E.E.T. is supported by T32 HL007605.

 Disclosure of potential conflict of interest: The authors have declared that they have no conflict of interest.

PII: S0091-6749(09)01401-8

doi:10.1016/j.jaci.2009.09.013

The Journal of Allergy and Clinical Immunology
Volume 124, Issue 6 , Pages 1204-1209.e9, December 2009