Literature DB >> 24324648

Genome-wide association study for levels of total serum IgE identifies HLA-C in a Japanese population.

Yohei Yatagai1, Tohru Sakamoto, Hironori Masuko, Yoshiko Kaneko, Hideyasu Yamada, Hiroaki Iijima, Takashi Naito, Emiko Noguchi, Tomomitsu Hirota, Mayumi Tamari, Yoshimasa Imoto, Takahiro Tokunaga, Shigeharu Fujieda, Satoshi Konno, Masaharu Nishimura, Nobuyuki Hizawa.   

Abstract

Most of the previously reported loci for total immunoglobulin E (IgE) levels are related to Th2 cell-dependent pathways. We undertook a genome-wide association study (GWAS) to identify genetic loci responsible for IgE regulation. A total of 479,940 single nucleotide polymorphisms (SNPs) were tested for association with total serum IgE levels in 1180 Japanese adults. Fine-mapping with SNP imputation demonstrated 6 candidate regions: the PYHIN1/IFI16, MHC classes I and II, LEMD2, GRAMD1B, and chr13∶60576338 regions. Replication of these candidate loci in each region was assessed in 2 independent Japanese cohorts (n = 1110 and 1364, respectively). SNP rs3130941 in the HLA-C region was consistently associated with total IgE levels in 3 independent populations, and the meta-analysis yielded genome-wide significance (P = 1.07×10(-10)). Using our GWAS results, we also assessed the reproducibility of previously reported gene associations with total IgE levels. Nine of 32 candidate genes identified by a literature search were associated with total IgE levels after correction for multiple testing. Our findings demonstrate that SNPs in the HLA-C region are strongly associated with total serum IgE levels in the Japanese population and that some of the previously reported genetic associations are replicated across ethnic groups.

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Year:  2013        PMID: 24324648      PMCID: PMC3851760          DOI: 10.1371/journal.pone.0080941

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Immunoglobulin E (IgE) is a class of antibodies that has an important role in the development of Th2 cell-mediated allergic inflammatory diseases such as asthma, allergic rhinitis, and atopic dermatitis. In atopic individuals, exposure to allergens results in Th2 cell-dependent stimulation of the immune response that causes production of IgE. Recent advances in the understanding of allergen sensitization have also revealed the sentinel role of innate immune mechanisms involved in the development of allergic diseases [1], [2]. Twin and family studies have shown that genetic factors are important for total serum IgE levels [3], [4] and account for about 36% to 78% heritability of its levels [3], [5]. Furthermore, it has been demonstrated that total serum IgE levels are mainly determined by genetic factors that are independent of antigen-specific IgE levels or atopic status [4], [6], [7]. Asthma affection status is known to be related to total serum IgE levels even after adjustment for atopic status [8], [9]. Thus far, a number of candidate gene association studies for total serum IgE levels have demonstrated many polymorphisms in genetic regions related to the Th2 cell-dependent pathways. Recently, 4 genome-wide association studies (GWASs) of total serum IgE levels in independent populations have revealed additional genetic loci, such as TBX18 and SOBP, which seem to be unrelated to the Th2 cell-dependent pathways [10]–[13]. Thus, because GWASs are unbiased by investigator preconceptions, they have the potential of providing new insights into the mechanism of IgE regulation and may be able to clarify unexpected IgE-related genetic loci. Three of the 4 GWASs of total IgE levels reported so far were conducted solely in populations of European ancestry, and the fourth of those studies also included African-American and Latino populations. In contrast, 2 GWASs recently performed in Asian populations did not identify any loci significantly associated with total serum IgE levels [14], [15]. In genetic association studies, replication of the initial findings in different ethnic groups is important to clarify the relevance of the findings. Here, we performed a GWAS of total serum IgE levels in a Japanese population and a replication analysis in 2 independent Japanese cohorts that was followed by a meta-analysis. In addition, we validated previously reported gene associations with total serum IgE levels using our GWAS data.

Results

Study Flow Chart

A flow chart outlining the steps of this study is shown in Figure S1.

Characteristics of the Study Cohorts

The characteristics of the original GWAS cohort and the replication cohorts are provided in Table 1. The ratio of female participants was higher in the Fukui cohort than in the Tsukuba and Hokkaido cohorts. The Tsukuba and Hokkaido cohorts included more asthmatic patients than did the Fukui cohort. Age, sex, asthma affection status, atopic status, and IgE levels differed significantly among the cohorts.
Table 1

Characteristics of the study cohorts.

Tsukuba cohort (n = 1180)Hokkaido cohort (n = 1110)Fukui cohort (n = 1364)
Age, y (SD)50.3 (10.4)44.6 (16.0)32.2 (9.8)
Female sex55.3%49.3%67.0%
Smoking status
Current smoker16.2%26.1%NA
Ex-smoker17.5%16.7%NA
Never smoker66.2%57.2%NA
Asthma18.1%44.2%6.5%
Atopy
Atopic56.6%53.7%67.2%
Nonatopic40.5%29.5%30.5%
Unknown2.9%16.8%2.3%
Log10 [total serum IgE] (SD)1.82 (0.60)2.08 (0.69)1.91 (0.62)

NA = not applicable; SD = standard deviation.

NA = not applicable; SD = standard deviation.

GWAS and Replication Analyses

A quantile-quantile plot is shown in Figure 1. The genomic inflation factor of 1.018 indicated a low possibility of false-positive associations resulting from population stratification. A Manhattan plot of the GWAS (Figure 2) showed no SNPs reaching the genome-wide significance threshold of 5.0×10−8. We focused on 4 distinct chromosomal regions in which P values were less than 1.0×10−5: chromosomes 1q23, 6p21, 11q24, and 13q21. Genotypes were imputed to determine the contribution of untyped SNPs to total IgE levels in these regions. Fine-mapping coupled with the imputed SNPs identified 6 candidate genomic regions (Figure 3): the PYHIN1/IFI16 region on chromosome 1q23.1 (chr1∶157229979; P = 3.19×10−7), the MHC class I and II regions on chromosome 6p21.3 (rs9264567, P = 2.33×10−7 and rs9271682, P = 1.55×10−7, respectively), the LEMD2 region on 6p21.31 (rs12173787, P = 7.03×10−8), the GRAMD1B region on chromosome 11q24.1 (rs2078158, P = 6.57×10−7), and the chr13∶60576338 region on chromosome 13q21.31 (rs1399315, P = 6.40×10−7). For each candidate region, we conducted a replication study using validated ready-to-use TaqMan® SNP Genotyping assays. The SNPs available for the replication studies are shown in Figure 3. Table 2 shows the association of these SNPs with total serum IgE levels in the primary Tsukuba cohort and the 2 replication cohorts. The association of rs3130941 in the MHC class I region was consistently replicated in both the Hokkaido and the Fukui cohort. Meta-analysis of the primary and the 2 replication cohorts demonstrated that rs3130941 in the MHC class I region reached the level of genome-wide significance at 1.07×10−10. Rs28366296 in the MHC class II region was replicated in the Hokkaido cohort only. Rs7939777 in the GRAMD1B region was replicated in the Fukui cohort only. As for rs7939777, a meta-analysis using the Tsukuba and Fukui cohorts yielded a P value of 3.35×10−10.
Figure 1

Quantile-quantile (Q-Q) plot of observed versus expected P values of the GWAS results.

The straight line in the Q-Q plot indicates the distribution of SNPs under the null hypothesis.

Figure 2

Manhattan plots of −log10 (P value) for association of 479,940 SNPs with total IgE levels.

Linear regression models adjusted for age, sex, smoking status (never, ex-, or current smoker), pack-year group (0, 0–10, or >10), and asthma affection status were performed. The red line shows the threshold (P = 1×10−5) for selection of genomic regions for further analysis including SNP imputation.

Figure 3

Fine-mapping identification of 6 candidate genomic regions.

Plots show the association results of both genotyped and imputed SNPs in the primary GWAS cohort. The most strongly associated SNPs (black letters) in the GWAS and the SNPs used for the replication studies (red letters) are indicated by arrows. The color of each circle reflects the LD (r2) between a particular SNP and the SNP used for the replication studies.

Table 2

Replication studies and meta-analysis.

Tsukuba cohortHokkaidocohortFukuiCohortMeta-analysis
Top SNP
ChromosomeGeneSNP forreplicationstudy P valueLD withtop SNP(r2)MAFMinoralleleβ P value P value P value
1q23.1 PYHIN1/IFI16 chr1∶1572299793.19E-0710.16G−0.168
rs37544665.65E-050.6370.20C−0.1190.2440.2220.378
6p21.3MHC class Irs92645672.33E-0710.28A0.132
rs31309412.28E-040.5490.25C0.0985.03E-046.12E-051.07E-10
6p21.3MHC class IIrs92716821.55E-0710.48A0.127
rs283662962.67E-050.6080.39A−0.0984.15E-025.44E-022.17E-05
6p21.31 LEMD2 rs121737877.03E-0810.17G0.161
rs9434741.30E-060.7860.16G0.1575.56E-020.3082.29E-02
11q24.1 GRAMD1B rs20781586.57E-0710.41A−0.118
rs79397771.13E-060.9430.42C−0.1147.63E-02* 7.58E-050.263
13q21.31noners13993156.40E-0710.48C0.114
rs31065989.51E-070.9970.48G0.1120.8170.8130.326

The direction of the effect was opposite to that of the Tsukuba cohort.

LD = linkage disequilibrium; MAF = minor allele frequency.

Quantile-quantile (Q-Q) plot of observed versus expected P values of the GWAS results.

The straight line in the Q-Q plot indicates the distribution of SNPs under the null hypothesis.

Manhattan plots of −log10 (P value) for association of 479,940 SNPs with total IgE levels.

Linear regression models adjusted for age, sex, smoking status (never, ex-, or current smoker), pack-year group (0, 0–10, or >10), and asthma affection status were performed. The red line shows the threshold (P = 1×10−5) for selection of genomic regions for further analysis including SNP imputation.

Fine-mapping identification of 6 candidate genomic regions.

Plots show the association results of both genotyped and imputed SNPs in the primary GWAS cohort. The most strongly associated SNPs (black letters) in the GWAS and the SNPs used for the replication studies (red letters) are indicated by arrows. The color of each circle reflects the LD (r2) between a particular SNP and the SNP used for the replication studies. The direction of the effect was opposite to that of the Tsukuba cohort. LD = linkage disequilibrium; MAF = minor allele frequency. When we repeated the meta-analyses by studying nonasthmatic healthy individuals only (n = 2861) or by adding atopic sensitization as an additional covariate, we confirmed the association between rs3130941 in the MHC class I region and levels of total serum IgE at genome-wide significance (Table S1 and Table S2).

Validation of Previous Genetic Associations

The PubMed search identified 448 related publications. After screening of the titles, abstracts, and text, 156 eligible publications were selected. Screening of the references of those publications identified 33 additional relevant publications. From the 189 selected publications, we found 32 candidate genes associated with total serum IgE levels; 25 of those genes were reported in 3 or more candidate gene association studies, and 7 (DARC, HLA-A, HLA-DQA2, HLA-G, RAD50, SOBP, and TBX18) were reported in at least 1 GWAS. Table 3 shows the SNP most significantly associated with total IgE levels in our GWAS data of each candidate gene on an autosomal chromosome. Nominal P values were less than 0.05 for 17 of the 32 candidate genes, including HLA-C. After corrections for multiple testing using SNPSpD software [16], the associations of 9 genes with total IgE levels remained significant. The strongest associations were detected at the genes in the MHC class I/II regions, including LTA on chromosome 6p21.3, although none of the top SNPs reached genome-wide significance. Previously reported polymorphisms associated with total serum IgE levels are shown in Table S3.
Table 3

Top SNPs with the strongest statistical evidence of association with total serum IgE levels.

GeneChromosomeNumber of SNPsSNPNominal P valueCorrected P value*
ADAM33 2012rs28532151.66E-020.150
ADRB2 517rs176405747.27E-020.728
CCL11 177rs65054030.2250.898
CD14 58rs38223560.7191
CMA1 149rs19569320.1791
CTLA4 23rs2317261.21E-022.31E-02
DARC 13rs8630020.3940.789
FCER1A 19rs24278243.06E-020.184
FLG 13rs31260850.2880.577
GSTP1 113rs6140800.7661
HLA-A 62rs27349596.64E-031.33E-02
HLA-C 626rs31324861.50E-041.88E-03
HLA-DQA2 624rs175004687.94E-058.06E-04
HLA-DQB1 611rs26470257.48E-053.74E-04
HLA-DRB1 666rs354655568.51E-051.83E-03
HLA-G 621rs16330537.58E-034.56E-02
IFNG 124rs31810323.56E-020.104
IL10 18rs18008960.1100.660
IL13 54rs1295686 7.41E-020.216
IL4 55rs22432882.08E-038.34E-03
IL4R 1623rs47879480.2191
LTA 612rs28577094.24E-052.97E-04
MS4A2 114rs5747000.2010.602
NOD2 166rs71948860.1560.468
NOS1 1245rs47675358.60E-030.235
NPSR1 766rs3239283.29E-020.867
RAD50 57rs177725831.82E-027.29E-02
SOBP 641rs37347475.43E-030.135
STAT6 127rs8417180.1710.854
TBX18 65rs20155193.71E-020.146
TLR2 44rs76564110.3280.983
TNF 611rs28444847.96E-020.478

The significance level was corrected for multiple testing using the SNPSpD program [16].

SNP previously reported for association with total serum IgE (the direction of the effect was the same).

The significance level was corrected for multiple testing using the SNPSpD program [16]. SNP previously reported for association with total serum IgE (the direction of the effect was the same).

Discussion

To the best of our knowledge, ours is the first GWAS that demonstrates positive results for levels of total serum IgE in an Asian population. In our primary GWAS cohort, fine-mapping using the imputed SNPs on chromosome 6p revealed 3 independent peaks: the MHC class I, MHC class II, and LEMD2 regions (Figure S2). In the meta-analysis, rs3130941 in the MHC class I region reached levels of genome-wide significance. This finding was not significantly influenced by the presence or absence of asthma or atopy. Rs3130941 is located between HLA-C and HCG27 (HLA complex group 27) (Figure 3). In the MHC class I region, 4 genes have been previously reported to be associated with total serum IgE levels: HLA-A (rs2517754, rs2571391), HLA-G (rs2523809), LTA (rs909253), and TNF (rs1800629, rs361525, rs1800630) [12], [17]–[22]. Linkage disequilibrium (LD) between rs3130941 and each of these SNPs estimated by r2 in our population was very weak (Table S4, Figure S3). Furthermore, the association of rs3130941 with total IgE levels was not influenced by inclusion of each of these SNPs in the statistical model as a covariate (Table S4). Therefore, rs3130941 in the HLA-C region is associated with total serum IgE levels independent of the genetic influence of HLA-A, HLA-G, LTA, or TNF. With respect to the functional consequence of rs3130941, the GENEVAR database (http://www.sanger.ac.uk/humgen/genevar/) [23] revealed that rs3094609 and rs3130931, both of which are in weak LD with rs3130941 (r2 = 0.566 and 0.324, respectively), are significantly associated with expression levels of HLA-C mRNA (P = 0.0495 and 0.00521, respectively), suggesting that rs3130941 may also be related to HLA-C expression. The MHC class II region is another candidate for regulation of IgE levels because MHC class II molecules are importantly involved in antigen-specific IgE synthesis [24]. Three genes in the MHC class II region have been reported to be associated with total IgE levels: HLA-DQA2, HLA-DQB1, and HLA-DRB1. In our primary GWAS, associations of SNPs in these genes were replicated (Table 3). Because the MHC class I and II regions are in very close proximity on chromosome 6p21.3, we examined whether the genetic impact of rs3130941 in the MHC class I region was influenced by rs28366296 in the MHC class II region. Although both rs3130941 and rs28366296 showed a strong association with total IgE levels in our study, the LD between these 2 SNPs was weak (Table S4) and a linear regression model including these 2 SNPs showed that each genetic association maintained significance after controlling for the effect of each of the remaining SNPs (Table S4). Therefore, we believe that the association of rs3130941 with total serum IgE levels is independent of the effects of MHC class II genes. A set of specific infections that strongly promote Th1 and natural killer (NK) cells likely has the potential to inhibit atopic disorder by repression of Th2 immunity. Among Japanese schoolchildren, positive tuberculin responses predicted a lower incidence of asthma, lower serum IgE levels, and biased Th1 cytokine profiles [25]. MHC class I-restricted CD8 T cells collaborate with CD4 Th1 cells to invoke Th1-type immunity, thereby counteracting CD4 Th2 cells, which results in inhibition of IgE production [26], [27]. HLA-C molecules also modulate NK cell function [28]. NK cytotoxicity is negatively controlled by inhibitory receptors, such as human killer cell Ig-like receptors (KIRs) specific for HLA-B and HLA-C [29]. Accordingly, as an intrinsic abnormality, impaired HLA-C-mediated triggering of protective immunity to microbial exposure would predispose an individual to increased levels of total serum IgE as a principal determinant of allergy. Although localizing the causal effects of the genes within the MHC region has been limited by the complexity and strong LD of this region, the genetic association between the MHC region and several immune and inflammatory diseases has been among the most robust. The HLA-C region has been associated particularly with Behçet disease, psoriasis, and sarcoidosis [30]–[32]. Of note, dysregulation of IgE has been reported in these diseases [33]–[35], which may also imply that HLA-C is involved in the genetic regulation of total IgE levels. Finally, it is also interesting to note that 1 locus (rs9266772) near HLA-C and MICA has been recently identified as one of the loci of allergy-specific susceptibility [36]. The meta-analysis of rs7939777 in GRAMD1B using the Tsukuba and Fukui cohorts yielded a P value of 3.35×10−10. Interestingly, although no studies demonstrated a relationship between GRAMD1B and serum IgE levels, a GWAS has identified a SNP near GRAMD1B on chromosome 11q24.1 associated with chronic lymphocytic leukemia (CLL) [37]. CLL is characterized by coexpression of CD19 and CD23 coupled with low levels of surface immunoglobulins [38]. CD23, also known as FCER2, is a low-affinity receptor for IgE and important for regulation of serum IgE levels. In addition, total serum IgE levels are inversely associated with risk of CLL [39]. Accordingly, polymorphisms of GRAMD1B could be related to regulation of total serum IgE levels. Although the SNP in the PYHIN1/IFI16 region did not reach genome-wide significance in the primary GWAS (P = 3.19×10−7), a recent meta-analysis of GWASs of asthma has identified a SNP in PYHIN1 in populations of African descent [40]. PYHIN1 and IFI16 have recently emerged as sensors of microbial DNA [41], and the innate immune response relies on the ability of immune cells to detect the presence of infection through these germline-encoded pattern recognition receptors. Given that environments with a wide range of microbial exposures are associated with protection from childhood asthma and atopy in proportion to their level of exposure to bacterial and fungal microbes [42], PYHIN1 and IFI16 deserve further attention as candidate genes for association with asthma and atopy. We have here tried to validate previously reported gene associations with IgE regulation. Among 32 autosomal genes, which were previously identified mainly in European populations, we found that 9 (28.1%) were replicated in a Japanese population after correction for multiple testing, indicating that some of the candidate genes for association with total serum IgE levels are effective across ethnic groups. Heterogeneity seems to exist in the genetic factors for total serum IgE levels among different ethnic groups [13], [43]. For SNPs that were not replicated in our study, causal SNPs for IgE regulation or SNPs tightly in LD with the causal SNPs may not exist in the regions analyzed in the Japanese population. Alternatively, our study sample size may have not have provided a significant power to detect the associations due to low minor allele frequencies of the true causal SNPs. In terms of the limitations of this study, because we chose only 1 SNP for each region to replicate the original findings in the discovery cohort, we cannot exclude the possibility that we have missed true functional genetic variants in the replication cohorts. In addition, we observed many differences in the population characteristics of the discovery cohort and of the replication cohorts, including in the proportion of asthmatic patients and levels of total serum IgE. These differences might have affected our results, especially because the genetic background for increased levels of total IgE may differ in nonasthmatic healthy individuals and in asthmatic patients [44]. Nevertheless, analyses excluding asthmatic patients produced similar results with genome-wide significance for the HLA-C region, indicating the robustness of our findings. As the mechanisms mediating the risk conferred by the HLA-C region remains to be found, future studies will identify the causal genes/variants within the susceptibility loci associated with levels of total serum IgE by fine-mapping and by investigating the biological link between rs3130941/HLA-C and regulation of IgE production. In summary, we performed a GWAS showing positive results for total serum IgE levels for the first time in an Asian population. Association of a SNP in the HLA-C region with total serum IgE levels reached genome-wide significance in our meta-analysis involving a total of 3654 Japanese adults. We also demonstrated that some of the previously reported genetic associations with total serum IgE levels were replicated across ethnicities.

Materials and Methods

Ethical Statement

This study was approved by the Human Genome Analysis and Epidemiology Research Ethics Committee of the University of Tsukuba and by the Human Genome/Gene Analysis Research Ethics Review Committees of the Tsukuba Medical Center, RIKEN, the Hokkaido University School of Medicine, and the University of Fukui. Written informed consent was obtained from each participant in accordance with institutional requirements and the principles of the Declaration of Helsinki.

Study Participants

The discovery cohort (Tsukuba cohort) consisted of 1180 individuals of Japanese ethnicity (967 healthy volunteers and 213 patients with asthma). The healthy volunteers without pulmonary diseases such as asthma and COPD were originally recruited for a genetic study of pulmonary function from the general population who visited the Tsukuba Medical Center for an annual health checkup [45]. All the participants were asked about their respiratory health, medical history, lifestyle, and exposure to environmental irritants (eg, cigarette smoke, allergens, and air pollution) and underwent heart and lung auscultation. The patients with asthma were recruited for genetic analysis of asthma from the Tsukuba University Hospital and its affiliated hospitals [46]. Asthma was diagnosed by pulmonary physicians according to the American Thoracic Society criteria as previously described [47]. Specific serum IgE antibody was measured for both the healthy and the asthmatic groups with the multiple allergen simultaneous test (MAST)-26 chemiluminescent assay systems (Hitachi Chemical Company, Tokyo, Japan) [48]. Atopy was assessed by measurement of specific IgE responsiveness to 14 common inhaled allergens including Dermatophagoides farinae, grass pollens, animal dander, and molds. We defined atopy as a positive response (>4.40 lumicount) to at least 1 of the 14 allergens. To replicate our findings in the discovery cohort, we analyzed 2 independent Japanese cohorts. The first replication cohort (Hokkaido cohort) comprised 619 healthy volunteers and 491 asthmatic patients from the Hokkaido University Hospital and its affiliated hospitals. This population was originally recruited for a case-control genetic association study searching for susceptibility genes to asthma and atopy [49]. Serum-specific IgE to Dermatophagoides species, molds, pollen, and animal dander was measured by a radioallergosorbent test (RAST). Atopy was defined as a positive response (>0.70 UA/mL) to at least 1 of these allergens. The second replication cohort (Fukui cohort) comprised 1275 healthy volunteers and 89 asthmatic patients. This population was originally recruited from workers and students of the University of Fukui for a study of the genetic epidemiology of allergic rhinitis [50]. Serum IgE antibody specific to Japanese cedar, house dust, orchard grass, ragweed mix, Candida species, or Aspergillus species was measured by RAST. Atopy was defined as a positive response (>0.70 UA/mL) to at least 1 of these allergens.

Genotyping

Genomic DNA was extracted from peripheral blood samples of all participants by an automated DNA extraction system (QuickGene-610L; Fujifilm, Tokyo, Japan). Genotyping of the Tsukuba cohort was carried out using the Illumina HumanHap550v3 BeadChip (Illumina, San Diego, CA, USA) for the healthy volunteers and the HumanHap610-Quad BeadChip for the asthmatic patients. The concordance rate between the genotypes determined by the Illumina HumanHap550v3 BeadChip and the Illumina HumanHap610-Quad BeadChip among 182 duplicated samples was 0.99998 [46]. Quality control checks for the SNPs were performed separately using PLINK version 1.07 software [51]. None of the healthy volunteers or the asthmatic patients were removed owing to a call rate for autosomal SNPs of <0.02. SNPs with a missing genotype rate >0.01, minor allele frequency <0.01, or Hardy-Weinberg equilibrium P value <1.0×10−6 were excluded, leaving 479,940 SNPs that were common to the 2 arrays for analysis. Raw data is available upon request. Genotyping accuracy on the X chromosome is often lower than that on other chromosomes because of difficulties involving clustering algorithms, higher frequencies of chromosome anomalies, and more missing data on X chromosome variants [52]. Genotyping of the pseudoautosomal region shared with the Y chromosome and hemizygous males can also be problematic. These analytic complexities could reduce the power of X chromosome analyses, making detection of reliable associations difficult. Therefore, in the current study, we decided to exclude the X chromosome from the analysis. We imputed the genotypes of missing SNPs by using MACH version 1.0 software [53] to improve the resolution of candidate regions identified as associated with total IgE levels at P values <1×10−5. MACH employs a Markov chain algorithm and imputes missing genotypes by taking phased haplotypes as templates. We used 1000 Genomes Project data of Asian origin (JPT+CHB) (http://www.sph.umich.edu/csg/abecasis/MACH/download/1000G-2010-06.html) as the reference panel. To evaluate missing genotypes, we used 50 iterations of the Markov sampler to ensure reliable results. To obtain the genomic inflation factor, we performed the multidimensional scaling (MDS) method using PLINK version 1.07 software. The MDS method is widely used in stratification methods, matching cases to controls based on genotype information (identity-by-state), resulting in discrete strata of individuals that can be analyzed using the Cochran–Mantel–Haenszel test [51]. For replication analyses of the original GWAS data, to obtain high-confidence results, we selected SNPs that are available in the ready-to-use predesigned TaqMan® SNP Genotyping assays (Applied Biosystems, Foster City, CA, USA) in each candidate region that satisfied the following conditions in the discovery Tsukuba cohort: (1) in strongest LD with the SNP most significantly associated with total IgE levels and (2) minor allele frequency >0.15. All assays are quality control tested using a mass spectrophotometer to verify sequence and yield. All assays have 1 VIC® and 1 FAM™ dye-labeled probe and 2 target-specific primers and undergo bioinformatics evaluation of target SNP sequences.

Validation of Association of Previously Reported Genes

A literature search was conducted in PubMed of publications up to June 1, 2013 on genetic association studies of total serum IgE levels. Keywords in the search strategy were (“IgE level” or “IgE concentration” or “serum IgE”) and (“polymorphism” or “SNP” or “genetics”) and (“association”). The search was restricted to human studies written in English. We reviewed the titles, abstracts, and texts of the publications to identify positive genetic association studies. Review articles and studies analyzing antigen-specific IgE production were excluded, as were studies using linkage analysis and transmission disequilibrium tests. We selected only genetic association studies. The references of the collected articles were also screened to find additional matching studies. From the retrieved publications, we selected eligible genes that were reported in 3 or more independent association studies or demonstrated by at least 1 GWAS so that we could as far as possible exclude potentially false-positive findings. Because LD structures may be quite different between Japanese and Caucasian populations, we attempted gene-level replication instead of SNP-level replication. From the primary GWAS data, we chose the SNP with the strongest statistical evidence in a region extending +/−10 kilobases (kb) from each literature-selected candidate gene. The significance level was corrected for multiple testing using the SNPSpD program [16], which corrects for multiple testing of SNPs in LD with each other on the basis of the spectral decomposition of matrices of pairwise LD between SNPs. This method provides a useful alternative to more computationally intensive permutation tests.

Statistical Analysis

In the primary GWAS cohort, associations of genotypes of all the SNPs with log-transformed (base 10) levels of total serum IgE were analyzed by multiple linear regression models in PLINK version 1.07. Because total serum IgE levels are influenced by age, sex, smoking status, and asthma affection status [8], [54], the original GWAS of the total serum IgE levels in the current study was adjusted according to these variables. Quantile-quantile plots and genomic inflation factors were calculated in PLINK version 1.07. In the replication studies, the associations were examined by the same methods in the Hokkaido cohort. As smoking behavior was not available in the Fukui cohort, the associations were adjusted only for age, sex, and asthma affection status in this cohort. Replication was declared only if P<0.05 and the direction of the effect was the same as in the primary GWAS. Combined analysis of the primary GWAS with the replication studies was performed by the basic meta-analysis function in PLINK version 1.07. Random-effect meta-analysis P values were estimated. We used the Haploview 4.2 program [55] to analyze the LD values between SNPs. Study flow chart. GWAS for total IgE levels was performed, followed by replication studies and meta-analysis. Validation of previously reported genes for IgE was also conducted using the GWAS data. (TIFF) Click here for additional data file. Fine-mapping association plots on chromosome 6p21. Three peaks are identified: the MHC class I, MHC class II, and LEMD2 regions. (TIFF) Click here for additional data file. Fine-mapping association plots in the MHC class I region. The color of each circle reflects the LD (r2) between a particular SNP and rs3130941 indicated as a purple diamond. (TIFF) Click here for additional data file. Results of meta-analysis for nonasthmatic healthy individuals only. (DOCX) Click here for additional data file. Results of meta-analysis after inclusion of atopic status as a covariate. (DOCX) Click here for additional data file. Previously reported polymorphisms significantly associated with total serum IgE. (DOCX) Click here for additional data file. Genetic influences of SNPs in the MHC class I/II regions on the association between rs3130941 and total IgE levels. (DOCX) Click here for additional data file.
  55 in total

1.  Association of TNF haplotypes with asthma, serum IgE levels, and correlation with serum TNF-alpha levels.

Authors:  Shilpy Sharma; Amit Sharma; Sarvesh Kumar; Surendra K Sharma; Balaram Ghosh
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2.  PLINK: a tool set for whole-genome association and population-based linkage analyses.

Authors:  Shaun Purcell; Benjamin Neale; Kathe Todd-Brown; Lori Thomas; Manuel A R Ferreira; David Bender; Julian Maller; Pamela Sklar; Paul I W de Bakker; Mark J Daly; Pak C Sham
Journal:  Am J Hum Genet       Date:  2007-07-25       Impact factor: 11.025

3.  A genome-wide association study identifies six susceptibility loci for chronic lymphocytic leukemia.

Authors:  Maria Chiara Di Bernardo; Dalemari Crowther-Swanepoel; Peter Broderick; Emily Webb; Gabrielle Sellick; Ruth Wild; Kate Sullivan; Jayaram Vijayakrishnan; Yufei Wang; Alan M Pittman; Nicola J Sunter; Andrew G Hall; Martin J S Dyer; Estella Matutes; Claire Dearden; Tryfonia Mainou-Fowler; Graham H Jackson; Geoffrey Summerfield; Robert J Harris; Andrew R Pettitt; Peter Hillmen; David J Allsup; James R Bailey; Guy Pratt; Chris Pepper; Chris Fegan; James M Allan; Daniel Catovsky; Richard S Houlston
Journal:  Nat Genet       Date:  2008-08-31       Impact factor: 38.330

4.  Association of tumor necrosis factor-alpha -308G>A polymorphism with IgE-mediated allergy to betalactams in an Italian population.

Authors:  R-M Guéant-Rodriguez; J-L Guéant; M Viola; D Tramoy; F Gaeta; A Romano
Journal:  Pharmacogenomics J       Date:  2007-05-01       Impact factor: 3.550

5.  Prevalence of allergic rhinitis and sensitization to common aeroallergens in a Japanese population.

Authors:  Masafumi Sakashita; Tomomitsu Hirota; Michishige Harada; Reiichiro Nakamichi; Tatsuhiko Tsunoda; Yoko Osawa; Akihiro Kojima; Masayuki Okamoto; Dai Suzuki; Seita Kubo; Yoshimasa Imoto; Yusuke Nakamura; Mayumi Tamari; Shigeharu Fujieda
Journal:  Int Arch Allergy Immunol       Date:  2009-09-29       Impact factor: 2.749

Review 6.  Genotype imputation.

Authors:  Yun Li; Cristen Willer; Serena Sanna; Gonçalo Abecasis
Journal:  Annu Rev Genomics Hum Genet       Date:  2009       Impact factor: 8.929

7.  Immunoglobulin E levels and risk of lymphoma in a case-control study in Spain.

Authors:  Lis Ellison-Loschmann; Yolanda Benavente; Jeroen Douwes; Enric Buendia; Rebecca Font; Tomás Alvaro; Manolis Kogevinas; Silvia de Sanjosé
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2007-07       Impact factor: 4.254

8.  A functional polymorphism in IL-18 is associated with severity of bronchial asthma.

Authors:  Michishige Harada; Kazuhiko Obara; Tomomitsu Hirota; Tomohiro Yoshimoto; Yuki Hitomi; Masafumi Sakashita; Satoru Doi; Akihiko Miyatake; Kimie Fujita; Tadao Enomoto; Masami Taniguchi; Noritaka Higashi; Yuma Fukutomi; Kenji Nakanishi; Yusuke Nakamura; Mayumi Tamari
Journal:  Am J Respir Crit Care Med       Date:  2009-09-10       Impact factor: 21.405

9.  Genome-wide scan on total serum IgE levels identifies FCER1A as novel susceptibility locus.

Authors:  Stephan Weidinger; Christian Gieger; Elke Rodriguez; Hansjörg Baurecht; Martin Mempel; Norman Klopp; Henning Gohlke; Stefan Wagenpfeil; Markus Ollert; Johannes Ring; Heidrun Behrendt; Joachim Heinrich; Natalija Novak; Thomas Bieber; Ursula Krämer; Dietrich Berdel; Andrea von Berg; Carl Peter Bauer; Olf Herbarth; Sibylle Koletzko; Holger Prokisch; Divya Mehta; Thomas Meitinger; Martin Depner; Erika von Mutius; Liming Liang; Miriam Moffatt; William Cookson; Michael Kabesch; H-Erich Wichmann; Thomas Illig
Journal:  PLoS Genet       Date:  2008-08-22       Impact factor: 5.917

10.  A genome-wide association study of total serum and mite-specific IgEs in asthma patients.

Authors:  Jeong-Hyun Kim; Hyun Sub Cheong; Jong Sook Park; An-Soo Jang; Soo-Taek Uh; Yong-Hoon Kim; Mi-Kyeong Kim; Inseon S Choi; Sang Heon Cho; Byoung Whui Choi; Joon Seol Bae; Choon-Sik Park; Hyoung Doo Shin
Journal:  PLoS One       Date:  2013-08-13       Impact factor: 3.240

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  13 in total

1.  Genome-wide association study of recalcitrant atopic dermatitis in Korean children.

Authors:  Kyung Won Kim; Rachel A Myers; Ji Hyun Lee; Catherine Igartua; Kyung Eun Lee; Yoon Hee Kim; Eun-Jin Kim; Dankyu Yoon; Joo-Shil Lee; Tomomitsu Hirota; Mayumi Tamari; Atsushi Takahashi; Michiaki Kubo; Je-Min Choi; Kyu-Earn Kim; Dan L Nicolae; Carole Ober; Myung Hyun Sohn
Journal:  J Allergy Clin Immunol       Date:  2015-04-30       Impact factor: 10.793

2.  Rhinovirus infection induces distinct transcriptome profiles in polarized human macrophages.

Authors:  Charu Rajput; Megan P Walsh; Breanna N Eder; Ediri E Metitiri; Antonia P Popova; Marc B Hershenson
Journal:  Physiol Genomics       Date:  2018-03-09       Impact factor: 3.107

3.  Genome-wide association study and admixture mapping reveal new loci associated with total IgE levels in Latinos.

Authors:  Maria Pino-Yanes; Christopher R Gignoux; Joshua M Galanter; Albert M Levin; Catarina D Campbell; Celeste Eng; Scott Huntsman; Katherine K Nishimura; Pierre-Antoine Gourraud; Kiana Mohajeri; Brian J O'Roak; Donglei Hu; Rasika A Mathias; Elizabeth A Nguyen; Lindsey A Roth; Badri Padhukasahasram; Andres Moreno-Estrada; Karla Sandoval; Cheryl A Winkler; Fred Lurmann; Adam Davis; Harold J Farber; Kelley Meade; Pedro C Avila; Denise Serebrisky; Rocio Chapela; Jean G Ford; Michael A Lenoir; Shannon M Thyne; Emerita Brigino-Buenaventura; Luisa N Borrell; William Rodriguez-Cintron; Saunak Sen; Rajesh Kumar; Jose R Rodriguez-Santana; Carlos D Bustamante; Fernando D Martinez; Benjamin A Raby; Scott T Weiss; Dan L Nicolae; Carole Ober; Deborah A Meyers; Eugene R Bleecker; Steven J Mack; Ryan D Hernandez; Evan E Eichler; Kathleen C Barnes; L Keoki Williams; Dara G Torgerson; Esteban G Burchard
Journal:  J Allergy Clin Immunol       Date:  2014-12-06       Impact factor: 10.793

4.  An epigenome-wide association study of total serum IgE in Hispanic children.

Authors:  Wei Chen; Ting Wang; Maria Pino-Yanes; Erick Forno; Liming Liang; Qi Yan; Donglei Hu; Daniel E Weeks; Andrea Baccarelli; Edna Acosta-Perez; Celeste Eng; Yueh-Ying Han; Nadia Boutaoui; Catherine Laprise; Gwyneth A Davies; Julian M Hopkin; Miriam F Moffatt; William O C M Cookson; Glorisa Canino; Esteban G Burchard; Juan C Celedón
Journal:  J Allergy Clin Immunol       Date:  2017-01-06       Impact factor: 10.793

5.  Contribution of Antigen-Processing Machinery Genetic Polymorphisms to Atopic Dermatitis.

Authors:  Wanda Niepiekło-Miniewska; Łukasz Matusiak; Joanna Narbutt; Alekandra Lesiak; Piotr Kuna; Andrzej Wiśniewski; Piotr Kuśnierczyk
Journal:  Life (Basel)       Date:  2021-04-10

Review 6.  Genetic risk factors for the development of allergic disease identified by genome-wide association.

Authors:  M A Portelli; E Hodge; I Sayers
Journal:  Clin Exp Allergy       Date:  2015-01       Impact factor: 5.018

Review 7.  A decade of research on the 17q12-21 asthma locus: Piecing together the puzzle.

Authors:  Michelle M Stein; Emma E Thompson; Nathan Schoettler; Britney A Helling; Kevin M Magnaye; Catherine Stanhope; Catherine Igartua; Andréanne Morin; Charles Washington; Dan Nicolae; Klaus Bønnelykke; Carole Ober
Journal:  J Allergy Clin Immunol       Date:  2018-01-04       Impact factor: 10.793

8.  A cis-eQTL allele regulating reduced expression of CHI3L1 is associated with late-onset adult asthma in Japanese cohorts.

Authors:  Jun Kanazawa; Haruna Kitazawa; Hironori Masuko; Yohei Yatagai; Tohru Sakamoto; Yoshiko Kaneko; Hiroaki Iijima; Takashi Naito; Takefumi Saito; Emiko Noguchi; Satoshi Konno; Masaharu Nishimura; Tomomitsu Hirota; Mayumi Tamari; Nobuyuki Hizawa
Journal:  BMC Med Genet       Date:  2019-04-02       Impact factor: 2.103

9.  Humoral immune factors and asthma among American Indian children: a case-control study.

Authors:  Lyle G Best; Rae A O'Leary; Marcia A O'Leary; Joseph M Yracheta
Journal:  BMC Pulm Med       Date:  2016-06-13       Impact factor: 3.317

10.  Association of the Promoter Haplotype of IFN-γ-Inducible Protein 16 Gene with Schizophrenia in a Korean Population.

Authors:  Won Sub Kang; Su Kang Kim; Hae Jeong Park
Journal:  Psychiatry Investig       Date:  2020-02-13       Impact factor: 2.505

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