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Investigating highly replicated asthma genes as candidate genes for allergic rhinitis

Contributed equally
BMC Medical Genetics201314:51

DOI: 10.1186/1471-2350-14-51

Received: 25 October 2012

Accepted: 6 May 2013

Published: 10 May 2013

Abstract

Background

Asthma genetics has been extensively studied and many genes have been associated with the development or severity of this disease. In contrast, the genetic basis of allergic rhinitis (AR) has not been evaluated as extensively. It is well known that asthma is closely related with AR since a large proportion of individuals with asthma also present symptoms of AR, and patients with AR have a 5–6 fold increased risk of developing asthma. Thus, the relevance of asthma candidate genes as predisposing factors for AR is worth investigating. The present study was designed to investigate if SNPs in highly replicated asthma genes are associated with the occurrence of AR.

Methods

A total of 192 SNPs from 21 asthma candidate genes reported to be associated with asthma in 6 or more unrelated studies were genotyped in a Swedish population with 246 AR patients and 431 controls. Genotypes for 429 SNPs from the same set of genes were also extracted from a Singapore Chinese genome-wide dataset which consisted of 456 AR cases and 486 controls. All SNPs were subsequently analyzed for association with AR and their influence on allergic sensitization to common allergens.

Results

A limited number of potential associations were observed and the overall pattern of P-values corresponds well to the expectations in the absence of an effect. However, in the tests of allele effects in the Chinese population the number of significant P-values exceeds the expectations. The strongest signals were found for SNPs in NPSR1 and CTLA4. In these genes, a total of nine SNPs showed P-values <0.001 with corresponding Q-values <0.05. In the NPSR1 gene some P-values were lower than the Bonferroni correction level. Reanalysis after elimination of all patients with asthmatic symptoms excluded asthma as a confounding factor in our results. Weaker indications were found for IL13 and GSTP1 with respect to sensitization to birch pollen in the Swedish population.

Conclusions

Genetic variation in the majority of the highly replicated asthma genes were not associated to AR in our populations which suggest that asthma and AR could have less in common than previously anticipated. However, NPSR1 and CTLA4 can be genetic links between AR and asthma and associations of polymorphisms in NPSR1 with AR have not been reported previously.

Keywords

Allergic rhinitis Association Asthma Case–control Replication

Background

Allergic rhinitis (AR) is a major chronic respiratory disease and the most common allergic disorder with a worldwide prevalence of 10-25% [1]. It has long been recognized that the development of AR is dependent on interactions between genetic and environmental factors and that the genetic factors play a major role with an estimated heritability for AR as high as 70-90% [2, 3]. A large number of studies have identified more than 100 single nucleotide polymorphisms (SNPs) associated with AR, but few of them have been successfully replicated. The general reproducibility of a majority of these AR associations was found to be low in a previous study [4]. Only one genome-wide association study (GWAS) has been performed to identify genetic variants specifically for AR [5]. In that study, no associations were detected at a genome-wide significance level, and only two at a suggestive significance level. In addition, a genome-wide meta-analysis based on self-reported AR identified few genetic variants in spite of analyzing 2.2 million SNPs in close to 4000 AR cases and 9000 controls [6]. Only one locus reached genome-wide significance and six suggestive loci were identified. Comparing these two studies there were no significant association signals in common. In addition, no association signals of earlier linkage and candidate gene association studies coincide with any of the loci identified in the GWAS and the meta-study. This is not surprising, since the replication of different genotype-phenotype associations has in general proven to be much more difficult than initially appreciated [7]. Experience gathered in several different diseases indicates that there is a positive correlation between the ability to replicate previous associations and the size and number of previous studies. Thus, in diseases where many large previous association studies have been performed replication is often more successful.

It is well known that asthma is closely related to AR since a large proportion of individuals with asthma also present symptoms of AR, and patients with AR have a 5–6 fold increased risk of developing asthma [810]. Asthma genetics has been extensively studied and many genes have been associated with the development or severity of this disease. Ober and Hoffjan (2006) listed 118 genes that had been reported to be associated with asthma or atopy-related phenotypes [11]. Of these genes, 25 were positively associated with asthma in six or more independent studies and were thus highly implicated as true susceptibility genes for asthma-related phenotypes. The original associations were identified in many different types of studies; linkage, positional cloning and candidate gene association studies and were subsequently replicated mostly by association studies. Several studies have investigated the reproducibility of asthma candidate gene associations. One study by Rogers et al. (2009) investigated 160 associated SNPs from 39 genes from an Illumina 550k array in 422 families and successfully replicated 10 SNPs in six genes [12]. At the level of the gene they found additional support for association in 15 of the 39 genes but none were significant after adjustment for multiple comparisons. In a consortium-based GWAS investigating 10,365 asthma patients with 16,110 controls a total of seven loci with genome-wide significance were identified [13]. None of the implicated genes overlapped with the genes identified in the study by Rogers et al. [12]. A meta-analysis of GWAS in ethnically diverse North American populations identified five susceptibility loci, four of whom at previously reported loci [14]. Also this study was very large and analyzed 5,416 patients with replication in 12,649 patients. The combined results of the many previous association studies for asthma illustrate the challenges in the search and replication of risk factors for asthma.

Due to the close relationship between the occurrence of asthma and AR we hypothesize that these two phenotypes have genetic risk factors in common. The present study was thus designed to investigate if SNPs in highly replicated asthma genes as reported in the Ober and Hoffjan study [11] are associated with the occurrence of AR.

Methods

Subjects

The Swedish study population consists of 246 AR patients (108 female, 138 male) and 431 control individuals (185 female, 246 male) and was recruited from southern Sweden in 2003–2009. All subjects are unrelated and of western European origin, with both parents born in Sweden. The diagnosis of birch and/or grass pollen induced AR was based on a positive history of AR for at least two years and a positive skin prick test (SPT) or Phadiatop test with at least class two to birch and/or timothy grass pollen. A total of 59% of the patients showed a positive SPT for both allergens. All patients were classified as having severe symptoms i.e., nasal itching, sneezing, rhinorrhea and nasal congestion during pollen season and they had all been treated with antihistamines and nasal steroids during pollen seasons previous years. Control individuals had no history of AR or any other atopic disease and had a negative SPT or Phadiatop test. Genomic DNA was extracted from blood collected in EDTA using QIAamp DNA Blood Maxi or Mini kits (Qiagen, Hilden, Germany) and DNA concentrations determined by fluorometry using PicoGreen (Molecular Probes, Invitrogen, Eugene, OR, USA). The Swedish study population has previously been analyzed in several AR studies [4, 1517]. The Singapore Chinese population consists of 448 AR patients (250 female, 198 male) and 462 control individuals (337 female and 125 male) and was collected in Singapore between 2008 and 2010. The study population is of Chinese origin, residence of Singapore and all subjects are unrelated to one another. The diagnosis of dust mite induced AR was based on interviews of medical history using a standardized questionnaire and SPTs performed using a panel of common allergens in Singapore including the house dust mite Dermatophagoides pteronyssinus and Blomia tropicalis. A total of 89% of the patients showed a positive SPT for both allergens. AR is thus diagnosed based on the presence of atopic status and typical AR symptoms as defined by the ARIA 2008 guidelines i.e., two or more AR symptoms (nasal congestion, rhinorrhea, nasal itching, sneezing) persisting for four or more days a week during the past year. In this study, none of the patients suffered from severe asthma and less than 10% had moderate asthma with continuous medication. Control individuals had no history of AR or any other atopic disease and had a negative SPT. More detailed phenotypic characteristics of the Singapore Chinese population have been described previously [5]. Genomic DNA was extracted from buccal cells obtained from a mouthwash of 0.9% saline solution following a standardized protocol [18]. Samples were quantified in triplicate on the Nanodrop (Thermo Fisher Scientific Inc, Wilmington, DE, USA). In both populations, SPT were performed with saline buffer as negative and histamine chloride as positive controls. A wheal reaction diameter of more than three mm was considered a positive SPT response. SPT was only performed if the AR cases had not taken any anti-allergic drugs for at least three days prior to the test. Atopy is defined as a positive SPT reaction to either one of allergens. The study was approved by the Ethics Committee of the Medical Faculty, Lund University and the Institutional Review Board of National University of Singapore and written informed consent was obtained from all subjects. This study is also in compliance with the Helsinki declaration.

Genotyping

A total of 21 genes (IL4, IL13, CD14, MS4A2 (FCERB1), IL4R (IL4RA), ADAM33, GSTM1, IL10, CTLA4, SPINK5, LTC4S, NPSR1 (GPR154), NOD1 (CARD4), SCGB1A1 (CC16), GSTP1, STAT6, NOS1, CCL5, TBXA2R, ADRB2 and TGFB1) were selected from a compilation of 25 genes reported to be associated with asthma phenotypes in six or more unrelated independent studies [11]. SNPs of the 21 genes were analyzed for association with AR whereas no SNPs were analyzed for HLA-DRB1, HLA-DQB1, TNF, and LTA as they are located at the HLA locus. Since this study investigates asthma genes for their eventual contribution also to the AR phenotype, we use the gene as the replication unit and not the individual SNPs. For genotyping in the Swedish study population, HapMap (release 24) data were used to identify haplotype-tagging SNPs (r2 cut off =0.8, and minor allele frequency cut off =0.2) for each of the 21 genes. Non-synonymous SNPs reported in dbSNP or HapMap with minor allele frequencies >5% was added to this selection. Genotypes were determined using the Sequenom MassARRAY MALDI-TOF system. Assay design was made using the MassARRAY Assay Design ver. 2.0 software (Sequenom Inc, San Diego, CA, USA) and primers were obtained from Metabion GmbH (Martinsried, Germany). A total of 192 SNPs with a total genotyping rate of 98.4% were analyzed for association with AR in 246 patients and 431 controls. Whole genome genotyping in the Singapore Chinese population was performed using the Illumina HumanHap 550 k BeadChip version 3 (Illumina, San Diego, CA, USA) at the Genome Institute of Singapore as described earlier [5]. Of the 21 genes initially selected, three genes (LTC4S, NOD1 and GSTM1) had no SNPs in the Illumina Human Hap 550k panel while CCL5 had one SNP but was filtered out after quality control for SNPs. A total of 413 SNPs from 17 unique genes with a total genotyping rate of 98.4% were analyzed for association with AR in 448 patients and 462 controls. Additional samples (921 AR patients, 390 controls) from the Singapore Chinese cohort were genotyped for rs324981, using a Taqman-assay. Reactions were carried out according to the manufacturer’s protocol using an ABI PRISM 7900HT and the genotypes determined using SDS 2.4 software (Applied Biosystems, Foster City, CA, USA).

Statistical analysis

Statistical analyses were made using R statistical software [19] and PLINK v1.07 [20]. Genotype frequencies were calculated and tested for Hardy-Weinberg equilibrium in both cases and controls. Allele and genotype frequencies were then investigated for association with AR using a χ2-homogeneity test. Odds ratios and 95% confidence intervals were estimated by using the most common allele as the referent and are reported for each minor allele. Associations between SPT-response and genotype were analyzed using Kruskal-Wallis rank sum test. False discovery rate was quantified using the Q-value introduced by Storey [21] and calculated using the software QVALUE (ver.1.0).

Results

Association with AR phenotype in the Swedish population

A total of 192 SNPs from 21 genes were genotyped and analyzed for association with AR in 246 patients and 431 controls. For each SNP two tests of association were made, one of allele frequencies and one of genotype frequencies. Table 1 shows the results of the association analysis for SNPs with uncorrected P-values <0.05 and the corresponding Q-values and ORs (for complete results see Additional file 1: Table S1). In the tests of allele frequencies there were two P-values <0.01 and 11 P-values <0.05. In the tests of genotype frequencies there were three P-values <0.01 and eight P-values <0.05. None of the indicated SNPs had Q-values <0.1. In the absence of any association, the expected numbers of P-values <0.01 and <0.05 are 1.9 and 9.6, respectively, in each of the test categories. Thus, the results fit very well the expected pattern of P-values in the absence of any effects.
Table 1

Minor allele frequencies (MAF) and P-values for Hardy-Weinberg (HW) and association tests for SNPs with P<0.05 in the Swedish population

Gene

SNP ID

Chromosome position

Study MAF

HW test

Association test

OR

95% CI

Allele

Genotype

Lower

Upper

IL10

rs3021094

1

206944952

0.092

0.16

0.020

(0.72)

0.078

(0.92)

1.6

1.1

2.2

NOD1

rs4363092

7

30503938

0.18

0.36

0.050

(0.72)

0.045

(0.92)

1.3

1.0

1.8

NOD1

rs4720003

7

30508992

0.18

0.37

0.041

(0.72)

0.033

(0.92)

1.3

1.0

1.8

NPSR1

rs2022142

7

34705950

0.10

1.0

0.035

(0.72)

0.056

(0.92)

1.5

1.0

2.1

NPSR1

rs1379925

7

34715128

0.091

1.0

0.021

(0.72)

0.031

(0.92)

1.6

1.1

2.3

NPSR1

rs1379923

7

34717238

0.25

0.41

0.045

(0.72)

0.11

(0.92)

0.8

0.6

1.0

NPSR1

rs17788770

7

34793991

0.10

0.68

0.083

(0.72)

0.035

(0.92)

0.7

0.5

1.0

NPSR1

rs17789834

7

34871328

0.19

0.32

0.011

(0.70)

0.039

(0.92)

1.4

1.1

1.9

SCGB1A1

rs11231085

11

62190448

0.36

0.74

0.037

(0.72)

0.0049

(0.58)

1.3

1.0

1.6

CCL5

rs1065341

17

34198593

0.040

0.41

0.027

(0.72)

0.085

(0.92)

1.8

1.1

3.2

CCL5

rs3817655

17

34199641

0.17

0.12

0.0028

(0.29)

0.0088

(0.58)

1.6

1.2

2.1

CCL5

rs2107538

17

34207780

0.17

0.27

0.0021

(0.29)

0.0069

(0.58)

1.6

1.2

2.1

TBXA2R

rs3786989

19

3604004

0.93

0.25

0.038

(0.72)

0.086

(0.92)

0.6

0.4

1.0

†Association with AR estimated using a χ2-homogeneity test with Q-values in parenthesis calculated according to Storey (2002).

Odds ratio (OR) and 95% confidence interval were estimated by using the most common allele as the referent and are reported for each minor allele.

Association with SPT response in the Swedish population

A Kruskal-Wallis rank sum test was used to investigate the relationship between genotype and degree of sensitization to birch and timothy grass in AR-patients. A total of 24 SNPs had P-values <0.05 in the tests of SPTs for birch or timothy grass (Table 2 and Additional file 1: Table S1). In the tests of birch there were three P-values <0.001, four at P<0.01 and 10 at P<0.05 and in the test of timothy grass there were one P-value <0.01 and 16 at P<0.05. The Q-values of the three SNPs with P<0.001 for birch (rs1138272 in GSTP1, rs20541 and rs848 in IL13) were approximately 0.04 and all other Q-values were >0.1. The lowest P-value (rs1138272) is below the level for a Bonferroni corrected P-value of 0.05, i.e. 0.00022 vs. 0.00026. Although the overall distribution of P-values is close to the expectation under the assumption of absence of any association, the three P-values <0.001 can be considered an indication of an effect that warrants further investigation.
Table 2

Association of SNPs with P<0.05 for sensitization to allergens in the Swedish population

Gene

SNP ID

Chromosome position

Kruskal-Wallis test

Birch

Timothy

IL10

rs3024498

1

206941529

0.27

(0.95)

0.0094

(0.31)

IL10

rs3024492

1

206944112

0.17

(0.87)

0.025

(0.36)

IL13

rs20541

5

131995964

0.00040

(0.038)

0.58

(0.77)

IL13

rs848

5

131996500

0.00067

(0.043)

0.56

(0.77)

IL4

rs2243248

5

132008644

0.0044

(0.21)

0.52

(0.76)

IL4

rs2070874

5

132009710

0.051

(0.87)

0.016

(0.31)

IL4

rs2227284

5

132012725

0.015

(0.57)

0.18

(0.59)

IL4

rs2243266

5

132013789

0.046

(0.87)

0.014

(0.31)

IL4

rs2243288

5

132017944

0.046

(0.87)

0.013

(0.31)

SPINK5

rs4357026

5

147457939

0.77

(0.99)

0.048

(0.45)

SPINK5

rs9325073

5

147498652

0.90

(0.99)

0.020

(0.31)

SPINK5

rs1422993

5

147503820

0.96

(0.99)

0.015

(0.31)

SPINK5

rs4263489

5

147516195

0.049

(0.87)

0.61

(0.77)

LTC4S

rs730012

5

179220638

0.042

(0.87)

0.57

(0.77)

NPSR1

rs323917

7

34741643

0.048

(0.87)

0.35

(0.63)

NPSR1

rs12534369

7

34804709

0.64

(0.96)

0.033

(0.43)

NPSR1

rs17170017

7

34874209

0.54

(0.95)

0.011

(0.31)

N.D.

rs10897270

11

62183007

0.90

(0.99)

0.012

(0.31)

GSTP1

rs1138272

11

67353579

0.00022

(0.038)

0.20

(0.61)

NOS1

rs6490121

12

117708195

0.33

(0.95)

0.036

(0.44)

NOS1

rs12578547

12

117763347

0.091

(0.87)

0.018

(0.31)

NOS1

rs3782218

12

117771511

0.96

(0.99)

0.046

(0.45)

NOS1

rs17509231

12

117794323

0.43

(0.95)

0.011

(0.31)

IL4R

rs1029489

16

27376217

0.46

(0.95)

0.039

(0.44)

Association between genotype and sensitization to allergens was analyzed using a Kruskal-Wallis rank sum test. False discovery rate was quantified using the q-value introduced by Storey(2002) and are given in parenthesis.

Association with AR phenotype in the Chinese population

Of the 21 genes initially selected, a total of 413 SNPs from 17 genes were extracted from the Illumina Human Hap 550 k panel and tested for association with AR in the Singapore Chinese population. Just as in the Swedish population two association tests were made, one at the allele and one at the genotype level. Table 3 shows the results of the association analysis for SNPs with uncorrected P-values <0.05 and the corresponding Q-values and ORs (for complete results see Additional file 2: Table S2). A total of 50 SNPs had P-values <0.05. In the association test of alleles there were nine P-values <0.001, 18 at P< 0.01 and a total of 48 at P<0.05. All nine SNPs with P-values <0.001 had Q-values <0.05 and corresponds to rs10270663, rs324389, rs324957, rs10278663, rs324396, rs10267134, rs324987 in NPSR1/AAA1, and rs231804 and rs231735 in CTLA4. In the tests of association at the genotype level, the four lowest P-values were <0.001with Q-values <0.05 and coincided with the lowest P-values in the allele test. In addition, another nine P-values were <0.01 and five of them had Q-values <0.1. Of these five, four also coincide with the nine SNPs with P<0.001 in the allele test. In total, there were 30 P-values <0.05. In the absence of any association, the expected number of P-values <0.001, <0.01 and <0.05 are 0.4, 4.1 and 20.7, respectively, in each of the test categories. Thus, the observed numbers of significant P-values exceeds the expectation in the absence of any association for both the allele and the genotype tests. In the tests of allele effects, three P-values were lower than 0.00012 which is the Bonferroni limit at P=0.05 within each category. The lowest P-value, 0.000068, is larger than 0.00003 equal to the global Bonferroni limit for all tests taken together, but of the same order of magnitude. Thus, these results give a strong indication of a genetic effect of NPSR1/AAA1 and CTLA4 on the occurrence of AR, i.e. these genes can be considered strong candidates for future analyses.
Table 3

Minor allele frequencies (MAF) and P-values for Hardy-Weinberg (HW) and association tests for SNPs with P<0.05 in the Chinese population

Gene

SNP ID

Chromosome position

Study MAF

HW test

Association test

OR

95% CI

Allele

Genotype

Lower

Upper

CTLA4

rs231735

2

204402121

0.23

1.0

0.00090

(0.037)

0.0038

(0.12)

1.44

1.16

1.79

CTLA4

rs231804

2

204416891

0.22

0.93

0.00060

(0.028)

0.0025

(0.090)

1.46

1.18

1.82

CTLA4

rs1024161

2

204429997

0.34

0.57

0.0088

(0.21)

0.020

(0.34)

1.29

1.07

1.56

CTLA4

rs926169

2

204430997

0.34

0.89

0.0059

(0.20)

0.016

(0.29)

1.31

1.08

1.58

CTLA4

rs733618

2

204439189

0.40

1.0

0.012

(0.22)

0.030

(0.42)

0.79

0.66

0.95

CTLA4

rs231726

2

204449111

0.40

0.74

0.016

(0.22)

0.041

(0.50)

1.25

1.04

1.51

CTLA4

rs6748358

2

204465150

0.28

0.39

0.0077

(0.21)

0.0067

(0.18)

1.31

1.08

1.61

CTLA4

rs10197319

2

204471289

0.22

0.86

0.013

(0.22)

0.0058

(0.17)

1.31

1.06

1.63

CTLA4

rs3096851

2

204472127

0.40

0.90

0.015

(0.22)

0.028

(0.41)

1.26

1.05

1.51

CTLA4

rs3116504

2

204477299

0.40

0.90

0.015

(0.22)

0.028

(0.41)

1.26

1.05

1.51

SPINK5

rs7707803

5

147368427

0.33

0.23

0.021

(0.27)

0.077

(0.57)

1.25

1.03

1.52

SPINK5

rs7725292

5

147368581

0.33

0.28

0.017

(0.22)

0.061

(0.51)

1.27

1.04

1.54

SPINK5

rs10477360

5

147384474

0.50

0.90

0.037

(0.34)

0.066

(0.52)

0.82

0.69

0.99

SPINK5

rs12332673

5

147387572

0.12

0.17

0.045

(0.36)

NA

(NA)

0.75

0.56

0.99

SPINK5

rs11948836

5

147393693

0.12

0.17

0.039

(0.34)

NA

(NA)

0.74

0.56

0.99

SPINK5

rs17774892

5

147395161

0.12

0.88

0.035

(0.34)

NA

(NA)

0.74

0.55

0.98

SPINK5

rs10463396

5

147395535

0.20

1.0

0.016

(0.22)

0.053

(0.50)

0.76

0.60

0.95

SPINK5

rs17107650

5

147396591

0.12

0.17

0.039

(0.34)

NA

(NA)

0.74

0.56

0.99

SPINK5

rs1422982

5

147400217

0.20

1.00

0.016

(0.22)

0.053

(0.50)

0.76

0.60

0.95

SPINK5

rs17107673

5

147401681

0.12

0.29

0.041

(0.34)

NA

(NA)

0.74

0.56

0.99

SPINK5

rs4472254

5

147433830

0.20

0.69

0.016

(0.22)

0.044

(0.50)

0.76

0.60

0.95

SPINK5

rs7724165

5

147445445

0.50

0.80

0.027

(0.30)

0.054

(0.50)

1.23

1.02

1.47

SPINK5

rs4519913

5

147452004

0.50

0.85

0.024

(0.27)

0.057

(0.50)

0.81

0.68

0.97

ADRB2

rs11742519

5

148218501

0.45

0.90

0.039

(0.34)

0.056

(0.50)

1.21

1.01

1.45

NPSR1

rs411323

7

34668233

0.16

0.81

0.037

(0.34)

0.095

(0.62)

1.31

1.02

1.69

NPSR1/AAA1

rs10081183

7

34706738

0.45

0.66

0.0066

(0.21)

0.023

(0.36)

0.78

0.65

0.93

NPSR1/AAA1

rs1345267

7

34714584

0.46

0.31

0.012

(0.22)

0.036

(0.48)

0.79

0.66

0.95

NPSR1/AAA1

rs1419791

7

34722086

0.48

0.85

0.0096

(0.21)

0.010

(0.21)

1.27

1.06

1.52

NPSR1/AAA1

rs1419791

7

34722086

0.48

0.85

0.0096

(0.21)

0.010

(0.21)

1.27

1.06

1.52

NPSR1/AAA1

rs324374

7

34723121

0.48

0.90

0.0095

(0.21)

0.010

(0.21)

1.27

1.06

1.52

NPSR1/AAA1

rs324389

7

34744239

0.46

0.66

0.00010

(0.014)

0.00055

(0.044)

0.70

0.58

0.84

NPSR1/AAA1

rs10270663

7

34752923

0.46

0.52

0.000068

(0.014)

0.00038

(0.044)

0.69

0.58

0.83

NPSR1/AAA1

rs324396

7

34756648

0.42

1.0

0.00035

(0.021)

0.0012

(0.065)

1.40

1.16

1.68

NPSR1/AAA1

rs324957

7

34767897

0.43

0.61

0.00011

(0.014)

0.00052

(0.044)

1.44

1.20

1.73

NPSR1/AAA1

rs10267134

7

34769628

0.34

0.89

0.00039

(0.021)

0.0014

(0.065)

0.71

0.58

0.86

NPSR1/AAA1

rs10278663

7

34774996

0.34

0.83

0.00032

(0.021)

0.0012

(0.065)

0.70

0.58

0.85

NPSR1

rs324987

7

34787953

0.44

0.34

0.00021

(0.019)

0.00049

(0.044)

1.41

1.18

1.70

NPSR1

rs17199888

7

34830864

0.33

0.89

0.0022

(0.083)

0.0075

(0.18)

0.74

0.61

0.90

NPSR1

rs1419868

7

34834082

0.25

0.018

0.013

(0.22)

0.054

(0.50)

1.31

1.06

1.61

GSTP1

rs614080

11

67103863

0.28

0.44

0.40

(0.80)

0.050

(0.50)

1.09

0.89

1.33

NOS1

rs884847

12

116207996

0.15

0.90

0.26

(0.75)

0.043

(0.50)

1.01

0.90

1.50

NOS1

rs532967

12

116216722

0.20

0.55

0.032

(0.34)

0.0024

(0.090)

1.03

1.02

1.62

NOS1

rs545654

12

116261432

0.32

0.47

0.019

(0.24)

0.043

(0.50)

1.19

0.65

0.96

NOS1

rs693534

12

116269101

0.28

0.64

0.0094

(0.21)

0.014

(0.29)

0.84

0.62

0.94

NOS1

rs3782221

12

116280264

0.49

0.31

0.024

(0.27)

0.047

(0.50)

1.08

0.67

0.97

NOS1

rs11068466

12

116320260

0.17

0.73

0.023

(0.27)

0.016

(0.29)

0.91

0.59

0.96

NOS1

rs10774914

12

116331323

0.12

0.56

0.042

(0.34)

0.10

(0.62)

1.13

1.01

1.78

IL4R

rs3024535

16

27259622

0.16

0.023

0.034

(0.34)

NA

(NA)

1.31

1.02

1.68

IL4R

rs3024585

16

27267345

0.38

0.12

0.034

(0.34)

0.088

(0.62)

0.82

0.68

0.99

IL4R

rs2074570

16

27282658

0.07

0.63

0.040

(0.34)

NA

(NA)

1.45

1.02

2.07

†Association with AR estimated using a χ2-homogeneity test with Q-values in parenthesis calculated according to Storey (2002).

Odds ratio (OR) and 95% confidence interval were estimated by using the most common allele as the referent and are reported for each minor allele.

In addition, we investigated the functional NPSR1 coding variant rs324981 (Ile107Asn), which is in complete linkage disequilibrium with rs324987 (P-value for association =0.00021, OR=1.41, see Table 3). A TaqMan assay was used to determine the rs324981 genotypes of additional individuals of the Singapore Chinese cohort (921 AR patients, 390 controls). The P-value of association was 0.0070 with an odds ratio (OR) of 1.14 for the heterozygous genotype and an increased OR of 1.65 for the homozygous genotype in comparison with the reference genotype. Thus, both analyses support the involvement of NPSR1 in AR.

Since genetic variation of all genes tested for association with AR in the present study has previously been associated with asthma and since patients with AR have an increased incidence of asthma, we investigated asthma as a confounding factor for our results. Since the strongest associations are detected in the Chinese population, we excluded all Chinese patients with any asthmatic symptoms and repeated the association analysis for this population (Additional file 3: Table S3). Comparing the significant association results before and after elimination of AR patients with asthma shows that: 1) The elimination of 144 patients with asthma out of 448 (32%) result in a general increase in P-values corresponding to the loss of power due to a smaller sample size, 2) the nine SNPs with P-values <0.001 detected in the initial analysis of all 448 AR patients, all showed P-values ≤0.01 after elimination of the 144 patients, 3) these SNPs also showed very small changes in their ORs (<0.08), 4) most ORs were highly similar before and after elimination of the 144 patients, the exception being five SNPs in the NOS1 gene that may indicate confounding due to asthma.

Association with SPT response in the Chinese population

A Kruskal-Wallis rank sum test was used to investigate the relationship between genotype and degree of sensitization to D. pteronyssinus and B. tropicalis in AR-patients. All tests of the SPT with an uncorrected P-value <0.05 are shown in Table 4 (for complete results see Additional file 2: Table S2). A total of 44 SNPs had P-values <0.05 in the tests of D. pteronyssinus and B. tropicalis. In the tests of B. tropicalis there were six P-values <0.01 and a total of 24 P-values <0.05. In the tests of D. pteronyssinus one P-value was <0.001, six were <0.01 and a total of 22 were <0.05. None of the indicated SNPs had corresponding Q-values <0.1. Thus, the tests of the SPT response conformed well to the expectations under independence and give therefore no indication of any association with sensitization of the tested allergens.
Table 4

Association of SNPs with P<0.05 for sensitization to allergens in the Chinese population

Gene

SNP ID

Chromosome position

Kruskal-Wallis test

B.tropicalis

D. pteronyssinus

SPINK5

rs10477360

5

147384474

0.027

(0.65)

0.69

(1.0)

ADRB2

rs2163752

5

148125331

0.027

(0.65)

0.054

(0.92)

ADRB2

rs30306

5

148132557

0.028

(0.65)

0.074

(0.97)

ADRB2

rs30325

5

148143517

0.27

(0.82)

0.010

(0.52)

ADRB2

rs30328

5

148146640

0.28

(0.82)

0.025

(0.75)

ADRB2

rs30330

5

148148525

0.32

(0.82)

0.027

(0.75)

ADRB2

rs9285673

5

148153121

0.049

(0.78)

0.90

(1.0)

ADRB2

rs10075995

5

148273622

0.53

(0.82)

0.014

(0.52)

NPSR1/AAA1

rs2058163

7

34301616

0.049

(0.78)

0.025

(0.75)

NPSR1/AAA1

rs1419842

7

34321625

0.41

(0.82)

0.031

(0.75)

NPSR1/AAA1

rs2392268

7

34380952

0.44

(0.82)

0.031

(0.75)

NPSR1/AAA1

rs6947789

7

34417405

0.018

(0.65)

0.83

(1.0)

NPSR1/AAA1

rs736295

7

34417742

0.054

(0.79)

0.039

(0.75)

NPSR1

rs2530545

7

34663665

0.94

(0.90)

0.040

(0.75)

NPSR1

rs11761197

7

34666914

0.78

(0.90)

0.013

(0.52)

NPSR1

rs1379928

7

34667814

0.51

(0.82)

0.0098

(0.52)

NPSR1

rs2609224

7

34672931

0.62

(0.85)

0.011

(0.52)

NPSR1

rs2609220

7

34676579

0.68

(0.86)

0.0067

(0.52)

NPSR1

rs2531841

7

34686074

0.81

(0.90)

0.012

(0.52)

NPSR1

rs1419837

7

34692064

0.88

(0.90)

0.018

(0.62)

NPSR1

rs1419779

7

34779833

0.21

(0.82)

0.0011

(0.15)

NPSR1

rs324978

7

34780857

0.20

(0.82)

0.00098

(0.15)

NPSR1

rs1859409

7

34906409

0.049

(0.78)

0.83

(1.0)

NPSR1

rs4723388

7

34909345

0.0056

(0.51)

0.52

(0.98)

NPSR1

rs1186717

7

34937434

0.33

(0.82)

0.036

(0.75)

NPSR1

rs1637673

7

34964375

0.15

(0.82)

0.0081

(0.52)

NPSR1

rs4236340

7

34976719

0.0061

(0.51)

0.46

(0.98)

NPSR1

rs328902

7

34987368

0.41

(0.82)

0.038

(0.75)

NPSR1

rs328906

7

34990440

0.0080

(0.51)

0.58

(0.98)

NPSR1

rs2023328

7

34998155

0.0053

(0.51)

0.60

(0.98)

NPSR1

rs329240

7

35024965

0.41

(0.82)

0.038

(0.75)

MS4A2

rs540170

11

59636614

0.049

(0.78)

0.98

(1.0)

MS4A2

rs581133

11

59638882

0.043

(0.78)

0.99

(1.0)

NOS1

rs1093325

12

116179703

0.031

(0.7)

0.23

(0.98)

NOS1

rs1004356

12

116261755

0.026

(0.65)

0.43

(0.98)

IL4R

rs3024585

16

27267345

0.0036

(0.51)

0.98

(1.0)

IL4R

rs1805011

16

27281373

0.011

(0.51)

0.076

(0.97)

IL4R

rs1805012

16

27281465

0.011

(0.51)

0.076

(0.97)

IL4R

rs1805015

16

27281681

0.022

(0.65)

0.11

(0.97)

IL4R

rs3024685

16

27284411

0.045

(0.78)

0.21

(0.98)

IL4R

rs4787956

16

27285750

0.0087

(0.51)

0.17

(0.97)

IL4R

rs4787426

16

27292232

0.026

(0.65)

0.37

(0.98)

ADAM33

rs512625

20

3596378

0.017

(0.65)

0.22

(0.98)

ADAM33

rs2853210

20

3606211

0.046

(0.78)

0.0010

(0.15)

Association between genotype and sensitization to allergens was analyzed using a Kruskal-Wallis rank sum test. False discovery rate was quantified using the q-value introduced by Storey(2002) and are given in parenthesis.

Discussion

In this study, we investigated the SNP associations of well-replicated asthma candidate genes with AR in two independent populations, one Swedish and one Singapore Chinese population. Since there are inherent differences in the genetic architecture between the two populations and this study investigates asthma genes for their eventual contribution also to the AR phenotype, the gene was used as the level of replication and not the individual SNP [22]. A limited number of potential associations were observed and the overall pattern of P-values corresponds in general well to the expectations in the absence of an effect. However, in the tests of allele effects in the Chinese population, the number of significant P-values exceeds the expectations. The strongest signals were found for SNPs in CTLA4 and NPSR1. In each of these genes, more than one SNP showed P-values <0.05 with corresponding Q-values <0.05. In the NPSR1 gene some P-values were lower than the Bonferroni correction level indicating the existence of a true association. When comparing the results from the two populations, i.e. Table 1 vs Table 3 and Table 2 vs Table 4, it is with few exceptions different genes that show significant SNPs. This is what is expected if the significances mainly are due to chance effects generated by the multiple testing. The conclusion that there are few genes in common between AR and asthma is further strengthened by this observation. On the other hand, there is one exception to this, the NPSR1 gene that recurs in all four tables. This observation in turn further point to this gene as the strongest candidate for being a link between AR and asthma, even if one keep in mind the fact that the NPSR1 gene is represented by the largest number of SNPs in both populations. To further investigate this hypothesis, one SNP in NPSR1 (rs324981) was evaluated in an independent sample of 921 AR patients and 390 controls from the Singapore Chinese population. The results (OR=1.65, P=0.007) further strengthen this hypothesis.

Previous studies have reported significant associations for a large region of 47 kb in the NPSR1 gene with asthma even after Bonferroni correction for multiple comparisons (P<0.001). Vergara et al. [23], investigated SNPs in the NPSR1 (GPR154) gene and found associations with asthma and total IgE. Furthermore, this gene has been replicated in studies of Caucasian [2428] and Chinese populations [29], but was not replicated in a Mexican cohort of childhood asthmatics [30]. Thus, the association between variation in NPSR1 and asthma appear to be strongly supported. Since the present study strongly indicates an association with genetic variation in the NPSR1 gene also in AR, there is an obvious risk of asthma being a cxonfounding factor for our results. This was investigated by comparing the association results before and after elimination of patients with any symptoms of asthma. The results convincingly showed that asthma is no confounding factor for the SNPs in NPSR1 and CTLA4 in the Chinese population.

The present result indicates that NPSR1 could be a genetic link between AR and asthma and associations of NPSR1 polymorphisms with AR have not been reported prior to this.

Conclusion

In summary, we have identified NPSR1 and CTLA4 as potential susceptibility genes for AR. However, these genes need to be replicated in additional populations and further characterized to elucidate their role in AR predisposition and pathogenesis. The majority of the highly replicated asthma genes were not associated with AR in our populations, which suggest that asthma and AR could be less similar at the genetic level than previously anticipated.

Notes

Declarations

Acknowledgements

The authors would like to thank all the volunteers and their family members who participated in this study from both the Swedish and Singapore Chinese cohorts.

Authors’ Affiliations

(1)
Department of Biological Sciences, National University of Singapore
(2)
Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR)
(3)
Division of ENT Diseases, CLINTEC, Karolinska Institutet
(4)
Kristianstad University, Section Biomedicine
(5)
Department of Otolaryngology, National University of Singapore
(6)
Department of Cell and Organism Biology, Lund University

References

  1. Bousquet J, Khaltaev N, Cruz AA, Denburg J, Fokkens WJ, Togias A, Zuberbier T, Baena-Cagnani CE, Canonica GW, van Weel C: Allergic Rhinitis and its Impact on Asthma (ARIA) 2008 update (in collaboration with the World Health Organization, GA(2)LEN and AllerGen). Allergy. 2008, 63 (Suppl 86): 8-160.View ArticlePubMedGoogle Scholar
  2. van Beijsterveldt CE, Boomsma DI: Genetics of parentally reported asthma, eczema and rhinitis in 5-yr-old twins. Eur Respir J. 2007, 29 (3): 516-521. 10.1183/09031936.00065706.View ArticlePubMedGoogle Scholar
  3. Rasanen M, Laitinen T, Kaprio J, Koskenvuo M, Laitinen LA: Hay fever–a Finnish nationwide study of adolescent twins and their parents. Allergy. 1998, 53 (9): 885-890. 10.1111/j.1398-9995.1998.tb03996.x.View ArticlePubMedGoogle Scholar
  4. Nilsson D, Andiappan AK, Halldén C, Tim CF, Säll T, Wang DY, Cardell LO: Poor reproducibility of allergic rhinitis SNP associations. PLoS One. in press
  5. Andiappan AK, Wang DY, Anantharaman R, Parate PN, Suri BK, Low HQ, Li Y, Zhao W, Castagnoli P, Liu J: Genome-wide association study for atopy and allergic rhinitis in a Singapore Chinese population. PLoS One. 2011, 6 (5): e19719-10.1371/journal.pone.0019719.View ArticlePubMedPubMed CentralGoogle Scholar
  6. Ramasamy A, Curjuric I, Coin LJ, Kumar A, McArdle WL, Imboden M, Leynaert B, Kogevinas M, Schmid-Grendelmeier P, Pekkanen J: A genome-wide meta-analysis of genetic variants associated with allergic rhinitis and grass sensitization and their interaction with birth order. J Allergy Clin Immunol. 2011, 128 (5): 996-1005. 10.1016/j.jaci.2011.08.030.View ArticlePubMedGoogle Scholar
  7. Chanock SJ, Manolio T, Boehnke M, Boerwinkle E, Hunter DJ, Thomas G, Hirschhorn JN, Abecasis G, Altshuler D, Bailey-Wilson JE: Replicating genotype-phenotype associations. Nature. 2007, 447 (7145): 655-660. 10.1038/447655a.View ArticlePubMedGoogle Scholar
  8. Leynaert B, Neukirch C, Kony S, Guenegou A, Bousquet J, Aubier M, Neukirch F: Association between asthma and rhinitis according to atopic sensitization in a population-based study. J Allergy Clin Immunol. 2004, 113 (1): 86-93. 10.1016/j.jaci.2003.10.010.View ArticlePubMedGoogle Scholar
  9. Linneberg A, Nielsen NH, Frolund L, Madsen F, Dirksen A, Jorgensen T: The link between allergic rhinitis and allergic asthma: a prospective population-based study. The Copenhagen Allergy Study. Allergy. 2002, 57 (11): 1048-1052. 10.1034/j.1398-9995.2002.23664.x.View ArticlePubMedGoogle Scholar
  10. Sichletidis L, Markou S, Daskalopoulou E, Constantinidis T, Tsiotsios J, Pechlivanidis T: The prevalence of asthma and allergic rhinitis among children in Greece. Am J Respir Crit Care Med. 1999, 159 (3): A143-A143.Google Scholar
  11. Ober C, Hoffjan S: Asthma genetics 2006: the long and winding road to gene discovery. Genes Immun. 2006, 7 (2): 95-100. 10.1038/sj.gene.6364284.View ArticlePubMedGoogle Scholar
  12. Rogers AJ, Raby BA, Lasky-Su JA, Murphy A, Lazarus R, Klanderman BJ, Sylvia JS, Ziniti JP, Lange C, Celedon JC: Assessing the reproducibility of asthma candidate gene associations, using genome-wide data. Am J Respir Crit Care Med. 2009, 179 (12): 1084-1090. 10.1164/rccm.200812-1860OC.View ArticlePubMedPubMed CentralGoogle Scholar
  13. Moffatt MF, Gut IG, Demenais F, Strachan DP, Bouzigon E, Heath S, von Mutius E, Farrall M, Lathrop M, Cookson WOCM: A Large-Scale, Consortium-Based Genomewide Association Study of Asthma. N Engl J Med. 2010, 363 (13): 1211-1221. 10.1056/NEJMoa0906312.View ArticlePubMedPubMed CentralGoogle Scholar
  14. Torgerson DG, Ampleford EJ, Chiu GY, Gauderman WJ, Gignoux CR, Graves PE, Himes BE, Levin AM, Mathias RA, Hancock DB: Meta-analysis of genome-wide association studies of asthma in ethnically diverse North American populations. Nat Genet. 2011, 43 (9): 887-U103. 10.1038/ng.888.View ArticlePubMedPubMed CentralGoogle Scholar
  15. Bryborn M, Halldén C, Säll T, Adner M, Cardell LO: Comprehensive evaluation of genetic variation in S100A7 suggests an association with the occurrence of allergic rhinitis. Respir Res. 2008, 9: 29-10.1186/1465-9921-9-29.View ArticlePubMedPubMed CentralGoogle Scholar
  16. Bryborn M, Halldén C, Säll T, Cardell LO: CLC- a novel susceptibility gene for allergic rhinitis?. Allergy. 2010, 65 (2): 220-228. 10.1111/j.1398-9995.2009.02141.x.View ArticlePubMedGoogle Scholar
  17. Nilsson D, Andiappan AK, Halldén C, Yun WD, Säll T, Tim CF, Cardell LO: Toll-like receptor gene polymorphisms are associated with allergic rhinitis: a case control study. BMC Med Genet. 2012, 13 (1): 66-View ArticlePubMedPubMed CentralGoogle Scholar
  18. Anantharaman R, Chew FT: Validation of pooled genotyping on the Affymetrix 500 k and SNP6.0 genotyping platforms using the polynomial-based probe-specific correction. BMC Genet. 2009, 10:Google Scholar
  19. R Development Core Team: R: A language and environment for statistical computing. 2009, Vienna, Austria: R Foundation for Statistical ComputingGoogle Scholar
  20. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker PIW, Daly MJ: PLINK: A tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007, 81 (3): 559-575. 10.1086/519795.View ArticlePubMedPubMed CentralGoogle Scholar
  21. Storey JD: A direct approach to false discovery rates. J R Stat Soc Series B Stat Methodol. 2002, 64: 479-498. 10.1111/1467-9868.00346.View ArticleGoogle Scholar
  22. Neale BM, Sham PC: The future of association studies: gene-based analysis and replication. Am J Hum Genet. 2004, 75 (3): 353-362. 10.1086/423901.View ArticlePubMedPubMed CentralGoogle Scholar
  23. Vergara C, Jimenez S, Acevedo N, Martinez B, Mercado D, Gusmao L, Rafaels N, Hand T, Barnes KC, Caraballo L: Association of G-protein-coupled receptor 154 with asthma and total IgE in a population of the Caribbean coast of Colombia. Clin Exp Allergy. 2009, 39 (10): 1558-1568. 10.1111/j.1365-2222.2009.03311.x.View ArticlePubMedGoogle Scholar
  24. Laitinen T, Polvi A, Rydman P, Vendelin J, Pulkkinen V, Salmikangas P, Makela S, Rehn M, Pirskanen A, Rautanen A: Characterization of a common susceptibility locus for asthma-related traits. Science. 2004, 304 (5668): 300-304. 10.1126/science.1090010.View ArticlePubMedGoogle Scholar
  25. Kormann MSD, Carr D, Klopp N, Illig T, Leupold W, Fritzsch C, Weiland SK, von Mutius E, Kabesch M: G-protein-coupled receptor polymorphisms are associated with asthma in a large German population. Am J Respir Crit Care Med. 2005, 171 (12): 1358-1362. 10.1164/rccm.200410-1312OC.View ArticlePubMedGoogle Scholar
  26. Melen E, Bruce S, Doekes G, Kabesch M, Laitinen T, Lauener R, Lindgren CM, Riedler J, Scheynius A, van Hage-Hamsten M: Haplotypes of G protein-coupled receptor 154 are associated with childhood allergy and asthma. Am J Respir Crit Care Med. 2005, 171 (10): 1089-1095. 10.1164/rccm.200410-1317OC.View ArticlePubMedGoogle Scholar
  27. Malerba G, Lindgren CM, Xumerle L, Kiviluoma P, Trabetti E, Laitinen T, Galavotti R, Pescollderungg L, Boner AL, Kere J: Chromosome 7p linkage and GPR154 gene association in Italian families with allergic asthma. Clin Exp Allergy. 2007, 37 (1): 83-89. 10.1111/j.1365-2222.2006.02615.x.View ArticlePubMedGoogle Scholar
  28. Hersh CP, Raby BA, Soto-Quiros ME, Murphy AJ, Avila L, Lasky-Su J, Sylvia JS, Klanderman BJ, Lange C, Weiss ST: Comprehensive testing of positionally cloned asthma genes in two populations. Am J Respir Crit Care Med. 2007, 176 (9): 849-857. 10.1164/rccm.200704-592OC.View ArticlePubMedPubMed CentralGoogle Scholar
  29. Feng Y, Hong X, Wang L, Jiang S, Chen C, Wang B, Yang J, Fang Z, Zang T, Xu X: G protein-coupled receptor 154 gene polymorphism is associated with airway hyperresponsiveness to methacholine in a Chinese population. J Allergy Clin Immunol. 2006, 117 (3): 612-617. 10.1016/j.jaci.2005.11.045.View ArticlePubMedGoogle Scholar
  30. Wu H, Romieu I, Sienra-Monge JJ, del Rio-Navarro BE, Burdett L, Yuenger J, Li H, Chanock SJ, London SJ: Lack of association between genetic variation in G-protein-coupled receptor for asthma susceptibility and childhood asthma and atopy. Genes Immun. 2008, 9 (3): 224-230. 10.1038/gene.2008.8.View ArticlePubMedPubMed CentralGoogle Scholar
  31. Pre-publication history

    1. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2350/14/51/prepub

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