G-ProteineCcoupled Receptor Polymorphisms Are Associated with Asthma in a Large German Population
http://www.100md.com
美国呼吸和危急护理医学 2005年第6期
University Children's Hospital, Ludwig Maximilian's University Munich, Munich
Institute of Epidemiology, GSFeCResearch Centre for Environment and Health, Neuherberg
University Children's Hospital Dresden, Dresden
University Children's Hospital Leipzig, Leipzig
Institute of Epidemiology, University of Ulm, Ulm, Germany
ABSTRACT
Rationale: Recently, a new asthma susceptibility gene, GPRA (G-proteineCrelated receptor for asthma), has been identified by positional cloning. Initial association studies in a Finnish and Canadian population suggested an association with asthma and elevated serum IgE levels. Objective: In a large, nested case-control study, associations between GPRA polymorphisms, asthma, and serum IgE levels were analyzed. Methods: Using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) technology, 1,872 German children aged 9 to 11 years (including 624 children with asthma and/or bronchial hyperresponsiveness) were genotyped for seven polymorphisms in the GPRA gene. Measurements: Hardy-Weinberg equilibrium was assessed, and association studies with single nucleotide polymorphisms (SNPs) and haplotypes were performed. Main Results: SNP 546333 increased the risk for asthma (odds ratio [OR], 1.40; 95% confidence interval [CI], 1.04eC1.88; p = 0.025) and concomitant asthma and bronchial hyperresponsiveness (BHR; OR, 2.38; 95% CI, 1.22eC4.66; p = 0.009). Also, SNP 585883 was associated with asthma (OR, 1.34; 95% CI, 1.04eC1.72; p = 0.022) and asthma in combination with BHR (OR, 2.71; 95% CI, 1.45eC5.09; p = 0.001). Furthermore, SNP 585883 was associated with elevated serum IgE levels (OR, 1.63; 95% CI, 1.10eC2.42; p = 0.015). Haplotype combinations of risk alleles increased the OR for asthma to 1.83 (95% CI, 1.08eC3.08; p = 0.024) and for asthma and concomitant BHR to OR 3.51 (95% CI, 1.08eC11.37; p = 0.036). Conclusions: These results indicate that GPRA polymorphisms increase the susceptibility for asthma and BHR, and to a lesser degree for the elevation of serum IgE, in a German population, confirming initial observations in other white populations.
Key Words: asthma children GPRA IgE polymorphism
In the last 2 years, three asthma genes have been identified by positional cloning (1eC3). Only recently, Laitinen and coworkers (4) suggested a fourth potential asthma gene discovered by the same basic approach on chromosome 7p. The gene has been named GPRA for G-proteineCcoupled receptor for asthma susceptibility. GPRA polymorphisms were reported to be associated with elevated serum IgE levels in a Finnish and Canadian population. Furthermore, two GPRA isoforms, differing in length between 371 (isoform A) and 377 (isoform B) amino acids, were identified and transcript expression of both isoforms were detected in the lung. Immunohistochemical staining indicated that GPRA isoform B is significantly overexpressed in smooth muscle cells of human patients with asthma compared with normal control subjects. Taken together, these initially reported results indicate that GPRA may play a role in the development of asthma susceptibility. Thus, we tested the hypothesis proposed by Laitinen and coworkers, that GPRA polymorphisms are associated with asthma and the elevation of serum IgE in a large asthma case-control study of German children (n = 1,872).
METHODS
Population Description
Between 1995 and 1996, cross-sectional studies were conducted in Munich (International Study of Asthma and Allergies in Childhood II [ISAAC II]), in Dresden (ISAAC II), and in Leipzig to assess the prevalence of asthma and allergies in 7,963 schoolchildren aged 9 to 11 years (5, 6). Informed, written consent was obtained from all parents of children included in the study. All study methods were approved by the local ethics committees. Because the populations and phenotyping methods have been described in detail before (5), only an overview of the methods pertaining to this analysis is given here. For this analysis, all children who had a doctor's diagnosis of asthma and/or showed bronchial hyperresponsiveness (BHR; n = 671; Munich, n = 264; Dresden, n = 276; Leipzig, n = 131) were selected from the total study population. These children were matched at a 2:1 ratio with a random selection of healthy children without asthma or atopy and without a diagnosis of BHR (n = 1,342; Munich, n = 528; Dresden, n = 552; Leipzig, n = 262), and finally, only children of German origin who had both DNA and IgE data available were included (n = 1,872; Munich, n = 690; Dresden, n = 789; Leipzig, n = 393).
Subject Phenotyping
Questionnaires.
Parental questionnaires for self-completion were sent through the schools to the families, including the ISAAC core questions, whereas slightly different questionnaires were used for the Leipzig population (7). All children whose parents reported that a doctor diagnosed "asthma" at least once or "asthmatic, spastic, or obstructive bronchitis" more than once were defined as having asthma.
Spirometry and bronchial challenge.
Lung function was measured by MasterScope version 4.1 (Jger, Wezburg, Germany) according to ISAAC phase II protocols. A minimum of two baseline spirograms were recorded and the highest of two reproducible (within 5%) measurements of FEV1 was recorded as baseline FEV1. In Munich and Dresden, bronchial reactivity was assessed by changes in FEV1 after inhalation of nebulized, hyperosmolar (4.5%) saline for increasing periods of time using ultrasound nebulizers (DeVilbiss Sunrise Medical, Langen, Germany). In Leipzig, BHR was measured by cold air (eC15°C) hyperventilation for 4 minutes (6). All children with a drop in FEV1 of 15% or more from baseline after hypertonic saline challenge or a 9% drop after cold air challenge were classified as having BHR.
Blood analysis.
Levels of total serum IgE were measured in a 50% random subsample of all children with serum specimen using the Insulite system (DPC Biermann, Bad Nauheim, Germany). On the basis of all available study subjects with existing IgE measurements in our dataset (n = 3,063), IgE percentiles were calculated. The 90th percentile (457 IU/ml) for total serum IgE was used as the outcome variable.
Genetic Analyses
Genomic DNA was extracted from whole blood by a standard salting-out method (8), and a modified primer extension preamplification (PEP) method was applied to reduce the amount of DNA necessary for the analysis (9). For genotyping, the MassArray system (Sequenom, San Diego, CA) was used (10). First, a polymerase chain reaction was performed in a total volume of 6 e with 5 ng PEP-DNA, a final primer concentration each of 1 e (Table 1), 2.5 mM MgCl2, 0.2 mM of each deoxynucleoside triphosphate (dNTP) and 0.1 U of HotStarTaq DNA polymerase (Qiagen, Hilden, Germany). To remove excessive dNTPs, shrimp alkaline phosphatase (Amersham, Freiburg, Germany) was added to the polymerase chain reaction products for 20 minutes at 37°C with a following step to inactivate the shrimp alkaline phosphatase at 85°C for 10 minutes. The base-specific extension reaction (Table 1) was performed in 10-e reactions by Thermosequenase (Amersham, Piscataway, NJ), with a final concentration of 5.4 e of the extension primer. For the base extension reaction, the denaturation was performed at 94°C for 2 minutes, followed by 94°C for 5 seconds, 56°C for 5 seconds, and 72°C for 5 seconds for 40 cycles. All reactions (polymerase chain reaction amplification and base extension) were performed in a Tetrad polymerase chain reaction thermal cycler (MJ Research, Waltham, MA). The final base extension products were treated with SpectroClean resin (Sequenom) to remove salts out of the reaction buffer. This step was performed with a Multimek 96-channel autopipette (Beckman Coulter, Fullerton, CA), and 16 e of water was added into each base extension reaction, making the total volume 26 e. After a quick centrifugation (2,000 rpm, 3 minutes) in a Centrifuge 5810 (Eppendorf, Hamburg, Germany), 10 nl of reaction solution were dispensed onto a 384-format SpectroChip (Sequenom) prespotted with a matrix of 3-hydroxypicolinic acid by using a SpectroPoint nanodispenser (Sequenom). A matrix-assisted laser desorption ionization time-of-flight mass spectrometer, model Bruker Autoflex (Sequenom), was used for data acquisitions from the SpectroChip. Genotyping calls were made in real time with MassArray RT software (Sequenom).
Statistical Analyses
Hardy-Weinberg equilibrium (HWE) was tested as a genotyping quality control procedure using the 2 statistic, with expected frequencies derived from allele frequencies. Univariate associations between single nucleotide polymorphisms (SNPs) and outcomes for asthma and elevated IgE (90th percentile) were investigated using odds ratios (11). Haplotype frequencies were estimated using the expectation-maximization algorithm (12). To evaluate associations with traits, haplotype trend regression models were estimated, where the estimated probabilities of the haplotypes are modeled in a logistic regression as independent variables (13, 14). A stepwise approach was implemented with haplotypes from combinations of two to six SNPs. All statistical analyses were performed using the SAS statistical software package (version 9.1; SAS, Inc., Cary, NC); the haplotype analyses were implemented using the SAS/Genetics module, whereas the graphical overview of linkage disequilibrium (GOLD) was created using the GOLD 1.0 package (http://www.well.ox.ac.uk/asthma/GOLD).
RESULTS
Seven SNPs representing all previously observed haplotypes were selected for genotyping (Table 1). Call rates for SNPs in GPRA ranged from 96.7 to 99.1%, and all SNPs except 555608 were in HWE (Table 2). Thus, SNP 555608 was excluded from further haplotype analyses. In our large German sample, all SNPs showed allele frequencies similar to those originally reported in the Finish and Canadian population (Table 1). Using a normalized correlation coefficient, the degree of linkage disequilibrium was assessed between single polymorphisms, and a GOLD plot of the average linkage disequilibrium across the GPRA SNPs is shown (Figure 1). Color denotes the degree of linkage disequilibrium between a given pair.
A summary of association results between single GPRA polymorphisms, asthma, BHR, concomitant asthma and BHR, and elevated serum IgE (90th percentile) is given in Table 3 as odds ratios (OR) and 95% confidence intervals (95% CI). A significant association was observed between the SNPs 546333, and 585883 and the risk to develop asthma, whereas the minor allele of SNP 563704 was protective against the development of asthma. Associations with BHR per se did not reach statistical significance. However, in a subgroup analysis of children with concomitant asthma and BHR, the addition of BHR amplified the association between the two SNPs related to asthma: SNP 546333 was highly significantly associated with asthma and BHR (OR, 2.38; 95% CI, 1.22eC4.66; p = 0.009) and a similar modification of the risk for asthma and concomitant BHR was observed for SNP 585883 (OR, 2.71; 95% CI, 1.45eC5.09; p = 0.001). In addition, homozygote carriers of the polymorphic forms of SNP 563704 were protected against the development of elevated serum IgE levels (OR, 0.33; 95% CI, 0.12eC0.93; p = 0.028). In contrast, having at least one polymorphic allele of SNP 585883 increased the risk for very high serum IgE levels (OR, 1.63; 95% CI, 1.01eC2.54; p = 0.015).
For haplotype analysis, 1,794 samples were available in which genotyping was successful for all six GPRA polymorphisms (SNP 555608 was excluded from further analysis because of HWE). When all available haplotype combinations with a frequency more than 3% were assessed, haplotype CCAACC, which combined the risk alleles of all observed single SNP associations, showed a significant association with asthma (OR, 1.83; 95% CI, 1.08eC3.08; p = 0.024) and with the subphenotype combination of asthma and BHR (OR, 3.51; 95% CI, 1.08eC11.37; p = 0.036; Table 4). A borderline association with elevated IgE levels was observed for the same high-risk haplotype (OR, 2.16; 95% CI, 0.97eC4.83; p = 0.060). Because our population was selected as a case-control population for asthma, the effects of GPRA polymorphisms on other atopic diseases like hay fever or atopic dermatitis could not be assessed because of potential selection bias in a case-control setting.
DISCUSSION
Asthma genes detected by positional cloning based on linkage studies had been anticipated for years and when they finally started to appear, they were celebrated enthusiastically as a big step toward the disentanglement of the Gordian knot of the complex asthma genetics. However, it seems that reports on positionally cloned genes deserve the same amount of initial skepticism as the ever-increasing number of results stemming from association studies using the candidate gene approach. Learning from experience with ADAM33, DPP10, and PHF11, it seems clear that the dissection of the functional relevance of SNPs in these genes as well as independent replications of the original associations in large population samples are key for the assessment of their impact on asthma susceptibility. Although functional studies of polymorphism effects are necessary to understand disease mechanisms, they are time-consuming and tedious. On the other hand, using modern genotyping techniques, replication of associations in independent populations can be achieved quickly to prove or disprove initial findings.
This study examined seven SNPs in the GPRA gene. Although all tested SNPs are located within a short physical distance in the region of intron 2, they represent all possible haplotypes in the previously described 77-kb risk haplotype block harboring the GPRA gene (4). SNP 555608 has been finally excluded from association analyses because it showed deviation from expected HWE genotype frequencies. A departure from HWE may be indicative of methodologic assay problems in genotyping a certain SNP. Thus, it has been proposed to exclude SNPs deviating from HWE as an approach to improve data quality (15). However, distortion from HWE may also be caused by biological effects or population characteristics leading to a nonrandom distribution of alleles. This can be the case in populations with strong founder effects or clear biological and reproductive advantages of certain SNPs. In the case of GPRA, both methodologic and biological effects could be responsible for the observed deviation from HWE. Because we cannot rule out a methodologic genotyping error or a selection bias, SNP 555608 was excluded from further analyses following common practice in genetic studies to avoid false association reports.
The associations initially observed between GPRA haplotypes, elevated serum IgE, and asthma in cohorts from Finland and Canada could be replicated in our large German case-control sample. A statistically significant increased risk to develop asthma was observed for two single SNPs. When a subphenotype of concomitant asthma and BHR was analyzed, the observed risk for both SNPs and the strength of these associations further increased. These findings may indicate that GPRA is a gene involved in lung-specific allergic inflammation because GPRA polymorphisms are strongly associated with BHR in the presence of an asthmatic airway inflammation but no association was observed with BHR alone. Because of the consistent association between GPRA and the regulation of serum IgE in our population and in that of Laitinen and coworkers (4), it may be speculated that GPRA is not only a pulmonary-expressed gene important for asthma susceptibility but that it may also play a more general immunomodulatory role. On the basis of the detection of GPRA molecules in ciliated cells of the airways and airway smooth muscle cells after sensitization (4), it is possible that GPRA may play an important role in conferring bronchial asthma by translating atopic sensitization into bronchial inflammation and BHR. In this sense, GPRA may be a link between systemic atopic sensitization and the development of pulmonary symptoms. Thus, GPRA polymorphisms could modify this translation from atopy to asthma. One could also hypothesize that individuals with asthma with certain GPRA polymorphisms are more likely to present BHR as an expression of a more severe form of asthma and that GPRA may also be involved in airway remodeling. However, to further investigate this hypothesis, cohort studies may be needed.
An even more profound effect was observed when GPRA haplotypes were analyzed. Associations for all haplotypes composed of the six investigated SNPs with a frequency larger than 3% were assessed. The combination CCAACC, present in 9% of the population, showed a higher risk for asthma than any single SNP. Furthermore, the risk for asthma and concomitant BHR increased substantially from an OR of 2.71 for the maximum effect for a single SNP to 3.51 for the risk haplotype CCAACC (Table 4). It is interesting that the haplotype CCAACC conferring the highest risk for asthma and asthma with concomitant BHR in our study population is equivalent to the originally reported haplotype H4, which was associated with elevated levels of serum IgE in the Finnish population (4). We also investigated haplotype H2 (CCAG[T]CG) reported to be associated with asthma in the Quebec population but could not confirm the previous findings. In addition, the exclusion of SNP 555608 because of HWE in our population made it impossible to discriminate haplotypes H3 and H6 originally described by Laitinen and coworkers as nonrisk. In a parallel study by Meleen and coworkers (16), however, the rather infrequent haplotype H6 conferred a risk for atopic sensitization in two populations. Because of the missing information on SNP 555608, both H3 and H6 had to be analyzed together in our study and a potential effect of H6 may have been missed.
In contrast to the original study by Laitinen and coworkers in adults, we here present data on the association between GPRA polymorphisms and asthma, BHR, and IgE regulation in children. There may be profound differences in clinical as well as immunologic aspects of childhood asthma compared with adult asthma. It has been proposed that different forms of asthma may overlap during childhood, potentially representing different etiologies. Early transient, continuous, and late-onset wheezing can be distinguished in longitudinal studies of childhood asthma (17). In our cross-sectional study, children were evaluated at the age of 9 to 11 years, and the definition of asthma was based on lifetime prevalence assessed through questionnaires. Therefore, in our population, these three subgroups of wheezers cannot be determined unambiguously. However, because of the inclusion criteria in the questionnaire, transient wheezers should not have been labeled asthmatic in our study population. Even though some heterogeneity exists between different forms of childhood asthma and between childhood asthma and adult asthma, our results in combination with those of Laitinen and colleagues (4) indicate that mechanisms common to both childhood and adult asthma may be influenced by GPRA polymorphisms. How GPRA exerts its function and how SNPs in GPRA alter these mechanisms is still not clear. However, it seems that the consistent effects of GPRA polymorphisms now documented in different independent studies may well justify a closer look into the functional properties of GPRA in the development of asthma, BHR, and atopy.
Acknowledgments
The authors thank Cecilia Lindgren and Juha Kere from the Karolinska Institute, Stockholm, Sweden, for their kind supply of primer and assay information for genotyping. Genotyping was performed in the Genome Analysis Center of the GSF (Gesellschaft fe Strahlenforschung).
REFERENCES
Van Eerdewegh P, Little RD, Dupuis J, Del Mastro RG, Falls K, Simon J, Torrey D, Pandit S, McKenny J, Braunschweiger K, et al. Association of the ADAM33 gene with asthma and bronchial hyperresponsiveness. Nature 2002;418:426eC430.
Allen M, Heinzmann A, Noguchi E, Abecasis G, Broxholme J, Ponting CP, Bhattacharyya S, Tinsley J, Zhang Y, Holt R, et al. Positional cloning of a novel gene influencing asthma from chromosome 2q14. Nat Genet 2003;35:258eC263.
Zhang Y, Leaves NI, Anderson GG, Ponting CP, Broxholme J, Holt R, Edser P, Bhattacharyya S, Dunham A, Adcock IM, et al. Positional cloning of a quantitative trait locus on chromosome 13q14 that influences immunoglobulin E levels and asthma. Nat Genet 2003;34:181eC186.
Laitinen T, Polvi A, Rydman P, Vendelin J, Pulkkinen V, Salmikangas P, Makela S, Rehn M, Pirskanen A, Rautanen A, et al. Characterization of a common susceptibility locus for asthma-related traits. Science 2004;304:300eC304.
Weiland SK, von Mutius E, Hirsch T, Duhme H, Fritzsch C, Werner B, Husing A, Stender M, Renz H, Leupold W, et al. Prevalence of respiratory and atopic disorders among children in the East and West of Germany five years after unification. Eur Respir J 1999;14:862eC870.
von Mutius E, Weiland SK, Fritzsch C, Duhme H, Keil U. Increasing prevalence of hay fever and atopy among children in Leipzig, East Germany. Lancet 1998;351:862eC866.
ISAAC Steering Committee (Writing Committee: Beasley RKU, von Mutius E, Pearce N). Worldwide variations in the prevalence of atopic diseases: the International Study of Asthma and Allergies in Childhood (ISAAC). Lancet 1998;351:1225eC1232.
Miller SA, Dykes DD, Poletsky HF. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res 1988;16:1215.
Zhang L, Cui X, Schmitt K, Hubert R, Navidi W, Arnheim N. Whole genome amplification from a single cell: implications for genetic analysis. Proc Natl Acad Sci USA 1992;89:5847eC5851.
Ding C, Cantor CR. A high-throughput gene expression analysis technique using competitive PCR and matrix-assisted laser desorption ionization time-of-flight MS. Proc Natl Acad Sci USA 2003;100:3059eC3064.
Sasieni PD. From genotypes to genes: doubling the sample size. Biometrics 1997;53:1253eC1261.
Excoffier L, Slatkin M. Maximum-likelihood estimation of molecular haplotype frequencies in a diploid population. Mol Biol Evol 1995;12:921eC927.
Zaykin DV, Westfall PH, Young SS, Karnoub MA, Wagner MJ, Ehm MG. Testing association of statistically inferred haplotypes with discrete and continuous traits in samples of unrelated individuals. Hum Hered 2002;53:79eC91.
SAS II. SAS/Genetics(r) user's guide. Cary, NC: SAS, Inc.; 2002.
Hosking L, Lumsden S, Lewis K, Yeo A, McCarthy L, Bansal A, Riley J, Purvis I, Xu CF. Detection of genotyping errors by Hardy-Weinberg equilibrium testing. Eur J Hum Genet 2004;12:395eC399.
Meleen E, Bruce S, Doekes G, Kabesch M, Laitinen T, Lauener R, Lindgren CM, Riedler J, Schneynius A, van Hage-Hamsten M, et al. Haplotypes of G proteineCcoupled receptor 154 are associated with childhood allergy and asthma. Am J Respir Crit Care Med (In press)
Martinez FD, Wright AL, Taussig LM, Holberg CJ, Halonen M, Morgan WJ. Asthma and wheezing in the first six years of life. The Group Health Medical Associates. N Engl J Med 1995;332:133eC138.(Michael S. D. Kormann, Da)
Institute of Epidemiology, GSFeCResearch Centre for Environment and Health, Neuherberg
University Children's Hospital Dresden, Dresden
University Children's Hospital Leipzig, Leipzig
Institute of Epidemiology, University of Ulm, Ulm, Germany
ABSTRACT
Rationale: Recently, a new asthma susceptibility gene, GPRA (G-proteineCrelated receptor for asthma), has been identified by positional cloning. Initial association studies in a Finnish and Canadian population suggested an association with asthma and elevated serum IgE levels. Objective: In a large, nested case-control study, associations between GPRA polymorphisms, asthma, and serum IgE levels were analyzed. Methods: Using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) technology, 1,872 German children aged 9 to 11 years (including 624 children with asthma and/or bronchial hyperresponsiveness) were genotyped for seven polymorphisms in the GPRA gene. Measurements: Hardy-Weinberg equilibrium was assessed, and association studies with single nucleotide polymorphisms (SNPs) and haplotypes were performed. Main Results: SNP 546333 increased the risk for asthma (odds ratio [OR], 1.40; 95% confidence interval [CI], 1.04eC1.88; p = 0.025) and concomitant asthma and bronchial hyperresponsiveness (BHR; OR, 2.38; 95% CI, 1.22eC4.66; p = 0.009). Also, SNP 585883 was associated with asthma (OR, 1.34; 95% CI, 1.04eC1.72; p = 0.022) and asthma in combination with BHR (OR, 2.71; 95% CI, 1.45eC5.09; p = 0.001). Furthermore, SNP 585883 was associated with elevated serum IgE levels (OR, 1.63; 95% CI, 1.10eC2.42; p = 0.015). Haplotype combinations of risk alleles increased the OR for asthma to 1.83 (95% CI, 1.08eC3.08; p = 0.024) and for asthma and concomitant BHR to OR 3.51 (95% CI, 1.08eC11.37; p = 0.036). Conclusions: These results indicate that GPRA polymorphisms increase the susceptibility for asthma and BHR, and to a lesser degree for the elevation of serum IgE, in a German population, confirming initial observations in other white populations.
Key Words: asthma children GPRA IgE polymorphism
In the last 2 years, three asthma genes have been identified by positional cloning (1eC3). Only recently, Laitinen and coworkers (4) suggested a fourth potential asthma gene discovered by the same basic approach on chromosome 7p. The gene has been named GPRA for G-proteineCcoupled receptor for asthma susceptibility. GPRA polymorphisms were reported to be associated with elevated serum IgE levels in a Finnish and Canadian population. Furthermore, two GPRA isoforms, differing in length between 371 (isoform A) and 377 (isoform B) amino acids, were identified and transcript expression of both isoforms were detected in the lung. Immunohistochemical staining indicated that GPRA isoform B is significantly overexpressed in smooth muscle cells of human patients with asthma compared with normal control subjects. Taken together, these initially reported results indicate that GPRA may play a role in the development of asthma susceptibility. Thus, we tested the hypothesis proposed by Laitinen and coworkers, that GPRA polymorphisms are associated with asthma and the elevation of serum IgE in a large asthma case-control study of German children (n = 1,872).
METHODS
Population Description
Between 1995 and 1996, cross-sectional studies were conducted in Munich (International Study of Asthma and Allergies in Childhood II [ISAAC II]), in Dresden (ISAAC II), and in Leipzig to assess the prevalence of asthma and allergies in 7,963 schoolchildren aged 9 to 11 years (5, 6). Informed, written consent was obtained from all parents of children included in the study. All study methods were approved by the local ethics committees. Because the populations and phenotyping methods have been described in detail before (5), only an overview of the methods pertaining to this analysis is given here. For this analysis, all children who had a doctor's diagnosis of asthma and/or showed bronchial hyperresponsiveness (BHR; n = 671; Munich, n = 264; Dresden, n = 276; Leipzig, n = 131) were selected from the total study population. These children were matched at a 2:1 ratio with a random selection of healthy children without asthma or atopy and without a diagnosis of BHR (n = 1,342; Munich, n = 528; Dresden, n = 552; Leipzig, n = 262), and finally, only children of German origin who had both DNA and IgE data available were included (n = 1,872; Munich, n = 690; Dresden, n = 789; Leipzig, n = 393).
Subject Phenotyping
Questionnaires.
Parental questionnaires for self-completion were sent through the schools to the families, including the ISAAC core questions, whereas slightly different questionnaires were used for the Leipzig population (7). All children whose parents reported that a doctor diagnosed "asthma" at least once or "asthmatic, spastic, or obstructive bronchitis" more than once were defined as having asthma.
Spirometry and bronchial challenge.
Lung function was measured by MasterScope version 4.1 (Jger, Wezburg, Germany) according to ISAAC phase II protocols. A minimum of two baseline spirograms were recorded and the highest of two reproducible (within 5%) measurements of FEV1 was recorded as baseline FEV1. In Munich and Dresden, bronchial reactivity was assessed by changes in FEV1 after inhalation of nebulized, hyperosmolar (4.5%) saline for increasing periods of time using ultrasound nebulizers (DeVilbiss Sunrise Medical, Langen, Germany). In Leipzig, BHR was measured by cold air (eC15°C) hyperventilation for 4 minutes (6). All children with a drop in FEV1 of 15% or more from baseline after hypertonic saline challenge or a 9% drop after cold air challenge were classified as having BHR.
Blood analysis.
Levels of total serum IgE were measured in a 50% random subsample of all children with serum specimen using the Insulite system (DPC Biermann, Bad Nauheim, Germany). On the basis of all available study subjects with existing IgE measurements in our dataset (n = 3,063), IgE percentiles were calculated. The 90th percentile (457 IU/ml) for total serum IgE was used as the outcome variable.
Genetic Analyses
Genomic DNA was extracted from whole blood by a standard salting-out method (8), and a modified primer extension preamplification (PEP) method was applied to reduce the amount of DNA necessary for the analysis (9). For genotyping, the MassArray system (Sequenom, San Diego, CA) was used (10). First, a polymerase chain reaction was performed in a total volume of 6 e with 5 ng PEP-DNA, a final primer concentration each of 1 e (Table 1), 2.5 mM MgCl2, 0.2 mM of each deoxynucleoside triphosphate (dNTP) and 0.1 U of HotStarTaq DNA polymerase (Qiagen, Hilden, Germany). To remove excessive dNTPs, shrimp alkaline phosphatase (Amersham, Freiburg, Germany) was added to the polymerase chain reaction products for 20 minutes at 37°C with a following step to inactivate the shrimp alkaline phosphatase at 85°C for 10 minutes. The base-specific extension reaction (Table 1) was performed in 10-e reactions by Thermosequenase (Amersham, Piscataway, NJ), with a final concentration of 5.4 e of the extension primer. For the base extension reaction, the denaturation was performed at 94°C for 2 minutes, followed by 94°C for 5 seconds, 56°C for 5 seconds, and 72°C for 5 seconds for 40 cycles. All reactions (polymerase chain reaction amplification and base extension) were performed in a Tetrad polymerase chain reaction thermal cycler (MJ Research, Waltham, MA). The final base extension products were treated with SpectroClean resin (Sequenom) to remove salts out of the reaction buffer. This step was performed with a Multimek 96-channel autopipette (Beckman Coulter, Fullerton, CA), and 16 e of water was added into each base extension reaction, making the total volume 26 e. After a quick centrifugation (2,000 rpm, 3 minutes) in a Centrifuge 5810 (Eppendorf, Hamburg, Germany), 10 nl of reaction solution were dispensed onto a 384-format SpectroChip (Sequenom) prespotted with a matrix of 3-hydroxypicolinic acid by using a SpectroPoint nanodispenser (Sequenom). A matrix-assisted laser desorption ionization time-of-flight mass spectrometer, model Bruker Autoflex (Sequenom), was used for data acquisitions from the SpectroChip. Genotyping calls were made in real time with MassArray RT software (Sequenom).
Statistical Analyses
Hardy-Weinberg equilibrium (HWE) was tested as a genotyping quality control procedure using the 2 statistic, with expected frequencies derived from allele frequencies. Univariate associations between single nucleotide polymorphisms (SNPs) and outcomes for asthma and elevated IgE (90th percentile) were investigated using odds ratios (11). Haplotype frequencies were estimated using the expectation-maximization algorithm (12). To evaluate associations with traits, haplotype trend regression models were estimated, where the estimated probabilities of the haplotypes are modeled in a logistic regression as independent variables (13, 14). A stepwise approach was implemented with haplotypes from combinations of two to six SNPs. All statistical analyses were performed using the SAS statistical software package (version 9.1; SAS, Inc., Cary, NC); the haplotype analyses were implemented using the SAS/Genetics module, whereas the graphical overview of linkage disequilibrium (GOLD) was created using the GOLD 1.0 package (http://www.well.ox.ac.uk/asthma/GOLD).
RESULTS
Seven SNPs representing all previously observed haplotypes were selected for genotyping (Table 1). Call rates for SNPs in GPRA ranged from 96.7 to 99.1%, and all SNPs except 555608 were in HWE (Table 2). Thus, SNP 555608 was excluded from further haplotype analyses. In our large German sample, all SNPs showed allele frequencies similar to those originally reported in the Finish and Canadian population (Table 1). Using a normalized correlation coefficient, the degree of linkage disequilibrium was assessed between single polymorphisms, and a GOLD plot of the average linkage disequilibrium across the GPRA SNPs is shown (Figure 1). Color denotes the degree of linkage disequilibrium between a given pair.
A summary of association results between single GPRA polymorphisms, asthma, BHR, concomitant asthma and BHR, and elevated serum IgE (90th percentile) is given in Table 3 as odds ratios (OR) and 95% confidence intervals (95% CI). A significant association was observed between the SNPs 546333, and 585883 and the risk to develop asthma, whereas the minor allele of SNP 563704 was protective against the development of asthma. Associations with BHR per se did not reach statistical significance. However, in a subgroup analysis of children with concomitant asthma and BHR, the addition of BHR amplified the association between the two SNPs related to asthma: SNP 546333 was highly significantly associated with asthma and BHR (OR, 2.38; 95% CI, 1.22eC4.66; p = 0.009) and a similar modification of the risk for asthma and concomitant BHR was observed for SNP 585883 (OR, 2.71; 95% CI, 1.45eC5.09; p = 0.001). In addition, homozygote carriers of the polymorphic forms of SNP 563704 were protected against the development of elevated serum IgE levels (OR, 0.33; 95% CI, 0.12eC0.93; p = 0.028). In contrast, having at least one polymorphic allele of SNP 585883 increased the risk for very high serum IgE levels (OR, 1.63; 95% CI, 1.01eC2.54; p = 0.015).
For haplotype analysis, 1,794 samples were available in which genotyping was successful for all six GPRA polymorphisms (SNP 555608 was excluded from further analysis because of HWE). When all available haplotype combinations with a frequency more than 3% were assessed, haplotype CCAACC, which combined the risk alleles of all observed single SNP associations, showed a significant association with asthma (OR, 1.83; 95% CI, 1.08eC3.08; p = 0.024) and with the subphenotype combination of asthma and BHR (OR, 3.51; 95% CI, 1.08eC11.37; p = 0.036; Table 4). A borderline association with elevated IgE levels was observed for the same high-risk haplotype (OR, 2.16; 95% CI, 0.97eC4.83; p = 0.060). Because our population was selected as a case-control population for asthma, the effects of GPRA polymorphisms on other atopic diseases like hay fever or atopic dermatitis could not be assessed because of potential selection bias in a case-control setting.
DISCUSSION
Asthma genes detected by positional cloning based on linkage studies had been anticipated for years and when they finally started to appear, they were celebrated enthusiastically as a big step toward the disentanglement of the Gordian knot of the complex asthma genetics. However, it seems that reports on positionally cloned genes deserve the same amount of initial skepticism as the ever-increasing number of results stemming from association studies using the candidate gene approach. Learning from experience with ADAM33, DPP10, and PHF11, it seems clear that the dissection of the functional relevance of SNPs in these genes as well as independent replications of the original associations in large population samples are key for the assessment of their impact on asthma susceptibility. Although functional studies of polymorphism effects are necessary to understand disease mechanisms, they are time-consuming and tedious. On the other hand, using modern genotyping techniques, replication of associations in independent populations can be achieved quickly to prove or disprove initial findings.
This study examined seven SNPs in the GPRA gene. Although all tested SNPs are located within a short physical distance in the region of intron 2, they represent all possible haplotypes in the previously described 77-kb risk haplotype block harboring the GPRA gene (4). SNP 555608 has been finally excluded from association analyses because it showed deviation from expected HWE genotype frequencies. A departure from HWE may be indicative of methodologic assay problems in genotyping a certain SNP. Thus, it has been proposed to exclude SNPs deviating from HWE as an approach to improve data quality (15). However, distortion from HWE may also be caused by biological effects or population characteristics leading to a nonrandom distribution of alleles. This can be the case in populations with strong founder effects or clear biological and reproductive advantages of certain SNPs. In the case of GPRA, both methodologic and biological effects could be responsible for the observed deviation from HWE. Because we cannot rule out a methodologic genotyping error or a selection bias, SNP 555608 was excluded from further analyses following common practice in genetic studies to avoid false association reports.
The associations initially observed between GPRA haplotypes, elevated serum IgE, and asthma in cohorts from Finland and Canada could be replicated in our large German case-control sample. A statistically significant increased risk to develop asthma was observed for two single SNPs. When a subphenotype of concomitant asthma and BHR was analyzed, the observed risk for both SNPs and the strength of these associations further increased. These findings may indicate that GPRA is a gene involved in lung-specific allergic inflammation because GPRA polymorphisms are strongly associated with BHR in the presence of an asthmatic airway inflammation but no association was observed with BHR alone. Because of the consistent association between GPRA and the regulation of serum IgE in our population and in that of Laitinen and coworkers (4), it may be speculated that GPRA is not only a pulmonary-expressed gene important for asthma susceptibility but that it may also play a more general immunomodulatory role. On the basis of the detection of GPRA molecules in ciliated cells of the airways and airway smooth muscle cells after sensitization (4), it is possible that GPRA may play an important role in conferring bronchial asthma by translating atopic sensitization into bronchial inflammation and BHR. In this sense, GPRA may be a link between systemic atopic sensitization and the development of pulmonary symptoms. Thus, GPRA polymorphisms could modify this translation from atopy to asthma. One could also hypothesize that individuals with asthma with certain GPRA polymorphisms are more likely to present BHR as an expression of a more severe form of asthma and that GPRA may also be involved in airway remodeling. However, to further investigate this hypothesis, cohort studies may be needed.
An even more profound effect was observed when GPRA haplotypes were analyzed. Associations for all haplotypes composed of the six investigated SNPs with a frequency larger than 3% were assessed. The combination CCAACC, present in 9% of the population, showed a higher risk for asthma than any single SNP. Furthermore, the risk for asthma and concomitant BHR increased substantially from an OR of 2.71 for the maximum effect for a single SNP to 3.51 for the risk haplotype CCAACC (Table 4). It is interesting that the haplotype CCAACC conferring the highest risk for asthma and asthma with concomitant BHR in our study population is equivalent to the originally reported haplotype H4, which was associated with elevated levels of serum IgE in the Finnish population (4). We also investigated haplotype H2 (CCAG[T]CG) reported to be associated with asthma in the Quebec population but could not confirm the previous findings. In addition, the exclusion of SNP 555608 because of HWE in our population made it impossible to discriminate haplotypes H3 and H6 originally described by Laitinen and coworkers as nonrisk. In a parallel study by Meleen and coworkers (16), however, the rather infrequent haplotype H6 conferred a risk for atopic sensitization in two populations. Because of the missing information on SNP 555608, both H3 and H6 had to be analyzed together in our study and a potential effect of H6 may have been missed.
In contrast to the original study by Laitinen and coworkers in adults, we here present data on the association between GPRA polymorphisms and asthma, BHR, and IgE regulation in children. There may be profound differences in clinical as well as immunologic aspects of childhood asthma compared with adult asthma. It has been proposed that different forms of asthma may overlap during childhood, potentially representing different etiologies. Early transient, continuous, and late-onset wheezing can be distinguished in longitudinal studies of childhood asthma (17). In our cross-sectional study, children were evaluated at the age of 9 to 11 years, and the definition of asthma was based on lifetime prevalence assessed through questionnaires. Therefore, in our population, these three subgroups of wheezers cannot be determined unambiguously. However, because of the inclusion criteria in the questionnaire, transient wheezers should not have been labeled asthmatic in our study population. Even though some heterogeneity exists between different forms of childhood asthma and between childhood asthma and adult asthma, our results in combination with those of Laitinen and colleagues (4) indicate that mechanisms common to both childhood and adult asthma may be influenced by GPRA polymorphisms. How GPRA exerts its function and how SNPs in GPRA alter these mechanisms is still not clear. However, it seems that the consistent effects of GPRA polymorphisms now documented in different independent studies may well justify a closer look into the functional properties of GPRA in the development of asthma, BHR, and atopy.
Acknowledgments
The authors thank Cecilia Lindgren and Juha Kere from the Karolinska Institute, Stockholm, Sweden, for their kind supply of primer and assay information for genotyping. Genotyping was performed in the Genome Analysis Center of the GSF (Gesellschaft fe Strahlenforschung).
REFERENCES
Van Eerdewegh P, Little RD, Dupuis J, Del Mastro RG, Falls K, Simon J, Torrey D, Pandit S, McKenny J, Braunschweiger K, et al. Association of the ADAM33 gene with asthma and bronchial hyperresponsiveness. Nature 2002;418:426eC430.
Allen M, Heinzmann A, Noguchi E, Abecasis G, Broxholme J, Ponting CP, Bhattacharyya S, Tinsley J, Zhang Y, Holt R, et al. Positional cloning of a novel gene influencing asthma from chromosome 2q14. Nat Genet 2003;35:258eC263.
Zhang Y, Leaves NI, Anderson GG, Ponting CP, Broxholme J, Holt R, Edser P, Bhattacharyya S, Dunham A, Adcock IM, et al. Positional cloning of a quantitative trait locus on chromosome 13q14 that influences immunoglobulin E levels and asthma. Nat Genet 2003;34:181eC186.
Laitinen T, Polvi A, Rydman P, Vendelin J, Pulkkinen V, Salmikangas P, Makela S, Rehn M, Pirskanen A, Rautanen A, et al. Characterization of a common susceptibility locus for asthma-related traits. Science 2004;304:300eC304.
Weiland SK, von Mutius E, Hirsch T, Duhme H, Fritzsch C, Werner B, Husing A, Stender M, Renz H, Leupold W, et al. Prevalence of respiratory and atopic disorders among children in the East and West of Germany five years after unification. Eur Respir J 1999;14:862eC870.
von Mutius E, Weiland SK, Fritzsch C, Duhme H, Keil U. Increasing prevalence of hay fever and atopy among children in Leipzig, East Germany. Lancet 1998;351:862eC866.
ISAAC Steering Committee (Writing Committee: Beasley RKU, von Mutius E, Pearce N). Worldwide variations in the prevalence of atopic diseases: the International Study of Asthma and Allergies in Childhood (ISAAC). Lancet 1998;351:1225eC1232.
Miller SA, Dykes DD, Poletsky HF. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res 1988;16:1215.
Zhang L, Cui X, Schmitt K, Hubert R, Navidi W, Arnheim N. Whole genome amplification from a single cell: implications for genetic analysis. Proc Natl Acad Sci USA 1992;89:5847eC5851.
Ding C, Cantor CR. A high-throughput gene expression analysis technique using competitive PCR and matrix-assisted laser desorption ionization time-of-flight MS. Proc Natl Acad Sci USA 2003;100:3059eC3064.
Sasieni PD. From genotypes to genes: doubling the sample size. Biometrics 1997;53:1253eC1261.
Excoffier L, Slatkin M. Maximum-likelihood estimation of molecular haplotype frequencies in a diploid population. Mol Biol Evol 1995;12:921eC927.
Zaykin DV, Westfall PH, Young SS, Karnoub MA, Wagner MJ, Ehm MG. Testing association of statistically inferred haplotypes with discrete and continuous traits in samples of unrelated individuals. Hum Hered 2002;53:79eC91.
SAS II. SAS/Genetics(r) user's guide. Cary, NC: SAS, Inc.; 2002.
Hosking L, Lumsden S, Lewis K, Yeo A, McCarthy L, Bansal A, Riley J, Purvis I, Xu CF. Detection of genotyping errors by Hardy-Weinberg equilibrium testing. Eur J Hum Genet 2004;12:395eC399.
Meleen E, Bruce S, Doekes G, Kabesch M, Laitinen T, Lauener R, Lindgren CM, Riedler J, Schneynius A, van Hage-Hamsten M, et al. Haplotypes of G proteineCcoupled receptor 154 are associated with childhood allergy and asthma. Am J Respir Crit Care Med (In press)
Martinez FD, Wright AL, Taussig LM, Holberg CJ, Halonen M, Morgan WJ. Asthma and wheezing in the first six years of life. The Group Health Medical Associates. N Engl J Med 1995;332:133eC138.(Michael S. D. Kormann, Da)