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Ammarin Thakkinstian, Mark McEvoy, Cosetta Minelli, Peter Gibson, Bob Hancox, David Duffy, John Thompson, Ian Hall, Joel Kaufman, Ting-fan Leung, Peter Joseph Helms, Hakon Hakonarson, Eva Halpi, Ruth Navon, John Attia, Systematic Review and Meta-Analysis of the Association between β2-Adrenoceptor Polymorphisms and Asthma: A HuGE Review, American Journal of Epidemiology, Volume 162, Issue 3, 1 August 2005, Pages 201–211, https://doi.org/10.1093/aje/kwi184
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Abstract
A number of studies have investigated two common polymorphisms in the β2-adrenoceptor gene, Arg/Gly16 and Gln/Glu27, in relation to asthma susceptibility. The authors performed a meta-analysis of each polymorphism, as well as haplotype analysis, for adult and pediatric populations separately, using published data, supplemented by additional data requested from the original authors. Individual analysis detected no effect of Arg/Gly16 in adults but did suggest a recessive protective effect of Gly16 for children, with an odds ratio of 0.71 (95% confidence interval (CI): 0.53, 0.96) compared with the other genotypes. Results for Gln/Glu27 in adults seem to indicate that heterozygotes are at decreased risk of asthma than either homozygote (odds ratio = 0.73, 95% CI: 0.62, 0.87), although the studies are heterogeneous; in children, the Glu/Glu genotype has a decreased risk of asthma (odds ratio = 0.60, 95% CI: 0.35, 0.99) compared with the other genotypes. Despite the proximity of these two polymorphic sites, the linkage disequilibrium coefficient of 0.41 was not high (p < 0.001). Haplotype analysis suggests that there may be an interaction between the two sites, with a lower risk of asthma associated with the Glu27 allele (compared with Gln27), and that this risk is modified by the allele at position 16.
One of the main thrusts of genetic epidemiology is to understand the genetic contribution to complex diseases such as cardiac disease, diabetes, and asthma. One of the most popular study designs in this area is a molecular association study in which a polymorphism is linked to the disease outcome, either in cases and controls or in a cohort. These studies are often limited by small sample sizes (1), so there is a role for meta-analysis in pooling these studies, particularly to detect the small effect sizes that may be associated with these polymorphisms.
The β2-adrenoceptor gene is a key gene to study in asthma. β2-Adrenoceptors are present on many airway cells, including smooth muscle cells which are hyperreactive in asthma, and β2-adrenoceptor agonists form a major treatment class in asthma. Functional polymorphisms of this gene may influence both disease susceptibility and treatment response in asthma.
A number of studies have investigated polymorphisms in the β2-adrenoceptor gene in relation to asthma. Two common polymorphisms are Arg/Gly16 and Gln/Glu27; in the former polymorphism, glycine is substituted for arginine at codon 16 (Arg16→Gly) and, in the latter, glutamic acid is substituted for glutamine at codon 27 (Gln27→Glu) (2, 3). In vitro studies indicate that the Gly16 allele enhances agonist-induced down regulation of the receptor, whereas the Glu27 allele enhances resistance to down regulation (4, 5). It is plausible that these differences in receptor regulation influence the reactivity of airway smooth muscle in response to airway inflammation and thereby alter the risk of asthma. However, epidemiologic studies have yielded conflicting results, with the direction of the effects not always congruent with the in vitro results. Several narrative reviews of these two polymorphisms and asthma (4–6) have been conducted; however, neither a magnitude nor a mode of gene effect was provided in these reviews. Furthermore, new studies that examine this association have been reported since those reviews, and there have been new developments in the methodology of meta-analysis of genetic studies (1, 7, 8). We therefore performed a systematic review of the association between Arg/Gly16 and Gln/Glu27 and asthma with the following objectives: first, to estimate allele frequencies; second, to ascertain if there is an effect of these polymorphisms on asthma susceptibility, and if so to estimate the magnitude of that effect and the possible mode of inheritance (1, 7, 8); third, to determine linkage disequilibrium between these two polymorphisms; and fourth, to infer haplotypes of these polymorphisms and link them with asthma susceptibility.
MATERIALS AND METHODS
Search strategy
Embase and Medline databases (from January 1966 to March 2004) were searched using the Embase, PubMed, and Ovid search engines. The search strategy for allele frequency was as follows: beta2* AND prevalence AND gene. The search strategy for association between gene polymorphisms and asthma was the following: asthma AND (beta receptor or beta-2 or adrenoceptor) AND (polymorph* or mutation* or variant* or genotype*). Searching was performed in duplicate by two independent reviewers (A. T. and M. M.).
Inclusion criteria
For allele frequency, any human studies that estimated the prevalence of β2-adrenoceptor polymorphisms at codon 16 (Arg/Gly16) and/or codon 27 (Gln/Glu27) and reported on ethnically homogeneous populations were included, regardless of size. For assessing association, human studies, regardless of sample size, were included if they met the following criteria:The reference lists of the articles retrieved were also reviewed to identify publications on the same topic. The most complete and recent results were used where there were multiple publications from the same study group.
β2-Adrenoceptor polymorphisms at codon 16 (Arg/Gly16) and/or codon 27 (Gln/Glu27) were determined. The wild-type alleles for these two polymorphisms were Arg and Gln, respectively.
The outcome was asthma (incident or prevalent), and there were at least two comparison groups, for example, asthma versus control (nonasthma) groups.
Participants could be either children or adults, but results should be reported separately.
There were sufficient results for extraction of data, that is, number of subjects for each genotype in asthma and control groups. Where eligible papers had insufficient information, we contacted authors by e-mail for additional information.
Data extraction
Data were extracted independently and in duplicate by two reviewers (A. T. and M. M.) who used a standardized data extraction form. Any disagreement was adjudicated by a third author (J. A.). Covariables, such as mean age, gender, and ethnicity, were also extracted for each study.
Quality score assessment
The quality of studies was also independently assessed by the same two reviewers who used quality assessment scores that were modified from our previous meta-analysis of molecular association studies (7) (appendix table 1). These scores were based on both traditional epidemiologic considerations and genetic issues (1). Total scores ranged from 0 (worst) to 13 (best).
Statistical analysis
Data analyses were performed as follows. First, the frequency of Arg16 and Gln27 alleles in various ethnic groups was estimated by the inverse variance method, as described in the Appendix.
Second, estimation of the gene effect on asthma was performed by a logistic regression approach described previously (8). In brief, the steps were as follows. Hardy-Weinberg equilibrium was assessed for each study by use of the χ2 test or Fisher's exact test, where appropriate, and only in control groups. A Q test for heterogeneity was performed separately for three odds ratios (ORs), that is, Gly/Gly versus Arg/Arg (OR1), Arg/Gly versus Arg/Arg (OR2), and Gly/Gly versus Arg/Gly (OR3) for the Arg/Gly16 polymorphism and Glu/Glu versus Gln/Gln (OR1), Gln/Glu versus Gln/Gln (OR2), and Glu/Glu versus Gln/Glu (OR3) for the Gln/Glu27 polymorphism. If there was heterogeneity on at least one of these odds ratios, the cause of heterogeneity was explored by fitting a covariable (e.g., ethnicity, age, gender, or quality score) in a meta-regression model (9–11). If there was no heterogeneity, logistic regression analysis with the fixed-effect model was used to determine the gene effect; otherwise, the random-effect model was used to pool. A likelihood ratio test was used to gauge whether the overall gene effect was significant. If the main effect of the genotype was statistically significant, further comparisons of OR1, OR2, and OR3 were explored. These pairwise differences were used to indicate the most appropriate genetic model as follows.
If OR1 = OR3 ≠ 1 and OR2 = 1, then a recessive model is suggested.
If OR1 = OR2 ≠ 1 and OR3 = 1, then a dominant model is suggested.
If OR2 = 1/OR3 ≠ 1 and OR1 = 1, then a complete overdominant model is suggested (also referred to as a “homozygous model” or “heterosis”).
If OR1 > OR2 > 1 and OR1 > OR3 > 1 (or OR1 < OR2 < 1 and OR1 < OR3 < 1), then a codominant model is suggested.
Third, the gene effect was estimated by use of a newer, “parsimonious” approach detailed elsewhere (C. Minelli et al., University of Leicester, unpublished manuscript). In brief, this approach summarizes the genetic model in terms of a parameter lambda (λ), which is the ratio between log(OR1) (Glu/Glu vs. Gln/Gln) and log(OR2) (Gln/Glu vs. Gln/Gln). This parameter, which represents the heterozygote effect as a proportion of the homozygote variant effect, captures information about the genetic mode of action as follows: a recessive model if λ = 0, a dominant model if λ = 1, a codominant model if λ = 0.5, and homozygous or overdominant if λ is greater than 1 or less than 0. The two log odds ratios are modeled as either fixed or random effects, as described in the second statistical analysis enumerated above.
Once the best genetic model is identified, this model is used to collapse the three genotypes into two groups (except in the case of a codominant model) and to pool the results again. Sensitivity analyses were performed by including or excluding studies not in Hardy-Weinberg equilibrium.
Fourth, with haplotype analysis, the haplotype frequencies of Arg/Gly16 and Gln/Glu27 polymorphisms were inferred using the expectation-maximization algorithm (12). The odds ratio was then estimated by use of the profile likelihood. The linkage disequilibrium coefficient was then estimated (13). The likelihood ratio test was used to test whether the linkage disequilibrium was significant.
All analyses were performed using Stata software, version 8.0 (14), apart from the parsimonious approach, for which WinBugs 1.4 (15) with vague prior distributions was used. A p value of less than 0.05 was considered statistically significant, except for tests of heterogeneity where a level of 0.10 was used.
RESULTS
For pooling allele frequency, 67 studies were identified, of which 16 (16–31) reported separate information for defined ethnic groups. Fourteen studies (2, 3, 32–43) retrieved from the search for gene effect were also included.
Allele frequencies
Arg allele
To estimate the pooled frequency, we used data only from control groups where a case-control design was used or from the entire group where a cohort design was used. Twenty-six studies (2, 3, 17, 18, 20–22, 24, 26–43) reported Arg allele frequencies (table 1), with 13 studies of Caucasian adults, three of Caucasian children, four of Black adults, six of Oriental adults, two of Oriental children, and one of Semite (Jews/Arabs) adults. Of these, six were not in Hardy-Weinberg equilibrium, leaving 12 studies of Caucasians, three of Blacks, and seven of Orientals for pooling.
Subjects, first author (reference no.) . | Hardy-Weinberg equilibrium (p value) . | Total no. . | Arg allele frequency (no.) . | % with Arg allele . |
---|---|---|---|---|
Caucasian adults* | ||||
Santillan (3) | 0.07 | 1,208 | 520 | 43 |
Barr (2) | 0.50 | 274 | 164 | 60 |
Holloway (32) | 0.30 | 182 | 73 | 40 |
Dewar (33) | 0.32 | 1,268 | 489 | 39 |
Arnaiz (34) | 0.02† | 102 | 42 | 41 |
Reihsaus (35) | 0.04† | 112 | 30 | 27 |
Hakonarson (36) | 0.75 | 362 | 127 | 35 |
Rosmond (17) | <0.001† | 534 | 238 | 45 |
Dallongeville (20) | 0.53 | 2,258 | 857 | 38 |
Tang (21) | 0.06 | 248 | 95 | 38 |
Aynacioglu (22) | 0.84 | 208 | 84 | 40 |
Weir (30) | 1.00 | 168 | 102 | 61 |
Xie (31) | <0.05† | 376 | 172 | 46 |
Caucasian children* | ||||
Martinez (37) | 0.90 | 538 | 206 | 38 |
Binaei (38) | 0.13 | 310 | 135 | 44 |
Hopes (39) | 0.12 | 838 | 279 | 33 |
Black adults‡ | ||||
Kotanko (18) | <0.05† | 162 | 63 | 33 |
Tang (21) | 0.51 | 286 | 144 | 50 |
Candy (24) | 0.37 | 246 | 119 | 48 |
Xie (31) | 1.00 | 246 | 120 | 49 |
Oriental adults§ | ||||
Wang (42) | 0.50 | 272 | 140 | 51 |
Sugaya (26) | <0.05† | 414 | 165 | 40 |
Chang (27) | 0.11 | 260 | 137 | 53 |
Kim (28) | 0.37 | 178 | 115 | 65 |
Iwamoto (29) | 0.71 | 238 | 115 | 48 |
Xie (31) | 0.69 | 208 | 122 | 59 |
Oriental children§ | ||||
Leung (41) | 0.48 | 140 | 81 | 58 |
Lin (40) | 0.06 | 298 | 182 | 61 |
Jewish/Arab adults | ||||
Shachor (43) | 0.45 | 222 | 101 | 45.5 |
Subjects, first author (reference no.) . | Hardy-Weinberg equilibrium (p value) . | Total no. . | Arg allele frequency (no.) . | % with Arg allele . |
---|---|---|---|---|
Caucasian adults* | ||||
Santillan (3) | 0.07 | 1,208 | 520 | 43 |
Barr (2) | 0.50 | 274 | 164 | 60 |
Holloway (32) | 0.30 | 182 | 73 | 40 |
Dewar (33) | 0.32 | 1,268 | 489 | 39 |
Arnaiz (34) | 0.02† | 102 | 42 | 41 |
Reihsaus (35) | 0.04† | 112 | 30 | 27 |
Hakonarson (36) | 0.75 | 362 | 127 | 35 |
Rosmond (17) | <0.001† | 534 | 238 | 45 |
Dallongeville (20) | 0.53 | 2,258 | 857 | 38 |
Tang (21) | 0.06 | 248 | 95 | 38 |
Aynacioglu (22) | 0.84 | 208 | 84 | 40 |
Weir (30) | 1.00 | 168 | 102 | 61 |
Xie (31) | <0.05† | 376 | 172 | 46 |
Caucasian children* | ||||
Martinez (37) | 0.90 | 538 | 206 | 38 |
Binaei (38) | 0.13 | 310 | 135 | 44 |
Hopes (39) | 0.12 | 838 | 279 | 33 |
Black adults‡ | ||||
Kotanko (18) | <0.05† | 162 | 63 | 33 |
Tang (21) | 0.51 | 286 | 144 | 50 |
Candy (24) | 0.37 | 246 | 119 | 48 |
Xie (31) | 1.00 | 246 | 120 | 49 |
Oriental adults§ | ||||
Wang (42) | 0.50 | 272 | 140 | 51 |
Sugaya (26) | <0.05† | 414 | 165 | 40 |
Chang (27) | 0.11 | 260 | 137 | 53 |
Kim (28) | 0.37 | 178 | 115 | 65 |
Iwamoto (29) | 0.71 | 238 | 115 | 48 |
Xie (31) | 0.69 | 208 | 122 | 59 |
Oriental children§ | ||||
Leung (41) | 0.48 | 140 | 81 | 58 |
Lin (40) | 0.06 | 298 | 182 | 61 |
Jewish/Arab adults | ||||
Shachor (43) | 0.45 | 222 | 101 | 45.5 |
Pooled prevalence (%): 42 (95% confidence interval (CI): 38.4, 45.7).
Not included in pooled prevalence.
Pooled prevalence: 49.2 (95% CI: 45.7, 52.7).
Pooled prevalence: 56.2 (95% CI: 51.9, 60.6).
Subjects, first author (reference no.) . | Hardy-Weinberg equilibrium (p value) . | Total no. . | Arg allele frequency (no.) . | % with Arg allele . |
---|---|---|---|---|
Caucasian adults* | ||||
Santillan (3) | 0.07 | 1,208 | 520 | 43 |
Barr (2) | 0.50 | 274 | 164 | 60 |
Holloway (32) | 0.30 | 182 | 73 | 40 |
Dewar (33) | 0.32 | 1,268 | 489 | 39 |
Arnaiz (34) | 0.02† | 102 | 42 | 41 |
Reihsaus (35) | 0.04† | 112 | 30 | 27 |
Hakonarson (36) | 0.75 | 362 | 127 | 35 |
Rosmond (17) | <0.001† | 534 | 238 | 45 |
Dallongeville (20) | 0.53 | 2,258 | 857 | 38 |
Tang (21) | 0.06 | 248 | 95 | 38 |
Aynacioglu (22) | 0.84 | 208 | 84 | 40 |
Weir (30) | 1.00 | 168 | 102 | 61 |
Xie (31) | <0.05† | 376 | 172 | 46 |
Caucasian children* | ||||
Martinez (37) | 0.90 | 538 | 206 | 38 |
Binaei (38) | 0.13 | 310 | 135 | 44 |
Hopes (39) | 0.12 | 838 | 279 | 33 |
Black adults‡ | ||||
Kotanko (18) | <0.05† | 162 | 63 | 33 |
Tang (21) | 0.51 | 286 | 144 | 50 |
Candy (24) | 0.37 | 246 | 119 | 48 |
Xie (31) | 1.00 | 246 | 120 | 49 |
Oriental adults§ | ||||
Wang (42) | 0.50 | 272 | 140 | 51 |
Sugaya (26) | <0.05† | 414 | 165 | 40 |
Chang (27) | 0.11 | 260 | 137 | 53 |
Kim (28) | 0.37 | 178 | 115 | 65 |
Iwamoto (29) | 0.71 | 238 | 115 | 48 |
Xie (31) | 0.69 | 208 | 122 | 59 |
Oriental children§ | ||||
Leung (41) | 0.48 | 140 | 81 | 58 |
Lin (40) | 0.06 | 298 | 182 | 61 |
Jewish/Arab adults | ||||
Shachor (43) | 0.45 | 222 | 101 | 45.5 |
Subjects, first author (reference no.) . | Hardy-Weinberg equilibrium (p value) . | Total no. . | Arg allele frequency (no.) . | % with Arg allele . |
---|---|---|---|---|
Caucasian adults* | ||||
Santillan (3) | 0.07 | 1,208 | 520 | 43 |
Barr (2) | 0.50 | 274 | 164 | 60 |
Holloway (32) | 0.30 | 182 | 73 | 40 |
Dewar (33) | 0.32 | 1,268 | 489 | 39 |
Arnaiz (34) | 0.02† | 102 | 42 | 41 |
Reihsaus (35) | 0.04† | 112 | 30 | 27 |
Hakonarson (36) | 0.75 | 362 | 127 | 35 |
Rosmond (17) | <0.001† | 534 | 238 | 45 |
Dallongeville (20) | 0.53 | 2,258 | 857 | 38 |
Tang (21) | 0.06 | 248 | 95 | 38 |
Aynacioglu (22) | 0.84 | 208 | 84 | 40 |
Weir (30) | 1.00 | 168 | 102 | 61 |
Xie (31) | <0.05† | 376 | 172 | 46 |
Caucasian children* | ||||
Martinez (37) | 0.90 | 538 | 206 | 38 |
Binaei (38) | 0.13 | 310 | 135 | 44 |
Hopes (39) | 0.12 | 838 | 279 | 33 |
Black adults‡ | ||||
Kotanko (18) | <0.05† | 162 | 63 | 33 |
Tang (21) | 0.51 | 286 | 144 | 50 |
Candy (24) | 0.37 | 246 | 119 | 48 |
Xie (31) | 1.00 | 246 | 120 | 49 |
Oriental adults§ | ||||
Wang (42) | 0.50 | 272 | 140 | 51 |
Sugaya (26) | <0.05† | 414 | 165 | 40 |
Chang (27) | 0.11 | 260 | 137 | 53 |
Kim (28) | 0.37 | 178 | 115 | 65 |
Iwamoto (29) | 0.71 | 238 | 115 | 48 |
Xie (31) | 0.69 | 208 | 122 | 59 |
Oriental children§ | ||||
Leung (41) | 0.48 | 140 | 81 | 58 |
Lin (40) | 0.06 | 298 | 182 | 61 |
Jewish/Arab adults | ||||
Shachor (43) | 0.45 | 222 | 101 | 45.5 |
Pooled prevalence (%): 42 (95% confidence interval (CI): 38.4, 45.7).
Not included in pooled prevalence.
Pooled prevalence: 49.2 (95% CI: 45.7, 52.7).
Pooled prevalence: 56.2 (95% CI: 51.9, 60.6).
There was heterogeneity among the 12 Caucasian studies (
Gln allele
Twenty-six studies (3, 16, 17, 19, 20, 22–25, 27–43) reported the frequency of the Gln/Glu27 polymorphism, 12 studies of Caucasian adults, three of Caucasian children, three of Black adults, seven of Oriental adults, two of Oriental children, one of Jewish adults, and one of Polynesian adults (table 2). Three studies, all of Caucasians, did not observe Hardy-Weinberg equilibrium and were not included in pooling.
Subjects, first author (reference no.) . | Hardy-Weinberg equilibrium (p value) . | Total no. . | Gln allele frequency (no.) . | % with Gln allele . |
---|---|---|---|---|
Caucasian adults* | ||||
Arnaiz (34) | <0.05† | 102 | 54 | 53 |
Santillan (3) | 0.12 | 1,208 | 972 | 81 |
Holloway (32) | 0.13 | 182 | 107 | 59 |
Dewar (33) | 0.58 | 1,260 | 656 | 52 |
Reihsaus (35) | 0.19 | 112 | 57 | 51 |
Hakonarson (36) | 0.09 | 398 | 208 | 52 |
Rosmond (17) | 0.45 | 532 | 314 | 45 |
Heckbert (19) | 0.81 | 8,882 | 5,069 | 57 |
Dallongeville (20) | <0.001† | 2,982 | 1,321 | 44 |
Aynacioglu (22) | 0.81 | 208 | 142 | 68 |
Weir (30) | 1.00 | 168 | 90 | 54 |
Xie (31) | 0.06 | 376 | 245 | 65 |
Caucasian children* | ||||
Martinez (37) | 0.69 | 538 | 343 | 64 |
Hopes (39) | 0.38 | 838 | 433 | 52 |
Binaei (38) | <0.05† | 310 | 250 | 81 |
Black adults‡ | ||||
Heckbert (19) | 0.64 | 1,616 | 1,315 | 81 |
Candy (24) | 0.75 | 246 | 204 | 83 |
Xie (31) | 0.78 | 246 | 195 | 79 |
Oriental adults§ | ||||
Wang (42) | 1.00 | 272 | 248 | 91 |
Kawamura (16) | 0.16 | 838 | 772 | 92 |
Kahara (23) | 1.00 | 248 | 233 | 94 |
Chang (27) | 0.55 | 260 | 240 | 92 |
Kim (28) | 0.59 | 176 | 156 | 89 |
Iwamoto (29) | 1.00 | 238 | 221 | 93 |
Xie (31) | 1.00 | 208 | 193 | 93 |
Oriental children§ | ||||
Leung (41) | 1.00 | 140 | 125 | 89 |
Lin (40) | 1.00 | 298 | 267 | 90 |
Jewish/Arab adults | ||||
Shachor (43) | 0.66 | 218 | 150 | 69 |
Polynesian | ||||
Duarte (25) | 0.51 | 2,044 | 1,944 | 95 |
Subjects, first author (reference no.) . | Hardy-Weinberg equilibrium (p value) . | Total no. . | Gln allele frequency (no.) . | % with Gln allele . |
---|---|---|---|---|
Caucasian adults* | ||||
Arnaiz (34) | <0.05† | 102 | 54 | 53 |
Santillan (3) | 0.12 | 1,208 | 972 | 81 |
Holloway (32) | 0.13 | 182 | 107 | 59 |
Dewar (33) | 0.58 | 1,260 | 656 | 52 |
Reihsaus (35) | 0.19 | 112 | 57 | 51 |
Hakonarson (36) | 0.09 | 398 | 208 | 52 |
Rosmond (17) | 0.45 | 532 | 314 | 45 |
Heckbert (19) | 0.81 | 8,882 | 5,069 | 57 |
Dallongeville (20) | <0.001† | 2,982 | 1,321 | 44 |
Aynacioglu (22) | 0.81 | 208 | 142 | 68 |
Weir (30) | 1.00 | 168 | 90 | 54 |
Xie (31) | 0.06 | 376 | 245 | 65 |
Caucasian children* | ||||
Martinez (37) | 0.69 | 538 | 343 | 64 |
Hopes (39) | 0.38 | 838 | 433 | 52 |
Binaei (38) | <0.05† | 310 | 250 | 81 |
Black adults‡ | ||||
Heckbert (19) | 0.64 | 1,616 | 1,315 | 81 |
Candy (24) | 0.75 | 246 | 204 | 83 |
Xie (31) | 0.78 | 246 | 195 | 79 |
Oriental adults§ | ||||
Wang (42) | 1.00 | 272 | 248 | 91 |
Kawamura (16) | 0.16 | 838 | 772 | 92 |
Kahara (23) | 1.00 | 248 | 233 | 94 |
Chang (27) | 0.55 | 260 | 240 | 92 |
Kim (28) | 0.59 | 176 | 156 | 89 |
Iwamoto (29) | 1.00 | 238 | 221 | 93 |
Xie (31) | 1.00 | 208 | 193 | 93 |
Oriental children§ | ||||
Leung (41) | 1.00 | 140 | 125 | 89 |
Lin (40) | 1.00 | 298 | 267 | 90 |
Jewish/Arab adults | ||||
Shachor (43) | 0.66 | 218 | 150 | 69 |
Polynesian | ||||
Duarte (25) | 0.51 | 2,044 | 1,944 | 95 |
Pooled prevalence (%): 59.6 (95% confidence interval (CI): 53.6, 65.6).
Not included in pooled prevalence.
Pooled prevalence: 81.3 (95% CI: 79.7, 83.0).
Pooled prevalence: 91.9 (95% CI: 90.9, 92.9).
Subjects, first author (reference no.) . | Hardy-Weinberg equilibrium (p value) . | Total no. . | Gln allele frequency (no.) . | % with Gln allele . |
---|---|---|---|---|
Caucasian adults* | ||||
Arnaiz (34) | <0.05† | 102 | 54 | 53 |
Santillan (3) | 0.12 | 1,208 | 972 | 81 |
Holloway (32) | 0.13 | 182 | 107 | 59 |
Dewar (33) | 0.58 | 1,260 | 656 | 52 |
Reihsaus (35) | 0.19 | 112 | 57 | 51 |
Hakonarson (36) | 0.09 | 398 | 208 | 52 |
Rosmond (17) | 0.45 | 532 | 314 | 45 |
Heckbert (19) | 0.81 | 8,882 | 5,069 | 57 |
Dallongeville (20) | <0.001† | 2,982 | 1,321 | 44 |
Aynacioglu (22) | 0.81 | 208 | 142 | 68 |
Weir (30) | 1.00 | 168 | 90 | 54 |
Xie (31) | 0.06 | 376 | 245 | 65 |
Caucasian children* | ||||
Martinez (37) | 0.69 | 538 | 343 | 64 |
Hopes (39) | 0.38 | 838 | 433 | 52 |
Binaei (38) | <0.05† | 310 | 250 | 81 |
Black adults‡ | ||||
Heckbert (19) | 0.64 | 1,616 | 1,315 | 81 |
Candy (24) | 0.75 | 246 | 204 | 83 |
Xie (31) | 0.78 | 246 | 195 | 79 |
Oriental adults§ | ||||
Wang (42) | 1.00 | 272 | 248 | 91 |
Kawamura (16) | 0.16 | 838 | 772 | 92 |
Kahara (23) | 1.00 | 248 | 233 | 94 |
Chang (27) | 0.55 | 260 | 240 | 92 |
Kim (28) | 0.59 | 176 | 156 | 89 |
Iwamoto (29) | 1.00 | 238 | 221 | 93 |
Xie (31) | 1.00 | 208 | 193 | 93 |
Oriental children§ | ||||
Leung (41) | 1.00 | 140 | 125 | 89 |
Lin (40) | 1.00 | 298 | 267 | 90 |
Jewish/Arab adults | ||||
Shachor (43) | 0.66 | 218 | 150 | 69 |
Polynesian | ||||
Duarte (25) | 0.51 | 2,044 | 1,944 | 95 |
Subjects, first author (reference no.) . | Hardy-Weinberg equilibrium (p value) . | Total no. . | Gln allele frequency (no.) . | % with Gln allele . |
---|---|---|---|---|
Caucasian adults* | ||||
Arnaiz (34) | <0.05† | 102 | 54 | 53 |
Santillan (3) | 0.12 | 1,208 | 972 | 81 |
Holloway (32) | 0.13 | 182 | 107 | 59 |
Dewar (33) | 0.58 | 1,260 | 656 | 52 |
Reihsaus (35) | 0.19 | 112 | 57 | 51 |
Hakonarson (36) | 0.09 | 398 | 208 | 52 |
Rosmond (17) | 0.45 | 532 | 314 | 45 |
Heckbert (19) | 0.81 | 8,882 | 5,069 | 57 |
Dallongeville (20) | <0.001† | 2,982 | 1,321 | 44 |
Aynacioglu (22) | 0.81 | 208 | 142 | 68 |
Weir (30) | 1.00 | 168 | 90 | 54 |
Xie (31) | 0.06 | 376 | 245 | 65 |
Caucasian children* | ||||
Martinez (37) | 0.69 | 538 | 343 | 64 |
Hopes (39) | 0.38 | 838 | 433 | 52 |
Binaei (38) | <0.05† | 310 | 250 | 81 |
Black adults‡ | ||||
Heckbert (19) | 0.64 | 1,616 | 1,315 | 81 |
Candy (24) | 0.75 | 246 | 204 | 83 |
Xie (31) | 0.78 | 246 | 195 | 79 |
Oriental adults§ | ||||
Wang (42) | 1.00 | 272 | 248 | 91 |
Kawamura (16) | 0.16 | 838 | 772 | 92 |
Kahara (23) | 1.00 | 248 | 233 | 94 |
Chang (27) | 0.55 | 260 | 240 | 92 |
Kim (28) | 0.59 | 176 | 156 | 89 |
Iwamoto (29) | 1.00 | 238 | 221 | 93 |
Xie (31) | 1.00 | 208 | 193 | 93 |
Oriental children§ | ||||
Leung (41) | 1.00 | 140 | 125 | 89 |
Lin (40) | 1.00 | 298 | 267 | 90 |
Jewish/Arab adults | ||||
Shachor (43) | 0.66 | 218 | 150 | 69 |
Polynesian | ||||
Duarte (25) | 0.51 | 2,044 | 1,944 | 95 |
Pooled prevalence (%): 59.6 (95% confidence interval (CI): 53.6, 65.6).
Not included in pooled prevalence.
Pooled prevalence: 81.3 (95% CI: 79.7, 83.0).
Pooled prevalence: 91.9 (95% CI: 90.9, 92.9).
There was heterogeneity among the 10 Caucasian studies (
Assessing association between gene polymorphisms and asthma
Across both Embase and Medline databases, 435 studies were identified in total, of which 113 were duplicates, leaving 322 study abstracts that were reviewed. From these, 30 studies seemed to be relevant, and therefore the full papers were retrieved. Sixteen studies were judged to have met the inclusion criteria, of which eight provided complete data in the paper. Requests for additional data on the other eight studies were made, of which four were granted. Two additional studies (36, 43) were identified by a known expert (D. D.), and the authors provided additional data. The characteristics of the adult and pediatric study populations, for example, mean age, gender, ethnicity, type of subjects, and allele frequency, are given in table 3.
Subjects, first author (reference no.) . | Year . | Study design . | Race . | Mean age (years) . | % female . | Quality score . |
---|---|---|---|---|---|---|
Adults | ||||||
Shachor (43) | 2003 | Case-control | Jewish/Arab | 38 | 53.0 | 5 |
Arnaiz (34) | 2003 | Cohort | Caucasian | 28 | 1.9 | 9 |
Santillan (3) | 2003 | Case-control | Caucasian | 37.3 | 15.0 | 13 |
Barr (2) | 2001 | Case-control | Caucasian | 58.4 | 64.9 | 10 |
Wang (42) | 2001 | Case-control | Asian | 33.0 | 61.7 | 13 |
Hakonarson (36) | 2001 | Case-control | Caucasian | 47.5 | 56.3 | 6 |
Holloway (32) | 2000 | Case-control | Caucasian | 31.4 | 54.9 | 6 |
Dewar (33) | 1998 | Cross-sectional | Caucasian | 18–70* | 54.0 | 6 |
Reihsaus (35) | 1993 | Case-control | Unknown | 46 | 5 | |
Children | ||||||
Martinez (37) | 1997 | Cross-sectional | Caucasian | 10.8 | 9 | |
Hopes (39) | 1998 | Cross-sectional | Caucasian | 10.5 | 5 | |
Leung (41) | 2002 | Case-control | Asian | 10.8 | 55.0 | 5 |
Binaei (38) | 2003 | Case-control | Caucasian | 1 | ||
Lin (40) | 2003 | Cross-sectional | Asian | 13.9 | 9 |
Subjects, first author (reference no.) . | Year . | Study design . | Race . | Mean age (years) . | % female . | Quality score . |
---|---|---|---|---|---|---|
Adults | ||||||
Shachor (43) | 2003 | Case-control | Jewish/Arab | 38 | 53.0 | 5 |
Arnaiz (34) | 2003 | Cohort | Caucasian | 28 | 1.9 | 9 |
Santillan (3) | 2003 | Case-control | Caucasian | 37.3 | 15.0 | 13 |
Barr (2) | 2001 | Case-control | Caucasian | 58.4 | 64.9 | 10 |
Wang (42) | 2001 | Case-control | Asian | 33.0 | 61.7 | 13 |
Hakonarson (36) | 2001 | Case-control | Caucasian | 47.5 | 56.3 | 6 |
Holloway (32) | 2000 | Case-control | Caucasian | 31.4 | 54.9 | 6 |
Dewar (33) | 1998 | Cross-sectional | Caucasian | 18–70* | 54.0 | 6 |
Reihsaus (35) | 1993 | Case-control | Unknown | 46 | 5 | |
Children | ||||||
Martinez (37) | 1997 | Cross-sectional | Caucasian | 10.8 | 9 | |
Hopes (39) | 1998 | Cross-sectional | Caucasian | 10.5 | 5 | |
Leung (41) | 2002 | Case-control | Asian | 10.8 | 55.0 | 5 |
Binaei (38) | 2003 | Case-control | Caucasian | 1 | ||
Lin (40) | 2003 | Cross-sectional | Asian | 13.9 | 9 |
Range.
Subjects, first author (reference no.) . | Year . | Study design . | Race . | Mean age (years) . | % female . | Quality score . |
---|---|---|---|---|---|---|
Adults | ||||||
Shachor (43) | 2003 | Case-control | Jewish/Arab | 38 | 53.0 | 5 |
Arnaiz (34) | 2003 | Cohort | Caucasian | 28 | 1.9 | 9 |
Santillan (3) | 2003 | Case-control | Caucasian | 37.3 | 15.0 | 13 |
Barr (2) | 2001 | Case-control | Caucasian | 58.4 | 64.9 | 10 |
Wang (42) | 2001 | Case-control | Asian | 33.0 | 61.7 | 13 |
Hakonarson (36) | 2001 | Case-control | Caucasian | 47.5 | 56.3 | 6 |
Holloway (32) | 2000 | Case-control | Caucasian | 31.4 | 54.9 | 6 |
Dewar (33) | 1998 | Cross-sectional | Caucasian | 18–70* | 54.0 | 6 |
Reihsaus (35) | 1993 | Case-control | Unknown | 46 | 5 | |
Children | ||||||
Martinez (37) | 1997 | Cross-sectional | Caucasian | 10.8 | 9 | |
Hopes (39) | 1998 | Cross-sectional | Caucasian | 10.5 | 5 | |
Leung (41) | 2002 | Case-control | Asian | 10.8 | 55.0 | 5 |
Binaei (38) | 2003 | Case-control | Caucasian | 1 | ||
Lin (40) | 2003 | Cross-sectional | Asian | 13.9 | 9 |
Subjects, first author (reference no.) . | Year . | Study design . | Race . | Mean age (years) . | % female . | Quality score . |
---|---|---|---|---|---|---|
Adults | ||||||
Shachor (43) | 2003 | Case-control | Jewish/Arab | 38 | 53.0 | 5 |
Arnaiz (34) | 2003 | Cohort | Caucasian | 28 | 1.9 | 9 |
Santillan (3) | 2003 | Case-control | Caucasian | 37.3 | 15.0 | 13 |
Barr (2) | 2001 | Case-control | Caucasian | 58.4 | 64.9 | 10 |
Wang (42) | 2001 | Case-control | Asian | 33.0 | 61.7 | 13 |
Hakonarson (36) | 2001 | Case-control | Caucasian | 47.5 | 56.3 | 6 |
Holloway (32) | 2000 | Case-control | Caucasian | 31.4 | 54.9 | 6 |
Dewar (33) | 1998 | Cross-sectional | Caucasian | 18–70* | 54.0 | 6 |
Reihsaus (35) | 1993 | Case-control | Unknown | 46 | 5 | |
Children | ||||||
Martinez (37) | 1997 | Cross-sectional | Caucasian | 10.8 | 9 | |
Hopes (39) | 1998 | Cross-sectional | Caucasian | 10.5 | 5 | |
Leung (41) | 2002 | Case-control | Asian | 10.8 | 55.0 | 5 |
Binaei (38) | 2003 | Case-control | Caucasian | 1 | ||
Lin (40) | 2003 | Cross-sectional | Asian | 13.9 | 9 |
Range.
Arg/Gly16 polymorphism
Adult asthma.
Nine studies (2, 3, 32–36, 42, 43) determined the association between Arg/Gly16 and asthma in adults (table 4). Total sample sizes for asthma and control groups were 1,331 and 1,872, respectively. Within the asthma group, the mean age was 41 (standard deviation: 11) years, and 49 percent were females. Within the control group, the mean age was 39 (standard deviation: 11) years, and 35 percent were females.
Subjects, first author (reference no.) . | Asthma group . | . | . | . | . | Control group . | . | . | . | . | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | No. . | % with Arg allele . | Genotype (no.) . | . | . | No. . | % with Arg allele . | Genotype (no.) . | . | . | ||||||||
. | . | . | Arg/Arg . | Arg/Gly . | Gly/Gly . | . | . | Arg/Arg . | Arg/Gly . | Gly/Gly . | ||||||||
Adults | ||||||||||||||||||
Arnaiz (34)* | 12 | 54 | 4 | 5 | 3 | 39 | 37 | 9 | 11 | 19 | ||||||||
Santillan (3) | 303 | 45 | 56 | 163 | 84 | 604 | 43 | 101 | 318 | 185 | ||||||||
Barr (2) | 171 | 49 | 36 | 97 | 38 | 137 | 60 | 51 | 62 | 24 | ||||||||
Wang (42) | 128 | 62 | 52 | 54 | 22 | 136 | 51 | 38 | 64 | 34 | ||||||||
Holloway (32) | 154 | 34 | 29 | 47 | 78 | 91 | 40 | 17 | 39 | 35 | ||||||||
Dewar (33) | 117 | 33 | 14 | 50 | 53 | 517 | 40 | 74 | 263 | 180 | ||||||||
Reihsaus (35)* | 51 | 28 | 5 | 19 | 27 | 56 | 27 | 7 | 16 | 33 | ||||||||
Hakonarson (36) | 323 | 37 | 45 | 151 | 127 | 181 | 35 | 21 | 85 | 75 | ||||||||
Shachor (43) | 72 | 46 | 13 | 40 | 19 | 111 | 46 | 25 | 51 | 35 | ||||||||
Total | 1,331 | 254 | 626 | 451 | 1,872 | 343 | 909 | 510 | ||||||||||
Children | ||||||||||||||||||
Martinez (37) | 38 | 37 | 5 | 18 | 15 | 231 | 35 | 35 | 108 | 88 | ||||||||
Leung (41) | 76 | 58 | 25 | 38 | 13 | 70 | 58 | 22 | 37 | 11 | ||||||||
Binaei (38) | 38 | 10 | 7 | 24 | 7 | 155 | 44 | 34 | 67 | 54 | ||||||||
Lin (40) | 80 | 58 | 34 | 35 | 11 | 69 | 57 | 27 | 25 | 17 | ||||||||
Hopes (39) | 102 | 37 | 11 | 54 | 37 | 317 | 32 | 28 | 147 | 142 | ||||||||
Total | 334 | 82 | 169 | 83 | 842 | 146 | 384 | 312 |
Subjects, first author (reference no.) . | Asthma group . | . | . | . | . | Control group . | . | . | . | . | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | No. . | % with Arg allele . | Genotype (no.) . | . | . | No. . | % with Arg allele . | Genotype (no.) . | . | . | ||||||||
. | . | . | Arg/Arg . | Arg/Gly . | Gly/Gly . | . | . | Arg/Arg . | Arg/Gly . | Gly/Gly . | ||||||||
Adults | ||||||||||||||||||
Arnaiz (34)* | 12 | 54 | 4 | 5 | 3 | 39 | 37 | 9 | 11 | 19 | ||||||||
Santillan (3) | 303 | 45 | 56 | 163 | 84 | 604 | 43 | 101 | 318 | 185 | ||||||||
Barr (2) | 171 | 49 | 36 | 97 | 38 | 137 | 60 | 51 | 62 | 24 | ||||||||
Wang (42) | 128 | 62 | 52 | 54 | 22 | 136 | 51 | 38 | 64 | 34 | ||||||||
Holloway (32) | 154 | 34 | 29 | 47 | 78 | 91 | 40 | 17 | 39 | 35 | ||||||||
Dewar (33) | 117 | 33 | 14 | 50 | 53 | 517 | 40 | 74 | 263 | 180 | ||||||||
Reihsaus (35)* | 51 | 28 | 5 | 19 | 27 | 56 | 27 | 7 | 16 | 33 | ||||||||
Hakonarson (36) | 323 | 37 | 45 | 151 | 127 | 181 | 35 | 21 | 85 | 75 | ||||||||
Shachor (43) | 72 | 46 | 13 | 40 | 19 | 111 | 46 | 25 | 51 | 35 | ||||||||
Total | 1,331 | 254 | 626 | 451 | 1,872 | 343 | 909 | 510 | ||||||||||
Children | ||||||||||||||||||
Martinez (37) | 38 | 37 | 5 | 18 | 15 | 231 | 35 | 35 | 108 | 88 | ||||||||
Leung (41) | 76 | 58 | 25 | 38 | 13 | 70 | 58 | 22 | 37 | 11 | ||||||||
Binaei (38) | 38 | 10 | 7 | 24 | 7 | 155 | 44 | 34 | 67 | 54 | ||||||||
Lin (40) | 80 | 58 | 34 | 35 | 11 | 69 | 57 | 27 | 25 | 17 | ||||||||
Hopes (39) | 102 | 37 | 11 | 54 | 37 | 317 | 32 | 28 | 147 | 142 | ||||||||
Total | 334 | 82 | 169 | 83 | 842 | 146 | 384 | 312 |
Arnaiz and Reihsaus were not included in the pooled gene effect.
Subjects, first author (reference no.) . | Asthma group . | . | . | . | . | Control group . | . | . | . | . | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | No. . | % with Arg allele . | Genotype (no.) . | . | . | No. . | % with Arg allele . | Genotype (no.) . | . | . | ||||||||
. | . | . | Arg/Arg . | Arg/Gly . | Gly/Gly . | . | . | Arg/Arg . | Arg/Gly . | Gly/Gly . | ||||||||
Adults | ||||||||||||||||||
Arnaiz (34)* | 12 | 54 | 4 | 5 | 3 | 39 | 37 | 9 | 11 | 19 | ||||||||
Santillan (3) | 303 | 45 | 56 | 163 | 84 | 604 | 43 | 101 | 318 | 185 | ||||||||
Barr (2) | 171 | 49 | 36 | 97 | 38 | 137 | 60 | 51 | 62 | 24 | ||||||||
Wang (42) | 128 | 62 | 52 | 54 | 22 | 136 | 51 | 38 | 64 | 34 | ||||||||
Holloway (32) | 154 | 34 | 29 | 47 | 78 | 91 | 40 | 17 | 39 | 35 | ||||||||
Dewar (33) | 117 | 33 | 14 | 50 | 53 | 517 | 40 | 74 | 263 | 180 | ||||||||
Reihsaus (35)* | 51 | 28 | 5 | 19 | 27 | 56 | 27 | 7 | 16 | 33 | ||||||||
Hakonarson (36) | 323 | 37 | 45 | 151 | 127 | 181 | 35 | 21 | 85 | 75 | ||||||||
Shachor (43) | 72 | 46 | 13 | 40 | 19 | 111 | 46 | 25 | 51 | 35 | ||||||||
Total | 1,331 | 254 | 626 | 451 | 1,872 | 343 | 909 | 510 | ||||||||||
Children | ||||||||||||||||||
Martinez (37) | 38 | 37 | 5 | 18 | 15 | 231 | 35 | 35 | 108 | 88 | ||||||||
Leung (41) | 76 | 58 | 25 | 38 | 13 | 70 | 58 | 22 | 37 | 11 | ||||||||
Binaei (38) | 38 | 10 | 7 | 24 | 7 | 155 | 44 | 34 | 67 | 54 | ||||||||
Lin (40) | 80 | 58 | 34 | 35 | 11 | 69 | 57 | 27 | 25 | 17 | ||||||||
Hopes (39) | 102 | 37 | 11 | 54 | 37 | 317 | 32 | 28 | 147 | 142 | ||||||||
Total | 334 | 82 | 169 | 83 | 842 | 146 | 384 | 312 |
Subjects, first author (reference no.) . | Asthma group . | . | . | . | . | Control group . | . | . | . | . | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | No. . | % with Arg allele . | Genotype (no.) . | . | . | No. . | % with Arg allele . | Genotype (no.) . | . | . | ||||||||
. | . | . | Arg/Arg . | Arg/Gly . | Gly/Gly . | . | . | Arg/Arg . | Arg/Gly . | Gly/Gly . | ||||||||
Adults | ||||||||||||||||||
Arnaiz (34)* | 12 | 54 | 4 | 5 | 3 | 39 | 37 | 9 | 11 | 19 | ||||||||
Santillan (3) | 303 | 45 | 56 | 163 | 84 | 604 | 43 | 101 | 318 | 185 | ||||||||
Barr (2) | 171 | 49 | 36 | 97 | 38 | 137 | 60 | 51 | 62 | 24 | ||||||||
Wang (42) | 128 | 62 | 52 | 54 | 22 | 136 | 51 | 38 | 64 | 34 | ||||||||
Holloway (32) | 154 | 34 | 29 | 47 | 78 | 91 | 40 | 17 | 39 | 35 | ||||||||
Dewar (33) | 117 | 33 | 14 | 50 | 53 | 517 | 40 | 74 | 263 | 180 | ||||||||
Reihsaus (35)* | 51 | 28 | 5 | 19 | 27 | 56 | 27 | 7 | 16 | 33 | ||||||||
Hakonarson (36) | 323 | 37 | 45 | 151 | 127 | 181 | 35 | 21 | 85 | 75 | ||||||||
Shachor (43) | 72 | 46 | 13 | 40 | 19 | 111 | 46 | 25 | 51 | 35 | ||||||||
Total | 1,331 | 254 | 626 | 451 | 1,872 | 343 | 909 | 510 | ||||||||||
Children | ||||||||||||||||||
Martinez (37) | 38 | 37 | 5 | 18 | 15 | 231 | 35 | 35 | 108 | 88 | ||||||||
Leung (41) | 76 | 58 | 25 | 38 | 13 | 70 | 58 | 22 | 37 | 11 | ||||||||
Binaei (38) | 38 | 10 | 7 | 24 | 7 | 155 | 44 | 34 | 67 | 54 | ||||||||
Lin (40) | 80 | 58 | 34 | 35 | 11 | 69 | 57 | 27 | 25 | 17 | ||||||||
Hopes (39) | 102 | 37 | 11 | 54 | 37 | 317 | 32 | 28 | 147 | 142 | ||||||||
Total | 334 | 82 | 169 | 83 | 842 | 146 | 384 | 312 |
Arnaiz and Reihsaus were not included in the pooled gene effect.
The seven studies (2, 3, 32, 33, 36, 42, 43) that observed Hardy-Weinberg equilibrium were pooled. Heterogeneity was checked for OR1 (Gly/Gly vs. Arg/Arg), OR2 (Arg/Gly vs. Arg/Arg), and OR3 (Gly/Gly vs. Arg/Gly). Results indicated heterogeneity for OR1 and OR2 but not for OR3 (for OR1:
Genotype . | Logistic regression . | . | Model-free approach . | . | ||
---|---|---|---|---|---|---|
. | Adjusted odds ratio . | 95% confidence interval . | Adjusted odds ratio . | 95% confidence interval . | ||
Arg/Gly16 | ||||||
Adults | ||||||
Gly/Gly vs. Arg/Arg | 1.00 | 0.80, 1.24 | 1.01 | 0.79, 1.32 | ||
Arg/Gly vs. Arg/Arg | 0.99 | 0.81, 1.22 | 1.00 | 0.79, 1.30 | ||
Gly/Gly vs. Arg/Gly | 1.01 | 0.85, 1.20 | λ = 0.15 | −4.15, 4.99 | ||
Children | ||||||
Gly/Gly vs. Arg/Arg | 0.75 | 0.50, 1.12 | 0.88 | 0.52, 1.20 | ||
Arg/Gly vs. Arg/Arg | 1.08 | 0.76, 1.55 | 1.04 | 0.76, 1.54 | ||
Gly/Gly vs.Arg/Gly | 0.70 | 0.51, 0.96 | λ = −0.16 | −3.85, 4.39 | ||
Gly/Gly vs. Arg/Arg + Arg/Gly (recessive effect) | 0.71 | 0.53, 0.96 | ||||
Gln/Glu27 | ||||||
Adults | ||||||
Glu/Glu vs. Gln/Gln (OR1*) | 0.88 | 0.68, 1.14 | 0.97 | 0.75, 1.27 | ||
Gln/Glu vs. Gln/Gln (OR2*) | 0.72 | 0.60, 0.85 | 0.88 | 0.63, 1.18 | ||
Glu/Glu vs. Gln/Glu (OR3*) | 1.22 | 0.94, 1.60 | λ = 0.61 | −4.66, 5.54 | ||
Gln/Glu vs. Gln/Gln + Glu/Glu (overdominant effect) | 0.73 | 0.62, 0.87 | ||||
Glu/Glu vs. Gln/Gln (OR1) | 0.62 | 0.36, 1.07 | 0.90 | 0.49, 1.22 | ||
Gln/Glu vs. Gln/Gln (OR2) | 1.05 | 0.75, 1.48 | 1.02 | 0.76, 1.40 | ||
Glu/Glu vs. Gln/Glu (OR3) | 0.59 | 0.35, 0.99 | λ = −0.04 | −3.63, 4.30 | ||
Glu/Glu vs. Gln/Glu + Gln/Gln (recessive effect) | 0.60 | 0.37, 1.00 |
Genotype . | Logistic regression . | . | Model-free approach . | . | ||
---|---|---|---|---|---|---|
. | Adjusted odds ratio . | 95% confidence interval . | Adjusted odds ratio . | 95% confidence interval . | ||
Arg/Gly16 | ||||||
Adults | ||||||
Gly/Gly vs. Arg/Arg | 1.00 | 0.80, 1.24 | 1.01 | 0.79, 1.32 | ||
Arg/Gly vs. Arg/Arg | 0.99 | 0.81, 1.22 | 1.00 | 0.79, 1.30 | ||
Gly/Gly vs. Arg/Gly | 1.01 | 0.85, 1.20 | λ = 0.15 | −4.15, 4.99 | ||
Children | ||||||
Gly/Gly vs. Arg/Arg | 0.75 | 0.50, 1.12 | 0.88 | 0.52, 1.20 | ||
Arg/Gly vs. Arg/Arg | 1.08 | 0.76, 1.55 | 1.04 | 0.76, 1.54 | ||
Gly/Gly vs.Arg/Gly | 0.70 | 0.51, 0.96 | λ = −0.16 | −3.85, 4.39 | ||
Gly/Gly vs. Arg/Arg + Arg/Gly (recessive effect) | 0.71 | 0.53, 0.96 | ||||
Gln/Glu27 | ||||||
Adults | ||||||
Glu/Glu vs. Gln/Gln (OR1*) | 0.88 | 0.68, 1.14 | 0.97 | 0.75, 1.27 | ||
Gln/Glu vs. Gln/Gln (OR2*) | 0.72 | 0.60, 0.85 | 0.88 | 0.63, 1.18 | ||
Glu/Glu vs. Gln/Glu (OR3*) | 1.22 | 0.94, 1.60 | λ = 0.61 | −4.66, 5.54 | ||
Gln/Glu vs. Gln/Gln + Glu/Glu (overdominant effect) | 0.73 | 0.62, 0.87 | ||||
Glu/Glu vs. Gln/Gln (OR1) | 0.62 | 0.36, 1.07 | 0.90 | 0.49, 1.22 | ||
Gln/Glu vs. Gln/Gln (OR2) | 1.05 | 0.75, 1.48 | 1.02 | 0.76, 1.40 | ||
Glu/Glu vs. Gln/Glu (OR3) | 0.59 | 0.35, 0.99 | λ = −0.04 | −3.63, 4.30 | ||
Glu/Glu vs. Gln/Glu + Gln/Gln (recessive effect) | 0.60 | 0.37, 1.00 |
OR1, odds ratio of asthma with the preceding comparison of genotypes (OR2 and OR3 defined similarly).
Genotype . | Logistic regression . | . | Model-free approach . | . | ||
---|---|---|---|---|---|---|
. | Adjusted odds ratio . | 95% confidence interval . | Adjusted odds ratio . | 95% confidence interval . | ||
Arg/Gly16 | ||||||
Adults | ||||||
Gly/Gly vs. Arg/Arg | 1.00 | 0.80, 1.24 | 1.01 | 0.79, 1.32 | ||
Arg/Gly vs. Arg/Arg | 0.99 | 0.81, 1.22 | 1.00 | 0.79, 1.30 | ||
Gly/Gly vs. Arg/Gly | 1.01 | 0.85, 1.20 | λ = 0.15 | −4.15, 4.99 | ||
Children | ||||||
Gly/Gly vs. Arg/Arg | 0.75 | 0.50, 1.12 | 0.88 | 0.52, 1.20 | ||
Arg/Gly vs. Arg/Arg | 1.08 | 0.76, 1.55 | 1.04 | 0.76, 1.54 | ||
Gly/Gly vs.Arg/Gly | 0.70 | 0.51, 0.96 | λ = −0.16 | −3.85, 4.39 | ||
Gly/Gly vs. Arg/Arg + Arg/Gly (recessive effect) | 0.71 | 0.53, 0.96 | ||||
Gln/Glu27 | ||||||
Adults | ||||||
Glu/Glu vs. Gln/Gln (OR1*) | 0.88 | 0.68, 1.14 | 0.97 | 0.75, 1.27 | ||
Gln/Glu vs. Gln/Gln (OR2*) | 0.72 | 0.60, 0.85 | 0.88 | 0.63, 1.18 | ||
Glu/Glu vs. Gln/Glu (OR3*) | 1.22 | 0.94, 1.60 | λ = 0.61 | −4.66, 5.54 | ||
Gln/Glu vs. Gln/Gln + Glu/Glu (overdominant effect) | 0.73 | 0.62, 0.87 | ||||
Glu/Glu vs. Gln/Gln (OR1) | 0.62 | 0.36, 1.07 | 0.90 | 0.49, 1.22 | ||
Gln/Glu vs. Gln/Gln (OR2) | 1.05 | 0.75, 1.48 | 1.02 | 0.76, 1.40 | ||
Glu/Glu vs. Gln/Glu (OR3) | 0.59 | 0.35, 0.99 | λ = −0.04 | −3.63, 4.30 | ||
Glu/Glu vs. Gln/Glu + Gln/Gln (recessive effect) | 0.60 | 0.37, 1.00 |
Genotype . | Logistic regression . | . | Model-free approach . | . | ||
---|---|---|---|---|---|---|
. | Adjusted odds ratio . | 95% confidence interval . | Adjusted odds ratio . | 95% confidence interval . | ||
Arg/Gly16 | ||||||
Adults | ||||||
Gly/Gly vs. Arg/Arg | 1.00 | 0.80, 1.24 | 1.01 | 0.79, 1.32 | ||
Arg/Gly vs. Arg/Arg | 0.99 | 0.81, 1.22 | 1.00 | 0.79, 1.30 | ||
Gly/Gly vs. Arg/Gly | 1.01 | 0.85, 1.20 | λ = 0.15 | −4.15, 4.99 | ||
Children | ||||||
Gly/Gly vs. Arg/Arg | 0.75 | 0.50, 1.12 | 0.88 | 0.52, 1.20 | ||
Arg/Gly vs. Arg/Arg | 1.08 | 0.76, 1.55 | 1.04 | 0.76, 1.54 | ||
Gly/Gly vs.Arg/Gly | 0.70 | 0.51, 0.96 | λ = −0.16 | −3.85, 4.39 | ||
Gly/Gly vs. Arg/Arg + Arg/Gly (recessive effect) | 0.71 | 0.53, 0.96 | ||||
Gln/Glu27 | ||||||
Adults | ||||||
Glu/Glu vs. Gln/Gln (OR1*) | 0.88 | 0.68, 1.14 | 0.97 | 0.75, 1.27 | ||
Gln/Glu vs. Gln/Gln (OR2*) | 0.72 | 0.60, 0.85 | 0.88 | 0.63, 1.18 | ||
Glu/Glu vs. Gln/Glu (OR3*) | 1.22 | 0.94, 1.60 | λ = 0.61 | −4.66, 5.54 | ||
Gln/Glu vs. Gln/Gln + Glu/Glu (overdominant effect) | 0.73 | 0.62, 0.87 | ||||
Glu/Glu vs. Gln/Gln (OR1) | 0.62 | 0.36, 1.07 | 0.90 | 0.49, 1.22 | ||
Gln/Glu vs. Gln/Gln (OR2) | 1.05 | 0.75, 1.48 | 1.02 | 0.76, 1.40 | ||
Glu/Glu vs. Gln/Glu (OR3) | 0.59 | 0.35, 0.99 | λ = −0.04 | −3.63, 4.30 | ||
Glu/Glu vs. Gln/Glu + Gln/Gln (recessive effect) | 0.60 | 0.37, 1.00 |
OR1, odds ratio of asthma with the preceding comparison of genotypes (OR2 and OR3 defined similarly).
Sensitivity analysis was performed by including the two studies (34, 35) that did not observe Hardy-Weinberg equilibrium; the results were similar in showing no genetic effect (LR2 = 0.41, p = 0.96).
Childhood asthma.
Five studies (37–41) determined the association between the Arg/Gly16 polymorphism and asthma in children (table 4), and all observed Hardy-Weinberg equilibrium. The total sample size was 334 with asthma and 842 controls.
No heterogeneity was detected for OR1 (Gly/Gly vs. Arg/Arg), OR2 (Arg/Gly vs. Arg/Arg), or OR3 (Gly/Gly vs. Arg/Gly) (for OR1:
Gln/Glu27 polymorphism
Adult asthma.
Eight studies (3, 32–36, 42, 43) assessed the association between the Gln/Glu27 polymorphism and asthma in adult patients (table 6). The sample size was 1,162 for asthma and 1,745 for control groups. All studies except one (34) observed Hardy-Weinberg equilibrium, and seven studies were therefore pooled to assess gene effect.
Subjects, first author (reference no.) . | Asthma group . | . | . | . | . | Control group . | . | . | . | . | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | No. . | % with Gln allele . | Genotype (no.) . | . | . | No. . | % with Gln allele . | Genotype (no.) . | . | . | ||||||||
. | . | . | Gln/Gln . | Gln/Glu . | Glu/Glu . | . | . | Gln/Gln . | Gln/Glu . | Glu/Glu . | ||||||||
Adults | ||||||||||||||||||
Arnaiz (34)* | 12 | 58 | 6 | 2 | 4 | 39 | 51 | 14 | 12 | 13 | ||||||||
Santillan (3) | 303 | 88 | 241 | 53 | 9 | 604 | 80 | 385 | 202 | 17 | ||||||||
Wang (42) | 128 | 92 | 108 | 19 | 1 | 136 | 91 | 113 | 22 | 1 | ||||||||
Holloway (32) | 153 | 87 | 49 | 76 | 28 | 91 | 59 | 35 | 37 | 19 | ||||||||
Dewar (33) | 119 | 49 | 33 | 51 | 35 | 511 | 53 | 134 | 271 | 106 | ||||||||
Reihsaus (35) | 51 | 39 | 13 | 26 | 12 | 56 | 51 | 17 | 23 | 16 | ||||||||
Hakonarson (36) | 324 | 55 | 92 | 173 | 59 | 199 | 52 | 48 | 112 | 39 | ||||||||
Shachor (43) | 72 | 73 | 38 | 29 | 5 | 109 | 69 | 50 | 50 | 9 | ||||||||
Total | 1,162 | 580 | 429 | 153 | 1,745 | 796 | 729 | 220 | ||||||||||
Children | ||||||||||||||||||
Martinez (37) | 38 | 64 | 16 | 17 | 5 | 231 | 64 | 95 | 104 | 32 | ||||||||
Hopes (39) | 102 | 54 | 24 | 63 | 15 | 317 | 51 | 83 | 156 | 78 | ||||||||
Leung (41) | 76 | 92 | 64 | 12 | 0 | 70 | 89 | 55 | 15 | 0 | ||||||||
Binaei (38)* | 37 | 78 | 23 | 12 | 2 | 155 | 81 | 107 | 36 | 12 | ||||||||
Lin (40) | 80 | 91 | 65 | 15 | 0 | 69 | 88 | 54 | 14 | 1 | ||||||||
Total | 333 | 192 | 119 | 22 | 842 | 394 | 325 | 123 |
Subjects, first author (reference no.) . | Asthma group . | . | . | . | . | Control group . | . | . | . | . | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | No. . | % with Gln allele . | Genotype (no.) . | . | . | No. . | % with Gln allele . | Genotype (no.) . | . | . | ||||||||
. | . | . | Gln/Gln . | Gln/Glu . | Glu/Glu . | . | . | Gln/Gln . | Gln/Glu . | Glu/Glu . | ||||||||
Adults | ||||||||||||||||||
Arnaiz (34)* | 12 | 58 | 6 | 2 | 4 | 39 | 51 | 14 | 12 | 13 | ||||||||
Santillan (3) | 303 | 88 | 241 | 53 | 9 | 604 | 80 | 385 | 202 | 17 | ||||||||
Wang (42) | 128 | 92 | 108 | 19 | 1 | 136 | 91 | 113 | 22 | 1 | ||||||||
Holloway (32) | 153 | 87 | 49 | 76 | 28 | 91 | 59 | 35 | 37 | 19 | ||||||||
Dewar (33) | 119 | 49 | 33 | 51 | 35 | 511 | 53 | 134 | 271 | 106 | ||||||||
Reihsaus (35) | 51 | 39 | 13 | 26 | 12 | 56 | 51 | 17 | 23 | 16 | ||||||||
Hakonarson (36) | 324 | 55 | 92 | 173 | 59 | 199 | 52 | 48 | 112 | 39 | ||||||||
Shachor (43) | 72 | 73 | 38 | 29 | 5 | 109 | 69 | 50 | 50 | 9 | ||||||||
Total | 1,162 | 580 | 429 | 153 | 1,745 | 796 | 729 | 220 | ||||||||||
Children | ||||||||||||||||||
Martinez (37) | 38 | 64 | 16 | 17 | 5 | 231 | 64 | 95 | 104 | 32 | ||||||||
Hopes (39) | 102 | 54 | 24 | 63 | 15 | 317 | 51 | 83 | 156 | 78 | ||||||||
Leung (41) | 76 | 92 | 64 | 12 | 0 | 70 | 89 | 55 | 15 | 0 | ||||||||
Binaei (38)* | 37 | 78 | 23 | 12 | 2 | 155 | 81 | 107 | 36 | 12 | ||||||||
Lin (40) | 80 | 91 | 65 | 15 | 0 | 69 | 88 | 54 | 14 | 1 | ||||||||
Total | 333 | 192 | 119 | 22 | 842 | 394 | 325 | 123 |
Not in Hardy-Weinberg equilibrium and not pooled.
Subjects, first author (reference no.) . | Asthma group . | . | . | . | . | Control group . | . | . | . | . | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | No. . | % with Gln allele . | Genotype (no.) . | . | . | No. . | % with Gln allele . | Genotype (no.) . | . | . | ||||||||
. | . | . | Gln/Gln . | Gln/Glu . | Glu/Glu . | . | . | Gln/Gln . | Gln/Glu . | Glu/Glu . | ||||||||
Adults | ||||||||||||||||||
Arnaiz (34)* | 12 | 58 | 6 | 2 | 4 | 39 | 51 | 14 | 12 | 13 | ||||||||
Santillan (3) | 303 | 88 | 241 | 53 | 9 | 604 | 80 | 385 | 202 | 17 | ||||||||
Wang (42) | 128 | 92 | 108 | 19 | 1 | 136 | 91 | 113 | 22 | 1 | ||||||||
Holloway (32) | 153 | 87 | 49 | 76 | 28 | 91 | 59 | 35 | 37 | 19 | ||||||||
Dewar (33) | 119 | 49 | 33 | 51 | 35 | 511 | 53 | 134 | 271 | 106 | ||||||||
Reihsaus (35) | 51 | 39 | 13 | 26 | 12 | 56 | 51 | 17 | 23 | 16 | ||||||||
Hakonarson (36) | 324 | 55 | 92 | 173 | 59 | 199 | 52 | 48 | 112 | 39 | ||||||||
Shachor (43) | 72 | 73 | 38 | 29 | 5 | 109 | 69 | 50 | 50 | 9 | ||||||||
Total | 1,162 | 580 | 429 | 153 | 1,745 | 796 | 729 | 220 | ||||||||||
Children | ||||||||||||||||||
Martinez (37) | 38 | 64 | 16 | 17 | 5 | 231 | 64 | 95 | 104 | 32 | ||||||||
Hopes (39) | 102 | 54 | 24 | 63 | 15 | 317 | 51 | 83 | 156 | 78 | ||||||||
Leung (41) | 76 | 92 | 64 | 12 | 0 | 70 | 89 | 55 | 15 | 0 | ||||||||
Binaei (38)* | 37 | 78 | 23 | 12 | 2 | 155 | 81 | 107 | 36 | 12 | ||||||||
Lin (40) | 80 | 91 | 65 | 15 | 0 | 69 | 88 | 54 | 14 | 1 | ||||||||
Total | 333 | 192 | 119 | 22 | 842 | 394 | 325 | 123 |
Subjects, first author (reference no.) . | Asthma group . | . | . | . | . | Control group . | . | . | . | . | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | No. . | % with Gln allele . | Genotype (no.) . | . | . | No. . | % with Gln allele . | Genotype (no.) . | . | . | ||||||||
. | . | . | Gln/Gln . | Gln/Glu . | Glu/Glu . | . | . | Gln/Gln . | Gln/Glu . | Glu/Glu . | ||||||||
Adults | ||||||||||||||||||
Arnaiz (34)* | 12 | 58 | 6 | 2 | 4 | 39 | 51 | 14 | 12 | 13 | ||||||||
Santillan (3) | 303 | 88 | 241 | 53 | 9 | 604 | 80 | 385 | 202 | 17 | ||||||||
Wang (42) | 128 | 92 | 108 | 19 | 1 | 136 | 91 | 113 | 22 | 1 | ||||||||
Holloway (32) | 153 | 87 | 49 | 76 | 28 | 91 | 59 | 35 | 37 | 19 | ||||||||
Dewar (33) | 119 | 49 | 33 | 51 | 35 | 511 | 53 | 134 | 271 | 106 | ||||||||
Reihsaus (35) | 51 | 39 | 13 | 26 | 12 | 56 | 51 | 17 | 23 | 16 | ||||||||
Hakonarson (36) | 324 | 55 | 92 | 173 | 59 | 199 | 52 | 48 | 112 | 39 | ||||||||
Shachor (43) | 72 | 73 | 38 | 29 | 5 | 109 | 69 | 50 | 50 | 9 | ||||||||
Total | 1,162 | 580 | 429 | 153 | 1,745 | 796 | 729 | 220 | ||||||||||
Children | ||||||||||||||||||
Martinez (37) | 38 | 64 | 16 | 17 | 5 | 231 | 64 | 95 | 104 | 32 | ||||||||
Hopes (39) | 102 | 54 | 24 | 63 | 15 | 317 | 51 | 83 | 156 | 78 | ||||||||
Leung (41) | 76 | 92 | 64 | 12 | 0 | 70 | 89 | 55 | 15 | 0 | ||||||||
Binaei (38)* | 37 | 78 | 23 | 12 | 2 | 155 | 81 | 107 | 36 | 12 | ||||||||
Lin (40) | 80 | 91 | 65 | 15 | 0 | 69 | 88 | 54 | 14 | 1 | ||||||||
Total | 333 | 192 | 119 | 22 | 842 | 394 | 325 | 123 |
Not in Hardy-Weinberg equilibrium and not pooled.
Heterogeneity tests were negative for OR1 (Glu/Glu vs. Gln/Gln) and OR3 (Glu/Glu vs. Gln/Glu) but significant for OR2 (Gln/Glu vs. Gln/Gln) (for OR1:
The estimated OR1, OR2, and λ by the parsimonious approach were 0.97 (95 percent CI: 0.75, 1.27), 0.88 (95 percent CI: 0.63, 1.18), and 0.61 (95 percent CI: −4.66, 5.54), respectively. Sensitivity analysis was performed by adding the one study (34) not observing Hardy-Weinberg equilibrium, and the gene effect was robust: The estimated OR1, OR2, and OR3 were 0.88 (95 percent CI: 0.68, 1.13), 0.71 (95 percent CI: 0.60, 0.84), and 1.22 (95 percent CI: 0.95, 1.59), respectively This seems to indicate a homozygous or overdominant mode of effect, with heterozygotes being at lower risk of asthma than either homozygote. Pooling according to this model yielded an odds ratio of 0.73 (95 percent CI: 0.62, 0.87); that is, the chance of having asthma was about 27 percent less with Gln/Glu compared with Gln/Gln + Glu/Glu. Although this is a nonintuitive model, there is precedent for other genes acting in this manner (see Discussion); alternatively, this may be a spurious result due to the distribution of data and the possibility of interaction between the two polymorphic sites. We address this possibility further in the next section using haplotype analysis.
Childhood asthma.
There were five studies (37–41) addressing the association between the Gln/Glu27 polymorphism and asthma in children (table 6). All studies observed Hardy-Weinberg equilibrium except one (38).
The four studies observing Hardy-Weinberg equilibrium were pooled (37, 39–41). Since the studies by Lin et al. (40) and Leung et al. (41) had cells with no counts, we added 1 for each cell for these two studies. There was no evidence of heterogeneity for OR1 (Glu/Glu vs. Gln/Gln), OR2 (Gln/Glu vs. Gln/Gln), or OR3 (Glu/Glu vs. Gln/Glu) (for OR1:
Haplotype analysis of Arg/Gly16 and Gln/Glu27 polymorphisms
Three studies of adults provided data for haplotype analysis (3, 33, 36). The study by Weir et al. (30) reported inferred haplotype data among subjects who had only homozygous wild or mutant genotypes at one locus, so this study was not included in the present analysis. The expectation-maximization algorithm was applied to infer haplotypes for the three studies, and linkage disequilibrium was assessed. The estimated linkage disequilibrium coefficient was 0.48 (p < 0.001).
The haplotype frequency in asthmatics and controls is described in table 7. The three most common haplotypes were Arg/Gln (37.5 percent), Gly/Glu (31.7 percent), and Gly/Gln (28.2 percent). The estimated odds ratios were 0.39 (95 percent CI: 0.29, 0.58), 0.99 (95 percent CI: 0.74, 1.49), and 0.83 (95 percent CI: 0.62, 1. 24) for haplotypes Arg/Glu, Gly/Gln, and Gly/Glu compared with Arg/Gln. These numbers seem to indicate that, when Gln is present at position 27, the risk of asthma is the same regardless of what allele is present at position 16. However, with Glu at position 27, the risk of asthma is lower, and this decreased risk is modified by the allele at position 16, being lower with Arg16 than with Gly16.
Haplotype . | Control group (n = 2,331) . | . | Asthma group (n = 950) . | . | Adjusted odds ratio* . | 95% confidence interval . | ||
---|---|---|---|---|---|---|---|---|
. | No. . | % . | No. . | % . | . | . | ||
Arg/Gln | 978 | 37 | 573 | 39 | 1.00 | |||
Arg/Glu | 91 | 3 | 18 | 1 | 0.39 | 0.29, 0.58 | ||
Gly/Gln | 741 | 28 | 428 | 29 | 0.99 | 0.74, 1.49 | ||
Gly/Glu | 852 | 32 | 461 | 31 | 0.83 | 0.62, 1.24 |
Haplotype . | Control group (n = 2,331) . | . | Asthma group (n = 950) . | . | Adjusted odds ratio* . | 95% confidence interval . | ||
---|---|---|---|---|---|---|---|---|
. | No. . | % . | No. . | % . | . | . | ||
Arg/Gln | 978 | 37 | 573 | 39 | 1.00 | |||
Arg/Glu | 91 | 3 | 18 | 1 | 0.39 | 0.29, 0.58 | ||
Gly/Gln | 741 | 28 | 428 | 29 | 0.99 | 0.74, 1.49 | ||
Gly/Glu | 852 | 32 | 461 | 31 | 0.83 | 0.62, 1.24 |
Adjusted for study effect.
Haplotype . | Control group (n = 2,331) . | . | Asthma group (n = 950) . | . | Adjusted odds ratio* . | 95% confidence interval . | ||
---|---|---|---|---|---|---|---|---|
. | No. . | % . | No. . | % . | . | . | ||
Arg/Gln | 978 | 37 | 573 | 39 | 1.00 | |||
Arg/Glu | 91 | 3 | 18 | 1 | 0.39 | 0.29, 0.58 | ||
Gly/Gln | 741 | 28 | 428 | 29 | 0.99 | 0.74, 1.49 | ||
Gly/Glu | 852 | 32 | 461 | 31 | 0.83 | 0.62, 1.24 |
Haplotype . | Control group (n = 2,331) . | . | Asthma group (n = 950) . | . | Adjusted odds ratio* . | 95% confidence interval . | ||
---|---|---|---|---|---|---|---|---|
. | No. . | % . | No. . | % . | . | . | ||
Arg/Gln | 978 | 37 | 573 | 39 | 1.00 | |||
Arg/Glu | 91 | 3 | 18 | 1 | 0.39 | 0.29, 0.58 | ||
Gly/Gln | 741 | 28 | 428 | 29 | 0.99 | 0.74, 1.49 | ||
Gly/Glu | 852 | 32 | 461 | 31 | 0.83 | 0.62, 1.24 |
Adjusted for study effect.
This effect modification is marked, and the confidence interval of the odds ratio for the Arg/Glu haplotype does not overlap with that of the Gly/Glu haplotype (table 7). Subjects who had haplotypes Arg/Glu and Gly/Glu were 61 percent and 17 percent less likely to have asthma than were subjects who had haplotype Arg/Gln. However, subjects with haplotype Gly/Gln had the same chance of asthma as did subjects with Arg/Gln.
DISCUSSION
The various results of the individual single-nucleotide polymorphism (SNP) analyses and haplotype analyses are complex, but synthesizing the data overall seems to indicate the following. First, the Glu27 allele appears to be protective against asthma, reducing the risk of asthma by approximately 27 percent. This makes biologic sense because the Glu variant is resistant to down regulation in vitro, and it is possible that these individuals express higher β2-receptor levels in the context of inflammation. This was suggested in both adult and pediatric populations, although the genetic model in each was different.
Second, the protective effect of Glu27 may be due to the haplotype. It is probable that this is not an effect of this SNP in isolation but, instead, reflects a common haplotype that includes this allele. Drysdale et al. (44) investigated 13 SNPs in the human β2-adrenergic receptor gene promoter and coding regions in relation to responsiveness to β2 agonists. They found that, although there was no association when SNPs were analyzed individually, there was a clear relation between one of the common haplotypes (haplotype 2 in their paper, which included Glu27) and good response to β2 agonists in vivo, as well as increased messenger RNA levels and gene expression in vitro. Haplotypes that included Gln27 (e.g., haplotype 4 in their paper) had overall poorer response to β2 agonists and lower expression levels. Presumably, good response to exogenous agonists also reflects good response to endogenous agonists and, hence, a protective effect against asthma.
Third, the genetic model suggested by the data appears to be an overdominant protective effect of Glu27. This model is also called heterozygote advantage or positive heterosis, and although it may appear counterintuitive, a recent review indicates that this mode of action is perhaps more common than previously thought and cites numerous examples (45). Indeed, the IL12B promoter polymorphism has been associated with severity of asthma in children, and this also seems to observe a pattern of heterozygote advantage (46). The mechanism of such a model is still speculative but may include 1) advantages in having variation in a multimeric protein, such as better Vmax (47); 2) an allele with a selective advantage that is detrimental when homozygous (e.g., sickle cell and falciparum malaria); and 3) a greater range of expression of gene products and plasticity with heterozygotes than homozygotes (45). Alternatively, this may be a spurious result due to other untyped loci in the haplotypes analyzed.
Fourth, there may be interaction or synergism between different SNPs. The haplotype analysis raises the possibility that the position 16 polymorphism may be an effect modifier: The protective effect of Glu27 was accentuated with Arg16 compared with Gly16, although there was no independent effect of the position 16 polymorphism on its own. This would indicate that it may be difficult to predict a haplotype effect from its constituent SNPs.
Fifth, the linkage disequilibrium between position 16 and 27 polymorphisms is not high. This may be surprising given that they are only 30 nucleotides apart and there are no intervening introns. However, this is congruent with other studies indicating that recombination frequency is not strictly proportional to chromosomal distance, and it is sensitive to ancestral effects; for example, Drysdale et al. found that “some pairs of close sites have reduced levels of linkage disequilibrium relative to more spaced pairs of sites” (44, p. 10485).
The pooled allele frequencies at both the Arg16 and Gln27 sites confirm the presence of significant variation between racial groups and are similar to values generally recognized, for example, in ALFRED (Allele Frequency Database) (48). Although crude, these results do support a role of these polymorphisms in asthma susceptibility, given the varying incidence of asthma in these racial groups. Interestingly, the variation was more marked at the Gln27 locus than at Arg16, and it was the former that was more strongly implicated in asthma susceptibility in our results.
These findings must be taken with caution at the present time for a number of reasons. First, these estimates are obtained by pooling despite heterogeneity.
Second, the asthma phenotype was often not fully specified, and details of asthma diagnoses were often scanty. Future studies should clearly identify whether asthma cases were diagnosed from symptoms or on population screening, and they should include results of atopic testing, spirometry, or methacholine challenge. Without sufficient information in individual studies, the condition labeled as asthma in this meta-analysis is likely to be heterogeneous and may be contributing to the inconsistency of results.
Third, the haplotype results are very different from those found in the longitudinal Normative Aging Study cohort (49), where the Gly16/Gln27 haplotype had a protective effect compared with Arg16/Glu27 (a different reference genotype), whereas in our study there was an increased risk. This discrepancy, however, may be due to the fact that, in the latter, the outcome was airway hyperresponsiveness (which does not always correspond to asthma) and that the population was general, community-dwelling males screened with a methacholine challenge test, not diagnosed asthmatics.
Fourth, these findings do not take into account smoking status, since data were available from only two studies (3, 42). There are some indications that the genotype effects may be more apparent among nonsmokers (49).
Fifth, the findings in childhood and adult asthma are inconsistent. This may be due to chance, or, alternatively, there may be a genuinely different mode of action in adults compared with children, in that asthma is a clinically different disease in these two populations. Asthma in late childhood, which was the age range studied in these papers, is predominantly atopic in nature, more likely to be eosinophilic, more likely to be symptom diagnosed and episodic, and less likely to be associated with persistent airway hyperresponsiveness (49–52). Since the Glu27 polymorphism is associated with less airway hyperresponsiveness (53), this may explain differences between the associations in adults and children. Alternatively, given the incomplete understanding of asthma pathogenesis, there may be pleiotropic effects of the β2-receptor at different stages or etiologies of disease. Indeed, one of us has observed such an age-specific association for another gene candidate in a population of children followed from childhood into early adult life (54).
In summary, these results are suggestive of a protective effect of the Glu27 allele, probably as part of a haplotype, and they raise the possibility of interactions with the position 16 alleles and possibly other SNPs. This warrants further investigation in larger studies. The clinical implications of these findings are not clear. These polymorphisms may be involved in both conferring the risk to develop asthma and influencing the response to β2-agonists; this has been the subject of a recent randomized crossover trial (55) and is the topic of an ongoing meta-analysis (56).
APPENDIX
Criteria . | Score . |
---|---|
Representativeness of cases | |
Consecutive/randomly selected from case population with clearly defined sampling frame | 2 |
Consecutive/randomly selected from case population without clearly defined sampling frame or with extensive inclusion/exclusion criteria | 1 |
No method of selection described | 0 |
Representativeness of controls | |
Controls were consecutive/randomly drawn from the same sampling frame (ward/community) as cases | 2 |
Controls were consecutive/randomly drawn from a different sampling frame as cases | 1 |
Not described | 0 |
Ascertainment of asthma | |
Clearly described objective criteria for diagnosis of asthma | 2 |
Diagnosis of asthma by patient self-report or by patient history | 1 |
Not described | 0 |
Ascertainment of controls | |
Controls were tested to screen out asthma, i.e., measured FEV1* or PEFR* | 2 |
Controls were subjects who did not report asthma; no objective testing | 1 |
Not described | 0 |
Genotyping examination | |
Genotyping done under “blinded” condition | 1 |
Unblinded or not mentioned | 0 |
Hardy-Weinberg equilibrium | |
Hardy-Weinberg equilibrium in control group | 2 |
Hardy-Weinberg disequilibrium in control group | 1 |
No checking for Hardy-Weinberg equilibrium | 0 |
Association assessment | |
Assess association between genotypes and asthma with appropriate statistics and adjustment for confounders | 2 |
Assess association between genotypes and asthma with appropriate statistics without adjustment for confounders | 1 |
Inappropriate statistics used | 0 |
Response rate | |
Response rates for both groups are the same, i.e., to within 5% | 2 |
Response rates are different, between 5% and 10% | 1 |
Response rates are more than 10% different, or no mention of response rates | 0 |
Total |
Criteria . | Score . |
---|---|
Representativeness of cases | |
Consecutive/randomly selected from case population with clearly defined sampling frame | 2 |
Consecutive/randomly selected from case population without clearly defined sampling frame or with extensive inclusion/exclusion criteria | 1 |
No method of selection described | 0 |
Representativeness of controls | |
Controls were consecutive/randomly drawn from the same sampling frame (ward/community) as cases | 2 |
Controls were consecutive/randomly drawn from a different sampling frame as cases | 1 |
Not described | 0 |
Ascertainment of asthma | |
Clearly described objective criteria for diagnosis of asthma | 2 |
Diagnosis of asthma by patient self-report or by patient history | 1 |
Not described | 0 |
Ascertainment of controls | |
Controls were tested to screen out asthma, i.e., measured FEV1* or PEFR* | 2 |
Controls were subjects who did not report asthma; no objective testing | 1 |
Not described | 0 |
Genotyping examination | |
Genotyping done under “blinded” condition | 1 |
Unblinded or not mentioned | 0 |
Hardy-Weinberg equilibrium | |
Hardy-Weinberg equilibrium in control group | 2 |
Hardy-Weinberg disequilibrium in control group | 1 |
No checking for Hardy-Weinberg equilibrium | 0 |
Association assessment | |
Assess association between genotypes and asthma with appropriate statistics and adjustment for confounders | 2 |
Assess association between genotypes and asthma with appropriate statistics without adjustment for confounders | 1 |
Inappropriate statistics used | 0 |
Response rate | |
Response rates for both groups are the same, i.e., to within 5% | 2 |
Response rates are different, between 5% and 10% | 1 |
Response rates are more than 10% different, or no mention of response rates | 0 |
Total |
FEV1, forced expiratory volume in 1 second; PEFR, peak expiratory flow rate.
Criteria . | Score . |
---|---|
Representativeness of cases | |
Consecutive/randomly selected from case population with clearly defined sampling frame | 2 |
Consecutive/randomly selected from case population without clearly defined sampling frame or with extensive inclusion/exclusion criteria | 1 |
No method of selection described | 0 |
Representativeness of controls | |
Controls were consecutive/randomly drawn from the same sampling frame (ward/community) as cases | 2 |
Controls were consecutive/randomly drawn from a different sampling frame as cases | 1 |
Not described | 0 |
Ascertainment of asthma | |
Clearly described objective criteria for diagnosis of asthma | 2 |
Diagnosis of asthma by patient self-report or by patient history | 1 |
Not described | 0 |
Ascertainment of controls | |
Controls were tested to screen out asthma, i.e., measured FEV1* or PEFR* | 2 |
Controls were subjects who did not report asthma; no objective testing | 1 |
Not described | 0 |
Genotyping examination | |
Genotyping done under “blinded” condition | 1 |
Unblinded or not mentioned | 0 |
Hardy-Weinberg equilibrium | |
Hardy-Weinberg equilibrium in control group | 2 |
Hardy-Weinberg disequilibrium in control group | 1 |
No checking for Hardy-Weinberg equilibrium | 0 |
Association assessment | |
Assess association between genotypes and asthma with appropriate statistics and adjustment for confounders | 2 |
Assess association between genotypes and asthma with appropriate statistics without adjustment for confounders | 1 |
Inappropriate statistics used | 0 |
Response rate | |
Response rates for both groups are the same, i.e., to within 5% | 2 |
Response rates are different, between 5% and 10% | 1 |
Response rates are more than 10% different, or no mention of response rates | 0 |
Total |
Criteria . | Score . |
---|---|
Representativeness of cases | |
Consecutive/randomly selected from case population with clearly defined sampling frame | 2 |
Consecutive/randomly selected from case population without clearly defined sampling frame or with extensive inclusion/exclusion criteria | 1 |
No method of selection described | 0 |
Representativeness of controls | |
Controls were consecutive/randomly drawn from the same sampling frame (ward/community) as cases | 2 |
Controls were consecutive/randomly drawn from a different sampling frame as cases | 1 |
Not described | 0 |
Ascertainment of asthma | |
Clearly described objective criteria for diagnosis of asthma | 2 |
Diagnosis of asthma by patient self-report or by patient history | 1 |
Not described | 0 |
Ascertainment of controls | |
Controls were tested to screen out asthma, i.e., measured FEV1* or PEFR* | 2 |
Controls were subjects who did not report asthma; no objective testing | 1 |
Not described | 0 |
Genotyping examination | |
Genotyping done under “blinded” condition | 1 |
Unblinded or not mentioned | 0 |
Hardy-Weinberg equilibrium | |
Hardy-Weinberg equilibrium in control group | 2 |
Hardy-Weinberg disequilibrium in control group | 1 |
No checking for Hardy-Weinberg equilibrium | 0 |
Association assessment | |
Assess association between genotypes and asthma with appropriate statistics and adjustment for confounders | 2 |
Assess association between genotypes and asthma with appropriate statistics without adjustment for confounders | 1 |
Inappropriate statistics used | 0 |
Response rate | |
Response rates for both groups are the same, i.e., to within 5% | 2 |
Response rates are different, between 5% and 10% | 1 |
Response rates are more than 10% different, or no mention of response rates | 0 |
Total |
FEV1, forced expiratory volume in 1 second; PEFR, peak expiratory flow rate.
Editor's note: This paper is also available on the website of the Human Genome Epidemiology Network (http://www.cdc.gov/genomics/hugenet/).
Conflict of interest: none declared.
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