Association of β2-adrenergic receptor gene polymorphisms (rs1042713, rs1042714, rs1042711) with asthma risk: a systematic review and updated meta-analysis
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The published data on the association between β2-adrenergic receptor gene polymorphisms and asthma susceptibility are inconclusive. To derive a more precise estimation of this association, a meta-analysis was performed.
A literature search was conducted in PubMed, Web of Science, EMBASE, Wanfang, and the China National Knowledge Infrastructure (CNKI) databases to identify eligible studies. The pooled odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were used to calculate the strength of the association. A sensitivity analysis was performed to evaluate the influence of individual studies on the overall effect estimates, and funnel plots and Egger’s tests were used for indications of publication bias.
Seventy three studies with three single nucleotide polymorphisms (SNP) (rs1042713, c.G46A, p.Gly16Arg; rs1042714, c.G79C, p.Gln27Glu; rs1042711, c.T-47C, p.Cys19Arg) were finally identified. For the rs1042713 polymorphism, no significant association with asthma risk was found in the overall population. However, a significant protective association was found in the Indian population in the dominant model comparison (OR = 0.72, 95% CI = 0.59–0.87, I2 = 25%, studies = 5, cases = 1190, controls = 1241). A significant risk association was found in the Arab population in the dominant model comparison (OR = 1.75, 95% CI = 1.14–2.70, I2 = 0%, studies = 2, cases = 307, controls = 361) and the homozygote model comparison (OR = 1.88, 95% CI = 1.17–3.02, I2 = 0%, studies = 2, cases = 307, controls = 361), and in the Hispanic-Latino population in the dominant model comparison (OR = 1.68, 95% CI = 1.10–2.55, I2 = 77%, studies = 5, cases = 1026, controls = 1412). For the rs1042714 polymorphism, we found a significant association in the recessive model comparison (OR = 0.83, 95% CI = 0.70–0.98, I2 = 44%, studies = 52, cases = 8242, controls = 16,832), the homozygote genotype comparison (OR = 0.84, 95% CI = 0.72–0.98, I2 = 25%, studies = 52, cases = 8242, controls = 16,832) and the allelic genetic model (OR = 0.91, 95% CI = 0.83–0.99, I2 = 59%, studies = 52, cases = 8242, controls = 16,832) in the overall population. When stratified by age, a significant association was also found in children in the recessive model comparison (OR = 0.59, 95% CI = 0.39–0.88, I2 = 58%, studies = 18, cases = 2498, controls = 2510) and the homozygote genotype comparison (OR = 0.63, 95% CI = 0.43–0.92, I2 = 46%, studies = 18, cases = 2498, controls = 2510), but not in adult. For the rs1042711 polymorphism, no significant associations were found in the any genetic model.
The meta-analysis suggests that the ADRB2 rs1042714 polymorphism has a protective association with asthma in the overall population and the pediatric subgroup.
KeywordsADRB2 Polymorphism Asthma Meta-analysis
A Measurement Tool to Assess Systematic Reviews
China National Knowledge Infrastructure
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
Single nucleotide polymorphism
Asthma is a chronic respiratory inflammation disease characterized by airway hyperresponsiveness, reversible airway obstruction and airway wall remodeling . It is believed to be a multifactorial disorder with a strong genetic component in its pathogenesis [2, 3]. So far, many studies have evaluated the association between genetic variants and asthma susceptibility. Numerous genes have been identified as asthma-susceptible genes, from which the β-2 adrenergic receptor (ADRB2) is the most widely studied [4, 5, 6].
ADRB2 is encoded by an intronless gene on chromosome 5q31, which is abundantly expressed on many airway cells including smooth muscle cells [7, 8]. ADRB2 transcript has a 5′ leader cistron (5′ LC) harboring a short open reading frame (ORF) that encodes a 19-amino acid peptide, which regulates mRNA translation and controls the cellular expression of ADRB2. A variation at position 19 that causes a change from cysteine (Cys) to arginine (Arg) was reported in the 5′ LC, and this variation plays a role in regulating ADRB2 gene expression [9, 10, 11]. However, little is known regarding the possible role of this polymorphism in asthma. In addition, two missense variations (rs1042713, c.G46A, p.Gly16Arg and rs1042714, c.G79C, p.Gln27Glu) that occur in high allelic frequency in the general population have been identified, corresponding to a change from glycine (Gly) to arginine (Arg) at amino acid position 16 and glutamate (Gln) to glutamine (Glu) at amino acid position 27 . Studies in vitro  and primary cultures of cells expressing these endogenous variants  illustrated the different phenotypes between the polymorphic receptors. The Gly16 receptor could enhance agonist-promoted downregulation of receptor expression compared with the Arg16 receptor. In contrast, the Glu27 receptor is relatively resistant to agonist-promoted downregulation compared with the Gln27 receptor [13, 14]. Genetic studies have indicated that these variations not only affect the risk of asthma, but also affect the therapeutic outcomes of inhaled β2-adrenergic receptor agonists [15, 16, 17, 18, 19, 20].
Considering the impact of the asthma risk potentially resulting from ADRB2 gene variations, a number of case-control studies have explored the association between the ADRB2 gene polymorphisms and asthma risk in different ethnicities [21, 22, 23]. However, these results are conflicting and inconclusive, which are possibly due to the limitations associated with an individual studies and small sample size. To shed light on these contradictory results and to more precisely evaluate the relationship between the ADRB2 gene polymorphisms and asthma risk, several meta-analyses concerning the association between ADRB2 gene polymorphisms and asthma have been reported [15, 24, 25, 26, 27, 28, 29]. However, these meta-analyses have also shown inconsistent results. After publication of these meta-analyses, many additional case-control studies about the ADRB2 polymorphisms on asthma risk were carried out [30, 31, 32, 33, 34]. Therefore, we present the results of a comprehensively updated meta-analysis of all relevant published data to investigate the associations between ADRB2 gene polymorphisms and asthma risk with a focus on rs1042713, rs1042714 and rs1042711 polymorphisms.
This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement guidelines.
Publications were obtained from the PubMed, EMBASE, Web of Science, the Chinese National Knowledge Infrastructure, and Wanfang databases (the last search was conducted on September 1, 2018). The keywords searched in our investigation were (asthma or asthmatic) and (β2-adrenergic receptor or ADRB2 or β2-AR or beta2-adrenoreceptor or β2-adrenoceptor) and (polymorphism or mutation or variant or rs1042713 or G46A or Gly16Arg or rs1042714 or G79C or Gln27Glu or rs1042711 or T-47C or Cys19Arg). The search was performed in duplicate by two independent reviewers (Songlin Zhao and Wei Zhang).
Inclusion and exclusion criteria
The inclusion criteria of our study were as follows: (1) any human studies that estimated the prevalence of the β2-adrenergic receptor polymorphisms and asthma risk were included, which were published in English and Chinese. (2) They were case-control studies. (3) The genotype distributions or allele frequency of each study should be available for estimating an odds ratio with a 95% confidence interval. (4) When eligible papers had insufficient information, we contacted the authors for additional information via email. Studies were excluded from our meta-analysis if their authors did not provide us with the related data.
The basic information extracted from each study was as follows: name of the first author, publication year, country, ethnicity, age of cases and controls, sample size, and genotype frequencies in cases and controls. The data were extracted independently and in duplicate by two reviewers (Songlin Zhao and Wei Zhang) who used a standardized data extraction form. Any disagreement was adjudicated by a third author (Xiuhong Nie).
Study quality assessment and meta-analysis quality assessment
The Newcastle-Ottawa Scale (NOS) was used to assess the quality of the included studies. The items assessed included selection, comparability of case/controls, exposure/outcome, age and gender. The quality scores ranged from 0 to 9. We divided the NOS scores into three levels (higher quality, score ≥ 7; moderate quality, 4 ≤ score < 7; low quality, score < 4).
A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR 2) was used to assess the quality of the systematic reviews . The AMSTAR 2 calculator queries 16 items of relevance that provide insight into the quality of the systematic review methodology.
A Hardy-Weinberg equilibrium (HWE) was assessed for each study by use of the Pearson’s chi-square test in control groups, and significance was set at P < 0.05. The pooled ORs for the ADRB2 polymorphisms and asthma risk were calculated for the dominant genetic model, the recessive genetic model, the homozygote genetic model and the allele genetic model. The heterogeneity was assessed by using the Q-test and I2 test. A P-value> 0.10 of Q-test and I2 < 50% indicated a lack of heterogeneity among the studies; then, the fixed-effect model was used. Otherwise, the random effect model was used. Subgroup analyses were performed regarding ethnicity, case age and HWE P-value. The ethnicity subgroups were designed as Caucasian, Hispanic-Latinos, non-Hispanic Blacks, East-Asian, Indian and Arab. Age subgroups were designed as Adult and pediatric subgroups. HWE P-value subgroups were designed as P-value> 0.05 and P-value< 0.05 subgroups. Sensitivity analysis was conducted by sequentially excluding one study at a time to examine the effect of each study on the combined result. The funnel plot and Egger’s test was used to assess the potential publication bias. All the statistical analyses of this meta-analysis were performed using the STATA 11.0 software (State Corporation, College Station, TX, USA).
Characteristics of the studies included in the meta-analysis.
Meta-analysis of ADRB2 rs1042713 polymorphism and asthma risk
Results of the pooled and subgroup analyses for the ADRB2 rs1042713 polymorphism and asthma risk
Dominant model comparison
Recessive model comparison
Homozygote genotype comparison
Frequency of minor allele (A/(A + G))
1.08 [0.97, 1.21]
1.05 [0.94, 1.18]
1.10 [0.95, 1.27]
1.02 [0.95, 1.10]
1.12 [0.97, 1.28]
1.05 [0.92, 1.19]
1.12 [0.96, 1.32]
1.06 [0.98, 1.15]
1.13 [0.93, 1.38]
1.07 [0.85, 1.35]
1.13 [0.85, 1.51]
1.00 [0.85, 1.17]
1.00 [0.87, 1.16]
1.04 [0.87, 1.26]
1.03 [0.84, 1.26]
1.02 [0.93, 1.13]
0.72 [0.59, 0.87]
0.91 [0.69, 1.19]
0.72 [0.51, 1.03]
0.84 [0.69, 1.02]
1.75 [1.14, 2.70]
1.17 [0.59, 2.30]
1.88 [1.17, 3.02]
0.83 [0.34, 2.02]
1.68 [1.10, 2.55]
1.64 [0.86, 3.14]
2.09 [0.98, 4.45]
0.99 [0.60, 1.63]
1.55 [0.70, 3.42]
1.22 [0.68, 2.19]
1.40 [0.64, 3.06]
0.70 [0.55, 0.89]
1.05 [0.87, 1.25]
0.96 [0.83, 1.11]
1.01 [0.87, 1.16]
0.99 [0.89, 1.10]
HWE(P > 0.05)
0.99 [0.87, 1.13]
0.97 [0.85, 1.10]
0.98 [0.81, 1.16]
0.98 [0.90, 1.07]
HWE(P < 0.05)
1.22 [0.96, 1.55]
1.17 [0.94, 1.44]
1.17 [0.99, 1.38]
1.15 [1.01, 1.30]
Meta-analysis of the ADRB2 rs1042714 polymorphism and asthma risk
Results of the pooled and subgroup analyses for the ADRB2 rs1042714 polymorphism and asthma risk
Dominant model comparison
Recessive model comparison
Homozygote genotype comparison
Frequence of minor allele (G/(G + C))
0.92 [0.83, 1.02]
0.83 [0.70, 0.98]
0.84 [0.72, 0.98]
0.91 [0.83, 0.99]
0.89 [0.77, 1.02]
0.94 [0.83, 1.07]
0.94 [0.81, 1.08]
0.92 [0.83, 1.02]
0.97 [0.81, 1.16]
0.59 [0.39, 0.88]
0.63 [0.43, 0.92]
0.86 [0.69, 1.07]
0.94 [0.85, 1.04]
0.81 [0.65, 1.01]
0.82 [0.66, 1.03]
0.93 [0.85, 1.01]
0.85 [0.68, 1.07]
1.04 [0.70, 1.54]
0.95 [0.63, 1.43]
0.91 [0.76, 1.09]
0.98 [0.63, 1.51]
1.14 [0.49, 2.61]
1.11 [0.47, 2.60]
1.01 [0.71, 1.43]
0.67 [0.41, 1.10]
0.54 [0.13, 2.25]
0.54 [0.18, 1.64]
0.61 [0.33, 1.15]
1.06 [0.53, 2.09]
0.88 [0.40, 1.94]
0.94 [0.41, 2.12]
1.03 [0.74, 1.45]
0.98 [0.81, 1.19]
0.90 [0.78, 1.03]
0.92 [0.79, 1.08]
0.94 [0.82, 1.07]
HWE(P > 0.05)
0.89 [0.80, 0.99]
0.94 [0.83, 1.06]
0.94 [0.81, 1.08]
0.91 [0.84, 0.99]
HWE(P < 0.05)
0.95 [0.77, 1.17]
0.70 [0.47, 1.06]
0.73 [0.51, 1.05]
0.87 [0.70, 1.09]
Meta-analysis of the ADRB2 rs1042711 polymorphism and asthma risk
Results of the pooled analyses for the ADRB2 rs1042711 polymorphism and asthma risk
Dominant model comparison
0.91 [0.73, 1.14]
Recessive model comparison
1.24 [0.89, 1.74]
Homozygote genotype comparison
1.21 [0.86, 1.71]
0.95 [0.78, 1.18]
Frequence of minor allele (C/(T + C))
Publication bias results of Egger’s test
Dominant model comparison
Recessive model comparison
Homozygote genotype comparison
In this study, the associations between three ADRB2 gene SNPs (rs1042713, rs1042714 and rs1042711) and the risk of asthma were conducted base on the data from 73 studies involving 13,493 asthmatic patients and 22,931 controls. This meta-analysis showed that the rs1042713 polymorphism was not a risk factor for overall asthma susceptibility, which was consistent with most of the previous meta-analyses [15, 16, 25, 27, 28, 29]; however, the data contradict one of the latest meta-analyses . The difference between these results is seemingly due to the different inclusion criteria. The inclusion criteria in the Xie et al.  meta-analysis used P-value of the HWE; however, when stratified by the P-value of the HWE, there was still no association between the Gly16Arg polymorphism and asthma in the HWE (P > 0.05) subgroup in our study and in that of Liang et al. . When reviewing Xie et al.’s literature list, we found that they missed some studies that satisfied their inclusion criteria [31, 54, 77, 78, 79, 87, 88, 91, 92, 95], which may be a reason for the discrepancies.
Some studies reported that the genotype frequency and allele frequency of the rs1042713 polymorphism vary among different ethnic groups [98, 99]. A search of 1000 Genomes Project or Hapmap data showed an approximately 15% difference in allele frequency for the rs1042713 polymorphism. The Gly16 homozygous genotype frequency is more common in the non-Hispanic White than Chinese and more frequent in non-Hispanic White compared to non-Hispanic Black. Therefore, there is high heterogeneity for the rs1042713 polymorphism in the overall analysis. Even though we excluded some studies that did not meet the HWE, heterogeneity was not decreased. Selective bias in the literature has an important effect on the results of the overall meta-analysis. Large sample sizes can better reflect the truth of the effects of the rs1042713 polymorphism on the asthma risk.
Because the genotype frequency and allele frequency of the rs1042713 polymorphism vary among the different ethnic groups, we divided the ethnic groups according to the studies reported by Ortega et al. [100, 101], such that (1) non-Hispanic Whites of European ancestry were designated as Caucasian, (2) Mexicans and South Americans were designated as Hispanic-Latinos, (3) African Americans and non-Hispanic Blacks from Europe and Africa were designated as non-Hispanic Blacks; and (4) Chinese, Japanese and Korean individuals were considered separate Asian ethnic groups and designated as the East-Asian subgroup. In addition, Indian and Arab descendants were designated as separate ethnic groups because these ethnic subgroups have different genotypes and allele frequencies . The analysis stratified by ethnicity showed a significant risk association in Hispanic-Latinos in the dominant model comparison, consistent with a previous study where a significant association in the South American population was found . In addition, the previous study claimed to divide the cohorts by ethnicity, but for the most part, the cohorts were divided by continent when they combined Indian, Arab, Japanese and Han Chinese individuals as the Asian population [24, 25]. These populations have different genotypic and allelic frequencies for the rs1042713 polymorphism . After the stratified analysis, the heterogeneities in the Arab and Indian population were decreased, and a protective association in the Indian population in the dominant model comparison and a risk association in the Arab population in the dominant model comparison and the homozygote genotype comparison were found. However, there is a need for further studies with larger sample sets.
For the rs1042714 polymorphism in the current meta-analysis, benefitting from the inclusion of more case-control studies, a protective effect was found not only in the pediatric subgroup in the recessive model comparison and the homozygote genotype comparison but also in the overall population in the recessive model comparison, the homozygote genotype comparison and the allelic genetic model. This was consistent with previous reports by Liang et al.  and Ammarin et al.  that showed a protective effect in the pediatric subgroup in the recessive model comparison and the homozygote genotype comparison, confirming that the Glu27 polymorphism was a protective effect for asthma. A genetic study showed that Glu27 homozygotes had less reactive airways than Gln27 homozygotes, and these results could further suggest a protective role for the Glu27 polymorphism in asthma . In addition, in vitro and ex vivo functional studies indicated that Glu27 allele enhanced resistance to agonist-induced down regulation of the receptor, suggesting a protective role of Glu27 polymorphism in regard to receptor desensitisation [13, 14].
In the analysis stratified by HWE according to the P-value for the rs1042714 polymorphism, significant associations were found in the subgroup with P > 0.05 in the dominant model comparison and the allelic genetic model but not in the P < 0.05 subgroup. These results need to be interpreted with caution. The reason the control group population was not in HWE may be selection for a particular phenotype or that the population was not sufficiently large or random.
For the rs1042711 polymorphism, no significant associations with the risk of asthma were found in any comparison model. More research is needed because only seven case-controls were included in this study. There might not be sufficient statistical evidence to clarify the association between the rs1042711 polymorphism and the risk of asthma.
There could be several potential limitations to this meta-analysis. The first problem relates to the limitations of the literature. All available literature should be included in the meta-analysis, but we only included literature published in English and Chinese, thus neglecting studies published in other languages. Second, even though the existing literature had acceptable quality, detailed information was not provided such as asthma definition varied among different articles and this may be a confounding factor. Using a self- or physician-diagnosis of asthma can be confounded by individuals who do not have asthma such as older subjects with a smoking history who could have COPD. These physician-diagnosed cohorts many times do not have an objective diagnostic basis of asthma based on methacholine BHR or beta agonist responsiveness which could result in confounded and undetected associations. In addition, the participation rates for cases and controls were not reported in the majorities of included studies; thus, our meta-analysis was unable to explore the selection bias. Moreover, with limited information about maternal constitutional and environmental risk factors for asthma (such as smoking history), we could not evaluate the gene-gene and gene-environmental interactions. The different definitions of asthma and the environmental factors in individual studies were obvious sources of clinical heterogeneity and may produce bias. Therefore, moderate-to-high heterogeneities were found in some genetic models for the Gly16Arg polymorphism. Stratification by ethnicity may help to improve homogeneity among studies, but it may also influence statistical power. In addition, some meta-analysis studies claimed to divide the cohorts by ethnicity but it seems like the cohorts were actually being divided by continent for the most part, it will induce the contradictory findings. Third, the Gly16Arg and Gln27Glu polymorphisms tagging for rare variants modulated therapeutic responses and contributed to asthma risk ; however, these variants were not specifically genotyped.
In conclusion, the present meta-analysis indicates that the rs1042714 polymorphism is an important genetic protective factor to decrease the risk of developing asthma, especially in children. The rs1042713 polymorphism may be involved in the risk of asthma in the Arab and Hispanic-Latino populations and a protective factor in the Indian population. However, more well-designed and high-quality studies with larger sample sizes should be conducted to support this finding in various ethnic groups.
XN conceived and designed the experiments. SZ and WZ searched and assessed the literatures, and extracted the data from literature, respectively. SZ analyzed the data by STATA 11.0 software and prepared the figures SZ and XN drafted and revised the manuscript. All authors have read and approve the final manuscript.
Ethics approval and consent to participate
Consent for publication
The authors declare that they have no competing interests.
- 8.Dai XH, Zhou JP. Association of IL-13 and beta2 receptor gene polymorphisms with asthma. Shandong Med J. 2008;48(3):119–21.Google Scholar
- 10.McGraw DW, Liggett SB. Coding block and 5 leader cistron polymorphisms of the beta2-adrenergic receptor. Clin Exp Allergy. 1999;29(Suppl 4):43–5.Google Scholar
- 11.Parola AL, Kobilka BK. The peptide product of a 5′ leader cistron in the beta 2 adrenergic receptor mRNA inhibits receptor synthesis. J Biol Chem. 1994;269(6):4497–505.Google Scholar
- 20.Israel E, Drazen JM, Liggett SB, Boushey HA, Cherniack RM, Chinchilli VM, Cooper DM, Fahy JV, Fish JE, Ford JG, et al. The effect of polymorphisms of the beta (2)-adrenergic receptor on the response to regular use of albuterol in asthma. Am J Respir Crit Care Med. 2000;162(1):75–80.CrossRefGoogle Scholar
- 29.Chen JL, Huang X, Tan JY, Wan ZD, Wu XW, Li DX. Association between ADRB2 rs1042713 gene polymorphism and susceptibility of asthma in Chinese population: a meta-analysis. Chinese J Immunology. 2015;31(08):1037–9.Google Scholar
- 35.Shea BJ, Reeves BC, Wells G, Thuku M, Hamel C, Moran J, Moher D, Tugwell P, Welch V, Kristjansson E, et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ. 2017;358:j4008.CrossRefPubMedPubMedCentralGoogle Scholar
- 43.Gao G, Wang S, Zhang J. Study on beta 2 adrenergic receptor genetic polymorphisms in asthmatics in the people of the Han nationality of northern China. Zhonghua Jie He He Hu Xi Za Zhi. 2000;23(2):93–7.Google Scholar
- 45.Shachor J, Chana Z, Varsano S, Erlich T, Goldman E, Dror Y, Yakovy I, Navon R. Genetic polymorphisms of the beta-2 adrenergic receptor in Israelis with severe asthma compared to non-asthmatic Israelis. Isr Med Assoc J. 2003;5(11):821–4.Google Scholar
- 49.Gao JM, Lin YG, Qiu CC, Liu YW, Ma Y, Liu Y. Beta2-adrenergic receptor gene polymorphism in Chinese northern asthmatics. Chin Med Sci J. 2004;19(3):164–9.Google Scholar
- 59.Fu WP, Zhao ZH, Zhong L, Sun C, Fang LZ, Liu L, Zhang JQ, Wang L, Shu JK, Wang XM, et al. Relationship between polymorphisms in the 5′ leader cistron, positions 16 and 27 of the adrenergic beta2 receptor gene and asthma in a Han population from southwest China. Respirology. 2011;16(8):1221–7.CrossRefGoogle Scholar
- 65.Larocca N, Moreno D, Garmendia JV, Velasquez O, Martin-Rojo J, Talamo C, Garcia A, De Sanctis JB. Beta 2 adrenergic receptor polymorphisms, at codons 16 and 27, and bronchodilator responses in adult Venezuelan asthmatic patients. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub. 2013;157(4):374–8.CrossRefGoogle Scholar
- 66.Pino-Yanes M, Corrales A, Cumplido J, Poza P, Sanchez-Machin I, Sanchez-Palacios A, Figueroa J, Acosta-Fernandez O, Buset N, Garcia-Robaina JC, et al. Assessing the validity of asthma associations for eight candidate genes and age at diagnosis effects. PLoS One. 2013;8(9):e73157.CrossRefPubMedPubMedCentralGoogle Scholar
- 67.Saadi AV, Gupta H, Angural A, Dhanya SK, Mony S, Oberoi D, D'Souza SC, Sahoo RC, Hande MH, Gopinath PM, et al. Single nucleotide polymorphisms of ADRB2 gene and their association with susceptibility for plasmodium falciparum malaria and asthma in an Indian population. Infect Genet Evol. 2013;20:140–7.CrossRefGoogle Scholar
- 69.Leite N, Lazarotto L, Milano GE, Titski AC, Consentino CL, de Mattos F, de Andrade FA, Furtado-Alle L. Beta 2-adrenergic receptor gene association with overweight and asthma in children and adolescents and its relationship with physical fitness. Rev Paul Pediatr. 2015;33(4):381–6.CrossRefPubMedPubMedCentralGoogle Scholar
- 71.Shah NJ, Vinod Kumar S, Gurusamy U, Annan Sudarsan AK, Shewade DG. Effect of ADRB2 (adrenergic receptor beta2) gene polymorphisms on the occurrence of asthma and on the response to nebulized salbutamol in south Indian patients with bronchial asthma. J Asthma. 2015;52(8):755–62.CrossRefGoogle Scholar
- 72.Guo X, Zheng H, Mao C, Guan E, Si H. An association and meta-analysis study of 4 SNPs from beta-2 adrenergic receptor (ADRB2) gene with risk of asthma in children. Asian Pac J Allergy Immunol. 2016;34(1):11–20.Google Scholar
- 75.Hakonarson H, Bjornsdottir US, Ostermann E, Arnason T, Adalsteinsdottir AE, Halapi E, Shkolny D, Kristjansson K, Gudnadottir SA, Frigge ML, et al. Allelic frequencies and patterns of single-nucleotide polymorphisms in candidate genes for asthma and atopy in Iceland. Am J Respir Crit Care Med. 2001;164(11):2036–44.CrossRefPubMedPubMedCentralGoogle Scholar
- 78.Xing J, Wang C, Liu JZ, Yan M, Huang KW, et al. Association of receptor gene polymorphisms with asthma in Northern Chinese Han Population. Chinese J Internal Med. 2001;40(3):340–2.Google Scholar
- 79.Liao W, Li LW, Zhao CM, Guang LX, Yin XJ, et al. Preliminary study on the relationship between β2-adrenergic receptors genetic polymor- phisms and asthma in children of Han nationality of Chongqing. J Third Military Medical University. 2001;23:968–71.Google Scholar
- 80.Dai LM, Wang WZ, Zhang YP, Li W, Zhao ZH, et al. Association of beta2 receptor gene polymorphisms with lung function in asthma patients. Chinese Journal of Tuberculosis and Respiratory Diseases. 2002;25(2):554–5.Google Scholar
- 81.Wang W, Wufuer HMTL, Shabiti YLHMJ, Xiang YB, Abula ABLKM. Association between the genetic polymorphisms of β2-adrenergic receptor gene and the asthma susceptibility and clinical phenotypes in Uygur population. J Cardiovascular Pulmonary Dis. 2004;23:147–52.Google Scholar
- 82.Feng DX, Ye WX, Zhang XY, Yu H, Diao XY, et al. Study on β2-adrenergic receptor genetic polymorphisms and asthma. J Modern Clin Med Bioengineering. 2004;10:5–7.Google Scholar
- 84.Tuerxun KLBN, Shabiti YLHM, Wang W, Wufuer HMTL. Study on the β2AR polymorphism in asthmatic abnormal black savda patients. Journal of Xinjiang Medical University. 2007;30:945–8.Google Scholar
- 85.Cui LY, Liu XH, Gao LX, Fan DS. Study on the association between β2-adrenergic receptor genetic polymorphisms and asthma in the population of Inner Mongolia. Chinese journal of Clinical Medicin. 2007;14:477–81.Google Scholar
- 87.Zhang XY, Zhao WL, Gui Q, He NH. Relationship between genetic polymorphisms of β2-adrenergic receptor and childhood asthma. Journal of Clinical Pediatrics. 2008;26:399–408.Google Scholar
- 88.Xie Y, Yang Z, Chai BC. Relationship of genetic polymorphisms of β2 - adrenergic receptor and asthma in children in Shanghai area. J of Applied Clinical Pediatrics. 2008;23:272–3.Google Scholar
- 89.Liu L, Fang LZ, Dai LM. Combination Effect of Gene Polymorphisms in 16 Position of β2-adenergic Receptor and Cigarette Smoking on Asthma in Chinese Han Individuals. Medical Recapitulate. 2009;15(4):1247–78.Google Scholar
- 92.He XQLF, Tan JY, Yang XX. Association of single nucleotide polymorphisms of ADRB2 Arg16Gly with asthma in southern Chinese population. Immunological Journal. 2012;28:687–90.Google Scholar
- 93.Ye WXFD, Zhang XY, Yu H, Xu M. Study on the relationship between β2-adrenergic receptor genetic polymorphisms and asthma a in Miao nationality. J Med Res. 2011;40:83–5.Google Scholar
- 95.Yang ZZH, Wang W, Yin Y, Zhang L, et al. Effect of β2-adrenergic receptor polymorphisms on childhood asthma and therapeutic efficacy of long acting β2-agonist. J of Clin Pediatrics. 2012;30:739–43.Google Scholar
- 98.Maxwell TJ, Ameyaw MM, Pritchard S, Thornton N, Folayan G, Githang'a J, Indalo A, Tariq M, Mobarek A, Evans DA, et al. Beta-2 adrenergic receptor genotypes and haplotypes in different ethnic groups. Int J Mol Med. 2005;16(4):573–80.Google Scholar
- 99.Xie HG, Stein CM, Kim RB, Xiao ZS, He N, Zhou HH, Gainer JV, Brown NJ, Haines JL, Wood AJ. Frequency of functionally important beta-2 adrenoceptor polymorphisms varies markedly among African-American, Caucasian and Chinese individuals. Pharmacogenetics. 1999;9(4):511–6.Google Scholar
- 101.Humes K, Jones NA, Ramirez RR. Overview of race and Hispanic origin: 2010; 2011.Google Scholar
- 103.Ortega VE, Hawkins GA, Moore WC, Hastie AT, Ampleford EJ, Busse WW, Castro M, Chardon D, Erzurum SC, Israel E, et al. Effect of rare variants in ADRB2 on risk of severe exacerbations and symptom control during longacting beta agonist treatment in a multiethnic asthma population: a genetic study. Lancet Respir Med. 2014;2(3):204–13.CrossRefPubMedPubMedCentralGoogle Scholar
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