Asthma and bronchodilator responsiveness are associated with polymorphic markers of ARG1, CRHR2 and chromosome 17q21

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Journal Article

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Asthma, Bronchodilator responsiveness, Gene-gene interaction, Multifactor dimensionality reduction, Spirometry




Objective: Asthma is caused by complex interactions between multiple genes. β2-Agonist is the standard rescue treatment to relieve asthma symptoms and bronchoconstriction. A genetic study for spirometric parameters helps to predict the responses to this antiasthma treatment. This study investigated the relationship between asthma and bronchodilator responsiveness (BDR) and eight asthma genes.

Methods: Fifteen single-nucleotide polymorphisms in these genes were genotyped in 345 Chinese asthmatics and 464 controls. Gene–gene interactions were analysed by generalized multifactor dimensionality reduction (GMDR).

Results: The diagnosis of asthma was associated with rs7216389 in ORMDL3 [odds ratio (OR) 0.74 and 95% confidence interval (95% CI) 0.56–0.99] and rs3756780 in ARG1 (OR 0.67, 95% CI 0.51–0.89) and BDR with rs2749935 in ARG1. However, none of these associations remained significant at 5% when adjusted for multiple testing by the Bonferroni correction or a false discovery rate. GMDR analyses revealed that rs7216389 in ORMDL3 and rs3756780 in ARG1 might interact for a risk of asthma. Individuals with high-risk genotypes had OR 1.66 (95% CI 1.24–2.23) for asthma when compared with those with low-risk genotypes. GMDR suggested a two-locus model with rs2749935 in ARG1 and rs2190242 in CRHR2 to be associated with BDR. Specifically, reversibility of forced expiratory volume in 1 s was higher in high-risk than that in low-risk patients [mean (95% CI): 10.7 (8.6–12.9) vs. 6.8 (5.9–7.6)%] ; with the latter group showing higher forced expiratory volume in 1 s reversibility compared with high-risk controls [2.8 (1.4–4.3)%].

Conclusion: ARG1 and ORMDL3 may interact to determine the risk of asthma and ARG1 and CRHR2 to alter BDR in asthmatics. Nonetheless, this study is only hypothesis-generating as none of the single marker comparisons is significant when adjusted for multiple testing. These findings need to be confirmed in independent populations.

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Pharmacogenetics and Genomics

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