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Inhaled corticosteroids (ICS) are the most commonly used controller medications prescribed for asthma. Two single-nucleotide polymorphisms (SNPs), rs1876828 in corticotrophin releasing hormone receptor 1 and rs37973 in GLCCI1, have previously been associated with corticosteroid efficacy. We studied data from four existing clinical trials of asthmatics, who received ICS and had lung function measured by forced expiratory volume in 1 s (FEV1) before and after the period of such treatment. We combined the two SNPs rs37973 and rs1876828 into a predictive test of FEV1 change using a Bayesian model, which identified patients with good or poor steroid response (highest or lowest quartile, respectively) with predictive performance of 65.7% (P=0.039 vs random) area under the receiver-operator characteristic curve in the training population and 65.9% (P=0.025 vs random) in the test population. These findings show that two genetic variants can be combined into a predictive test that achieves similar accuracy and superior replicability compared with single SNP predictors.

Predicting inhaled corticosteroid response in asthma with two associated SNPs