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Predicting Inhaled Corticosteroid Response in Asthma with Two Associated SNPs

Inhaled corticosteroids are the most commonly used controller medications prescribed for asthma. Two single-nucleotide polymorphisms (SNPs), rs1876828 in CRHR1 and rs37973 in GLCCI1, have previously been associated with corticosteroid efficacy. We studied data from four existing clinical trials of a...

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Detalles Bibliográficos
Autores principales: McGeachie, Michael J., Wu, Ann C., Chang, Hsun-Hsien, Lima, John J., Peters, Stephen P., Tantisira, Kelan G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3434304/
https://www.ncbi.nlm.nih.gov/pubmed/22641026
http://dx.doi.org/10.1038/tpj.2012.15
Descripción
Sumario:Inhaled corticosteroids are the most commonly used controller medications prescribed for asthma. Two single-nucleotide polymorphisms (SNPs), rs1876828 in CRHR1 and rs37973 in GLCCI1, have previously been associated with corticosteroid efficacy. We studied data from four existing clinical trials of asthmatics who received inhaled corticosteroids and had lung function measured by forced expiratory volume in one second (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.