| Literature DB >> 25601762 |
Y Wang1, C Tong1, Z Wang2, Z Wang2, D Mauger1, K G Tantisira3, E Israel3, S J Szefler4, V M Chinchilli1, H A Boushey5, S C Lazarus5, R F Lemanske6, R Wu1.
Abstract
Asthma is a chronic lung disease that has a high prevalence. The therapeutic intervention of this disease can be made more effective if genetic variability in patients' response to medications is implemented. However, a clear picture of the genetic architecture of asthma intervention response remains elusive. We conducted a genome-wide association study (GWAS) to identify drug response-associated genes for asthma, in which 909 622 SNPs were genotyped for 120 randomized participants who inhaled multiple doses of glucocorticoids. By integrating pharmacodynamic properties of drug reactions, we implemented a mechanistic model to analyze the GWAS data, enhancing the scope of inference about the genetic architecture of asthma intervention. Our pharmacodynamic model observed associations of genome-wide significance between dose-dependent response to inhaled glucocorticoids (measured as %FEV1) and five loci (P=5.315 × 10(-7) to 3.924 × 10(-9)), many of which map to metabolic genes related to lung function and asthma risk. All significant SNPs detected indicate a recessive effect, at which the homozygotes for the mutant alleles drive variability in %FEV1. Significant associations were well replicated in three additional independent GWAS studies. Pooled together over these three trials, two SNPs, chr6 rs6924808 and chr11 rs1353649, display an increased significance level (P=6.661 × 10(-16) and 5.670 × 10(-11)). Our study reveals a general picture of pharmacogenomic control for asthma intervention. The results obtained help to tailor an optimal dose for individual patients to treat asthma based on their genetic makeup.Entities:
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Year: 2015 PMID: 25601762 PMCID: PMC6156797 DOI: 10.1038/tpj.2014.83
Source DB: PubMed Journal: Pharmacogenomics J ISSN: 1470-269X Impact factor: 3.550