title: Predicting response to short-acting bronchodilator medication using Bayesian networks.
abstract: OBJECTIVE
  Bronchodilator response tests measure the effect of beta(2)-agonists, the most commonly used short-acting reliever drugs for asthma. We sought to relate candidate gene SNP data with bronchodilator response and measure the predictive accuracy of a model constructed with genetic variants.
  
  
  METHODS
  Bayesian networks, multivariate models that are able to account for simultaneous associations and interactions among variables, were used to create a predictive model of bronchodilator response using candidate gene SNP data from 308 Childhood Asthma Management Program Caucasian subjects.
  
  
  RESULTS
  The model found that 15 SNPs in 15 genes predict bronchodilator response with fair accuracy, as established by a fivefold cross-validation area under the receiver-operating characteristic curve of 0.75 (standard error: 0.03).
  
  
  CONCLUSIONS
  Bayesian networks are an attractive approach to analyze large-scale pharmacogenetic SNP data because of their ability to automatically learn complex models that can be used for the prediction and discovery of novel biological hypotheses.
authors.affiliation: Harvard-MIT Division of Health Sciences and Technology, MA, USA. blanca_himes@hms.harvard.edu
authors.forename: Blanca E
authors.initials: BE
authors.lastname: Himes
authors.forename: Ann Chen
authors.initials: AC
authors.lastname: Wu
authors.forename: Qing Ling
authors.initials: QL
authors.lastname: Duan
authors.forename: Barbara
authors.initials: B
authors.lastname: Klanderman
authors.forename: Augusto A
authors.initials: AA
authors.lastname: Litonjua
authors.forename: Kelan
authors.initials: K
authors.lastname: Tantisira
authors.forename: Marco F
authors.initials: MF
authors.lastname: Ramoni
authors.forename: Scott T
authors.initials: ST
authors.lastname: Weiss
mesh_terms: D001249:Asthma / Q000188:drug therapy* / Q000235:genetics* / Q000503:physiopathology; D001499:Bayes Theorem; D001993:Bronchodilator Agents / Q000627:therapeutic use*; D002648:Child; D003627:Data Interpretation, Statistical; D005260:Female; D014644:Genetic Variation; D005838:Genotype; D006801:Humans; D016015:Logistic Models; D008297:Male; D016571:Neural Networks, Computer; D010597:Pharmacogenetics; D020641:Polymorphism, Single Nucleotide; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D012129:Respiratory Function Tests
chemical_list: D001993:Bronchodilator Agents