title: Development of a Pharmacogenetic Predictive Test in asthma: proof of concept.
abstract: OBJECTIVE
  To assess the feasibility of developing a Combined Clinical and Pharmacogenetic Predictive Test, comprised of multiple single nucleotide polymorphisms (SNPs) that is associated with poor bronchodilator response (BDR).
  
  
  METHODS
  We genotyped SNPs that tagged the whole genome of the parents and children in the Childhood Asthma Management Program (CAMP) and implemented an algorithm using a family-based association test that ranked SNPs by statistical power. The top eight SNPs that were associated with BDR comprised the Pharmacogenetic Predictive Test. The Clinical Predictive Test was comprised of baseline forced expiratory volume in 1 s (FEV1). We evaluated these predictive tests and a Combined Clinical and Pharmacogenetic Predictive Test in three distinct populations: the children of the CAMP trial and two additional clinical trial populations of asthma. Our outcome measure was poor BDR, defined as BDR of less than 20th percentile in each population. BDR was calculated as the percent difference between the prebronchodilator and postbronchodilator (two puffs of albuterol at 180 microg/puff) FEV1 value. To assess the predictive ability of the test, the corresponding area under the receiver operating characteristic curves (AUROCs) were calculated for each population.
  
  
  RESULTS
  The AUROC values for the Clinical Predictive Test alone were not significantly different from 0.50, the AUROC of a random classifier. Our Combined Clinical and Pharmacogenetic Predictive Test comprised of genetic polymorphisms in addition to FEV1 predicted poor BDR with an AUROC of 0.65 in the CAMP children (n = 422) and 0.60 (n = 475) and 0.63 (n = 235) in the two independent populations. Both the Combined Clinical and Pharmacogenetic Predictive Test and the Pharmacogenetic Predictive Test were significantly more accurate than the Clinical Predictive Test (AUROC between 0.44 and 0.55) in each of the populations.
  
  
  CONCLUSIONS
  Our finding that genetic polymorphisms with a clinical trait are associated with BDR suggests that there is promise in using multiple genetic polymorphisms simultaneously to predict which asthmatics are likely to respond poorly to bronchodilators.
authors.affiliation: Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, 133 Brookline Avenue, 6th Floor, Boston, MA 02215-5301, USA. ann.wu@childrens.harvard.edu
authors.forename: Ann Chen
authors.initials: AC
authors.lastname: Wu
authors.forename: Blanca E
authors.initials: BE
authors.lastname: Himes
authors.forename: Jessica
authors.initials: J
authors.lastname: Lasky-Su
authors.forename: Augusto
authors.initials: A
authors.lastname: Litonjua
authors.forename: Lingling
authors.initials: L
authors.lastname: Li
authors.forename: Christoph
authors.initials: C
authors.lastname: Lange
authors.forename: John
authors.initials: J
authors.lastname: Lima
authors.forename: Charles G
authors.initials: CG
authors.lastname: Irvin
authors.forename: Scott T
authors.initials: ST
authors.lastname: Weiss
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D019540:Area Under Curve; D001249:Asthma / Q000175:diagnosis*; D002648:Child; D002986:Clinical Trials as Topic; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010597:Pharmacogenetics / Q000379:methods*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D012372:ROC Curve