An integrative method for scoring candidate genes from association studies: application to warfarin dosing.
BACKGROUND
A key challenge in pharmacogenomics is the identification of genes whose variants contribute to drug response phenotypes, which can include severe adverse effects. Pharmacogenomics GWAS attempt to elucidate genotypes predictive of drug response. However, the size of these studies has severely limited their power and potential application. We propose a novel knowledge integration and SNP aggregation approach for identifying genes impacting drug response. Our SNP aggregation method characterizes the degree to which uncommon alleles of a gene are associated with drug response. We first use pre-existing knowledge sources to rank pharmacogenes by their likelihood to affect drug response. We then define a summary score for each gene based on allele frequencies and train linear and logistic regression classifiers to predict drug response phenotypes.


RESULTS
We applied our method to a published warfarin GWAS data set comprising 181 individuals. We find that our method can increase the power of the GWAS to identify both VKORC1 and CYP2C9 as warfarin pharmacogenes, where the original analysis had only identified VKORC1. Additionally, we find that our method can be used to discriminate between low-dose (AUROC=0.886) and high-dose (AUROC=0.764) responders.


CONCLUSIONS
Our method offers a new route for candidate pharmacogene discovery from pharmacogenomics GWAS, and serves as a foundation for future work in methods for predictive pharmacogenomics.
Biomedical Informatics Training Program, Stanford University School of Medicine, Stanford, CA, USA. nick.tatonetti@stanford.edu
Nicholas P
NP
Tatonetti
Joel T
JT
Dudley
Hersh
H
Sagreiya
Atul J
AJ
Butte
Russ B
RB
Altman
D000925:Anticoagulants / Q000008:administration & dosage*; D003577:Cytochrome P-450 Enzyme System / Q000235:genetics; D004305:Dose-Response Relationship, Drug; D005787:Gene Frequency; D055106:Genome-Wide Association Study; D005838:Genotype; D016015:Logistic Models; D006899:Mixed Function Oxygenases / Q000235:genetics; D010597:Pharmacogenetics / Q000379:methods*; D020641:Polymorphism, Single Nucleotide; D064417:Vitamin K Epoxide Reductases; D014859:Warfarin / Q000008:administration & dosage*
D000925:Anticoagulants; C400322:cytochrome P-450 CYP2C subfamily; D014859:Warfarin; D003577:Cytochrome P-450 Enzyme System; D006899:Mixed Function Oxygenases; D064417:Vitamin K Epoxide Reductases