title: Genome-wide association studies in pharmacogenomics: successes and lessons.
abstract: OBJECTIVE
  As genotyping technology has progressed, genome-wide association studies (GWAS) have matured into efficient and effective tools for mapping genes underlying human phenotypes.
  
  
  METHODS
  Recent studies have shown the utility of the GWAS approach for examining pharmacogenomic traits, including drug metabolism, efficacy, and toxicity.
  
  
  RESULTS
  Application of GWAS to pharmacogenomic outcomes presents unique challenges and opportunities.
  
  
  CONCLUSIONS
  In the current review, we discuss the potential promises and potential caveats of this approach specifically as it relates to pharmacogenomic studies. Concerns with study design, power and sample size, and analysis are reviewed. We further examine the features of successful pharmacogenomic GWAS, and describe consortia efforts that are likely to expand the reach of pharmacogenomic GWAS in the future.
authors.affiliation: Department of Statistics, Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina 27695-7566, USA. motsinger@stat.ncsu.edu
authors.forename: Alison A
authors.initials: AA
authors.lastname: Motsinger-Reif
authors.forename: Eric
authors.initials: E
authors.lastname: Jorgenson
authors.forename: Mary V
authors.initials: MV
authors.lastname: Relling
authors.forename: Deanna L
authors.initials: DL
authors.lastname: Kroetz
authors.forename: Richard
authors.initials: R
authors.lastname: Weinshilboum
authors.forename: Nancy J
authors.initials: NJ
authors.lastname: Cox
authors.forename: Dan M
authors.initials: DM
authors.lastname: Roden
mesh_terms: D016022:Case-Control Studies; D002874:Chromosome Mapping; D015331:Cohort Studies; D003933:Diagnosis; D055106:Genome-Wide Association Study; D005838:Genotype; D006801:Humans; D016014:Linear Models; D010597:Pharmacogenetics; D010599:Pharmacokinetics; D010641:Phenotype; D013812:Therapeutics