OBJECTIVE: The goal of pharmacogenomics is the translation of genomic discoveries into individualized patient care. Recent advances in the means to survey human genetic variation are fundamentally transforming our understanding of the genetic basis of interindividual variation in therapeutic response. The goal of this study was to systematically evaluate high-throughput genotyping technologies for their ability to assay variation in pharmacogenetically important genes (pharmacogenes). These platforms are either being proposed for or are already being widely used for clinical implementation; therefore, knowledge of coverage of pharmacogenes on these platforms would serve to better evaluate current or proposed pharmacogenetic association studies. METHOD: Among the genes included in our study are drug-metabolizing enzymes, transporters, receptors, and drug targets, of interest to the entire pharmacogenetic community. We considered absolute and linkage disequilibrium (LD)-informed coverage, minor allele frequency spectrum, and functional annotation for a Caucasian population. We also examined the effect of LD, effect size, and cohort size on the power to detect single nucleotide polymorphism associations. RESULTS: In our analysis of 253 pharmacogenes, we found that no platform showed more than 85% coverage of these genes (after accounting for LD). Furthermore, the lack of coverage showed a marked increase at minor allele frequencies of less than 20%. Even after accounting for LD, only 30% of the missense polymorphisms (which are enriched for low-frequency alleles) were covered by HapMap, with still lower coverage on the other platforms. CONCLUSION: We have conducted the first systematic evaluation of the Axiom Genomic Database, Omni 2.5 M, and the Drug Metabolizing Enzymes and Transporters chip. This study is the first to utilize the 1000 Genomes Project to present a comprehensive evaluative framework. Our results provide a much-needed assessment of microarray-based genotyping and next-generation sequencing technologies' ability to survey fully the variation in genes of particular interest to the pharmacogenetics community. Our findings demonstrate the limitations of genome-wide methods and the challenges of implementing pharmacogenomic tests into the clinical context.
OBJECTIVE: The goal of pharmacogenomics is the translation of genomic discoveries into individualized patient care. Recent advances in the means to survey human genetic variation are fundamentally transforming our understanding of the genetic basis of interindividual variation in therapeutic response. The goal of this study was to systematically evaluate high-throughput genotyping technologies for their ability to assay variation in pharmacogenetically important genes (pharmacogenes). These platforms are either being proposed for or are already being widely used for clinical implementation; therefore, knowledge of coverage of pharmacogenes on these platforms would serve to better evaluate current or proposed pharmacogenetic association studies. METHOD: Among the genes included in our study are drug-metabolizing enzymes, transporters, receptors, and drug targets, of interest to the entire pharmacogenetic community. We considered absolute and linkage disequilibrium (LD)-informed coverage, minor allele frequency spectrum, and functional annotation for a Caucasian population. We also examined the effect of LD, effect size, and cohort size on the power to detect single nucleotide polymorphism associations. RESULTS: In our analysis of 253 pharmacogenes, we found that no platform showed more than 85% coverage of these genes (after accounting for LD). Furthermore, the lack of coverage showed a marked increase at minor allele frequencies of less than 20%. Even after accounting for LD, only 30% of the missense polymorphisms (which are enriched for low-frequency alleles) were covered by HapMap, with still lower coverage on the other platforms. CONCLUSION: We have conducted the first systematic evaluation of the Axiom Genomic Database, Omni 2.5 M, and the Drug Metabolizing Enzymes and Transporters chip. This study is the first to utilize the 1000 Genomes Project to present a comprehensive evaluative framework. Our results provide a much-needed assessment of microarray-based genotyping and next-generation sequencing technologies' ability to survey fully the variation in genes of particular interest to the pharmacogenetics community. Our findings demonstrate the limitations of genome-wide methods and the challenges of implementing pharmacogenomic tests into the clinical context.
Authors: M R Nelson; S-A Bacanu; M Mosteller; L Li; C E Bowman; A D Roses; E H Lai; M G Ehm Journal: Pharmacogenomics J Date: 2008-02-26 Impact factor: 3.550
Authors: Alan R Shuldiner; Jeffrey R O'Connell; Kevin P Bliden; Amish Gandhi; Kathleen Ryan; Richard B Horenstein; Coleen M Damcott; Ruth Pakyz; Udaya S Tantry; Quince Gibson; Toni I Pollin; Wendy Post; Afshin Parsa; Braxton D Mitchell; Nauder Faraday; William Herzog; Paul A Gurbel Journal: JAMA Date: 2009-08-26 Impact factor: 56.272
Authors: J J Brugts; M P M de Maat; E Boersma; J C M Witteman; C van Duijn; A G Uitterlinden; M Bertrand; W Remme; K Fox; R Ferrari; A H J Danser; M L Simoons Journal: Cardiovasc Drugs Ther Date: 2008-12-10 Impact factor: 3.727
Authors: M Teichert; R H N van Schaik; A Hofman; A G Uitterlinden; P A G M de Smet; B H C H Stricker; L E Visser Journal: Clin Pharmacol Ther Date: 2009-02-18 Impact factor: 6.875