BACKGROUND: Drug metabolism is a multistep process by which the body disposes of xenobiotic agents such as therapeutic drugs. Genetic variation in the enzymes involved in this process can lead to variability in a patient's response to medication. METHODS: We used molecular-inversion probe technology to develop a multiplex genotyping assay that can simultaneously test for 1227 genetic variants in 169 genes involved in drug metabolism, excretion, and transport. Within this larger set of variants, we performed analytical validation of a clinically defined core set of 165 variants in 27 genes to assess accuracy, imprecision, and dynamic range. RESULTS: In a test set of 91 samples, genotyping accuracy for the core set probes was 99.8% for called genotypes, with a 1.2% no-call (NC) rate. The majority of the core set probes (133 of 165) had < or = 1 genotyping failure in the test set; a subset of 12 probes was responsible for the majority of failures (mainly NC). Genotyping results were reproducible upon repeat testing with overall within- and between-run variation of 1.1% and 1.4%, respectively-again, primarily NCs in a subset of probes. The assay showed stable genotyping results over a 6-fold range of input DNA. CONCLUSIONS: This assay generates a comprehensive assessment of a patient's metabolic genotype and is a tool that can provide a more thorough understanding of patient-to-patient variability in pharmacokinetic responses to drugs.
BACKGROUND: Drug metabolism is a multistep process by which the body disposes of xenobiotic agents such as therapeutic drugs. Genetic variation in the enzymes involved in this process can lead to variability in a patient's response to medication. METHODS: We used molecular-inversion probe technology to develop a multiplex genotyping assay that can simultaneously test for 1227 genetic variants in 169 genes involved in drug metabolism, excretion, and transport. Within this larger set of variants, we performed analytical validation of a clinically defined core set of 165 variants in 27 genes to assess accuracy, imprecision, and dynamic range. RESULTS: In a test set of 91 samples, genotyping accuracy for the core set probes was 99.8% for called genotypes, with a 1.2% no-call (NC) rate. The majority of the core set probes (133 of 165) had < or = 1 genotyping failure in the test set; a subset of 12 probes was responsible for the majority of failures (mainly NC). Genotyping results were reproducible upon repeat testing with overall within- and between-run variation of 1.1% and 1.4%, respectively-again, primarily NCs in a subset of probes. The assay showed stable genotyping results over a 6-fold range of input DNA. CONCLUSIONS: This assay generates a comprehensive assessment of a patient's metabolic genotype and is a tool that can provide a more thorough understanding of patient-to-patient variability in pharmacokinetic responses to drugs.
Authors: Federico M Goodsaid; Shashi Amur; Jiri Aubrecht; Michael E Burczynski; Kevin Carl; Jennifer Catalano; Rosane Charlab; Sandra Close; Catherine Cornu-Artis; Laurent Essioux; Albert J Fornace; Lois Hinman; Huixiao Hong; Ian Hunt; David Jacobson-Kram; Ansar Jawaid; David Laurie; Lawrence Lesko; Heng-Hong Li; Klaus Lindpaintner; James Mayne; Peter Morrow; Marisa Papaluca-Amati; Timothy W Robison; John Roth; Ina Schuppe-Koistinen; Leming Shi; Olivia Spleiss; Weida Tong; Sharada L Truter; Jacky Vonderscher; Agnes Westelinck; Li Zhang; Issam Zineh Journal: Nat Rev Drug Discov Date: 2010-06 Impact factor: 84.694
Authors: C A Fernandez; C Smith; W Yang; R Lorier; K R Crews; N Kornegay; J K Hicks; C F Stewart; J D Kawedia; L B Ramsey; C Liu; W E Evans; M V Relling; U Broeckel Journal: Clin Pharmacol Ther Date: 2012-08-08 Impact factor: 6.875
Authors: Michael D Caldwell; Tarif Awad; Julie A Johnson; Brian F Gage; Mat Falkowski; Paul Gardina; Jason Hubbard; Yaron Turpaz; Taimour Y Langaee; Charles Eby; Cristi R King; Amy Brower; John R Schmelzer; Ingrid Glurich; Humberto J Vidaillet; Steven H Yale; Kai Qi Zhang; Richard L Berg; James K Burmester Journal: Blood Date: 2008-02-04 Impact factor: 22.113
Authors: Yueshan Hu; Erik A Ehli; Kelly Nelson; Krista Bohlen; Christophina Lynch; Patty Huizenga; Julie Kittlelsrud; Timothy J Soundy; Gareth E Davies Journal: PLoS One Date: 2012-03-20 Impact factor: 3.240
Authors: Christoph Varenhorst; Stefan James; David Erlinge; John T Brandt; Oscar O Braun; Michael Man; Agneta Siegbahn; Joseph Walker; Lars Wallentin; Kenneth J Winters; Sandra L Close Journal: Eur Heart J Date: 2009-05-09 Impact factor: 29.983