Genetic variation in metabolizing enzyme and transporter genes: comprehensive assessment in 3 major East Asian subpopulations with comparison to Caucasians and Africans.

The advent of high-throughput technologies has proven valuable in the assessment of genetic differences and their effects on drug activation, metabolism, disposition, and transport. However, most studies to date have focused on a small number of genes or few alleles, some of which are rare and therefore observed infrequently or lacked rigorous ethnic characterization, thus reducing the ability to extrapolate within and among populations. In this study, the authors comprehensively assessed the allele frequencies of 165 variants comprising 27 drug-metabolizing enzyme and transporter (DMET) genes from 2188 participants across 3 major ethnic populations: Caucasians, Africans, and East Asians. This sample size was sufficiently large to demonstrate genetic differences among these major ethnic groups while concomitantly confirming similarities among East Asian subpopulations (Korean, Han Chinese, and Japanese). A comprehensive presentation of allele and genotype frequencies is included in the online supplement, and 3 of the most widely studied cytochrome P450 (CYP) genes, CYP2D6, CYP2C19, and CYP2C9; 2 non-CYP enzymes, NAT1 and TMPT; and 2 transporter genes, SLCO1B1 and SLCO2B1, are presented herein according to ethnic classification.

Multiplex assay for comprehensive genotyping of genes involved in drug metabolism, excretion, and transport.

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.

Comprehensive assessment of metabolic enzyme and transporter genes using the Affymetrix Targeted Genotyping System.

The combined effects of multiple polymorphisms in several drug-metabolizing enzyme and transporter genes can contribute to considerable interindividual variation in drug disposition and response. Therefore, it has been of increasing interest to generate scalable, flexible and cost-effective technologies for large-scale genotyping of the drug-metabolizing enzyme and transporter genes. However, the number of drug-metabolizing enzyme and transporter gene variants exceeds the capacity of current technologies to comprehensively assess multiple polymorphisms in a single, multiplexed assay. The Targeted Genotyping System (Affymetrix, CA, USA) provides a solution to this challenge, by combining molecular inversion probe technology with universal microarrays to provide a method that is capable of analyzing thousands of variants in a single reaction, while remaining relatively insensitive to cross-reactivity between reaction components. This review will focus on the Targeted Genotyping System and how this technology was adapted to enable comprehensive analysis of drug-metabolizing enzyme and transporter gene polymorphisms.