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1.
Clin Chem ; 53(7): 1222-30, 2007 Jul.
Article in English | MEDLINE | ID: mdl-17510302

ABSTRACT

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.


Subject(s)
Genetic Variation , Pharmaceutical Preparations/metabolism , Pharmacogenetics/methods , Biological Transport/genetics , Genotype , Humans , Oligonucleotide Array Sequence Analysis , Oligonucleotide Probes , Plasmids , Polymerase Chain Reaction/methods , Polymorphism, Single Nucleotide , Reproducibility of Results
2.
Pharmacogenomics ; 8(3): 293-305, 2007 Mar.
Article in English | MEDLINE | ID: mdl-17324118

ABSTRACT

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.


Subject(s)
Gene Targeting/methods , Membrane Transport Proteins/genetics , Membrane Transport Proteins/metabolism , Gene Targeting/trends , Genetic Techniques/trends , Genotype , Humans , Pharmacogenetics/methods , Pharmacogenetics/trends , Polymorphism, Genetic/genetics
3.
Eur J Hum Genet ; 14(2): 207-15, 2006 Feb.
Article in English | MEDLINE | ID: mdl-16306880

ABSTRACT

High-throughput genotyping technologies that enable large association studies are already available. Tools for genotype determination starting from raw signal intensities need to be automated, robust, and flexible to provide optimal genotype determination given the specific requirements of a study. The key metrics describing the performance of a custom genotyping study are assay conversion, call rate, and genotype accuracy. These three metrics can be traded off against each other. Using the highly multiplexed Molecular Inversion Probe technology as an example, we describe a methodology for identifying the optimal trade-off. The methodology comprises: a robust clustering algorithm and assessment of a large number of data filter sets. The clustering algorithm allows for automatic genotype determination. Many different sets of filters are then applied to the clustered data, and performance metrics resulting from each filter set are calculated. These performance metrics relate to the power of a study and provide a framework to choose the most suitable filter set to the particular study.


Subject(s)
Algorithms , Molecular Probe Techniques , Polymorphism, Single Nucleotide/genetics , Research Design , Cluster Analysis , Computer Simulation , Genetic Markers/genetics , Genotype , Reproducibility of Results
4.
Proc Natl Acad Sci U S A ; 102(41): 14717-22, 2005 Oct 11.
Article in English | MEDLINE | ID: mdl-16203980

ABSTRACT

Identification of the genetic basis of common disease may require comprehensive sequence analysis of coding regions and regulatory elements in patients and controls to find genetic effects caused by rare or heterogeneous mutations. In this study, we demonstrate how mismatch repair detection on tag arrays can be applied in a case-control study. Mismatch repair detection allows >1,000 amplicons to be screened for variations in a single laboratory reaction. Variation scanning in 939 amplicons, mostly in coding regions within a linkage peak, was done for 372 patients and 404 controls. In total, >180 Mb of DNA was scanned. Several variants more prevalent in patients than in controls were identified. This study demonstrates an approach to the discovery of susceptibility genes for common disease: large-scale direct sequence comparison between patients and controls. We believe this approach can be scaled up to allow sequence comparison in the whole-genome coding regions among large sets of cases and controls at a reasonable cost in the near future.


Subject(s)
Autistic Disorder/genetics , Base Pair Mismatch/genetics , Chromosomes, Human, Pair 2/genetics , Genetic Predisposition to Disease/genetics , Genetic Testing/methods , Cluster Analysis , Exons/genetics , Humans , Mutation/genetics
5.
Genome Res ; 15(2): 269-75, 2005 Feb.
Article in English | MEDLINE | ID: mdl-15687290

ABSTRACT

Large-scale genetic studies are highly dependent on efficient and scalable multiplex SNP assays. In this study, we report the development of Molecular Inversion Probe technology with four-color, single array detection, applied to large-scale genotyping of up to 12,000 SNPs per reaction. While generating 38,429 SNP assays using this technology in a population of 30 trios from the Centre d'Etude Polymorphisme Humain family panel as part of the International HapMap project, we established SNP conversion rates of approximately 90% with concordance rates >99.6% and completeness levels >98% for assays multiplexed up to 12,000plex levels. Furthermore, these individual metrics can be "traded off" and, by sacrificing a small fraction of the conversion rate, the accuracy can be increased to very high levels. No loss of performance is seen when scaling from 6,000plex to 12,000plex assays, strongly validating the ability of the technology to suppress cross-reactivity at high multiplex levels. The results of this study demonstrate the suitability of this technology for comprehensive association studies that use targeted SNPs in indirect linkage disequilibrium studies or that directly screen for causative mutations.


Subject(s)
Chromosome Inversion/genetics , Molecular Probe Techniques/trends , Polymorphism, Single Nucleotide/genetics , Chromosome Inversion/statistics & numerical data , Cluster Analysis , DNA Probes/genetics , Gene Expression Profiling , Genome, Human , Genotype , Humans , Molecular Probe Techniques/standards , Molecular Probe Techniques/statistics & numerical data , Molecular Probes/genetics , Research Design
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