Dataset Information

Concordance of DMET plus genotyping results with those of orthogonal genotyping methods.

ABSTRACT: There are several hurdles to the clinical implementation of pharmacogenetics. One approach is to employ pre-prescription genotyping, involving interrogation of multiple pharmacogenetic variants using a high-throughput platform. We compared the performance of the Drug Metabolizing Enzymes and Transporters (DMET) Plus array (1,931 variants in 225 genes) with that of orthogonal genotyping methods in 220 pediatric patients. A total of 1,692 variants had call rates >98% and were in Hardy-Weinberg equilibrium. Of these, 259 were genotyped by at least one independent method, and a total of 19,942 single-nucleotide polymorphism (SNP)-patient sample pairs were evaluated. The concordance rate was 99.9%, with only 28 genotype discordances observed. For the genes deemed most likely to be clinically relevant (TPMT, CYP2D6, CYP2C19, CYP2C9, VKORC1, DPYD, UGT1A1, and SLCO1B1), a total of 3,799 SNP-patient sample pairs were evaluable and had a concordance rate of 99.96%. We conclude that the DMET Plus array performs well with primary patient samples, with the results in good concordance with those of several lower-throughput genotyping methods.

SUBMITTER: Fernandez CA

PROVIDER: S-EPMC3516299 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature

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Concordance of DMET plus genotyping results with those of orthogonal genotyping methods.

Fernandez C A CA Smith C C Yang W W Lorier R R Crews K R KR Kornegay N N Hicks J K JK Stewart C F CF Kawedia J D JD Ramsey L B LB Liu C C Evans W E WE Relling M V MV Broeckel U U

Clinical pharmacology and therapeutics 20120808 3

There are several hurdles to the clinical implementation of pharmacogenetics. One approach is to employ pre-prescription genotyping, involving interrogation of multiple pharmacogenetic variants using a high-throughput platform. We compared the performance of the Drug Metabolizing Enzymes and Transporters (DMET) Plus array (1,931 variants in 225 genes) with that of orthogonal genotyping methods in 220 pediatric patients. A total of 1,692 variants had call rates >98% and were in Hardy-Weinberg equ ...[more]

PMID: 22871999

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Project description:BACKGROUND: Clinical Bioinformatics is currently growing and is based on the integration of clinical and omics data aiming at the development of personalized medicine. Thus the introduction of novel technologies able to investigate the relationship among clinical states and biological machineries may help the development of this field. For instance the Affymetrix DMET platform (drug metabolism enzymes and transporters) is able to study the relationship among the variation of the genome of patients and drug metabolism, detecting SNPs (Single Nucleotide Polymorphism) on genes related to drug metabolism. This may allow for instance to find genetic variants in patients which present different drug responses, in pharmacogenomics and clinical studies. Despite this, there is currently a lack in the development of open-source algorithms and tools for the analysis of DMET data. Existing software tools for DMET data generally allow only the preprocessing of binary data (e.g. the DMET-Console provided by Affymetrix) and simple data analysis operations, but do not allow to test the association of the presence of SNPs with the response to drugs. RESULTS: We developed DMET-Analyzer a tool for the automatic association analysis among the variation of the patient genomes and the clinical conditions of patients, i.e. the different response to drugs. The proposed system allows: (i) to automatize the workflow of analysis of DMET-SNP data avoiding the use of multiple tools; (ii) the automatic annotation of DMET-SNP data and the search in existing databases of SNPs (e.g. dbSNP), (iii) the association of SNP with pathway through the search in PharmaGKB, a major knowledge base for pharmacogenomic studies. DMET-Analyzer has a simple graphical user interface that allows users (doctors/biologists) to upload and analyse DMET files produced by Affymetrix DMET-Console in an interactive way. The effectiveness and easy use of DMET Analyzer is demonstrated through different case studies regarding the analysis of clinical datasets produced in the University Hospital of Catanzaro, Italy. CONCLUSION: DMET Analyzer is a novel tool able to automatically analyse data produced by the DMET-platform in case-control association studies. Using such tool user may avoid wasting time in the manual execution of multiple statistical tests avoiding possible errors and reducing the amount of time needed for a whole experiment. Moreover annotations and the direct link to external databases may increase the biological knowledge extracted. The system is freely available for academic purposes at: https://sourceforge.net/projects/dmetanalyzer/files/

Dataset Information

Concordance of DMET plus genotyping results with those of orthogonal genotyping methods.

Publications

Concordance of DMET plus genotyping results with those of orthogonal genotyping methods.

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