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Analysis of Genetic Variation in CYP450 Genes for Clinical Implementation

BACKGROUND: Genetic determinants of drug response remain stable throughout life and offer great promise to patient-tailored drug therapy. The adoption of pharmacogenetic (PGx) testing in patient care requires accurate, cost effective and rapid genotyping with clear guidance on the use of the results...

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Autores principales: Goh, Liuh Ling, Lim, Chia Wei, Sim, Wey Cheng, Toh, Li Xian, Leong, Khai Pang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5207784/
https://www.ncbi.nlm.nih.gov/pubmed/28046094
http://dx.doi.org/10.1371/journal.pone.0169233
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author Goh, Liuh Ling
Lim, Chia Wei
Sim, Wey Cheng
Toh, Li Xian
Leong, Khai Pang
author_facet Goh, Liuh Ling
Lim, Chia Wei
Sim, Wey Cheng
Toh, Li Xian
Leong, Khai Pang
author_sort Goh, Liuh Ling
collection PubMed
description BACKGROUND: Genetic determinants of drug response remain stable throughout life and offer great promise to patient-tailored drug therapy. The adoption of pharmacogenetic (PGx) testing in patient care requires accurate, cost effective and rapid genotyping with clear guidance on the use of the results. Hence, we evaluated a 32 SNPs panel for implementing PGx testing in clinical laboratories. METHODS: We designed a 32-SNP panel for PGx testing in clinical laboratories. The variants were selected using the clinical annotations of the Pharmacogenomics Knowledgebase (PharmGKB) and include polymorphisms of CYP2C9, CYP2C19, CYP2D6, CYP3A5 and VKORC1 genes. The CYP2D6 gene allele quantification was determined simultaneously with TaqMan copy number assays targeting intron 2 and exon 9 regions. The genotyping results showed high call rate accuracy according to concordance with genotypes identified by independent analyses on Sequenome massarray and droplet digital PCR. Furthermore, 506 genomic samples across three major ethnic groups of Singapore (Malay, Indian and Chinese) were analysed on our workflow. RESULTS: We found that 98% of our study subjects carry one or more CPIC actionable variants. The major alleles detected include CYP2C9*3, CYP2C19*2, CYP2D6*10, CYP2D6*36, CYP2D6*41, CYP3A5*3 and VKORC1*2. These translate into a high percentage of intermediate (IM) and poor metabolizer (PM) phenotypes for these genes in our population. CONCLUSION: Genotyping may be useful to identify patients who are prone to drug toxicity with standard doses of drug therapy in our population. The simplicity and robustness of this PGx panel is highly suitable for use in a clinical laboratory.
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spelling pubmed-52077842017-01-19 Analysis of Genetic Variation in CYP450 Genes for Clinical Implementation Goh, Liuh Ling Lim, Chia Wei Sim, Wey Cheng Toh, Li Xian Leong, Khai Pang PLoS One Research Article BACKGROUND: Genetic determinants of drug response remain stable throughout life and offer great promise to patient-tailored drug therapy. The adoption of pharmacogenetic (PGx) testing in patient care requires accurate, cost effective and rapid genotyping with clear guidance on the use of the results. Hence, we evaluated a 32 SNPs panel for implementing PGx testing in clinical laboratories. METHODS: We designed a 32-SNP panel for PGx testing in clinical laboratories. The variants were selected using the clinical annotations of the Pharmacogenomics Knowledgebase (PharmGKB) and include polymorphisms of CYP2C9, CYP2C19, CYP2D6, CYP3A5 and VKORC1 genes. The CYP2D6 gene allele quantification was determined simultaneously with TaqMan copy number assays targeting intron 2 and exon 9 regions. The genotyping results showed high call rate accuracy according to concordance with genotypes identified by independent analyses on Sequenome massarray and droplet digital PCR. Furthermore, 506 genomic samples across three major ethnic groups of Singapore (Malay, Indian and Chinese) were analysed on our workflow. RESULTS: We found that 98% of our study subjects carry one or more CPIC actionable variants. The major alleles detected include CYP2C9*3, CYP2C19*2, CYP2D6*10, CYP2D6*36, CYP2D6*41, CYP3A5*3 and VKORC1*2. These translate into a high percentage of intermediate (IM) and poor metabolizer (PM) phenotypes for these genes in our population. CONCLUSION: Genotyping may be useful to identify patients who are prone to drug toxicity with standard doses of drug therapy in our population. The simplicity and robustness of this PGx panel is highly suitable for use in a clinical laboratory. Public Library of Science 2017-01-03 /pmc/articles/PMC5207784/ /pubmed/28046094 http://dx.doi.org/10.1371/journal.pone.0169233 Text en © 2017 Goh et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Goh, Liuh Ling
Lim, Chia Wei
Sim, Wey Cheng
Toh, Li Xian
Leong, Khai Pang
Analysis of Genetic Variation in CYP450 Genes for Clinical Implementation
title Analysis of Genetic Variation in CYP450 Genes for Clinical Implementation
title_full Analysis of Genetic Variation in CYP450 Genes for Clinical Implementation
title_fullStr Analysis of Genetic Variation in CYP450 Genes for Clinical Implementation
title_full_unstemmed Analysis of Genetic Variation in CYP450 Genes for Clinical Implementation
title_short Analysis of Genetic Variation in CYP450 Genes for Clinical Implementation
title_sort analysis of genetic variation in cyp450 genes for clinical implementation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5207784/
https://www.ncbi.nlm.nih.gov/pubmed/28046094
http://dx.doi.org/10.1371/journal.pone.0169233
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