Dataset Information

Comprehensive analysis of important pharmacogenes in Koreans using the DMET™ platform.

ABSTRACT: Genetic polymorphisms of enzymes and transporters associated with the absorption, distribution, metabolism, and elimination (ADME) of drugs are one of the major factors that contribute to interindividual variations in drug response. In the present study, we aimed to elucidate the pharmacogenetic profiles of the Korean population using the Affymetrix Drug Metabolizing Enzyme and Transporters (DMET™) platform. A total of 1,012 whole blood samples collected from Korean subjects were genotyped using the DMET™ plus microarray. In total, 1,785 single nucleotide polymorphism (SNP) markers for 231 ADME genes were identified. The genotype and phenotype of 13 clinically important ADME genes implemented in the Clinical Pharmacogenetics Implementation Consortium guidelines were compared among different ethnic groups. Overall, the genotype frequencies of the Korean population were similar to those of the East Asian population. Several genes, notably CYP2C19 and VKORC1, showed marked differences in Koreans compared to Europeans (EURs) or Africans (AFRs). The percentage of CYP2C19 poor metabolizers was 15% in Koreans and less than 3% in EURs or AFRs. The frequencies of causative SNPs of the VKORC1 gene for the low warfarin dose phenotype were 90%, 60%, and 10% in Koreans, EURs and AFRs, respectively. Our findings can be utilized for optimal pharmacotherapy in Korean patients.

SUBMITTER: Kim B

PROVIDER: S-EPMC8492395 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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Comprehensive analysis of important pharmacogenes in Koreans using the DMET™ platform.

Kim Byungwook B Yoon Deok Yong DY Lee SeungHwan S Jang In-Jin IJ Yu Kyung-Sang KS Cho Joo-Youn JY Oh Jaeseong J

Translational and clinical pharmacology 20210902 3

Genetic polymorphisms of enzymes and transporters associated with the absorption, distribution, metabolism, and elimination (ADME) of drugs are one of the major factors that contribute to interindividual variations in drug response. In the present study, we aimed to elucidate the pharmacogenetic profiles of the Korean population using the Affymetrix Drug Metabolizing Enzyme and Transporters (DMET™) platform. A total of 1,012 whole blood samples collected from Korean subjects were genotyped using ...[more]

PMID: 34621706

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Project description:BackgroundClinical 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.ResultsWe 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.ConclusionDMET 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/

Project description:ObjectivesReliable identification of population-specific variants is important for building the single nucleotide polymorphism (SNP) profile. In this study, genomic variation using allele frequency differences of pharmacologically important genes for Gujarati Indians in Houston (GIH) and Indian Telugu in the U.K. (ITU) from the 1000 Genomes Project vis-à-vis global population data was studied to understand its role in drug response.MethodsJoint genotyping approach was used to derive variants of GIH and ITU independently. SNPs of both these populations with significant allele frequency variation (minor allele frequency ≥ 0.05) with super-populations from the 1000 Genomes Project and gnomAD based on Chi-square distribution with p-value of ≤ 0.05 and Bonferroni's multiple adjustment tests were identified. Population stratification and fixation index analysis was carried out to understand genetic differentiation. Functional annotation of variants was carried out using SnpEff, VEP and CADD score.ResultsPopulation stratification of VIP genes revealed four clusters viz., single cluster of GIH and ITU, one cluster each of East Asian, European, African populations and Admixed American was found to be admixed. A total of 13 SNPs belonging to ten pharmacogenes were identified to have significant allele frequency variation in both GIH and ITU populations as compared to one or more super-populations. These SNPs belong to VKORC1 (rs17708472, rs2359612, rs8050894) involved in Vitamin K cycle, cytochrome P450 isoforms CYP2C9 (rs1057910), CYP2B6 (rs3211371), CYP2A2 (rs4646425) and CYP2A4 (rs4646440); ATP-binding cassette (ABC) transporter ABCB1 (rs12720067), DPYD1 (rs12119882, rs56160474) involved in pyrimidine metabolism, methyltransferase COMT (rs9332377) and transcriptional factor NR1I2 (rs6785049). SNPs rs1544410 (VDR), rs2725264 (ABCG2), rs5215 and rs5219 (KCNJ11) share high fixation index (≥ 0.5) with either EAS/AFR populations. Missense variants rs1057910 (CYP2C9), rs1801028 (DRD2) and rs1138272 (GSTP1), rs116855232 (NUDT15); intronic variants rs1131341 (NQO1) and rs115349832 (DPYD) are identified to be 'deleterious'.ConclusionsAnalysis of SNPs pertaining to pharmacogenes in GIH and ITU populations using population structure, fixation index and allele frequency variation provides a premise for understanding the role of genetic diversity in drug response in Asian Indians.

Dataset Information

Comprehensive analysis of important pharmacogenes in Koreans using the DMET™ platform.

Publications

Comprehensive analysis of important pharmacogenes in Koreans using the DMET™ platform.

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