Dataset Information

The Affymetrix DMET Plus platform reveals unique distribution of ADME-related variants in ethnic Arabs.

ABSTRACT: The Affymetrix Drug Metabolizing Enzymes and Transporters (DMET) Plus Premier Pack has been designed to genotype 1936 gene variants thought to be essential for screening patients in personalized drug therapy. These variants include the cytochrome P450s (CYP450s), the key metabolizing enzymes, many other enzymes involved in phase I and phase II pharmacokinetic reactions, and signaling mediators associated with variability in clinical response to numerous drugs not only among individuals, but also between ethnic populations.We genotyped 600 Saudi individuals for 1936 variants on the DMET platform to evaluate their clinical potential in personalized medicine in ethnic Arabs.Approximately 49% each of the 437 CYP450 variants, 56% of the 581 transporters, 56% of 419 transferases, 48% of the 104 dehydrogenases, and 58% of the remaining 390 variants were detected. Several variants, such as rs3740071, rs6193, rs258751, rs6199, rs11568421, and rs8187797, exhibited significantly either higher or lower minor allele frequencies (MAFs) than those in other ethnic groups.The present study revealed some unique distribution trends for several variants in Arabs, which displayed partly inverse allelic prevalence compared to other ethnic populations. The results point therefore to the need to verify and ascertain the prevalence of a variant as a prerequisite for engaging it in clinical routine screening in personalized medicine in any given population.

SUBMITTER: Wakil SM

PROVIDER: S-EPMC4353852 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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The Affymetrix DMET Plus platform reveals unique distribution of ADME-related variants in ethnic Arabs.

Wakil Salma M SM Nguyen Cao C Muiya Nzioka P NP Andres Editha E Lykowska-Tarnowska Agnieszka A Baz Batoul B Tahir Asma I AI Meyer Brian F BF Morahan Grant G Dzimiri Nduna N

Disease markers 20150222

<h4>Background</h4>The Affymetrix Drug Metabolizing Enzymes and Transporters (DMET) Plus Premier Pack has been designed to genotype 1936 gene variants thought to be essential for screening patients in personalized drug therapy. These variants include the cytochrome P450s (CYP450s), the key metabolizing enzymes, many other enzymes involved in phase I and phase II pharmacokinetic reactions, and signaling mediators associated with variability in clinical response to numerous drugs not only among in ...[more]

PMID: 25802476

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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/

Project description:Genome-wide genotyping of a cohort using pools rather than individual samples has long been proposed as a cost-saving alternative for performing genome-wide association (GWA) studies. However, successful disease gene mapping using pooled genotyping has thus far been limited to detecting common variants with large effect sizes, which tend not to exist for many complex common diseases or traits. Therefore, for DNA pooling to be a viable strategy for conducting GWA studies, it is important to determine whether commonly used genome-wide SNP array platforms such as the Affymetrix 6.0 array can reliably detect common variants of small effect sizes using pooled DNA. Taking obesity and age at menarche as examples of human complex traits, we assessed the feasibility of genome-wide genotyping of pooled DNA as a single-stage design for phenotype association. By individually genotyping the top associations identified by pooling, we obtained a 14- to 16-fold enrichment of SNPs nominally associated with the phenotype, but we likely missed the top true associations. In addition, we assessed whether genotyping pooled DNA can serve as an inexpensive screen as the second stage of a multi-stage design with a large number of samples by comparing the most cost-effective 3-stage designs with 80% power to detect common variants with genotypic relative risk of 1.1, with and without pooling. Given the current state of the specific technology we employed and the associated genotyping costs, we showed through simulation that a design involving pooling would be 1.07 times more expensive than a design without pooling. Thus, while a significant amount of information exists within the data from pooled DNA, our analysis does not support genotyping pooled DNA as a means to efficiently identify common variants contributing small effects to phenotypes of interest. While our conclusions were based on the specific technology and study design we employed, the approach presented here will be useful for evaluating the utility of other or future genome-wide genotyping platforms in pooled DNA studies.

Dataset Information

The Affymetrix DMET Plus platform reveals unique distribution of ADME-related variants in ethnic Arabs.

Publications

The Affymetrix DMET Plus platform reveals unique distribution of ADME-related variants in ethnic Arabs.

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