Comprehensive analysis of important pharmacogenes in Koreans using the DMET™ platform.
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ABSTRACT:
SUBMITTER: Kim B
PROVIDER: S-EPMC8492395 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:In the era of personalized medicine, high-throughput technologies have allowed the investigation of genetic variations underlying the inter-individual variability in drug pharmacokinetics/pharmacodynamics. Several studies have recently moved from a candidate gene-based pharmacogenetic approach to genome-wide pharmacogenomic analyses to identify biomarkers for selection of patient-tailored therapies. In this aim, the identification of genetic variants affecting the individual drug metabolism is relevant for the definition of more active and less toxic treatments. This review focuses on the potentiality, reliability and limitations of the DMET™ (Drug Metabolism Enzymes and Transporters) Plus as pharmacogenomic drug metabolism multi-gene panel platform for selecting biomarkers in the final aim to optimize drugs use and characterize the individual genetic background.
| S-EPMC5288240 | biostudies-literature
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/
| S-EPMC3496574 | biostudies-literature
Project description:For predicting phenotypes and executing precision medicine, combination analysis of single nucleotide variants (SNVs) genotyping with copy number variations (CNVs) is required. The aim of this study was to discover SNVs or common copy CNVs and examine the combined frequencies of SNVs and CNVs in pharmacogenes using the Korean genome and epidemiology study (KoGES), a consortium project. The genotypes (N = 72,299) and CNV data (N = 1000) were provided by the Korean National Institute of Health, Korea Centers for Disease Control and Prevention. The allele frequencies of SNVs, CNVs, and combined SNVs with CNVs were calculated and haplotype analysis was performed. CYP2D6 rs1065852 (c.100C>T, p.P34S) was the most common variant allele (48.23%). A total of 8454 haplotype blocks in 18 pharmacogenes were estimated. DMD ranked the highest in frequency for gene gain (64.52%), while TPMT ranked the highest in frequency for gene loss (51.80%). Copy number gain of CYP4F2 was observed in 22 subjects; 13 of those subjects were carriers with CYP4F2*3 gain. In the case of TPMT, approximately one-half of the participants (N = 308) had loss of the TPMT*1*1 diplotype. The frequencies of SNVs and CNVs in pharmacogenes were determined using the Korean cohort-based genome-wide association study.
| S-EPMC7825650 | biostudies-literature
Project description:We have used a novel affinity-based proteomics technology to examine the protein signature of small secreted extracellular vesicles called exosomes. The technology uses a new class of protein binding reagents called SOMAmers® (slow off-rate modified aptamers) and allows the simultaneous precise measurement of over 1000 proteins. Exosomes were highly purified from the Du145 prostate cancer cell line, by pooling selected fractions from a continuous sucrose gradient (within the density range of 1.1 to 1.2 g/ml), and examined under standard conditions or with additional detergent treatment by the SOMAscan™ array (version 3.0). Lysates of Du145 cells were also prepared, and the profiles were compared. Housekeeping proteins such as cyclophilin-A, LDH, and Hsp70 were present in exosomes, and we identified almost 100 proteins that were enriched in exosomes relative to cells. These included proteins of known association with cancer exosomes such as MFG-E8, integrins, and MET, and also those less widely reported as exosomally associated, such as ROR1 and ITIH4. Several proteins with no previously known exosomal association were confirmed as exosomally expressed in experiments using individual SOMAmer® reagents or antibodies in micro-plate assays. Western blotting confirmed the SOMAscan™-identified enrichment of exosomal NOTCH-3, L1CAM, RAC1, and ADAM9. In conclusion, we describe here over 300 proteins of hitherto unknown association with prostate cancer exosomes and suggest that the SOMAmer®-based assay technology is an effective proteomics platform for exosome-associated biomarker discovery in diverse clinical settings.
| S-EPMC3977183 | biostudies-literature
Project description:Pharmacogenetic (PGx) testing has not been well adopted in current clinical practice. The phenotypic distribution of clinically relevant pharmacogenes remains to be fully characterized in large population cohorts. In addition, no study has explored actionable PGx alleles in the East Asian population at a large scale. This study comprehensively analyzed 14 actionable pharmacogene diplotypes and phenotypes in 172,854 Taiwanese Han individuals by using their genotype data. Furthermore, we analyzed data from electronic medical records to investigate the effect of the actionable phenotypes on the individuals. The PGx phenotype frequencies were comparable between our cohort and the East Asian population. Overall, 99.9% of the individuals harbored at least one actionable PGx phenotype, and 29% of them have been prescribed a drug to which they may exhibit an atypical response. Our findings can facilitate the clinical application of PGx testing and the optimization of treatment and dosage individually.
| S-EPMC9452738 | biostudies-literature
Project description:The anticancer agent docetaxel shows significant inter-individual variation in its pharmacokinetic and toxicity profile. Thalidomide is an active anticancer agent and also shows wide pharmacological variation. Past pharmacogenetic research has not explained this variation. Patients with prostate cancer enrolled in a randomized phase II trial using docetaxel and thalidomide versus docetaxel alone were genotyped using the Affymetrix DMET 1.0 platform, which tests for 1256 genetic variations in 170 drug disposition genes. Genetic polymorphisms were analyzed for associations with clinical response and toxicity. In all, 10 single-nucleotide polymorphisms (SNPs) in three genes were potentially associated with response to therapy: peroxisome proliferator-activated receptor-delta (PPAR-delta), sulfotransferase family, cytosolic, 1C, member 2 (SULT1C2) and carbohydrate (chondroitin 6) sulfotransferase 3 (CHST3). In addition, 11 SNPs in eight genes were associated with toxicities to treatment: spastic paraplegia 7 (pure and complicated autosomal recessive) (SPG7), CHST3, cytochrome P450, family 2, subfamily D, polypeptide 6 (CYP2D6), N-acetyltransferase 2 (arylamine N-acetyltransferase) (NAT2), ATP-binding cassette, sub-family C (CFTR/MRP), member 6 (ABCC6), ATPase, Cu++ transporting, alpha polypeptide (ATP7A), cytochrome P450, family 4, subfamily B, polypeptide 1 (CYP4B1) and solute carrier family 10 (sodium/bile acid cotransporter family), member 2 (SLC10A2). Genotyping results between drug metabolizing enzymes and transporters (DMET) and direct sequencing showed >96% of concordance. These findings highlight the role that non-CYP450 metabolizing enzymes and transporters may have in the pharmacology of docetaxel and thalidomide.
| S-EPMC6631360 | biostudies-literature
Project description:Objectives Reliable 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. Methods Joint 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. Results Population 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’. Conclusions Analysis 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.
| S-EPMC8590392 | biostudies-literature
Project description:BackgroundThe 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.Materials and methodsWe genotyped 600 Saudi individuals for 1936 variants on the DMET platform to evaluate their clinical potential in personalized medicine in ethnic Arabs.ResultsApproximately 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.DiscussionThe 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.
| S-EPMC4353852 | biostudies-literature
Project description:The implementation of pharmacogenetics (PGx) is a main milestones of precision medicine nowadays in order to achieve safer and more effective therapies. Nevertheless, the implementation of PGx diagnostics is extremely slow and unequal worldwide, in part due to a lack of ethnic PGx information. We analysed genetic data from 3006 Spanish individuals obtained by different high-throughput (HT) techniques. Allele frequencies were determined in our population for the main 21 actionable PGx genes associated with therapeutical changes. We found that 98% of the Spanish population harbours at least one allele associated with a therapeutical change and, thus, there would be a need for a therapeutical change in a mean of 3.31 of the 64 associated drugs. We also identified 326 putative deleterious variants that were not previously related with PGx in 18 out of the 21 main PGx genes evaluated and a total of 7122 putative deleterious variants for the 1045 PGx genes described. Additionally, we performed a comparison of the main HT diagnostic techniques, revealing that after whole genome sequencing, genotyping with the PGx HT array is the most suitable solution for PGx diagnostics. Finally, all this information was integrated in the Collaborative Spanish Variant Server to be available to and updated by the scientific community.
| S-EPMC10140932 | biostudies-literature
Project description:Genomic-guided pharmaceutical prescribing is increasingly recognized as an important clinical application of genetics. Accurate genotyping of pharmacogenomic (PGx) genes can be difficult, owing to their complex genetic architecture involving combinations of single-nucleotide polymorphisms and structural variation. Here, we introduce the Helix PGx database, an open-source star allele, genotype, and resulting metabolic phenotype frequency database for CYP2C9, CYP2C19, CYP2D6, and CYP4F2, based on short-read sequencing of >86,000 unrelated individuals enrolled in the Helix DNA Discovery Project. The database is annotated using a pipeline that is clinically validated against a broad range of alleles and designed to call CYP2D6 structural variants with high (98%) accuracy. We find that CYP2D6 has greater allelic diversity than the other genes, manifest in both a long tail of low-frequency star alleles, as well as a disproportionate fraction (36%) of all novel predicted loss-of-function variants identified. Across genes, we observe that many rare alleles (<0.1% frequency) in the overall cohort have 10 times higher frequency in one or more subgroups with non-European genetic ancestry. Extending these PGx genotypes to predicted metabolic phenotypes, we demonstrate that >90% of the cohort harbors a high-risk variant in one of the four pharmacogenes. Based on the recorded prescriptions for >30,000 individuals in the Healthy Nevada Project, combined with predicted PGx metabolic phenotypes, we anticipate that standard-of-care screening of these 4 pharmacogenes could impact nearly half of the general population.
| S-EPMC8453755 | biostudies-literature