Dataset Information

Analysis of Genetic Variation in CYP450 Genes for Clinical Implementation.

ABSTRACT:

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.

SUBMITTER: Goh LL

PROVIDER: S-EPMC5207784 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Publications

Analysis of Genetic Variation in CYP450 Genes for Clinical Implementation.

Goh Liuh Ling LL Lim Chia Wei CW Sim Wey Cheng WC Toh Li Xian LX Leong Khai Pang KP

PloS one 20170103 1

<h4>Background</h4>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.<h4>Methods</h4>We designed a 32-SNP panel for PGx testing in clinical laboratories. The variants wer ...[more]

PMID: 28046094

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Project description:BACKGROUND:The number of studies on the association between clock genes' polymorphisms and cancer susceptibility has increased over the last years but the results are often conflicting and no comprehensive overview and quantitative summary of the evidence in this field is available. RESULTS:Literature search identified 27 eligible studies comprising 96756 subjects (cases: 38231) and investigating 687 polymorphisms involving 14 clock genes. Overall, 1025 primary and subgroup meta-analyses on 366 gene variants were performed. Study distribution by tumor was as follows: breast cancer (n=15), prostate cancer (n=3), pancreatic cancer (n=2), non-Hodgkin's lymphoma (n=2), glioma (n=1), chronic lymphocytic leukemia (n=1), colorectal cancer (n=1), non-small cell lung cancer (n=1) and ovarian cancer (n=1).We identified 10 single nucleotide polymorphisms (SNPs) significantly associated with cancer risk: NPAS2 rs10165970 (mixed and breast cancer shiftworkers), rs895520 (mixed), rs17024869 (breast) and rs7581886 (breast); CLOCK rs3749474 (breast) and rs11943456 (breast); RORA rs7164773 (breast and breast cancer postmenopausal), rs10519097 (breast); RORB rs7867494 (breast cancer postmenopausal), PER3 rs1012477 (breast cancer subgroups) and assessed the level of quality evidence to be intermediate. We also identified polymorphisms with lower quality statistically significant associations (n=30). CONCLUSIONS:Our work supports the hypothesis that genetic variation of clock genes might affect cancer risk. These findings also highlight the need for more efforts in this research field in order to fully establish the contribution of clock gene variants to the risk of developing cancer. METHODS:We conducted a systematic review and meta-analysis of the evidence on the association between clock genes' germline variants and the risk of developing cancer. To assess result credibility, summary evidence was graded according to the Venice criteria and false positive report probability (FPRP) was calculated to further validate result noteworthiness. Subgroup meta-analysis was also performed based on participant features and tumor type. The breast cancer subgroup was further stratified by work conditions, estrogen receptor/progesterone receptor status and menopausal status, conditions associated with the risk of breast cancer in different studies.

Project description:BackgroundLonicera japonica is an important medicinal plant that has been widely used in traditional Chinese medicine for thousands of years. The pharmacological activities of L. japonica are mainly due to its rich natural active ingredients, most of which are secondary metabolites. CYP450s are a large, complex, and widespread superfamily of proteins that participate in many endogenous and exogenous metabolic reactions, especially secondary metabolism. Here, we identified CYP450s in L. japonica transcriptome and analyzed CYP450s that may be involved in chlorogenic acid (CGA) biosynthesis.MethodsThe recent availability of L. japonica transcriptome provided opportunity to identify CYP450s in this herb. BLAST based method and HMM based method were used to identify CYP450s in L. japonica transcriptome. Then, phylogenetic analysis, conserved motifs analysis, GO annotation, and KEGG annotation analyses were conducted to characterize the identified CYP450s. qRT-PCR was used to explore expression patterns of five CGA biosynthesis related CYP450s.ResultsIn this study, 151 putative CYP450s with complete cytochrome P450 domain, which belonged to 10 clans, 45 families and 76 subfamilies, were identified in L. japonica transcriptome. Phylogenetic analysis classified these CYP450s into two major branches, A-type (47%) and non-A type (53%). Both types of CYP450s had conserved motifs in L. japonica. The differences of typical motif sequences between A-type and non-A type CYP450s in L. japonica were similar with other plants. GO classification indicated that non-A type CYP450s participated in more molecular functions and biological processes than A-type. KEGG pathway annotation totally assigned 47 CYP450s to 25 KEGG pathways. From these data, we cloned two LjC3Hs (CYP98A subfamily) and three LjC4Hs (CYP73A subfamily) that may be involved in biosynthesis of CGA, the major ingredient for pharmacological activities of L. japonica. qRT-PCR results indicated that two LjC3Hs exhibited oppositing expression patterns during the flower development and LjC3H2 exhibited a similar expression pattern with CGA concentration measured by HPLC. The expression patterns of three LjC4Hs were quite different and the expression pattern of LjC4H3 was quite similar with that of LjC3H1.DiscussionOur results provide a comprehensive identification and characterization of CYP450s in L. japonica. Five CGA biosynthesis related CYP450s were cloned and their expression patterns were explored. The different expression patterns of two LjC3Hs and three LjC4Hs may be due to functional divergence of both substrate and catalytic specificity during plant evolution. The co-expression pattern of LjC3H1 and LjC4H3 strongly suggested that they were under coordinated regulation by the same transcription factors due to same cis elements in their promoters. In conclusion, this study provides insight into CYP450s and will effectively facilitate the research of biosynthesis of CGA in L. japonica.

Dataset Information

Analysis of Genetic Variation in CYP450 Genes for Clinical Implementation.

Background

Methods

Results

Conclusion

Publications

Analysis of Genetic Variation in CYP450 Genes for Clinical Implementation.

Similar Datasets

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