Literature DB >> 27732553

Rapid screening for targeted genetic variants via high-resolution melting curve analysis.

Allison B Chambliss, Molly Resnick, Athena K Petrides, William A Clarke, Mark A Marzinke.   

Abstract

BACKGROUND: Current methods for the detection of single nucleotide polymorphisms (SNPs) associated with aberrant drug-metabolizing enzyme function are hindered by long turnaround times and specialized techniques and instrumentation. In this study, we describe the development and validation of a high-resolution melting (HRM) curve assay for the rapid screening of variant genotypes for targeted genetic polymorphisms in the cytochrome P450 enzymes CYP2C9, CYP2C19, and CYP3A5.
METHODS: Sequence-specific primers were custom-designed to flank nine SNPs within the genetic regions of aforementioned drug metabolizing enzymes. PCR amplification was performed followed by amplicon denaturation by precise temperature ramping in order to distinguish genotypes by melting temperature (Tm). A standardized software algorithm was used to assign amplicons as 'reference' or 'variant' as compared to duplicate reference sequence DNA controls for each SNP.
RESULTS: Intra-assay (n=5) precision of Tms for all SNPs was ≤0.19%, while inter-assay (n=20) precision ranged from 0.04% to 0.21%. When compared to a reference method of Sanger sequencing, the HRM assay produced no false negative results, and overcall frequency ranged from 0% to 26%, depending on the SNP. Furthermore, HRM genotyping displayed accuracy over input DNA concentrations ranging from 10 to 200 ng/μL.
CONCLUSIONS: The presented assay provides a rapid method for the screening for genetic variants in targeted CYP450 regions with a result of 'reference' or 'variant' available within 2 h from receipt of extracted DNA. The method can serve as a screening approach to rapidly identify individuals with variant sequences who should be further investigated by reflexed confirmatory testing for aberrant cytochrome P450 enzymatic activity. Rapid knowledge of variant status may aid in the avoidance of adverse clinical events by allowing for dosing of normal metabolizer patients immediately while identifying the need to wait for confirmatory testing in those patients who are likely to possess pharmacogenetically-relevant variants.

Entities:  

Mesh:

Substances:

Year:  2017        PMID: 27732553      PMCID: PMC5550898          DOI: 10.1515/cclm-2016-0603

Source DB:  PubMed          Journal:  Clin Chem Lab Med        ISSN: 1434-6621            Impact factor:   3.694


  28 in total

1.  CPIC: Clinical Pharmacogenetics Implementation Consortium of the Pharmacogenomics Research Network.

Authors:  M V Relling; T E Klein
Journal:  Clin Pharmacol Ther       Date:  2011-01-26       Impact factor: 6.875

2.  PharmGKB summary: very important pharmacogene information for CYP3A5.

Authors:  Jatinder Lamba; Joan M Hebert; Erin G Schuetz; Teri E Klein; Russ B Altman
Journal:  Pharmacogenet Genomics       Date:  2012-07       Impact factor: 2.089

3.  Allele and genotype frequencies of CYP2B6 and CYP3A5 in the Japanese population.

Authors:  Masahiro Hiratsuka; Yoh Takekuma; Naomi Endo; Kaori Narahara; Samar Ismail Hamdy; Yukinaga Kishikawa; Masaki Matsuura; Yasuyuki Agatsuma; Tomoko Inoue; Michinao Mizugaki
Journal:  Eur J Clin Pharmacol       Date:  2002-08-14       Impact factor: 2.953

Review 4.  High-resolution DNA melting analysis for simple and efficient molecular diagnostics.

Authors:  Gudrun H Reed; Jana O Kent; Carl T Wittwer
Journal:  Pharmacogenomics       Date:  2007-06       Impact factor: 2.533

5.  Diagnostic method validation: High resolution melting (HRM) of small amplicons genotyping for the most common variants in the MTHFR gene.

Authors:  Patricia A Norambuena; Joshua A Copeland; Petra Krenková; Alexandra Stambergová; Milan Macek
Journal:  Clin Biochem       Date:  2009-05-08       Impact factor: 3.281

Review 6.  Pharmacogenomics in the clinic.

Authors:  Mary V Relling; William E Evans
Journal:  Nature       Date:  2015-10-15       Impact factor: 49.962

Review 7.  Preemptive clinical pharmacogenetics implementation: current programs in five US medical centers.

Authors:  Henry M Dunnenberger; Kristine R Crews; James M Hoffman; Kelly E Caudle; Ulrich Broeckel; Scott C Howard; Robert J Hunkler; Teri E Klein; William E Evans; Mary V Relling
Journal:  Annu Rev Pharmacol Toxicol       Date:  2014-10-02       Impact factor: 13.820

8.  Clinical Pharmacogenetics Implementation Consortium (CPIC) Guidelines for CYP3A5 Genotype and Tacrolimus Dosing.

Authors:  K A Birdwell; B Decker; J M Barbarino; J F Peterson; C M Stein; W Sadee; D Wang; A A Vinks; Y He; J J Swen; J S Leeder; Rhn van Schaik; K E Thummel; T E Klein; K E Caudle; I A M MacPhee
Journal:  Clin Pharmacol Ther       Date:  2015-06-03       Impact factor: 6.875

9.  PharmGKB summary: very important pharmacogene information for cytochrome P450, family 2, subfamily C, polypeptide 19.

Authors:  Stuart A Scott; Katrin Sangkuhl; Alan R Shuldiner; Jean-Sébastien Hulot; Caroline F Thorn; Russ B Altman; Teri E Klein
Journal:  Pharmacogenet Genomics       Date:  2012-02       Impact factor: 2.089

Review 10.  Cytochrome p450 and chemical toxicology.

Authors:  F Peter Guengerich
Journal:  Chem Res Toxicol       Date:  2007-12-06       Impact factor: 3.739

View more
  2 in total

1.  Heterozygous Single-Nucleotide Polymorphism Genotypes at Heat Shock Protein 70 Gene Potentially Influence Thermo-Tolerance Among Four Zebu Breeds of Nigeria.

Authors:  Gbolabo Olaitan Onasanya; George Mutani Msalya; Aranganoor Kannan Thiruvenkadan; Chirukandoth Sreekumar; Gopalan Krishnaswamy Tirumurugaan; Adeboye O Fafiolu; Matthew A Adeleke; Abdulmojeed Yakubu; Christian Obiora Ndubuisi Ikeobi; Moses Okpeku
Journal:  Front Genet       Date:  2021-04-12       Impact factor: 4.599

2.  Rapid screening of MMACHC gene mutations by high-resolution melting curve analysis.

Authors:  Chao Wang; Yang Liu; Fengying Cai; Xinjie Zhang; Xiaowei Xu; Yani Li; Qianqian Zou; Jie Zheng; Yuqin Zhang; Wei Guo; Chunquan Cai; Jianbo Shu
Journal:  Mol Genet Genomic Med       Date:  2020-03-21       Impact factor: 2.183

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.