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.