Affiliations 

  • 1 Carney Centre for Pharmacogenomics, Department of Pathology, University of OtagoChristchurch, New Zealand; Faculty of Pharmacy, Universiti Kebangsaan MalaysiaKuala Lumpur, Malaysia
  • 2 Carney Centre for Pharmacogenomics, Department of Pathology, University of Otago Christchurch, New Zealand
  • 3 School of Biological Sciences, The University of Auckland Auckland, New Zealand
  • 4 Auckland UniServices Sequenom Facility, Liggins Institute, The University of Auckland Auckland, New Zealand
  • 5 School of Medical Sciences, The University of Auckland Auckland, New Zealand
Front Pharmacol, 2016;7:1.
PMID: 26858644 DOI: 10.3389/fphar.2016.00001

Abstract

Whole-exome sequencing (WES) has been widely used for analysis of human genetic diseases, but its value for the pharmacogenomic profiling of individuals is not well studied. Initially, we performed an in-depth evaluation of the accuracy of WES variant calling in the pharmacogenes CYP2D6 and CYP2C19 by comparison with MiSeq(®) amplicon sequencing data (n = 36). This analysis revealed that the concordance rate between WES and MiSeq(®) was high, achieving 99.60% for variants that were called without exceeding the truth-sensitivity threshold (99%), defined during variant quality score recalibration (VQSR). Beyond this threshold, the proportion of discordant calls increased markedly. Subsequently, we expanded our findings beyond CYP2D6 and CYP2C19 to include more genes genotyped by the iPLEX(®) ADME PGx Panel in the subset of twelve samples. WES performed well, agreeing with the genotyping panel in approximately 99% of the selected pass-filter variant calls. Overall, our results have demonstrated WES to be a promising approach for pharmacogenomic profiling, with an estimated error rate of lower than 1%. Quality filters, particularly VQSR, are important for reducing the number of false variants. Future studies may benefit from examining the role of WES in the clinical setting for guiding drug therapy.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.