Published online before print March 26, 2009

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Copyright © 2009 American Society for Investigative Pathology
Journal of Molecular Diagnostics, doi:10.2353/jmoldx.2009.080123

Accepted for publication December 22, 2008.

Article

Validation of Clinical Testing for Warfarin Sensitivity. Comparison of CYP2C9-VKORC1 Genotyping Assays and Warfarin-Dosing Algorithms

Michael R. Langley^*, Jessica K. Booker^*, James P. Evans, Howard L. McLeod, and Karen E. Weck^*@

From the Departments of Pathology and Laboratory Medicine,* and Genetics and Medicine, and the Institute for Pharmacogenomics and Individualized Therapy, University of North Carolina, Chapel Hill, North Carolina

^@ To whom correspondence should be addressed. E-mail: kweck{at}unc.edu.

	Abstract

Responses to warfarin (Coumadin) anticoagulation therapy are affected by genetic variability in both the CYP2C9 and VKORC1 genes. Validation of pharmacogenetic testing for warfarin responses includes demonstration of analytical validity of testing platforms and of the clinical validity of testing. We compared four platforms for determining the relevant single nucleotide polymorphisms (SNPs) in both CYP2C9 and VKORC1 that are associated with warfarin sensitivity (Third Wave Invader Plus, ParagonDx/Cepheid Smart Cycler, Idaho Technology LightCycler, and AutoGenomics Infiniti). Each method was examined for accuracy, cost, and turnaround time. All genotyping methods demonstrated greater than 95% accuracy for identifying the relevant SNPs (CYP2C9 *2 and *3; VKORC1 -1639 or 1173). The ParagonDx and Idaho Technology assays had the shortest turnaround and hands-on times. The Third Wave assay was readily scalable to higher test volumes but had the longest hands-on time. The AutoGenomics assay interrogated the largest number of SNPs but had the longest turnaround time. Four published warfarin-dosing algorithms (Washington University, UCSF, Louisville, and Newcastle) were compared for accuracy for predicting warfarin dose in a retrospective analysis of a local patient population on long-term, stable warfarin therapy. The predicted doses from both the Washington University and UCSF algorithms demonstrated the best correlation with actual warfarin doses.