Challenges in CYP2D6 Phenotype Assignment from Genotype Data: A Critical Assessment and Call for Standardization

Author(s): J. Kevin Hicks, Jesse J. Swen, Andrea Gaedigk.

Journal Name: Current Drug Metabolism

Volume 15 , Issue 2 , 2014

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The cytochrome P450 2D6 (CYP2D6) enzyme contributes to the metabolism and/or bioactivation of approximately 25% of clinically used drugs. The CYP2D6 gene locus is highly polymorphic and complex, and variants within this gene locus affect CYP2D6 enzymatic function resulting in a wide range of metabolic activity from little to no activity to ultrarapid metabolism. For many of the drugs metabolized by CYP2D6, the variation in metabolic activity is one of the most important factors responsible for interindividual drug response. Therefore, determining an individual’s CYP2D6 phenotype, or metabolic status, will help identify individuals that may benefit from a change in drug or drug dosage. Genotype analysis has become the method of choice to predict a person's metabolic status. Numerous reference laboratories now offer CYP2D6 genotyping; however, there can be substantial differences in the number of genetic variants interrogated as well as test interpretation. Furthermore, there is no standardized process of how a CYP2D6 genotype result is translated into a phenotype assignment. This review summarizes the complexity of CYP2D6 genotyping and highlights the major challenges for phenotype classification. We call for the implementation of a universally accepted system for CYP2D6 phenotype assignment to promote consistency of test interpretation among reference laboratories and medical institutions. We propose a system that utilizes the CYP2D6 activity score system to place individuals into a continuum of activity scores - rather than using the traditional poor, intermediate, extensive and ultra-rapid metabolizer categorizations - and directly translating activity scores into clinically actionable recommendations.

Keywords: Activity score, CYP2D6, dextromethorphan, genotype, metabolizer status, personalized medicine, pharmacogenetics, phenotype, phenotype prediction.

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Article Details

Year: 2014
Page: [218 - 232]
Pages: 15
DOI: 10.2174/1389200215666140202215316
Price: $58

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