PMCID: PMC5292679 DOI: 10.1038/gim.2016.80
PURPOSE: Owing to its highly polymorphic nature and major contribution to the metabolism and bioactivation of numerous clinically used drugs, CYP2D6 is one of the most extensively studied drug-metabolizing enzymes and pharmacogenes. CYP2D6 alleles confer no, decreased, normal, or increased activity and cause a wide range of activity among individuals and between populations. However, there is no standard approach to translate diplotypes into predicted phenotype.
METHODS: We exploited CYP2D6 allele-frequency data that have been compiled for Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines (>60,000 subjects, 173 reports) in order to estimate genotype-predicted phenotype status across major world populations based on activity score (AS) assignments.
RESULTS: Allele frequencies vary considerably across the major ethnic groups predicting poor metabolizer status (AS = 0) between 0.4 and 5.4% across world populations. The prevalence of genotypic intermediate (AS = 0.5) and normal (AS = 1, 1.5, or 2) metabolizers ranges between 0.4 and 11% and between 67 and 90%, respectively. Finally, 1 to 21% of subjects (AS >2) are predicted to have ultrarapid metabolizer status.
CONCLUSIONS: This comprehensive study summarizes allele frequencies, diplotypes, and predicted phenotype across major populations, providing a rich data resource for clinicians and researchers. Challenges of phenotype prediction from genotype data are highlighted and discussed.Genet Med 19 1, 69-76.
Genetics in medicine : official journal of the American College of Medical Genetics
Cytochrome P-450 CYP2D6; Ethnic Groups; Female; Gene Frequency; Genetics, Population; Genotype; Humans; Inactivation, Metabolic; Male; Pharmacogenetics; Phenotype; Polymorphism, Genetic
Gene Frequency; Genetics
Gaedigk A, Sangkuhl K, Whirl-Carrillo M, Klein T, Leeder JS. Prediction of CYP2D6 phenotype from genotype across world populations [published correction appears in Genet Med. 2016 Nov;18(11):1167]. Genet Med. 2017;19(1):69-76. doi:10.1038/gim.2016.80
Copyright© 2017, The Author(s), under exclusive licence to the American College of Medical Genetics and Genomics
Creative Commons Attribution – NonCommercial – NoDerivs (CC BY-NC-ND 4.0)
Publisher's Link: https://www.gimjournal.org/article/S1098-3600(21)01541-0/fulltext