Cytochrome P450 2D6 Phenoconversion Is Common in Patients Being Treated for Depression

Preskorn, Sheldon; Kane, Cecelia P.; Lobello, Kasia; Nichols, Alice I.; Fayyad, Rana; Buckley, Gina; Focht, Kristen; Guico-Pabia, Christine J.

doi:10.4088/jcp.12m07807

Cited by 105 publications

(95 citation statements)

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“…Requirements or recommendations for genetic testing in these cases were rare because genotypes or efficacy associations were less strong than for targeted drugs. Many nongenetic causes of phenotypic variability (e.g., age, sex, concomitant drug use, body weight, renal function, comorbidities, and phenoconversion) 18,19 can explain why genotypes sometimes do not accurately predict drug response. Warfarin and clopidogrel are two examples for which pharmacogenomic biomarkers may not be clinically useful, contrary to previous expectations.…”

Section: Discussionmentioning

confidence: 99%

Guidance for pharmacogenomic biomarker testing in labels of FDA-approved drugs

Vivot

Boutron

Ravaud

et al. 2015

Genetics in Medicine

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Section: Discussionmentioning

confidence: 99%

Guidance for pharmacogenomic biomarker testing in labels of FDA-approved drugs

Vivot

Boutron

Ravaud

et al. 2015

Genetics in Medicine

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“…Patients with CYP2D6 IM genotype were phenoconverted into PM phenotype at a lower dose (50 mg day −1 or greater) of thioridazine than those of CYP2D6 EM genotype (150 mg day −1 ). In the study by Preskorn et al [60], phenoconversion to CYP2D6 PM phenotype occurred in 159 (21.3%) of 748 genotypic EM subjects and in only one (2.8%) of the 36 genotypic UM subjects. Lam et al [32] have also reported that the potential of paroxetine as an inhibitor may be affected by the genotypes and basal metabolic capacities of individual subjects.…”

Section: Genotype-dependent Susceptibility To Phenoconversionmentioning

confidence: 91%

Addressing phenoconversion: the Achilles' heel of personalized medicine

Shah

Smith

2015

Brit J Clinical Pharma

219

217

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Phenoconversion is a phenomenon that converts genotypic extensive metabolizers (EMs) into phenotypic poor metabolizers (PMs) of drugs, thereby modifying their clinical response to that of genotypic PMs. Phenoconversion, usually resulting from nongenetic extrinsic factors, has a significant impact on the analysis and interpretation of genotype-focused clinical outcome association studies and personalizing therapy in routine clinical practice. The high phenotypic variability or genotype-phenotype mismatch, frequently observed due to phenoconversion within the genotypic EM population, means that the real number of phenotypic PM subjects may be greater than predicted from their genotype alone, because many genotypic EMs would be phenotypically PMs. If the phenoconverted population with genotype-phenotype mismatch, most extensively studied for CYP2D6, is as large as the evidence suggests, there is a real risk that genotype-focused association studies, typically correlating only the genotype with clinical outcomes, may miss clinically strong pharmacogenetic associations, thus compromising any potential for advancing the prospects of personalized medicine. This review focuses primarily on co-medication-induced phenoconversion and discusses potential approaches to rectify some of the current shortcomings. It advocates routine phenotyping of subjects in genotype-focused association studies and proposes a new nomenclature to categorize study populations. Even with strong and reliable data associating patients' genotypes with clinical outcome(s), there are problems clinically in applying this knowledge into routine pharmacotherapy because of potential genotype-phenotype mismatch. Drug-induced phenoconversion during routine clinical practice remains a major public health issue. Therefore, the principal challenges facing personalized medicine, which need to be addressed, include identification of the following factors: (i) drugs that are susceptible to phenoconversion; (ii) co-medications that can cause phenoconversion; and (iii) dosage amendments that need to be applied during and following phenoconversion. Pharmacogenetics and personalized medicineThe majority of drug-metabolizing enzymes (DMEs) are subject to genetic polymorphism and show some degree of functionally significant polymorphism in the population. The clearest data in this regard relate to cytochromes P450 CYP2D6 and CYP2C19 and thiopurine methyltransferase (TPMT). These genetically determined polymorphisms give rise to three distinct genotype-based subpopulations with respect to each DME, namely extensive metabolizers (EMs), poor metabolizers (PMs) and a subgroup in between, the intermediate metabolizers (IMs). In addition, for CYP2D6 and CYP2C19, there is a fourth genotype, the ultrarapid metabolizer (UM) genotype, resulting from inheritance of either multiple copies of the functional wild-type allele, such as CYP2D6*1, or a higher metabolic capacity resulting from increased transcription of DME due to the presence of a genetic variant found in the promoter ...

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“…CYP2C19 metabolic status in vivo can be inferred from genotype or determined via therapeutic drug monitoring by measuring the metabolism of a probe substrate (Desta et al, 2002). Reliable genotyping platforms are currently available for both CYP2D6 and CYP2C19 (AmpliChip; Roche, Basel, Switzerland); however, accurate prediction of phenotype from genotype is impossible as phenoconversions due to nongenetic factors, such as drug-drug interactions for CYP2D6, are common (Preskorn et al, 2013). The uncertainty of the functional consequences of certain variant alleles in each individual, the inability to capture changes in activity caused by nongenetic factors, and the need to genotype for a large number of (rare or yet unknown) variant alleles and their combinations make the genotype test clinically and practically insufficient for identifying all poor metabolizers (PMs) of CYP2C19 in the general population.…”

Section: Introductionmentioning

confidence: 99%

CYP2C19 Phenoconversion by Routinely Prescribed Proton Pump Inhibitors Omeprazole and Esomeprazole: Clinical Implications for Personalized Medicine

Klieber

Oberacher

Hofstaetter

et al. 2015

J Pharmacol Exp Ther

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The phenotype pantoprazole-13 C breath test (Ptz-BT) was used to evaluate the extent of phenoconversion of CYP2C19 enzyme activity caused by commonly prescribed proton pump inhibitors (PPI) omeprazole and esomprazole. The Ptz-BT was administered to 26 healthy volunteers and 8 stable cardiovascular patients twice at baseline and after 28 days of PPI therapy to evaluate reproducibility of the Ptz-BT and changes in CYP2C19 enzyme activity (phenoconversion) after PPI therapy. The average intrapatient interday variability in CYP2C19 phenotype (n 5 31) determined by Ptz-BT was considerably low (coefficient of variation, 17%). Phenotype conversion resulted in 25 of 26 (96%) nonpoor metabolizer (non-PM) volunteers/ patients as measured by the Ptz-BT at baseline and after PPI therapy. The incidence of PM status by phenotype following administration of omeprazole/esomeprazole (known inhibitors of CYP2C19) was 10-fold higher than those who are genetically PMs in the general population, which could have critical clinical implications for personalizing medications primarily metabolized by CYP2C19, such as clopidogrel, PPI, cyclophosphamide, thalidomide, citalopram, clonazepam, diazepam, phenytoin, etc. The Ptz-BT can rapidly (30 minutes) evaluate CYP2C19 phenotype and, more importantly, can identify patients with phenoconversion in CYP2C19 enzyme activity caused by nongenetic factors such as concomitant drugs.

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Cytochrome P450 2D6 Phenoconversion Is Common in Patients Being Treated for Depression

Abstract: ClinicalTrials identifier: NCT00788944.

Cited by 105 publications

References 0 publications

Guidance for pharmacogenomic biomarker testing in labels of FDA-approved drugs

Guidance for pharmacogenomic biomarker testing in labels of FDA-approved drugs

Addressing phenoconversion: the Achilles' heel of personalized medicine

CYP2C19 Phenoconversion by Routinely Prescribed Proton Pump Inhibitors Omeprazole and Esomeprazole: Clinical Implications for Personalized Medicine

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