CYP450 Genotype-Phenotype Concordance Using the Geneva Micrococktail in a Clinical Setting

Tolterodine is a novel candidate for assessing CYP3A4 activity through metabolic volatiles to predict drug responses

Cytochrome P450 (CYP) 3A4 plays a major role in drug metabolism. Its activity could be determined by non-invasive and cost-effective assays, such as breath analysis, for the personalised monitoring of drug response. For the first time, we identify an isotopically unlabelled CYP3A4 substrate, tolterodine that leads to the formation of a non-toxic volatile metabolite, acetone, which could potentially be applied to monitor CYP3A4 activity in humans. In vitro biotransformation of tolterodine by HepG2 cells overexpressing CYP3A4, CYP2D6 or CYP2C9 was investigated by LC-MS analysis of cell culture supernatant for the non-volatile metabolite, N-dealkylated tolterodine, and PTR-ToF-MS analysis of the headspace for acetone. The highest level of the N-dealkylated metabolite was produced by HepG2-CYP3A4. Concentration dependent effects of tolterodine were analysed, resulting in TC50 values of 414 µM and 375 µM for HepG2-CYP3A4 and reference cells, respectively. Acetone and N-dealkylated tolterodine levels increased continuously over 24 h in HepG2-CYP3A4. Treatment with either a pan-CYP inhibitor, 1-aminobenzotriazole, or a CYP3A4 inhibitor, ketoconazole, considerably reduced the production of both metabolites in HepG2-CYP3A4 cells. These findings pave the way for the further development of non-invasive breath tests using unlabelled precursors to determine CYP enzyme activity in individuals.

Pharmacogenetic guided drug therapy - how to deal with phenoconversion in polypharmacy

INTRODUCTION

The prevalence of polypharmacy and the increasing availability of pharmacogenetic information in clinical practice have raised the prospect of data-driven clinical decision-making when addressing the issues of drug-drug interactions and genetic polymorphisms in metabolizing enzymes. Inhibition of metabolizing enzymes in drug interactions can lead to genotype-phenotype discrepancies (phenoconversion) that reduce the relevance of individual pharmacogenetic information.

AREAS COVERED

The aim of this review is to provide an overview of existing models of phenoconversion, and we discuss how phenoconversion models may be developed to estimate joint drug-interactions and genetic effects. Based on a literature search in PubMed, Google Scholar, and reference lists from review articles, we provide an overview of the current models of phenoconversion. The currently applied phenoconversion models are presented and discussed to predict the effects of drug-drug interactions while accounting for the pharmacogenetic status of patients.

EXPERT OPINION

While pharmacogenetic-dose recommendations alone are most relevant for rare and extreme genotypes, phenoconversion may increase the prevalence of these phenotypes. Therefore, in polypharmacy conditions, phenoconversion assessment is especially important for personalized drug therapy.

Cytochrome P450 phenotyping using the Geneva cocktail improves metabolic capacity prediction in a hospitalized patient population

AIMS

Liver cytochromes (CYPs) play an important role in drug metabolism but display a large interindividual variability resulting both from genetic and environmental factors. Most drug dose adjustment guidelines are based on genetics performed in healthy volunteers. However, hospitalized patients are not only more likely to be the target of new prescriptions and drug treatment modifications than healthy volunteers, but will also be more subject to polypharmacy, drug-drug interactions, or to suffer from disease or inflammation affecting CYP activities.

METHODS

We compared predicted phenotype based on genetic data and measured phenotype using the Geneva cocktail to determine the extent of drug metabolizing enzyme variability in a large population of hospitalized patients (>500) and healthy young volunteers (>300). We aimed to assess the correlation between predicted and measured phenotype in the two populations.

RESULTS

We found that, even in cases where the genetically predicted metabolizer group correlates well with measured CYP activity at group level, this prediction lacks accuracy for the determination of individual metabolizer capacities. Drugs can have a profound impact on CYP activity, but even after combining genetic and drug treatment information, the activity of a significant proportion of extreme metabolizers could not be explained.

CONCLUSIONS

Our results support the use of measured metabolic ratios in addition to genotyping for accurate determination of individual metabolic capacities to guide personalized drug prescription.

Clinical effects of CYP2D6 phenoconversion in patients with psychosis

BACKGROUND

Pharmacogenetics is considered a promising avenue for improving treatment outcomes, yet evidence arguing for the use of pharmacogenetics in the treatment of psychotic disorders is mixed and clinical usefulness is under debate. Many patients with psychosis use multiple medications, which can alter the metabolic capacity of CYP enzymes, a process called phenoconversion. In clinical studies, treatment outcomes of drugs for psychosis management may have been influenced by phenoconversion.

AIM

Here we evaluate the impact and predictive value of CYP2D6 phenoconversion in patients with psychotic disorders under pharmacological treatment.

METHOD

Phenoconversion-corrected phenotype was determined by accounting for inhibitor strength. Phenoconversion-corrected and genotype-predicted phenotypes were compared in association with side effects, subjective well-being and symptom severity.

RESULTS

Phenoconversion led to a large increase in poor metabolizers (PMs; 17-82, 16% of sample), due to concomitant use of the serotonin reuptake inhibitors fluoxetine and paroxetine. Neither CYP2D6-predicted nor phenoconversion-corrected phenotype was robustly associated with outcome measures. Risperidone, however, was most affected by the CYP2D6 genotype.

CONCLUSION

Polypharmacy and phenoconversion were prevalent and accounted for a significant increase in PMs. CYP2D6 may play a limited role in side effects, symptoms and well-being measures. However, due to the high frequency of occurrence, phenoconversion should be considered in future clinical trials.

Phenoconversion Due to Drug-Drug Interactions in CYP2C19 Genotyped Healthy Volunteers

To compensate for drug response variability, drug metabolism phenotypes are determined based on the results of genetic testing, and if necessary, drug dosages are adjusted. In some cases, discrepancies between predicted and observed phenotypes (phenoconversion) may occur due to drug-drug interactions caused by concomitant medications. We conducted a prospective, exploratory study to evaluate the risk of CYP2C19 phenoconversion in genotyped healthy volunteers exposed to CYP2C19 inhibitors. Three groups of volunteers were enrolled: CYP2C19 g-RM, g-NM, and g-IM (g- for genetically predicted). All volunteers received as CYP2C19 phenotyping substrate 10 mg omeprazole (OME) alone at the control session and in co-administration with CYP2C19 inhibitors: voriconazole 400 mg and fluvoxamine 50 mg in second and third study sessions, respectively. Phenoconversion occurred in over 80% of healthy volunteers, with variations among genotypic groups, revealing distinct proportions in response to fluvoxamine and voriconazole. Statistically significant differences were observed in mean metabolic ratios between CYP2C19 intermediate metabolizers (g-IMs) with *1/*2 and *2/*17 genotypes, with the *2/*17 group exhibiting lower ratios, and distinctions were noted between genotypic groups, emphasizing the impact of genetic variations on drug metabolism. When reclassified according to CYP2C19 baseline-measured phenotype into p-RM, p-NM, and p-IM (p- for measured phenotype), we observed 100% phenoconversion of p-RMs and a significant phenotype switch in p-NMs, p-IMs, and p-PMs after fluvoxamine and voriconazole, and complete phenoconversion of p-IMs to p-PMs on both inhibitors, emphasizing the impact of genetic variations on the vulnerability to CYP2C19 phenoconversion and the importance of considering both genotyping and phenotyping in predicting drug response.

Phenotype-Genotype Correlation Applying a Cocktail Approach and an Exome Chip Analysis Reveals Further Variants Contributing to Variation of Drug Metabolism

Although great progress has been made in the fine-tuning of diplotypes, there is still a need to further improve the predictability of individual phenotypes of pharmacogenetically relevant enzymes. The aim of this study was to analyze the additional contribution of sex and variants identified by exome chip analysis to the metabolic ratio of five probe drugs. A cocktail study applying dextromethorphan, losartan, omeprazole, midazolam, and caffeine was conducted on 200 healthy volunteers. CYP2D6, 2C9, 2C19, 3A4/5, and 1A2 genotypes were analyzed and correlated with metabolic ratios. In addition, an exome chip analysis was performed. These SNPs correlating with metabolic ratios were confirmed by individual genotyping. The contribution of various factors to metabolic ratios was assessed by multiple regression analysis. Genotypically predicted phenotypes defined by CPIC discriminated very well the log metabolic ratios with the exception of caffeine. There were minor sex differences in the activity of CYP2C9, 2C19, 1A2, and CYP3A4/5. For dextromethorphan (CYP2D6), IP6K2 (rs61740999) and TCF20 (rs5758651) affected metabolic ratios, but only IP6K2 remained significant after multiple regression analysis. For losartan (CYP2C9), FBXW12 (rs17080138), ZNF703 (rs79707182), and SLC17A4 (rs11754288) together with CYP diplotypes, and sex explained 50% of interindividual variability. For omeprazole (CYP2C19), no significant influence of CYP2C:TG haplotypes was observed, but CYP2C19 rs12777823 improved the predictability. The comprehensive genetic analysis and inclusion of sex in a multiple regression model significantly improved the explanation of variability of metabolic ratios, resulting in further improvement of algorithms for the prediction of individual phenotypes of drug-metabolizing enzymes.

The Relevance of Integrating CYP2C19 Phenoconversion Effects into Clinical Pharmacogenetics

INTRODUCTION

CYP2D6 and CYP2C19 functional status as defined by genotype is modulated by phenoconversion (PC) due to pharmacokinetic interactions. As of today, there is no data on the effect size of PC for CYP2C19 functional status. The primary aim of this study was to investigate the impact of PC on CYP2C19 functional status.

METHODS

Two patient cohorts (total n=316; 44.2±15.4 years) were investigated for the functional enzyme status of CYP2C19 applying two different correction methods (PCBousman, PCHahn&Roll) as well as serum concentration and metabolite-to-parent ratio of venlafaxine, amitriptyline, mirtazapine, sertraline, escitalopram, risperidone, and quetiapine.

RESULTS

There was a decrease in the number of normal metabolizers of CYP2C19 and an increase in the number of poor metabolizers. When controlled for age, sex, and, in the case of amitriptyline, venlafaxine, and risperidone, CYP2D6 functional enzyme status, an association was observed between the CYP2C19 phenotype/functional enzyme status and serum concentration of amitriptyline, sertraline, and escitalopram.

DISCUSSION

PC of CYP2C19 changes phenotypes but does not improve correlations with serum concentrations. However, only a limited number of patients received perturbators of CYP2C19. Studies with large numbers of patients are still lacking, and thus, it cannot be decided if there are minor differences and which method of correction to use. For the time being, PC is relevant in individual patients treated with CYP2C19-affecting drugs, for example, esomeprazole. To ensure adequate serum concentrations in these patients, this study suggests the use of therapeutic drug monitoring.

CYP1A2 expression rather than genotype is associated with olanzapine concentration in psychiatric patients

Olanzapine is a commonly prescribed atypical antipsychotic agent for treatment of patients with schizophrenia and bipolar disorders. Previous in vitro studies using human liver microsomes identified CYP1A2 and CYP2D6 enzymes being responsible for CYP-mediated metabolism of olanzapine. The present work focused on the impact of CYP1A2 and CYP2D6 genetic polymorphisms as well as of CYP1A2 metabolizing capacity influenced by non-genetic factors (sex, age, smoking) on olanzapine blood concentration in patients with psychiatric disorders (N = 139). CYP2D6 genotype-based phenotype appeared to have negligible contribution to olanzapine metabolism, whereas a dominant role of CYP1A2 in olanzapine exposure was confirmed. However, CYP1A2 expression rather than CYP1A2 genetic variability was demonstrated to be associated with olanzapine concentration in patients. Significant contribution of - 163C > A (rs762551), the most common SNP (single nucleotide polymorphism) in CYP1A2 gene, to enhanced inducibility was confirmed by an increase in CYP1A2 mRNA expression in smokers carrying - 163A, and smoking was found to have appreciable impact on olanzapine concentration normalized by the dose/bodyweight. Furthermore, patients' olanzapine exposure was in strong association with CYP1A2 expression; therefore, assaying CYP1A2 mRNA level in leukocytes can be an appropriate tool for the estimation of patients' olanzapine metabolizing capacity and may be relevant in optimizing olanzapine dosage.

The impact of CYP2C19 genotype on phenoconversion by concomitant medication

Introduction: Pharmacogenetics-informed drug prescribing is increasingly applied in clinical practice. Typically, drug metabolizing phenotypes are determined based on genetic test results, whereupon dosage or drugs are adjusted. Drug-drug-interactions (DDIs) caused by concomitant medication can however cause mismatches between predicted and observed phenotypes (phenoconversion). Here we investigated the impact of CYP2C19 genotype on the outcome of CYP2C19-dependent DDIs in human liver microsomes. Methods: Liver samples from 40 patients were included, and genotyped for CYP2C19*2, *3 and *17 variants. S-mephenytoin metabolism in microsomal fractions was used as proxy for CYP2C19 activity, and concordance between genotype-predicted and observed CYP2C19 phenotype was examined. Individual microsomes were subsequently co-exposed to fluvoxamine, voriconazole, omeprazole or pantoprazole to simulate DDIs. Results: Maximal CYP2C19 activity (V_max) in genotype-predicted intermediate metabolizers (IMs; *1/*2 or *2/*17), rapid metabolizers (RMs; *1/*17) and ultrarapid metabolizers (UMs; *17/*17) was not different from V_max of predicted normal metabolizers (NMs; *1/*1). Conversely, CYP2C19*2/*2 genotyped-donors exhibited V_max rates ∼9% of NMs, confirming the genotype-predicted poor metabolizer (PM) phenotype. Categorizing CYP2C19 activity, we found a 40% concordance between genetically-predicted CYP2C19 phenotypes and measured phenotypes, indicating substantial phenoconversion. Eight patients (20%) exhibited CYP2C19 IM/PM phenotypes that were not predicted by their CYP2C19 genotype, of which six could be linked to the presence of diabetes or liver disease. In subsequent DDI experiments, CYP2C19 activity was inhibited by omeprazole (-37% ± 8%), voriconazole (-59% ± 4%) and fluvoxamine (-85% ± 2%), but not by pantoprazole (-2 ± 4%). The strength of CYP2C19 inhibitors remained unaffected by CYP2C19 genotype, as similar percental declines in CYP2C19 activity and comparable metabolism-dependent inhibitory constants (K_inact/K_I) of omeprazole were observed between CYP2C19 genotypes. However, the consequences of CYP2C19 inhibitor-mediated phenoconversion were different between CYP2C19 genotypes. In example, voriconazole converted 50% of *1/*1 donors to a IM/PM phenotype, but only 14% of *1/*17 donors. Fluvoxamine converted all donors to phenotypic IMs/PMs, but *1/*17 (14%) were less likely to become PMs than *1/*1 (50%) or *1/*2 and *2/*17 (57%). Conclusion: This study suggests that the differential outcome of CYP2C19-mediated DDIs between genotypes are primarily dictated by basal CYP2C19 activity, that may in part be predicted by CYP2C19 genotype but likely also depends on disease-related factors.

Phenotyping Indices of CYP450 and P-Glycoprotein in Human Volunteers and in Patients Treated with Painkillers or Psychotropic Drugs

Drug-metabolizing enzymes and drug transporters are key determinants of drug pharmacokinetics and response. The cocktail-based cytochrome P450 (CYP) and drug transporter phenotyping approach consists in the administration of multiple CYP or transporter-specific probe drugs to determine their activities simultaneously. Several drug cocktails have been developed over the past two decades in order to assess CYP450 activity in human subjects. However, phenotyping indices were mostly established for healthy volunteers. In this study, we first performed a literature review of 27 clinical pharmacokinetic studies using drug phenotypic cocktails in order to determine 95%,95% tolerance intervals of phenotyping indices in healthy volunteers. Then, we applied these phenotypic indices to 46 phenotypic assessments processed in patients having therapeutic issues when treated with painkillers or psychotropic drugs. Patients were given the complete phenotypic cocktail in order to explore the phenotypic activity of CYP1A2, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A, and P-glycoprotein (P-gp). P-gp activity was evaluated by determining AUC_0-6h for plasma concentrations over time of fexofenadine, a well-known substrate of P-gp. CYP metabolic activities were assessed by measuring the CYP-specific metabolite/parent drug probe plasma concentrations, yielding single-point metabolic ratios at 2 h, 3 h, and 6 h or AUC_0-6h ratio after oral administration of the cocktail. The amplitude of phenotyping indices observed in our patients was much wider than those observed in the literature for healthy volunteers. Our study helps define the range of phenotyping indices with "normal" activities in human volunteers and allows classification of patients for further clinical studies regarding CYP and P-gp activities.

Allergic and other adverse reactions to drugs used in anesthesia and surgery

The list of drugs patients may be exposed to during the perioperative and postoperative periods is potentially extensive. It includes induction agents, neuromuscular blocking drugs (NMBDs), opioids, antibiotics, sugammadex, colloids, local anesthetics, polypeptides, antifibrinolytic agents, heparin and related anticoagulants, blue dyes, chlorhexidine, and a range of other agents depending on several factors related to individual patients’ clinical condition and progress in the postoperative recovery period. To avoid poor or ultrarapid metabolizers to a particular drug (for example tramadol and codeine) or possible adverse drug reactions (ADRs), some drugs may need to be avoided during or after surgery. This will be the case for patients with a history of anaphylaxis or other adverse events/intolerances to a known drug. Other drugs may be ceased for a period before surgery, e.g., anticoagulants that increase the chance of bleeding; diuretics for patients with acute renal failure; antihypertensives relative to kidney injury after major vascular surgery; and serotonergic drugs that together with some opioids may rarely induce serotonin toxicity. Studies of germline variations shown by genotyping and phenotyping to identify a predisposition of genetic factors to ADRs offer an increasingly important approach to individualize drug therapy. Studies of associations of human leukocyte antigen (HLA) genes with some serious delayed immune-mediated reactions are ongoing and variations of drug-metabolizing cytochrome CYP450 enzymes, P-glycoprotein, and catechol-O -methyltransferase show promise for the assessment of ADRs and non-responses to drugs, particularly opioids and other analgesics. Surveys of ADRs from an increasing number of institutions often cover small numbers of patients, are retrospective in nature, fail to clearly identify culprit drugs, and do not adequately distinguish immune-mediated from non-immune-mediated anaphylactoid reactions. From the many surveys undertaken, the large list of agents identified during and after anesthesia and surgery are examined for their ADR involvement. Drugs are classified into those most often involved, (NMBD and antibiotics); drugs that are becoming more frequently implicated, namely antibiotics (particularly teicoplanin), and blue dyes; those becoming less frequently involved; and drugs more rarely involved in perioperative, and postoperative adverse reactions but still important and necessary to keep in mind for the occasional potential sensitive patient. Clinicians should be aware of the similarities between drug-induced true allergic type I IgE/FcεRI- and pseudoallergic MRGPRX2-mediated ADRs, the clinical features of each, and their distinguishing characteristics. Procedures for identifying MRGPRX2 agonists and diagnosing and distinguishing pseudoallergic from allergic reaction mechanisms are discussed.

Practice of CYP450 genotyping and phenotyping in children in a real-life setting

Pharmacokinetics varies widely between children. Many factors play an important role in this variability, such as ontogeny, pharmacogenetics, gender, comorbidities, and drug-drug interactions. Significant work has already been done in adults to understand the impact of genetic polymorphisms on drug-metabolizing enzyme activity and drug response. Data remain poor in children due to ontogeny that impacts genotyping-phenotyping correlation and the difficulty enrolling children in prospective studies. Our study aimed to describe the use of cytochromes P450 (CYP) phenotyping and/or genotyping tests in children in a real-life setting and assess the correlation between the genotype and the phenotype. We reviewed the results of tests performed between January 2005 and December 2020. Fifty-two children were genotyped and/or phenotyped. Four patients were excluded from the present analysis as they only underwent ABCB1 genotyping, without CYP testing. Of the remainder, 18 underwent simultaneous CYP genotyping and phenotyping, while 17 underwent CYP genotyping only, and 13 underwent CYP phenotyping only. In all cases, investigations were performed after the following situations: insufficient clinical response to treatment, low plasma concentrations, and adverse drug reactions (ADR). The vast majority of cases were related to immunosuppressive or antipsychotic therapy. Genotyping and/or phenotyping explained or contributed to the aforementioned clinical events in 56% of cases. The correlation between the genotype and the phenotype showed variability depending on the assessed cytochrome. In several cases, the phenotype did not correspond to the genotype because of comedications. In conclusion, there is clearly value in guiding drug based on CYP activity in children.

Cytochromes P450 and P-Glycoprotein Phenotypic Assessment to Optimize Psychotropic Pharmacotherapy: A Retrospective Analysis of Four Years of Practice in Psychiatry

Altered cytochromes P450 enzymes (CYP) and P-glycoprotein transporter (P-gp) activity may explain variabilities in drug response. In this study, we analyzed four years of phenotypic assessments of CYP/P-gp activities to optimize pharmacotherapy in psychiatry. A low-dose probe cocktail was administered to evaluate CYP1A2, 2B6, 2D6, 2C9, 2C19, 3A4, and P-gp activities using the probe/metabolite concentration ratio in blood or the AUC. A therapeutic adjustment was suggested depending on the phenotyping results. From January 2017 to June 2021, we performed 32 phenotypings, 10 for adverse drug reaction, 6 for non-response, and 16 for both reasons. Depending on the CYP/P-gp evaluated, only 23% to 56% of patients had normal activity. Activity was decreased in up to 57% and increased in up to 60% of cases, depending on the CYP/P-gp evaluated. In 11/32 cases (34%), the therapeutic problem was attributable to the patient's metabolic profile. In 10/32 cases (31%), phenotyping excluded the metabolic profile as the cause of the therapeutic problem. For all ten individuals for which we had follow-up information, phenotyping allowed us to clearly state or clearly exclude the metabolic profile as a possible cause of therapeutic failure. Among them, seven showed a clinical improvement after dosage adaptation, or drug or pharmacological class switching. Our study confirmed the interest of CYP and P-gp phenotyping for therapeutic optimization in psychiatry.

Impact of the Genotype and Phenotype of CYP3A and P-gp on the Apixaban and Rivaroxaban Exposure in a Real-World Setting

Apixaban and rivaroxaban are the two most prescribed direct factor Xa inhibitors. With the increased use of DOACs in real-world settings, safety and efficacy concerns have emerged, particularly regarding their concomitant use with other drugs. Increasing evidence highlights drug−drug interactions with CYP3A/P-gp modulators leading to adverse events. However, current recommendations for dose adjustment do not consider CYP3A/P-gp genotype and phenotype. We aimed to determine their impact on apixaban and rivaroxaban blood exposure. Three-hundred hospitalized patients were included. CYP3A and P-gp phenotypic activities were assessed by the metabolic ratio of midazolam and AUC0−6h of fexofenadine, respectively. Relevant CYP3A and ABCB1 genetic polymorphisms were also tested. Capillary blood samples collected at four time-points after apixaban or rivaroxaban administration allowed the calculation of pharmacokinetic parameters. According to the developed multivariable linear regression models, P-gp activity (p < 0.001) and creatinine clearance (CrCl) (p = 0.01) significantly affected apixaban AUC0−6h. P-gp activity (p < 0.001) also significantly impacted rivaroxaban AUC0−6h. The phenotypic switch (from normal to poor metabolizer) of P-gp led to an increase of apixaban and rivaroxaban AUC0−6h by 16% and 25%, respectively, equivalent to a decrease of 38 mL/min in CrCl according to the apixaban model. CYP3A phenotype and tested SNPs of CYP3A/P-gp had no significant impact. In conclusion, P-gp phenotypic activity, rather than known CYP3A/P-gp polymorphisms, could be relevant for dose adjustment.

CYP1A2 mRNA Expression Rather than Genetic Variants Indicate Hepatic CYP1A2 Activity

CYP1A2, one of the most abundant hepatic cytochrome P450 enzymes, is involved in metabolism of several drugs and carcinogenic compounds. Data on the significance of CYP1A2 genetic polymorphisms in enzyme activity are highly inconsistent; therefore, the impact of CYP1A2 genetic variants (−3860G>A, −2467delT, −739T>G, −163C>A, 2159G>A) on mRNA expression and phenacetin O-dealkylation selective for CYP1A2 was investigated in human liver tissues and in psychiatric patients belonging to Caucasian populations. CYP1A2*1F, considered to be associated with high CYP1A2 inducibility, is generally identified by the presence of −163C>A polymorphism; however, we demonstrated that −163C>A existed in several haplotypes (CYP1A2*1F, CYP1A2*1L, CYP1A2*1M, CYP1A2*1V, CYP1A2*1W), and consequently, CYP1A2*1F was a much rarer allelic variant (0.4%) than reported in Caucasian populations. Of note, −163C>A polymorphism was found to result in an increase of neither mRNA nor the activity of CYP1A2. Moreover, hepatic CYP1A2 activity was associated with hepatic or leukocyte mRNA expression rather than genetic polymorphisms of CYP1A2. Consideration of non-genetic phenoconverting factors (co-medication with CYP1A2-specific inhibitors/inducers, tobacco smoking and non-specific factors, including amoxicillin+clavulanic acid therapy or chronic alcohol consumption) did not much improve genotype−phenotype estimation. In conclusion, CYP1A2-genotyping is inappropriate for the prediction of CYP1A2 function; however, CYP1A2 mRNA expression in leukocytes can inform about patients’ CYP1A2-metabolizing capacity.

CYP2B6 allelic variants and non-genetic factors influence CYP2B6 enzyme function

Human CYP2B6 enzyme although constitutes relatively low proportion (1–4%) of hepatic cytochrome P450 content, it is the major catalyst of metabolism of several clinically important drugs (efavirenz, cyclophosphamide, bupropion, methadone). High interindividual variability in CYP2B6 function, contributing to impaired drug-response and/or adverse reactions, is partly elucidated by genetic polymorphisms, whereas non-genetic factors can significantly modify the CYP2B6 phenotype. The influence of genetic and phenoconverting non-genetic factors on CYP2B6-selective activity and CYP2B6 expression was investigated in liver tissues from Caucasian subjects (N = 119). Strong association was observed between hepatic S-mephenytoin N-demethylase activity and CYP2B6 mRNA expression (P < 0.0001). In less than one third of the tissue donors, the CYP2B6 phenotype characterized by S-mephenytoin N-demethylase activity and/or CYP2B6 expression was concordant with CYP2B6 genotype, whereas in more than 35% of the subjects, an altered CYP2B6 phenotype was attributed to phenoconverting non-genetic factors (to CYP2B6-specific inhibitors and inducers, non-specific amoxicillin + clavulanic acid treatment and chronic alcohol consumption, but not to the gender). Furthermore, CYP2B6 genotype–phenotype mismatch still existed in one third of tissue donors. In conclusion, identifying potential sources of CYP2B6 variability and considering both genetic variations and non-genetic factors is a pressing requirement for appropriate elucidation of CYP2B6 genotype–phenotype mismatch.