CYP3A4*22 is related to increased plasma levels of 4-hydroxytamoxifen and partially compensates for reduced CYP2D6 activation of tamoxifen

EA, Udupa KS, Gota V, Mallayasamy S. Factors Influencing Pharmacokinetics of Tamoxifen in Breast Cancer Patients: A Systematic Review of Population Pharmacokinetic Models

BACKGROUND

Tamoxifen is useful in managing breast cancer and it is reported to have significant variability in its pharmacokinetics. This review aimed to summarize reported population pharmacokinetics studies of tamoxifen and to identify the factors affecting the pharmacokinetics of tamoxifen in adult breast cancer patients.

METHOD

A systematic search was undertaken in Scopus, Web of Science, and PubMed for papers published in the English language from inception to 20 August 2022. Studies were included in the review if the population pharmacokinetic modeling was based on non-linear mixed-effects modeling with a parametric approach for tamoxifen in breast cancer patients.

RESULTS

After initial selection, 671 records were taken for screening. A total of five studies were selected from Scopus, Web of Science, PubMed, and by manual searching. The majority of the studies were two-compartment models with first-order absorption and elimination to describe tamoxifen and its metabolites' disposition. The CYP2D6 phenotype and CYP3A4 genotype were the main covariates that affected the metabolism of tamoxifen and its metabolites. Other factors influencing the drug's pharmacokinetics included age, co-medication, BMI, medication adherence, CYP2B6, and CYP2C19 genotype.

CONCLUSION

The disposition of tamoxifen and its metabolites varies primarily due to the CYP2D6 phenotype and CYP3A4 genotype. However, other factors, such as anthropometric characteristics and menopausal status, should also be addressed when accounting for this variability. All these studies should be externally evaluated to assess their applicability in different populations and to use model-informed dosing in the clinical setting.

CYP3A4∗22 Genotyping in Clinical Practice: Ready for Implementation?

Cytochrome P450 3A4 (CYP3A4) is the most important drug metabolizing enzyme in the liver, responsible for the oxidative metabolism of ∼50% of clinically prescribed drugs. Therefore, genetic variation in CYP3A4 could potentially affect the pharmacokinetics, toxicity and clinical outcome of drug treatment. Thus far, pharmacogenetics for CYP3A4 has not received much attention. However, the recent discovery of the intron 6 single-nucleotide polymorphism (SNP) rs35599367C > T, encoding the CYP3A4^∗22 allele, led to several studies into the pharmacogenetic effect of CYP3A4^∗22 on different drugs. This allele has a relatively minor allele frequency of 3-5% and an effect on CYP3A4 enzymatic activity. Thus far, no review summarizing the data published on several drugs is available yet. This article therefore addresses the current knowledge on CYP3A4^∗22. This information may help in deciding if, and for which drugs, CYP3A4^∗22 genotype-based dosing could be helpful in improving drug therapy. CYP3A4^∗22 was shown to significantly influence the pharmacokinetics of several drugs, with currently being most thoroughly investigated tacrolimus, cyclosporine, and statins. Additional studies, focusing on toxicity and clinical outcome, are warranted to demonstrate clinical utility of CYP3A4^∗22 genotype-based dosing.

Effect of Genetic Variability in 20 Pharmacogenes on Concentrations of Tamoxifen and Its Metabolites

BACKGROUND

Tamoxifen, as a treatment of estrogen receptor positive (ER+) breast cancer, is a weak anti-estrogen that requires metabolic activation to form metabolites with higher anti-estrogenic activity. Endoxifen is the most-studied active tamoxifen metabolite, and endoxifen concentrations are highly associated with CYP2D6 activity. Associations of tamoxifen efficacy with measured or CYP2D6-predicted endoxifen concentrations have been inconclusive. Another active metabolite, 4-OHtam, and other, less active metabolites, Z-4'-endoxifen and Z-4'-OHtam, have also been reported to be associated with tamoxifen efficacy.

METHOD

Genotype for 20 pharmacogenes was determined by VeriDose^® Core Panel and VeriDose^®CYP2D6 CNV Panel, followed by translation to metabolic activity phenotype following standard activity scoring. Concentrations of tamoxifen and seven metabolites were measured by UPLC-MS/MS in serum samples collected from patients receiving 20 mg tamoxifen per day. Metabolic activity was tested for association with tamoxifen and its metabolites using linear regression with adjustment for upstream metabolites to identify genes associated with each step in the tamoxifen metabolism pathway.

RESULTS

A total of 187 patients with genetic and tamoxifen concentration data were included in the analysis. CYP2D6 was the primary gene associated with the tamoxifen metabolism pathway, especially the conversion of tamoxifen to endoxifen. CYP3A4 and CYP2C9 were also responsible for the metabolism of tamoxifen. CYP2C9 especially impacted the hydroxylation to 4-OHtam, and this involved the OATP1B1 (SLCO1B1) transporter.

CONCLUSION

Multiple genes are involved in tamoxifen metabolism and multi-gene panels could be useful to predict active metabolite concentrations and guide tamoxifen dosing.

Generating a Precision Endoxifen Prediction Algorithm to Advance Personalized Tamoxifen Treatment in Patients with Breast Cancer

Tamoxifen is an endocrine treatment for hormone receptor positive breast cancer. The effectiveness of tamoxifen may be compromised in patients with metabolic resistance, who have insufficient metabolic generation of the active metabolites endoxifen and 4-hydroxy-tamoxifen. This has been challenging to validate due to the lack of measured metabolite concentrations in tamoxifen clinical trials. CYP2D6 activity is the primary determinant of endoxifen concentration. Inconclusive results from studies investigating whether CYP2D6 genotype is associated with tamoxifen efficacy may be due to the imprecision in using CYP2D6 genotype as a surrogate of endoxifen concentration without incorporating the influence of other genetic and clinical variables. This review summarizes the evidence that active metabolite concentrations determine tamoxifen efficacy. We then introduce a novel approach to validate this relationship by generating a precision endoxifen prediction algorithm and comprehensively review the factors that must be incorporated into the algorithm, including genetics of CYP2D6 and other pharmacogenes. A precision endoxifen algorithm could be used to validate metabolic resistance in existing tamoxifen clinical trial cohorts and could then be used to select personalized tamoxifen doses to ensure all patients achieve adequate endoxifen concentrations and maximum benefit from tamoxifen treatment.

Sources of Interindividual Variability

The efficacy, safety, and tolerability of drugs are dependent on numerous factors that influence their disposition. A dose that is efficacious and safe for one individual may result in sub-therapeutic or toxic blood concentrations in others. A significant source of this variability in drug response is drug metabolism, where differences in presystemic and systemic biotransformation efficiency result in variable degrees of systemic exposure (e.g., AUC, C_max, and/or C_min) following administration of a fixed dose.Interindividual differences in drug biotransformation have been studied extensively. It is recognized that both intrinsic factors (e.g., genetics, age, sex, and disease states) and extrinsic factors (e.g., diet , chemical exposures from the environment, and the microbiome) play a significant role. For drug-metabolizing enzymes, genetic variation can result in the complete absence or enhanced expression of a functional enzyme. In addition, upregulation and downregulation of gene expression, in response to an altered cellular environment, can achieve the same range of metabolic function (phenotype), but often in a less predictable and time-dependent manner. Understanding the mechanistic basis for variability in drug disposition and response is essential if we are to move beyond the era of empirical, trial-and-error dose selection and into an age of personalized medicine that will improve outcomes in maintaining health and treating disease.

Recent advances in the personalized treatment of estrogen receptor-positive breast cancer with tamoxifen: a focus on pharmacogenomics

Introduction: Tamoxifen is still an important drug in hormone-dependent breast cancer therapy. Personalization of its clinical use beyond hormone receptor positivity could improve the substantial variability of the treatment response.Areas covered: The overview of the current evidence for the treatment personalization using therapeutic drug monitoring, or using genetic biomarkers including CYP2D6 is provided. Although many studies focused on the PK aspects or the impact of CYP2D6 variability the translation into clinical routine is not clearly defined due to the inconsistent clinical outcome data.Expert opinion: We believe that at least the main candidate factors, i.e. CYP2D6 polymorphism, CYP2D6 inhibition, endoxifen serum levels may become important predictors of clinical relevance for tamoxifen treatment personalization in the future. To achieve this aim, however, further research should take into consideration more precise characterization of the disease, epigenetic factors and also utilize an appropriately powered multifactorial approach instead of a single gene evaluating studies.

Obesity Alters Endoxifen Plasma Levels in Young Breast Cancer Patients: A Pharmacometric Simulation Approach

Endoxifen is one of the most important metabolites of the prodrug tamoxifen. High interindividual variability in endoxifen steady-state concentrations (CSS,min ENDX ) is observed under tamoxifen standard dosing and patients with breast cancer who do not reach endoxifen concentrations above a proposed therapeutic threshold of 5.97 ng/mL may be at a 26% higher recurrence risk compared with patients with endoxifen concentrations exceeding this value. In this investigation, 10 clinical tamoxifen studies were pooled (1,388 patients) to investigate influential factors on CSS,min ENDX using nonlinear mixed-effects modeling. Age and body weight were found to significantly impact CSS,min ENDX in addition to CYP2D6 phenotype. Compared with postmenopausal patients, premenopausal patients had a 30% higher risk for subtarget CSS,min ENDX at tamoxifen 20 mg per day. In treatment simulations for distinct patient subpopulations, young overweight patients had a 3.1-13.8-fold higher risk for subtarget CSS,min ENDX compared with elderly low-weight patients. Considering ever-rising obesity rates and the clinical importance of tamoxifen for premenopausal patients, this subpopulation may benefit most from individualized tamoxifen dosing.

Development and validation of a high throughput bioanalytical UPLC-MS/MS method for simultaneous determination of tamoxifen and sulphoraphane in rat plasma: Application to an oral pharmacokinetic study

Tamoxifen (TAM) is the choice of a drug approved by the Food and Drug Administration (FDA) for the treatment of estrogen-positive receptor (ER+) breast cancer. Sulphoraphane (SFN), a natural plant antioxidant compound, also acts on estrogen-positive breast cancer receptor. Thus, a combination of TAM with SFN is preferred as it helps to minimize the drug-related toxicity and increases the therapeutic efficacy by providing synergistic anticancer effects of both drugs. In the present study, a new simple, sensitive, precise, and selective UPLC-MS/MS method was developed for the simultaneous quantification of tamoxifen and sulphoraphane using propranolol as an internal standard (IS) in rat plasma. Chromatographic separation was achieved on reverse phase Acquity UPLC BEH C¹⁸ column (50 mm × 2.1 mm, i.d., 1.7 μm) with an isocratic mobile phase composed of solvent A (0.1% formic acid in acetonitrile) and B (0.1% formic acid in water) (80:20, v/v) at a flow-rate of 0.4 mL/min. The detection and quantification of analytes was performed on Waters Zspray^TM Xevo TQD using selected-ion monitoring operated under a positive electrospray ionization mode. The transitions were m/z = 372.0 [M+H]⁺ → 71.92 for tamoxifen, m/z = 177.9 [M+H]⁺ → 113.9 for sulphoraphane and m/z = 260.3 [M+H]⁺ → 116.1 for propranolol. The method was linear over the concentration range of 8-500 ng/mL (r² = 0.9996) for tamoxifen, 30-2000 ng/mL (r² = 0.9998) for sulphoraphane with insignificant matrix effect and high extraction recovery on spiked quality control (QC) samples. The intra- and inter-batch precisions and accuracy were within the acceptable limits, and both the analytes were found to be stable throughout the short term, long term and freeze thaw stability studies. The validated method was successfully applied for the simultaneous estimation of TAM and SFN in an oral pharmacokinetic study in female Wistar rats. This developed UPLC-MS/MS method could be a valuable tool for future pharmacokinetic interaction, therapeutic drug monitoring and pharmacokinetic characterization of novel formulations.

Factors Affecting Tamoxifen Metabolism in Patients With Breast Cancer: Preliminary Results of the French PHACS Study

In addition to the effect of cytochrome P450 (CYP) 2D6 genetic polymorphisms, the metabolism of tamoxifen may be impacted by other factors with possible consequences on therapeutic outcome (efficacy and toxicity). This analysis focused on the pharmacokinetic (PK)-pharmacogenetic evaluation of tamoxifen in 730 patients with adjuvant breast cancer included in a prospective multicenter study. Plasma concentrations of tamoxifen and six major metabolites, the genotype for 63 single-nucleotide polymorphisms, and comedications were obtained 6 months after treatment initiation. Plasma concentrations of endoxifen were significantly associated with CYP2D6 diplotype (P < 0.0001), CYP3A4*22 genotype (P = 0.0003), and concomitant intake of potent CYP2D6 inhibitors (P < 0.001). Comparison of endoxifen levels showed that the CYP2D6 phenotype classification could be improved by grouping intermediate metabolizer (IM)/IM and IM/poor metabolizer diplotype into IM phenotype for future use in tamoxifen therapy optimization. Finally, the multivariable regression analysis showed that formation of tamoxifen metabolites was independently impacted by CYP2D6 diplotype and CYP3A4*22, CYP2C19*2, and CYP2B6*6 genetic polymorphisms.

Impact of Curcumin (with or without Piperine) on the Pharmacokinetics of Tamoxifen

Tamoxifen is a prodrug that is primarily metabolized into the pharmacologically active metabolite endoxifen and eventually into inactive metabolites. The herb curcumin may increase endoxifen exposure by affecting phase II metabolism. We compared endoxifen and tamoxifen exposure in breast cancer patients with or without curcumin, and with addition of the bio-enhancer piperine. Tamoxifen (20⁻30mg per day (q.d.)) was either given alone, or combined with curcumin (1200 mg three times daily (t.i.d.)) +/- piperine (10 mg t.i.d.). The primary endpoint of this study was the difference in geometric means for the area under the curve (AUC) of endoxifen. Genotyping was performed to determine CYP2D6 and CYP3A4 phenotypes. The endoxifen AUC_0⁻24h decreased with 7.7% (95%CI: -15.4 to 0.7%; p = 0.07) with curcumin and 12.4% (95%CI: -21.9 to -1.9%; p = 0.02) with curcumin and piperine, compared to tamoxifen alone. Tamoxifen AUC_0⁻24h showed similar results. For patients with an extensive CYP2D6 metabolism phenotype (EM), effects were more pronounced than for intermediate CYP2D6 metabolizers (IMs). In conclusion, the exposure to tamoxifen and endoxifen was significantly decreased by concomitant use of curcumin (+/- piperine). Therefore, co-treatment with curcumin could lower endoxifen concentrations below the threshold for efficacy (potentially 20⁻40% of the patients), especially in EM patients.

Pharmacogenomics research and clinical implementation in Brazil

We searched PubMed entries and the Lattes database of Brazilian Pharmacogenetics Network investigators, for pharmacogenetic/genomic (PGx) studies in the Brazilian population, focusing on the drugs and genes included in the Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. Warfarin was the most extensively studied drug in a PGx context: a genomewide association study targeting warfarin stable dose identified significant signals in VKORC1 and CYP2C9, several PGx dosing algorithms were developed based on these and other genes, and the implications of population admixture on extrapolation of dosing recommendations in the CPIC guidelines were examined. A study in renal transplanted patients disclosed association of CYP3A5*6 and CYP3A5*7 with tacrolimus dosing, which led to addition of these variants to CYP3A5*3 in the CPIC tacrolimus guideline. Studies verified predisposition of HIV-positive carriers of UGT1A1*28 to severe atazanavir-induced hyperbilirubinaemia, intolerance to 5-fluorouracyl in gastrointestinal cancer patients with deleterious DPYD variants, failure of HCV-infected carriers of IFNL3 rs12979860 to obtain a sustained viral response to PEG-IFN-α, and hypersensitivity reactions to abacavir in HIV-positive carriers of HLA-B*57:01. No prospective analyses of drug therapy outcomes or cost-effectiveness assessments of PGx-guided therapy were found. In conclusion, the limited adoption of PGx-informed drug prescription in Brazil reflects combination of recognized barriers to PGx implementation worldwide plus factors specific to the Brazilian population. The latter include rarity/absence of genetic variants on which international PGx guidelines are based (eg HLA-B*15.02 for phenytoin and carbamazepine) and the caveat of extrapolating to the admixed Brazilian population, guidelines based on categorical variables, such as continental ancestry (eg warfarin guidelines), "race" or ethnicity.

Pharmacogenetic testing in oncology: a Brazilian perspective

Pharmacogenetics, a major component of individualized or precision medicine, relies on human genetic diversity. The remarkable developments in sequencing technologies have revealed that the number of genetic variants modulating drug action is much higher than previously thought and that a true personalized prediction of drug response requires attention to rare mutations (minor allele frequency, MAF<1%) in addition to polymorphisms (MAF>1%) in pharmacogenes. This has major implications for the conceptual development and clinical implementation of pharmacogenetics. Drugs used in cancer treatment have been major targets of pharmacogenetics studies, encompassing both germline polymorphisms and somatic variants in the tumor genome. The present overview, however, has a narrower scope and is focused on germline cancer pharmacogenetics, more specifically, on drug/gene pairs for which pharmacogenetics-informed prescription guidelines have been published by the Clinical Pharmacogenetics Implementation Consortium and/or the Dutch Pharmacogenetic Working Group, namely, thiopurines/TPMT, fluoropyrimidines/UGT1A1, irinotecan/UGT1A1 and tamoxifen/CYP2D6. I begin by reviewing the general principles of pharmacogenetics-informed prescription, pharmacogenetics testing and the perceived barriers to the adoption of routine pharmacogenetics testing in clinical practice. Then, I highlight aspects of the pharmacogenetics testing of the selected drug-gene pairs and finally present pharmacogenetics data from Brazilian studies pertinent to these drug-gene pairs. I conclude with the notion that pharmacogenetics testing has the potential to greatly benefit patients by enabling precision medicine applied to drug therapy, ensuring better efficacy and reducing the risk of adverse effects.

Pharmacogenomics Guided-Personalization of Warfarin and Tamoxifen

The use of pharmacogenomics to personalize drug therapy has been a long-sought goal for warfarin and tamoxifen. However, conflicting evidence has created reason for hesitation in recommending pharmacogenomics-guided care for both drugs. This review will provide a summary of the evidence to date on the association between cytochrome P450 enzymes and the clinical end points of warfarin and tamoxifen therapy. Further, highlighting the clinical experiences that we have gained over the past ten years of running a personalized medicine program, we will offer our perspectives on the utility and the limitations of pharmacogenomics-guided care for warfarin and tamoxifen therapy.

Effect of CYP3A4*22, CYP3A5*3, and CYP3A combined genotypes on tamoxifen metabolism

Background

Tamoxifen is one of the cornerstones of endocrine therapy for breast cancer. Recently, the decreased activity CYP3A4*22 allele and the loss of function CYP3A5*3 allele have been described as potential factors that could help to explain the inter-patient variability in tamoxifen metabolism. The aim of this study is to investigate the effect of CYP3A4*22, CYP3A5*3, and CYP3A combined genotypes on tamoxifen metabolism.

Methods

DNA from 667 women enrolled in the CYPTAM study (NTR1509) was genotyped (CYP2D6, CYP3A4*22, and CYP3A5*3). Tamoxifen and metabolite concentrations were measured in serum, and metabolic ratios were calculated. The effect of the CYP3A4*22, CYP3A5*3, and CYP3A combined genotypes in addition to the CYP2D6 genotypes was examined by multiple linear regression analysis.

Results

CYP3A4*22 carriers reached significant higher concentrations of tamoxifen, N-desmethyl-tamoxifen, and 4-hydroxy-tamoxifen compared to non-carriers, whereas a tendency toward increased endoxifen levels was observed (p = 0.088). The metabolic ratio tamoxifen/N-desmethyl-tamoxifen was significantly higher in CYP3A4*22 individuals (0.59 vs. 0.52, p < 0.001). At the same time, CYP3A4*22 genotype contributed to improving the inter-variability [R² of the (log-transformed) metabolic ratio tamoxifen/N-desmethyl-tamoxifen improved from 21.8 to 23.9%, p < 0.001]. CYP3A5*3 marginally improved the explained variability of the (log transformed) metabolic ratio 4-hydroxy-tamoxifen/endoxifen (from 44.9 to 46.2%, p < 0.038).

Conclusion

Our data demonstrate that CYP3A genotype has a minor effect to explaining the variability between patients in tamoxifen metabolism and has no added value in addition to CYP2D6 genotype.

Electronic supplementary material

The online version of this article (10.1007/s00228-017-2323-2) contains supplementary material, which is available to authorized users.

Improved Prediction of Endoxifen Metabolism by CYP2D6 Genotype in Breast Cancer Patients Treated with Tamoxifen

Purpose: Prediction of impaired tamoxifen (TAM) to endoxifen metabolism may be relevant to improve breast cancer treatment, e.g., via TAM dose increase. The polymorphic cytochrome P450 2D6 (CYP2D6) strongly determines an individual's capacity for endoxifen formation, however, CYP2D6 phenotype assignments inferred from genotype widely differ between studies. Thus, we modeled plasma endoxifen predictability depending on variable CYP2D6 genotype groupings. Methods: CYP2D6 diplotype and metabolite plasma concentrations were assessed in 908 pre- and post-menopausal estrogen receptor (ER)-positive, TAM treated early breast cancer patients of Caucasian (N = 678), Middle-Eastern Arab (N = 77), and Asian (N = 153) origin. Robust coefficients of determination (R2) were estimated for endoxifen (E) or metabolic ratio endoxifen/desmethyl-TAM (E/DMT) as dependent and different CYP2D6 phenotype assignments as independent variables. Allele activity scores (ASs) were modified with respect to a reduced ∗10 allele activity. Predictability of endoxifen plasma concentrations above the clinical threshold of 5.9 ng/mL was investigated by receiver operating characteristic (ROC) analysis. Results: CYP2D6 diplotypes (N = 898) were strongly associated with E and E/DMT independent of age (P < 10-15). Across all ethnicities, 68-82% inter-patient variability of E/DMT was explained by CYP2D6 diplotype, while plasma endoxifen was predictable by 39-58%. The previously used codeine specific phenotype classification showed worse prediction for both endpoints particularly in Asians (median R2< 20%; P < 10-9). Downgrading of ∗10 activity slightly improved the explanatory value of metabolizer phenotype (P < 0.002). Endoxifen plasma concentrations above the clinical threshold of 5.9 ng/mL were achieved in 82.3% of patients and were predictable (96% sensitivity, 57% specificity) by CYP2D6 diplotypes with AS > 0.5, i.e., omitting PM/PM and PM/IM patients. Conclusion: The CYP2D6 explanatory power for active drug level assessment is maximized by TAM-specific phenotype assignments while a genotype cutoff that separates PM/PM and PM/IM from the remaining patients may improve clinical benefit via increased endoxifen concentrations.

CYP450 genotype and pharmacogenetic association studies: a critical appraisal

Despite strong pharmacological support, association studies using genotype-predicted phenotype as a variable have yielded conflicting or inconclusive evidence to promote personalized pharmacotherapy. Unless the patient is a genotypic poor metabolizer, imputation of patient's metabolic capacity (or metabolic phenotype), a major factor in drug exposure-related clinical response, is a complex and highly challenging task because of limited number of alleles interrogated, population-specific differences in allele frequencies, allele-specific substrate-selectivity and importantly, phenoconversion mediated by co-medications and inflammatory co-morbidities that modulate the functional activity of drug metabolizing enzymes. Furthermore, metabolic phenotype and clinical outcomes are not binary functions; there is large intragenotypic and intraindividual variability. Therefore, the ability of association studies to identify relationships between genotype and clinical outcomes can be greatly enhanced by determining phenotype measures of study participants and/or by therapeutic drug monitoring to correlate drug concentrations with genotype and actual metabolic phenotype. To facilitate improved analysis and reporting of association studies, we propose acronyms with the prefixes ‘g’ (genotype-predicted phenotype) and ‘m’ (measured metabolic phenotype) to better describe this important variable of the study subjects. Inclusion of actually measured metabolic phenotype, and when appropriate therapeutic drug monitoring, promises to reveal relationships that may not be detected by using genotype alone as the variable.

Genotype and co-medication dependent CYP2D6 metabolic activity: effects on serum concentrations of aripiprazole, haloperidol, risperidone, paliperidone and zuclopenthixol

PURPOSE

Therapeutic drug monitoring (TDM) of antipsychotics can aid in therapy optimization, explaining adverse effects or non-response. One reason for therapeutic failure or adverse effects is caused by genetic variations in the cytochrome P450 drug-metabolizing genes. The aim of this study was to evaluate the impact of CYP2D6 polymorphisms on steady-state serum concentrations of antipsychotics metabolized by CYP2D6, taking into account the co-medication with CYP2D6 inhibitors.

METHODS

Serum and EDTA samples were collected from 82 psychiatric patients. After a liquid-liquid extraction, serum samples were analyzed using an ultra-high performance liquid chromatography-tandem mass spectrometric (UHPLC-MS/MS) method for quantification of the antipsychotics. CYP2D6 genotyping was performed using the Luminex xTAG® CYP2D6 Kit v3 (Luminex Corporation). Patients were divided into five phenotype subgroups by calculation of the activity score (AS): poor metabolizers (PM; AS 0), intermediate metabolizers (IM; AS 0.5-1), extensive metabolizers with slow activity (EM-s; AS 1-1.5), extensive metabolizers with fast activity (EM-f; AS 2), and ultra-rapid metabolizers (UM; AS >2). The influence of the phenotypes on the concentration-to-dose and metabolite-to-parent ratios was evaluated.

RESULTS

Overall, 6.1 % UM (n = 5), 25.6 % EM-f (n = 21), 46.3 % EM-s (n = 38), 1.2 % EM-s/EM-f (n = 1), 6.1 % IM (n = 5), and 14.6 % PM (n = 12) were found, taking co-administration of strong and moderate CYP2D6 inhibitors into account (phenoconversion). It was demonstrated that CYP2D6 polymorphisms affect the serum concentrations of aripiprazole (n = 18), haloperidol (n = 11), risperidone (n = 20), and zuclopenthixol (n = 6), while no influence was seen on the paliperidone serum concentrations (n = 31).

CONCLUSIONS

Even with a small number of patients per antipsychotic, the importance of CYP2D6 genotyping was still clearly stated. This study illustrates the high potential of combining TDM and CYP2D6 genotyping in clinical practice.

miRNA-27b levels are associated with CYP3A activity in vitro and in vivo

Previous in vitro studies have shown that microRNA‐27b (miR‐27b) may regulate mRNA levels of CYP3A4, vitamin D receptor (VDR), and Peroxisome proliferator‐activated receptor α (PPARα) as well as CYP3A4 protein expression and activity. In vitro studies have also shown that vitamin D may affect the expression of CYP3A4. The primary aim of this pilot study was to investigate the association between miR‐27b and CYP3A expression and activity. The secondary aim was to investigate the association between 25‐hydroxy vitamin D in serum and CYP3A activity. Mi‐RNA‐27b was quantified using real‐time PCR in serum samples (n = 28) and 25‐hydroxyvitamin D was measured and correlated with the levels of the endogenous CYP3A activity marker 4β‐hydroxycholesterol. In addition, the correlation between miR‐27b and CYP3A activity, measured by dextromethorphan N‐demethylation and 6β‐hydroxylation of testosterone and the gene expression of CYP3A4, VDR and PPARα were assessed in 20 human liver samples. A significant association between circulatory miR‐27b levels and 4β‐hydroxycholesterol ratio was found; P = 0.04, and between hepatic miR‐27b levels and CYP3A activity, measured by dextromethorphan N‐demethylation in human liver (P = 0.04). There was no association between hepatic miR‐27b and mRNA levels of CYP3A4, VDR or PPARα. There was a significant association between serum 25‐hydroxyvitamin D levels and 4β‐hydroxycholesterol ratio, P = 0.002. In conclusion, this pilot‐study supports the hypothesis that miR‐27b levels as well as 25‐hydroxyvitamin D may affect CYP3A activity in vivo. The results indicate that miR‐27b exerts its inhibitory effect on a translational level rather than affecting mRNA levels.