Identification of ω- or (ω-1)-Hydroxylated Medium-Chain Acylcarnitines as Novel Urinary Biomarkers for CYP3A Activity

Plasma metabolomic profiling reveals factors associated with dose-adjusted trough concentration of tacrolimus in liver transplant recipients

Inter- and intrapatient variability of tacrolimus exposure is a vital prognostic risk factor for the clinical outcome of liver transplantation. New factors or biomarkers characterizing tacrolimus disposition is essential for optimal dose prediction in recipients of liver transplant. The aim of the study was to identify potential plasma metabolites associated with the dose-adjusted trough concentration of tacrolimus in liver transplant recipients by using a global metabolomic approach. A total of 693 plasma samples were collected from 137 liver transplant recipients receiving tacrolimus and regular therapeutic drug monitoring. Untargeted metabolomic analysis was performed by ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry. Univariate and multivariate analyses with a mixed linear model were conducted, and the results showed that the dose-adjusted tacrolimus trough concentration was associated with 31 endogenous metabolites, including medium- and long-chain acylcarnitines such as stearoylcarnitine (β = 0.222, p = 0.001), microbiota-derived uremic retention solutes such as indolelactic acid (β = 0.194, p = 0.007), bile acids such as taurohyodeoxycholic acid (β = -0.056, p = 0.002), and steroid hormones such as testosterone (β = 0.099, p = 0.001). A multiple linear mixed model including 11 metabolites and clinical information was established with a suitable predictive performance (correlation coefficient based on fixed effects = 0.64 and correlation coefficient based on fixed and random effects = 0.78). These data demonstrated that microbiota-derived uremic retention solutes, bile acids, steroid hormones, and medium- and long-chain acylcarnitines were the main metabolites associated with the dose-adjusted trough concentration of tacrolimus in liver transplant recipients.

METABOLOMICS REVEALS BIOMARKERS IN HUMAN URINE AND PLASMA TO PREDICT CYP2D6 ACTIVITY

Background and Purpose

Individualized assessment of cytochrome P450 2D6 (CYP2D6) activity is usually performed through phenotyping following administration of a probe drug to measure the enzyme's activity. To avoid any iatrogenic harm (allergic drug reaction, dosing error) related to the probe drug, the development of non‐burdensome tools for real‐time phenotyping of CYP2D6 could significantly contribute to precision medicine. This study focuses on the identification of markers of the CYP2D6 enzyme in human biofluids using an LC‐high‐resolution mass spectrometry‐based metabolomic approach.

Experimental Approach

Plasma and urine samples from healthy volunteers were analysed before and after intake of a daily dose of paroxetine 20 mg over 7 days. CYP2D6 genotyping and phenotyping, using single oral dose of dextromethorphan 5 mg, were also performed in all participants.

Key Results

We report four metabolites of solanidine and two unknown compounds as possible novel CYP2D6 markers. Mean relative intensities of these features were significantly reduced during the inhibition session compared with the control session (n = 37). Semi‐quantitative analysis showed that the largest decrease (−85%) was observed for the ion m/z 432.3108 normalized to solanidine (m/z 398.3417). Mean relative intensities of these ions were significantly higher in the CYP2D6 normal–ultrarapid metabolizer group (n = 37) compared with the poor metabolizer group (n = 6). Solanidine intensity was more than 15 times higher in CYP2D6‐deficient individuals compared with other volunteers.

Conclusion and Implications

The applied untargeted metabolomic strategy identified potential novel markers capable of semi‐quantitatively predicting CYP2D6 activity, a promising discovery for personalized medicine.

Tertiary Oxidation of Deoxycholate Is Predictive of CYP3A Activity in Dogs

Deoxycholic acid (DCA, 3α, 12α-dihydroxy-5β-cholan-24-oic acid) is the major circulating secondary bile acid, which is synthesized by gut flora in the lower gut and selectively oxidized by CYP3A into tertiary metabolites, including 1β,3α,12α-trihydroxy-5β-cholan-24-oic acid (DCA-1β-ol) and 3α,5β,12α-trihydroxy-5β-cholan-24-oic acid (DCA-5β-ol) in humans. Since DCA has the similar exogenous nature and disposition mechanisms as xenobiotics, this work aimed to investigate whether the tertiary oxidations of DCA are predictive of in vivo CYP3A activities in beagle dogs. In vitro metabolism of midazolam (MDZ) and DCA in recombinant canine CYP1A1, 1A2, 2B11, 2C21, 2C41, 2D15, 3A12, and 3A26 enzymes clarified that CYP3A12 was primarily responsible for either the oxidation elimination of MDZ or the regioselective oxidation metabolism of DCA into DCA-1β-ol and DCA-5β-ol in dog liver microsomes. Six male dogs completed the CYP3A intervention studies including phases of baseline, inhibition (ketoconazole treatments), recovery, and induction (rifampicin treatments). The oral MDZ clearance after a single dose was determined on the last day of the baseline, inhibition, and induction phases, and subjected to correlation analysis with the tertiary oxidation ratios of DCA detected in serum and urine samples. The results confirmed that the predosing serum ratios of DCA oxidation, DCA-5β-ol/DCA, and DCA-1β-ol/DCA were significantly and positively correlated both intraindividually and interindividually with oral MDZ clearance. It was therefore concluded that the tertiary oxidation of DCA is predictive of CYP3A activity in beagle dogs. Clinical transitional studies following the preclinical evidence are promising to provide novel biomarkers of the enterohepatic CYP3A activities. SIGNIFICANCE STATEMENT: Drug development, clinical pharmacology, and therapeutics are under insistent demands of endogenous CYP3A biomarkers that avoid unnecessary drug exposure and invasive sampling. This work has provided the first proof-of-concept preclinical evidence that the CYP3A catalyzed tertiary oxidation of deoxycholate, the major circulating secondary bile acid synthesized in the lower gut by bacteria, may be developed as novel in vivo biomarkers of the enterohepatic CYP3A activities.

The 1β-Hydroxy-Deoxycholic Acid to Deoxycholic Acid Urinary Metabolic Ratio: Toward a Phenotyping of CYP3A Using an Endogenous Marker?

In this study, we assessed the potential use of the 1β-hydroxy-deoxycholic acid (1β-OH-DCA) to deoxycholic acid (DCA) urinary metabolic ratio (UMR) as a CYP3A metric in ten male healthy volunteers. Midazolam (MDZ) 1 mg was administered orally at three sessions: alone (control session), after pre-treatment with fluvoxamine 50 mg (12 h and 2 h prior to MDZ administration), and voriconazole 400 mg (2 h before MDZ administration) (inhibition session), and after a 7-day pre-treatment with the inducer rifampicin 600 mg (induction session). The 1β-OH-DCA/DCA UMR was measured at each session, and correlations with MDZ metrics were established. At baseline, the 1β-OH-DCA/DCA UMR correlated significantly with oral MDZ clearance (r = 0.652, p = 0.041) and C_max (r = -0.652, p = 0.041). In addition, the modulation of CYP3A was reflected in the 1β-OH-DCA/DCA UMR after the intake of rifampicin (induction ratio = 11.4, p < 0.01). During the inhibition session, a non-significant 22% decrease in 1β-OH-DCA/DCA was observed (p = 0.275). This result could be explained by the short duration of CYP3A inhibitors intake fixed in our clinical trial. Additional studies, particularly involving CYP3A inhibition for a longer period and larger sample sizes, are needed to confirm the 1β-OH-DCA/DCA metric as a suitable CYP3A biomarker.

Development and validation of a method for the simultaneous quantification of endogenous steroids metabolized by CYP3A

Cytochrome P450 (CYP) 3A enzymes, the most important phase 1 drug-metabolizing enzymes, are responsible for 50% of the metabolism of clinically used drugs. CYP3A activity varies widely among individuals, which can affect the probability of adverse drug reactions and drug-drug interactions mediated by the induction or inhibition of the enzyme. Hence, it is important to be able to predict CYP3A activity in individuals to reduce the incidence of unexpected drug responses. To specifically and quickly measure CYP3A activity, we developed method based on gas chromatography interfaced with triple-quadrupole mass spectrometry for the quantification of cortisol, cortisone, 6β-hydroxycortisol, and 6β-hydroxycortisone simultaneously in urine and 4β-hydroxycholesterol in plasma. The results were calculated based on charcoal-stripped steroid-free urine and plasma control samples. The accuracy and precision were 93.18% to 110.0% and 1.96% to 5.34%, respectively. This method was then applied to measure endogenous steroids from urine and plasma samples of healthy Korean males and females. The calibration curves of all analytes showed good linearity with a correlation coefficient (r²) that ranged from 0.9953 to 0.9999. Therefore, this validated method can be used to measure endogenous biomarkers to predict CYP3A activity and might be applicable in the prediction of CYP3A-mediated drug interactions of new drug candidates.

Perspectives from the Innovation and Quality Consortium Induction Working Group on Factors Impacting Clinical Drug-Drug Interactions Resulting from Induction: Focus on Cytochrome 3A Substrates

A recent publication from the Innovation and Quality Consortium Induction Working Group collated a large clinical data set with the goal of evaluating the accuracy of drug-drug interaction (DDI) prediction from in vitro data. Somewhat surprisingly, comparison across studies of the mean- or median-reported area under the curve ratio showed appreciable variability in the magnitude of outcome. This commentary explores the possible drivers of this range of outcomes observed in clinical induction studies. While recommendations on clinical study design are not being proposed, some key observations were informative during the aggregate analysis of clinical data. Although DDI data are often presented using median data, individual data would enable evaluation of how differences in study design, baseline expression, and the number of subjects contribute. Since variability in perpetrator pharmacokinetics (PK) could impact the overall DDI interpretation, should this be routinely captured? Maximal induction was typically observed after 5-7 days of dosing. Thus, when the half-life of the inducer is less than 30 hours, are there benefits to a more standardized study design? A large proportion of CYP3A4 inducers were also CYP3A4 inhibitors and/or inactivators based on in vitro data. In these cases, using CYP3A selective substrates has limitations. More intensive monitoring of changes in area under the curve over time is warranted. With selective CYP3A substrates, the net effect was often inhibition, whereas less selective substrates could discern induction through mechanisms not susceptible to inhibition. The latter included oral contraceptives, which raise concerns of reduced efficacy following induction. Alternative approaches for modeling induction, such as applying biomarkers and physiologically based pharmacokinetic modeling (PBPK), are also considered. SIGNIFICANCE STATEMENT: The goal of this commentary is to stimulate discussion on whether there are opportunities to optimize clinical drug-drug interaction study design. The overall aim is to reduce, understand and contextualize the variability observed in the magnitude of induction across reported clinical studies. A large clinical CYP3A induction dataset was collected and further analyzed to identify trends and gaps. Reporting individual victim PK data, characterizing perpetrator PK and including additional PK assessments for mixed-mechanism perpetrators may provide insights into how these factors impact differences observed in clinical outcomes. The potential utility of biomarkers and PBPK modeling are discussed in considering future directions.

Quantitative prediction of hepatic CYP3A activity using endogenous markers in healthy subjects after administration of CYP3A inhibitors or inducers

Accurate prediction of cytochrome P450 (CYP) 3A activity in the early stage of drug development and in clinical practice is important. This study aimed to evaluate the previously constructed CYP3A activity prediction model after administration of CYP3A inhibitors and inducers and to modify the model for better prediction of CYP3A activity. Healthy male subjects received the following study drugs during three study periods: midazolam alone (control phase); midazolam with 200 mg of itraconazole (CYP3A inhibition phase); and midazolam with 150 mg of rifampicin (CYP3A induction phase). We quantified the concentrations of several endogenous CYP3A markers in both urine and plasma using gas chromatography-mass spectrometry. The urinary markers, including 6β-hydroxy (OH)-cortisol/cortisol, 6β-OH-cortisone/cortisone, 16α-OH-dehydroepiandrosterone (DHEA)/DHEA, 16α-OH-androstenedione (A-dione)/A-dione and 7β-OH-DHEA/DHEA, were significantly correlated with midazolam clearance in both the CYP3A inhibition and induction phases. We constructed a statistical prediction model after integrating data from a previous study to predict midazolam clearance as follows: Ln(midazolam clearance) = 2.5545 + 0.3988 × ln(7β-OH-DHEA/DHEA) + 0.1984 × ln(16α-OH-DHEA/DHEA) + 0.5031 × ln(6β-OH-cortisol/cortisol) - 0.1261 [ln(7β-OH-DHEA/DHEA) × ln(6β-OH-cortisol/cortisol)] (r² = 0.75). We suggest that quantitating endogenous markers in vivo coupled with the statistical prediction model may be useful for predicting CYP3A parameters.

Utility of Integrated Analysis of Pharmacogenomics and Pharmacometabolomics in Early Phase Clinical Trial: A Case Study of a New Molecular Entity

In this report, we present a case study of how pharmacogenomics and pharmacometabolomics can be useful to characterize safety and pharmacokinetic profiles in early phase new drug development clinical trials. During conducting a first-in-human trial for a new molecular entity, we were able to determine the mechanism of dichotomized variability in plasma drug concentrations, which appeared closely related to adverse drug reactions (ADRs) through integrated omics analysis. The pharmacogenomics screening was performed from whole blood samples using the Affymetrix DMET (Drug-Metabolizing Enzymes and Transporters) Plus microarray, and confirmation of genetic variants was performed using real-time polymerase chain reaction. Metabolomics profiling was performed from plasma samples using liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. A GSTM1 null polymorphism was identified in pharmacogenomics test and the drug concentrations was higher in GSTM1 null subjects than GSTM1 functional subjects. The apparent drug clearance was 13-fold lower in GSTM1 null subjects than GSTM1 functional subjects (p < 0.001). By metabolomics analysis, we identified that the study drug was metabolized by cysteinylglycine conjugation in GSTM functional subjects but those not in GSTM1 null subjects. The incidence rate and the severity of ADRs were higher in the GSTM1 null subjects than the GSTM1 functional subjects. Through the integrated omics analysis, we could understand the mechanism of inter-individual variability in drug exposure and in adverse response. In conclusion, integrated multi-omics analysis can be useful for elucidating the various characteristics of new drug candidates in early phase clinical trials.