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Record W2289967391 · doi:10.1111/bcpt.12536

Effect of Omeprazole and Dextromethorphan on the Urinary Metabolic Ratio of Flurbiprofen

2015· article· en· W2289967391 on OpenAlexaboutno aff
Silvia Vogl, Matthias Steinfath, Werner K. Lutz, Gilbert Schönfelder

Bibliographic record

VenueBasic & Clinical Pharmacology & Toxicology · 2015
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsnot available
Fundersnot available
KeywordsDextromethorphanOmeprazoleFlurbiprofenCYP2C19PharmacologyCYP2C9CYP2D6DrugDrug metabolismMedicineCYP3A4Cytochrome P450Drug interactionDextrorphanPharmacogeneticsInternal medicineChemistryMetabolismGenotypeBiochemistry

Abstract

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Interindividual differences in drug response – especially due to drug metabolism – are among the most important reasons for severe adverse drug reactions (ADR) in patients. About 80% of drugs causing clinically relevant ADR are metabolized by polymorphic enzymes 1. The most important human enzymes for oxidative drug metabolism belong to the cytochrome P450 (CYP) monooxygenase superfamily. Several CYP possess high levels of genetic polymorphism and can be induced or inhibited, thereby causing pronounced interindividual differences in enzyme activity and drug response. The assessment of CYP activity (phenotyping) of a patient before drug treatment might minimize the occurrence of ADR and treatment failures. In the last decades, CYP phenotyping procedures were simplified by combining up to five probe drugs into a so-called probe drug cocktail 2-8. Two of these, the Pittsburgh and the Geneva cocktail, use flurbiprofen (FLB) as CYP2C9 probe drug 8-10. It was recently shown that the metabolic ratio of FLB measured in plasma 2 hr after administration was not influenced by a combination of flurbiprofen with caffeine, omeprazole, dextromethorphan and midazolam 9. As urine can also be used for CYP2C9 phenotyping 3, we aimed to verify whether the urinary measure is also unaffected by concomitant administration of the probe drugs dextromethorphan (CYP2D6) or omeprazole (CYP2C19). The study was approved by the Medical Faculty's Ethical Committee of Würzburg University and included 23 volunteers of Western European descent with age ranges from 21 to 31 years (19 female individuals) and 22 to 26 years (four male individuals). All individuals were of good health, did not ingest any drugs with known influence on flurbiprofen (FLB) metabolism and gave informed written consent. At the first session, after voiding the bladder, the volunteers ingested 8.75 mg FLB as lozenge (Dobendan Direkt® lozenges; Boots Healthcare, Hamburg, Germany). At the second session after 1 week, volunteers were given 8.75 mg FLB together with 10 mg dextromethorphan in water (as dextromethorphan hydrobromide monohydrate; Fagron, Barsbüttel, Germany). After another 1-week washout period, 8.75 mg FLB was administered together with 20 mg omeprazole as enteric coated tablet (Gastracid®; AWD.pharma, Radebeul, Germany). On all study days, urine was collected for 2 hr after drug administration. The amount of urine was determined and aliquots were stored at −20°C. A sample of venous blood was taken from each participant for CYP2C9 genotyping. Flurbiprofen and its CYP2C9-dependent metabolite 4′-hydroxyflurbiprofen (OHF) were analysed as previously published 11. A metabolic ratio (MR) was calculated for all individuals by dividing the urinary concentration of OHF by the concentration of FLB: MR = [OHF]/[FLB]. This is the originally described formula to calculate MRFLB, which is reciprocal to the commonly used MR for dextromethorphan (DEX) 3. DEX and its CYP2D6-dependent metabolite dextrorphan (DOR) were analysed using LC-MS/MS. Standard solutions, urine standard samples and sample preparation were performed as previously published 12. Dextromethorphan-d3 and dextrorphan-d3 (TRC, Toronto, Canada) were used as internal standards, and isocratic chromatography was performed with water/acetonitrile 70/30 (v/v) containing 0.1% formic acid. The metabolic ratio MRDEX was obtained by dividing the urinary concentration of DEX by the concentration of DOR: MR = [DEX]/[DOR]. The logarithmic metabolic ratio (log10MRDEX), which is the commonly used phenotyping metric for dextromethorphan (CYP2D6), was calculated for all individuals. Findings of preliminary stability studies for omeprazole (OME) and its CYP2C19-dependent metabolite 5′-OH-omeprazole (OHOME) suggest that urinary MROME cannot be used as a reliable phenotyping metric (own unpublished data). This is due to interindividual differences in urinary pH value and the different pH-dependent half-lives of OME and OHOME in urine. Therefore, MROME (CYP2C19 phenotyping metric) should be determined in plasma. However, timed blood sampling was not part of this study design, and OME and its CYP2C19-dependent metabolite OHOME were not analysed. Genotyping in peripheral blood for CYP2C9*2 (3608C>T, position referring to NCBI Reference Sequence: NG_008385.1) and CYP2C9*3 (42614A>C) was performed as previously described 11. All alleles that were negative for the nucleotide substitutions at position 3608 (*2) and 42614 (*3) were presumed to represent CYP2C9*1. Statistical analyses were performed using GraphPad Prism Software version 5 (GraphPad Software, La Jolla California USA) or R (R Core Team, 2015, http://www.R-project.org). Pharmacokinetic interaction was tested on the basis of geometric mean ratios, and respective 90% confidence intervals were calculated from the t-distribution. Geometric mean ratios for MR, total amount of FLB and OHF in urine were calculated as ratios of the geometric means obtained after administration of FLB alone to those obtained after administration of FLB with either dextromethorphan or omeprazole. For the MRs, results are presented as the mean ± S.D. Exact p-values of the Wilcoxon test were calculated with the R function wilcox.test. Paired Wilcoxon signed rank tests were two-tailed, and a probability of p < 0.05 was considered significant. To test for correlation, Pearson correlation was calculated using the R function cor.test and the result was shown as the 95% confidence interval (CI) of the correlation coefficient. The study cohort consisted of 17 individuals with genotype CYP2C9*1/*1, five individuals with CYP2C9*1/*2 and one individual with CYP2C9*1/*3 genotype. It was shown by Zgheib et al. that the correlation between the urinary metabolic ratio of FLB and the OHF formation clearance, calculated as the total amount of OHF recovered in urine (24 hr) divided by the 24-hr FLB area under the curve (AUC0–24), is comparable between the urine collection intervals of 0–2 and 0–8 hr after drug administration 3. We therefore used 2-hr flurbiprofen (FLB) urinary MR for CYP2C9 phenotyping, as it resulted in a more practicable working schedule. The 2-hr urinary MR for flurbiprofen (MRFLB) was 1.13 ± 0.32 for all genotypes with values of 1.26 ± 0.31 and 1.04 ± 0.15 for CYP2C9*1/*1 and CYP2C9*1/*2, respectively. As expected, the carrier of the CYP2C9 *1/*3 genotype showed the lowest MRFLB under all conditions (0.53 for FLB alone). Co-administration of dextromethorphan did not have a statistically significant effect on the urinary FLB MRFLB (fig. 1, centre versus left). The MRFLB in combination with dextromethorphan increased in 11 individuals (solid lines) and decreased in 12 individuals (broken lines). Additionally, we tested whether the increase or decrease of the individual MRFLB values measured after DEX co-administration was associated with the CYP2D6 phenotype of the individual. The Pearson correlation coefficient for a correlation of the differences of MRFLB (with DEX) minus MRFLB (without DEX) with log10MRDEX/DOR revealed no correlation (95% CI −0.505 to 0.310). For bioequivalence studies, it is generally acknowledged that a variation of pharmacokinetic parameters of two formulations of an active ingredient of less than 20% is not considered clinically relevant 13. To reflect this, an acceptance interval of 80–125% for the 90% confidence intervals (CI) for the ratio of geometric means was used to test for relevant pharmacokinetic interactions of the probe drugs. Values were 1.14 ± 0.36, the ratio of the geometric means (FLB-DEX combination versus FLB alone) was 96%, and its 90% CI was 91–102%. It can therefore be assumed that there is no relevant influence of DEX on this FLB pharmacokinetic parameter. Combination of FLB with omeprazole resulted in a significant increase of the overall MRFLB of the cohort (MRFLB = 1.41 ± 0.32). As depicted in the right part of fig. 1, 22 individuals showed an increased MRFLB after co-administration of omeprazole (solid lines); only 1 (genotype: CYP2C9*1/*1) had a smaller value (broken line). A paired Wilcoxon signed rank test resulted in the rejection of the hypothesis that the impact of omeprazole on the MRFLB (+0.28) could have been due to chance (p-value = 0.00004). Significance holds also for the subgroup with the CYP2C9*1/*1 genotype (p-value = 0.001). While all carriers of the two other genotypes showed increased MRFLB after co-administration of omeprazole, statistical significance could not be shown due to small group numbers. As the MRFLB is a ratio of OHF/FLB concentrations, we tested whether the observed increase of MRFLB that resulted from omeprazole co-administration was due to a decrease of FLB amounts or an increase of OHF amounts. No trend was seen for FLB while an increase of OHF amount was found in 18 of 23 individuals after omeprazole co-administration (p-value = 0.0027). Significance also holds for the subgroup of the CYP2C9*1/*1 genotype (p-value = 0.017) as well as for females alone (p-value = 0.014). It is known that OME is not only a substrate but also a potent inhibitor of CYP2C19 14. OME also appears to inhibit CYP3A4 in vivo, based, for example, on a 90% increase in carbamazepine AUC 15, 16. The enhanced excretion of OHF might therefore be due to the inhibition of competing metabolic pathways of FLB. CYP2C9 enzyme induction is not likely to be responsible for the higher amount of OHF in urine, as enzyme induction is supposed to take hours to days before an effect can be seen 17. The effect of omeprazole on OHF amounts was not observed in 2-hr blood samples, as described by Bosilkovska et al. 9. The difference may be due to different analytical methods: while we conducted an acyl glucuronide cleavage prior to FLB and OHF measurement, Bosilkovska et al. 9 only measured unconjugated FLB and OHF. UDP-glucuronosyltransferase (UGT) 2B7 and UGT1A9, which are responsible for the glucuronidation of FLB, are genetically polymorphic 18. It is very likely that OHF is also glucuronidated by these UGT. The effect of omeprazole on FLB metabolism might therefore be masked by different rates of FLB and OHF glucuronidation when only unconjugated FLB and OHF are measured. Under the given experimental conditions, co-administration of omeprazole had a small but clear effect on the 2-hr urinary amounts of OHF and hence the MRFLB. The 90% CI of the ratio of the geometric means for MRFLB (with/without OME) was between 115% and 127% and therefore outside the acceptance interval of 80–125%. In our study, the 2-hr urinary MRFLB measured after administration of FLB alone and in combination with OME could not be considered equivalent. This finding suggests that a phenotyping cocktail containing flurbiprofen and omeprazole might give falsified results for the urinary MRFLB and therefore the CYP2C9 phenotyping metric. However, there are limitations to our study, and our results should therefore be considered preliminary. We only detected FLB and OHF in urine, and data about the systemic AUC for FLB were not included. Even though Zgheib et al. showed that there is a good correlation between the 2-hr urinary MRFLB and the OHF formation clearance, further studies with more extensive pharmacokinetic data for flurbiprofen (i.e. AUC) should be conducted to confirm our findings.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.207
GPT teacher head0.518
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2015
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