Studies on CYP2C8-mediated drug interactions

Useiden lääkkeiden yhtäaikainen käyttö on nykyään hyvin yleistä, mikä lisää lääkeaineiden haitallisten yhteisvaikutusten riskiä. Lääkeaineiden poistumisessa elimistöstä ovat tärkeässä osassa niitä hajottavat (metaboloivat) maksan sytokromi P450 (CYP) entsyymit. Vasta aivan viime vuosina on havaittu, että CYP2C8-entsyymillä voi olla tärkeä merkitys mm. lääkeaineyhteisvaikutuksissa. Eräät lääkeaineet voivat estää (inhiboida) CYP2C8-entsyymin kautta tapahtuvaa metaboliaa. Tässä työssä selvitettiin CYP2C8-entsyymiä estävien lääkkeiden vaikutusta sellaisten lääkeaineiden pitoisuuksiin, joiden aikaisemman tiedon perusteella arveltiin metaboloituvan CYP2C8-välitteisesti. Näiden lääkeaineiden metaboliaa tutkittiin myös koeputkiolosuhteissa (in vitro -menetelmillä). Lisäksi CYP2C8-entsyymiä estävän lipidilääke gemfibrotsiilin yhteisvaikutusmekanismia tutkittiin selvittämällä interaktion säilymistä koehenkilöillä gemfibrotsiilin annostelun lopettamisen jälkeen. Yhteisvaikutuksia tutkittiin terveillä vapaaehtoisilla koehenkilöillä käyttäen vaihtovuoroista koeasetelmaa. Koehenkilöille annettiin CYP2C8-entsyymiä estävää lääkitystä muutaman päivän ajan ja tämän jälkeen kerta-annos tutkimuslääkettä. Koehenkilöiltä otettiin useita verinäytteitä, joista määritettiin lääkepitoisuudet nestekromatografisilla tai massaspektrometrisillä menetelmillä. Gemfibrotsiili nosti ripulilääke loperamidin pitoisuudet keskimäärin kaksinkertaiseksi. Gemfibrotsiili lisäsi, mutta vain hieman, kipulääke ibuprofeenin pitoisuuksia, eikä sillä ollut mitään vaikutusta unilääke tsopiklonin pitoisuuksiin toisin kuin aiemman kirjallisuuden perusteella oli odotettavissa. Toinen CYP2C8-estäjä, mikrobilääke trimetopriimi, nosti diabeteslääke pioglitatsonin pitoisuuksia keskimäärin noin 40 %. Gemfibrotsiili nosti diabeteslääke repaglinidin pitoisuudet 7-kertaiseksi ja tämä yhteisvaikutus säilyi lähes yhtä voimakkaana vielä 12 tunnin päähän viimeisestä gemfibrotsiiliannoksesta. Tehdyt havainnot ovat käytännön lääkehoidon kannalta merkittäviä ja ne selvittävät CYP2C8-entsyymin merkitystä useiden lääkkeiden metaboliassa. Gemfibrotsiilin tai muiden CYP2C8-entsyymiä estävien lääkkeiden yhteiskäyttö loperamidin kanssa voi lisätä loperamidin tehoa tai haittavaikutuksia. Toisaalta CYP2C8-entsyymin osuus tsopiklonin ja ibuprofeenin metaboliassa näyttää olevan pieni. Trimetopriimi nosti kohtalaisesti pioglitatsonin pitoisuuksia, ja kyseisten lääkkeiden yhteiskäyttö voi lisätä pioglitatsonin annosriippuvaisia haittavaikutuksia. Gemfibrotsiili-repaglinidi-yhteisvaikutuksen päämekanismi in vivo näyttää olevan CYP2C8-entsyymin palautumaton esto. Tämän vuoksi gemfibrotsiilin estovaikutus ja yhteisvaikutusriski säilyvät pitkään gemfibrotsiilin annostelun lopettamisen jälkeen, mikä tulee ottaa huomioon käytettäessä sitä CYP2C8-välitteisesti metaboloituvien lääkkeiden kanssa.Cytochrome P450 (CYP) 2C8 is involved in the metabolism of several clinically used drugs, including paclitaxel, repaglinide and rosiglitazone. Drug interactions caused by inhibition or induction of CYP2C8 can cause considerable variation in the effective exposure to its substrates. The aim of this work was to investigate the effect of model inhibitors of CYP2C8 on the pharmacokinetics of loperamide, zopiclone, ibuprofen and pioglitazone, in order to characterise the role of CYP2C8 in their metabolism. Gemfibrozil and trimethoprim were used as model inhibitors of CYP2C8. In addition, the effect of the CYP2C8*3 allele on the pharmacokinetics of pioglitazone was investigated. Finally, the effect of dosing interval between gemfibrozil and repaglinide was studied in relation to the gemfibrozil-repaglinide interaction. Studies I to V were randomised crossover studies with 2 to 5 phases. 10 to 16 healthy volunteers participated in each study. Pre-treatment with a clinically relevant dose of inhibitor (gemfibrozil, itraconazole or trimethoprim) was followed by a single oral dose of the study drug (loperamide, zopiclone, ibuprofen, pioglitazone or repaglinide). Thereafter, blood and urine samples were collected for the determination of drug concentrations. The pharmacodynamics of loperamide and zopiclone were assessed by psychomotor tests and subjective evaluations, and that of repaglinide by blood glucose measurements. Additionally, the metabolism of zopiclone and pioglitazone was studied in vitro in studies II and IV. Gemfibrozil, itraconazole and their combination raised the area under the concentration-time curve (AUC) of loperamide 2.2- (P < 0.05), 3.8- (P < 0.001) and 12.6-fold (P < 0.001), respectively, compared to placebo. Gemfibrozil had no effect on the pharmacokinetics of parent zopiclone. On the other hand, gemfibrozil raised the AUC of R-ibuprofen by 34% (P < 0.001) and increased its elimination half-life (t½) from 2.9 to 4.5 hours (P < 0.001), with only minor effects on the S-enantiomer of ibuprofen. Trimethoprim raised the AUC of pioglitazone by 42% (P < 0.001) and prolonged its dominant t½ from 3.9 to 5.1 hours (P < 0.001), but had no effect on its peak plasma concentration (Cmax). The CYP2C8*3 allele was associated with a decreased AUC of pioglitazone compared to the subjects with the reference genotype (CYP2C8*1/*1), and after correction for weight, this difference was statistically significant (P < 0.05). The gemfibrozil-repaglinide interaction persisted up to a 12 hour dosing interval between gemfibrozil and repaglinide. Gemfibrozil ingested simultaneously with or 3, 6, or 12 hours before repaglinide increased repaglinide AUC0-∞ 7.0-, 6.5-, 6.2- and 5.0-fold, respectively (P < 0.001), and the Cmax of repaglinide increased about two-fold in all gemfibrozil phases (P < 0.001), compared to control. During repaglinide administration, the mean blood glucose concentration from 0 to 9 hours decreased in each of the gemfibrozil phases, compared to control (P < 0.005), whereas the pharmacodynamics of loperamide and zopiclone were not affected by the pre-treatment drugs. In vitro, zopiclone (500 nM) elimination was not affected by the CYP2C8 inhibitors montelukast and gemfibrozil, but the CYP3A4 inhibitors itraconazole and ketoconazole markedly inhibited its elimination. Pioglitazone metabolite M-IV formation was inhibited by trimethoprim in pooled human liver microsomes (HLM) and recombinant human CYP2C8 (rhCYP2C8). At clinically relevant concentrations of pioglitazone, CYP2C8 was predominantly responsible for M-IV formation, whereas at higher concentrations the role of CYP3A4 increased. These studies clarify the role of CYP2C8 in the metabolism of several drugs. The concentrations of loperamide and R-ibuprofen were found to be increased by the CYP2C8 inhibitor gemfibrozil, indicating that CYP2C8 participates in the metabolism of these drugs in vivo. On the other hand, the metabolism of zopiclone at clinically relevant concentrations was not affected in vivo or in vitro by CYP2C8 inhibition. Trimethoprim moderately raised the plasma concentrations of pioglitazone by inhibiting its CYP2C8-mediated biotransformation. In addition, the CYP2C8*3 allele was associated with increased metabolic clearance of pioglitazone in vivo, which is in line with the results of pharmacogenetic studies on repaglinide and rosiglitazone. The inhibitory effect of gemfibrozil on CYP2C8 persists at least 12 hours, strongly suggesting that the main mechanism of the gemfibrozil-repaglinide interaction is irreversible mechanism-based inhibition of CYP2C8

Digoxin use and outcomes after myocardial infarction in patients with atrial fibrillation

Digoxin is used for rate control in atrial fibrillation (AF), but evidence for its efficacy and safety after myocardial infarction (MI) is scarce and mixed. We studied post-MI digoxin use effects on AF patient outcomes in a nationwide registry follow-up study in Finland. Digoxin was used by 18.6% of AF patients after MI, with a decreasing usage trend during 2004-2014. Baseline differences in digoxin users (n = 881) and controls (n = 3898) were balanced with inverse probability of treatment weight adjustment. The median follow-up was 7.4 years. Patients using digoxin after MI had a higher cumulative all-cause mortality (77.4% vs. 72.3%; hazard ratio [HR]: 1.19; confidence interval [CI]: 1.07-1.32; p = 0.001) during a 10-year follow-up. Mortality differences were detected in a subgroup analysis of patients without baseline heart failure (HF) (HR: 1.23; p = 0.019) but not in patients with baseline HF (HR: 1.05; p = 0.413). Cumulative incidences of HF hospitalizations, stroke and new MI were similar between digoxin group and controls. In conclusion, digoxin use after MI is associated with increased mortality but not with HF hospitalizations, new MI or stroke in AF patients. Increased mortality was detected in patients without baseline HF. Results suggest caution with digoxin after MI in AF patients, especially in the absence of HF.Peer reviewe

Translational aspects of cytochrome P450-mediated drug-drug interactions : A case study with clopidogrel

Multimorbidity, polypharmacotherapy and drug interactions are increasingly common in the ageing population. Many drug-drug interactions (DDIs) are caused by perpetrator drugs inhibiting or inducing cytochrome P450 (CYP) enzymes, resulting in alterations of the plasma concentrations of a victim drug. DDIs can have a major negative health impact, and in the past, unrecognized DDIs have resulted in drug withdrawals from the market. Signals to investigate DDIs may emerge from a variety of sources. Nowadays, standard methods are widely available to identify and characterize the mechanisms of CYP-mediated DDIs in vitro. Clinical pharmacokinetic studies, in turn, provide experimental data on pharmacokinetic outcomes of DDIs. Physiologically based pharmacokinetic (PBPK) modelling utilizing both in vitro and in vivo data is a powerful tool to predict different DDI scenarios. Finally, epidemiological studies can provide estimates on the health outcomes of DDIs. Thus, to fully characterize the mechanisms, clinical effects and implications of CYP-mediated DDIs, translational research approaches are required. This minireview provides an overview of translational approaches to study CYP-mediated DDIs, going beyond regulatory DDI guidelines, and an illustrative case study of how the DDI potential of clopidogrel was unveiled by combining these different methods.Peer reviewe

Early statin use and cardiovascular outcomes after myocardial infarction: A population-based case-control study

Background and aimsStatin therapy is a cornerstone of secondary prevention after myocardial infarction (MI). However, many patients do not use statins. We studied the association of not using statin early after MI with adverse outcomes.MethodsConsecutive MI patients admitted to 20 Finnish hospitals (n = 64,401; median age 71) were retrospectively studied. Statin was not used by 17.1% within 90 days after MI discharge (exposure). Differences in baseline features, comorbidities, revascularization, and other evidence-based medications were balanced with propensity score matching, resulting in 10,051 pairs of patients with and without statin. Median follow-up was 5.9 years.ResultsPatients not using statin early after MI had higher all-cause mortality in 1-year (15.8% vs. 11.9%; HR 1.38; CI 1.30–1.46; p ConclusionsLack of statin therapy early after MI is associated with adverse outcomes across the spectrum of MI patients. Results underline the importance of timely statin use after MI.</p

Clinical Studies on Drug-Drug Interactions Involving Metabolism and Transport : Methodology, Pitfalls, and Interpretation

Many drug-drug interactions (DDIs) are based on alterations of the plasma concentrations of a victim drug due to another drug causing inhibition and/or induction of the metabolism or transporter-mediated disposition of the victim drug. In the worst case, such interactions cause more than tenfold increases or decreases in victim drug exposure, with potentially life-threatening consequences. There has been tremendous progress in the predictability and modeling of DDIs. Accordingly, the combination of modeling approaches and clinical studies is the current mainstay in evaluation of the pharmacokinetic DDI risks of drugs. In this paper, we focus on the methodology of clinical studies on DDIs involving drug metabolism or transport. We specifically present considerations related to general DDI study designs, recommended enzyme and transporter index substrates and inhibitors, pharmacogenetic perspectives, index drug cocktails, endogenous substrates, limited sampling strategies, physiologically-based pharmacokinetic modeling, complex DDIs, methodological pitfalls, and interpretation of DDI information.Peer reviewe

Performance of Plasma Coproporphyrin I and III as OATP1B1 Biomarkers in Humans

A previous study in 356 healthy Finnish volunteers showed that glycochenodeoxycholate 3-O-glucuronide (GCDCA-3G) and glycodeoxycholate 3-O-glucuronide (GDCA-3G) are promising biomarkers of organic anion transporting polypeptide 1B1 (OATP1B1). In the same cohort, we now evaluated the performances of two other OATP1B1 biomarkers, coproporphyrin I (CPI) and III (CPIII), and compared them with GCDCA-3G and GDCA-3G. Based on decreased (*5 and *15) and increased (*14 and *20) function SLCO1B1 haplotypes, we stratified the participants to poor, decreased, normal, increased, and highly increased OATP1B1 function groups. Fasting plasma CPI concentration was 68% higher in the poor (95% confidence interval, 44%, 97%; P = 1.74 x 10(-10)), 7% higher in the decreased (0%, 15%; P = 0.0385), 10% lower in the increased (3%, 18%; P = 0.0087), and 23% lower in the highly increased (1%, 40%; P = 0.0387) function group than in the normal function group. CPIII concentration was 27% higher (7%, 51%; P = 0.0071) in the poor function group than in the normal function group. CPI and CPIII detected poor OATP1B1 function with areas under the precision-recall curve (AUPRC) of 0.388 (95% confidence interval, 0.197, 0.689) and 0.0798 (0.0485, 0.203), and receiver operating characteristic curve (AUROC) of 0.888 (0.851, 0.919) and 0.731 (0.682, 0.776). The AUPRC and AUROC of GCDCA-3G were, however, 0.389 (0.258, 0.563) and 0.100 (-0.0046, 0.204; P = 0.0610) larger than those of CPI, and 0.697 (0.555, 0.831) and 0.257 (0.141, 0.373; P < 0.0001) larger than those of CPIII. In conclusion, these data indicate that plasma CPI outperforms CPIII in detecting altered OATP1B1 function, but GCDCA-3G is an even more sensitive OATP1B1 biomarker than CPI.Peer reviewe

Digoxin use and outcomes after myocardial infarction in patients with atrial fibrillation

Digoxin is used for rate control in atrial fibrillation (AF), but evidence for its efficacy and safety after myocardial infarction (MI) is scarce and mixed. We studied post-MI digoxin use effects on AF patient outcomes in a nationwide registry follow-up study in Finland. Digoxin was used by 18.6% of AF patients after MI, with a decreasing usage trend during 2004-2014. Baseline differences in digoxin users (n = 881) and controls (n = 3898) were balanced with inverse probability of treatment weight adjustment. The median follow-up was 7.4 years. Patients using digoxin after MI had a higher cumulative all-cause mortality (77.4% vs. 72.3%; hazard ratio [HR]: 1.19; confidence interval [CI]: 1.07-1.32; p = 0.001) during a 10-year follow-up. Mortality differences were detected in a subgroup analysis of patients without baseline heart failure (HF) (HR: 1.23; p = 0.019) but not in patients with baseline HF (HR: 1.05; p = 0.413). Cumulative incidences of HF hospitalizations, stroke and new MI were similar between digoxin group and controls. In conclusion, digoxin use after MI is associated with increased mortality but not with HF hospitalizations, new MI or stroke in AF patients. Increased mortality was detected in patients without baseline HF. Results suggest caution with digoxin after MI in AF patients, especially in the absence of HF

Translational aspects of cytochrome P450-mediated drug-drug interactions: A case study with clopidogrel

Multimorbidity, polypharmacotherapy and drug interactions are increasingly common in the ageing population. Many drug-drug interactions (DDIs) are caused by perpetrator drugs inhibiting or inducing cytochrome P450 (CYP) enzymes, resulting in alterations of the plasma concentrations of a victim drug. DDIs can have a major negative health impact, and in the past, unrecognized DDIs have resulted in drug withdrawals from the market. Signals to investigate DDIs may emerge from a variety of sources. Nowadays, standard methods are widely available to identify and characterize the mechanisms of CYP-mediated DDIs in vitro. Clinical pharmacokinetic studies, in turn, provide experimental data on pharmacokinetic outcomes of DDIs. Physiologically based pharmacokinetic (PBPK) modelling utilizing both in vitro and in vivo data is a powerful tool to predict different DDI scenarios. Finally, epidemiological studies can provide estimates on the health outcomes of DDIs. Thus, to fully characterize the mechanisms, clinical effects and implications of CYP-mediated DDIs, translational research approaches are required. This minireview provides an overview of translational approaches to study CYP-mediated DDIs, going beyond regulatory DDI guidelines, and an illustrative case study of how the DDI potential of clopidogrel was unveiled by combining these different methods.</p

Itraconazole Increases Ibrutinib Exposure 10-Fold and Reduces Interindividual Variation-A Potentially Beneficial Drug-Drug Interaction

The oral bioavailability of ibrutinib is low and variable, mainly due to extensive first-pass metabolism by cytochrome P450 (CYP) 3A4. The unpredictable exposure can compromise its safe and effective dosing. We examined the impact of itraconazole on ibrutinib pharmacokinetics. In a randomized crossover study, 11 healthy subjects were administered itraconazole 200 mg or placebo twice on day 1, and once on days 2-4. On day 3, 1 hour after itraconazole (placebo) and breakfast, ibrutinib (140 mg during placebo; 15 mg during itraconazole) was administered. Itraconazole increased the dose-adjusted geometric mean area under the concentration-time curve from zero to infinity (AUC(0-infinity)) of ibrutinib 10.0-fold (90% confidence interval (CI) 7.2-13.9; P <0.001) and peak plasma concentration (C-max) 8.8-fold (90% CI 6.3-12.1; P <0.001). During itraconazole, the intersubject variation for the AUC(0-infinity) (55%) and C-max (53%) was around half of that during placebo (104%; 99%). In conclusion, itraconazole markedly increases ibrutinib bioavailability and decreases its interindividual variability, offering a possibility to improved dosing accuracy and cost savings.Peer reviewe

Common Statin Intolerance Variants in ABCB1 and LILRB5 Show Synergistic Effects on Statin Response:An Observational Study Using Electronic Health Records

Background: Statin intolerance impacts approximately 10% of statin users, with side effects ranging from mild myalgia to extreme intolerance resulting in myopathy and rhabdomyolysis. Statin intolerance results in poor adherence to therapy and can impact statin efficacy. Many genetic variants are associated with statin intolerance. The effect of these variants on statin efficacy has not been systematically explored.Methods: Using longitudinal electronic health records and genetic biobank data from Tayside, Scotland, we examined the effect of seven genetic variants with previously reported associations with simvastatin or atorvastatin intolerance on the outcome of statin response. Statin response was measured by the reduction achieved when comparing pre- and post-statin non-high-density lipoprotein-cholesterol (non-HDL-C). Post-treatment statin response was limited to non-HDL-C measured within 6months of therapy initiation. Univariate and multivariable linear regression models were used to assess the main and adjusted effect of the variants on statin efficacy.Results: Around 9,401 statin users met study inclusion criteria, of whom 8,843 were first prescribed simvastatin or atorvastatin. The average difference in post-treatment compared to pre-treatment non-HDL-cholesterol was 1.45 (±1.04) mmol/L. In adjusted analyses, only two variants, one in the gene ATP-binding cassette transporter B1 (ABCB1; rs1045642), and one in leukocyte immunoglobulin like receptor B5 (LILRB5; rs12975366), were associated with statin efficacy. In ABCB1, homozygous carriers of the C allele at rs1045642 had 0.06mmol/L better absolute reduction in non-HDL-cholesterol than carriers of the T allele (95% CI: 0.01, 0.1). In LILRB5 (rs12975366), carriers of the C allele had 0.04mmol/L better absolute reduction compared to those homozygous for the T allele (95% CI: 0.004, 0.08). When combined into a two-variant risk score, individuals with both the rs1045642-CC genotype and the rs12975366-TC or CC genotype had a 0.11mmol/L greater absolute reduction in non-HDL-cholesterol compared to those with rs1045642-TC or TT genotype and the rs12975366-TT genotype (95% CI: 0.05, 0.16; p&lt;0.001).Conclusion: We report two genetic variants for statin adverse drug reactions (ADRs) that are associated with statin efficacy. While the ABCB1 variant has been shown to have an association with statin pharmacokinetics, no similar evidence for LILRB5 has been reported. These findings highlight the value of genetic testing to deliver precision therapeutics to statin users