Posaconazole-ibrutinib interaction cannot be avoided by staggered dosing: How to optimize ibrutinib dose during posaconazole treatment.

AIMS: Ibrutinib is used in the treatment of certain B-cell malignancies. Due to its CYP3A4-mediated metabolism and highly variable pharmacokinetics, it is prone to potentially harmful drug-drug interactions. METHODS: In a randomized, placebo-controlled, three-phase crossover study, we examined the effect of the CYP3A4-inhibiting antifungal posaconazole on ibrutinib pharmacokinetics. Eleven healthy participants ingested repeated doses of 300 mg of posaconazole either in the morning or in the evening, or placebo. A single dose of ibrutinib (30, 70 or 140 mg, respectively) was administered at 9 AM, 1 or 12 h after the preceding posaconazole/placebo dose. RESULTS: On average, morning posaconazole increased the dose-adjusted geometric mean area under the plasma concentration-time curve from zero to infinity (AUC0-∞ ) and peak plasma concentration (Cmax ) of ibrutinib 9.5-fold (90% confidence interval [CI] 6.3-14.3, P < 0.001) and 8.5-fold (90% CI 5.7-12.8, P < 0.001), respectively, while evening posaconazole increased those 10.3-fold (90% CI 6.7-16.0, P < 0.001) and 8.2-fold (90% CI 5.2-13.2, P < 0.001), respectively. Posaconazole had no significant effect on the half-life of ibrutinib, but substantially reduced the metabolite PCI-45227 to ibrutinib AUC0-∞ ratio. There were no significant differences in ibrutinib pharmacokinetics between morning and evening posaconazole phases. CONCLUSIONS: Posaconazole increases ibrutinib exposure substantially, by about 10-fold. This interaction cannot be avoided by dosing the drugs 12 h apart. In general, a 70-mg daily dose of ibrutinib should not be exceeded during posaconazole treatment to avoid potentially toxic systemic ibrutinib concentrations.

Absorption pharmacokinetics and feasibility of intranasal dexmedetomidine in patients under general anaesthesia.

BACKGROUND: The use of intranasal dexmedetomidine is hampered by a limited understanding of its absorption pharmacokinetics. METHODS: We examined the pharmacokinetics and feasibility of intranasal dexmedetomidine administered in the supine position to adult patients undergoing general anaesthesia. Twenty-eight patients between 35 and 80 years of age, ASA 1-3 and weight between 50 and 100 kg, who underwent elective unilateral total hip or knee arthroplasty under general anaesthesia were recruited. All patients received 100 µg of intranasal dexmedetomidine after anaesthesia induction. Six venous blood samples (at 0, 5, 15, 45, 60, 240 min timepoints from dexmedetomidine administration) were collected from each patient and dexmedetomidine plasma concentrations were measured. Concentration-time profiles after nasal administration were pooled with earlier data from a population analysis of intravenous dexmedetomidine (n = 202) in order to estimate absorption parameters using nonlinear mixed effects. Peak concentration (CMAX) and time (TMAX) were estimated using simulation (n = 1000) with parameter estimates and their associated variability. RESULTS: There were 28 adult patients with a mean (SD) age of 66 (8) years and weight of 83 (10) kg. The mean weight-adjusted dose of dexmedetomidine was 1.22 (0.15) µg kg-1. CMAX 0.273 µg L-1 was achieved at 98 min after intranasal administration (TMAX). The relative bioavailability of dexmedetomidine was 80% (95% CI 75-91%). The absorption half-time (TABS = 120 min; 95% CI 90-147 min) was slower than that in previous pharmacokinetic studies on adult patients. Perioperative haemodynamics of all patients remained stable. CONCLUSIONS: Administration of intranasal dexmedetomidine in the supine position during general anaesthesia is feasible with good bioavailability. This administration method has slower absorption when compared to awake patients in upright position, with consequent concentrations attained after TMAX for several hours.

Lack of Statin Therapy and Outcomes After Ischemic Stroke: A Population-Based Study.

BACKGROUND: Statin treatment is effective at preventing adverse vascular events after ischemic stroke (IS). However, many patients fail to use statins after IS. We studied the impact of not using statins after IS on adverse outcomes. METHODS: IS patients (n=59 588) admitted to 20 Finnish hospitals were retrospectively studied. Study data were combined from national registries on hospital admissions, mortality, cancer diagnoses, prescription medication purchases, and permissions for special reimbursements for medications. Usage of prescription medication was defined as drug purchase within 90 days after hospital discharge. Ongoing statin use during follow-up was analyzed in 90-day intervals. Differences in baseline features, comorbidities, other medications, and recanalization therapies were balanced with inverse probability of treatment weighting. Median follow-up was 5.7 years. RESULTS: Statin therapy was not used by 27.1% of patients within 90 days after IS discharge, with women and older patients using statins less frequently. The average proportion of patients without ongoing statin during the 12-year follow-up was 36.0%. Patients without early statins had higher all-cause mortality at 1 year (7.5% versus 4.4% in patients who did use statins; hazard ratio [HR], 1.74 [CI, 1.61-1.87]) and 12 years (56.8% versus 48.6%; HR, 1.37 [CI, 1.33-1.41]). Cumulative incidence of major adverse cerebrovascular or cardiovascular event was higher at 1 year (subdistribution HR, 1.36 [CI, 1.29-1.43]) and 12 years (subdistribution HR, 1.21 [CI, 1.18-1.25]) without early statin use. Cardiovascular death, recurrent IS, and myocardial infarction were more frequent without early statin use. Early statin use was not associated with hemorrhagic stroke during follow-up. Lack of ongoing statin during follow-up was associated with risk of death in time-dependent analysis (adjusted HR, 3.03 [CI, 2.96-3.23]). CONCLUSIONS: Lack of statin treatment after IS is associated with adverse long-term outcomes. Measures to further improve timely statin use after IS are needed.

Real-world pharmacogenetics of statin intolerance: effects of SLCO1B1, ABCG2 , and CYP2C9 variants.

OBJECTIVE: The association of SLCO1B1 c.521T>C with simvastatin-induced muscle toxicity is well characterized. However, different statins are subject to metabolism and transport also by other proteins exhibiting clinically meaningful genetic variation. Our aim was to investigate associations of SLCO1B1 c.521T>C with intolerance to atorvastatin, fluvastatin, pravastatin, rosuvastatin, or simvastatin, those of ABCG2 c.421C>A with intolerance to atorvastatin, fluvastatin, or rosuvastatin, and that of CYP2C9*2 and *3 alleles with intolerance to fluvastatin. METHODS: We studied the associations of these variants with statin intolerance in 2042 patients initiating statin therapy by combining genetic data from samples from the Helsinki Biobank to clinical chemistry and statin purchase data. RESULTS: We confirmed the association of SLCO1B1 c.521C/C genotype with simvastatin intolerance both by using phenotype of switching initial statin to another as a marker of statin intolerance [hazard ratio (HR) 1.88, 95% confidence interval (CI) 1.08-3.25, P  = 0.025] and statin switching along with creatine kinase measurement (HR 5.44, 95% CI 1.49-19.9, P  = 0.011). No significant association was observed with atorvastatin and rosuvastatin. The sample sizes for fluvastatin and pravastatin were relatively small, but SLCO1B1 c.521T>C carriers had an increased risk of pravastatin intolerance defined by statin switching when compared to homozygous reference T/T genotype (HR 2.11, 95% CI 1.01-4.39, P  = 0.047). CONCLUSION: The current results can inform pharmacogenetic statin prescribing guidelines and show feasibility for the methodology to be used in larger future studies.

A comprehensive pharmacogenomic study indicates roles for SLCO1B1, ABCG2 and SLCO2B1 in rosuvastatin pharmacokinetics.

AIMS: The aim was to comprehensively investigate the effects of genetic variability on the pharmacokinetics of rosuvastatin. METHODS: We conducted a genome-wide association study and candidate gene analyses of single dose rosuvastatin pharmacokinetics in a prospective study (n = 159) and a cohort of previously published studies (n = 88). RESULTS: In a genome-wide association meta-analysis of the prospective study and the cohort of previously published studies, the SLCO1B1 c.521 T > C (rs4149056) single nucleotide variation (SNV) associated with increased area under the plasma concentration-time curve (AUC) and peak plasma concentration of rosuvastatin (P = 1.8 × 10-12 and P = 3.2 × 10-15 ). The candidate gene analysis suggested that the ABCG2 c.421C > A (rs2231142) SNV associates with increased rosuvastatin AUC (P = .0079), while the SLCO1B1 c.388A > G (rs2306283) and SLCO2B1 c.1457C > T (rs2306168) SNVs associate with decreased rosuvastatin AUC (P = .0041 and P = .0076). Based on SLCO1B1 genotypes, we stratified the participants into poor, decreased, normal, increased and highly increased organic anion transporting polypeptide (OATP) 1B1 function groups. The OATP1B1 poor function phenotype associated with 2.1-fold (90% confidence interval 1.6-2.8, P = 4.69 × 10-5 ) increased AUC of rosuvastatin, whereas the OATP1B1 highly increased function phenotype associated with a 44% (16-62%; P = .019) decreased rosuvastatin AUC. The ABCG2 c.421A/A genotype associated with 2.2-fold (1.5-3.0; P = 2.6 × 10-4 ) increased AUC of rosuvastatin. The SLCO2B1 c.1457C/T genotype associated with 28% decreased rosuvastatin AUC (11-42%; P = .01). CONCLUSION: These data suggest roles for SLCO1B1, ABCG2 and SLCO2B1 in rosuvastatin pharmacokinetics. Poor SLCO1B1 or ABCG2 function genotypes may increase the risk of rosuvastatin-induced myotoxicity. Reduced doses of rosuvastatin are advisable for patients with these genotypes.

Placental transporter-mediated drug interactions and offspring congenital anomalies.

AIMS: P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP) are efflux transporters expressed in the placenta, limiting their substrates from reaching the foetus. Our aim was to investigate if concomitant prenatal exposure to several substrates or inhibitors of these transporters increases the risk of congenital anomalies. METHODS: The national Drugs and Pregnancy database, years 1996-2014, was utilized in this population-based birth cohort study. In the database, the Medical Birth Register, the Register on Induced Abortions, the Malformation register and the Register on Reimbursed Drug Purchases have been linked. The University of Washington Metabolism and Transport Drug Interaction Database was used to identify substrates and inhibitors of P-gp and BCRP. We included singleton pregnancies ending in birth or elective termination of pregnancy due to foetal anomaly. Known teratogens were excluded. We identified women exposed 1 month before pregnancy or during the first trimester to P-gp/BCRP polytherapy (n = 21 186); P-gp/breast cancer resistance protein monotherapy (n = 97 906); non-P-gp/BCRP polytherapy (n = 78 636); and unexposed (n = 728 870). We investigated the association between the exposure groups and major congenital anomalies using logistic regression adjusting for several confounders. RESULTS: The prevalence of congenital anomalies was higher in the P-gp/BCRP polytherapy group (5.5%) compared to the P-gp/BCRP monotherapy (4.7%, OR 1.13; 95% CI 1.05-1.21), the non-P-gp/BCRP polytherapy (4.9%, OR 1.14; 95% CI 1.06-1.22), and to the unexposed groups (4.2%, OR 1.23; 95% CI 1.15-1.31). CONCLUSION: The results suggest a role of placental transporter-mediated drug interactions in teratogenesis.

Clopidogrel and Gemfibrozil Strongly Inhibit the CYP2C8-Dependent Formation of 3-Hydroxydesloratadine and Increase Desloratadine Exposure In Humans.

A recent in vitro study suggested that CYP2C8 is essential in the metabolism of desloratadine, an H1 receptor antagonist. If the proposed biotransformation mechanism takes place in vivo in humans, desloratadine could serve as a selective CYP2C8 probe substrate in drug-drug interaction studies. Glucuronide metabolites of clopidogrel and gemfibrozil act as time-dependent inhibitors of CYP2C8, but they have not been compared clinically. We conducted a randomized crossover study in 11 healthy subjects to characterize the involvement of CYP2C8 in desloratadine metabolism and to compare the CYP2C8 inhibitory strength of clopidogrel (300 and 75 mg on two following days) with that of gemfibrozil (600 mg BID for 5 days). Compared with placebo (control), clopidogrel increased the area under the plasma concentration-time curve (AUC0-∞) and peak plasma concentration (C max) of desloratadine to 280% (P = 3 × 10-7) and 165% (P = 0.0006), respectively. The corresponding increases by gemfibrozil were to 462% (P = 4 × 10-7) and 174% (P = 0.0006). Compared with placebo, clopidogrel and gemfibrozil decreased 3-hydroxyloratadine AUC0-71h to 52% (P = 5 × 10-5) and 6% (P = 2 × 10-8), respectively. Moreover, the 3-hydroxydesloratadine:desloratadine AUC0-71 h ratios were 21% (P = 7 × 10-10) and 1.7% (P = 8 × 10-11) of control during the clopidogrel and gemfibrozil phases. Our results confirm that CYP2C8 plays a critical role in the formation of 3-hydroxydesloratadine in humans, making desloratadine a potential CYP2C8 probe substrate. Furthermore, the findings corroborate the previous estimates that clinically relevant doses of clopidogrel cause strong CYP2C8 inhibition, whereas those of gemfibrozil almost completely inactivate the enzyme in humans.

Clopidogrel Carboxylic Acid Glucuronidation is Mediated Mainly by UGT2B7, UGT2B4, and UGT2B17: Implications for Pharmacogenetics and Drug-Drug Interactions .

The antiplatelet drug clopidogrel is metabolized to an acyl-ß-d-glucuronide, which causes time-dependent inactivation of CYP2C8. Our aim was to characterize the UDP-glucuronosyltransferase (UGT) enzymes that are responsible for the formation of clopidogrel acyl-ß-d-glucuronide. Kinetic analyses and targeted inhibition experiments were performed using pooled human liver and intestine microsomes (HLMs and HIMs, respectively) and selected human recombinant UGTs based on preliminary screening. The effects of relevant UGT polymorphisms on the pharmacokinetics of clopidogrel were evaluated in 106 healthy volunteers. UGT2B7 and UGT2B17 exhibited the greatest level of clopidogrel carboxylic acid glucuronidation activities, with a CLint,u of 2.42 and 2.82 µl⋅min-1⋅mg-1, respectively. Of other enzymes displaying activity (UGT1A3, UGT1A9, UGT1A10-H, and UGT2B4), UGT2B4 (CLint,u 0.51 µl⋅min-1⋅mg-1) was estimated to contribute significantly to the hepatic clearance. Nonselective UGT2B inhibitors strongly inhibited clopidogrel acyl-ß-d-glucuronide formation in HLMs and HIMs. The UGT2B17 inhibitor imatinib and the UGT2B7 and UGT1A9 inhibitor mefenamic acid inhibited clopidogrel carboxylic acid glucuronidation in HIMs and HLMs, respectively. Incubation of clopidogrel carboxylic acid in HLMs with UDPGA and NADPH resulted in strong inhibition of CYP2C8 activity. In healthy volunteers, the UGT2B17*2 deletion allele was associated with a 10% decrease per copy in the plasma clopidogrel acyl-ß-d-glucuronide to clopidogrel carboxylic acid area under the plasma concentration-time curve from 0 to 4 hours (AUC0-4) ratio (P < 0.05). To conclude, clopidogrel carboxylic acid is metabolized mainly by UGT2B7 and UGT2B4 in the liver and by UGT2B17 in the small intestinal wall. The formation of clopidogrel acyl-ß-d-glucuronide is impaired in carriers of the UGT2B17 deletion. These findings may have implications regarding the intracellular mechanisms leading to CYP2C8 inactivation by clopidogrel.

Implications of intercorrelation between hepatic CYP3A4-CYP2C8 enzymes for the evaluation of drug-drug interactions: a case study with repaglinide.

AIMS: Statistically significant positive correlations are reported for the abundance of hepatic drug-metabolizing enzymes. We investigate, as an example, the impact of CYP3A4-CYP2C8 intercorrelation on the predicted interindividual variabilities of clearance and drug-drug interactions (DDIs) for repaglinide using physiologically based pharmacokinetic (PBPK) modelling. METHODS: PBPK modelling and simulation were employed using Simcyp Simulator (v15.1). Virtual populations were generated assuming intercorrelations between hepatic CYP3A4-CYP2C8 abundances derived from observed values in 24 human livers. A repaglinide PBPK model was used to predict PK parameters in the presence and absence of gemfibrozil in virtual populations, and the results were compared with a clinical DDI study. RESULTS: Coefficient of variation (CV) of oral clearance was 52.5% in the absence of intercorrelation between CYP3A4-CYP2C8 abundances, which increased to 54.2% when incorporating intercorrelation. In contrast, CV for predicted DDI (as measured by AUC ratio before and after inhibition) was reduced from 46.0% in the absence of intercorrelation between enzymes to 43.8% when incorporating intercorrelation: these CVs were associated with 5th/95th percentiles (2.48-11.29 vs. 2.49-9.69). The range of predicted DDI was larger in the absence of intercorrelation (1.55-77.06) than when incorporating intercorrelation (1.79-25.15), which was closer to clinical observations (2.6-12). CONCLUSIONS: The present study demonstrates via a systematic investigation that population-based PBPK modelling incorporating intercorrelation led to more consistent estimation of extreme values than those observed in interindividual variabilities of clearance and DDI. As the intercorrelations more realistically reflect enzyme abundances, virtual population studies involving PBPK and DDI should avoid using Monte Carlo assignment of enzyme abundance.

A common missense variant of LILRB5 is associated with statin intolerance and myalgia.

Aims: A genetic variant in LILRB5 (leukocyte immunoglobulin-like receptor subfamily-B) (rs12975366: T > C: Asp247Gly) has been reported to be associated with lower creatine phosphokinase (CK) and lactate dehydrogenase (LDH) levels. Both biomarkers are released from injured muscle tissue, making this variant a potential candidate for susceptibility to muscle-related symptoms. We examined the association of this variant with statin intolerance ascertained from electronic medical records in the GoDARTS study. Methods and results: In the GoDARTS cohort, the LILRB5 Asp247 variant was associated with statin intolerance (SI) phenotypes; one defined as having raised CK and being non-adherent to therapy [odds ratio (OR) 1.81; 95% confidence interval (CI): 1.34-2.45] and the other as being intolerant to the lowest approved dose of a statin before being switched to two or more other statins (OR 1.36; 95% CI: 1.07-1.73). Those homozygous for Asp247 had increased odds of developing both definitions of intolerance. Importantly the second definition did not rely on CK elevations. These results were replicated in adjudicated cases of statin-induced myopathy in the PREDICTION-ADR consortium (OR1.48; 95% CI: 1.05-2.10) and for the development of myalgia in the JUPITER randomized clinical trial of rosuvastatin (OR1.35, 95% CI: 1.10-1.68). A meta-analysis across the studies showed a consistent association between Asp247Gly and outcomes associated with SI (OR1.34; 95% CI: 1.16-1.54). Conclusion: This study presents a novel immunogenetic factor associated with statin intolerance, an important risk factor for cardiovascular outcomes. The results suggest that true statin-induced myalgia and non-specific myalgia are distinct, with a potential role for the immune system in their development. We identify a genetic group that is more likely to be intolerant to their statins.

Clopidogrel Markedly Increases Plasma Concentrations of CYP2C8 Substrate Pioglitazone.

The glucose-lowering drug pioglitazone undergoes hepatic CYP2C8-mediated biotransformation to its main metabolites. The antiplatelet drug clopidogrel is metabolized to clopidogrel acyl-ß-d-glucuronide, which was recently found to be a strong time-dependent inhibitor of CYP2C8 in humans. Therefore, we studied the effect of clopidogrel on the pharmacokinetics of pioglitazone. In a randomized crossover study, 10 healthy volunteers ingested either 300 mg of clopidogrel on day 1, and 75 mg on days 2 and 3, or placebo. Pioglitazone 15 mg was administered 1 hour after placebo and clopidogrel on day 1. Plasma concentrations of pioglitazone, clopidogrel, and their main metabolites were measured up to 72 hours. Clopidogrel increased the area under the plasma concentration-time curve (AUC0-∞) of pioglitazone 2.1-fold [P < 0.001, 90% confidence interval (CI) 1.8-2.6] and prolonged its half-life from 6.7 to 11 hours (P = 0.002). The peak concentration of pioglitazone was unaffected but the concentration at 24 hours was increased 4.5-fold (range 1.6-9.8; P < 0.001, 90% CI 3.17-6.45) by clopidogrel. The M-IV-to-pioglitazone AUC0-∞ ratio was 49% (P < 0.001, 90% CI 0.40-0.59) of that during the control phase, indicating that clopidogrel inhibited the CYP2C8-mediated biotransformation of pioglitazone. Clopidogrel increases the exposure to pioglitazone by inhibiting its CYP2C8-mediated biotransformation. In consequence, use of clopidogrel may increase the risk of fluid retention and other concentration-related adverse effects of pioglitazone.

SLCO1B1 polymorphism markedly affects the pharmacokinetics of lovastatin acid.

OBJECTIVE: Organic anion transporting polypeptide 1B1 (OATP1B1, encoded by SLCO1B1 gene) is a hepatic uptake transporter, and its genetic variability is associated with pharmacokinetics and muscle toxicity risk of simvastatin. We examined the possible effects of variations in the SLCO1B1 gene on the pharmacokinetics of lovastatin in a prospective genotype panel study. PARTICIPANTS AND METHODS: Seven healthy volunteers with the SLCO1B1*1B/*1B genotype, five with the SLCO1B1*5/*15 or *15/*15 genotype, and 15 with the SLCO1B1*1A/*1A genotype (controls) were recruited. Each study participant ingested a single 40-mg dose of lovastatin. Plasma concentrations of lovastatin (inactive lactone) and its active metabolite lovastatin acid were measured up to 24 h. RESULTS: In the SLCO1B1*5/*15 or *15/*15 genotype group, the geometric mean Cmax and AUC0-24 of lovastatin acid were 340 and 286% of the corresponding values in the SLCO1B1*1A/*1A (reference) genotype group (P<0.005). In contrast, the AUC0-24 of lovastatin acid in the SLCO1B1*1B/*1B genotype group was only 68% of that in the reference genotype group (P=0.03). No statistically significant association was observed between the SLCO1B1 genotype and the pharmacokinetics of lovastatin lactone. CONCLUSION: SLCO1B1*5/*15 and *15/*15 genotypes markedly increase the exposure to active lovastatin acid, but have no significant effect on lovastatin lactone, similar to their effects on simvastatin and simvastatin acid. Accordingly, it is probable that the risk of muscle toxicity during lovastatin treatment is increased in individuals carrying the SLCO1B1*5 or *15 allele. The SLCO1B1*1B/*1B genotype is associated with reduced lovastatin acid concentrations, consistent with enhanced hepatic uptake.

Clopidogrel Has No Clinically Meaningful Effect on the Pharmacokinetics of the Organic Anion Transporting Polypeptide 1B1 and Cytochrome P450 3A4 Substrate Simvastatin.

Simvastatin and clopidogrel are commonly used together in the treatment of cardiovascular diseases. Organic anion transporting polypeptide (OATP) 1B1 activity markedly affects the hepatic uptake of simvastatin acid, whereas both simvastatin and simvastatin acid are sensitive to changes in cytochrome P450 3A4 activity. Clopidogrel and its metabolites inhibit OATP1B1 and CYP3A4 in vitro. We studied the effect of clopidogrel on the pharmacokinetics of simvastatin in a randomized crossover study. Twelve healthy volunteers ingested either a dose of placebo (control) or 300 mg of clopidogrel on day 1 and 75 mg on days 2 and 3. Simvastatin 40 mg was administered 1 hour after placebo and after clopidogrel on days 1 and 3. Plasma drug concentrations were measured for up to 12 hours. Clopidogrel 300 mg (day 1) increased the concentrations of simvastatin and simvastatin acid during the absorption phase. After clopidogrel 300 mg, the area under the concentration time curve (AUC) of simvastatin from 0 to 2 hours was 156% (P = 0.02) and its AUC(0-12 hours) was 132% (P = 0.08) of that during placebo, whereas the AUC(0-2 hours) and the AUC(0-12 hours) of simvastatin acid were 148% (P = 0.04) and 112% (P = 0.52) of control. Clopidogrel 75 mg (day 3) had no significant effect on the pharmacokinetic variables of simvastatin or simvastatin acid compared with placebo. The effect of clopidogrel seemed independent of the SLCO1B1 c.521T>C genotype. In conclusion, as clopidogrel did not have significant effects on the total exposure to simvastatin or simvastatin acid, clopidogrel does not seem to inhibit OATP1B1 or CYP3A4 to a clinically relevant extent.

Effect of grapefruit juice on the bioactivation of prasugrel.

AIMS: The P2Y12 inhibitor prasugrel is a prodrug, which is activated after its initial hydrolysis partly by cytochrome P450 (CYP) 3A4. Grapefruit juice, a strong inactivator of intestinal CYP3A4, greatly reduces the activation and antiplatelet effects of clopidogrel. The aim of this study was to investigate the effects of grapefruit juice on prasugrel. METHODS: In a randomized crossover study, seven healthy volunteers ingested 200 ml of grapefruit juice or water three times daily for 4 days. On day 3, they ingested a single 10 mg dose of prasugrel with an additional 200 ml of grapefruit juice or water. Plasma concentrations of prasugrel metabolites and the antiplatelet effect were measured. RESULTS: Grapefruit juice increased the geometric mean area under the plasma concentration-time curve (AUC(0-∞)) of the primary, inactive metabolite of prasugrel to 164% of the control value (95% confidence interval 122-220%, P = 0.008), without a significant effect on its peak plasma concentration (C(max)). The C(max) and AUC(0-∞) of the secondary, active metabolite were decreased to 51% (95% confidence interval 32-84%, P = 0.017) and 74% of the control value (95% confidence interval 60-91%, P = 0.014) by grapefruit juice (P < 0.05). The average platelet inhibition, assessed with the VerifyNow® method at 0-24 h after prasugrel intake, was 5 percentage points (95% confidence interval 1-10 percentage points) lower in the grapefruit juice phase than in the water phase (P = 0.034). CONCLUSIONS: Grapefruit juice reduces the bioactivation of prasugrel, but this has only a limited effect on the antiplatelet effect of prasugrel.

Effect of carboxylesterase 1 c.428G > A single nucleotide variation on the pharmacokinetics of quinapril and enalapril.

AIM: The aim of the present study was to investigate the effects of the carboxylesterase 1 (CES1) c.428G > A (p.G143E, rs71647871) single nucleotide variation (SNV) on the pharmacokinetics of quinapril and enalapril in a prospective genotype panel study in healthy volunteers. METHODS: In a fixed-order crossover study, 10 healthy volunteers with the CES1 c.428G/A genotype and 12 with the c.428G/G genotype ingested a single 10 mg dose of quinapril and enalapril with a washout period of at least 1 week. Plasma concentrations of quinapril and quinaprilat were measured for up to 24 h and those of enalapril and enalaprilat for up to 48 h. Their excretion into the urine was measured from 0 h to 12 h. RESULTS: The area under the plasma concentration-time curve from 0 h to infinity (AUC0-∞) of active enalaprilat was 20% lower in subjects with the CES1 c.428G/A genotype than in those with the c.428G/G genotype (95% confidence interval of geometric mean ratio 0.64, 1.00; P = 0.049). The amount of enalaprilat excreted into the urine was 35% smaller in subjects with the CES1 c.428G/A genotype than in those with the c.428G/G genotype (P = 0.044). The CES1 genotype had no significant effect on the enalaprilat to enalapril AUC0-∞ ratio or on any other pharmacokinetic or pharmacodynamic parameters of enalapril or enalaprilat. The CES1 genotype had no significant effect on the pharmacokinetic or pharmacodynamic parameters of quinapril. CONCLUSIONS: The CES1 c.428G > A SNV decreased enalaprilat concentrations, probably by reducing the hydrolysis of enalapril, but had no observable effect on the pharmacokinetics of quinapril.

Association of Central Nervous System-Affecting Medications With Occurrence and Short-Term Mortality of Traumatic Brain Injury.

BACKGROUND AND OBJECTIVES: The use of medications commonly prescribed after traumatic brain injury (TBI) has been little studied before TBI. This study examined the association between the use of medications that affect the central nervous system (CNS) and the occurrence and short-term mortality of TBI. METHODS: Mandatory Finnish registries were used to identify TBI admissions, fatal TBIs, and drug purchases during 2005-2018. Patients with TBI were 1:1 matched to nontrauma control patients to investigate the association between medications and the occurrence of TBI and 30-day mortality after TBI. Number needed to harm (NNH) was calculated for all medications. RESULTS: The cohort included 59 606 patients with TBI and a similar number of control patients. CNS-affecting drugs were more common in patients with TBI than in controls [odds ratio = 2.07 (2.02-2.13), P < .001)]. Benzodiazepines were the most common type of medications in patients with TBI (17%) and in controls (11%). The lowest NNH for the occurrence of TBI was associated with benzodiazepines (15.4), selective serotonin uptake inhibitors (18.5), and second-generation antipsychotics (25.8). Eight percent of the patients with TBI died within 30 days. The highest hazard ratios (HR) and lowest NNHs associated with short-term mortality were observed with strong opioids [HR = 1.41 (1.26-1.59), NNH = 33.1], second-generation antipsychotics [HR = 1.36 (1.23-1.50), NNH = 37.1], and atypical antidepressants [HR = 1.17 (1.04-1.31), NNH = 77.7]. CONCLUSION: Thirty-seven percent of patients with TBI used at least 1 CNS-affecting drug. This proportion was significantly higher than in the control population (24%). The highest risk and lowest NNH for short-term mortality were observed with strong opioids, second-generation antipsychotics, and atypical antidepressants. The current risks underscore the importance of weighing the benefits and risks before prescribing CNS-affecting drugs in patients at risk of head injury.

Non-targeted metabolomics for the identification of plasma metabolites associated with organic anion transporting polypeptide 1B1 function.

Our aim was to evaluate biomarkers for organic anion transporting polypeptide 1B1 (OATP1B1) function using a hypothesis-free metabolomics approach. We analyzed fasting plasma samples from 356 healthy volunteers using non-targeted metabolite profiling by liquid chromatography high-resolution mass spectrometry. Based on SLCO1B1 genotypes, we stratified the volunteers to poor, decreased, normal, increased, and highly increased OATP1B1 function groups. Linear regression analysis, and random forest (RF) and gradient boosted decision tree (GBDT) regressors were used to investigate associations of plasma metabolite features with OATP1B1 function. Of the 9152 molecular features found, 39 associated with OATP1B1 function either in the linear regression analysis (p < 10-5) or the RF or GBDT regressors (Gini impurity decrease > 0.01). Linear regression analysis showed the strongest associations with two features identified as glycodeoxycholate 3-O-glucuronide (GDCA-3G; p = 1.2 × 10-20 for negative and p = 1.7 × 10-19 for positive electrospray ionization) and one identified as glycochenodeoxycholate 3-O-glucuronide (GCDCA-3G; p = 2.7 × 10-16). In both the RF and GBDT models, the GCDCA-3G feature showed the strongest association with OATP1B1 function, with Gini impurity decreases of 0.40 and 0.17. In RF, this was followed by one GDCA-3G feature, an unidentified feature with a molecular weight of 809.3521, and the second GDCA-3G feature. In GBDT, the second and third strongest associations were observed with the GDCA-3G features. Of the other associated features, we identified with confidence two representing lysophosphatidylethanolamine 22:5. In addition, one feature was putatively identified as pregnanolone sulfate and one as pregnenolone sulfate. These results confirm GCDCA-3G and GDCA-3G as robust OATP1B1 biomarkers in human plasma.

Genome-Wide Association Study of Atorvastatin Pharmacokinetics: Associations With SLCO1B1, UGT1A3, and LPP.

In a genome-wide association study of atorvastatin pharmacokinetics in 158 healthy volunteers, the SLCO1B1 c.521T>C (rs4149056) variant associated with increased area under the plasma concentration-time curve from time zero to infinity (AUC0-∞) of atorvastatin (P = 1.2 × 10-10), 2-hydroxy atorvastatin (P = 4.0 × 10-8), and 4-hydroxy atorvastatin (P = 2.9 × 10-8). An intronic LPP variant, rs1975991, associated with reduced atorvastatin lactone AUC0-∞ (P = 3.8 × 10-8). Three UGT1A variants linked with UGT1A3*2 associated with increased 2-hydroxy atorvastatin lactone AUC0-∞ (P = 3.9 × 10-8). Furthermore, a candidate gene analysis including 243 participants suggested that increased function SLCO1B1 variants and decreased activity CYP3A4 variants affect atorvastatin pharmacokinetics. Compared with individuals with normal function SLCO1B1 genotype, atorvastatin AUC0-∞ was 145% (90% confidence interval: 98-203%; P = 5.6 × 10-11) larger in individuals with poor function, 24% (9-41%; P = 0.0053) larger in those with decreased function, and 41% (16-59%; P = 0.016) smaller in those with highly increased function SLCO1B1 genotype. Individuals with intermediate metabolizer CYP3A4 genotype (CYP3A4*2 or CYP3A4*22 heterozygotes) had 33% (14-55%; P = 0.022) larger atorvastatin AUC0-∞ than those with normal metabolizer genotype. UGT1A3*2 heterozygotes had 16% (5-25%; P = 0.017) smaller and LPP rs1975991 homozygotes had 34% (22-44%; P = 4.8 × 10-5) smaller atorvastatin AUC0-∞ than noncarriers. These data demonstrate that genetic variation in SLCO1B1, UGT1A3, LPP, and CYP3A4 affects atorvastatin pharmacokinetics. This is the first study to suggest that LPP rs1975991 may reduce atorvastatin exposure. [Correction added on 6 April, after first online publication: An incomplete sentence ("= 0.017) smaller in heterozygotes for UGT1A3*2 and 34% (22%, 44%; P × 10-5) smaller in homozygotes for LPP noncarriers.") has been corrected in this version.].

Grapefruit juice markedly increases the plasma concentrations and antiplatelet effects of ticagrelor in healthy subjects.

AIM: This study examined the effects of grapefruit juice on the new P2Y12 inhibitor ticagrelor, which is a substrate of CYP3A4 and P-glycoprotein. METHODS: In a randomized crossover study, 10 healthy volunteers ingested 200 ml of grapefruit juice or water thrice daily for 4 days. On day 3, they ingested a single 90 mg dose of ticagrelor. RESULTS: Grapefruit juice increased ticagrelor geometric mean peak plasma concentration (Cmax ) to 165% (95% confidence interval 147, 184%) and area under the concentration-time curve (AUC(0,∞)) to 221% of control (95% confidence interval 200, 245%). The Cmax and AUC(0,34 h) (P < 0.05) but not the AUC(0,∞) of the active metabolite C12490XX were decreased significantly. Grapefruit juice had a minor effect on ticagrelor elimination half-life prolonging it from 6.7 to 7.2 h (P = 0.036). In good correlation with the elevated plasma ticagrelor concentrations, grapefruit juice enhanced the antiplatelet effect of ticagrelor, assessed with VerifyNow® and Multiplate® methods, and postponed the recovery of platelet reactivity. CONCLUSIONS: Grapefruit juice increased ticagrelor exposure by more than two-fold, leading to an enhanced and prolonged ticagrelor antiplatelet effect. The grapefruit juice-ticagrelor interaction seems clinically important and indicates the significance of intestinal metabolism to ticagrelor pharmacokinetics.

Initial statin dose after myocardial infarction and long-term cardiovascular outcomes.

AIMS: Effective statin therapy is a cornerstone of secondary prevention after myocardial infarction (MI). Real-life statin dosing is nevertheless suboptimal and largely determined early after MI. We studied long-term outcome impact of initial statin dose after MI. METHODS AND RESULTS: Consecutive MI patients treated in Finland who used statins early after index event were retrospectively studied (N = 72 401; 67% men; mean age 68 years) using national registries. High-dose statin therapy was used by 26.3%, moderate dose by 69.2%, and low dose by 4.5%. Differences in baseline features, comorbidities, revascularisation, and usage of other evidence-based medications were adjusted for with multivariable regression. The primary outcome was major adverse cardiovascular or cerebrovascular event (MACCE) within 10 years. Median follow-up was 4.9 years. MACCE was less frequent in high-dose group compared with moderate dose [adjusted hazard ratio (HR) 0.92; P < 0.0001; number needed to treat (NNT) 34.1] and to low dose [adj.HR 0.81; P < 0.001; NNT 13.4] as well as in moderate-dose group compared with low dose (adj.HR 0.88; P < 0.0001; NNT 23.4). Death (adj.HR 0.87; P < 0.0001; NNT 23.6), recurrent MI (adj.sHR 0.91; P = 0.0001), and stroke (adj.sHR 0.86; P < 0.0001) were less frequent with a high- vs. moderate-dose statin. Higher initial statin dose after MI was associated with better long-term outcomes in subgroups by age, sex, atrial fibrillation, dementia, diabetes, heart failure, revascularisation, prior statin usage, or usage of other evidence-based medications. CONCLUSION: Higher initial statin dose after MI is dose-dependently associated with better long-term cardiovascular outcomes. These results underline the importance of using a high statin dose early after MI.