Identification of Potential Biomarkers for Diagnosis of Patients with Methamphetamine Use Disorder.

The current method for diagnosing methamphetamine use disorder (MUD) relies on self-reports and interviews with psychiatrists, which lack scientific rigor. This highlights the need for novel biomarkers to accurately diagnose MUD. In this study, we identified transcriptome biomarkers using hair follicles and proposed a diagnostic model for monitoring the MUD treatment process. We performed RNA sequencing analysis on hair follicle cells from healthy controls and former and current MUD patients who had been detained in the past for illegal use of methamphetamine (MA). We selected candidate genes for monitoring MUD patients by performing multivariate analysis methods, such as PCA and PLS-DA, and PPI network analysis. We developed a two-stage diagnostic model using multivariate ROC analysis based on the PLS-DA method. We constructed a two-step prediction model for MUD diagnosis using multivariate ROC analysis, including 10 biomarkers. The first step model, which distinguishes non-recovered patients from others, showed very high accuracy (prediction accuracy, 98.7%). The second step model, which distinguishes almost-recovered patients from healthy controls, showed high accuracy (prediction accuracy, 81.3%). This study is the first report to use hair follicles of MUD patients and to develop a MUD prediction model based on transcriptomic biomarkers, which offers a potential solution to improve the accuracy of MUD diagnosis and may lead to the development of better pharmacological treatments for the disorder in the future.

Association between Serum Prolactin Levels and Neurodegenerative Diseases: Systematic Review and Meta-Analysis.

INTRODUCTION: Prolactin (PRL) exerts inflammatory and anti-inflammatory properties and is also thought to play an important role in the pathogenesis of neurodegenerative diseases (NDs). However, serum PRL levels in patients with NDs were inconsistent in the research literature. OBJECTIVE: We aimed to assess the serum PRL levels in patients with NDs. METHODS: Electronic databases, including MEDLINE, Embase, Cochrane Library database, clinicaltrials.gov, Web of Science, and Google Scholar, and reference lists of articles were searched up to December 31, 2020. Pooled standard mean difference (SMD) with 95% confidence interval (CI) was calculated by fixed-effect or random-effect model analysis. RESULTS: A total of 36 comparisons out of 29 studies (3 RCTs and 26 case controls) focusing on NDs (including Parkinson's disease, Alzheimer's disease, Huntington's disease [HD], multiple sclerosis [MS], and epilepsy) were reported. The meta-analysis showed that there was no statistically significant difference in serum PRL levels between patients with NDs and healthy controls (SMD = 0.40, 95% CI: -0.16 to 0.96, p = 0.16). Subgroup analysis showed that serum PRL levels in patients with HD and MS were higher than those of healthy controls. Furthermore, patients with NDs aged <45 years had higher serum PRL levels (SMD = 0.97, 95% CI: 0.16-1.78, p = 0.018) than healthy controls. High serum PRL levels were found in subgroups such as the microenzymatic method, Asia, and the Americas. CONCLUSIONS: Our meta-analysis showed serum PRL levels in patients with HD and MS were significantly higher than those in healthy controls. Serum PRL levels were associated with age, region, and detection method. Other larger sample studies using more uniform detection methods are necessary to confirm our results.

Pitavastatin induces apoptosis in oral squamous cell carcinoma through activation of FOXO3a.

Statins are a class of lipid-lowering drugs that have recently been used in drug repositioning in the treatment of human cancer. However, the underlying mechanism of statin-induced cancer cell death has not been clearly defined. In the present study, we evaluated the anticancer effect of pitavastatin on oral squamous cell carcinoma (OSCC), SCC15 and SCC4 cells and found that FOXO3a might be a direct target in pitavastatin-induced cancer cell death. Our data revealed that pitavastatin selectively suppressed cell viability and induced intrinsic apoptosis in a FOXO3a-dependent manner in SCC15 cells while no effect was observed in SCC4 cells. Notably, treatment with pitavastatin in SCC15 cells induced the nuclear translocation of FOXO3a via dual regulation of two upstream kinases, AMPK and Akt, resulting in the up-regulation of PUMA, a transcriptional target gene of FOXO3a. Furthermore, our data revealed that FOXO3a-mediated PUMA induction plays a role in pitavastatin-induced intrinsic apoptosis in SCC15 cells. Taken together, our findings suggest that pitavastatin activates the FOXO3a/PUMA apoptotic axis by regulation of nuclear translocation of FOXO3a via Akt/FOXO3a or AMPK/FOXO3a signalling. Therefore, these findings might help to elucidate the underlying mechanism of the anticancer effects of pitavastatin on OSCC.

Effects of CYP2C19 and CYP3A5 genetic polymorphisms on the pharmacokinetics of cilostazol and its active metabolites.

PURPOSE: CYP3A4, CYP2C19, and CYP3A5 are primarily involved in the metabolism of cilostazol. We investigated the effects of CYP2C19 and CYP3A5 genetic polymorphisms on the pharmacokinetics of cilostazol and its two active metabolites. METHODS: Thirty-three healthy Korean volunteers were administered a single 100-mg oral dose of cilostazol. The concentrations of cilostazol and its active metabolites (OPC-13015 and OPC-13213) in the plasma were determined by HPLC-MS/MS. RESULTS: Although the pharmacokinetic parameters for cilostazol were similar in different CYP2C19 and CYP3A5 genotypes, CYP2C19PM subjects showed significantly higher AUC0-∞ for OPC-13015 and lower for OPC-13213 compared to those in CYP2C19EM subjects (P < 0.01 and P < 0.001, respectively). Pharmacokinetic differences in OPC-13015 between CYP3A5 non-expressors and expressors were significant only within CYP2C19PM subjects. The amount of cilostazol potency-adjusted total active moiety was the greatest in subjects with CYP2C19PM-CYP3A5 non-expressor genotype. CONCLUSION: These results suggest that CYP2C19 and CYP3A5 genetic polymorphisms affect the plasma exposure of cilostazol total active moiety. CYP2C19 plays a crucial role in the biotransformation of cilostazol.

Strongly increased exposure of meloxicam in CYP2C9*3/*3 individuals.

OBJECTIVE: The effects of CYP2C9*1/*3 and *3/*3 genotypes on the pharmacokinetics and pharmacodynamics of meloxicam were evaluated in healthy Korean subjects. METHODS: After oral administration of 15 mg meloxicam, the plasma concentrations of meloxicam were assessed in 11 CYP2C9*1/*1 individuals, eight CYP2C9*1/*3 individuals, and three CYP2C9*3/*3 individuals. The pharmacodynamic effects were determined by measuring thromboxane B2 generated in blood. RESULTS: A nine-fold lower apparent oral clearance and an eight-fold higher AUC0-∞ of single-dose meloxicam were observed in CYP2C9*3/*3 individuals when compared with CYP2C9*1/*1 individuals. CYP2C9*3/*3 individuals also showed markedly increased inhibition of thromboxane B2 generation by meloxicam. CONCLUSION: These results indicate that CYP2C9*3/*3 individuals may be at a higher risk for concentration-dependent adverse effects during long-term treatment with standard doses of meloxicam.

Effects of CYP2C19 genetic polymorphisms on atomoxetine pharmacokinetics.

Atomoxetine is a selective norepinephrine reuptake inhibitor indicated for the treatment of attention-deficit/hyperactivity disorder. Atomoxetine metabolism is mediated by CYP2D6 and CYP2C19. This study aimed to investigate the effect of the CYP2C19 genetic polymorphism on the pharmacokinetics of atomoxetine and its metabolites, 4-hydroxyatomoxetine and N-desmethylatomoxetine. A single 40-mg oral dose of atomoxetine was administered to 40 subjects with different CYP2C19 genotypes (all participants carried the CYP2D6*1/*10 genotype). Concentrations of atomoxetine and its metabolites were analyzed using high-performance liquid chromatography with tandem mass spectrometry in plasma samples that were collected up to 24 hours after drug intake. For atomoxetine, the CYP2C19 poor metabolizer (PM) group showed significantly increased maximum plasma concentration and AUC0-∞ (area under the plasma concentration-time curve from 0 to infinity) and decreased apparent oral clearance compared with samples of the CYP2C19 extensive metabolizer (EM) and intermediate metabolizer (IM) groups (P < 0.001 for all). The half-life of atomoxetine in the CYP2C19PM group was also significantly longer than in the other genotype groups (P < 0.01 for CYP2C19EM and P < 0.05 for CYP2C19IM groups). The maximum plasma concentration and AUC 0-∞ of 4-hydroxyatomoxetine were significantly higher in the CYP2C19PM group compared with those in the CYP2C19EM and IM groups (P < 0.001 for CYP2C19EM and P < 0.05 for CYP2C19IM, respectively), whereas the corresponding values for N-desmethylatomoxetine in the CYP2C19PM group were significantly lower than those in the 2 genotype groups (P < 0.001 for both genotype groups). These results suggest that the genetic polymorphisms of CYP2C19 significantly affect the pharmacokinetics of atomoxetine.

Ursodeoxycholic acid, an inhibitor of hepatocyte nuclear factor 1α, did not increase the systemic exposure of pitavastatin.

OBJECTIVE: Pitavastatin, a highly potent inhibitor of 3-hydroxy-methylglutarylcoenzyme A reductase, is a known substrate of OATP1B1. Ursodeoxycholic acid (UDCA) inhibits OATP1B1 expression by repressing hepatocyte nuclear factor 1α (HNF1α). Thus, the effects of UDCA on the pharmacokinetics of pitavastatin were investigated in healthy subjects. METHODS: An open-label, 2-phase, parallel study was conducted with 13 healthy volunteers. In the control phase, after an overnight fast, each subject received a single dose of 2 mg pitavastatin. After a 1-week washout period, in the UDCA phase, subjects received a daily oral dose of 600 mg of UDCA (300 mg b.i.d.) for 14 days. On day 15, 2 mg of pitavastatin was administered as described previously for the control phase. RESULTS: In the UDCA phase, the maximum plasma concentration (C(max)) of pitavastatin was slightly higher than in the control phase (48.6 ± 22.9 ng/mL vs. 42.4 ± 16.1 ng/mL). However, the overall pharmacokinetic parameters of pitavastatin and pitavastatin lactone during the two study phases were not significantly different. CONCLUSIONS: UDCA had no significant effect on the pharmacokinetics of pitavastatin. These results do not support the notion that UDCA increases the systemic exposure of OATP1B1 substrate by inhibiting HNF1α and decreasing OATP1B1 transporter expression.

Physiologically based pharmacokinetic (PBPK) modeling of pitavastatin in relation to SLCO1B1 genetic polymorphism.

Pitavastatin, a potent 3-hydroxymethylglutaryl coenzyme A reductase inhibitor, is indicated for the treatment of hypercholesterolemia and mixed dyslipidemia. Hepatic uptake of pitavastatin is predominantly occupied by the organic anion transporting polypeptide 1B1 (OATP1B1) and solute carrier organic anion transporter family member 1B1 (SLCO1B1) gene, which is a polymorphic gene that encodes OATP1B1. SLCO1B1 genetic polymorphism significantly alters the pharmacokinetics of pitavastatin. This study aimed to establish the physiologically based pharmacokinetic (PBPK) model to predict pitavastatin pharmacokinetics according to SLCO1B1 genetic polymorphism. PK-Sim® version 10.0 was used to establish the whole-body PBPK model of pitavastatin. Our pharmacogenomic data and a total of 27 clinical pharmacokinetic data with different dose administration and demographic properties were used to develop and validate the model, respectively. Physicochemical properties and disposition characteristics of pitavastatin were acquired from previously reported data or optimized to capture the plasma concentration-time profiles in different SLCO1B1 diplotypes. Model evaluation was performed by comparing the predicted pharmacokinetic parameters and profiles to the observed data. Predicted plasma concentration-time profiles were visually similar to the observed profiles in the non-genotyped populations and different SLCO1B1 diplotypes. All fold error values for AUC and Cmax were included in the two fold range of observed values. Thus, the PBPK model of pitavastatin in different SLCO1B1 diplotypes was properly established. The present study can be useful to individualize the dose administration strategy of pitavastatin in individuals with various ages, races, and SLCO1B1 diplotypes.

PBPK modeling to predict the pharmacokinetics of venlafaxine and its active metabolite in different CYP2D6 genotypes and drug-drug interactions with clarithromycin and paroxetine.

Venlafaxine, a serotonin-norepinephrine reuptake inhibitor (SNRI), is indicated for the treatment of major depressive disorder, social anxiety disorder, generalized anxiety disorder, and panic disorder. Venlafaxine is metabolized to the active metabolite desvenlafaxine mainly by CYP2D6. Genetic polymorphism of CYP2D6 and coadministration with other medications can significantly affect the pharmacokinetics and/or pharmacodynamics of venlafaxine and its active metabolite. This study aimed to establish the PBPK models of venlafaxine and its active metabolite related to CYP2D6 genetic polymorphism and to predict drug-drug interactions (DDIs) with clarithromycin and paroxetine in different CYP2D6 genotypes. Clinical pharmacogenomic data for venlafaxine and desvenlafaxine were collected to build the PBPK model. Physicochemical and absorption, distribution, metabolism, and excretion (ADME) characteristics of respective compounds were obtained from previously reported data, predicted by the PK-Sim® software, or optimized to capture the plasma concentration-time profiles. Model evaluation was performed by comparing the predicted pharmacokinetic parameters and plasma concentration-time profiles to the observed data. Predicted plasma concentration-time profiles of venlafaxine and its active metabolite were visually similar to the observed profiles and all predicted AUC and Cmax values for respective compounds were included in the twofold error range of observed values in non-genotyped populations and different CYP2D6 genotypes. When clarithromycin or clarithromycin plus paroxetine was concomitantly administered, predicted plasma concentration-time profiles of venlafaxine properly captured the observed profiles in two different CYP2D6 genotypes and all predicted DDI ratios for AUC and Cmax were included within the acceptance range. Consequently, the present model successfully captured the pharmacokinetic alterations of venlafaxine and its active metabolite according to CYP2D6 genetic polymorphism as well as the DDIs between venlafaxine and two CYP inhibitors. The present model can be used to predict the pharmacokinetics of venlafaxine and its active metabolite considering different races, ages, coadministered drugs, and CYP2D6 activity of individuals and it can contribute to individualized pharmacotherapy of venlafaxine.

Skp1 proteins are structural components of the synaptonemal complex in C. elegans.

The synaptonemal complex (SC) is a zipper-like protein assembly that links homologous chromosomes to regulate recombination and segregation during meiosis. The SC has been notoriously refractory to in vitro reconstitution, thus leaving its molecular organization largely unknown. Here, we report a moonlighting function of two paralogous S-phase kinase-associated protein 1 (Skp1)-related proteins (SKR-1 and SKR-2), well-known adaptors of the Skp1-Cul1-F-box (SCF) ubiquitin ligase, as the key missing components of the SC in Caenorhabditis elegans. SKR proteins repurpose their SCF-forming interfaces to dimerize and interact with meiosis-specific SC proteins, thereby driving synapsis independent of SCF activity. SKR-1 enables the formation of the long-sought-after soluble complex with previously identified SC proteins in vitro, which we propose it to represent a complete SC building block. Our findings demonstrate how a conserved cell cycle regulator has been co-opted to interact with rapidly evolving meiotic proteins to construct the SC and provide a foundation for understanding its structure and assembly mechanisms.

A chitosan/alginate coated nano-liposome to improve intestinal absorption of curcumin for oral administration.

Attempts to improve low absorption and rapid metabolic conversion of curcumin were made by developing curcumin-loaded bilayer nanoliposomes coated with chitosan and alginate for intestinal-specific drug delivery. A curcumin-loaded nano-liposome was prepared with optimized formulations with phosphatidylcholine, curcumin, chitosan, and alginate. The particle size of the optimized formulation was approximately 400 nm, and the encapsulation efficiency was more than 99%. In the in vitro release study, curcumin release from the curcumin-loaded nanoliposome with double layers of chitosan/alginate (CNL-CH/AL) was suppressed in the simulated gastric fluid (SGF, pH 1.2) and enhanced in the simulated intestinal fluid (SIF, pH 6.8). In the in vivo pharmacokinetic study in rats, the CNL-CH/AL-treated group showed a prolonged absorption pattern of curcumin and the area under the plasma concentration-time curve from 0 to 24 h (AUC0-24) was improved 109-fold compared to the control group treated with a curcumin solution without a nanocarrier.

PBPK modeling to predict the pharmacokinetics of pantoprazole in different CYP2C19 genotypes.

Pantoprazole is used to treat gastroesophageal reflux disease (GERD), maintain healing of erosive esophagitis (EE), and control symptoms related to Zollinger-Ellison syndrome (ZES). Pantoprazole is mainly metabolized by cytochrome P450 (CYP) 2C19, converting to 4'-demethyl pantoprazole. CYP2C19 is a genetically polymorphic enzyme, and the genetic polymorphism affects the pharmacokinetics and/or pharmacodynamics of pantoprazole. In this study, we aimed to establish the physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics of pantoprazole in populations with various CYP2C19 metabolic activities. A comprehensive investigation of previous reports and drug databases was conducted to collect the clinical pharmacogenomic data, physicochemical data, and disposition properties of pantoprazole, and the collected data were used for model establishment. The model was evaluated by comparing the predicted plasma concentration-time profiles and/or pharmacokinetic parameters (AUC and Cmax) with the clinical observation results. The predicted plasma concentration-time profiles in different CYP2C19 phenotypes properly captured the observed profiles. All fold error values for AUC and Cmax were included in the two-fold range. Consequently, the minimal PBPK model for pantoprazole related to CYP2C19 genetic polymorphism was properly established and it can predict the pharmacokinetics of pantoprazole in different CYP2C19 phenotypes. The present model can broaden the insight into the individualized pharmacotherapy for pantoprazole.

Effects of OCT2 c.602C > T genetic variant on the pharmacokinetics of lamivudine.

1. The renal excretion of organic cation drugs, including lamivudine, is mostly mediated by OCT2 in vitro. To date, three putatively relevant single nucleotide polymorphisms (SNPs), including c.596C > T (p.Thr199Ile), c.602C > T (p.Thr201Met), and c.808G > T (p.Ala270Ser) have been observed in Asians. The effects of the SLC22A2 c.602C > T genetic variant on the pharmacokinetics of lamivudine were studied with healthy Korean subjects. 2. Nineteen healthy subjects carrying either the SLC22A2 c.602CC (n = 12) or c.602CT (n = 7) genotype volunteered for this study. A single 100 mg dose of lamivudine was orally administered to each subject. Blood samples were collected for up to 24 h and the plasma concentrations of lamivudine were measured using liquid chromatography-tandem mass spectrometry. 3. The mean plasma concentration-time profiles of lamivudine in the c.602CC and c.602CT genotype groups were similar. There was no significant difference in the overall pharmacokinetic parameters of lamivudine between the c.602CC and c.602CT genotype groups. Differences in renal clearance and tubular secretion clearance were also not statistically significant between the two genotype groups. 4. The SLC22A2 c.602C > T genotype did not affect the pharmacokinetics of lamivudine in humans in vivo. Dose adjustment of lamivudine is not required between individuals with c.602CC and c.602CT genotypes.

Alcohol perturbed locomotor behavior, metabolism, and pharmacokinetics of gamma-hydroxybutyric acid in rats.

Gamma-hydroxybutyric acid (GHB), both a metabolic precursor and product of gamma-aminobutyric acid (GABA), is a central nervous system depressant used for the treatment of narcolepsy-associated cataplexy and alcohol withdrawal. However, administration of GHB with alcohol (ethanol) is a major cause of hospitalizations related to GHB intoxication. In this study, we investigated locomotor behavior as well as metabolic and pharmacokinetic interactions following co-administration of GHB and ethanol in rats. The locomotor behavior of rats was evaluated following the intraperitoneal administration of GHB (sodium salt, 500 mg/kg) and/or ethanol (2 g/kg). Further, time-course urinary metabolic profiling of GHB and its biomarker metabolites glutamic acid, GABA, succinic acid, 2,4-dihydroxybutyric acid (OH-BA), 3,4-OH-BA, and glycolic acid as well as pharmacokinetic analysis were performed. GHB/ethanol co-administration significantly reduced locomotor activity, compared to the individual administration of GHB or ethanol. The urinary and plasma concentrations of GHB and other target compounds, except for 2,4-OH-BA, were significantly higher in the GHB/ethanol co-administration group than the group administered only GHB. The pharmacokinetic analysis results showed that the co-administration of GHB and ethanol significantly increased the half-life of GHB while the total clearance decreased. Moreover, a comparison of the metabolite-to-parent drug area under the curve ratios demonstrated that the metabolic pathways of GHB, such α- and ß-oxidation, were inhibited by ethanol. Consequently, the co-administration of GHB and ethanol aggravated the metabolism and elimination of GHB and enhanced its sedative effect. These findings will contribute to clinical interpretation of GHB intoxication.

Effects of CYP2C9 and CYP2C19 genetic polymorphisms on the pharmacokinetics and pharmacodynamics of gliclazide in healthy subjects.

Gliclazide metabolism is mediated by genetically polymorphic CYP2C9 and CYP2C19 enzymes. We investigated the effects of CYP2C9 and CYP2C19 genetic polymorphisms on the pharmacokinetics and pharmacodynamics of gliclazide. Twenty-seven Korean healthy volunteers were administered a single oral dose of gliclazide 80 mg. The plasma concentration of gliclazide was quantified for the pharmacokinetic analysis and plasma concentrations of glucose and insulin were measured as pharmacodynamic parameters. The pharmacokinetics of gliclazide showed a significant difference according to the number of defective alleles of combined CYP2C9 and CYP2C19. The two defective alleles group (group 3) and one defective allele group (group 2) showed 2.34- and 1.46-fold higher AUC0-∞ (P < 0.001), and 57.1 and 32.3% lower CL/F (P < 0.001), compared to those of the no defective allele group (group 1), respectively. The CYP2C9IM-CYP2C19IM group had AUC0-∞ increase of 1.49-fold (P < 0.05) and CL/F decrease by 29.9% (P < 0.01), compared with the CYP2C9 Normal Metabolizer (CYP2C9NM)-CYP2C19IM group. The CYP2C9NM-CYP2C19PM group and CYP2C9NM-CYP2C19IM group showed 2.41- and 1.51-fold higher AUC0-∞ (P < 0.001), and 59.6 and 35.4% lower CL/F (P < 0.001), compared to those of the CYP2C9NM-CYP2C19NM group, respectively. The results represented that CYP2C9 and CYP2C19 genetic polymorphisms significantly affected the pharmacokinetics of gliclazide. Although the genetic polymorphism of CYP2C19 had a greater effect on the pharmacokinetics of gliclazide, the genetic polymorphism of CYP2C9 also had a significant effect. On the other hand, plasma glucose and insulin responses to gliclazide were not significantly affected by the CYP2C9-CYP2C19 genotypes, requiring further well-controlled studies with long-term dosing of gliclazide in diabetic patients.

Effects of CYP2D6*10 allele on the pharmacokinetics of tolperisone.

Tolperisone, a muscle relaxant used for post-stroke spasticity, has been reported to have a very wide interindividual pharmacokinetic variability. It is metabolized mainly by CYP2D6 and, to a lesser extent, by CYP2C19 and CYP1A2. CYP2D6 is a highly polymorphic enzyme, and CYP2D6*wt/*wt, CYP2D6*wt/*10 and CYP2D6*10/*10 genotypes constitute more than 90% of the CYP2D6 genotypes in the Korean population. Thus, effects of the CYP2D6*10 on tolperisone pharmacokinetics were investigated in this study to elucidate the reasons for the wide interindividual variability. Oral tolperisone 150 mg was given to sixty-four healthy Koreans, and plasma concentrations of tolperisone were measured by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The CYP2D6*10/*10 and CYP2D6*wt/*10 groups had significantly higher Cmax and lower CL/F values than the CYP2D6*wt/*wt group. The AUCinf of CYP2D6*10/*10 and CYP2D6*wt/*10 groups were 5.18-fold and 2.25-fold higher than the CYP2D6*wt/*wt group, respectively. There were considerable variations in the Cmax and AUC values within each genotype group, and the variations were greater as the activity of CYP2D6 decreased. These results suggest that the genetic polymorphism of CYP2D6 significantly affected tolperisone pharmacokinetics and factor(s) other than CYP2D6 may also have significant effects on the pharmacokinetics of tolperisone.

CYP2C9 3 and 13 alleles significantly affect the pharmacokinetics of irbesartan in healthy Korean subjects.

PURPOSE: To evaluate the effects of two major polymorphisms of CYP2C9, CYP2C9 3 and CYP2C9 13, on the pharmacokinetics of irbesartan in healthy Korean volunteers. METHODS: A single 150-mg oral dose of irbesartan was given to 28 Korean volunteers, who had different CYP2C9 genotypes (12, 10, and 6 carriers of CYP2C9 1/ 1, 1/ 3, and 1/13 genotypes respectively). Irbesartan levels were analyzed using HPLC fluorescence in plasma samples collected up to 36 h after the drug intake. RESULTS: Compared with CYP2C9 1 homozygous subjects, not only were the maximum plasma concentrations (C(max)) of irbesartan in CYP2C9 1/ 3 and 1/ 13 subjects 1.56- and 1.50-fold higher (P = 0.001), but the half-lives were also 1.38- and 1.50-fold longer (P = 0.001). The area under the plasma concentration-time curve (AUC) was 1.64- and 1.79-fold higher (P < 0.001). The oral clearance of irbesartan was 39.3% and 44.0% lower in the CYP2C9 1/ 3 and 1/ 13 subjects respectively, than in the 1/ 1 subjects (P < 0.001). Likewise, the increases in half-life and decreases in oral clearance observed in CYP2C9 1/ 13 individuals were similar to those in participants expressing the CYP2C9 1/ 3 genotype. CONCLUSIONS: CYP2C9 genetic polymorphisms markedly affected the pharmacokinetics of irbesartan in this study sample. The CYP2C9 3 and CYP2C9 13 alleles appear to be associated with the decreased metabolism of irbesartan.

Effects of the SLCO1B1*15 allele on the pharmacokinetics of pitavastatin.

The hepatic uptake of pitavastatin is mediated by carriers, especially OATP1B1, which is encoded by the SLCO1B1 gene. Because the liver is a target organ of pitavastatin, OATP1B1 is responsible for both the pharmacological effects and clearance of pitavastatin. The effects of the SLCO1B1*15 allele on the pharmacokinetics (PK) of pitavastatin were studied. Pitavastatin 2 mg was orally administered to 38 subjects with SLCO1B1*1a/*1b (n = 20), *1b/*15 (n = 13), or *15/*15 (n = 5). After pitavastatin administration, the plasma concentrations of pitavastatin and pitavastatin lactone were assayed for up to 48 h using liquid chromatography-tandem mass spectrometry. In comparison to the SLCO1B1*1a/*1b subjects, only a C(max) was slightly higher in the SLCO1B1*1b/*15 subjects. However, the SLCO1B1*15/*15 subjects had a 1.74-fold higher AUC(inf) (285.5 ± 14.5 vs. 164.6 ± 41.3 ng·h/mL; p < 0.001), a 2.21-fold higher C(max) (106.7 ± 15.1 vs. 48.3 ± 13.4 ng/mL; p < 0.001), and a 47.3% lower apparent oral clearance (13.1 ± 3.9 vs. 6.9 ± 0.4 L/h; p < 0.001) of pitavastatin. For pitavastatin lactone, there were no significant differences in AUC(inf), C(max), t(1/2), and t(max) among the three genotypes. Unlike previous studies, the disposition of pitavastatin exposure was not altered in subjects with the SLCO1B1*1b/*15 genotype, except C(max). However, pitavastatin exposure was significantly increased in subjects with the SLCO1B1*15/*15 genotype due to reduced hepatic absorption.

Effects of CYP2C9*1/*3 and *1/*13 on the pharmacokinetics of losartan and its active metabolite E-3174.

OBJECTIVE: The effects of CYP2C9*1/*3 and *1/*13 genotypes were evaluated on the pharmacokinetics of losartan and its active metabolite, E-3174, in Korean subjects. METHODS: Losartan (50 mg) was administered in 43 Korean volunteers with different CYP2C9 genotypes (CYP2C9*1/*1, *1/*3 and *1/*13). Losartan and E-3174 levels in the plasma and urine were analyzed by HPLC using fluorescence. RESULTS: The CYP2C9*1/*13 subjects showed lower oral clearance (p < 0.001) and greater AUC0-∞ (p < 0.01) of losartan and higher Cmax (p < 0.01) and longer half-life (p < 0.001) of E-3174 than the CYP2C9*1/*1 subjects, but AUC0-∞ of E-3174 was not different. The CYP2C9*1/*3 subjects showed lower oral clearance (p < 0.001) of losartan and higher Cmax (p < 0.01) and longer half-life (p < 0.01) of E-3174 than the CYP2C9*1/*1 subjects. However, AUC0-∞ of losartan was greater in CYP2C9*1/*3 subjects than in CYP2C9*1/*1, but these results were not significant (p < 0.05, but statistical power < 0.8). In addition, AUC0-∞ of E-3174 was not different. There were no significant differences in pharmacokinetic parameters between the CYP2C9*1/*13 and CYP2C9*1/*3 subjects. CONCLUSION: These results suggest that CYP2C9*1/*3 and CYP2C9*1/*13 are similarly associated with decreased formation of E-3174 from losartan, but the clinical effects of losartan may not be reduced by CYP2C9*1/*3 and CYP2C9*1/*13.

Effects of CYP2C9*3 and *13 alleles on the pharmacokinetics and pharmacodynamics of glipizide in healthy Korean subjects.

Glipizide is a second-generation sulfonylurea antidiabetic drug. It is principally metabolized to inactive metabolites by genetically polymorphic CYP2C9 enzyme. In this study, we investigated the effects of CYP2C9*3 and *13 variant alleles on the pharmacokinetics and pharmacodynamics of glipizide. Twenty-four healthy Korean volunteers (11 subjects with CYP2C9*1/*1, 8 subjects with CYP2C9*1/*3, and 5 subjects with CYP2C9*1/*13) were recruited for this study. They were administered a single oral dose of glipizide 5 mg. The plasma concentration of glipizide was quantified for pharmacokinetic analysis and plasma glucose and insulin concentrations were measured as pharmacodynamic parameters. The results represented that CYP2C9*3 and *13 alleles significantly affected the pharmacokinetics of glipizide. In subjects with CYP2C9*1/*3 and CYP2C9*1/*13 genotypes, the mean AUC0-∞ were increased by 44.8% and 58.2%, respectively (both P < 0.001), compared to those of subjects with CYP2C9*1/*1 genotype, while effects of glipizide on plasma glucose and insulin levels were not significantly different between CYP2C9 genotype groups. In conclusion, individuals carrying the defective CYP2C9*3 and CYP2C9*13 alleles have markedly elevated plasma concentrations of glipizide compared with CYP2C9*1/*1 wild-type.