No significant effect of ABCB1 haplotypes on the pharmacokinetics of fluvastatin, pravastatin, lovastatin, and rosuvastatin.
ABSTRACT: AIMS: This study aimed to investigate possible effects of ABCB1 genotype on fluvastatin, pravastatin, lovastatin, and rosuvastatin pharmacokinetics. METHODS: In a fixed-order crossover study, 10 healthy volunteers with the ABCB1 c.1236C/C-c.2677G/G-c.3435C/C (CGC/CGC) genotype and 10 with the c.1236T/T-c.2677T/T-c.3435T/T (TTT/TTT) genotype ingested a single 20-mg dose of fluvastatin, pravastatin, lovastatin, and rosuvastatin. Plasma fluvastatin, pravastatin, and lovastatin concentrations were measured up to 12 h and plasma and urine rosuvastatin concentrations up to 48 and 24 h, respectively. RESULTS: The ABCB1 genotype had no significant effect on the pharmacokinetics of any of the investigated statins. The geometric mean ratio (95% confidence interval) of the area under the plasma concentration-time curve from 0 h to infinity (AUC(0-infinity)) in participants with the TTT/TTT genotype to that in those with the CGC/CGC genotype was 0.96 (0.77, 1.20; P= 0.737) for fluvastatin, 0.92 (0.53, 1.62; P= 0.772) for pravastatin, 0.83 (0.36, 1.90; P= 0.644) for lovastatin, 1.25 (0.72, 2.17; P= 0.400) for lovastatin acid, and 1.10 (0.73, 1.65; P= 0.626) for rosuvastatin. The AUC(0-infinity) of lovastatin acid correlated significantly with that of rosuvastatin (r= 0.570, P= 0.009), but none of the other AUC(0-infinity) pairs showed a significant correlation. CONCLUSIONS: These data suggest that the ABCB1 c.1236C-c.2677G-c.3435C and c.1236T-c.2677T-c.3435T haplotypes play no significant role in the interindividual variability in the pharmacokinetics of fluvastatin, pravastatin, lovastatin, and rosuvastatin.
Project description:The objectives of this study were to determine if ABCB1 polymorphisms are associated with interindividual variability in sitagliptin pharmacokinetics and if atorvastatin alters the pharmacokinetic disposition of sitagliptin in healthy volunteers.In this open-label, randomized, two-phase crossover study, healthy volunteers were prospectively stratified according to ABCB1 1236/2677/3435 diplotype (n = 9, CGC/CGC; n = 10, CGC/TTT; n = 10, TTT/TTT). In one phase, participants received a single 100 mg dose of sitagliptin; in the other phase, participants received 40 mg of atorvastatin for 5 days, with a single 100 mg dose of sitagliptin administered on day 5. A 24-h pharmacokinetic study followed each sitagliptin dose, and the study phases were separated by a 14-day washout period.Sitagliptin pharmacokinetic parameters did not differ significantly between ABCB1 CGC/CGC, CGC/TTT, and TTT/TTT diplotype groups during the monotherapy phase. Atorvastatin administration did not significantly affect sitagliptin pharmacokinetics, with geometric mean ratios (90 % confidence intervals) for sitagliptin maximum plasma concentration, plasma concentration-time curve from zero to infinity, renal clearance, and fraction of sitagliptin excreted unchanged in the urine of 0.93 (0.86-1.01), 0.96 (0.91-1.01), 1.02 (0.93-1.12), and 0.98 (0.90-1.06), respectively.ABCB1 CGC/CGC, CGC/TTT, and TTT/TTT diplotypes did not influence sitagliptin pharmacokinetics in healthy volunteers. Furthermore, atorvastatin had no effect on the pharmacokinetics of sitagliptin in the setting of ABCB1 CGC/CGC, CGC/TTT, and TTT/TTT diplotypes.
Project description:BACKGROUND: Cholesterol management drugs known as statins are widely used and often well tolerated; however, a variety of muscle-related side effects can arise. These adverse events (AEs) can have serious impact, and form a significant barrier to therapy adherence. Surveillance of post-marketing AEs is of vital importance to understand real-world AEs and reporting differences between individual statin drugs. We conducted a review of post-approval muscle and tendon AE reports in association with statin use, to assess differences within the drug class. METHODS: We analyzed all case reports from the FDA AE Reporting System (AERS) database linking muscle-related AEs to statin use (07/01/2005-03/31/2011). Drugs examined were: atorvastatin, simvastatin, lovastatin, pravastatin, rosuvastatin, and fluvastatin. RESULTS: Relative risk rates for rosuvastatin were consistently higher than other statins. Atorvastatin and simvastatin showed intermediate risks, while pravastatin and lovastatin appeared to have the lowest risk rates. Relative risk of muscle-related AEs, therefore, approximately tracked with per milligram LDL-lowering potency, with fluvastatin an apparent exception. Incorporating all muscle categories, rates for atorvastatin, simvastatin, pravastatin, and lovastatin were, respectively, 55%, 26%, 17%, and 7.5% as high, as rosuvastatin, approximately tracking per milligram potency (Rosuvastatin>Atorvastatin>Simvastatin>Pravastatin ? Lovastatin) and comporting with findings of other studies. Relative potency, therefore, appears to be a fundamental predictor of muscle-related AE risk, with fluvastatin, the least potent statin, an apparent exception (risk 74% vs rosuvastatin). INTERPRETATION: AE reporting rates differed strikingly for drugs within the statin class, with relative reporting aligning substantially with potency. The data presented in this report offer important reference points for the selection of statins for cholesterol management in general and, especially, for the rechallenge of patients who have experienced muscle-related AEs (for whom agents of lower expected potency should be preferred).
Project description:Introduction:No proven drug and no immunisation are yet available for COVID-19 disease. The SARS-CoV-2 main protease (Mpro), a key coronavirus enzyme, which is a potential drug target, has been successfully crystallised. There is evidence suggesting that statins exert anti-viral activity and may block the infectivity of enveloped viruses. The aim of this study was to assess whether statins are potential COVID-19 Mpro inhibitors, using a molecular docking study. Material and methods:Molecular docking was performed using AutoDock/Vina, a computational docking program. SARS-CoV-2 Mpro was docked with all statins, while antiviral and antiretroviral drugs - favipiravir, nelfinavir, and lopinavir - were used as standards for comparison. Results:The binding energies obtained from the docking of 6LU7 with native ligand favipiravir, nelfinavir, lopinavir, simvastatin, rosuvastatin, pravastatin, pitavastatin, lovastatin, fluvastatin, and atorvastatin were -6.8, -5.8, -7.9, -7.9, -7.0, -7.7, -6.6, -8.2, -7.4, -7.7, and -6.8 kcal/mol, respectively. The number of hydrogen bonds between statins and amino acid residues of Mpro were 7, 4, and 3 for rosuvastatin, pravastatin, and atorvastatin, respectively, while other statins had two hydrogen bonds. Conclusions:These results indicate, based upon the binding energy of pitavastatin, rosuvastatin, lovastatin, and fluvastatin, that statins could be efficient SARS-CoV-2 Mpro inhibitors. This is supported by the fact that the effects of some statins, especially pitavastatin, have a binding energy that is even greater than that of protease or polymerase inhibitors. However, further research is necessary to investigate their potential use as drugs for COVID-19.
Project description:Objective:To assess the effect of statins compared with placebo on the risk of developing hypertransaminasemia. Patients and Methods:We performed a systematic review of electronic databases and included articles published between January 1, 1965, and April 10, 2017. Randomized clinical trials (RCTs) comparing statins vs placebo were included. Odds ratios (ORs) were pooled in random-effect meta-analyses according to established methods recommended by the Cochrane Collaboration. Results:Seventy-three eligible RCTs, comprising 123,051 patients, were identified. Statins associated with a significantly risk of hypertransaminasemia (OR 1.45; 95% confidence interval [CI], 1.24-1.69; P<.001). Atorvastatin showed the highest odds (OR 2.66; 95% CI, 1.74-4.06; P<.001) followed by rosuvastatin (OR 1.35; 95% CI, 1.06-1.70; P=.01) and lovastatin (OR 1.53; 95% CI, 1.03-2.28; P=.04). Pravastatin, fluvastatin, and simvastatin yielded no statistically different odds compared with placebo. Conclusions:A dose-dependent risk of developing hypertransaminasemia occurs in patients taking atorvastatin, rosuvastatin, and lovastatin.
Project description:Introduction:Statins are known to lower CRP, and this reduction has been suggested to contribute to the established efficacy of these drugs in reducing cardiovascular events and outcomes. However, the exact mechanism underlying the CRP-lowering effect of statins remains elusive. Methods:In order to test the possibility of direct interaction, we performed an <i>in silico</i> study by testing the orientation of the respective ligands (statins) and phosphorylcholine (the standard ligand of CRP) in the CRP active site using Molecular Operating Environment (MOE) software. Results:Docking experiments showed that all statins could directly interact with CRP. Among statins, rosuvastatin had the strongest interaction with CRP (pKi = 16.14), followed by fluvastatin (pKi = 15.58), pitavastatin (pKi = 15.26), atorvastatin (pKi = 14.68), pravastatin (pKi = 13.95), simvastatin (pKi = 7.98) and lovastatin (pKi = 7.10). According to the above-mentioned results, rosuvastatin, fluvastatin, pitavastatin and atorvastatin were found to have stronger binding to CRP compared with the standard ligand phosphocholine (pKi = 14.55). Conclusions:This finding suggests a new mechanism of interaction between statins and CRP that could be independent of the putative cholesterol-lowering activity of statins.
Project description:To date, malignant pheochromocytomas and paragangliomas (PHEOs/PGLs) cannot be effectively cured and thus novel treatment strategies are urgently needed. Lovastatin has been shown to effectively induce apoptosis in mouse PHEO cells (MPC) and the more aggressive mouse tumor tissue-derived cells (MTT), which was accompanied by decreased phosphorylation of mitogen-activated kinase (MAPK) pathway players. The MAPK pathway plays a role in numerous aggressive tumors and has been associated with a subgroup of PHEOs/PGLs, including K-RAS-, RET-, and NF1-mutated tumors. Our aim was to establish whether MAPK signaling may also play a role in aggressive, succinate dehydrogenase (SDH) B mutation-derived PHEOs/PGLs. Expression profiling and western blot analysis indicated that specific aspects of MAPK-signaling are active in SDHB PHEOs/PGLs, suggesting that inhibition by statin treatment could be beneficial. Moreover, we aimed to assess whether the anti-proliferative effect of lovastatin on MPC and MTT differed from that exerted by fluvastatin, simvastatin, atorvastatin, pravastatin, or rosuvastatin. Simvastatin and fluvastatin decreased cell proliferation most effectively and the more aggressive MTT cells appeared more sensitive in this respect. Inhibition of MAPK1 and 3 phosphorylation following treatment with fluvastatin, simvastatin, and lovastatin was confirmed by western blot. Increased levels of CASP-3 and PARP cleavage confirmed induction of apoptosis following the treatment. At a concentration low enough not to affect cell proliferation, spontaneous migration of MPC and MTT was significantly inhibited within 24 hours of treatment. In conclusion, lipophilic statins may present a promising therapeutic option for treatment of aggressive human paragangliomas by inducing apoptosis and inhibiting tumor spread.
Project description:AIMS: To determine the frequencies of the genotypes of CYP3A5 and MDR1 and to examine the influence of the polymorphisms of these genes on tacrolimus pharmacokinetics in the Korean population. METHODS: Twenty-nine healthy Koreans who participated in the previous tacrolimus pharmacokinetic study were genotyped for CYP3A4*1B, CYP3A5*3, MDR1 c.1236C-->T, MDR1 c.2677G-->A/T and MDR1 c.3435C-->T. The relationship between the genotypes so obtained and tacrolimus pharmacokinetics observed in the previous study was examined. RESULTS: No subject in this study had the CYP3A4*1B variant. The observed frequencies of CYP3A5*1/*1, *1/*3, and *3/*3 were 0.069 [confidence interval (CI) -0.023, 0.161], 0.483 (CI 0.301, 0.665) and 0.448 (CI 0.267, 0.629), respectively. AUC(0-infinity) for the CYP3A5*1/*1 or *1/*3 genotype was 131.5 +/- 44.8 ng h ml(-1) (CI 109.6, 153.5), which was much lower compared with the CYP3A5*3/*3 genotype of 323.8 +/- 129.3 ng h ml(-1) (CI 253.5, 394.1) (P = 2.063E-07). Similarly, C(max) for the CYP3A5*1/*1 or *1/*3 genotype was 11.8 +/- 3.4 ng ml(-1) (CI 10.1, 13.5), which was also much lower compared with the CYP3A5*3/*3 genotype of 24.4 +/- 12.3 ng ml(-1) (CI 17.8, 31.1) (P = 0.0001). However, there was no significant difference in tacrolimus pharmacokinetics among the MDR1 diplotypes of CGC-CGC, CGC-TTT, CGC-TGC, TTT-TGC or TTT-TTT (P = 0.2486). CONCLUSIONS: This study shows that the CYP3A5*3 genetic polymorphisms may be associated with the individual difference in tacrolimus pharmacokinetics. An individualized dosage regimen design incorporating such genetic information would help increase clinical efficacy of the drug while reducing adverse drug reactions.
Project description:AIMS: Tacrolimus (TAC) is one of the most successful immunosuppressive drugs in transplantation. Its pharmacokinetics (PK) and pharmacogenetics (PG) have been extensively studied, with many studies showing the influence of CYP3A5 on TAC metabolism and bioavailability. However, data concerning the functional significance of ABCB1 polymorphisms are uncertain due to inconsistent results. We evaluated the association between ABCB1 diplotypes, CYP3A5 polymorphisms and TAC disposition in a cohort of Brazilian transplant recipients. METHODS: Individuals were genotyped for the CYP3A5*3 allele and ABCB1 polymorphisms (2677G>A/T, 1236C>T, 3435C/T) using a TaqMan® PCR technique. Diplotypes were analyzed for correlation with the TAC dose-normalized ratio (Co?:?dose). RESULTS: We genotyped 108 Brazilian kidney recipients for CYP3A5 (11% CYP3A5*1/*1; 31% CYP3A5*1/*3 and 58% CYP3A5*3/*3) and ABCB1 haplotypes (42% CGC/CGC; 41% GCG/TTT and 17% TTT/TTT). Homozygous subjects for the CYP3A5*3 allele or carriers of the ABCB1?TTT/TTT diplotype showed a higher Co?:?dose ratio compared with wild type subjects [median (interquartile range) 130.2 (97.5-175.4) vs. 71.3 (45.6-109.0), P < 0.0001 and 151.8 (112.1-205.6) vs. 109.6 (58.1-132.9), P = 0.01, respectively]. When stratified for the CYP3A5*3 group, ABCB1?TTT/TTT individuals showed a higher Co?:?dose ratio compared with non-TTT/TTT individuals [167.8 (130.4-218.0) vs. 119.4 (100.2-166.3), P?=?0.04]. Multivariate linear regression analysis showed that the effects of CYP3A5 polymorphisms and ABCB1 diplotypes remained significant after correction for confounding factors. CONCLUSIONS: CYP3A5 is the major enzyme responsible for the marked interindividual variability in TAC PK, but it cannot be considered alone when predicting dose adjustment because ABCB1 diplotypes also affect TAC disposition, showing independent and additive effects on the TAC dose-normalized concentration.
Project description:Statins, potent lipid-lowering drugs, were also shown to exert anti-proliferative activity. The aim of this study was to identify the biological pathways affected by changes in gene expression activity after statins treatment and to compare the results with observed anti-proliferative effects. The study was performed in vitro on a pancreatic cancer cell line MIA PaCa-2. The changes in gene expression were measured after 24 h of treatment by the statins (atorvastatin, lovastatin, simvastatin, fluvastatin, cerivastatin, pravastatin, rosuvastatin, and pitavastatin). The statins affected expression of a significant number of genes with mevalonate pathway, cell cycle regulation, and DNA replication being the most affected metabolic/signalling pathways.
Project description:WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT: A single nucleotide polymorphism in ABCB1, which encodes P-glycoprotein, has retrospectively been associated with symptoms of nortriptyline-induced postural hypotension in depressed patients. This finding needs to be replicated in independent studies before recommendations regarding pharmacogenetic testing can be made. WHAT THIS STUDY ADDS: In a prospective study of healthy volunteers homozygous for ABCB1 (1236-2677-3435, TTT/TTT or CGC/CGC), a single dose of nortriptyline was administered, plasma exposure was determined and blood pressure and heart rate were monitored during posture change. No differences between ABCB1 haplotype groups were found in plasma exposure of nortriptyline and its active metabolites, E- and Z-10-hydroxynortriptyline. The heart rate response to posture change was increased with nortriptyline, whereas there was no difference in blood pressure response. However, no differences between haplotype groups were observed except that the pre dose heart rate response to standing was greater in the TTT than CGC homozygotes. The association between ABCB1 polymorphisms and nortriptyline-induced postural hypotension found in a previous study could not be confirmed. The results raise the possibility of a predisposition in heart rate response in the TTT homozygotes rather than an effect of nortriptyline. AIMS To investigate the influence of ABCB1 (1236-2677-3435) polymorphisms on nortriptyline pharmacokinetics and nortriptyline-induced postural hypotension in healthy volunteers. METHODS: Genetic screening of 67 healthy volunteers identified eight CGC homozygotes and nine TTT homozygotes of ABCB1 (1236-2677-3435), who were administered a single dose of nortriptyline 25 mg. Plasma exposure of nortriptyline and its active metabolites, E- and Z-10-hydroxynortriptyline, was determined over 72 h. Heart rate and blood pressure responses to posture change (active standing and passive head-up tilt) were measured continuously using finger plethysmography. RESULTS: There were no differences in plasma exposure between ABCB1 haplotype groups, as the geometric mean (95% CI) AUC(0,72 h) ratios were 0.98 (0.94, 1.03), 1.02 (0.96, 1.09) and 0.95 (0.80, 1.10) for nortriptyline, E- and Z-10-hydroxynortriptyline, respectively. The pre dose heart rate response to standing was greater in the TTT than CGC homozygotes (mean (95% CI) difference 7.4 (1.5, 13.4) beats min(-1) , P = 0.02). At t(max) at 8 h post dose, nortriptyline increased the heart rate response to posture change in all subjects with mean (95% CI) Δ heart rate values of 7.4 (3.6, 11.3) beats min(-1) on active standing (P = 0.0009) and 4.8 (2.0, 7.6) beats min(-1) on head-up tilt (P = 0.002), but no difference was observed between haplotype groups. There was no difference in blood pressure response to posture change in either group. CONCLUSION: The association between ABCB1 polymorphisms and nortriptyline-induced postural hypotension found in the previous study could not be confirmed. The results raise the possibility of a predisposition in heart rate response in the TTT homozygotes rather than an effect of nortriptyline.