Effect of the Interrelation between CYP3A5 Genotype, Concentration/Dose Ratio and Intrapatient Variability of Tacrolimus on Kidney Graft Function: Monte Carlo Simulation Approach

Background: Tacrolimus (Tac) is characterized by large between- and within-patient (IPV) variability in pharmacokinetics and exposure. Aim: This study aimed to assess and validate the effect of Tac IPV and trough concentration-to-dose ratio (C0/D) over 6–12 months on reduced estimated glomerular filtration rate (eGFR) values in the late period after kidney transplantation (Tx), applying Monte Carlo (MC) simulation. Methods: The previously published linear regression was the basis for MC simulation, performed to determine how variations in significant predictors affect the distribution of eGFR from 13 to 36 months post-transplantation. The input C0/D values were derived from CYP3A5 genotype subgroups. Results: Patients characterized by high Tac IPV and low mean C0/D over 6–12 months could have been at greater risk of lower eGFR values in a three-year period following Tx compared to the other patient groups. This effect was more pronounced in patients with a lower eGFR at the 6th month and a history of acute rejection. The proven contribution of CYP3A5 expresser genotype to low C0/D values may suggest its indirect effect on long-term graft function. Conclusion: The findings indicate that simultaneous assessment of Tac IPV, C0/D, and CYP3A5 genotype may identify patients at risk of deterioration of graft function in the long-term post-transplantation period.

The CYP3A5 and ABCB1 Gene Polymorphisms in Kidney Transplant Patients and Establishment of Initial Daily Tacrolimus Dosing Formula

Background Tacrolimus is an immunosuppressive drug used to prevent organ rejections. Many factors could influence blood concentration of tacrolimus. Objective To detect genotypes of cytochrome P450 3A5 ( CYP3A5) and ABCB1 in kidney transplant patients and establish initial daily tacrolimus dosing formula based on genotypes of CYP3A5 and ABCB1 and patients’ clinical parameters. Methods Sequence specific primer polymerase chain reaction (PCR) and PCR restriction fragment length polymorphism were used to detect genotypes of CYP3A5 and ABCB1. The blood cell, procalcitonin, C-reactive protein, height, weight, age, gender and other clinical parameters were recorded. Multiple linear regression analysis and Pearson correlation analysis were used to conduct date analysis. Results 102 cases were enrolled in cohort 1, and there were 10 cases of CYP3A5 *1/*1 (9.8%), 28 cases of CYP3A5 *1/*3 (27.5%), and 64 cases of CYP3A5 *3/*3 (62.7%). The distributions of ABCB1 C3435T genotype were CC 36 (35.3%), CT 52 (51.0%), and TT 14 (13.7%). The distributions of ABCB1 G2677T/A genotype were GG 39 (38.2%), GT 40 (39.2%), and TT 23 (22.5%). The formula was 7.499 + (0.053 × Weight) − (0.029 × Hemoglobin concentration) − (1.045 × CYP3A5 genotype) ( CYP3A5 genotype: *1/*1 type inputs 0, *1/*3 type inputs 1, *3/*3 type inputs 2). The predicted doses from the established formula had a significant correlation ( r = 0.605) with actual clinical doses ( P < 0.05). Conclusion and Relevance Hemoglobin concentration, weight, and CYP3A5 genotype should be considered using tacrolimus. The initial daily tacrolimus dosing formula established can make a good prediction.

CYP3A5 Genotype-Dependent Drug-Drug Interaction Between Tacrolimus and Nifedipine in Chinese Renal Transplant Patients

Purpose: The drug-drug interactions (DDIs) of tacrolimus greatly contributed to pharmacokinetic variability. Nifedipine, frequently prescribed for hypertension, is a competitive CYP3A5 inhibitor which can inhibit tacrolimus metabolism. The objective of this study was to investigate whether CYP3A5 genotype could influence tacrolimus-nifedipine DDI in Chinese renal transplant patients.Method: All renal transplant patients were divided into CYP3A5*3/*3 homozygotes (group I) and CYP3A5*1 allele carriers (CYP3A5*1/*1 + CYP3A5*1/*3) (group II). Each group was subdivided into patients taking tacrolimus co-administered with nifedipine (CONF) and that administrated with tacrolimus alone (Controls). Tacrolimus trough concentrations (C0) were measured using high performance liquid chromatography. A retrospective analysis compared tacrolimus dose (D)-corrected trough concentrations (C0) (C0/D) between CONF and Controls in group I and II, respectively. At the same time, a multivariate line regression analysis was made to evaluate the effect of variates on C0/D.Results: In this study, a significant DDI between tacrolimus and nifedipine with respect to the CYP3A5*3 polymorphism was confirmed. In group I (n = 43), the C0/D of CONF was significantly higher than in Controls [225.2 ± 66.3 vs. 155.1 ± 34.6 ng/ml/(mg/kg); p = 0.002]. However, this difference was not detected in group II (n = 27) (p = 0.216). The co-administrated nifedipine and CYP3A5*3/*3 homozygotes significantly increased tacrolimus concentrations in multivariate line regression analysis.Discussion: A CYP3A5 genotype-dependent DDI was found between tacrolimus and nifedipine. Therefore, personalized therapy accounting for CYP3A5 genotype detection as well as therapeutic drug monitoring are necessary for renal transplant patients when treating with tacrolimus and nifedipine.

POS0868 THE FORMULA TO PREDICT TACROLIMUS CONCENTRATION ACCORDING TO GENOTYPING OF CYP3A5 IS USEFUL FOR EFFECTIVE TREATMENT IN INTERSTITIAL LUNG DISEASE WITH DERMATOMYOSITIS

Background:Tacrolimus (TAC), an immunosuppressant, can be used in second-line maintenance therapy for interstitial lung disease (ILD) in patients with dermatomyositis (DM) [1]. Although some studies reported the clinical efficacy of initial high-trough levels of TAC in combination with GC and IVCY in induction therapy for severe DM-ILD [2], there have been no useful clinical tools for deciding suitable initial dose of TAC. Genotype of polymorphisms in cytochrome P450 (CYP) 3A5 enzyme was reported to play an important role in pharmacokinetics of TAC [3], and we made a formula for deciding initial dose of TAC according to CYP3A5 genotypes in our previous study.Objectives:In our previous study (retrospective study), we set the target trough according to the severity for nine DM-ILD patients, six of whom were CYP3A5 *3/*3 and investigated the dose of TAC that could attain the trough using their CYP3A5 genootyping. Using these results, we developed a formula for deciding initial daily dose of TAC (target trough*weight / [(151.1, if CYP3A5 *3/*3) or (86.5, if CYP3A5 *1 allele)]). In this study, we prospectively examined the usefulness and accuracy of this formula.Methods:We introduced TAC for new six DM-ILD patients who visited our hospital between November 2019 and May 2020 (prospective study). The starting dose of TAC was decided by using the formula. We assessed the association between predicted and observed trough concentration of TAC at first measurement date (from day 2 to day4), using linear regression analysis. We also assessed the days for attaining the target trough concentration between the patients using the formula (prospective group) and six patients with CYP3A5 *3/*3 (retrospective group).Results:CYP3A5 genotype of all six DM-ILD patients were *3/*3 and underwent the TAC treatment by using the formula. The predicted and observed trough concentration of first measurement date were significantly correlated in the patients (r 2= 0.897, p=0.0041) (Fig.1). Compared with our retrospective study, target trough was more quickly attained in patients of the prospective study (Fig.2).Conclusion:The formula which we made for attainment target trough concentration based on CYP3A5 genotype was useful for deciding the starting dose of TAC. We also showed that we could attain the target trough concentration at early stage of initial treatment by using the formula.References:[1]Oddis CV and Aggarwal R. Nat Rev Rheumatol 2018;14(5):279-89.[2]Suzuka T et al. Int J Rheum dis 2019;22: 303-13.[3]Y. Muraki et al. Exp Ther Med 2018;15:532-38.Figure 1.Correlation of predicted and observed tacrolimus trough concentration at first measurement in the prospective studyFigure 2.Days to attain the target trough concentration of tacrolimus in the prospective group and the retrospective groupDisclosure of Interests:None declared

SLCO1B1 Phenotype and CYP3A5 Polymorphism Significantly Affect Atorvastatin Bioavailability

Atorvastatin, prescribed for the treatment of hypercholesterolemia, demonstrated overwhelming benefits in reducing cardiovascular morbidity and mortality. However, many patients discontinue therapy due to adverse reactions, especially myopathy. The Dutch Pharmacogenetics Working Group (DPWG) recommends an alternative agent to atorvastatin and simvastatin or a dose adjustment depending on other risk factors for statin-induced myopathy in SLCO1B1 rs4149056 CC or TC carriers. In contrast, the Clinical Pharmacogenetics Implementation Consortium (CPIC) published their guideline on simvastatin, but not on atorvastatin. In this work, we aimed to demonstrate the effect of SLCO1B1 phenotype and other variants (e.g., in CYP3A4/5, UGT enzymes or SLC transporters) on atorvastatin pharmacokinetics. For this purpose, a candidate-gene pharmacogenetic study was proposed. The study population comprised 156 healthy volunteers enrolled in atorvastatin bioequivalence clinical trials. The genotyping strategy comprised a total of 60 variants in 15 genes. Women showed higher exposure to atorvastatin compared to men (p = 0.001), however this difference disappeared after dose/weight (DW) correction. The most relevant pharmacogenetic differences were the following: AUC/DW and Cmax /DW based on (a) SLCO1B1 phenotype (p < 0.001 for both) and (b) CYP3A5*3 (p = 0.004 and 0.018, respectively). As secondary findings: SLC22A1 *2/*2 genotype was related to higher Cmax/DW (ANOVA p = 0.030) and SLC22A1 *1/*5 genotype was associated with higher Vd/F (ANOVA p = 0.032) compared to SLC22A1 *1/*1, respectively. Finally, UGT2B7 rs7439366 *1/*1 genotype was associated with higher tmax as compared with the *1/*3 genotype (ANOVA p = 0.024). Based on our results, we suggest that SLCO1B1 is the best predictor for atorvastatin pharmacokinetic variability and that prescription should be adjusted based on it. We suggest that the CPIC should include atorvastatin in their statin-SLCO1B1 guidelines. Interesting and novel results were observed based on CYP3A5 genotype, which should be confirmed with further studies.