Variability In Tacrolimus Pharmacokinetics Research Articles

Composite CYP3A phenotypes influence tacrolimus dose-adjusted concentration in lung transplant recipients.

Interpatient variability in tacrolimus pharmacokinetics is attributed to metabolism by cytochrome P-450 3A4/5 isoenzymes (encoded by CYP3A4 and CYP3A5). Guidelines for adjusting tacrolimus based on CYP3A5 test results are published; however, CYP3A4 variants also contribute to the variability in tacrolimus pharmacokinetics. The effects of composite phenotypes incorporating CYP3A5 and CYP3A4 increased (*1G, *1B) and decreased (*22) function variants have not been evaluated. The objective of this study is to investigate the impact of both increased and decreased function CYP3A variants on weight and dose-adjusted tacrolimus concentration (C0/D). We performed a single-center retrospective cohort study of lung transplant recipients to evaluate the median tacrolimus C0/D by composite CYP3A phenotype groups during the index transplant hospitalization. CYP3A4 and CYP3A5 alleles were used to classify patients into four CYP3A groups from least to most CYP3A activity. Exploratory analyses of ABCB1 and additional candidate genes were also assessed. Of the 92 included individuals, most (58) were CYP3A Group 2. The median tacrolimus C0/D differed significantly between CYP3A groups (P = 0.0001). CYP3A Group 2 median tacrolimus C0/D was 190.5 (interquartile range: 147.6-267.5) (ng/ml)/(mg/kg/d) and significantly higher than Group 4 [107.9 (90.4-116.1), P = 0.0001)]. Group 2 median tacrolimus C0/D did not significantly differ from Group 1 and Group 3 [373.5 (149.2-490.3) and 81.4 (62.6-184.1), respectively]. No significant differences in tacrolimus C0/D were found for the ABCB1 diplotypes. These data indicate that a composite CYP3A phenotype incorporating both increase and decrease variant information from CYP3A4 in addition to CYP3A5 may significantly influence tacrolimus C0/D during the early postoperative period.

External Evaluation of a Single Center Precision Tacrolimus Dosing Model for Pediatric Heart Transplant

<h3>Purpose</h3> Extensive variability in tacrolimus pharmacokinetics (PK) influences attainment of therapeutic immunosuppression following pediatric heart transplant. Population PK (popPK) model-based personalized dosing of tacrolimus can reduce the need for tacrolimus titration and improve long-term pediatric heart transplant outcomes. The objective of this study was to externally evaluate a previously described single-center popPK model for personalized tacrolimus therapy. <h3>Methods</h3> A multicenter, retrospective analysis utilized demographics, tacrolimus dosing and concentration data, and laboratory values collected from pediatric inpatients during the first 6 weeks post-transplant, or until discharge, from three sites. PopPK analysis used the modeling software NONMEM v7.2. Observed concentration data were compared to data simulated with our single-center popPK model, using median prediction error (MPE, a measure of bias, <15% acceptable) and median absolute prediction error (MAPE, a measure of accuracy, <30% acceptable). <h3>Results</h3> A total of 285 children: 115 female, 196 white, 32 black, were included. Median age and creatinine clearance were 9.1 years and 101 mL/min/1.73m², respectively. Fluconazole use was rare, occurring in only 6 subjects. When utilizing all data the MPE and MAPE (interquartile range) were acceptable, at -3% (-25%, 10%) and 18% (5%, 49%), respectively, and not different by institution. However, when allowed only 3 concentrations (i.e. the minimum number to adequately predict future concentrations in our prior single-center study) the model poorly predicted future concentrations at all sites (MPE=31%; MAPE=47%). MPE and MAPE varied by site, ranging from 7 to 61% and 30 to 63%, respectively. Including site as a covariate in the popPK model improved predictions (MPE=21%; MAPE=37%) and decreased variability in predictive ability between sites (MPE: 11 to 34%; MAPE: 32 to 45%). <h3>Conclusion</h3> Our single-center popPK model did not adequately predict tacrolimus concentrations from external institutions. Study site appears to drive some of the poor model performance. Future directions include identifying study site differences that influence model performance, as well as identifying additional patient-specific factors affecting tacrolimus dosing requirements.

Population Pharmacokinetic Model Development of Tacrolimus in Pediatric and Young Adult Patients Undergoing Hematopoietic Cell Transplantation.

Background: With a notably narrow therapeutic window and wide intra- and interindividual pharmacokinetic (PK) variability, initial weight-based dosing along with routine therapeutic drug monitoring of tacrolimus are employed to optimize its clinical utilization. Both supratherapeutic and subtherapeutic tacrolimus concentrations can result in poor outcomes, thus tacrolimus PK variability is particularly important to consider in the pediatric population given the differences in absorption, distribution, metabolism, and excretion among children of various sizes and at different stages of development. The primary goals of the current study were to develop a population PK (PopPK) model for tacrolimus IV continuous infusion in the pediatric and young adult hematopoietic cell transplant (HCT) population and implement the PopPK model in a clinically available Bayesian forecasting tool. Methods: A retrospective chart review was conducted of 111 pediatric and young adult patients who received IV tacrolimus by continuous infusion early in the post-transplant period during HCT from February 2016 to July 2020 at our institution. PopPK model building was performed in NONMEM. The PopPK model building process included identifying structural and random effects models that best fit the data and then identifying which patient-specific covariates (if any) further improved model fit. Results: A total of 1,648 tacrolimus plasma steady-state trough concentrations were included in the PopPK modeling process. A 2-compartment structural model best fit the data. Allometrically-scaled weight was a covariate that improved estimation of both clearance and volume of distribution. Overall, model predictions only showed moderate bias, with minor under-prediction at lower concentrations and minor over-prediction at higher predicted concentrations. The model was implemented in a Bayesian dosing tool and made available at the point-of-care. Discussion: Novel therapeutic drug monitoring strategies for tacrolimus within the pediatric and young adult HCT population are necessary to reduce toxicity and improve efficacy in clinical practice. The model developed presents clinical utility in optimizing the use of tacrolimus by enabling model-guided, individualized dosing of IV, continuous tacrolimus via a Bayesian forecasting platform.

Tacrolimus Therapy in Adult Heart Transplant Recipients: Evaluation of a Bayesian Forecasting Software.

Therapeutic drug monitoring is recommended to guide tacrolimus dosing because of its narrow therapeutic window and considerable pharmacokinetic variability. This study assessed tacrolimus dosing and monitoring practices in heart transplant recipients and evaluated the predictive performance of a Bayesian forecasting software using a renal transplant-derived tacrolimus model to predict tacrolimus concentrations. A retrospective audit of heart transplant recipients (n = 87) treated with tacrolimus was performed. Relevant data were collected from the time of transplant to discharge. The concordance of tacrolimus dosing and monitoring according to hospital guidelines was assessed. The observed and software-predicted tacrolimus concentrations (n = 931) were compared for the first 3 weeks of oral immediate-release tacrolimus (Prograf) therapy, and the predictive performance (bias and imprecision) of the software was evaluated. The majority (96%) of initial oral tacrolimus doses were guideline concordant. Most initial intravenous doses (93%) were lower than the guideline recommendations. Overall, 36% of initial tacrolimus doses were administered to transplant recipients with an estimated glomerular filtration rate of <60 mL/min/1.73 m despite recommendations to delay the commencement of therapy. Of the tacrolimus concentrations collected during oral therapy (n = 1498), 25% were trough concentrations obtained at steady-state. The software displayed acceptable predictions of tacrolimus concentration from day 12 (bias: -6%; 95%confidence interval, -11.8 to 2.5; imprecision: 16%; 95% confidence interval, 8.7-24.3) of therapy. Tacrolimus dosing and monitoring were discordant with the guidelines. The Bayesian forecasting software was suitable for guiding tacrolimus dosing after 11 days of therapy in heart transplant recipients. Understanding the factors contributing to the variability in tacrolimus pharmacokinetics immediately after transplant may help improve software predictions.

Unraveling the Genomic Architecture of the CYP3A Locus and ADME Genes for Personalized Tacrolimus Dosing.

Tacrolimus (TAC) is an immunosuppressant widely prescribed following an allogenic organ transplant. Due to wide interindividual pharmacokinetic (PK) variability, optimizing TAC dosing based on genetic factors is required to minimize nephrotoxicity and acute rejections. We enrolled 1133 participants receiving TAC from 4 cohorts, consisting of 3 with kidney transplant recipients and 1 with healthy males from clinical trials. The effects of clinical factors were estimated to appropriately control confounding variables. A genome-wide association study, haplotype analysis, and a gene-based association test were conducted using the Korea Biobank Array or targeted sequencing for 114 pharmacogenes. Genome-wide association study verified that CYP3A5*3 is the only common variant associated with TAC PK variability in Koreans. We detected several CYP3A5 and CYP3A4 rare variants that could potentially affect TAC metabolism. The haplotype structure of CYP3A5 stratified by CYP3A5*3 was a significant factor for CYP3A5 rare variant interpretation. CYP3A4 rare variant carriers among CYP3A5 intermediate metabolizers displayed higher TAC trough levels. Gene-based association tests in the 61 absorption, distribution, metabolism, and excretion genes revealed that CYP1A1 are associated with additional TAC PK variability: CYP1A1 rare variant carriers among CYP3A5 poor metabolizers showed lower TAC trough levels than the noncarrier controls. Our study demonstrates that rare variant profiling of CYP3A5 and CYP3A4, combined with the haplotype structures of CYP3A locus, provide additive value for personalized TAC dosing. We also identified a novel association between CYP1A1 rare variants and TAC PK variability in the CYP3A5 nonexpressers that needs to be further investigated.

Influence of the Circadian Timing System on Tacrolimus Pharmacokinetics and Pharmacodynamics After Kidney Transplantation.

Introduction: Tacrolimus is the backbone immunosuppressant after solid organ transplantation. Tacrolimus has a narrow therapeutic window with large intra- and inter-patient pharmacokinetic variability leading to frequent over- and under-immunosuppression. While routine therapeutic drug monitoring (TDM) remains the standard of care, tacrolimus pharmacokinetic variability may be influenced by circadian rhythms. Our aim was to analyze tacrolimus pharmacokinetic/pharmacodynamic profiles on circadian rhythms comparing morning and night doses of a twice-daily tacrolimus formulation. Methods: This is a post-hoc analysis from a clinical trial to study the area under curve (AUC) and the area under effect (AUE) profiles of calcineurin inhibition after tacrolimus administration in twenty-five renal transplant patients. Over a period of 24 h, an intensive sampling (0, 0.5, 1, 1.5, 2, 3, 4, 6, 8, 12, 12.5, 13, 13.5, 14, 15, 20, and 24 h) was carried out. Whole blood and intracellular tacrolimus concentrations and calcineurin activity were measured by UHPLC-MS/MS. Results: Whole blood and intracellular AUC12–24 h and Cmax achieved after tacrolimus night dose was significantly lower than after morning dose administration (AUC0–12 h) (p < 0.001 for both compartments). AUE0–12 h and AUE12–24 h were not statistically different after morning and night doses. Total tacrolimus daily exposure (AUC0–24 h), in whole blood and intracellular compartments, was over-estimated when assessed by doubling the morning AUC0–12 h data. Conclusion: The lower whole blood and intracellular tacrolimus concentrations after night dose might be influenced by a distinct circadian clock. This significantly lower tacrolimus exposure after night dose was not translated into a significant reduction of the pharmacodynamic effect. Our study may provide conceptual bases for better understanding the TDM of twice-daily tacrolimus formulation.

Multiple microRNAs regulate tacrolimus metabolism through CYP3A5

The CYP3A5 gene polymorphism accounts for the majority of inter-individual variability in tacrolimus pharmacokinetics. We found that the basal expression of CYP3A5 in donor grafts also played a significant role in tacrolimus metabolism under the same genetic conditions after pediatric liver transplantation. Thus, we hypothesized that some potential epigenetic factors could affect CYP3A5 expression and contributed to the variability. We used a high-throughput functional screening for miRNAs to identify miRNAs that had the most abundant expression in normal human liver and could regulate tacrolimus metabolism in HepaRG cells and HepLPCs. Four of these miRNAs (miR-29a-3p, miR-99a-5p, miR-532-5p, and miR-26-5p) were selected for testing. We found that these miRNAs inhibited tacrolimus metabolism that was dependent on CYP3A5. Putative miRNAs targeting key drug-metabolizing enzymes and transporters (DMETs) were selected using an in silico prediction algorithm. Luciferase reporter assays and functional studies showed that miR-26b-5p inhibited tacrolimus metabolism by directly regulating CYP3A5, while miR-29a-5p, miR-99a-5p, and miR-532-5p targeted HNF4α, NR1I3, and NR1I2, respectively, in turn regulating the downstream expression of CYP3A5; the corresponding target gene siRNAs markedly abolished the effects caused by miRNA inhibitors. Also, the expression of miR-29a-3p, miR-99a-5p, miR-532-5p, and miR-26b-5p in donor grafts were negatively correlated with tacrolimus C/D following pediatric liver transplantation. Taken together, our findings identify these miRNAs as novel regulators of tacrolimus metabolism.

Beyond Single Nucleotide Polymorphisms: CYP3A5∗3∗6∗7 Composite and ABCB1 Haplotype Associations to Tacrolimus Pharmacokinetics in Black and White Renal Transplant Recipients.

Interpatient variability in tacrolimus pharmacokinetics is attributed to metabolism by cytochrome P-450 3A5 (CYP3A5) isoenzymes and membrane transport by P-glycoprotein. Interpatient pharmacokinetic variability has been associated with genotypic variants for both CYP3A5 or ABCB1. Tacrolimus pharmacokinetics was investigated in 65 stable Black and Caucasian post-renal transplant patients by assessing the effects of multiple alleles in both CYP3A5 and ABCB1. A metabolic composite based upon the CYP3A5 polymorphisms: ∗3(rs776746), ∗6(10264272), and ∗7(41303343), each independently responsible for loss of protein expression was used to classify patients as extensive, intermediate and poor metabolizers. In addition, the role of ABCB1 on tacrolimus pharmacokinetics was assessed using haplotype analysis encompassing the single nucleotide polymorphisms: 1236C > T (rs1128503), 2677G > T/A(rs2032582), and 3435C > T(rs1045642). Finally, a combined analysis using both CYP3A5 and ABCB1 polymorphisms was developed to assess their inter-related influence on tacrolimus pharmacokinetics. Extensive metabolizers identified as homozygous wild type at all three CYP3A5 loci were found in 7 Blacks and required twice the tacrolimus dose (5.6 ± 1.6 mg) compared to Poor metabolizers [2.5 ± 1.1 mg (P < 0.001)]; who were primarily Whites. These extensive metabolizers had 2-fold faster clearance (P < 0.001) with 50% lower AUC∗ (P < 0.001) than Poor metabolizers. No differences in C12 h were found due to therapeutic drug monitoring. The majority of blacks (81%) were classified as either Extensive or Intermediate Metabolizers requiring higher tacrolimus doses to accommodate the more rapid clearance. Blacks who were homozygous for one or more loss of function SNPS were associated with lower tacrolimus doses and slower clearance. These values are comparable to Whites, 82% of who were in the Poor metabolic composite group. The ABCB1 haplotype analysis detected significant associations of the wildtype 1236T-2677T-3435T haplotype to tacrolimus dose (P = 0.03), CL (P = 0.023), CL/LBW (P = 0.022), and AUC∗ (P = 0.078). Finally, analysis combining CYP3A5 and ABCB1 genotypes indicated that the presence of the ABCB1 3435 T allele significantly reduced tacrolimus clearance for all three CPY3A5 metabolic composite groups. Genotypic associations of tacrolimus pharmacokinetics can be improved by using the novel composite CYP3A5∗3∗4∗5 and ABCB1 haplotypes. Consideration of multiple alleles using CYP3A5 metabolic composites and drug transporter ABCB1 haplotypes provides a more comprehensive appraisal of genetic factors contributing to interpatient variability in tacrolimus pharmacokinetics among Whites and Blacks.

Impacts of High Intra- and Inter-Individual Variability in Tacrolimus Pharmacokinetics and Fast Tacrolimus Metabolism on Outcomes of Solid Organ Transplant Recipients

Tacrolimus is a first-line calcineurin inhibitor (CNI) and an integral part of the immunosuppressive strategy in solid organ transplantation. Being a dose-critical drug, tacrolimus has a narrow therapeutic index that necessitates periodic monitoring to maintain the drug’s efficacy and reduce the consequences of overexposure. Tacrolimus is characterized by substantial intra- and inter-individual pharmacokinetic variability. At steady state, the tacrolimus blood concentration to daily dose ratio (C/D ratio) has been described as a surrogate for the estimation of the individual metabolism rate, where a low C/D ratio reflects a higher rate of metabolism. Fast tacrolimus metabolism (low C/D ratio) is associated with the risk of poor outcomes after transplantation, including reduced allograft function and survival, higher allograft rejection, CNI nephrotoxicity, a faster decline in kidney function, reduced death-censored graft survival (DCGS), post-transplant lymphoproliferative disorders, dyslipidemia, hypertension, and cardiovascular events. In this article, we discuss the potential role of the C/D ratio in a noninvasive monitoring strategy for identifying patients at risk for potential adverse events post-transplant.

SUN-342 UNUSUAL HIGH DOSE OF TACROLIMUS IN RENAL TRANSPLANT PATIENTS: A CASE SERIES

Tacrolimus, is an immunosuppressant, characterized by highly variable pharmacokinetics (PK) and a small therapeutic window, which make therapeutic drug monitoring (TDM) mandatory for maintaining adequate exposure. TDM allows dose adjustment in order to avoid graft rejection and tac-induced adverse effects, which are the most challenging after transplantation. Tacrolimus is metabolized specifically by the CYP3A isoenzyme: CYP3A4 and CYP3A5. Many single nucleotide polymorphisms (SNPs) such as CYP3A4*1B -392A>G, CYP34*22 15389C>T, and CYP3A5*3 6986A>G related to the expression levels of CYP enzymes may explain a part of the variability in tacrolimus PK. It is admitted that patients harboring the predominant CYP3A5*3, associated with enzymatic function loss, require roughly 50% lower tacrolimus doses than those with CYP3A5*1. CYP3A4*1B. Recently, it has been shown that CYP3A4*22 carriers had a lower clearance of tacrolimus (-16%). We describe herein two cases of renal transplant patients who have great difficulty in reaching the desired trough blood levels despite the use of high dose tacrolimus. It is a retrospective study reporting the case of 2 patients with difficulty in reaching the desired trough blood levels of tacrolimus. Our first patient is a 34-year-old man who received a living donor kidney transplant (his mother) on March 15, 2017. He was prescribed Tacrolimus at an initial dose of 14 mg/day divided every 12 hours (0.12-0.15 mg/kg/day) in association with a corticosteroid and mycophenolate mofetil. The trough blood concentration C0 was 5ng/ml. The dose was progressively increased reaching a daily dose of 22 mg divided every 12 hours with the trough blood concentration C0 = 6.4 ng/ml.CYP3A4 and CYP3A5 genotyping were performed using polymerase chain reaction-restriction fragment length polymorphism (PCR–RFLP). The patient was heterozygous for the CYP3A5*3 allele (*1/*3) and homozygous for the CYP3A4*1B (*1B/*1B) and CYP3A4*22 alleles (*1/*1). So the patient was considered a high metabolizer, the reason behind the need for elevated doses of tacrolimus to achieve a therapeutic trough concentration. Our second patient is a 42-year-old man who received a living donor kidney transplant (his sister) on September 28, 2016. He was initially prescribed Tacrolimus at 12mg/day in two divided doses (0.12-0.15 mg/kg/day) in association with a corticosteroid and mycophenolate mofetil. The trough blood concentration (C0) was 3 ng/ml. The dose was then progressively increased reaching a daily dose of 20 mg/day. C0 was 4.1 ng/ml. The patient was homozygous for the three alleles (CYP3A5*1/*3, CYP3A4*1B/*1B, and CYP3A4*1/*1). Our patient is a CYP3A5 expressor and a CYP3A4*1B and CYP3A4*22 carrier, thereby making him a high metabolizer and requiring high doses of tacrolimus in order to achieve a therapeutic trough concentration. The present case series appears to confirm the main responsibility of the CYA3A4 and CYP3A5 genetic polymorphisms in determining the dose requirements of tacrolimus in renal transplant patients. Although pharmacogenetic analysis cannot substitute TDM, the availability of genotyping renders possible to better define the initial tacrolimus dosage.

Reduced variability in tacrolimus pharmacokinetics following intramuscular injection compared to oral administration in cynomolgus monkeys: Investigating optimal dosing regimens

Tacrolimus is one of the most commonly used immunosuppressive agents in animal models of transplantation. However, in these models, oral administration is often problematic due to the lowered compliance associated with highly invasive surgery and due to malabsorption in the intestinal tract. Therefore, we carried out a study to determine the pharmacokinetics of tacrolimus after intramuscular (IM) injection and to determine the optimal IM dosing regimens in primate models. Six male cynomolgus monkeys (Macaca fascicularis) were used in the study. Doses of 0.1 mg/kg and 5 mg were administered via IM injection and oral administration, respectively, once to determine single-dose pharmacokinetics and once daily for 5 days to determine multiple-dose pharmacokinetics. According to pharmacokinetic model estimates, the inter- and intra-individual variabilities in bioavailability following IM injection were remarkably reduced compared with those following oral administration. Monte Carlo simulations revealed that Cpeak, Ctrough and AUC would also have less variability following IM injection compared with oral administration. In this study, we found that the pharmacokinetic characteristics of tacrolimus were more constant following IM injection compared with oral administration. These results suggest that IM injection can be an alternative route of administration fin non-human primate model studies.

Evaluating tacrolimus pharmacokinetic models in adult renal transplant recipients with different CYP3A5 genotypes.

Numerous studies have been conducted on the population pharmacokinetics of tacrolimus in adult renal transplant recipients. It has been reported that the cytochrome P450 (CYP) 3A5 genotype is an important cause of variability in tacrolimus pharmacokinetics. However, the predictive performance of population pharmacokinetic (PK) models of tacrolimus should be evaluated prior to their implementation in clinical practice. The aim of the study reported here was to test the predictive performance of these published PK models of tacrolimus. A literature search of the PubMed and Web of Science databases ultimately led to the inclusion of eight one-compartment models in our analysis. We collected a total of 1715 trough concentrations from 174 patients. Predictive performance was assessed based on visual and numerical comparison bias and imprecision and by the use of simulation-based diagnostics and Bayesian forecasting. Of the eight one-compartment models assessed, seven showed better predictive performance in CYP3A5 extensive metabolizers in terms of bias and imprecision. Results of the simulation-based diagnostics also supported the findings. The model based on a Chinese population in 2013 (model 3) showed the best and most stable predictive performance in all the tests and was more informative in CYP3A5 extensive metabolizers. As expected, Bayesian forecasting improved model predictability. Diversity among models and between different CYP3A5 genotypes of the same model was also narrowed by Bayesian forecasting. Based on our results, we recommend using model 3 in CYP3A5 extensive metabolizers in clinical practice. All models had a poor predictive performance in CYP3A5 poor metabolizers, and they should be used with caution in this patient population. However, Bayesian forecasting improved the predictability and reduced differences, and thus the models could be applied in this latter patient population for the design of maintenance dose.

Population Pharmacokinetic Analysis of Tacrolimus in Adult Mexican Patients with Renal Transplant

The aim of this study was to estimate the population pharmacokinetic parameters of Tacrolimus in Mexican adults undergoing kidney transplantation and to identify the clinical factors affecting Tacrolimus pharmacokinetics. Using Non-linear mixed effects modeling (NONMEM) with First-order absorption and elimination, a total of 592 retrospective-prospective drug monitoring data points were collected from 36 patients with renal transplant receiving Tacrolimus (Prograf® twice daily during the first 6 post-transplantation months and a generic product thereafter. The absorption rate constant was fixed at 4.5 h –1 , and the following population pharmacokinetic estimates were obtained: Tacrolimus clearance (CL/F), 22.5 L/h, and apparent volume of distribution (V/F), 812 L. Interindividual variability was 52.9 and 82.1% for CL/F and V/F, respectively. The covariates that significantly affect Tacrolimus pharmacokinetics parameters were concomitantly administered calcium channel blocker drug and hematocrit level. The population pharmacokinetic analysis identified important sources of variability in Tacrolimus pharmacokinetics. The model will help to calculate Tacrolimus dose requirements in Mexican renal transplant recipients according to specific clinical factors affecting Tacrolimus clearance and volume of distribution and it will also be useful for therapeutic drug monitoring.

Donor ABCB1 genetic polymorphisms influence epithelial-to-mesenchyme transition in tacrolimus-treated kidney recipients.

The contribution of epithelial-mesenchymal transition (EMT) has been suggested in renal transplant recipients receiving calcineurin inhibitors and developing nephrotoxicity. We assessed whether interindividual variability in tacrolimus pharmacokinetics is associated with the occurrence in tubular cells of two EMT markers (vimentin, β-catenin) detected at 3-month in 140 allograft biopsies. We investigated whether genetic polymorphisms affecting CYP3A5 and ABCB1 influence EMT and kidney fibrosis. In univariate analysis, the donor CYP3A5*1 allele was significantly associated with a lower vimentin expression. In multivariate analysis, grafts carrying ABCB1 3435T allele(s) developed significantly less EMT and less interstitial fibrosis. Donor SNPs significantly influence the epithelial program in the context of kidney transplantation, and the epithelial metabolism of tacrolimus is one key to understand graft fibrogenesis.

Relationship of CYP3A5 genotype and ABCB1 diplotype to tacrolimus disposition in Brazilian kidney transplant patients

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. 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). 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. 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.

Association of Hemoglobin Levels, CYP3A5, and NR1I3 Gene Polymorphisms with Tacrolimus Pharmacokinetics in Liver Transplant Patients

Tacrolimus is a widely used immunosuppressant after organ transplantation. The narrow therapeutic window and individual variability in tacrolimus pharmacokinetics make management of this agent a great challenge. This study was undertaken to determine the association of clinical markers, cytochrome P450, family 3, subfamily A, polypeptide 5 (CYP3A5) and nuclear receptor subfamily 1, group I, member 3 (NR1I3) gene polymorphisms with tacrolimus pharmacokinetics. A total of 96 liver transplant patients were enrolled in the study. Tacrolimus dose-adjusted trough concentration (C/D ratio) and clinical markers were recorded for one month after transplantation. CYP3A5 and NR1I3 gene polymorphisms for both donor and recipient were genotyped. In single variable analysis, hemoglobin (Hb), hematocrit (Hct), donor CYP3A5, NR1I3 gene polymorphisms and recipient CYP3A5 gene polymorphisms were associated with log-transformed tacrolimus C/D ratios. Hb, donor CYP3A5, NR1I3 gene polymorphisms and recipient CYP3A5 gene polymorphisms showed association with log-transformed tacrolimus C/D ratios in the final multiple linear regression model. Donor CYP3A5 polymorphisms were the most important variant, accounting for 14.3% of total variation involved in tacrolimus pharmacokinetics. This information could be useful in developing individualized tacrolimus treatment after liver transplantation.

The Role of Pharmacogenetics in the Disposition of and Response to Tacrolimus in Solid Organ Transplantation

The calcineurin inhibitor tacrolimus is the backbone of immunosuppressive drug therapy after solid organ transplantation. Tacrolimus is effective in preventing acute rejection but has considerable toxicity and displays marked inter-individual variability in its pharmacokinetics and pharmacodynamics. The genetic basis of these phenomena is reviewed here. With regard to its pharmacokinetic variability, a single nucleotide polymorphism (SNP) in cytochrome P450 (CYP) 3A5 (6986A>G) has been consistently associated with tacrolimus dose requirement. Patients expressing CYP3A5 (those carrying the Anucleotide, defined as the *1 allele) have a dose requirement that is around 50% higher than non-expressers (those homozygous for the Gnucleotide, defined as the *3 allele). A randomised controlled study in kidney transplant recipients has demonstrated that a CYP3A5 genotype-based approach to tacrolimus dosing leads to more patients reaching the target concentration early after transplantation. However, no improvement of clinical outcomes (rejection incidence, toxicity) was observed, which may have been the result of the design of this particular study. In addition to CYP3A5 genotype, other genetic variants may also contribute to the variability in tacrolimus pharmacokinetics. Among these, the CYP3A4*22 and POR*28 SNPs are the most promising. Individuals carrying the CYP3A4*22 T-variant allele have a lower tacrolimus dose requirement than individuals with the CYP3A4*22 CC genotype and this effect appears to be independent of CYP3A5 genotype status. Individuals carrying the POR*28 T-variant allele have a higher tacrolimus dose requirement than POR*28 CC homozygotes but this association was only found in CYP3A5-expressing individuals. Other, less well-defined SNPs have been inconsistently associated with tacrolimus dose requirement. It is envisaged that in the future, algorithms incorporating clinical, demographic and genetic variables will be developed that will aid clinicians with the determination of the tacrolimus starting dose for an individual transplant recipient. Such an approach may limit early tacrolimus under-exposure and toxicity. With regard to tacrolimus pharmacodynamics, no strong genotype-phenotype relationships have been identified. Certain SNPs associate with rejection risk but these observations await replication. Likewise, the genetic basis of tacrolimus-induced toxicity remains unclarified. SNPs in the genes encoding for the drug transporter ABCB1 and the CYP3A enzymes may relate to chronic nephrotoxicity but findings have been inconsistent. No genetic markers reliably predict new-onset diabetes mellitus after transplantation, hypertension or neurotoxicity. The CYP3A5*1 SNP is currently the most promising biomarker for tailoring tacrolimus treatment. However, before CYP3A5 genotyping is incorporated into the routine clinical care of transplant recipients, prospective clinical trials are needed to determine whether such a strategy improves patient outcomes. The role of pharmacogenetics in tacrolimus pharmacodynamics should be explored further by the study of intra-lymphocyte and tissue tacrolimus concentrations.

PP132—Contribution of genetic (CYP3A5, ABCB1 and POR) and non-genetic variables to the oral tacrolimus clearance in children’s with stable kidney transplant, during advagraf® treatment

There is a large interindividual variation in tacrolimus (TAC) disposition. Genetic information (mainly CYP3A5) has been shown to influence TAC pharmacokinetics and potentially contribute to the optimization of its dosing. The aim of this study was to evaluate the influence of genetic and clinical factors on TAC pharmacokinetic variability in stable pediatric renal transplant patients.

Effects of CYP3A4 and CYP3A5 polymorphisms on tacrolimus pharmacokinetics in Chinese adult renal transplant recipients

Tacrolimus is used clinically for the long-term treatment of antirejection of transplanted organs in liver and kidney transplant recipients, although dose optimization is poorly managed. The aim of this study was to examine the association between tacrolimus pharmacokinetic variability and CYP3A4 and CYP3A5 genotypes by a population pharmacokinetic analysis based on routine drug monitoring data in adult renal transplant recipients. Trough tacrolimus concentrations were obtained from 161 adult kidney transplant recipients after transplantation. The population pharmacokinetic analysis was carried out using the nonlinear mixed-effect modeling software NONMEM version 7.2. The CYP3A4*1G and CYP3A5*3 genetic polymorphisms from the patients studied were determined by direct sequencing using a validated automated genetic analyzer. A one-compartment model with first-order absorption and elimination adequately described the pharmacokinetics of tacrolimus. Covariates including CYP3A5*3 and CYP3A4*1G alleles and hematocrit were retained in the final model. The apparent clearance of tacrolimus was about two-fold higher in kidney transplant patients with higher enzymatic activity of CYP3A5*1 and CYP3A4*1G (with the CYP3A5*1/*1 or *1/*3 and CYP3A4*1/*1G or CYP3A4*1G/*1G) compared with those with lower enzymatic activity (CYP3A5*3/*3 and CYP3A4*1/*1). This is the first study to extensively determine the effect of CYP3A4*1G and CYP3A5*3 genetic polymorphisms and hematocrit value on tacrolimus pharmacokinetics in Chinese renal transplant recipients. The findings suggest that CYP3A5*3 and CYP3A4*1G polymorphisms and hematocrit are determinant factors in the apparent clearance of tacrolimus. The initial dose design is mainly based on CYP3A5 and CYP3A4 genotypes as well as hematocrit. This result may also be useful for maintenance tacrolimus dose optimization and may help to avoid fluctuating tacrolimus levels and improve the efficacy and tolerability of tacrolimus in kidney transplant recipients.

In Vivo CYP3A4-Activity, CYP3A5-Genotype and Hematocrit Predict Tacrolimus Dose-Requirements and Clearance in Renal Transplant Recipients

Introduction: Tacrolimus (Tac) is metabolized by CYP3A4 and CYP3A5 and is characterized by a narrow therapeutic index and a high interindividual variability in pharmacokinetics. It has been hypothesized that the latter is due to interindividual differences in in vivo CYP3A4-activity and genetically determined CYP3A5 expression (CYP3A5*1 SNP). Methods: Cross-sectional study in 59 renal transplant recipients tested 3 months after transplantation investigating the relationship between in vivo CYP3A4-activity (assessed using midazolam (MDZ) as a drug probe) and CYP3A5 genotype (CYP3A5*1-allele carriers vs. CYP3A5*3/*3 homozygous patients), and Tac pharmacokinetics (assessed using dose interval concentration time profiles), taking into account other possible determinants of Tac disposition. Of note, systemic MDZ clearance (MDZ Cl) reflects hepatic CYP3A4-activity, whereas apparent oral MDZ clearance (MDZ Cl/F) reflects in vivo CYP3A4 mediated first pass metabolism and thus combined intestinal and hepatic CYP3A4-activity. Results: Baseline characteristics did not differ between CYP3A5 expressers (CYP3A5*1-allele carriers, n=10) and non-expresser (CYP3A5*3/*3 homozygous patients, n=49). Tac dose requirements (D), dose corrected AUC (AUC0-12/D) and clearance (Clss) were respectively 1.8-fold higher, 2-fold lower and 1.8-fold higher in CYP3A5 expressers. MDZ Cl and MDZ Cl/F did not differ between genotype groups. Figures 1 and 2 depict the relationship between MDZ Cl/F and Tac D (Fig 1) and Tac Clss (Fig 2) in CYP3A5 expressers (red dots) and non-expressers (blue dots), as well as the bivariate (MDZ Cl/F and CYP3A5 genotype) models predicting Tac D and Tac Clss respectively. In multivariate regression analysis MDZ Cl/F, CYP3A5 genotype and hematocrit independently predicted Tac D, Tac AUC0-12/D and Tac Clss: model R2 0.60-0.70, partial R2CYP3A5 genotype 0.31-0.33, partial R2 MDZ Cl/F 0.25-0.26 and partial R2 hematocrit 0.04-0.11 (p< 0.0001 for all).[Fig 1][Fig 2]Conclusion: In renal transplant recipients in vivo CYP3A4-activity (reflected by apparent oral midazolam clearance) and CYP3A5 genotype explain 55-60 % of interindividual variability in tacrolimus dose-requirements and clearance, while hematocrit accounts for an additional 10 %. These results demonstrate the importance of CYP3A mediated tacrolimus metabolism for explaining the clinically observed high interindividual variability in tacrolimus pharmacokinetics and provide a potential basis for a comprehensive approach in predicting tacrolimus dose requirements in individual patients.