Concentration of tacrolimus and major metabolites in kidney transplant recipients as a function of diabetes mellitus and cytochrome P450 3A gene polymorphism

Tacrolimus Monitoring in Liver Transplant Recipients, Posttransplant Cholestasis: A Comparative Between 2 Commercial Immunoassays and a Liquid Chromatography-Tandem Mass Spectrometry Method

BACKGROUND

Cholestasis commonly occurs after orthotopic liver transplantation. It can be extrahepatic because of mechanical obstruction or intrahepatic because of various causes. During cholestasis episodes, blood concentrations of tacrolimus (TAC) metabolites may increase, potentially affecting TAC concentrations measured by immunoassays. This study aimed to simultaneously evaluate the analytical performance of 2 TAC immunoassays, a quantitative microsphere system (QMS) immunoassay, and chemiluminescence microparticle immunoassay, using liquid chromatography-tandem mass spectrometry (LC-MS/MS) as a reference method in liver transplant recipients.

METHODS

This single-center study included 265 patients who underwent orthotopic liver transplantation. In total, 942 blood samples were collected. TAC trough concentrations were measured using LC-MS/MS and 2 immunoassays in parallel. The plasma concentrations of conjugated bilirubin were measured in all samples. The results were analyzed using Bland-Altman plots and Passing-Bablok regressions.

RESULTS

The Bland-Altman plot analysis showed that the TAC QMS immunoassay has a significant bias (+37%) compared with LC-MS/MS, and this bias was higher in patients with cholestasis with hyperbilirubinemia (≤+70% in patients with conjugated bilirubin >150 µmol/L). In comparison, the chemiluminescence microparticle immunoassay showed acceptable analytical performance in patients with hyperbilirubinemia (bias <10%).

CONCLUSIONS

In agreement with previous findings, the TAC QMS immunoassay showed a positive bias compared with LC-MS/MS. This bias is remarkably high in patients with cholestasis and hyperbilirubinemia, suggesting the cross-reactivity of TAC metabolites with the monoclonal antibody used in the QMS immunoassay.

Improving prediction of tacrolimus concentration using a combination of population pharmacokinetic modeling and machine learning in chinese renal transplant recipients

Aims

The population pharmacokinetic (PPK) model-based machine learning (ML) approach offers a novel perspective on individual concentration prediction. This study aimed to establish a PPK-based ML model for predicting tacrolimus (TAC) concentrations in Chinese renal transplant recipients.

Methods

Conventional TAC monitoring data from 127 Chinese renal transplant patients were divided into training (80%) and testing (20%) datasets. A PPK model was developed using the training group data. ML models were then established based on individual pharmacokinetic data derived from the PPK basic model. The prediction performances of the PPK-based ML model and Bayesian forecasting approach were compared using data from the test group.

Results

The final PPK model, incorporating hematocrit and CYP3A5 genotypes as covariates, was successfully established. Individual predictions of TAC using the PPK basic model, postoperative date, CYP3A5 genotype, and hematocrit showed improved rankings in ML model construction. XGBoost, based on the TAC PPK, exhibited the best prediction performance.

Conclusion

The PPK-based machine learning approach emerges as a superior option for predicting TAC concentrations in Chinese renal transplant recipients.

Leptin receptor gene polymorphisms in kidney transplant patients with post-transplant diabetes mellitus treated with tacrolimus

Post-transplant diabetes mellitus (PTDM) is a metabolic complication that often occurs after kidney transplantation. Factors that increase the risk of this complication are currently being researched, including polymorphisms in genes affecting carbohydrate-lipid metabolism. Leptin is a hormone that affects appetite and adipose tissue and plays an important role in regulating insulin secretion as well as glucose and lipid metabolism. The aim of this study was to examine the association between leptin receptor gene polymorphisms and the development of post-transplant diabetes mellitus in patients treated with tacrolimus. The study was carried out in a group of 201 patients who underwent kidney transplantation. The follow-up period was 12 months. PTDM was diagnosed in 35 patients. Analysing the LEPR gene rs1137101 polymorphism, we observed in patients with PTDM an increased frequency of GG genotype carriers (GG vs AA, OR 3.36; 95 % CI 0.99-11.46; p = 0.04). There were no statistically significant differences in the distribution of the LEPR rs1137100 and LEPR rs1805094 polymorphisms between patients with and without PTDM. Multivariate regression analysis confirmed that female sex, advanced age, increased BMI and a higher number of LEPR rs1137101 G alleles were independent risk factors for PTDM development. The risk of PTDM development was almost 3.5 times greater in LEPR rs1137101 G allele carriers than in AA homozygotes (GG + AG vs AA; OR 3.48; 95 %CI (1.09-11.18), p = 0.035). The results suggest that patients after kidney transplantation with the LEPR gene rs1137101 G allele may have an increased risk of post-transplant diabetes development.

The Association between CDKAL1 Gene rs10946398 Polymorphism and Post-Transplant Diabetes in Kidney Allograft Recipients Treated with Tacrolimus

Post-transplant diabetes mellitus (PTDM) is a common complication that occurs in kidney transplant patients, increasing the risk of infection, cardiovascular disease and loss of graft function. Currently, factors that increase the risk of this complication are being sought, among them polymorphisms in genes that regulate carbohydrate metabolism and influence pancreatic β-cell function. The aim of this study was to evaluate the association of selected polymorphisms of genes affecting carbohydrate metabolism, such as CDKAL1 rs10946398, GCK rs1799884, GCKR rs780094 and DGKB/TMEM195 rs2191349, with the development of post-transplant diabetes in kidney transplant patients. This study included 201 Caucasian patients after kidney transplantation treated with tacrolimus. An association was observed between the CDKAL1 rs10946398 gene polymorphism and PTDM. Among patients with PTDM, there was an increased prevalence of the CC genotype in the PTDM group compared to the group without PTDM. The chance of PTDM in those with the CC genotype was 2.60 times higher compared to those with the AC + AA genotypes (CC vs. AC + AA OR (95% CI): 2.60 (1.02-6.61), p = 0.040). Multivariate logistic regression analysis showed that advanced age and the CC genotype (rare homozygote) of CDKAL1 rs10946398 were risk factors for the development of PTDM at 1 year after transplantation. There was no statistically significant association between GCK rs1799884, GCKR rs780094 or DGKB/TMEM195 rs2191349 polymorphisms and the development of post-transplant diabetes mellitus in kidney transplant patients. The results of this study suggest that the CDKAL1 rs10946398 CC genotype is associated with the increased risk of PTDM development in patients after kidney graft transplantation treated with tacrolimus.

Developing supervised machine learning algorithms to evaluate the therapeutic effect and laboratory-related adverse events of cyclosporine and tacrolimus in renal transplants

BACKGROUND

Single nucleotide polymorphisms influence the effects of tacrolimus and cyclosporine in renal transplants.

AIM

We set out to use machine learning algorithms (MLAs) to identify variables that predict the therapeutic effects and adverse events following tacrolimus and cyclosporine administration in renal transplant patients.

METHOD

We sampled 120 adult renal transplant patients (on cyclosporine or tacrolimus). Generalized linear model (GLM), support vector machine (SVM), artificial neural network (ANN), Chi-square automatic interaction detection, classification and regression tree, and K-nearest neighbors were the chosen MLAs. The mean absolute error (MAE), relative mean square error (RMSE), and regression coefficient (β) with a 95% confidence interval (CI) were used as the model parameters.

RESULTS

For a stable dose of tacrolimus, the MAEs (RMSEs) of GLM, SVM, and ANN were 1.3 (1.5), 1.3 (1.8), and 1.7 (2.3) mg/day, respectively. GLM revealed that the POR*28 genotype and age significantly predicted the stable dose of tacrolimus as follows: POR*28 (β -1.8; 95% CI -3, -0.5; p = 0.006), and age (β -0.04; 95% CI -0.1, -0.006; p = 0.02). For a stable dose of cyclosporine, MAEs (RMSEs) of 93.2 (103.4), 79.1 (115.2), and 73.7 (91.7) mg/day were observed with GLM, SVM, and ANN, respectively. GLM revealed the following predictors of a stable dose of cyclosporine: CYP3A5*3 (β -80.8; 95% CI -130.3, -31.2; p = 0.001), and age (β -3.4; 95% CI -5.9, -0.9; p = 0.007).

CONCLUSION

We observed that various MLAs could identify significant predictors that were useful to optimize tacrolimus and cyclosporine dosing regimens; yet, the findings must be externally validated.

Diabetes is a significant and independent predictor for tacrolimus immediate release and LCP-tacrolimus conversion ratios

Diabetes (DM) is a common comorbidity in transplant patients with known effects on gastrointestinal (GI) motility and absorption; however, DM's impact on immediate release (IR) tacrolimus to LCP-tacrolimus (LCP) conversion ratios has not been studied. This multivariable analysis of a retrospective longitudinal cohort study included kidney transplant recipients converted from IR to LCP between 2019 and 2020. The primary outcome was IR to LCP conversion ratio based on DM status. Other outcomes included tacrolimus variability, rejection, graft loss, and death. Of the 292 patients included, 172 patients had DM and 120 did not. The IR:LCP conversion ratio was significantly higher with DM (67.5% ± 21.1% no DM vs. 79.8% ± 28.7% in DM; P < .001). In multivariable modeling, DM was the only variable significantly and independently associated with IR:LCP conversion ratios. No difference was observed in rejection rates. Graft (97.5% no DM vs. 92.4% in DM; P = .062) and patient survival (100% no DM vs. 94.8% in DM; P = .011) were lower with DM. The presence of DM significantly increased the IR:LCP conversion ratio by 13%-14%, compared to patients without DM. On multivariable analysis, DM was the only significant predictor of conversion ratios, potentially related to GI motility or absorption differences.

Expression of ATP-binding cassette subfamily B member 1 gene in peripheral blood of patients with acute myocardial infarction

This study aimed to determine the amount of expression of the ATP-binding cassette subfamily B member 1 (ABCB1) gene chip as a prospective diagnostic marker for acute myocardial infarction (AMI) in a wide population . In the AMI and control groups, 113 patients with AMI and 83 persons with non-coronary artery disease were selected for peripheral venous leukocyte collection. Western blot and real-time polymerase chain reaction (RT-PCR) were employed to detect relative ABCB1 expression in both groups. The results showed that the ABCB1 transcription and protein levels in the AMI group were higher than in the control. The relative mRNA expression of ABCB1 was 0.26 (0.03-0.79) in the AMI group and 0.13 (0.01-0.52) in the control group (P < 0.05). The expression of the ABCB1 gene at the protein level in the AMI group was 1.65 times that in the control (P < 0.05). Further, the subjects in the AMI group were older (P < 0.001), had lower levels of high-density lipoprotein cholesterol (P = 0.038), and had higher incidence of type II diabetes mellitus (P = 0.003) compared with the control. Logistic regression analysis showed that the expression of ABCB1 in peripheral blood was correlated with the occurrence of AMI (P = 0.003). High ABCB1 expression, type II diabetes, and advanced age were found to serve as potential independent risk factors for AMI, with a 4.88-fold, 2.99-fold, and 2.63-fold increased risk of AMI. Overall, the high expression of ABCB1 in peripheral blood might be related to the occurrence of AMI.

Effects of MAO-A and CYP450 on primaquine metabolism in healthy volunteers

Eliminating the Plasmodium vivax malaria parasite infection remains challenging. One of the main problems is its capacity to form hypnozoites that potentially lead to recurrent infections. At present, primaquine is the only drug used for the management of hypnozoites. However, the effects of primaquine may differ from one individual to another. The aim of this work is to determine new measures to reduce P. vivax recurrence, through primaquine metabolism and host genetics. A genetic study of MAO-A, CYP2D6, CYP1A2 and CYP2C19 and their roles in primaquine metabolism was undertaken of healthy volunteers (n = 53). The elimination rate constant (K_e) and the metabolite-to-parent drug concentration ratio (Cm/Cp) were obtained to assess primaquine metabolism. Allelic and genotypic analysis showed that polymorphisms MAO-A (rs6323, 891G>T), CYP2D6 (rs1065852, 100C>T) and CYP2C19 (rs4244285, 19154G>A) significantly influenced primaquine metabolism. CYP1A2 (rs762551, -163C>A) did not influence primaquine metabolism. In haplotypic analysis, significant differences in K_e (p = 0.00) and Cm/Cp (p = 0.05) were observed between individuals with polymorphisms, GG-MAO-A (891G>T), CT-CYP2D6 (100C>T) and GG-CYP2C19 (19154G>A), and individuals with polymorphisms, TT-MAO-A (891G>T), TT-CYP2D6 (100C>T) and AA-CYP2C19 (19154G>A), as well as polymorphisms, GG-MAO-A (891G>T), TT-CYP2D6 (100C>T) and GA-CYP2C19 (19154G>A). Thus, individuals with CYP2D6 polymorphisms had slower primaquine metabolism activity. The potential significance of genetic roles in primaquine metabolism and exploration of these might help to further optimise the management of P. vivax infection.

Artificial neural network model for predicting the bioavailability of tacrolimus in patients with renal transplantation

The objective of the current study was to explore the role of ABCB1 and CYP3A5 genetic polymorphisms in predicting the bioavailability of tacrolimus and the risk for post-transplant diabetes. Artificial neural network (ANN) and logistic regression (LR) models were used to predict the bioavailability of tacrolimus and risk for post-transplant diabetes, respectively. The five-fold cross-validation of ANN model showed good correlation with the experimental data of bioavailability (r2 = 0.93-0.96). Younger age, male gender, optimal body mass index were shown to exhibit lower bioavailability of tacrolimus. ABCB1 1236 C>T and 2677G>T/A showed inverse association while CYP3A5*3 showed a positive association with the bioavailability of tacrolimus. Gender bias was observed in the association with ABCB1 3435 C>T polymorphism. CYP3A5*3 was shown to interact synergistically in increasing the bioavailability in combination with ABCB1 1236 TT or 2677GG genotypes. LR model showed an independent association of ABCB1 2677 G>T/A with post transplant diabetes (OR: 4.83, 95% CI: 1.22-19.03). Multifactor dimensionality reduction analysis (MDR) revealed that synergistic interactions between CYP3A5*3 and ABCB1 2677 G>T/A as the determinants of risk for post-transplant diabetes. To conclude, the ANN and MDR models explore both individual and synergistic effects of variables in modulating the bioavailability of tacrolimus and risk for post-transplant diabetes.

Pharmacokinetics, Pharmacodynamics and Pharmacogenomics of Immunosuppressants in Allogeneic Haematopoietic Cell Transplantation: Part I

Although immunosuppressive treatments and target concentration intervention (TCI) have significantly contributed to the success of allogeneic haematopoietic cell transplantation (alloHCT), there is currently no consensus on the best immunosuppressive strategies. Compared with solid organ transplantation, alloHCT is unique because of the potential for bidirectional reactions (i.e. host-versus-graft and graft-versus-host). Postgraft immunosuppression typically includes a calcineurin inhibitor (cyclosporine or tacrolimus) and a short course of methotrexate after high-dose myeloablative conditioning, or a calcineurin inhibitor and mycophenolate mofetil after reduced-intensity conditioning. There are evolving roles for the antithymyocyte globulins (ATGs) and sirolimus as postgraft immunosuppression. A review of the pharmacokinetics and TCI of the main postgraft immunosuppressants is presented in this two-part review. All immunosuppressants are characterized by large intra- and interindividual pharmacokinetic variability and by narrow therapeutic indices. It is essential to understand immunosuppressants' pharmacokinetic properties and how to use them for individualized treatment incorporating TCI to improve outcomes. TCI, which is mandatory for the calcineurin inhibitors and sirolimus, has become an integral part of postgraft immunosuppression. TCI is usually based on trough concentration monitoring, but other approaches include measurement of the area under the concentration-time curve (AUC) over the dosing interval or limited sampling schedules with maximum a posteriori Bayesian personalization approaches. Interpretation of pharmacodynamic results is hindered by the prevalence of studies enrolling only a small number of patients, variability in the allogeneic graft source and variability in postgraft immunosuppression. Given the curative potential of alloHCT, the pharmacodynamics of these immunosuppressants deserves to be explored in depth. Development of sophisticated systems pharmacology models and improved TCI tools are needed to accurately evaluate patients' exposure to drugs in general and to immunosuppressants in particular. Sequential studies, first without and then with TCI, should be conducted to validate the clinical benefit of TCI in homogenous populations; randomized trials are not feasible, because there are higher-priority research questions in alloHCT. In Part I of this article, we review the alloHCT process to facilitate optimal design of pharmacokinetic and pharmacodynamics studies. We also review the pharmacokinetics and TCI of calcineurin inhibitors and methotrexate.

Occurrence of immunosuppressive drugs and their metabolites in the sewage-impacted Vistula and Utrata Rivers and in tap water from the Warsaw region (Poland)

Immunosuppresive therapy following organ transplant frequently includes treatment with tacrolimus and mycophenolic acid derivatives. These pharmaceuticals may enter the environment through wastewater treatment plant (WWTP) effluents and may have a potentially harmful effect on aquatic biota. Tacrolimus, mycophenolic acid and their metabolites were measured at specific points of a large Polish river (Vistula), a smaller river (Utrata) and in tap water samples from the Warsaw region. Analysis was performed using liquid chromatography tandem mass spectrometry, after solid phase extraction for water samples, or QuEChERS extraction for sediments. Residues of tacrolimus were below quantitation limits in both water and sediment samples. However, in water samples mycophenolic acid concentrations were measured at up to 180 ng L(-1) downstream of WWTP outfalls. No immunosuppressive drugs were detected in tap water. Concentrations of mycophenolic acid exceeded the predicted no effect concentration (PNEC) value in some Polish surface water, and risk calculations predicted at least twice higher concentrations in some other countries of the European Union. To the best of the authors' knowledge, this is the first report of these immunosuppressive drug concentrations in the environment.

Adiponectin and leptin gene polymorphisms in patients with post-transplant diabetes mellitus

Background: Post-transplant diabetes mellitus (PTDM) is a common metabolic complication after organ transplantation and may be associated with the use of calcineurin inhibitors (tacrolimus and cyclosporine). Leptin and adiponectin are adipokines and play an important role in the regulation of insulin secretion as well as glucose and lipid metabolism. Aim: The aim of this study was to examine the association between adiponectin and leptin gene polymorphisms and development of PTDM. Materials & methods: The study included 323 patients who received kidney transplants and were treated with calcineurin inhibitors (tacrolimus or cyclosporine). Results: The association between adiponectin and leptin gene polymorphisms and PTDM was studied in three models of Cox regression analysis – additive, dominant and recessive. In these three models, the LEP rs2167270 gene polymorphism was statistically significantly associated with increased risk of PTDM. The association between the LEP rs2167270 polymorphism and PTDM was confirmed by multivariate regression analysis. Conclusion: The results of our study suggest an association between the leptin rs2167270 gene A allele and PTDM.

Original submitted 27 February 2015; Revision submitted 22 May 2015

Effects of the CYP3A4*1B Genetic Polymorphism on the Pharmacokinetics of Tacrolimus in Adult Renal Transplant Recipients: A Meta-Analysis

BACKGROUND AND OBJECTIVE

The association between the CYP3A4*1B single nucleotide polymorphism (SNP) and tacrolimus pharmacokinetics in different studies is controversial. Therefore, a meta-analysis was employed to evaluate the correlation between the CYP3A4*1B genetic polymorphism and tacrolimus pharmacokinetics at different post-transplantation times in adult renal transplant recipients.

METHODS

Studies evaluating the CYP3A4*1B genetic polymorphism and tacrolimus pharmacokinetics were retrieved through a systematical search of Embase, PubMed, the Cochrane Library, ClinicalTrials.gov and three Chinese literature databases (up to Sept. 2014). The pharmacokinetic parameters (weight-adjusted tacrolimus daily dose and tacrolimus trough concentration/weight-adjusted tacrolimus daily dose ratio) were extracted, and the meta-analysis was performed using Stata 12.1.

RESULTS

Seven studies (involving 1182 adult renal transplant recipients) were included in this meta-analysis. For the weight-adjusted tacrolimus daily dose, in all included renal transplant recipients (European & Indian populations), CYP3A4*1/*1 recipients required a significantly lower weight-adjusted tacrolimus daily dose than did CYP3A4*1B carriers at 7 days (WMD -0.048; 95% CI -0.083 ~ -0.014), 6 months (WMD -0.058; 95% CI -0.081 ~ -0.036) and 12 months (WMD - 0.061; 95% CI -0.096 ~ -0.027) post-transplantation. In light of the heterogeneity, the analysis was repeated after removing the only study in an Indian population, and CYP3A4*1/*1 European recipients (mostly Caucasian) required a lower weight-adjusted tacrolimus daily dose within the first year post-transplantation. The tacrolimus trough concentration/weight-adjusted tacrolimus daily dose ratio (C0/Dose ratio) was significantly higher in CYP3A4*1/*1 recipients than in CYP3A4*1B carriers at 6 months (WMD 52.588; 95% CI 22.387 ~ 82.789) and 12 months (WMD 62.219; 95% CI 14.218 ~ 110.221) post-transplantation. When the only study in an Indian population was removed to examine European recipients (mostly Caucasian), the significant difference persisted at 1 month, 6 months and 12 months post-transplantation.

CONCLUSION

Based on our meta-analysis, the CYP3A4*1B genetic polymorphism affects tacrolimus dose requirements and tacrolimus trough concentration/weight-adjusted tacrolimus daily dose ratio within the first year post-transplantation in adult renal transplant recipients, especially in European recipients (mostly Caucasian).

Pharmacokinetics of total and unbound prednisone and prednisolone in stable kidney transplant recipients with diabetes mellitus

BACKGROUND

The corticosteroid prednisone is an important component of posttransplantation immunosuppressive therapy. Pharmacokinetic parameters of prednisone or its pharmacologically active metabolite, prednisolone, are not well characterized in transplant recipients. The objective of this study was to compare the pharmacokinetics of total and unbound prednisone and prednisolone in diabetic and nondiabetic stable kidney transplant recipients and to evaluate the factors influencing plasma protein binding of prednisolone.

METHODS

Prednisone and prednisolone concentration-time profiles were obtained in 20 diabetic and 18 nondiabetic stable kidney transplant recipients receiving an oral dose of 5-10 mg prednisone per day. In addition to drug and metabolite exposures, factors influencing prednisolone protein binding were evaluated using a nonlinear mixed-effects modeling approach. This model takes into account the binding of prednisolone and cortisol to corticosteroid-binding globulin (CBG) in a saturable fashion and binding of prednisolone to albumin in a nonsaturable fashion. Finally, we have investigated the influence of several covariates including diabetes, glucose concentration, hemoglobin A1c, creatinine clearance, body mass index, gender, age, and time after transplantation on the affinity constant (K) between corticosteroids and their binding proteins.

RESULTS

In patients with diabetes, the values of dose-normalized area under the concentration-time curves were 27% and 23% higher for total and unbound prednisolone, respectively. Moreover, the ratio of total prednisolone to prednisone concentrations (active/inactive forms) was higher in diabetic subjects (P < 0.001). Modeling protein binding results revealed that the affinity constant of corticosteroid-binding globulin-prednisolone (KCBG,PL) was related to the patient's gender and diabetes status.

CONCLUSIONS

Higher prednisolone exposure could potentially lead to the increased risk of corticosteroid-related complications in diabetic kidney transplant recipients.

Multidrug resistance-associated protein 2 (MRP2/ABCC2) haplotypes significantly affect the pharmacokinetics of tacrolimus in kidney transplant recipients

BACKGROUND AND OBJECTIVE

Tacrolimus is an immunosuppressive drug used for the prevention of the allograft rejection in kidney transplant recipients. It exhibits a narrow therapeutic index and large pharmacokinetic variability. Tacrolimus is mainly metabolized by cytochrome P450 (CYP) 3A4 and 3A5 and effluxed via ATP-binding cassette (ABC) transporters such as P-glycoprotein (P-gp), encoded by ABCB1 gene. The influence of CYP3A5*3 on the pharmacokinetics of tacrolimus has been well characterized. On the other hand, the contribution of polymorphisms in other genes is controversial. In addition, the involvement of other efflux transporters than P-gp in tacrolimus disposition is uncertain. The present study was designed to investigate the effects of genetic polymorphisms of CYP3As and efflux transporters on the pharmacokinetics of tacrolimus.

SUBJECTS AND METHODS

A total of 500 blood concentrations of tacrolimus from 102 adult stable kidney transplant recipients were included in the analyses. Genetic polymorphisms in CYP3A4 and CYP3A5 genes were determined. In addition, the genes of efflux transporters including P-gp (ABCB1), multidrug resistance-associated protein (MRP2/ABCC2) and breast cancer resistance protein (BCRP/ABCG2) were genotyped. For ABCC2 gene, haplotypes were determined as follows: H1 (wild type), H2 (1249G>A), H9 (3972C>T) and H12 (-24C>T and 3972C>T). Population pharmacokinetic analysis was performed using nonlinear mixed effects modeling.

RESULTS

Analyses revealed that the CYP3A5 expressers (CYP3A5*1 carriers) and MRP2 high-activity group (ABCC2 H2/H2 and H1/H2) showed a decreased dose-normalized trough concentration of tacrolimus by 2.3-fold (p < 0.001) and 1.5-fold (p = 0.007), respectively. The pharmacokinetics of tacrolimus were best described using a two-compartment model with first order absorption and an absorption lag time. In the population pharmacokinetic analysis, CYP3A5 expressers and MRP2 high-activity groups were identified as the significant covariates for tacrolimus apparent clearance expressed as 20.7 × (age/50)(-0.78) × 2.03 (CYP3A5 expressers) × 1.40 (MRP2 high-activity group). No other CYP3A4, ABCB1 or ABCG2 polymorphisms were associated with the apparent clearance of tacrolimus.

CONCLUSIONS

This is the first report showing that MRP2/ABCC2 has a crucial impact on the pharmacokinetics of tacrolimus in a haplotype-specific manner. Determination of the ABCC2 as well as CYP3A5 genotype may be useful for more accurate tacrolimus dosage adjustment.