Factors associated with changes in tacrolimus blood concentration after food initiation in patients with ulcerative colitis.

The therapeutic effect of tacrolimus against ulcerative colitis (UC) is correlated with its trough blood concentration. Conventionally, oral tacrolimus for the treatment of UC is initiated under fasting conditions; once the symptoms improve, food intake is resumed. Tacrolimus blood concentration decreases with food intake compared with that under fasting conditions. The aim of this study was to explore the characteristics of patients with UC whose tacrolimus blood concentrations tended to decrease after food initiation. Medical data of 13 patients with UC and treated with tacrolimus were retrospectively obtained. The participant characteristics associated with the changes in tacrolimus blood concentrations after food initiation were analyzed using regression analysis based on the rate of decrease in the concentration/dose (C/D) ratio after food initiation. Single regression analysis showed that the number of days required from tacrolimus initiation to food resumption (P = 0.0071) and individual differences in the increase in tacrolimus blood concentration after administration (P = 0.0247) were significantly associated with the rate of decrease in the C/D ratio after food initiation. Furthermore, multiple regression analysis showed a significant effect of the number of days to food resumption (P = 0.0004) and individual differences in the increase in tacrolimus blood concentration after administration (P = 0.0012). The results suggest that the degree of change in blood tacrolimus concentration after food initiation may be related to the severity of the symptoms and pathology of UC. Early identification of participant characteristics may help control tacrolimus blood concentration fluctuations after food initiation.

A joint population pharmacokinetic model to assess the high variability of whole-blood and intracellular tacrolimus in early adult renal transplant recipients.

Tacrolimus (TAC) has high pharmacokinetic (PK) variability during the early transplantation period. The relationships between whole-blood and intracellular TAC concentrations and clinical outcomes remain controversial. This study identifies the factors affecting the PK variability of TAC and characterizes the relationships between whole-blood and intracellular TAC concentrations. Data regarding whole-blood TAC concentrations of 1,787 samples from 215 renal transplant recipients (<90 days postoperative) across two centers and intracellular TAC concentrations (648 samples) digitized from previous studies were analyzed using nonlinear mixed-effects modeling. The effects of potential covariates were screened, and the distribution of whole-blood to intracellular TAC concentration ratios (RWB:IC) was estimated. The final model was evaluated using bootstrap, goodness of fit, and prediction-corrected visual predictive checks. The optimal dosing regimens and target ranges for each type of immune cell subsets were determined using Monte Carlo simulations. A two-compartment model adequately described the data, and the estimated mean TAC CL/F was 23.6 L·h-1 (relative standard error: 11.5 %). The hematocrit level, CYP3A5*3 carrier status, co-administration with Wuzhi capsules, and tapering prednisolone dose may contribute to the high variability of TAC PK variability during the early post-transplant period. The estimated RWB:IC of all TAC concentrations in peripheral blood mononuclear cells (PBMCs) was 4940, and inter-center variability of PBMCs was observed. The simulated TAC target range in PBMCs was 20.2-85.9 pg·million cells-1. Inter-center variability in intracellular concentrations should be taken into account in further analyses. TAC dosage adjustments can be guided based on PK/PD variability and simulated intracellular concentrations.

External validation of population pharmacokinetic models of tacrolimus in Thai adult liver transplant recipients.

OBJECTIVE: Several population pharmacokinetic models of tacrolimus in liver transplant patients were built, and their predictability was evaluated in their settings. However, the extrapolation in the prediction was unclear. This study aimed to evaluate the predictive performance of published tacrolimus models in adult liver transplant recipients using data from the Thai population as an external dataset. METHODS: The selected published models were systematically searched and evaluated for their quality. The external dataset of patients who underwent the first liver transplant and received immediate-release tacrolimus was used to assess the predictive performance of each selected model. Trough concentrations between 3 and 6 months were retrospectively collected to evaluate the predictability of each model using prediction-based diagnostics, simulation-based diagnostics, and Bayesian forecasting. RESULTS: Sixty-seven patients with 360 trough concentrations and eight selected published models were included in this study. None of the models met the predictive precision criteria in prediction-based diagnostics. Meanwhile, four published population pharmacokinetic models showed a normal distribution in NPDE testing. Regarding Bayesian forecasting, all models improved their forecasts with at least one prior information data point. CONCLUSION: Bayesian forecasting is more accurate and precise than other testing methods for predicting drug concentrations. However, none of the evaluated models provides satisfactory predictive performance for generalization to Thai liver transplant patients. This underscores the need for future research to develop population PK models tailored to the Thai population. Such efforts should consider the inclusion of nonlinear pharmacokinetics and region-specific factors, including genetic variability, to improve model accuracy and applicability.

Identification and characterization of critical values in therapeutic drug monitoring: a retrospective analysis.

Therapeutic drug monitoring (TDM) is a crucial clinical practice that improves pharmacological effectiveness and prevent severe drug-related adverse events. Timely reporting and intervention of critical values during TDM are essential for patient safety. In this study, we retrospectively analyzed the laboratory data to provide an overview of the incidence, distribution pattern and biochemical correlates of critical values during TDM. A total of 19,110 samples were tested for nine drug concentrations between January 1, 2019, and December 31, 2020. Of these, 241 critical values were identified in 165 patients. The most common critical values were vancomycin trough (63.4%), followed by tacrolimus trough (16.9%) and digoxin (15.2%). The primary sources of drug critical values were the department of general intensive care unit (ICU), cardiology, and surgery ICU. At baseline or the time of critical value, significant differences were found between the vancomycin, digoxin, and tacrolimus groups in terms of blood urea nitrogen (BUN), creatinine, N-terminal Pro-B-Type Natriuretic Peptide (NT-proBNP), and lymphocyte percentage, P < 0.05. Therefore, it is important to prioritize and closely monitor drug concentrations to reduce laboratory critical values during TDM.

Pharmacodynamic monitoring by residual gene expression of the nuclear factor of activated T cell-regulated genes in lung transplant recipients and its correlation with tacrolimus blood levels.

Introduction: Trough blood levels (C0) of tacrolimus are used to adjust drug dosage, but they do not consistently correlate with clinical outcomes. Measurement of residual gene expression of nuclear factor of activated T cell (NFAT)-regulated genes (NFAT-RGE) has been proposed as a pharmacodynamic biomarker to assess the degree of immunosuppression in certain solid organ transplantations, but little is known regarding lung transplant recipients (LTR). Our primary objective is to correlate tacrolimus blood levels with NFAT-RGE. Methods: NFAT-RGE and tacrolimus C0 and peak (C1.5) levels were determined in 42 patients at three, six and 12 months post-transplantation. Results: Tacrolimus C0 did not exhibit a correlation with NFAT-RGE, whereas C1.5 did. Besides, over 20% of measurements indicated high levels of immunosuppression based on the below 30% NFAT-RGE threshold observed in many studies. Among those measurements within the therapeutic range, 19% had an NFAT-RGE<30%. Conclusion: Consequently, a subset of patients within the tacrolimus therapeutic range may be more susceptible to infection or cancer, potentially benefiting from NFAT-RGE and tacrolimus peak level monitoring to tailor their dosage. Further quantitative risk assessment studies are needed to elucidate the relationship between NFAT-RGE and the risk of infection, cancer, or rejection.

Cassia angustifolia and tacrolimus interaction in a liver transplant patient, a case report.

Cassia angustifolia is a species of plant from the Senna family that has traditionally been used as a laxative in different herbal products and commercial medicines. Even though there are few documented drug-plant interactions, the use of C. angustifolia with different drugs may have additive effects, such as with other laxatives or potassium-depleting diuretics. Its use also increases peristalsis which, may reduce drug absorption. The combination with digoxin has been associated with an increased risk of digoxin toxicity, probably due to an increase in plasma digoxin concentrations and hypokalaemia. We present a case with supratherapeutic trough concentration of tacrolimus, an immunosuppressive agent, and a herbal product in a liver transplant patient after concomitant intake of tacrolimus and a herbal product based on C. angustifolia, suggesting a possible drug-lant interaction through by P-glycoprotein. We observed an increase in the patient's blood concentration 2.8-fold and the area under the curve at steady state 2.1-fold. This interaction could be of clinical relevance, given the dose-dependent side effects of tacrolimus, such as nephrotoxicity, neurotoxicity, hypertension, hyperglycaemia, or electrolyte alterations.

Follow the Area Under the Curve Not the Trough Concentration: A Case Study of Tacrolimus Monitoring in a Kidney Transplant Recipient Cotreated With Phenobarbital.

ABSTRACT: The authors described tacrolimus dosing in a kidney transplant patient concurrently treated with phenobarbital, where measuring the tacrolimus area under the curve was necessary to achieve adequate drug exposure and improve kidney function.

Association of CYP3A4-392A/G, CYP3A5-6986A/G, and ABCB1-3435C/T Polymorphisms with Tacrolimus Dose, Serum Concentration, and Biochemical Parameters in Mexican Patients with Kidney Transplant.

Tacrolimus (TAC) is an immunosuppressant drug that prevents organ rejection after transplantation. This drug is transported from cells via P-glycoprotein (ABCB1) and is a metabolic substrate for cytochrome P450 (CYP) 3A enzymes, particularly CYP3A4 and CYP3A5. Several single-nucleotide polymorphisms (SNPs) have been identified in the genes encoding CYP3A4, CYP3A5, and ABCB1, including CYP3A4-392A/G (rs2740574), CYP3A5 6986A/G (rs776746), and ABCB1 3435C/T (rs1045642). This study aims to evaluate the association among CYP3A4-392A/G, CYP3A5-6986A/G, and ABCB1-3435C/T polymorphisms and TAC, serum concentration, and biochemical parameters that may affect TAC pharmacokinetics in Mexican kidney transplant (KT) patients. METHODS: Forty-six kidney transplant recipients (KTR) receiving immunosuppressive treatment with TAC in different combinations were included. CYP3A4, CYP3A5, and ABCB1 gene polymorphisms were genotyped using qPCR TaqMan. Serum TAC concentration (as measured) and intervening variables were assessed. Logistic regression analyses were performed at baseline and after one month to assess the extent of the association between the polymorphisms, intervening variables, and TAC concentration. RESULTS: The GG genotype of CYP3A5-6986 A/G polymorphism is associated with TAC pharmacokinetic variability OR 4.35 (95%CI: 1.13-21.9; p = 0.0458) at one month of evolution; in multivariate logistic regression, CYP3A5-6986GG genotype OR 9.32 (95%CI: 1.54-93.08; p = 0.028) and the use of medications or drugs that increase serum TAC concentration OR 9.52 (95%CI: 1.79-88.23; p = 0.018) were strongly associated with TAC pharmacokinetic variability. CONCLUSION: The findings of this study of the Mexican population showed that CYP3A5-6986 A/G GG genotype is associated with a four-fold increase in the likelihood of encountering a TAC concentration of more than 15 ng/dL. The co-occurrence of the CYP3A5-6986GG genotype and the use of drugs that increase TAC concentration correlates with a nine-fold increased risk of experiencing a TAC at a level above 15 ng/mL. Therefore, these patients have an increased susceptibility to TAC-associated toxicity.

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.

Tacrolimus Variability and Clinical Outcomes in the Early Post-lung Transplantation Period: Oral Versus Continuous Intravenous Administration.

BACKGROUND AND OBJECTIVE: High variability in tacrolimus pharmacokinetics directly after lung transplantation (LuTx) may increase the risk for acute kidney injury (AKI) and transplant rejection. The primary objective was to compare pharmacokinetic variability in patients receiving tacrolimus orally versus intravenously early after LuTx. METHODS: Pharmacokinetic and clinical data from 522 LuTx patients transplanted between 2010 and 2020 in two university hospitals were collected to compare orally administered tacrolimus to intravenous tacrolimus early post-transplantation. Tacrolimus blood concentration variability, measured as intrapatient variability (IPV%) and  percentage of time within the therapeutic range (TTR%), was analyzed within the first 14 days after LuTx. Secondary outcomes were AKI, acute rejection, length of stay in the intensive care unit (ICU), and mortality in the ICU and during hospital admission. RESULTS: We included 224 patients in the oral and 298 in the intravenous group. The mean adjusted IPV% was 10.8% (95% confidence interval [CI] 6.9-14.6; p < 0.001) higher in the oral group (27.2%) than the intravenous group (16.4%). The mean TTR% was 7.3% (95% CI - 11.3 to - 3.4; p < 0.001) lower in the oral group (39.6%) than in the intravenous group (46.9%). The incidence of AKI was 46.0% for oral and 42.6% for intravenous administration (adjusted odds ratio [OR] 1.2; 95% CI 0.8-1.8; p = 0.451). The frequencies of clinically diagnosed acute rejection in the oral and intravenous groups were nonsignificant (24.6% vs 17.8%; OR 1.5 [95% CI 1.0-2.3; p = 0.059]). ICU and hospital mortality rate and ICU length of stay were similar. CONCLUSIONS: Administering tacrolimus orally directly after LuTx leads to a higher variability in blood concentrations compared to intravenous administration. There was no difference in the occurrence of AKI or transplant rejection.

Population pharmacokinetics of everolimus in renal transplant recipients receiving long-term multiple immunosuppressive therapy.

Everolimus is used for immunosuppression after renal transplantation. This study aimed to develop a population pharmacokinetic (PopPK) model of everolimus using therapeutic drug monitoring (TDM) data of patients under long-term multiple immunosuppressive therapy, including tacrolimus. To develop the model, 185 renal transplant recipients with 3358 everolimus blood concentrations during a median postoperative period of 35.3 months were included. The PopPK model is described as a one-compartment model with first-order absorption. The population mean of apparent clearance is 8.92 L/h (relative standard error = 3.6%), and this negatively correlated with the dose-normalized concentration (C/D) of tacrolimus and hematocrit value, and positively correlated with a daily dose of everolimus (i.e. TDM effect). The usefulness of dose adjustment using the final popPK model was assessed by a simulation study. The ratio of the first trough measurement within the therapeutic range of 3-8 ng/mL increased from 69.8% in the original dose to 87.9% in the individual dose calculated by the final PopPK model. The tacrolimus C/D ratio before initiating everolimus therapy and the hematocrit value were useful to estimate the initial dose of everolimus and can improve the safety and effectiveness of immunosuppressive therapy involving everolimus.

High intra-patient variability of tacrolimus within post-operative 1 month predicted worse 1-year outcomes in pediatric liver transplant recipients.

BACKGROUND: The pharmacokinetics of tacrolimus (TAC) show high intra-patient variability (IPV), which is associated with poor long-term outcomes following adult liver transplantation (LT). However, this relationship remains to be confirmed in pediatric liver transplant (PLT) recipients. The present study aimed to investigate the association between TAC IPV and grafts or patient outcomes after pediatric liver transplantion. METHODS: This retrospective study included 848 PLT recipients (including infants) between January, 2016, and June, 2021. The IPV of TAC concentrations was estimated by calculating the coefficient of variation (CV) of trough concentrations in whole blood within 1 month after transplantation. Patients were categorized into two groups, low IPV (CV < 45%) and high IPV (CV ≥ 45%), based on the third quartile of the CV distribution. RESULTS: A total of 848 patients were included in our study. The low CV group included 614 patients, with a mean TAC trough concentration of 8.59 ± 1.65 ng/ml and a median CV of 32.37%. In contrast, the high CV group included 214 patients, the mean TAC trough concentration and median CV were 8.81 ± 2.00 ng/ml and 54.88%, respectively. The median hospital duration was significantly higher in the high CV group (22 days vs. 20 days, P = 0.01). Univariate analysis was performed to evaluate the significant differences in 1-year recipient survival (P = 0.041) and 1-year graft survival (P = 0.005) between the high- and low-CV groups. Moreover, high CV (HR 2.316, 95%CI 1.026-5.231, P = 0.043) and persistent EBV viremia (HR 13.165, 95%CI 3.090-56.081, P < 0.001) were identified as independent risk factors for 1- year mortality after PLT. CONCLUSIONS: PLT recipients with high TAC trough concentration of CV in the first month were associated with poor 1-year outcomes. This CV calculation provides a valuable strategy to monitor TAC exposure.

Clinical effects of tacrolimus blood concentrations early after allogeneic hematopoietic stem cell transplantation.

BACKGROUND AIMS: Tacrolimus (TAC) plus short-term methotrexate (stMTX) is used for graft-versus-host disease (GVHD) prophylaxis after allogeneic hematopoietic stem cell transplantation (allo-HSCT). TAC blood concentrations are frequently adjusted to enhance the graft-versus-leukemia/lymphoma effect or attenuate severe GVHD. Limited information is available on the clinical impact of these adjustments and the optimal time to perform them in order to achieve good clinical outcomes. METHODS: We retrospectively analyzed 211 patients who underwent allo-HSCT at our institutes. RESULTS: Higher TAC concentrations in week 3 correlated with a significantly higher cumulative incidence of relapse (CIR) (P = 0.03) and lower nonrelapse mortality (P = 0.04). The clinical impact of high TAC concentrations in week 3 on CIR was detected in the refined disease risk index: low/intermediate (P = 0.04) and high (P < 0.01), and conditioning regimens other than cyclophosphamide/total body irradiation and busulfan/cyclophosphamide (P = 0.07). Higher TAC concentrations in week 1 correlated with a lower grade 2-4 acute GVHD rate (P = 0.01). Higher TAC concentrations in weeks 2 and 3 correlated with slightly lower (P = 0.05) and significantly lower (P = 0.02) grade 3-4 acute GVHD rates, respectively. Higher TAC concentrations in weeks 1 and 3 were beneficial for severe acute GVHD in patients with a human leukocyte antigen-matched donor (P = 0.03 and P < 0.01, respectively), not treated with anti-thymocyte globulin (P = 0.02 and P = 0.02, respectively), and receiving three stMTX doses (P = 0.03 and P = 0.02, respectively). CONCLUSIONS: The clinical impact of TAC concentrations varied according to patient characteristics, including disease malignancy, conditioning regimens, donor sources, and GVHD prophylaxis. These results suggest that TAC management needs to be based on patient profiles.

Good correlation between tacrolimus concentrations using improved CMIA on the Alinity i analyzer and LC-MS/MS method from a reference laboratory but unexpected negative bias with another LC-MS/MS method from a different reference laboratory.

OBJECTIVES: We compared tacrolimus concentrations obtained by the more recently US Food and Drug Administration-approved tacrolimus assay (CMIA) on the Alinity i analyzer (Abbott Laboratories) with a liquid chromatography/tandem mass spectrometry (LC-MS/MS)-based method from 2 reference laboratories. We also investigated the correlation between the CMIA tacrolimus and Elecsys tacrolimus assays. METHODS: Tacrolimus concentrations were measured in EDTA whole blood by the chemiluminescent microparticle immunoassay (CMIA) using the Alinity i analyzer, and then 2 aliquots were sent to 2 reference laboratories, both using ascomycin as the internal standard for the LC-MS/MS method. RESULTS: The total precision of the CMIA tacrolimus assay was excellent. When tacrolimus concentrations obtained by the LC-MS/MS method from reference laboratory A were plotted on the x-axis and corresponding CMIA values were plotted on the y-axis, the following regression equation was observed: y = 0.9721x + 1.005 (r = 0.95), indicating no significant bias with the CMIA. However, when tacrolimus values obtained from reference laboratory B were used for comparison, the regression equation was y = 0.7664x + 1.775 (r = 0.93), indicating significant negative bias with the CMIA. When we compared tacrolimus concentrations obtained by reference laboratories A and B, we observed positive bias with tacrolimus concentrations obtained by reference laboratory B. However, tacrolimus concentrations obtained by both CMIA and Elecsys immunoassays were comparable. CONCLUSIONS: Because of good correlation of tacrolimus concentrations using the CMIA and LC-MS/MS from reference laboratory A, our long-term reference laboratory for drug analysis, we concluded that the CMIA on the Alinity i can be used for therapeutic drug monitoring of tacrolimus.

Effect of Extraction Procedure Substitution on Automated Tacrolimus, Sirolimus, and Cyclosporine Assays.

BACKGROUND: An erroneously high tacrolimus level was reported to a clinician. A root cause analysis investigation failed to determine the cause of the error. It was suspected that the incorrect preanalytical extraction reagent and procedure was used during testing; however, how this would affect the assayed drug concentration was unclear. Here we investigated the effect of the substitution of sirolimus, tacrolimus, and cyclosporine extraction reagents on assayed drug concentration. METHODS: Tacrolimus, sirolimus, and cyclosporine concentration were measured on the Abbott Architect i2000 analyzer. Each assay requires a preanalytical extraction step, with a distinct reagent. We investigated the effect of the substitution of the extraction reagents and procedure between the 3 assays on the measured drug concentration. Two experiments were performed, one on samples of known drug concentration and one on samples with no drug present. RESULTS: Substituting cyclosporine and sirolimus extraction procedures increased assayed tacrolimus concentrations from 5.6 to 8.47 (+51.25%) and 8.13 (+45.18%) ng/mL, respectively. Extraction procedure substitutions decreased assayed sirolimus from 13.63 to 4.60 (-66.25%) and 8.07 (-40.79%) ng/mL for cyclosporine and tacrolimus. Cyclosporine concentration increased from 274.60 to 391.30 (+42.50%) ng/mL using sirolimus extraction reagents and to 757.30 (+175.78%) ng/mL using tacrolimus extraction reagents. Cross-reactivity was observed between the tacrolimus assay and sirolimus and cyclosporine extraction reagents. CONCLUSIONS: Significant changes, both positive and negative, are observed in assayed drug concentration when incorrect extraction procedures are used in the Abbott i2000 tacrolimus, sirolimus, and cyclosporine assays. Preanalytic extraction procedures should be investigated when performing root cause analysis for erroneous therapeutic drug values.

Effects of ABCB1 DNA methylation in donors on tacrolimus blood concentrations in recipients following liver transplantation.

AIMS: To investigate the effects of ABCB1 DNA methylation in donors on individual differences in tacrolimus blood concentrations following liver transplantation. METHODS: Twenty-three donor liver samples carrying the CYP3A5*3/*3 genotype were classified into 2 groups based on their initial tacrolimus blood concentrations (C0  >10 µg/L or <5 µg/L) following liver transplantation. ABCB1 mRNA levels in liver tissues and HepG2 cells were determined by quantitative reverse transcriptase polymerase chain reaction. DNA methylation status in liver tissues and HepG2 cells was determined using Illumina 850 methylation chip sequencing technology and pyrosequencing. 5-Aza-2dC was used to reverse methylation in HepG2 cells. Intracellular tacrolimus concentrations were determined by liquid mass spectrometry. RESULTS: Genome-wide methylation sequencing and pyrosequencing analyses showed that the methylation levels of 3 ABCB1 CpG sites (cg12501229, cg00634941 and cg05496710) were significantly different between groups with different tacrolimus concentration/dose (C0 /D) ratios. ABCB1 mRNA expression in donor livers was found to be positively correlated with tacrolimus C0 /D ratio (R = .458, P < .05). After treatment with 5-Aza-2-Dc, the methylation levels of the ABCB1 CpG sites in HepG2 cells significantly decreased, and this was confirmed by pyrosequencing; there was also a significant increase in ABCB1 transcription, which induced a decrease in intracellular tacrolimus concentrations. CONCLUSION: ABCB1 CpG site methylation affects tacrolimus metabolism in humans by regulating ABCB1 expression. Therefore, ABCB1 DNA methylation in donor livers might be an important epigenetic factor that affects tacrolimus blood concentrations following liver transplantation.

Flat Pattern Peaks of Tacrolimus Absorption and Associated Pharmacogenomic Variants in Kidney Transplantation Recipients.

BACKGROUND: Tacrolimus is the most commonly used immunosuppressive drug in solid organ transplantation. After administering a conventional twice-daily dose of tacrolimus, peak levels were achieved within the first 1.5 to 2 hours. A group of patients showed different early absorption phase of tacrolimus after kidney transplantation. METHODS: Trough(C0) and 1.5-hour blood levels (C1.5) of tacrolimus were measured in 95 kidney transplantation recipients. Patients with a C1.5/C0 < 1.5 and > 1.5 were defined as those having flat pattern peaks and as controls, respectively. Transplantation outcomes were compared between the groups. Whole exome sequencing was performed to investigate the genetic susceptibility to flat pattern peaks. RESULTS: Twenty-eight patients showed flat pattern peaks. The mean C1.5/C0 values were 1.13 ± 0.22 and 3.78 ± 1.25 in the flat pattern peak and control groups, respectively. In multivariate analysis, flat pattern peak was an independent risk factor for biopsy-proven acute rejection (BPAR) and/or borderline change (P = 0.014). Patients having flat pattern peaks showed significantly lower post-transplant 36-month estimated glomerular filtration rate (P = 0.001). Two single nucleotide variants in ABCB1 genes, rs1922242 and rs2235035, were associated with flat pattern peaks (P = 0.019 and P = 0.027, respectively). CONCLUSION: Both of C1.5 and C0 should be measured to distinguish the patients showing unique initial absorption. A C1.5/C0 ratio lower than 1.5 was associated with an increased risk of BPAR and/or borderline change. Single nucleotide variants s in ABCB1 gene might influence the flat pattern peaks of tacrolimus absorption.

CYP3A7, CYP3A4, and CYP3A5 genetic polymorphisms in recipients rather than donors influence tacrolimus concentrations in the early stages after liver transplantation.

AIM: The purpose of this study was to investigate the effect of CYP3A7, CYP3A4, and CYP3A5 genetic polymorphisms in liver transplant recipients and donors on tacrolimus concentrations in the early stages after liver transplantation. METHODS: One hundred and thirty-eight liver transplant recipients and matched donors were genotyped for CYP3A7 (rs10211 and rs2257401), CYP3A4 (rs4646437 and rs2242480), and CYP3A5*3 (rs776746) polymorphisms. The relationships between dose-adjusted trough concentrations (C0/D) of tacrolimus and corresponding genotypes were investigated. RESULTS: Recipient CYP3A polymorphisms were associated with tacrolimus concentrations. The CYP3A7 rs10211 AA carriers (186.2 vs 90.5, p < 0.001), CYP3A4 rs4646437 CC carriers (184.0 vs 88.8, p < 0.001), CYP3A4*1G rs2242480 CC carriers (189.8 vs 99.7, p < 0.001), and CYP3A5*3 rs776746 GG carriers (197.3 vs 86.0, p < 0.001) had an almost twofold increase in the tacrolimus C0/D compared to that of the non-carriers. We further investigated the effect of the combination of recipient (intestinal) and donor (hepatic) genotypes on tacrolimus concentrations. Regardless of the genotype of the matched donor, CYP3A7 rs10211, CYP3A4*1G (rs2242480), and CYP3A5*3 (rs776746) polymorphisms of recipients could affect tacrolimus concentrations. For the CYP3A4 rs4646437 polymorphisms, when the donor carried CYP3A4 rs4646437 CC, the recipient CYP3A4 rs4646437 polymorphism was associated with the C0/D of tacrolimus, and when the donor carried CYP3A4 rs4646437 CT/TT genotype, the recipient CYP3A4 rs4646437 polymorphism also affected on tacrolimus C0/D, although the effect was not significant. CONCLUSION: The large inter-individual variation in tacrolimus concentrations in the early stages after liver transplantation is influenced by genetic polymorphisms of CYP3A7, CYP3A4, and CYP3A5. Recipient (intestinal) CYP3A7, CYP3A4, and CYP3A5 polymorphisms seem to contribute more to such variation than donors. Therefore, the detection of CYP3A polymorphisms in recipients could help to predict the tacrolimus starting dose in the early stages after liver transplantation.