Individualization of tacrolimus dosage basing on cytochrome P450 3A5 polymorphism--a prospective, randomized, controlled study

Steroid-tacrolimus drug-drug interaction and the effect of CYP3A genotypes

AIMS

Tacrolimus, metabolized by CYP3A4 and CYP3A5 enzymes, is susceptible to drug-drug interactions (DDI). Steroids induce CYP3A genes to increase tacrolimus clearance, but the effect is variable. We hypothesized that the extent of the steroid-tacrolimus DDI differs by CYP3A4/5 genotypes.

METHODS

Kidney transplant recipients (n = 2462) were classified by the number of loss of function alleles (LOF) (CYP3A5*3, *6 and *7 and CYP3A4*22) and steroid use at each tacrolimus trough in the first 6 months post-transplant. A population pharmacokinetic analysis was performed by nonlinear mixed-effect modelling (NONMEM) and stepwise covariate modelling to define significant covariates affecting tacrolimus clearance. A stochastic simulation was performed and translated into a Shiny application with the mrgsolve and Shiny packages in R.

RESULTS

Steroids were associated with modestly higher (3%-11.8%) tacrolimus clearance. Patients with 0-LOF alleles receiving steroids showed the greatest increase (11.8%) in clearance compared to no steroids, whereas those with 2-LOFs had a negligible increase (2.6%) in the presence of steroids. Steroid use increased tacrolimus clearance by 5% and 10.3% in patients with 1-LOF and 3/4-LOFs, respectively.

CONCLUSIONS

Steroids increase the clearance of tacrolimus but vary slightly by CYP3A genotype. This is important in individuals of African ancestry who are more likely to carry no LOF alleles, may more commonly receive steroid treatment, and will need higher tacrolimus doses.

Antihypertensive treatment for kidney transplant recipients

BACKGROUND

The comparative effects of specific blood pressure (BP) lowering treatments on patient-important outcomes following kidney transplantation are uncertain. Our 2009 Cochrane review found that calcium channel blockers (CCBs) improved graft function and prevented graft loss, while the evidence for other BP-lowering treatments was limited. This is an update of the 2009 Cochrane review.

OBJECTIVES

To compare the benefits and harms of different classes and combinations of antihypertensive drugs in kidney transplant recipients.

SEARCH METHODS

We contacted the Information Specialist and searched the Cochrane Kidney and Transplant Register of Studies up to 3 July 2024 using search terms relevant to this review. Studies in the Register were identified through searches of CENTRAL, MEDLINE, EMBASE, conference proceedings, the International Clinical Trials Registry Platform (ICTRP) Search Portal, and ClinicalTrials.gov.

SELECTION CRITERIA

Randomised controlled trials (RCTs) and quasi-RCTs evaluating any BP-lowering agent in recipients of a functioning kidney transplant for at least two weeks were eligible.

DATA COLLECTION AND ANALYSIS

Two authors independently assessed the risks of bias and extracted data. Treatment estimates were summarised using the random-effects model and expressed as relative risk (RR) or mean difference (MD) with 95% confidence intervals (CI). Evidence certainty was assessed using Grades of Recommendation, Assessment, Development and Evaluation (GRADE) processes. The primary outcomes included all-cause death, graft loss, and kidney function.

MAIN RESULTS

Ninety-seven studies (8706 participants) were included. One study evaluated treatment in children. The overall risk of bias was unclear to high across all domains. Compared to placebo or standard care alone, CCBs probably reduce all-cause death (23 studies, 3327 participants: RR 0.83, 95% CI 0.72 to 0.95; I2 = 0%; moderate certainty evidence) and graft loss (24 studies, 3577 participants: RR 0.84, 95% CI 0.75 to 0.95; I2 = 0%; moderate certainty evidence). CCBs may make little or no difference to estimated glomerular filtration rate (eGFR) (11 studies, 2250 participants: MD 1.89 mL/min/1.73 m2, 95% CI -0.70 to 4.48; I2 = 48%; low certainty evidence) and acute rejection (13 studies, 906 participants: RR 10.8, 95% CI 0.85 to 1.35; I2 = 0%; moderate certainty evidence). CCBs may reduce systolic BP (SBP) (3 studies, 329 participants: MD -5.83 mm Hg, 95% CI -10.24 to -1.42; I2 = 13%; low certainty evidence) and diastolic BP (DBP) (3 studies, 329 participants: MD -3.98 mm Hg, 95% CI -5.98 to -1.99; I2 = 0%; low certainty evidence). CCBs have uncertain effects on proteinuria. Compared to placebo or standard care alone, angiotensin-converting-enzyme inhibitors (ACEi) may make little or no difference to all-cause death (7 studies, 702 participants: RR 1.13, 95% CI 0.58 to 2.21; I2 = 0%; low certainty evidence), graft loss (6 studies, 718 participants: RR 0.75, 95% CI 0.49 to 1.13; I2 = 0%; low certainty evidence), eGFR (4 studies, 509 participants: MD -2.46 mL/min/1.73 m2, 95% CI -7.66 to 2.73; I2 = 64%; low certainty evidence) and acute rejection (4 studies, 388 participants: RR 1.75, 95% CI 0.76 to 4.04; I2 = 0%; low certainty evidence). ACEi may reduce proteinuria (5 studies, 441 participants: MD -0.33 g/24 hours, 95% CI -0.64 to -0.01; I2 = 67%; low certainty evidence) but had uncertain effects on SBP and DBP. Compared to placebo or standard care alone, angiotensin receptor blockers (ARB) may make little or no difference to all-cause death (6 studies, 1041 participants: RR 0.69, 95% CI 0.36 to 1.31; I2 = 0%; low certainty evidence), eGRF (5 studies, 300 participants: MD -1.91 mL/min/1.73 m2, 95% CI -6.20 to 2.38; I2 = 57%; low certainty evidence), and acute rejection (4 studies, 323 participants: RR 1.00, 95% CI 0.44 to 2.29; I2 = 0%; low certainty evidence). ARBs may reduce graft loss (6 studies, 892 participants: RR 0.35, 95% CI 0.15 to 0.84; I2 = 0%; low certainty evidence), SBP (10 studies, 1239 participants: MD -3.73 mm Hg, 95% CI -7.02 to -0.44; I2 = 63%; moderate certainty evidence) and DBP (9 studies, 1086 participants: MD -2.75 mm Hg, 95% CI -4.32 to -1.18; I2 = 47%; moderate certainty evidence), but has uncertain effects on proteinuria. The effects of CCBs, ACEi or ARB compared to placebo or standard care alone on cardiovascular outcomes (including fatal or nonfatal myocardial infarction, fatal or nonfatal stroke) or other adverse events were uncertain. The comparative effects of ACEi plus ARB dual therapy, alpha-blockers, and mineralocorticoid receptor antagonists compared to placebo or standard care alone were rarely evaluated. Head-to-head comparisons of ACEi, ARB or thiazide versus CCB, ACEi versus ARB, CCB or ACEi versus alpha- or beta-blockers, or ACEi plus CCB dual therapy versus ACEi or CCB monotherapy were scarce. No studies reported outcome data for cancer or life participation.

AUTHORS' CONCLUSIONS

For kidney transplant recipients, the use of CCB therapy to reduce BP probably reduces death and graft loss compared to placebo or standard care alone, while ARB may reduce graft loss. The effects of ACEi and ARB compared to placebo or standard care on other patient-centred outcomes were uncertain. The effects of dual therapy, alpha-blockers, and mineralocorticoid receptor antagonists compared to placebo or standard care alone and the comparative effects of different treatments were uncertain.

Artificial Neural Network Analysis of Determinants of Tacrolimus Pharmacokinetics in Liver Transplant Recipients

BACKGROUND

The efficacy and toxicity of tacrolimus are closely related to its trough blood concentrations. Identifying the influencing factors of pharmacokinetics of tacrolimus in the early postoperative period is conducive to the optimization of the individualized tacrolimus administration protocol and to help liver transplant (LT) recipients achieve the target blood concentrations.

OBJECTIVE

This study aimed to develop an artificial neural network (ANN) for predicting the blood concentration of tacrolimus soon after liver transplantation and for identifying determinants of the concentration based on Shapley additive explanation (SHAP).

METHODS

In this retrospective study, we enrolled 31 recipients who were first treated with liver transplantation from the Department of Liver Transplantation and Hepatic Surgery, the First Affiliated Hospital of Shandong First Medical University (Shandong Provincial Qianfoshan Hospital) from November 2020 to May 2021. The basic information, biochemical indexes, use of concomitant drugs, and genetic factors of organ donors and recipients were used for the ANN model inputs, and the output was the steady-state trough concentration (C0) of tacrolimus after oral administration in LT recipients. The ANN model was established to predict C0 of tacrolimus, SHAP was applied to the trained model, and the SHAP value of each input was calculated to analyze quantitatively the influencing factors for the output C0.

RESULTS

A back-propagation ANN model with 3 hidden layers was established using deep learning. The mean prediction error was 0.27 ± 0.75 ng/mL; mean absolute error, 0.60 ± 0.52 ng/mL; correlation coefficient between predicted and actual C0 values, 0.9677; and absolute prediction error of all blood concentrations obtained by the ANN model, ≤3.0 ng/mL. The results indicated that the following factors had the most significant effect on C0: age, daily drug dose, genotype at CYP3A5 polymorphism rs776746 in both recipient and donor, and concomitant use of caspofungin. The predicted C0 value of tacrolimus in LT recipients increased in a dose-dependent manner when the daily dose exceeded 3 mg, whereas it decreased with age when LT recipients were older than 48 years. The predicted C0 was higher when recipients and donors had the genotype CYP3A5*3*3 than when they had the genotype CYP3A5*1. The predicted C0 value also increased with the use of caspofungin or Wuzhi capsule.

CONCLUSION AND RELEVANCE

The established ANN model can be used to predict the C0 value of tacrolimus in LT recipients with high accuracy and good predictive ability, serving as a reference for personalized treatment in the early stage after liver transplantation.

A prospective controlled, randomized clinical trial of kidney transplant recipients developed personalized tacrolimus dosing using model-based Bayesian Prediction

For three decades, tacrolimus (Tac) dose adjustment in clinical practice has been calculated empirically according to the manufacturer's labeling based on a patient's body weight. Here, we developed and validated a Population pharmacokinetic (PPK) model including pharmacogenetics (cluster CYP3A4/CYP3A5), age, and hematocrit. Our study aimed to assess the clinical applicability of this PPK model in the achievement of Tac Co (therapeutic trough Tac concentration) compared to the manufacturer's labelling dosage. A prospective two-arm, randomized, clinical trial was conducted to determine Tac starting and subsequent dose adjustments in 90 kidney transplant recipients. Patients were randomized to a control group with Tac adjustment according to the manufacturer's labeling or the PPK group adjusted to reach target Co (6-10 ng/ml) after the first steady state (primary endpoint) using a Bayesian prediction model (NONMEM). A significantly higher percentage of patients from the PPK group (54.8%) compared with the control group (20.8%) achieved the therapeutic target fulfilling 30% of the established superiority margin defined. Patients receiving PPK showed significantly less intra-patient variability compared to the control group, reached the Tac Co target sooner (5 days vs 10 days), and required significantly fewer Tac dose modifications compared to the control group within 90 days following kidney transplant. No statistically significant differences occurred in clinical outcomes. Thus, PPK-based Tac dosing offers significant superiority for starting Tac prescription over classical labeling-based dosing according to the body weight, which may optimize Tac-based therapy in the first days following transplantation.

Tacrolimus-why pharmacokinetics matter in the clinic

The calcineurin inhibitor (CNI) Tacrolimus (Tac) is the most prescribed immunosuppressant drug after solid organ transplantation. After renal transplantation (RTx) approximately 95% of recipients are discharged with a Tac-based immunosuppressive regime. Despite the high immunosuppressive efficacy, its adverse effects, narrow therapeutic window and high intra- and interpatient variability (IPV) in pharmacokinetics require therapeutic drug monitoring (TDM), which makes treatment with Tac a major challenge for physicians. The C/D ratio (full blood trough level normalized by daily dose) is able to classify patients receiving Tac into two major metabolism groups, which were significantly associated with the clinical outcomes of patients after renal or liver transplantation. Therefore, the C/D ratio is a simple but effective tool to identify patients at risk of an unfavorable outcome. This review highlights the challenges of Tac-based immunosuppressive therapy faced by transplant physicians in their daily routine, the underlying causes and pharmacokinetics (including genetics, interactions, and differences between available Tac formulations), and the latest data on potential solutions to optimize treatment of high-risk patients.

Pathway-level multi-omics analysis of the molecular mechanisms underlying the toxicity of long-term tacrolimus exposure

Tacrolimus (TAC)-based treatment is associated with nephrotoxicity and hepatotoxicity; however, the underlying molecular mechanisms responsible for this toxicity have not been fully explored. This study elucidated the molecular processes underlying the toxic effects of TAC using an integrative omics approach. Rats were sacrificed after 4 weeks of daily oral TAC administration at a dose of 5 mg/kg. The liver and kidney underwent genome-wide gene expression profiling and untargeted metabolomics assays. Molecular alterations were identified using individual data profiling modalities and further characterized by pathway-level transcriptomics-metabolomics integration analysis. Metabolic disturbances were mainly related to an imbalance in oxidant-antioxidant status, as well as in lipid and amino acid metabolism in the liver and kidney. Gene expression profiles also indicated profound molecular alterations, including in genes associated with a dysregulated immune response, proinflammatory signals, and programmed cell death in the liver and kidney. Joint-pathway analysis indicated that the toxicity of TAC was associated with DNA synthesis disruption, oxidative stress, and cell membrane permeabilization, as well as lipid and glucose metabolism. In conclusion, our pathway-level integration of transcriptome and metabolome and conventional analyses of individual omics profiles, provided a more comprehensive picture of the molecular changes resulting from TAC toxicity. This study also serves as a valuable resource for subsequent investigations aiming to understand the mechanism underlying the molecular toxicology of TAC.

Model-Based Tacrolimus Follow-up Dosing in Adult Renal Transplant Recipients: A Simulation Trial

BACKGROUND

Initial algorithm-based dosing appears to be effective in predicting tacrolimus dose requirement. However, achieving and maintaining the target concentrations is challenging. Model-based follow-up dosing, which considers patient characteristics and pharmacological data, may further personalize treatment. This study investigated whether model-based follow-up dosing could lead to more accurate tacrolimus exposure than standard therapeutic drug monitoring (TDM) in kidney transplant recipients after an initial algorithm-based dose.

METHODS

This simulation trial included patients from a prospective trial that received an algorithm-based tacrolimus starting dose followed by TDM. For every measured tacrolimus predose concentration (C 0,obs ), model-based dosing advice was simulated using the InsightRX software. Based on previous tacrolimus doses and C 0 , age, body surface area, CYP3A4 and CYP3A5 genotypes, hematocrit, albumin, and creatinine, the optimal next dose, and corresponding tacrolimus concentration (C 0,pred ) were predicted.

RESULTS

Of 190 tacrolimus C 0 values measured in 59 patients, 121 (63.7%; 95% CI 56.8-70.5) C 0,obs were within the therapeutic range (7.5-12.5 ng/mL) versus 126 (66.3%, 95% CI 59.6-73.0) for C 0,pred ( P = 0.89). The median absolute difference between the tacrolimus C 0 and the target tacrolimus concentration (10.0 ng/mL) was 1.9 ng/mL for C 0,obs versus 1.6 ng/mL for C 0,pred . In a historical cohort of 114 kidney transplant recipients who received a body weight-based starting dose followed by TDM, 172 of 335 tacrolimus C 0 (51.3%) were within the therapeutic range (10.0-15.0 ng/mL).

CONCLUSIONS

The combination of an algorithm-based tacrolimus starting dose with model-based follow-up dosing has the potential to minimize under- and overexposure to tacrolimus in the early posttransplant phase, although the additional effect of model-based follow-up dosing on initial algorithm-based dosing seems small.

Tacrolimus Exposure in Obese Patients: and A Case-Control Study in Kidney Transplantation

BACKGROUND

Tacrolimus pharmacokinetics in obese (Ob) patients has been poorly studied. In this article, the authors explored the impact of obesity on tacrolimus exposure in kidney transplant recipients (KTRs) and estimated a more suitable initial dosage in this population.

METHODS

A retrospective, observational, monocentric case-control study was performed in obese KTRs (BMI > 30 kg/m2) who received tacrolimus between 2013 and 2017 (initial dose: 0.15 mg/kg/d) (actual weight). Nonobese (Nob) controls (BMI <30 kg/m2) were matched for age and sex. Weekly centralized monitoring of tacrolimus trough levels was performed by liquid chromatography/mass spectrometry until the third month (M3). Target trough levels were set between 8 and 10 ng/mL. All patients received antilymphocyte globulin, corticosteroids, and mycophenolate mofetil.

RESULTS

Of the 541 KTRs, 28 tacrolimus-treated Ob patients were included and compared with 28 NOb-matched controls. With a mean of 22 assays/patient, tacrolimus trough levels were higher in Ob patients (mean 9.9 versus 8.7 ng/mL; P = 0.008); the weight-related dose of Tac was lower at M3 (mean 0.10 versus 0.13 mg/kg/d, P < 0.0001). The tacrolimus concentration to dose (C0/D) was higher in the Ob cohort [mean 116 versus 76 (ng/mL)/(mg/kg/d); P = 0.001]. In Ob patients, a mean decrease of -4.6 mg/d in the 3 months after tacrolimus initiation was required (versus -1.12 in NOb; P = 0.001) to remain within the therapeutic range. Obesity, high mycophenolate mofetil daily dose at M3, and CYP3A5 expression were independently associated with higher tacrolimus exposure. Four dose-adaptation strategies were simulated and compared with the study results.

CONCLUSIONS

An initial dose calculation based on either ideal or lean body weight may allow for faster achievement of tacrolimus trough level targets in Ob KTRs, who are at risk of overexposure when tacrolimus is initiated at 0.15 mg/kg/d. A prospective study is required to validate alternative dose calculation strategies in these patients.

Clinical Impact of the Adaptation of Initial Tacrolimus Dosing to the CYP3A5 Genotype After Kidney Transplantation: Systematic Review and Meta-Analysis of Randomized Controlled Trials

OBJECTIVE

The aim of this systematic review and meta-analysis was to compare the clinical outcomes between genotype-guided and conventional tacrolimus doses in kidney transplantation patients.

MATERIALS AND METHODS

We performed a comprehensive literature search of the PubMed, EMBASE, and Cochrane databases from the date of inception to 26 February 2020. References of the retrieved articles were also reviewed and any further relevant studies were included. The search terms included 'tacrolimus', 'cytochrome P-450 CYP3A', 'polymorphism, genetic', 'genomics', 'genome', 'genotype', 'genes', 'alleles', and 'pharmacogenetics'.

RESULTS

Our study showed that the genotype-guided group included an increased proportion of patients with tacrolimus concentrations in the therapeutic range at steady state (risk ratio [RR] 1.40, 95% confidence interval [CI] 1.14-1.72, p = 0.001; high quality), with a trend for achieving therapeutic concentrations earlier compared with those in the conventional group. However, there was no statistical difference in the incidence of delayed graft function (RR 1.98, 95% CI 0.92-1.76, p = 0.12; moderate quality), incidence of acute rejection (RR 1.00, 95% CI 0.64-1.55, p = 1.00; moderate quality), incidence of graft survival censored for death (RR 1.02, 95% CI 0.98-1.06, p = 0.37; moderate quality), and incidence of adverse effects (AEs).

CONCLUSIONS

Although the genotype-guided group had a higher proportion of patients within the targeted concentration and less median time to achieve the therapeutic range, the clinical endpoints, including delayed graft function, acute rejection, graft survival censored for death, and AEs were similar in both groups. All in all, evidence suggested there was no utility in pharmacogenetics for tacrolimus based on the cytochrome P450 (CYP) 3A5 genotype. Studies with Chinese and African American populations are needed due to the frequency of genetic polymorphisms of CYP3A5. Furthermore, a dosing algorithm that includes demographic and clinical factors plus multiple genetic variants should be added for consideration, and may optimize early tacrolimus exposure.

Avoiding Tacrolimus Underexposure and Overexposure with a Dosing Algorithm for Renal Transplant Recipients: A Single Arm Prospective Intervention Trial

Bodyweight‐based tacrolimus dosing followed by therapeutic drug monitoring is standard clinical care after renal transplantation. However, after transplantation, a meager 38% of patients are on target at first steady‐state and it can take up to 3 weeks to reach the target tacrolimus predose concentration (C₀). Tacrolimus underexposure and overexposure is associated with an increased risk of rejection and drug‐related toxicity, respectively. To minimize subtherapeutic and supratherapeutic tacrolimus exposure in the immediate post‐transplant phase, a previously developed dosing algorithm to predict an individual’s tacrolimus starting dose was tested prospectively. In this single‐arm, prospective, therapeutic intervention trial, 60 de novo kidney transplant recipients received a tacrolimus starting dose based on a dosing algorithm instead of a standard, bodyweight‐based dose. The algorithm included cytochrome P450 (CYP)3A4 and CYP3A5 genotype, body surface area, and age as covariates. The target tacrolimus C₀, measured for the first time at day 3, was 7.5–12.5 ng/mL. Between February 23, 2019, and July 7, 2020, 60 patients were included. One patient was excluded because of a protocol violation. On day 3 post‐transplantation, 34 of 59 patients (58%, 90% CI 47–68%) had a tacrolimus C₀ within the therapeutic range. Markedly subtherapeutic (< 5.0 ng/mL) and supratherapeutic (> 20 ng/mL) tacrolimus concentrations were observed in 7% and 3% of the patients, respectively. Biopsy‐proven acute rejection occurred in three patients (5%). In conclusion, algorithm‐based tacrolimus dosing leads to the achievement of the tacrolimus target C₀ in as many as 58% of the patients on day 3 after kidney transplantation.

A retrospective cohort study exploring diltiazem as a pharmaco-enhancer for tacrolimus, in a post-heart transplant setting

BACKGROUND

A significant proportion of heart transplant-associated expenditure are attributable to immunosuppressants. Post-transplant hypertension adds to the pill burden and subsequent costs. In this study, we describe the effect of diltiazem-the antihypertensive and pharmaco-enhancer-on reducing the required oral dose of tacrolimus.

METHODS

We included 17 recipients who had successfully undergone heart transplants but later developed post-transplant hypertension and were treated with diltiazem. Serum trough levels of the immunosuppressant tacrolimus were measured every 2 weeks. Required doses before and after the introduction of diltiazem were compared. Patients were assessed at each follow-up visit for any evidence of toxicity. Medication-related expenditure was estimated based on government-mandated standardized retail price.

RESULTS

The power of the study was 98.92% at α = 0.05. The mean tacrolimus dose required prior to initiation of diltiazem was 5.85 ± 1.55 mg. After initiating diltiazem, the mean required doses reduced to 2.88 ± 1.24 mg (p < .0001). Relatively, the required doses reduced by 52.4 ± 10.9%-independently of age, sex, and dose of diltiazem. Medication-related monthly expenditure reduced by 50.3 ± 10.4%. No patient demonstrated evidence of toxicity.

CONCLUSIONS

Concomitant use of diltiazem and tacrolimus can safely, effectively, and predictably reduce the required dose of tacrolimus and significantly reduce corresponding costs.

Tacrolimus Starting Dose Prediction Based on Genetic Polymorphisms and Clinical Factors in Chinese Renal Transplant Recipients

Aims: Tacrolimus has extensive pharmacokinetic variability among patients and a narrow therapeutic window. The U.S. Clinical Pharmacogenetics Implementation Consortium recommends a starting dose for tacrolimus of 0.15-0.3 mg/kg/day, which is much higher compared with 0.05-0.15 mg/kg/day used in China. The purpose of this study was to investigate the influence of clinical factors and single nucleotide polymorphisms (SNPs) on tacrolimus concentrations in Chinese renal transplant recipients. Methods: This study enrolled 406 tacrolimus-treated patients. After renal transplantation, the first tacrolimus trough concentration and corresponding clinical information were collected from all patients. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry was used to genotype 15 SNPs. The relationship between the genetic and clinical factors and dose-adjusted tacrolimus trough concentration was examined. The tacrolimus starting dose was predicted using a classification and regression tree analysis. Results: Examination of the 15 SNPs and several clinical factors identified the CYP3A5 genotype (p = 5.6 × 10^-11) and hemoglobin (p = 8.4 × 10^-10) as the most significant determinants of tacrolimus C₀/D. Accordingly, a concise tacrolimus recommendation dosage model, a classification scheme, and a regression tree were developed. Conclusion: A new classification and regression tree model was developed for establishing the starting dose of tacrolimus based on the CYP3A5 genotype and hemoglobin values. This result may help clinicians prescribe an appropriate initial tacrolimus dose. ClinicalTrials.gov ID: 2020-KY-147.

Frequency of CYP3A5 Genetic Polymorphisms and Tacrolimus Pharmacokinetics in Pediatric Liver Transplantation

The evidence available in the pediatric population is limited for making clinical decisions regarding the optimization of tacrolimus (TAC) in pharmacotherapy. The objective of this study was to estimate the frequency of CYP3A5 genetic polymorphisms and their relationship with tacrolimus requirements in the pediatric population. This was a longitudinal cohort study with a two-year follow-up of 77 patients under 18 years old who underwent a liver transplant during the period 2009–2012 at the J.P. Garrahan Pediatric Hospital. Tacrolimus levels from day five up to two years after the transplant were obtained from hospital records of routine therapeutic drug monitoring. The genotyping of CYP3A5 (CYP3A5*1/*3 or *3/*3) was performed in liver biopsies from both the donor and the recipient. The frequency of CYP3A5*1 expression for recipients was 37.1% and 32.2% for donors. Patients who received an expresser organ showed lower Co/dose, especially following 90 days after the surgery. The role of each polymorphism is different according to the number of days after the transplant, and it must be taken into account to optimize the benefits of TAC therapy during the post-transplant induction and maintenance phases.

Physicochemical Properties, Biotransformation, and Transport Pathways of Established and Newly Approved Medications: A Systematic Review of the Top 200 Most Prescribed Drugs vs. the FDA-Approved Drugs Between 2005 and 2016

BACKGROUND

Enzyme-mediated biotransformation of pharmacological agents is a crucial step in xenobiotic detoxification and drug disposition. Herein, we investigated the metabolism and physicochemical properties of the top 200 most prescribed drugs (established) as well as drugs approved by the US Food and Drug Administration (FDA) between 2005 and 2016 (newly approved).

OBJECTIVE

Our objective was to capture the changing trends in the routes of administration, physicochemical properties, and prodrug medications, as well as the contributions of drug-metabolizing enzymes and transporters to drug clearance.

METHODS

The University of Washington Drug Interaction Database (DIDB^®) as well as other online resources (e.g., CenterWatch.com, Drugs.com, DrugBank.ca, and PubChem.ncbi.nlm.nih.gov) was used to collect and stratify the dataset required for exploring the above-mentioned trends.

RESULTS

Analyses revealed that ~ 90% of all drugs in the established and newly approved drug lists were administered systemically (oral or intravenous). Meanwhile, the portion of biologics (molecular weight > 1 kDa) was 15 times greater in the newly approved list than established drugs. Additionally, there was a 4.5-fold increase in the number of compounds with a high calculated partition coefficient (cLogP > 3) and a high total polar surface area (> 75 Å²) in the newly approved drug vs. the established category. Further, prodrugs in established or newly approved lists were found to be converted to active compounds via hydrolysis, demethylases, and kinases. The contribution of cytochrome P450 (CYP) 3A4, as the major biotransformation pathway, has increased from 40% in the established drug list to 64% in the newly approved drug list. Moreover, the role of CYP1A2, CYP2C19, and CYP2D6 were decreased as major metabolizing enzymes among the newly approved medications. Among non-CYP major metabolizers, the contribution of alcohol dehydrogenases/aldehyde dehydrogenases (ADH/ALDH) and sulfotransferases decreased in the newly approved drugs compared with the established list. Furthermore, the highest contribution among uptake and efflux transporters was found for Organic Anion Transporting Polypeptide 1B1 (OATP1B1) and P-glycoprotein (P-gp), respectively.

CONCLUSIONS

The higher portion of biologics in the newly approved drugs compared with the established list confirmed the growing demands for protein- and antibody-based therapies. Moreover, the larger number of hydrophilic drugs found in the newly approved list suggests that the probability of toxicity is likely to decrease. With regard to CYP-mediated major metabolism, CYP3A5 showed an increased involvement owing to the identification of unique probe substrates to differentiate CYP3As. Furthermore, the contribution of OATP1B1 and P-gp did not show a significant shift in the newly approved drugs as compared to the established list because of their broad substrate specificity.

Fast Tac Metabolizers at Risk ⁻ It is Time for a C/D Ratio Calculation

Tacrolimus (Tac) is a part of the standard immunosuppressive regimen after renal transplantation (RTx). However, its metabolism rate is highly variable. A fast Tac metabolism rate, defined by the Tac blood trough concentration (C) divided by the daily dose (D), is associated with inferior renal function after RTx. Therefore, we hypothesize that the Tac metabolism rate impacts patient and graft survival after RTx. We analyzed all patients who received a RTx between January 2007 and December 2012 and were initially treated with an immunosuppressive regimen containing Tac (Prograf^®), mycophenolate mofetil, prednisolone and induction therapy. Patients with a Tac C/D ratio <1.05 ng/mL × 1/mg at three months after RTx were characterized as fast metabolizers and those with a C/D ratio ≥1.05 ng/mL × 1/mg as slow metabolizers. Five-year patient and overall graft survival were noticeably reduced in fast metabolizers. Further, fast metabolizers showed a faster decline of eGFR (estimated glomerular filtration rate) within five years after RTx and a higher rejection rate compared to slow metabolizers. Calculation of the Tac C/D ratio three months after RTx may assist physicians in their daily clinical routine to identify Tac-treated patients at risk for the development of inferior graft function, acute rejections, or even higher mortality.

A population pharmacokinetic model to predict the individual starting dose of tacrolimus in adult renal transplant recipients

Aims

The aims of this study were to describe the pharmacokinetics of tacrolimus immediately after kidney transplantation, and to develop a clinical tool for selecting the best starting dose for each patient.

Methods

Data on tacrolimus exposure were collected for the first 3 months following renal transplantation. A population pharmacokinetic analysis was conducted using nonlinear mixed‐effects modelling. Demographic, clinical and genetic parameters were evaluated as covariates.

Results

A total of 4527 tacrolimus blood samples collected from 337 kidney transplant recipients were available. Data were best described using a two‐compartment model. The mean absorption rate was 3.6 h⁻¹, clearance was 23.0 l h^–1 (39% interindividual variability, IIV), central volume of distribution was 692 l (49% IIV) and the peripheral volume of distribution 5340 l (53% IIV). Interoccasion variability was added to clearance (14%). Higher body surface area (BSA), lower serum creatinine, younger age, higher albumin and lower haematocrit levels were identified as covariates enhancing tacrolimus clearance. Cytochrome P450 (CYP) 3A5 expressers had a significantly higher tacrolimus clearance (160%), whereas CYP3A4*22 carriers had a significantly lower clearance (80%). From these significant covariates, age, BSA, CYP3A4 and CYP3A5 genotype were incorporated in a second model to individualize the tacrolimus starting dose: Dosemg=222nghml–1*22.5lh–1*1.0ifCYP3A5*3/*3or1.62ifCYP3A5*1/*3orCYP3A5*1/*1*1.0ifCYP3A4*1or unknownor0.814ifCYP3A4*22*Age56−0.50*BSA1.930.72/1000Both models were successfully internally and externally validated. A clinical trial was simulated to demonstrate the added value of the starting dose model.

Conclusions

For a good prediction of tacrolimus pharmacokinetics, age, BSA, CYP3A4 and CYP3A5 genotype are important covariates. These covariates explained 30% of the variability in CL/F. The model proved effective in calculating the optimal tacrolimus dose based on these parameters and can be used to individualize the tacrolimus dose in the early period after transplantation.

Impact of CYP3A5 genomic variances on clinical outcomes among African American kidney transplant recipients

Little is known about the impact of CYP3A5 polymorphisms on transplantation outcomes among African American (AA) kidney transplant recipients (KTRs). To assess this issue, clinical outcomes were compared between AA CYP3A5*1 expressers and nonexpressers. This retrospective cohort study analyzed AA KTRs. Biopsy-proven acute rejection (BPAR), delayed graft function (DGF), glomerular filtration rate (GFR), infections, and tacrolimus dosing requirements were examined in 106 immunologically high-risk AA kidney transplant patients over a 2-year follow-up period. In CYP3A5*1 expressers compared to nonexpressers, the incidence of BPAR was significantly higher in the first 6 months (13% vs 0%; P = .016) compared to 24 months (13% vs 7%; P = .521). Tacrolimus total daily dose at first therapeutic level was significantly higher in CYP3A5*1 expressers (12 mg/day) compared to nonexpressers (8 mg/day; P < .001). Compared to CYP3A5*1 nonexpressers, DGF incidence was significantly higher among CYP3A5*1 expressers (27.6% vs 6.7%; P = .006). By contrast, median GFR was significantly higher in CYP3A5*1 expressers compared to nonexpressers (54.5 mL/min vs 50.0 mL/min; P = .003) at 24 months. The findings from this retrospective study suggest that AAs with CYP3A5*1 expression require 50% more tacrolimus and have an increased incidence of DGF and acute rejection.

Comparison of tacrolimus and cyclosporin A in CYP3A5 expressing Chinese de novo kidney transplant recipients: a 2-year prospective study

AIMS

To assess the efficacy and safety of tacrolimus and cyclosporin A (CsA)-based immunosuppressive regimens in Chinese de novo kidney transplant recipients who are CYP3A5 expressers.

METHODS

The CYP3A5 (6986 A>G, rs776746) polymorphism of eligible patients was determined before transplantation. De novo kidney transplant recipients enrolled in this study were assigned to tacrolimus (Tac group) or CsA (CsA group) based therapy. The follow-up period was 2 years. The incidence of acute rejection, patient and graft survival rates, renal allograft function and post-transplant complications were compared. The intra-individual variability (IIV) of Tac and CsA blood concentrations was analysed. Medication costs were also compared. The analysis was conducted on the intention-to-treat principle.

RESULTS

A total of 72 CYP3A5 expressers were enrolled, with 36 patients in each group. AR incidence was higher in the Tac group (11.1% vs. 5.6%), but there was no significant difference (p > 0.05). The 2-year patient and graft survival was comparable, and renal function was comparable in the two groups. Notably, the Tac group presented a significantly higher incidence of BK viremia (22.2% vs. 5.6%, p < 0.05) and BK viruria (38.9% vs. 16.7%, p < 0.05) than the CsA group. The CsA IIV at 1 and 3 months post-transplant was significantly lower than the Tac IIV (p < 0.05). The medical costs of both immunosuppressive drugs and management of complications was significantly lower in the CsA group.

CONCLUSIONS

Cyclosporin A-based maintenance therapy is safe for Chinese de novo kidney transplant recipients who are CYP3A5 expressers. CsA significantly reduced medication costs and decreased BKV infection, suggesting that it is more beneficial for this specific population.

Dynamic effects of CYP3A5 polymorphism on dose requirement and trough concentration of tacrolimus in renal transplant recipients

WHAT IS KNOWN AND OBJECTIVE

Tacrolimus is a widely used immunosuppressive drug with marked pharmacokinetic variability partly due to CYP3A5 polymorphism. Our study aimed to investigate the dynamic effects of CYP3A5 genotypes on dose requirement and trough concentration (C₀ ) of tacrolimus in renal transplant recipients.

METHODS

A total of 194 Chinese renal transplant recipients received oral tacrolimus twice daily. Whole-blood C₀ of tacrolimus were measured on the 3rd day, 7th day, 14th day, 1st month, 3rd month and 6th month post-transplantation. CYP3A5 genotypes were determined and the recipients were categorized as CYP3A5 expressers (CYP3A5*1 allele carriers) and non-expressers (homozygous CYP3A5*3). The correlated serum creatinine, haematocrit and albumin were also detected.

RESULTS

The allele frequencies for CYP3A5*1/*1, *1/*3 and *3/*3 were 7·7%, 44·8% and 47·4%, respectively. There were no significant variability in serum creatinine, haematocrit and albumin values between CYP3A5 expressers and non-expressers. Larger doses were administered to CYP3A5 expressers than to non-expressers after surgery except the initial dose. C₀ were much lower in CYP3A5 expressers than in non-expressers on the 3rd day, 7th day, 14th day and 1st month post-transplantation (P < 0·01); however, no significant differences were found on the 3rd and 6th months post-transplantation. All of the dose-adjusted C₀ in CYP3A5 expressers were significantly lower than non-expressers (P < 0·01). Less of the recipients achieving target C₀ (4-8 ng/mL) were found in CYP3A5 expressers than in non-expressers after initial dose (35·7% vs. 50%). Meanwhile, CYP3A5 non-expressers were detected having higher C₀ (>8 ng/mL) during 3 months post-transplantation. Besides, the proportions in the two groups both increased gradually over time and up to 91·8% and 94% on the 6th month, respectively.

WHAT IS NEW AND CONCLUSION

There are no significant differences in serum creatinine, haematocrit and albumin values between CYP3A5 expressers and non-expressers. CYP3A5 expressers have decreased dose-adjusted tacrolimus C₀ when compared to non-expressers. Dose-adjusted C₀ of tacrolimus increases in a time-dependent manner in both groups.

The POR rs1057868-rs2868177 GC-GT diplotype is associated with high tacrolimus concentrations in early post-renal transplant recipients

AIM

Cytochrome P450 oxidoreductase (POR) is the only flavoprotein that donates electrons to all microsomal P450 enzymes (CYP), and several POR SNPs have been shown to be important contributors to altered CYP activity or CYP-mediated drug metabolism. In this study we examined the association between 6 POR SNPs and tacrolimus concentrations in Chinese renal transplant recipients.

METHODS

A total of 154 renal transplant recipients were enrolled. Genotyping of CYP3A5*3 and 6 POR SNPs was performed. All patients received a triple immunosuppressive regimen comprising tacrolimus, mycophenolate mofetil and prednisone. Dose-adjusted tacrolimus trough concentrations were obtained on d 7 (C0D7/D) after transplantation when steady-state concentration of tacrolimus was achieved (dosage had been unchanged for more than 3 d).

RESULTS

Tacrolimus C0D7/D in CYP3A5*3/*3/ POR rs1057868-rs2868177 GC-GT diplotype carriers was 1.62- and 2.72-fold higher than those in CYP3A5*3/*3/ POR rs1057868-rs2868177 GC-GT diplotype non-carriers and CYP3A5*1 carriers (220.17±48.09 vs 135.69±6.86 and 80.84±5.27 ng/mL/mg/kg, respectively, P<0.0001). Of CYP3A5*3/*3/ POR rs1057868-rs2868177GC-GT diplotype carriers, 85.71% exceeded the upper limit of the target range (8 ng/mL), which was also significantly higher compared with the latter two groups (14.29% and 0.00%, respectively, P<0.0001). The CYP3A5*3 and POR rs1057868-rs2868177 GC-GT diplotype explained 31.7% and 5.7%, respectively, of the inter-individual variability of tacrolimus C0D7/D, whereas the POR rs1057868-rs2868177 GC-GT diplotype could explain 10.9% of the inter-individual variability of tacrolimus C0D7/D in CYP3A5 non-expressers.

CONCLUSION

The CYP3A5*3 and POR rs1057868-rs2868177 GC-GT diplotype accounted for the inter-individual variation of tacrolimus C0D7/D. Genotyping of POR rs1057868-rs2868177 diplotypes would help to differentiate initial tacrolimus dose requirements and to achieve early target C0 ranges in Chinese renal transplant recipients.

Pharmacogenetic aspects of the use of tacrolimus in renal transplantation: recent developments and ethnic considerations

INTRODUCTION

Tacrolimus (Tac) is effective in preventing acute rejection but has considerable toxicity and inter-individual variability in pharmacokinetics and pharmacodynamics. Part of this is explained by polymorphisms in genes encoding Tac-metabolizing enzymes and transporters. A better understanding of Tac pharmacokinetics and pharmacodynamics may help to minimize different outcomes amongst transplant recipients by personalizing immunosuppression.

AREAS COVERED

The pharmacogenetic contribution of Tac metabolism will be examined, with a focus on recent discoveries, new developments and ethnic considerations.

EXPERT OPINION

The strongest and most consistent association in pharmacogenetics is between the CYP3A5 genotype and Tac dose requirement, with CYP3A5 expressers having a ~ 40-50% higher dose requirement compared to non-expressers. Two recent randomized-controlled clinical trials using CYP3A5 genotype, however, did not show a decrease in acute rejections nor reduced toxicity. CYP3A4*22, CYP3A4*26, and POR*28 are also associated with Tac dose requirements and may be included to provide the expected improvement of Tac therapy. Studies focusing on the intracellular drug concentrations and on calcineurin inhibitor-induced nephrotoxicity also seem promising. For all studies, however, the ethnic prevalence of genotypes should be taken into account, as this may significantly impact the effect of pre-emptive genotyping.

Individualizing liver transplant immunosuppression using a phenotypic personalized medicine platform

Postoperative liver transplant immunosuppression was personalized using a phenotypic, disease mechanism–independent and indication-agnostic approach.

Interactive effects of CYP3A4, CYP3A5, MDR1 and NR1I2 polymorphisms on tracrolimus trough concentrations in early postrenal transplant recipients

Aims: To evaluate the influences of CYP3A4, CYP3A5, MDR1 and NR1I2 polymorphisms on tacrolimus concentration in early postrenal transplant recipients. Patients & methods: A total of 159 patients were included, dose-adjusted tacrolimus trough concentration on day 7 after transplantation (C0D7/D) was calculated and 10 SNPs in four genes were genotyped. Results: CYP3A5*3 explained 32.8% of variability of tacrolimus C0D7/D. CYP3A4*1G, MDR1 1236–2677–3435 diplotype and NR1I2 -25385C > T explained 21.4% of variability of tacrolimus C0D7/D in CYP3A5 nonexpressers. Conclusion: CYP3A5*3 was the predominant determinant affecting tacrolimus concentration. Genotyping of CYP3A4/MDR1/NR1I2 polymorphisms may be helpful for better guiding tacrolimus dosing in CYP3A5 nonexpressers.

Tacrolimus in preventing transplant rejection in Chinese patients--optimizing use

Tacrolimus is a product of fermentation of Streptomyces, and belongs to the family of calcineurin inhibitors. It is a widely used immunosuppressive drug for preventing solid-organ transplant rejection. Compared to cyclosporine, tacrolimus has greater immunosuppressive potency and a lower incidence of side effects. It has been accepted as first-line treatment after liver and kidney transplantation. Tacrolimus has specific features in Chinese transplant patients; its in vivo pharmacokinetics, treatment regimen, dose and administration, and adverse-effect profile are influenced by multiple factors, such as genetics and the spectrum of primary diseases in the Chinese population. We reviewed the clinical experience of tacrolimus use in Chinese liver- and kidney-transplant patients, including the pharmacology of tacrolimus, the immunosuppressive effects of tacrolimus versus cyclosporine, effects of different factors on tacrolimus metabolism on Chinese patients, personalized medicine, clinical safety profile, and patient satisfaction and adherence. This article provides guidance for the rational and efficient use of tacrolimus in Chinese organ-transplant patients.

Long-term outcome of ketoconazole and tacrolimus co-administration in kidney transplant patients

AIM: To study the long-term outcome of ketoconazole and tacrolimus combination in kidney transplant recipients.

METHODS: From 2006 to 2010, ketoconazole was given in 199 patients and was continued for at least 1 year or until graft failure (Group 1), while 149 patients did not receive any ketoconazole (Group 2). A combination of tacrolimus, mycophenolate and steroid was used as maintenance therapy. High risk patients received basiliximab induction.

RESULTS: Basic demographic data was similar between the 2 groups. The 5-year cumulative incidence of biopsy-confirmed and clinically-treated acute rejection was significantly higher in Group 1 than in Group 2 (34% vs 18%, P = 0.01). The 5-year Kaplan-Meier estimated graft survival (74.3% vs 76.4%, P = 0.58) and patient survival (87.8% vs 87.5%, P = 0.93) were not different between the 2 groups. Multivariable analyses identified ketoconazole usage as an independent risk of acute rejection (HR = 2.33, 95%CI: 1.33-4.07; P = 0.003) while tacrolimus dose in the 2^nd month was protective (HR = 0.89, 95%CI: 0.75-0.96; P = 0.041).

CONCLUSION: Co-administration of ketoconazole and tacrolimus is associated with significantly higher incidence of acute rejection in kidney transplant recipients.

Impact of the CYP3A5, CYP3A4, COMT, IL-10 and POR genetic polymorphisms on tacrolimus metabolism in Chinese renal transplant recipients

Tacrolimus is a widely used immunosuppressive drug for preventing the rejection of solid organ transplants. The efficacy of tacrolimus shows considerable variability, which might be related to genetic variation among recipients. We conducted a retrospective study of 240 Chinese renal transplant recipients receiving tacrolimus as immunosuppressive drug. The retrospective data of all patients were collected for 40 days after transplantation. Seventeen SNPs of CYP3A5, CYP3A4, COMT, IL-10 and POR were identified by the SNaPshot assay. Tacrolimus blood concentrations were obtained on days 1-3, days 6-8 and days 12-14 after transplantation, as well as during the period of the predefined therapeutic concentration range. Kruskal-Wallis test was used to examine the effect of genetic variation on the tacrolimus concentration/dose ratio (C 0/D) at different time points. Chi-square test was used to compare the proportions of patients who achieved the target C 0 range in the different genotypic groups at weeks 1, 2, 3 and 4 after transplantation. After correction for multiple testing, there was a significant association of C 0/D with CYP3A5*3, CYP3A4*1G and CYP3A4 rs4646437 T>C at different time points after transplantation. The proportion of patients in the IL-10 rs1800871-TT group who achieved the target C 0 range was greater (p = 0.004) compared to the IL-10 rs1800871-CT and IL-10 rs1800871-CC groups at week 3 after transplantation. CYP3A5*3, CYP3A4 *1G, CYP3A4 rs4646437 T>C and IL-10 rs1800871 C>T might be potential polymorphisms affecting the interindividual variability in tacrolimus metabolism among Chinese renal transplant recipients.

Pharmacogenetic considerations for optimizing tacrolimus dosing in liver and kidney transplant patients

The introduction of tacrolimus in clinical practice has improved patient survival after organ transplant. However, despite the long use of tacrolimus in clinical practice, the best way to use this agent is still a matter of intense debate. The start of the genomic era has generated new research areas, such as pharmacogenetics, which studies the variability of drug response in relation to the genetic factors involved in the processes responsible for the pharmacokinetics and/or the action mechanism of a drug in the body. This variability seems to be correlated with the presence of genetic polymorphisms. Genotyping is an attractive option especially for the initiation of the dosing of tacrolimus; also, unlike phenotypic tests, the genotype is a stable characteristic that needs to be determined only once for any given gene. However, prospective clinical studies must show that genotype determination before transplantation allows for better use of a given drug and improves the safety and clinical efficacy of that medication. At present, research has been able to reliably show that the CYP3A5 genotype, but not the CYP3A4 or ABCB1 ones, can modify the pharmacokinetics of tacrolimus. However, it has not been possible to incontrovertibly show that the corresponding changes in the pharmacokinetic profile are linked with different patient outcomes regarding tacrolimus efficacy and toxicity. For these reasons, pharmacogenetics and individualized medicine remain a fascinating area for further study and may ultimately become the face of future medical practice and drug dosing.