A published pharmacogenetic algorithm was poorly predictive of tacrolimus clearance in an independent cohort of renal transplant recipients

Calcineurin inhibition may prevent Alzheimer disease in people with Down syndrome

Virtually all people with Down syndrome will develop Alzheimer disease pathology during their lifetime. As Alzheimer disease is the third leading cause of death and a significant factor in end-of-life complications for adults with Down syndrome, identifying interventions is a medical necessity. Calcineurin, a Ca2+/calmodulin-dependent protein phosphatase, has recently been investigated as a possible Alzheimer treatment. This review explores the histories behind Down syndrome and Alzheimer disease, and their intersecting pathologies. This is followed by the role that calcineurin and its U.S. Food and Drug Administration-approved pharmacological inhibitor, tacrolimus, may play in the prevention or treatment of Alzheimer disease. Finally, this review discusses the gap in the literature surrounding the role of calcineurin, its regulators, and calcineurin inhibitors in the context of Down syndrome and comorbid Alzheimer disease. Future studies investigating the role that calcineurin plays in this pathology will be essential in determining the viability of calcineurin inhibitors to treat Alzheimer disease in people with Down syndrome. HIGHLIGHTS: Calcineurin, a Ca2+/calmodulin-dependent protein phosphatase, has become prominent as a possible therapeutic target to treat Alzheimer disease. People with Down syndrome develop Alzheimer pathology as they age, requiring novel therapeutics for treatment. People with Down syndrome may exhibit contraindications to calcineurin inhibition-based therapy, as they overexpress RCAN1 and DYRK1A, regulators of calcineurin. There is a significant gap in the literature involving the expression of calcineurin, RCAN1 and DYRK1A, in people with Down syndrome and Alzheimer disease, which must be addressed to determine the efficacy and safety of newly developed therapeutics.

Synergistic Effect of Cytochrome P450 Family 3 Subfamily A Member 5 (CYP3A5) Genetic Variants in Tacrolimus Dose Determination in Indian Renal Transplant Patients

Tacrolimus (TAC) has a narrow therapeutic index and shows interindividual variabilities in its blood concentration. Although guidelines recommend a genetic variant (rs776746) to determine the optimized TAC dose, discrepancies in accuracy have been noted. Therefore, studying other variants of CYP3A5 may improve the accuracy of the TAC dose. Clinical exome sequencing (CES) was performed in 219 renal transplant patients. The SNPs of CYP3A5 covered by CES were recorded. The TAC blood trough concentration/dose (C 0/D) was calculated on day 7 and months 1, 3, 6, and 12 of post-transplantation, and association with CYP3A5 genotypes was studied. Further, biopsy-proven rejection and pathological events were analyzed for their association with CYP3A5 genotypes. Out of 35 variants of CYP3A5 covered in CES, rs776746, rs15524, rs4646449, and rs464645 were significantly associated with the TAC C 0/D on day 7 and months 1, 3, and 6. Further analysis showed that the slow-metabolizing genotypes of all four SNPs synergistically associated with the TAC C 0/D on day 7 and months 1, 3, 6, and 12. The "CC" genotype of rs776746 showed a significant association (RR = 1.613; p = 0.035) with allograft rejection. In addition, cox regression analysis showed that the presence of the "CA" genotype of rs4646453 increased (HR = 7.258; 95% CI = 1.354-38.904) the risk of development of pathological events, respectively. Four variants of CYP3A5 were synergistically associated with the TAC dose determination. In addition, rs776746 and rs4646453 may be associated with allograft rejection and pathological events, respectively.

Removing the physician from the equation: Patient-controlled, home-based therapeutic drug self-monitoring of tacrolimus

The dosing of tacrolimus, which forms the backbone of immunosuppressive therapy after kidney transplantation, is complex. This is due to its variable pharmacokinetics (both between and within individual patients), narrow therapeutic index, and the severe consequences of over- and underexposure, which may cause toxicity and rejection, respectively. Tacrolimus is, therefore, routinely dosed by means of therapeutic drug monitoring (TDM). TDM is performed for as long as the transplant functions and frequent and often lifelong sampling is therefore the rule. This puts a significant burden on patients and transplant professionals and is associated with high healthcare-associated costs. Furthermore, by its very nature, TDM is reactive and has no predictive power. Finally, the current practice of TDM does not foresee in an active role for patients themselves. Rather, the physician or pharmacist prescribes the next tacrolimus dose after obtaining the concentration measurement test results. In this article, we propose a strategy of patient-controlled, home-based, self-TDM of the immunosuppressant tacrolimus after transplantation. We argue that with the combined use of population tacrolimus pharmacokinetic models, home-based sampling by means of dried blood spotting and implementation of telemedicine, this may become a feasible approach in the near future.

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.

A systematic review and meta-analysis recite the efficacy of Tacrolimus treatment in renal transplant patients in association with genetic variants of CYP3A5 gene

Tacrolimus is an immunosuppressant with a narrow therapeutic index and pharmacokinetic variability. This variability may be attributed to genetic variants in gene CYP3A5 associated with Tacrolimus metabolism. Studies focusing on genetic variants in the CYP3A5 gene associated with Tacrolimus metabolism have been published, a meta-analysis of these published articles may provide a direction that can change the future research and clinical management of renal transplant patients. In this systematic review and meta-analysis, we have reviewed and analyzed the studies and clinical trials conducted to determine the association between genetic variants of CYP3A5 and Tacrolimus metabolism from the PubMed database and clinical trials (www.clinicaltrials.gov). This meta-analysis also assessed the correlation of CYP3A5 genotype (rs776746) with concentration/dose (Co/D) of Tacrolimus in renal transplant patients. The 59 published articles on genetic association of the CYP3A5 on Tacrolimus doses were reviewed for this systematic review. Meta-analysis showed that the Tacrolimus Co/D ratio is significantly lower in the CYP3A5 expressor group as compared with non-expressor in Asian, European as well as in mixed populations at any post-transplant period (P<0.0001). Our study further confirmed that the CYP3A5 variant (rs776746) is clinically relevant for the dose determination of Tacrolimus. Variations in Tacrolimus Co/D have been found to be significantly linked to the patient's CYP3A5 genetic variant (rs776746). The addition of other genetic variants involved in the pharmacokinetic of Tacrolimus may determine efficient regimen for drug dose. Our meta-analysis confirmed that the CYP3A5 genetic variant (rs776746) analysis is relevant in personalizing the Tacrolimus dose determination in renal transplant patients.

Current status of xenotransplantation research and the strategies for preventing xenograft rejection

Transplantation is often the last resort for end-stage organ failures, e.g., kidney, liver, heart, lung, and pancreas. The shortage of donor organs is the main limiting factor for successful transplantation in humans. Except living donations, other alternatives are needed, e.g., xenotransplantation of pig organs. However, immune rejection remains the major challenge to overcome in xenotransplantation. There are three different xenogeneic types of rejections, based on the responses and mechanisms involved. It includes hyperacute rejection (HAR), delayed xenograft rejection (DXR) and chronic rejection. DXR, sometimes involves acute humoral xenograft rejection (AHR) and cellular xenograft rejection (CXR), which cannot be strictly distinguished from each other in pathological process. In this review, we comprehensively discussed the mechanism of these immunological rejections and summarized the strategies for preventing them, such as generation of gene knock out donors by different genome editing tools and the use of immunosuppressive regimens. We also addressed organ-specific barriers and challenges needed to pave the way for clinical xenotransplantation. Taken together, this information will benefit the current immunological research in the field of xenotransplantation.

Development of De Novo Donor-specific HLA Antibodies and AMR in Renal Transplant Patients Depends on CYP3A5 Genotype

BACKGROUND

The single-nucleotide polymorphism CYP3A5 rs776746 is related to a reduction in the metabolizing activity of the CYP3A5 enzyme. People carrying at least one copy of the wild-type allele, defined as CYP3A5 expressers, exhibit higher clearance and lower trough concentrations of tacrolimus than homozygous nonexpressers, and this difference may affect alloimmunization and allograft function.

METHODS

We retrospectively studied 400 kidney transplant recipients treated with a tacrolimus-based immunosuppression regimen to detect CYP3A5 genotype, de novo formation of HLA antibodies and donor-specific antibodies (DSAs), and clinical outcome up to 5 y after transplant.

RESULTS

We found that 69 (17%) of the 400 patients were CYP3A5 expressers. During the first 3 y after transplant, CYP3A5 expressers tended to have lower tacrolimus trough levels than nonexpressers, although their tacrolimus dosage was as much as 80% higher. De novo DSAs were found more frequently in CYP3A5 expressers than in nonexpressers (13/69 [19%] versus 33/331 [10%], P = 0.02). De novo DSA-free survival rates (P = 0.02) were significantly lower for expressers than for nonexpressers. CYP3A5 genotype had no effect on allograft failure, but CYP3A5 expressers exhibited a significantly higher frequency of antibody-mediated rejection. CYP3A5 expresser status was an independent risk factor for the development of de novo DSAs (relative risk, 2.34, P = 0.01).

CONCLUSIONS

Early detection of CYP3A5 expressers, enabling genotype-based dose adjustment of tacrolimus immediately after renal transplant, may be a useful strategy for reducing the risk of de novo DSA production and antibody-mediated rejection.

An Integrated Clinical and Genetic Prediction Model for Tacrolimus Levels in Pediatric Solid Organ Transplant Recipients

BACKGROUND

There are challenges in achieving and maintaining therapeutic tacrolimus levels after solid organ transplantation (SOT). The purpose of this genome-wide association study was to generate an integrated clinical and genetic prediction model for tacrolimus levels in pediatric SOT.

METHODS

In a multicenter prospective observational cohort study (2015-2018), children <18 years old at their first SOT receiving tacrolimus as maintenance immunosuppression were included (455 as discovery cohort; 322 as validation cohort). Genotyping was performed using a genome-wide single nucleotide polymorphism (SNP) array and analyzed for association with tacrolimus trough levels during 1-y follow-up.

RESULTS

Genome-wide association study adjusted for clinical factors identified 25 SNPs associated with tacrolimus levels; 8 were significant at a genome-wide level (P < 1.025 × 10-7). Nineteen SNPs were replicated in the validation cohort. After removing SNPs in strong linkage disequilibrium, 14 SNPs remained independently associated with tacrolimus levels. Both traditional and machine learning approaches selected organ type, age at transplant, rs776746, rs12333983, and rs12957142 SNPs as the top predictor variables for dose-adjusted 36- to 48-h posttacrolimus initiation (T1) levels. There was a significant interaction between age and organ type with rs776476*1 SNP (P < 0.05). The combined clinical and genetic model had lower prediction error and explained 30% of the variation in dose-adjusted T1 levels compared with 18% by the clinical and 12% by the genetic only model.

CONCLUSIONS

Our study highlights the importance of incorporating age, organ type, and genotype in predicting tacrolimus levels and lays the groundwork for developing an individualized age and organ-specific genotype-guided tacrolimus dosing algorithm.

Efficacy and outcomes of CYP3A5 genotype-based tacrolimus dosing compared to conventional body weight-based dosing in living donor kidney transplant recipients

Introduction:

Clinical use of tacrolimus has been challenging due to its narrow therapeutic index and highly variable pharmacokinetics. In this study, we compared patients who received body weight-based tacrolimus dosing pre-transplant (transplanted from 2016 to 2018) with those who received CYP3A5 genotype-based dosing (2018 to 2020).

Methods:

Eighty-two renal transplant recipients were non-randomly assigned to genotype-adapted or bodyweight-based tacrolimus dosing groups. The primary end point was to study the proportion of subjects who achieved the target tacrolimus C₀ on post-op day 4. Secondary end points included clinical outcomes and safety.

Results:

The proportion of subjects who achieved the target tacrolimus C₀ on postoperative days 4 and 10 were significantly higher in the adapted group, 53.6% and 47.5%, compared to 24.3% and 17% in controls, respectively (P = 0.01). Adapted group subjects achieved their first target tacrolimus C₀ significantly earlier (4 days) compared to 25 days in controls (P = 0.01). The total number of tacrolimus dose modifications required in the first postop month were lower in the adapted group; 47 compared to 68 in the controls (P = 0.05). The proportion of subjects with sub-therapeutic tacrolimus exposure on postoperative day 4 was significantly higher in the controls, 56% versus 10% in the adapted group (P < 0.001). There were no significant differences between the groups in the rate of biopsy proven acute rejections, adverse events, and graft function at the end of 3 months follow up.

Conclusion:

Genotype-based tacrolimus dosing leads to more subjects achieving the target tacrolimus C₀ earlier. However, there may be a higher risk of tacrolimus nephrotoxicity.

The Relationship between Initial Tacrolimus Metabolism Rate and Recipients Body Composition in Kidney Transplantation

There are several premises that the body composition of kidney transplant recipients may play a role in tacrolimus metabolism early after transplantation. The present study aimed at analyzing the relationship between the body composition parameters assessed by bioimpedance analysis (BIA) and initial tacrolimus metabolism. Immediately prior to transplantation, BIA using InBody 770 device was performed in 122 subjects. Tacrolimus concentration-to-dose (C/D) ratio was calculated based on the first blood trough level measurement. There was no difference in phase angle, visceral fat area, lean body mass index (LBMI) and the proportion of lean mass as a percentage of total body mass between the subgroups of slow and fast metabolizers. However, subjects with LBMI ≥ median value of 18.7 kg/m², despite similar initial tacrolimus dose per kg of body weight, were characterized by a significantly lower tacrolimus C/D ratio (median 1.39 vs. 1.67, respectively; p < 0.05) in comparison with the subgroup of lower LBMI. Multivariate regression analysis confirmed that age (r_partial = 0.322; p < 0.001) and LBMI (r_partial = −0.254; p < 0.01) independently influenced the tacrolimus C/D ratio. A LBMI assessed by BIA may influence the tacrolimus metabolism in the early post-transplant period and can be a useful in the optimization of initial tacrolimus dosing.

Pharmacogenetics Based Dose Prediction Model for Initial Tacrolimus Dosing in Renal Transplant Recipients

Tacrolimus, an immunosuppressant used in solid organ transplantation, has a narrow therapeutic index and exhibits inter-individual pharmacokinetic variability. Achieving and maintaining a therapeutic level of the drug by giving appropriate doses is crucial for successful immunosuppression, especially during the initial post-transplant period. We studied the effect of CYP3A5, CYP3A4, and ABCB1 gene polymorphisms on tacrolimus trough concentrations in South Indian renal transplant recipients from Kerala to formulate a genotype-based dosing equation to calculate the required starting daily dose of tacrolimus to be given to each patient to attain optimal initial post-transplant period drug level. We also investigated the effect of these genes on drug-induced adverse effects and rejection episodes and looked into the global distribution of allele frequencies of these polymorphisms. One hundred forty-five renal transplant recipients on a triple immunosuppressive regimen of tacrolimus, mycophenolate mofetil, and steroid were included in this study. Clinical data including tacrolimus daily doses, trough levels (C0) and dose-adjusted tacrolimus trough concentration (C0/D) in blood at three time points (day 6, 6 months, and 1-year post-transplantation), adverse drug effects, rejection episodes, serum creatinine levels, etc., were recorded. The patients were genotyped for CYP3A5*3, CYP3A4*1B, CYP3A4*1G, ABCB1 G2677T, and ABCB1 C3435T polymorphisms by the PCR-RFLP method. We found that CYP3A5*3 polymorphism was the single most strongly associated factor determining the tacrolimus C0/D in blood at all three time points (p < 0.001). Using multiple linear regression, we formulated a simple and easy to compute equation that will help the clinician calculate the starting tacrolimus dose per kg body weight to be administered to a patient to attain optimal initial post-transplant period tacrolimus level. CYP3A5 expressors had an increased chance of rejection than non-expressors (p = 0.028), while non-expressors had an increased risk for new-onset diabetes mellitus after transplantation (NODAT) than expressors (p = 0.018). Genotype-guided initial tacrolimus dosing would help transplant recipients achieve optimal initial post-transplant period tacrolimus levels and thus prevent the adverse effects due to overdose and rejection due to inadequate dose. We observed inter-population differences in allele frequencies of drug metabolizer and transporter genes, emphasizing the importance of formulating population-specific dose prediction models to draw results of clinical relevance.

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.

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.

Pharmacokinetics, Pharmacodynamics and Pharmacogenetics of Tacrolimus in Kidney Transplantation

Background:

Tacrolimus (Tac, or FK506), a calcineurin inhibitor (CNI), is the first-line immu-nosuppressant which consists of the footstone as immunosuppressive regimens in kidney transplantation. However, the drug toxicity and the significant differences of pharmacokinetics (PK) and pharmacodynam-ics (PD) among individuals are hidden troubles for clinical application. Recently, emerging evidences of Tac pharmacogenetics (PG) regarding drug absorption, metabolism, disposition, excretion and response are discovered for better understanding of this drug.

Method:

We reviewed the published articles regarding the Tac PG and its effects on PK and PD in kidney transplantation. In addition, we summarized information on polygenic algorithms.

Results:

The polymorphism of genes encoding metabolic enzymes and transporters related to Tac were largely investigated, but the results were inconsistent. In addition to CYP3A4, CYP3A5 and P-gp (also known as ABCB1), single nucleotide polymorphisms (SNPs) might also affect the PK and PD parameters of Tac.

Conclusion:

The correlation between Tac PK, PD and PG is very complex. Although many factors need to be verified, it is envisaged that thorough understanding of PG may assist clinicians to predict the optimal starting dosage, help adjust the maintenance regimen, as well as identify high risk patients for adverse ef-fects or drug inefficacy

Biomarkers and Pharmacogenomics in Kidney Transplantation

This review is focused on present and future biomarkers, along with pharmacogenomics used in clinical practice for kidney transplantation. It aims to highlight biomarkers that could potentially be used to improve kidney transplant early and long-term graft survival, but also potentially patient co-morbidity. Future directions for improving outcomes are discussed, which include immune tolerance and personalising immunosuppression regimens.

CYP3A5 polymorphisms in renal transplant recipients: influence on tacrolimus treatment

Tacrolimus is a commonly used immunosuppressant after kidney transplantation. It has a narrow therapeutic range and demonstrates wide interindividual variability in pharmacokinetics, leading to potential underimmunosuppression or toxicity. Genetic polymorphism in CYP3A5 enzyme expression contributes to differences in tacrolimus bioavailability between individuals. Individuals carrying one or more copies of the wild-type allele *1 express CYP3A5, which increases tacrolimus clearance. CYP3A5 expressers require 1.5 to 2-fold higher tacrolimus doses compared to usual dosing to achieve therapeutic blood concentrations. Individuals with homozygous *3/*3 genotype are CYP3A5 nonexpressers. CYP3A5 nonexpression is the most frequent phenotype in most ethnic populations, except blacks. Differences between CYP3A5 genotypes in tacrolimus disposition have not translated into differences in clinical outcomes, such as acute rejection and graft survival. Therefore, although genotype-based dosing may improve achievement of therapeutic drug concentrations with empiric dosing, its role in clinical practice is unclear. CYP3A5 genotype may predict differences in absorption of extended-release and immediate-release oral formulations of tacrolimus. Two studies found that CYP3A5 expressers require higher doses of tacrolimus in the extended-release formulation compared to immediate release. CYP3A5 genotype plays a role in determining the impact of interacting drugs, such as fluconazole, on tacrolimus pharmacokinetics. Evidence conflicts regarding the impact of CYP3A5 genotype on risk of nephrotoxicity associated with tacrolimus. Further study is required.

Pharmacokinetic considerations related to therapeutic drug monitoring of tacrolimus in kidney transplant patients

INTRODUCTION

Tacrolimus (Tac) is the cornerstone of immunosuppressive therapy after solid organ transplantation and will probably remain so. Excluding belatacept, no new immunosuppressive drugs were registered for the prevention of acute rejection during the last decade. For several immunosuppressive drugs, clinical development halted because they weren't sufficiently effective or more toxic. Areas covered: Current methods of monitoring Tac treatment, focusing on traditional therapeutic drug monitoring (TDM), controversies surrounding TDM, novel matrices, pharmacogenetic and pharmacodynamic monitoring are discussed. Expert opinion: Due to a narrow therapeutic index and large interpatient pharmacokinetic variability, TDM has been implemented for individualization of Tac dose to maintain drug efficacy and minimize the consequences of overexposure. The relationship between predose concentrations and the occurrence of rejection or toxicity is controversial. Acute cellular rejection also occurs when the Tac concentration is within the target range, suggesting that Tac whole blood concentrations don't necessarily correlate with pharmacological effect. Intracellular Tac, the unbound fraction of Tac or pharmacodynamic monitoring could be better biomarkers/tools for adequate Tac exposure - research into this has been promising. Traditional TDM, perhaps following pre-emptive genotyping for Tac-metabolizing enzymes, must suffice for a few years before these strategies can be implemented in clinical practice.

A Randomized Controlled Trial Comparing the Efficacy of Cyp3a5 Genotype-Based With Body-Weight-Based Tacrolimus Dosing After Living Donor Kidney Transplantation

Patients expressing the cytochrome P450 (CYP) 3A5 gene require a higher tacrolimus dose to achieve therapeutic exposure compared with nonexpressers. This randomized-controlled study investigated whether adaptation of the tacrolimus starting dose according to CYP3A5 genotype increases the proportion of kidney transplant recipients being within the target tacrolimus predose concentration range (10-15 ng/mL) at first steady-state. Two hundred forty living-donor, renal transplant recipients were assigned to either receive a standard, body-weight-based or a CYP3A5 genotype-based tacrolimus starting dose. At day 3, no difference in the proportion of patients having a tacrolimus exposure within the target range was observed between the standard-dose and genotype-based groups: 37.4% versus 35.6%, respectively; p = 0.79. The proportion of patients with a subtherapeutic (i.e. <10 ng/mL) or a supratherapeutic (i.e. >15 ng/mL) Tac predose concentration in the two groups was also not significantly different. The incidence of acute rejection was comparable between both groups (p = 0.82). Pharmacogenetic adaptation of the tacrolimus starting dose does not increase the number of patients having therapeutic tacrolimus exposure early after transplantation and does not lead to improved clinical outcome in a low immunological risk population.

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.

Multigene predictors of tacrolimus exposure in kidney transplant recipients

AIM

Determine the effect of the genetic variants beyond CYP3A5*3 on tacrolimus disposition.

PATIENTS & METHODS

We studied genetic correlates of tacrolimus trough concentrations with POR*28, CYP3A4*22 and ABCC2 haplotypes in a large, ethnically diverse kidney transplant cohort (n = 2008).

RESULTS

Subjects carrying one or more CYP3A5*1 alleles had lower tacrolimus trough concentrations (p = 9.2 × 10(-75)). The presence of one or two POR*28 alleles was associated with a 4.63% reduction in tacrolimus trough concentrations after adjusting for CYP3A5*1 and clinical factors (p = 0.037). In subset analyses, POR*28 was significant only in CYP3A5*3/*3 carriers (p = 0.03). The CYP3A4*22 variant and the ABBC2 haplotypes were not associated.

CONCLUSION

This study confirmed that CYP3A5*1 was associated with lower tacrolimus trough concentrations. POR*28 was associated with decreased tacrolimus trough concentrations although the effect was small possibly through enhanced CYP3A4 enzyme activity. CYP3A4*22 and ABCC2 haplotypes did not influence tacrolimus trough concentrations. Original submitted 19 December 2014; Revision submitted 2 April 2015.

Role of pharmacogenomics in dialysis and transplantation

PURPOSE OF REVIEW

Pharmacogenomics is the study of differences in drug response on the basis of individual genetic background. With rapidly advancing genomic technologies and decreased costs of genotyping, the field of pharmacogenomics continues to develop. Application to patients with kidney disease provides growing opportunities for improving drug therapy.

RECENT FINDINGS

Pharmacogenomics studies are lacking in patients with chronic kidney disease and dialysis, but are abundant in the kidney transplant field. A potentially clinically actionable genetic variant exists in the CYP3A5 gene, with the initial tacrolimus dose selection being optimized based on CYP3A5 genotype. Although many pharmacogenomics studies have focused on transplant immunosuppression pharmacokinetics, an expanding literature on pharmacodynamic outcomes, such as calcineurin inhibitor toxicity and new onset diabetes, is providing new information on patients at risk.

SUMMARY

Appropriately powered pharmacogenomics studies with well-defined phenotypes are needed to validate existing studies and unearth new findings in patients with kidney disease, especially the chronic kidney disease and dialysis population.

Improved prediction of tacrolimus concentrations early after kidney transplantation using theory-based pharmacokinetic modelling

Aims

The aim was to develop a theory-based population pharmacokinetic model of tacrolimus in adult kidney transplant recipients and to externally evaluate this model and two previous empirical models.

Methods

Data were obtained from 242 patients with 3100 tacrolimus whole blood concentrations. External evaluation was performed by examining model predictive performance using Bayesian forecasting.

Results

Pharmacokinetic disposition parameters were estimated based on tacrolimus plasma concentrations, predicted from whole blood concentrations, haematocrit and literature values for tacrolimus binding to red blood cells. Disposition parameters were allometrically scaled to fat free mass. Tacrolimus whole blood clearance/bioavailability standardized to haematocrit of 45% and fat free mass of 60 kg was estimated to be 16.1 l h⁻¹ [95% CI 12.6, 18.0 l h⁻¹]. Tacrolimus clearance was 30% higher (95% CI 13, 46%) and bioavailability 18% lower (95% CI 2, 29%) in CYP3A5 expressers compared with non-expressers. An E_max model described decreasing tacrolimus bioavailability with increasing prednisolone dose. The theory-based model was superior to the empirical models during external evaluation displaying a median prediction error of −1.2% (95% CI −3.0, 0.1%). Based on simulation, Bayesian forecasting led to 65% (95% CI 62, 68%) of patients achieving a tacrolimus average steady-state concentration within a suggested acceptable range.

Conclusion

A theory-based population pharmacokinetic model was superior to two empirical models for prediction of tacrolimus concentrations and seemed suitable for Bayesian prediction of tacrolimus doses early after kidney transplantation.

Gut microbiota and tacrolimus dosing in kidney transplantation

Tacrolimus dosing to establish therapeutic levels in recipients of organ transplants is a challenging task because of much interpatient and intrapatient variability in drug absorption, metabolism, and disposition. In view of the reported impact of gut microbial species on drug metabolism, we investigated the relationship between the gut microbiota and tacrolimus dosing requirements in this pilot study of adult kidney transplant recipients. Serial fecal specimens were collected during the first month of transplantation from 19 kidney transplant recipients who either required a 50% increase from initial tacrolimus dosing during the first month of transplantation (Dose Escalation Group, n=5) or did not require such an increase (Dose Stable Group, n=14). We characterized bacterial composition in the fecal specimens by deep sequencing of the PCR amplified 16S rRNA V4-V5 region and we investigated the hypothesis that gut microbial composition is associated with tacrolimus dosing requirements. Initial tacrolimus dosing was similar in the Dose Escalation Group and in the Stable Group (4.2±1.1 mg/day vs. 3.8±0.8 mg/day, respectively, P=0.61, two-way between-group ANOVA using contrasts) but became higher in the Dose Escalation Group than in the Dose Stable Group by the end of the first transplantation month (9.6±2.4 mg/day vs. 3.3±1.5 mg/day, respectively, P<0.001). Our systematic characterization of the gut microbial composition identified that fecal Faecalibacterium prausnitzii abundance in the first week of transplantation was 11.8% in the Dose Escalation Group and 0.8% in the Dose Stable Group (P=0.002, Wilcoxon Rank Sum test, P<0.05 after Benjamini-Hochberg correction for multiple hypotheses). Fecal Faecalibacterium prausnitzii abundance in the first week of transplantation was positively correlated with future tacrolimus dosing at 1 month (R=0.57, P=0.01) and had a coefficient±standard error of 1.0±0.6 (P=0.08) after multivariable linear regression. Our novel observations may help further explain inter-individual differences in tacrolimus dosing to achieve therapeutic levels.

CYP3A5 and CYP3A4, but not ABCB1 polymorphisms affect tacrolimus dose-adjusted trough concentrations in kidney transplant recipients

BACKGROUND

Tacrolimus (TAC), acting as a calcineurin inhibitor, is an immunosuppressant widely used after kidney transplantation. TAC requires blood concentration monitoring due to large interindividual variability in its pharmacokinetics and a narrow therapeutic index. Since genetic factors are considered responsible for a part of the observed pharmacokinetic variability, hereby SNPs within the CYP3A4, CYP3A5 and ABCB1 genes in kidney transplant patients of Polish Caucasian origin were investigated.

PATIENTS & METHODS

A total of 241 patients treated with TAC through the first year after kidney transplantation were genotyped for the presence of common SNPs: rs776746:A>G (CYP3A5*3), rs35599367:C>T (CYP3A4*22), rs2740574:A>G (CYP3A4*1B) and rs1045642:C>T (ABCB1 3435C>T) using TaqMan(®) assays.

RESULTS

CYP3A5 expressers received significantly higher weight-adjusted TAC doses, and were characterized by markedly lower C0 and dose adjusted C0 values in the course of treatment. CYP3A4*1B was significantly associated with TAC pharmacokinetics in univariate analysis. Impact of the CYP3A4*22 allele was significant only at particular time points, that is, 3 months after transplantation, with marginal significance 6 months after transplantation. The ABCB1 genotype did not influence TAC pharmacokinetics. Multivariate analysis of all the studied loci demonstrated that only the CYP3A5*1 (starting from month 1) and CYP3A4*22 alleles (at 3 and 6 months) were independent predictors of TAC dose-adjusted C0.

CONCLUSION

Our results confirm the impact of the CYP3A4*22 allele on TAC pharmacokinetics, as a second significant genetic factor (in addition to the CYP3A5*1 allele) influencing TAC dose-adjusted blood concentrations in kidney transplant recipients.

Clinical implementation of pharmacogenetics in kidney transplantation: calcineurin inhibitors in the starting blocks

Pharmacogenetics has generated many expectations for its potential to individualize therapy proactively and improve medical care. However, despite the huge amount of reported genetic associations with either pharmacokinetics or pharmacodynamics of drugs, the translation into patient care is still slow. In fact, strong evidence for a substantial clinical benefit of pharmacogenetic testing is still limited, with a few exceptions. In kidney transplantation, established pharmacogenetic discoveries are being investigated for application in the clinic to improve efficacy and to limit toxicity associated with the use of immunosuppressive drugs, especially the frequently used calcineurin inhibitors (CNIs) tacrolimus and ciclosporin. The purpose of the present review is to picture the current status of CNI pharmacogenetics and to discuss the most promising leads that have been followed so far.