Impact of CYP3A4/5 and ABCB1 polymorphisms on tacrolimus exposure and response in pediatric primary nephrotic syndrome

Effect of Age, Comedications, and CYP3A4/5 Polymorphisms on Perampanel Exposure in Chinese Pediatric Patients With Epilepsy

Perampanel (PER) is a new type of antiseizure medication used for partial or generalized seizures. However, the plasma concentration shows obvious individual variability in children. The present study aims to ascertain the effect of age, comedications, and cytochrome P450 (CYP) 3A4/5 polymorphisms on PER exposure in Chinese pediatric patients with epilepsy. Clinical data were retrospectively collected in a tertiary children's hospital medical records system from January 2021 to December 2022. The influence factors on the daily dose, plasma concentration, and concentration-to-dose ratio (CDR) of PER were investigated. A total of 135 pediatric patients with 178 blood samples were involved. With a median daily dose of 4.0 mg (interquartile range, 3.0-5.0 mg), the median plasma concentration was 409.4 ng/mL (interquartile range, 251.7-639.4 ng/mL). The CDR in patients aged less than 4 years was significantly decreased by 48.0% and 39.1% compared with those aged 4-11 years and 12 years or older, respectively. Enzyme inducers significantly decreased the CDR of PER by 34.5%, while valproic acid showed an increase of 71.7%. In addition, genotype CYP3A5*3/*3 carriers presented a significant increase of 21.5% compared to the CYP3A5*1/*3 expresser. No correlations were observed between the CDR and CYP3A4∗1G polymorphism. PER showed high variations in individual plasma concentrations. Age younger than 4 years, comedication with enzyme inducers or valproic acid, and possession of the CYP3A5*3 genotype potentially predicted PER exposure in pediatric patients with epilepsy.

Meta-analysis of the effects of CYP3A5*3 gene polymorphisms on tacrolimus blood concentration and effectiveness in Chinese patients with membranous nephropathy

Objective

The study aimed to systematically evaluate the relationship between CYP3A5*3 gene polymorphisms and the blood concentration and effectiveness of tacrolimus (TAC) in patients with membranous nephropathy (MN).

Methods

PubMed, Cochrane Library, Embase, Web of Science, China Biomedical, China National Knowledge Infrastructure, Wanfang, Vipshop, ReadShow, Clinical Trials Registry, and other databases were searched. Studies on the relationship between CYP3A5*3 gene polymorphism and TAC blood concentration in MN patients were collected, and meta-analysis was performed using Stata 16 software.

Results

A total of eight publications were included in the study, including 498 MN patients. CYP3A5*3 gene polymorphisms are associated with tacrolimus blood levels in patients with MN. The results of the relationship between CYP3A5*3 genotype polymorphisms and tacrolimus blood trough concentrations of the AA + AG genotype were lower than those of the GG genotype at ≤1 month [WMD = -2.08, 95% CI (-2.57, -1.59), p < 0.001] and 1-6 months [WMD = -0.63, 95% CI (-0.98, -0.27), p < 0.001]; however, they were not statistically significant at ≥6 months (p = 0.211). Furthermore, the subgroup analysis revealed that the dose-adjusted concentration of tacrolimus (C0/D) of the AA + AG genotype was lower than that of the GG genotype at ≤1 month [SMD = -1.93, 95% CI (-2.79, -1.08), p < 0.001], 1-6 months [SMD = -2.25, 95% CI (-2.71, -1.79), p < 0.001], and ≥6 months [SMD = -2.36, 95% CI (-2.86, -1.86), p < 0.001]. In addition, there was no statistically significant difference in effectiveness between the two groups at 3, 6, and 12 months of TAC administration (p > 0.05).

Conclusion

Serum TAC concentrations in MN patients were correlated with CYP3A5*3 genotype polymorphisms. Detection of the CYP3A5*3 genotype before the administration of TAC may provide some clinical value for optimizing the treatment of MN patients.

Systematic Review Registration

https://inplasy.com/, identifier [INPLASY202430083].

Dosage optimization of tacrolimus based on the glucocorticoid dose and pharmacogenetics in adult patients with systemic lupus erythematosus

BACKGROUND

The purpose of the study was to develop a genotype-incorporated population pharmacokinetic (PPK) model of tacrolimus (TAC) in adults with systemic lupus erythematosus (SLE) to investigate the factors influencing TAC pharmacokinetics and to develop an individualized dosing regimen based on the model. In addition, a non-genotype-incorporated model was also established to assess its predictive performance compared to the genotype-incorporated model.

METHODS

A total of 365 trough concentrations from 133 adult SLE patients treated with TAC were collected to develop a genotype-incorporated PPK model and a non-genotype-incorporated PPK model of TAC using a nonlinear mixed-effects model (NONMEM). External validation of the two models was performed using data from an additional 29 patients. Goodness-of-fit diagnostic plots, bootstrap method, and normalized predictive distribution error test were used to validate the predictive performance and stability of the final models. The goodness-of-fit of the two final models was compared using the Akaike information criterion (AIC). The dosing regimen was optimized using Monte Carlo simulations based on the developed optimal model.

RESULTS

The typical value of the apparent clearance (CL/F) of TAC estimated in the final genotype-incorporated model was 14.3 L h-1 with inter-individual variability of 27.6%. CYP3A5 polymorphism and coadministered medication were significant factors affecting TAC-CL/F. CYP3A5 rs776746 GG genotype carriers had only 77.3% of the TAC-CL/F of AA or AG genotype carriers. Omeprazole reduced TAC-CL/F by 3.7 L h-1 when combined with TAC, while TAC-CL/F increased nonlinearly as glucocorticoid dose increased. Similar findings were demonstrated in the non-genotype-incorporated PPK model. Comparing these two models, the genotype-incorporated PPK model was superior to the non-genotype-incorporated PPK model (AIC = 643.19 vs. 657.425). Monte Carlo simulation based on the genotype-incorporated PPK model indicated that CYP3A5 rs776746 AA or AG genotype carriers required a 1/2-1 fold higher dose of TAC than GG genotype carriers to achieve the target concentration. And as the daily dose of prednisone increases, the dose of TAC required to reach the target concentration increases appropriately.

CONCLUSIONS

We developed the first pharmacogenetic-based PPK model of TAC in adult patients with SLE and proposed a dosing regimen based on glucocorticoid dose and CYP3A5 genotype according to the model, which could facilitate individualized dosing for TAC.

Population pharmacokinetic analyses of tacrolimus in non-transplant patients: a systematic review

BACKGROUND AND OBJECTIVES

Tacrolimus (TAC) has been increasingly used in patients with non-transplant settings. Because of its large between-subject variability, several population pharmacokinetic (PPK) studies have been performed to facilitate individualized therapy. This review summarized published PPK models of TAC in non-transplant patients, aiming to clarify factors affecting PKs of TAC and identify the knowledge gap that may require further research.

METHODS

The PubMed, Embase databases, and Cochrane Library, as well as related references, were searched from the time of inception of the databases to February 2023, to identify TAC population pharmacokinetic studies modeled in non-transplant patients using a non-linear mixed-effects modeling approach.

RESULTS

Sixteen studies, all from Asian countries (China and Korea), were included in this study. Of these studies, eleven and four were carried out in pediatric and adult patients, respectively. One-compartment models were the commonly used structural models for TAC. The apparent clearance (CL/F) of TAC ranged from 2.05 to 30.9 L·h^-1 (median of 14.9 L·h^-1). Coadministered medication, genetic factors, and weight were the most common covariates affecting TAC-CL/F, and variability in the apparent volume of distribution (V/F) was largely explained by weight. Coadministration with Wuzhi capsules reduced CL/F by about 19 to 43%. For patients with CYP3A5*1*1 and *1*3 genotypes, the CL/F was 39-149% higher CL/F than patients with CYP3A5*1*1.

CONCLUSION

The optimal TAC dosage should be adjusted based on the patient's co-administration, body weight, and genetic information (especially CYP3A5 genotype). Further studies are needed to assess the generalizability of the published models to other ethnic groups. Moreover, external validation should be frequently performed to improve the clinical practicality of the models.

Tacrolimus in the treatment of childhood nephrotic syndrome: Machine learning detects novel biomarkers and predicts efficacy

STUDY OBJECTIVE

The pharmacokinetics and pharmacodynamics of tacrolimus (TAC) vary greatly among individuals, hindering its precise utilization. Moreover, effective models for the early prediction of TAC efficacy in patients with nephrotic syndrome (NS) are lacking. We aimed to identify key factors affecting TAC efficacy and develop efficacy prediction models for childhood NS using machine learning algorithms.

DESIGN

This was an observational cohort study of patients with pediatric refractory NS.

SETTING

Guangzhou Women and Children's Medical Center between June 2013 and December 2018.

PATIENTS

203 patients with pediatric refractory NS were used for model generation and 35 patients were used for model validation.

INTERVENTION

All patients regularly received double immunosuppressive therapy comprising TAC and low-dose prednisone or methylprednisolone. In this observational cohort study of 203 pediatric patients with refractory NS, clinical and genetic variables, including single-nucleotide polymorphism (SNPs), were identified. TAC efficacy was evaluated 3 months after administration according to two different evaluation criteria: response or non-response (Group 1) and complete remission, partial remission, or non-remission (Group 2).

MEASUREMENTS

Logistic regression, extremely random trees, gradient boosting decision trees, random forest, and extreme gradient boosting algorithms were used to develop and validate the models. Prediction models were validated among a cohort of 35 patients with NS.

MAIN RESULTS

The random forest models performed best in both groups, and the area under the receiver operating characteristics curve of these two models was 80.7% (Group 1) and 80.3% (Group 2). These prediction models included urine erythrocyte count before administration, steroid types, and eight SNPs (ITGB4 rs2290460, TRPC6 rs3824934, CTGF rs9399005, IL13 rs20541, NFKBIA rs8904, NFKBIA rs8016947, MAP3K11 rs7946115, and SMARCAL1 rs11886806).

CONCLUSIONS

Two pre-administration models with good predictive performance for TAC response of patients with NS were developed and validated using machine learning algorithms. These accurate models could assist clinicians in predicting TAC efficacy in pediatric patients with NS before utilization to avoid treatment failure or adverse effects.

Population Pharmacokinetic Modelling for Nifedipine to Evaluate the Effect of Parathyroid Hormone on CYP3A in Patients with Chronic Kidney Disease

Purpose

Parathyroid hormone (PTH) can induce the downregulation of CYP3A in chronic kidney disease (CKD). Nevertheless, the effect of PTH on CYP3A-mediated clearance pathways from a clinical perspective remains unclear.

Methods

This study employed population pharmacokinetic (PopPK) modeling to delineate potential changes in CYP3A activity in patients with CKD. Pharmacokinetic data for nifedipine, a typical CYP3A substrate, as well as covariate information, were prospectively collected from 157 patients with a total of 612 concentrations. PopPK data analysis was performed using a nonlinear mixed-effects model.

Results

The pharmacokinetics of nifedipine were optimally described according to a one-compartment model with zero-order absorption and first-order elimination. The estimated population parameters (and interindividual variability) were apparent clearance (CL/F) 49.61 L/h (58.33%) and apparent volume of distribution (V/F) 2300.26 L (45.62%), and the PTH level negatively correlated with CL/F. In comparison with the reference level, it was observed that the dosage of nifedipine should be reduced with the maximum boundary value of PTH, after a Monte Carlo simulation.

Conclusion

This study provides insight into the effects of PTH on CYP3A-mediated clearance pathways. Moreover, PTH could be used as a guide for the appropriate administration of CYP3A eliminated drugs in patients with CKD.

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

BACKGROUND

Tacrolimus is the most commonly used immunosuppressive drug in solid organ transplantation. After administering a conventional twice-daily dose of tacrolimus, peak levels were achieved within the first 1.5 to 2 hours. A group of patients showed different early absorption phase of tacrolimus after kidney transplantation.

METHODS

Trough(C₀) and 1.5-hour blood levels (C_1.5) of tacrolimus were measured in 95 kidney transplantation recipients. Patients with a C_1.5/C₀ < 1.5 and > 1.5 were defined as those having flat pattern peaks and as controls, respectively. Transplantation outcomes were compared between the groups. Whole exome sequencing was performed to investigate the genetic susceptibility to flat pattern peaks.

RESULTS

Twenty-eight patients showed flat pattern peaks. The mean C_1.5/C₀ values were 1.13 ± 0.22 and 3.78 ± 1.25 in the flat pattern peak and control groups, respectively. In multivariate analysis, flat pattern peak was an independent risk factor for biopsy-proven acute rejection (BPAR) and/or borderline change (P = 0.014). Patients having flat pattern peaks showed significantly lower post-transplant 36-month estimated glomerular filtration rate (P = 0.001). Two single nucleotide variants in ABCB1 genes, rs1922242 and rs2235035, were associated with flat pattern peaks (P = 0.019 and P = 0.027, respectively).

CONCLUSION

Both of C_1.5 and C₀ should be measured to distinguish the patients showing unique initial absorption. A C_1.5/C₀ ratio lower than 1.5 was associated with an increased risk of BPAR and/or borderline change. Single nucleotide variants s in ABCB1 gene might influence the flat pattern peaks of tacrolimus absorption.

Impact of Sampling Time Variability on Tacrolimus Dosage Regimen in Pediatric Primary Nephrotic Syndrome: Single-Center, Prospective, Observational Study

Background: Tacrolimus (TAC) is an important immunosuppressant for children with primary nephrotic syndrome (PNS). The relationship between sampling time variability in TAC therapeutic drug monitoring and dosage regimen in such children is unknown. Methods: In this single-center, prospective, observational study, we evaluated the sampling time variability, concentration error (CE), relative CE (RCE), and the impact of the sampling time on TAC dosage regimens in 112 PNS children with 188 blood samples. Nominal concentration (C_nom) at 12-h after last TAC dose was simulated based on observed concentration (C_obs) via previously published pharmacokinetic models, then CE and RCE were calculated. Inappropriate dosing adjustments resulting from deviated sampling time were evaluated based on a target C_nom of 5-10 ng/ml. Results: We found that 32 and 68% of samples were respectively collected early (2-180 min) and delayed (4-315 min). Furthermore, 24, 22, 22, and 32% of blood samples were drawn within deviations of ≤0.5, 0.5-1, 1-2, and >2 h, respectively, and 0.3 ng/ml of CE and 6% RCE per hour of deviation occurred. Within a deviation of >2 h, 25% of C_obs might result in inappropriate dosing adjustments. Early and delayed sampling might result in inappropriate dose holding or unnecessary dose increments, respectively, in patients with C_obs ∼ 5 ng/ml. Conclusions: Variable sampling time might lead to inappropriate dosing adjustment in a minority of children with PNS, particularly those with TAC C_obs ∼ 5 ng/ml collected with a deviation of >2 h.

Long-term, low-dose macrolide antibiotic treatment in pediatric chronic airway diseases

Macrolide antibiotics are one of the most commonly used broad-spectrum antibiotics. They have an inhibitory effect on a variety of respiratory pathogens; besides, they have non-anti-infective effects, including anti-inflammatory, regulating airway secretion, immune regulation, and other effects. A growing number of studies have shown that the non-anti-infective effects of macrolides have important and potential value in the treatment of pediatric chronic airway diseases; the therapy was described as "long-term, low-dose usage"; unfortunately, there is no guideline or consensus that applies to children. To better carry out the mechanism and clinical research of non-anti-infective effect and promote its rational use in children, the authors summarize the evidence of the usage of long-term, low-dose macrolide antibiotic therapy (LLMAT) in the treatment of chronic airway diseases in children and the progress in recent years. IMPACT: This review summarizes the evidence (mostly in recent 5 years) of the usage of long-term, low-dose macrolide antibiotic therapy in the treatment of chronic airway diseases. The recent studies and guidelines support and enrich the point that long-term, low-dose macrolide antibiotic therapy has potential benefit for children with severe asthma, CF, non-CF bronchiectasis, and BO, which provides clinical references and is of clinical interest. Long-term, low-dose macrolide antibiotic therapy has good safety, and no serious events have been reported; however, potential cardiac side effects and macrolide resistance should be clinically noted.

Effect of CYP3A5 and CYP3A4 Genetic Variants on Fentanyl Pharmacokinetics in a Pediatric Population

Fentanyl is an anesthetic/analgesic commonly used in surgical and recovery settings. CYP3A4 and CYP3A5 encode enzymes, which metabolize fentanyl; genetic variants in these genes impact fentanyl pharmacokinetics in adults. Pharmacokinetic (PK) studies are difficult to replicate in children due to the burden of additional blood taken solely for research purposes. The aim of this study is to test the effect of CYP3A5 and CYP3A4 genetic variants on fentanyl PKs in children using opportunistically collected samples. Fentanyl concentrations were measured from remnant blood specimens and dosing data were extracted from electronic health records. Variant data defining CYP3A4*1G and CYP3A5*3 and *6 alleles were available from prior genotyping; alleles with no variant were defined as *1. The study cohort included 434 individuals (median age 9 months, 52% male subjects) and 1,937 fentanyl concentrations were available. A two-compartment model was selected as the base model, and the final covariate model included age, weight, and surgical severity score. Clearance was significantly associated with either CYP3A5*3 or CYP3A5*6 alleles, but not the CYP3A4*1G allele. A genotype of CYP3A5*1/*3 or CYP3A5*1/*6 (i.e., intermediate metabolizer status) was associated with a 0.84-fold (95% confidence interval (CI): 0.71-1.00) reduction in clearance vs. CYP3A5*1/*1 (i.e., normal metabolizer status). CYP3A5*3/*3, CYP3A5*3/*6, or CYP3A5*6/*6 (i.e., poor metabolizer status) was associated with a 0.76-fold (95% CI: 0.58-0.99) reduction in clearance. In the final model, expected clearance was 8.9 and 6.8 L/hour for a normal and poor metabolizer, respectively, with median population covariates (9 months old, 7.7 kg, low surgical severity).

Predicting Blood Concentration of Tacrolimus in Patients With Autoimmune Diseases Using Machine Learning Techniques Based on Real-World Evidence

Tacrolimus is a widely used immunosuppressive drug in patients with autoimmune diseases. It has a narrow therapeutic window, thus requiring therapeutic drug monitoring (TDM) to guide the clinical regimen. This study included 193 cases of tacrolimus TDM data in patients with autoimmune diseases at Southern Medical University Nanfang Hospital from June 7, 2018, to December 31, 2020. The study identified nine important variables for tacrolimus concentration using sequential forward selection, including height, tacrolimus daily dose, other immunosuppressants, low-density lipoprotein cholesterol, mean corpuscular volume, mean corpuscular hemoglobin, white blood cell count, direct bilirubin, and hematocrit. The prediction abilities of 14 models based on regression analysis or machine learning algorithms were compared. Ultimately, a prediction model of tacrolimus concentration was established through eXtreme Gradient Boosting (XGBoost) algorithm with the best predictive ability (R² = 0.54, mean absolute error = 0.25, and root mean square error = 0.33). Then, SHapley Additive exPlanations was used to visually interpret the variable’s impacts on tacrolimus concentration. In conclusion, the XGBoost model for predicting blood concentration of tacrolimus on the basis of real-world evidence has good predictive performance, providing guidance for the adjustment of regimen in clinical practice.

Population pharmacokinetics and pharmacogenomics of tacrolimus in Chinese children receiving a liver transplant: initial dose recommendation

BACKGROUND

In order to improve the precision of treatment with tacrolimus in Chinese patients undergoing pediatric liver transplantation, the optimum initial dose of tacrolimus was determined based on population pharmacokinetics and pharmacogenomics.

METHODS

Demographic data, clinical parameters, drug combinations and pharmacogenomics were integrated to build a population pharmacokinetic model using NONMEM. Additionally, Monte Carlo simulations were used to optimize the recommended initial dose.

RESULTS

Weight, patient cytochrome 450 3A (CYP3A)5 genotype, and co-administration with wuzhi-capsule (WZ) were incorporated into the final model. For children with a CYP3A5*3/*3 genotype not co-administered WZ, 0.10 mg/kg/day split into two doses was recommended for patients weighing 5-17 kg, and 0.05 mg/kg/day split into two doses was recommended for patients weighing 17-60 kg. For children with a CYP3A5*1 allele not co-administered WZ, 0.25 mg/kg/day for patients weighing 5-10 kg, 0.20 mg/kg/day for patients weighing 10-17 kg, 0.15 mg/kg/day for patients weighing 17-36 kg, and 0.10 mg/kg/day for patients weighing 36-60 kg; all split into two doses was recommended. For children with a CYP3A5*3/*3 genotype co-administered WZ, 0.10 mg/kg/day for patients weighing 5-11 kg, and 0.05 mg/kg/day for patients weighing 11-60 kg; both split into two doses was recommended. For children with a CYP3A5*1 allele who were co-administered WZ, 0.20 mg/kg/day for patients weighing 5-10 kg, 0.15 mg/kg/day for patients weighing 10-22 kg, and 0.10 mg/kg/day for patients weighing 22-60 kg all split into two doses was recommended.

CONCLUSIONS

The optimal initial dose of tacrolimus was determined based on population pharmacokinetics and pharmacogenomics in Chinese patients undergoing pediatric liver transplantation.

Marked decrease of tacrolimus blood concentration caused by compound Chinese herbal granules in a patient with refractory nephrotic syndrome

WHAT IS KNOWN AND OBJECTIVE

The blood concentration of tacrolimus can be affected by co-administrated drugs. The objective is to draw more attention to herb-drug interactions in China, where herbal medicines are commonly used.

CASE DESCRIPTION

The blood concentration of tacrolimus in a girl with refractory nephrotic syndrome decreased nearly a half despite no change in dose. Nebulizer therapy, cyclophosphamide and a compound Chinese herbal medicine were the only additional treatments than usual.

WHAT IS NEW AND CONCLUSION

The most possible cause of the decrease in tacrolimus concentration was the administration of Radix Astragali among compound Chinese herbal medicine granules.

Diltiazem on tacrolimus exposure and dose sparing in Chinese pediatric primary nephrotic syndrome: impact of CYP3A4, CYP3A5, ABCB1, and SLCO1B3 polymorphisms

PURPOSE

To evaluate the role of diltiazem on tacrolimus sparing in pediatric primary nephrotic syndrome (PNS) and its relation to CYP3A4, CYP3A5, ABCB1, and SLCO1B3 polymorphisms.

METHODS

The PNS children treated with tacrolimus and with steady-state trough concentration (C₀) were retrospectively collected. The impacts of diltiazem on tacrolimus dose-adjusted C₀ (C₀/D), target concentration achievement, and required dose were evaluated. Meanwhile, the relationship between the polymorphisms (including CYP3A4*1G, CYP3A5*3, ABCB1-C3435T, and SCLO1B3) and dose-sparing effect were investigated.

RESULTS

A total of 71 children with 535 concentrations, including 16 children with concomitant diltiazem, were involved. Significantly increased C₀/D (94.0 vs 83.8 ng/mL per mg/kg, p = 0.038) and lower required daily dose of tacrolimus (0.056 vs 0.064 mg/kg, p = 0.003) were observed in patients co-administered with diltiazem. Subpopulation carrying CYP3A4*1G, CYP3A5*1, ABCB1-3435TT, or SLCO1B3-699AA was presented with enhanced increment in tacrolimus C₀/D by 38.8-102.9%.

CONCLUSION

Moderate effect of diltiazem on tacrolimus sparing, which might relate to the polymorphisms of CYP3A4, CYP3A5, ABCB1, and SLCO1B3, was documented.