Recipient ABCB1, donor and recipient CYP3A5 genotypes influence tacrolimus pharmacokinetics in liver transplant cases

Naushad, Shaik Mohammad; Pavani, Addepalli; Rupasree, Yedluri; Hussain, Tajamul; Alrokayan, Salman A.; Kutala, Vijay Kumar

doi:10.1016/j.pharep.2019.01.006

Cited by 11 publications

(2 citation statements)

References 29 publications

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“…For example, singlenucleotide polymorphisms in the gene CYP3A5 in liver transplant (LT) recipients and donors affect tacrolimus PK; in particular, donor genotype at CYP3A5 influences prognosis soon after liver transplantation. [4][5][6][7][8][9][10] The CYP3A5*1 encodes a functional cytochrome P450 enzyme, which can metabolize tacrolimus and reduce its bioavailability, whereas the CYP3A5*3 allele contains premature termination codons that give rise to truncated, nonfunctional enzyme. 4,11,12 For the same tacrolimus dose, individuals with a CYP3A5*3*3 genotype show a higher drug concentration in the blood than individuals with genotypes *1*1 or *1*3.…”

Section: Introductionmentioning

confidence: 99%

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

Zhang

Yang

et al. 2023

Ann Pharmacother

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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.

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Section: Introductionmentioning

confidence: 99%

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

Zhang

Yang

et al. 2023

Ann Pharmacother

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“…However, almost all clinical liver transplantation is allogeneic, and the genotypes of the recipients and their corresponding donors were different. The integration of donor and recipient CYP3A5 rs776746 genotypes could be a more appropriate approach for forecasting tacrolimus metabolism [ 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

The influence of recipient SLCO1B1 rs2291075 polymorphism on tacrolimus dose–corrected trough concentration in the early period after liver transplantation

Fang

Wang

et al. 2021

Eur J Clin Pharmacol

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Purpose To explore the relationship between rs2291075 polymorphism in SLCO1B1 gene, which encodes an influx transmembrane protein transporter, and tacrolimus dose–corrected trough concentration (C/D, ng ml−1 mg−1 kg−1) in the early period after liver transplantation. Methods CYP3A5 rs776746 and SLCO1B1 rs2291075 polymorphisms of 210 liver transplantation patients and their corresponding donor livers were assessed by PCR amplification and DNA sequencing. The influence of gene polymorphisms on C/D values of tacrolimus was analyzed. The early postoperative period after liver transplantation was divided into the convalescence phase (1–14 days) and stationary phase (15–28 days) according to the change of liver function and tacrolimus C/D values. Results The combined analysis of donor and recipient CYP3A5 rs776746 could distinguish the metabolic phenotype of tacrolimus into three groups: fast elimination (FE), intermediate elimination (IE), and slow elimination (SE), which was entitled the FIS classification system. Tacrolimus C/D ratios of recipient SLCO1B1 rs2291075 CT and TT carriers were very close and were significantly lower than those of recipient SLCO1B1 rs2291075 CC genotype carriers in convalescence phase (p = 0.0195) and in stationary phase (p = 0.0152). There were no statistically significant differences between tacrolimus C/D ratios of patients carried with SLCO1B1 rs2291075 CT, TT genotype donors, and those carried with SLCO1B1 rs2291075 CC genotype donors. A model consisting of tacrolimus daily dose, total bilirubin, FIS classification, and recipient SLCO1B1 rs2291075 could predict tacrolimus C/D ratios in the convalescence phase by multivariate analysis. However, recipient SLCO1B1 rs2291075 genotype failed to enter forecast model for C/D ratios in stationary phase. Recipient SLCO1B1 rs2291075 genotype had significant effect on tacrolimus C/D ratios in convalescence phase (p = 0.0300) and stationary phase (p = 0.0400) in subgroup, which excluded the interference come from donor and recipient CYP3A5 rs776746. Conclusion SLCO1B1 rs2291075 could be a novel genetic locus associated with tacrolimus metabolism. The combined analysis of donor and recipient CYP3A5 rs776746, recipient SLCO1B1 rs2291075 genotypes, could be helpful to guide the personalized administration of tacrolimus in early period after liver transplantation.

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The impact of IL-10 and CYP3A5 gene polymorphisms on dose-adjusted trough blood tacrolimus concentrations in early post-renal transplant recipients

et al. 2021

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Recipient ABCB1, donor and recipient CYP3A5 genotypes influence tacrolimus pharmacokinetics in liver transplant cases

Cited by 11 publications

References 29 publications

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

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

The influence of recipient SLCO1B1 rs2291075 polymorphism on tacrolimus dose–corrected trough concentration in the early period after liver transplantation

The impact of IL-10 and CYP3A5 gene polymorphisms on dose-adjusted trough blood tacrolimus concentrations in early post-renal transplant recipients

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