Pharmacogenomics and Personalized Medicine (Feb 2024)

Pharmacogenomic Analysis of CYP3A5*3 and Tacrolimus Trough Concentrations in Vietnamese Renal Transplant Outcomes

  • Nguyen TVA,
  • Le BH,
  • Nguyen MT,
  • Le VT,
  • Tran VT,
  • Le DT,
  • Vu DAM,
  • Truong QK,
  • Le TH,
  • Nguyen HTL

Journal volume & issue
Vol. Volume 17
pp. 53 – 64

Abstract

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Thi Van Anh Nguyen,1,* Ba Hai Le,2,* Minh Thanh Nguyen,2,* Viet Thang Le,3,* Viet Tien Tran,4,* Dinh Tuan Le,5,* Duong Anh Minh Vu,2,* Quy Kien Truong,3,* Trong Hieu Le,2,* Huong Thi Lien Nguyen2,* 1Department of Pharmacy, 103 Military Hospital, Hanoi, Vietnam; 2Department of Clinical Pharmacy, Hanoi University of Pharmacy, Hanoi, Vietnam; 3Department of Nephrology and Dialysis, 103 Military Hospital, Hanoi, Vietnam; 4Department of Infectious Diseases, 103 Military Hospital, Hanoi, Vietnam; 5Department of Rheumatology and Endocrinology, 103 Military Hospital, Hanoi, Vietnam*These authors contributed equally to this workCorrespondence: Huong Thi Lien Nguyen, Department of Clinical Pharmacy, Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hoan Kiem, Hanoi, Vietnam, Tel +84904308406, Email [email protected]: CYP3A5 polymorphisms have been associated with variations in the pharmacokinetics of tacrolimus (Tac) in kidney transplant patients. Our study aims to quantify how the CYP3A5 genotype influences tacrolimus trough concentrations (C0) in a Vietnamese outpatient population by selecting an appropriate population pharmacokinetic model of Tac for our patients.Patients and Methods: The external dataset was obtained prospectively from 54 data of adult kidney transplant recipients treated at the 103 Military Hospital. All published Tac population pharmacokinetic models were systematically screened from PubMed and Scopus databases and were selected based on our patient’s available characteristics. Mean absolute prediction error (MAPE), mean prediction error, and goodness-of-fit plots were used to identify the appropriate model for finding the formula that identifies the influence of CYP3A5 genotype on the pharmacokinetic data of Vietnamese patients.Results: The model of Zhu et al had a good predictive ability with MAPE of 19.29%. The influence of CYP3A5 genotype on tacrolimus clearance was expressed by the following formulas: . The simulation result showed that Tac C0 was significantly higher in patients not expressing CYP3A5 (p< 0.001).Conclusion: The incorporation of the CYP3A5 phenotype into Zhu’s structural model has significantly enhanced our ability to predict Tacrolimus trough levels in the Vietnamese population. This study’s results underscore the valuable role of CYP3A5 phenotype in optimizing the forecast of Tac concentrations, offering a promising avenue to assist health-care practitioners in their clinical decision-making and ultimately advance patient care outcomes.Keywords: tacrolimus, population pharmacokinetic, CYP3A5, Vietnam

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