Xi Luo1,2,3, Li-jun Zhu4, Ning-fang Cai5, Li-yun Zheng2, Ze-neng Cheng2. 1. School of Life Sciences, Central South University, Changsha 410083, China. 2. School of Pharmaceutical Sciences, Central South University, Changsha 410013, China. 3. The State Key Laboratory of Medical Genetics, Central South University, Changsha 410078, China. 4. Research Center of National Health Ministry on Transplantation Medicine Engineering and Technology, the 3rd Affiliated Hospital of Xiangya Medical Institute, Central South University, Changsha 410013, China. 5. Department of Pharmacy, Zhangzhou Municipal Hospital of Fujian Province, Zhangzhou 363000, China.
Abstract
AIM: To examine how the endogenous CYP3A4 phenotype and CYP3A5(*)3 genotype of Chinese renal transplant recipients influenced the dose-corrected trough concentration (C0/D) and weight-corrected daily dose (D/W) of tacrolimus. METHODS: A total of 101 medically stable kidney transplant recipients were enrolled, and their blood and urine samples were gathered. The endogenous CYP3A4 phenotype was assessed by the ratio of 6β-hydroxycortisol and 6β-hydroxycortisone to cortisol and cortisone in urine. CYP3A5(*)3 genotype was determined using PCR-RELP. RESULTS: In overall renal transplant recipients, a multiple regression analysis including the endogenous CYP3A4 phenotype, CYP3A5(*)3 genotype and post-operative period accounted for 60.1% of the variability in C0/D ratio; a regression equation consisting of the endogenous CYP3A4 phenotype, post-operative period, body mass index, CYP3A5(*)3 genotype, gender, total bilirubin and age explained 61.0% of the variability in D/W ratio. In CYP3A5(*)3/(*)3 subjects, a combination of the endogenous CYP3A4 phenotype, post-operative period and age was responsible for 65.3% of the variability in C0/D ratio; a predictive equation including the endogenous CYP3A4 phenotype, post-operative period, body mass index, gender and age explained 61.2% of the variability in the D/W ratio. Base on desired target range of tacrolimus trough concentrations, individual daily dosage regimen was calculated, and all the observed daily doses were within the predicted range. CONCLUSION: This study provides the equations to predict tacrolimus metabolism and dosage requirements based on the endogenous CYP3A4 phenotype, CYP3A5(*)3 genotype and other non-genetic variables.
AIM: To examine how the endogenous CYP3A4 phenotype and CYP3A5(*)3 genotype of Chinese renal transplant recipients influenced the dose-corrected trough concentration (C0/D) and weight-corrected daily dose (D/W) of tacrolimus. METHODS: A total of 101 medically stable kidney transplant recipients were enrolled, and their blood and urine samples were gathered. The endogenous CYP3A4 phenotype was assessed by the ratio of 6β-hydroxycortisol and 6β-hydroxycortisone to cortisol and cortisone in urine. CYP3A5(*)3 genotype was determined using PCR-RELP. RESULTS: In overall renal transplant recipients, a multiple regression analysis including the endogenous CYP3A4 phenotype, CYP3A5(*)3 genotype and post-operative period accounted for 60.1% of the variability in C0/D ratio; a regression equation consisting of the endogenous CYP3A4 phenotype, post-operative period, body mass index, CYP3A5(*)3 genotype, gender, total bilirubin and age explained 61.0% of the variability in D/W ratio. In CYP3A5(*)3/(*)3 subjects, a combination of the endogenous CYP3A4 phenotype, post-operative period and age was responsible for 65.3% of the variability in C0/D ratio; a predictive equation including the endogenous CYP3A4 phenotype, post-operative period, body mass index, gender and age explained 61.2% of the variability in the D/W ratio. Base on desired target range of tacrolimus trough concentrations, individual daily dosage regimen was calculated, and all the observed daily doses were within the predicted range. CONCLUSION: This study provides the equations to predict tacrolimus metabolism and dosage requirements based on the endogenous CYP3A4 phenotype, CYP3A5(*)3 genotype and other non-genetic variables.
Authors: P Kuehl; J Zhang; Y Lin; J Lamba; M Assem; J Schuetz; P B Watkins; A Daly; S A Wrighton; S D Hall; P Maurel; M Relling; C Brimer; K Yasuda; R Venkataramanan; S Strom; K Thummel; M S Boguski; E Schuetz Journal: Nat Genet Date: 2001-04 Impact factor: 38.330
Authors: I Cascorbi; T Gerloff; A Johne; C Meisel; S Hoffmeyer; M Schwab; E Schaeffeler; M Eichelbaum; U Brinkmann; I Roots Journal: Clin Pharmacol Ther Date: 2001-03 Impact factor: 6.875
Authors: David A Katz; David R Grimm; Steven C Cassar; Maria C Gentile; Xin Ye; Matthew J Rieser; Eric F Gordon; Jill E Polzin; Linda E Gustavson; Rita M Driscoll; Robert F O'dea; Laura A Williams; Stanley Bukofzer Journal: Clin Pharmacol Ther Date: 2004-06 Impact factor: 6.875
Authors: Moataz E Mohamed; David P Schladt; Weihua Guan; Baolin Wu; Jessica van Setten; Brendan J Keating; David Iklé; Rory P Remmel; Casey R Dorr; Roslyn B Mannon; Arthur J Matas; Ajay K Israni; William S Oetting; Pamala A Jacobson Journal: Am J Transplant Date: 2019-05-13 Impact factor: 8.086
Authors: Nemanja Rancic; Viktorija Dragojevic-Simic; Neven Vavic; Aleksandra Kovacevic; Zoran Segrt; Natasa Djordjevic Journal: Front Public Health Date: 2016-08-31
Authors: Joy Obayemi; Brendan Keating; Lauren Callans; Krista L Lentine; Mark A Schnitzler; Yasar Caliskan; Huiling Xiao; Vikas R Dharnidharka; Roslyn B Mannon; David A Axelrod Journal: Transplant Direct Date: 2022-09-15