Literature DB >> 23175667

Increased hospital stay and allograft dysfunction in renal transplant recipients with Cyp2c19 AA variant in SNP rs4244285.

Virginia Bosó1, María José Herrero, Sergio Bea, María Galiana, Patricia Marrero, María Remedios Marqués, Julio Hernández, Jaime Sánchez-Plumed, José Luis Poveda, Salvador F Aliño.   

Abstract

Pharmacogenetics correlates certain genetic variants, such as single nucleotide polymorphisms (SNPs), with blood drug levels, efficacy, and adverse effects of the treatment. Tacrolimus is mainly metabolized via CYP3A4/5, whereas CYP2C19 and CYP3A4/5 are responsible for omeprazole metabolism. Omeprazole inhibits tacrolimus metabolism via CYP3A5 in patients carrying variant alleles of CYP2C19, increasing tacrolimus blood concentrations. Seventy-five renal transplant recipients treated with tacrolimus and concomitant omeprazole were genotyped in a panel of 37 SNPs with use of Sequenom MassArray. The patients with CYP2C19*2/*2 genotype (n = 4) showed a median posttransplantation hospital stay of 27.5 days (95% confidence interval [CI], 23-39 days), compared with 12 days (95% CI, 10-15 days) in patients with CYP2C19*1/*1 or CYP2C19*1/*2 (n = 71; P = 0.016, Kruskal-Wallis test).The difference in hospital stay was directly correlated with an increase in tacrolimus levels (C(min)/[dose/weight]) during the first week after trasplantation (in 59 patients with data on levels; P = 0.021, Kruskal-Wallis), excluding the patients with atypical metabolisms due to CYP3A5*1/*3 or CYP3A5*1/*1 genotype. Recipients with CYP2C19*2/*2 genotype also showed allograft delayed function (acute tubular necrosis in 3 patients). Genotyping of CYP3A5 and CYP2C19 in renal transplantation should be considered to be of interest when treating with tacrolimus and omeprazole, because CYP2C19*2/*2 variant indirectly elicits an increase of tacrolimus blood levels and, in our study population, the adverse effects described.

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Year:  2012        PMID: 23175667     DOI: 10.1124/dmd.112.047977

Source DB:  PubMed          Journal:  Drug Metab Dispos        ISSN: 0090-9556            Impact factor:   3.922


  7 in total

1.  Genome-wide association study identifies the common variants in CYP3A4 and CYP3A5 responsible for variation in tacrolimus trough concentration in Caucasian kidney transplant recipients.

Authors:  W S Oetting; B Wu; D P Schladt; W Guan; R P Remmel; R B Mannon; A J Matas; A K Israni; P A Jacobson
Journal:  Pharmacogenomics J       Date:  2017-11-21       Impact factor: 3.550

2.  Attempted validation of 44 reported SNPs associated with tacrolimus troughs in a cohort of kidney allograft recipients.

Authors:  William S Oetting; Baolin Wu; David P Schladt; Weihua Guan; Rory P Remmel; Casey Dorr; Roslyn B Mannon; Arthur J Matas; Ajay K Israni; Pamala A Jacobson
Journal:  Pharmacogenomics       Date:  2018-01-10       Impact factor: 2.533

3.  The impact of cytochrome P450 3A5 genotype on early tacrolimus metabolism and clinical outcomes in lung transplant recipients.

Authors:  Wenwen Du; Xiaoxing Wang; Dan Zhang; Wenqian Chen; Xianglin Zhang; Pengmei Li
Journal:  Int J Clin Pharm       Date:  2021-12-03

4.  Utilization of an EMR-biorepository to identify the genetic predictors of calcineurin-inhibitor toxicity in heart transplant recipients.

Authors:  Matthew Oetjens; William S Bush; Kelly A Birdwell; Holli H Dilks; Erica A Bowton; Joshua C Denny; Russell A Wilke; Dan M Roden; Dana C Crawford
Journal:  Pac Symp Biocomput       Date:  2014

5.  CYP3A5 Genotype-Dependent Drug-Drug Interaction Between Tacrolimus and Nifedipine in Chinese Renal Transplant Patients.

Authors:  Yilei Yang; Xin Huang; Yinping Shi; Rui Yang; Haiyan Shi; Xinmei Yang; Guoxiang Hao; Yi Zheng; Jianning Wang; Lequn Su; Yan Li; Wei Zhao
Journal:  Front Pharmacol       Date:  2021-07-05       Impact factor: 5.810

6.  Impact of Single Nucleotide Polymorphisms (SNPs) on Immunosuppressive Therapy in Lung Transplantation.

Authors:  Jesus Ruiz; María José Herrero; Virginia Bosó; Juan Eduardo Megías; David Hervás; Jose Luis Poveda; Juan Escrivá; Amparo Pastor; Amparo Solé; Salvador Francisco Aliño
Journal:  Int J Mol Sci       Date:  2015-08-25       Impact factor: 5.923

7.  A Machine Learning-Based Identification of Genes Affecting the Pharmacokinetics of Tacrolimus Using the DMETTM Plus Platform.

Authors:  Jeong-An Gim; Yonghan Kwon; Hyun A Lee; Kyeong-Ryoon Lee; Soohyun Kim; Yoonjung Choi; Yu Kyong Kim; Howard Lee
Journal:  Int J Mol Sci       Date:  2020-04-04       Impact factor: 5.923

  7 in total

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