Literature DB >> 26067485

Multigene predictors of tacrolimus exposure in kidney transplant recipients.

Rebecca A Pulk1, David S Schladt2, William S Oetting1, Weihua Guan3, Ajay K Israni2, Arthur J Matas4, Rory P Remmel5, Pamala A Jacobson1.   

Abstract

AIM: Determine the effect of the genetic variants beyond CYP3A5*3 on tacrolimus disposition. PATIENTS &
METHODS: We studied genetic correlates of tacrolimus trough concentrations with POR*28, CYP3A4*22 and ABCC2 haplotypes in a large, ethnically diverse kidney transplant cohort (n = 2008).
RESULTS: Subjects carrying one or more CYP3A5*1 alleles had lower tacrolimus trough concentrations (p = 9.2 × 10(-75)). The presence of one or two POR*28 alleles was associated with a 4.63% reduction in tacrolimus trough concentrations after adjusting for CYP3A5*1 and clinical factors (p = 0.037). In subset analyses, POR*28 was significant only in CYP3A5*3/*3 carriers (p = 0.03). The CYP3A4*22 variant and the ABBC2 haplotypes were not associated.
CONCLUSION: This study confirmed that CYP3A5*1 was associated with lower tacrolimus trough concentrations. POR*28 was associated with decreased tacrolimus trough concentrations although the effect was small possibly through enhanced CYP3A4 enzyme activity. CYP3A4*22 and ABCC2 haplotypes did not influence tacrolimus trough concentrations. Original submitted 19 December 2014; Revision submitted 2 April 2015.

Entities:  

Keywords:  ABCC2; POR; calcineurin inhibitor; cytochrome P450 3A4 and 3A5; kidney transplant; pharmacogenomics; pharmacokinetics; tacrolimus

Mesh:

Substances:

Year:  2015        PMID: 26067485      PMCID: PMC4527535          DOI: 10.2217/pgs.15.42

Source DB:  PubMed          Journal:  Pharmacogenomics        ISSN: 1462-2416            Impact factor:   2.533


  49 in total

1.  Genetics of P450 oxidoreductase: sequence variation in 842 individuals of four ethnicities and activities of 15 missense mutations.

Authors:  Ningwu Huang; Vishal Agrawal; Kathleen M Giacomini; Walter L Miller
Journal:  Proc Natl Acad Sci U S A       Date:  2008-01-29       Impact factor: 11.205

2.  Dosing equation for tacrolimus using genetic variants and clinical factors.

Authors:  Chaitali Passey; Angela K Birnbaum; Richard C Brundage; William S Oetting; Ajay K Israni; Pamala A Jacobson
Journal:  Br J Clin Pharmacol       Date:  2011-12       Impact factor: 4.335

3.  The CYP3A4*22 allele affects the predictive value of a pharmacogenetic algorithm predicting tacrolimus predose concentrations.

Authors:  Laure Elens; Dennis A Hesselink; Ron H N van Schaik; Teun van Gelder
Journal:  Br J Clin Pharmacol       Date:  2013-06       Impact factor: 4.335

Review 4.  CYP3A4*22: promising newly identified CYP3A4 variant allele for personalizing pharmacotherapy.

Authors:  Laure Elens; Teun van Gelder; Dennis A Hesselink; Vincent Haufroid; Ron H N van Schaik
Journal:  Pharmacogenomics       Date:  2013-01       Impact factor: 2.533

5.  A published pharmacogenetic algorithm was poorly predictive of tacrolimus clearance in an independent cohort of renal transplant recipients.

Authors:  Oliver Boughton; Gabor Borgulya; Maurizio Cecconi; Salim Fredericks; Michelle Moreton-Clack; Iain A M MacPhee
Journal:  Br J Clin Pharmacol       Date:  2013-09       Impact factor: 4.335

6.  Rapid determination of enzyme activities of recombinant human cytochromes P450, human liver microsomes and hepatocytes.

Authors:  Anima Ghosal; Neil Hapangama; Yuan Yuan; Xiaowen Lu; Debra Horne; James E Patrick; Shmuel Zbaida
Journal:  Biopharm Drug Dispos       Date:  2003-12       Impact factor: 1.627

Review 7.  Pharmacogenetics of P450 oxidoreductase: implications in drug metabolism and therapy.

Authors:  Lei Hu; Wei Zhuo; Yi-Jing He; Hong-Hao Zhou; Lan Fan
Journal:  Pharmacogenet Genomics       Date:  2012-11       Impact factor: 2.089

8.  Pharmacogenomics of human liver cytochrome P450 oxidoreductase: multifactorial analysis and impact on microsomal drug oxidation.

Authors:  Ana M Gomes; Stefan Winter; Kathrin Klein; Miia Turpeinen; Elke Schaeffeler; Matthias Schwab; Ulrich M Zanger
Journal:  Pharmacogenomics       Date:  2009-04       Impact factor: 2.533

9.  CYP3A4 intron 6 C>T polymorphism (CYP3A4*22) is associated with reduced CYP3A4 protein level and function in human liver microsomes.

Authors:  Maho Okubo; Norie Murayama; Makiko Shimizu; Tsutomu Shimada; F Peter Guengerich; Hiroshi Yamazaki
Journal:  J Toxicol Sci       Date:  2013       Impact factor: 2.196

10.  Global pharmacogenomics: distribution of CYP3A5 polymorphisms and phenotypes in the Brazilian population.

Authors:  Guilherme Suarez-Kurtz; Daniela D Vargens; Ana Beatriz Santoro; Mara H Hutz; Maria Elisabete de Moraes; Sérgio D J Pena; Ândrea Ribeiro-dos-Santos; Marco A Romano-Silva; Claudio José Struchiner
Journal:  PLoS One       Date:  2014-01-10       Impact factor: 3.240

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  14 in total

1.  Analysis of 75 Candidate SNPs Associated With Acute Rejection in Kidney Transplant Recipients: Validation of rs2910164 in MicroRNA MIR146A.

Authors:  William S Oetting; David P Schladt; Casey R Dorr; Baolin Wu; Weihua Guan; Rory P Remmel; David Iklé; Roslyn B Mannon; Arthur J Matas; Ajay K Israni; Pamala A Jacobson
Journal:  Transplantation       Date:  2019-08       Impact factor: 4.939

2.  Dosage Optimization Based on Population Pharmacokinetic Analysis of Tacrolimus in Chinese Patients with Nephrotic Syndrome.

Authors:  Tong Lu; Xu Zhu; Shansen Xu; Mingming Zhao; Xueshi Huang; Zhanyou Wang; Limei Zhao
Journal:  Pharm Res       Date:  2019-02-04       Impact factor: 4.200

3.  Effect of ABCB1 diplotype on tacrolimus disposition in renal recipients depends on CYP3A5 and CYP3A4 genotype.

Authors:  T Vanhove; P Annaert; D Lambrechts; D R J Kuypers
Journal:  Pharmacogenomics J       Date:  2016-07-05       Impact factor: 3.550

4.  The POR rs1057868-rs2868177 GC-GT diplotype is associated with high tacrolimus concentrations in early post-renal transplant recipients.

Authors:  Shu Liu; Rong-Xin Chen; Jun Li; Yu Zhang; Xue-Ding Wang; Qian Fu; Ling-Yan Chen; Xiao-Man Liu; Hong-Bing Huang; Min Huang; Chang-Xi Wang; Jia-Li Li
Journal:  Acta Pharmacol Sin       Date:  2016-08-08       Impact factor: 6.150

5.  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

6.  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

Review 7.  Pharmacogenetics of Membrane Transporters of Tacrolimus in Solid Organ Transplantation.

Authors:  Camille Tron; Florian Lemaitre; Céline Verstuyft; Antoine Petitcollin; Marie-Clémence Verdier; Eric Bellissant
Journal:  Clin Pharmacokinet       Date:  2019-05       Impact factor: 6.447

8.  Tacrolimus trough and dose intra-patient variability and CYP3A5 genotype: Effects on acute rejection and graft failure in European American and African American kidney transplant recipients.

Authors:  Stephan R Seibert; David P Schladt; Baolin Wu; Weihua Guan; Casey Dorr; Rory P Remmel; Arthur J Matas; Roslyn B Mannon; Ajay K Israni; William S Oetting; Pamala A Jacobson
Journal:  Clin Transplant       Date:  2018-10-31       Impact factor: 2.863

Review 9.  Genetics of acute rejection after kidney transplantation.

Authors:  Casey R Dorr; William S Oetting; Pamala A Jacobson; Ajay K Israni
Journal:  Transpl Int       Date:  2017-11-08       Impact factor: 3.782

Review 10.  Population Pharmacokinetic Modelling and Bayesian Estimation of Tacrolimus Exposure: Is this Clinically Useful for Dosage Prediction Yet?

Authors:  Emily Brooks; Susan E Tett; Nicole M Isbel; Christine E Staatz
Journal:  Clin Pharmacokinet       Date:  2016-11       Impact factor: 6.447

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