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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Genet. | doi: 10.3389/fgene.2019.00871

The Impact of CYP3A4*22 on Tacrolimus Pharmacokinetics and Outcome in Clinical Practice at a Single Kidney Transplant Center

Emaad Abdel-Kahaar1, 2,  Stefan Winter3,  Elke Schaeffeler3, 4,  Elke Schaeffeler3, 4, Christoph Olbricht5,  Eberhard Wieland6, 7,  Matthias Schwab3, 8*,  Maria Shipkova6, 7 and  Simon U. Jaeger3, 4
  • 1Medizinische Fakultät, Universität Ulm, Germany
  • 2South Valley University, Egypt
  • 3Dr. Margarete Fischer-Bosch Institut für Klinische Pharmakologie (IKP), Germany
  • 4University of Tübingen, Germany
  • 5Department of Nephrology, Katharinenhospital, Germany
  • 6Central Institute for Clinical Chemistry and Laboratory Medicine, Katharinenhospital, Germany
  • 7SYNLAB, Germany
  • 8Departments of Clinical Pharmacology, Pharmacy and Biochemistry, University of Tübingen, Germany

Although there is evidence that the CYP3A4*22 variant should be considered in tacrolimus dosing in renal transplantation, its impact beyond tacrolimus dose requirements remains controversial.
Methods
In a cohort of 121 kidney transplant recipients, we analyzed the CYP3A4*1B, CYP3A4*22, CYP3A5*3 alleles and the ABCB1 variants 1236C>T, 2677G>T/A, 3435C>T for their impact on exposure and dose requirement. Relevant clinical outcome measures such as acute rejection (AR) within the first year after transplantation, delayed graft function (DGF) and renal function at discharge (eGFR, estimated glomerular filtration rate) were evaluated.
Results
Extensive metabolizer (EM, n=17, CYP3A4*1/*1 carriers with at least one CYP3A5*1 allele) showed significantly higher tacrolimus dose requirement (P=0.004) compared to both intermediate metabolizer (IM, n=93, CYP3A5*3/*3 plus CYP3A4*1/*1 or CYP3A4*22 carriers plus one CYP3A5*1 allele), and poor metabolizer (PM, n=11, CYP3A4*22 allele in combination with CYP3A5*3/*3) after onset of therapy. Significantly higher dose requirement was observed in CYP3A5 expressers (P=0.046) compared to non-expressers again at onset of therapy. Using the log additive genetic model, the area under the curve (AUC) for the total observation period up to 16 days was significantly associated with the CYP3A5*3 genotype (P=3.34x10-4) as well as with the IM or EM phenotype (P=1.54x10-4), even after adjustment for multiple testing. Heterozygous carriers for CYP3A4*22 showed significantly higher AUCs than the CYP3A4*1/*1 genotype in the second week post-transplantation (adjusted P=0.016). Regarding clinical outcomes, AR was significantly associated with HLA mismatch (≥3 alleles; OR=12.14, 95% CI 1.76, 525.21, P=0.019 after correction for multiple testing). Graft recipients from deceased donors showed higher DGF (OR 7.15, 95% CI 2.23, 30.46, adjusted P=0.0008) and a lower eGFR at discharge (p=0.0001). Tested CYP3A4 or CYP3A5 variants did not show any effects on clinical outcome parameters. ABCB1 variants did neither impact on pharmacokinetics nor on clinical endpoints.
Conclusion
At our transplantation center both CYP3A5*3 and to a lesser extent CYP3A4*22 affect tacrolimus pharmacokinetics early after onset of therapy with consequences for steady state treatment in routine clinical practice.

Keywords: CYP3A5, CYP3A4*22, Tacrolimus, Therapeutic drug monitoring, Renal Transplantation (RTx), ABCB1, Pharmacogenetics

Received: 02 Apr 2019; Accepted: 20 Aug 2019.

Copyright: © 2019 Abdel-Kahaar, Winter, Schaeffeler, Schaeffeler, Olbricht, Wieland, Schwab, Shipkova and Jaeger. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Prof. Matthias Schwab, Dr. Margarete Fischer-Bosch Institut für Klinische Pharmakologie (IKP), Stuttgart, 70376, Baden-Württemberg, Germany, matthias.schwab@ikp-stuttgart.de