Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Pharmacogenetics and immunosuppressive drugs in solid organ transplantation

Nature Reviews Nephrology volume 10, pages 725–731 (2014)Cite this article

Subjects

Key Points

  • The prediction made 15 years ago that pharmacogenetics would revolutionize pharmacotherapy has not materialized

  • For several immunosuppressive drugs, studies show significant associations between polymorphisms in genes encoding metabolizing enzymes and pharmacokinetic data

  • Studies showing a clinical benefit if immunosuppressive drug dose is based on pharmacogenetic data are lacking

  • Efficient therapeutic drug monitoring can rapidly correct for deviations in drug exposure

  • Treatment algorithms that include polymorphisms in genes encoding pharmacodynamic parameters, drug transporter proteins, and predictors of toxicity will provide additional benefit

Abstract

The transplantation literature includes numerous papers that report associations between polymorphisms in genes encoding metabolizing enzymes and drug transporters, and pharmacokinetic data on immunosuppressive drugs. Most of these studies are retrospective in design, and although a substantial number report significant associations, pharmacogenetic tests are hardly used in clinical practice. One of the reasons for this poor implementation is the current lack of evidence of improved clinical outcome with pharmacogenetic testing. Furthermore, with efficient therapeutic drug monitoring it is possible to rapidly correct for the effect of genotypic deviations on pharmacokinetics, thereby decreasing the utility of genotype-based dosing. The future of pharmacogenetics will be in treatment models in which patient characteristics are combined with data on polymorphisms in multiple genes. These models should focus on pharmacodynamic parameters, variations in the expression of drug transporter proteins, and predictors of toxicity. Such models will provide more information than the relatively small candidate gene studies performed so far. For implementation of these models into clinical practice, linkage of genotype data to medication prescription systems within electronic health records will be crucial.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Similar content being viewed by others

References

  1. US Department of Health and Human Services. Table of pharmacogenomic biomarkers in drug labeling [online], (2014).

  2. Swen, J. J. et al. Pharmacogenetics: from bench to byte—an update of guidelines. Clin. Pharmacol. Ther. 89, 662–673 (2011).

    Article  CAS  PubMed  Google Scholar 

  3. Overby, C. L., Tarczy-Hornoch, P., Hoath, J. I., Kalet, I. J. & Veenstra, D. L. Feasibility of incorporating genomic knowledge into electronic medical records for pharmacogenomic clinical decision support. BMC Bioinformatics 11 (Suppl. 9), S10 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Birdwell, K. A. et al. The use of a DNA biobank linked to electronic medical records to characterize pharmacogenomic predictors of tacrolimus dose requirement in kidney transplant recipients. Pharmacogenet. Genomics 22, 32–42 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. PharmGKB. The Pharmacogenomics Knowledge Base [online], (2014).

  6. Thervet, E. et al. Long-term results of TPMT activity monitoring in azathioprine-treated renal allograft recipients. J. Am. Soc. Nephrol. 12, 170–176 (2001).

    CAS  PubMed  Google Scholar 

  7. Evans, W. E. Pharmacogenetics of thiopurine S-methyltransferase and thiopurine therapy. Ther. Drug Monit. 26, 186–191 (2004).

    Article  CAS  PubMed  Google Scholar 

  8. Budhiraja, P. & Popovtzer, M. Azathioprine-related myelosuppression in a patient homozygous for TPMT*3A. Nat. Rev. Nephrol. 7, 478–484 (2011).

    Article  CAS  PubMed  Google Scholar 

  9. Schaeffeler, E. et al. Highly multiplexed genotyping of thiopurine s-methyltransferase variants using MALD-TOF mass spectrometry: reliable genotyping in different ethnic groups. Clin. Chem. 54, 1637–1647 (2008).

    Article  CAS  PubMed  Google Scholar 

  10. Thompson, A. J. et al. The cost-effectiveness of a pharmacogenetic test: a trial-based evaluation of TPMT genotyping for azathioprine. Value Health 17, 22–33 (2014).

    Article  PubMed  Google Scholar 

  11. Kurzawski, M., Dziewanowski, K., Gawron´ska-Szklarz, B., Doman´ski, L. & Droz´dzik, M. The impact of thiopurine s-methyltransferase polymorphism on azathioprine-induced myelotoxicity in renal transplant recipients. Ther. Drug Monit. 27, 435–441 (2005).

    Article  CAS  PubMed  Google Scholar 

  12. Relling, M. V. et al. Clinical Pharmacogenetics Implementation Consortium guidelines for thiopurine methyltransferase genotype and thiopurine dosing. Clin. Pharmacol. Ther. 89, 387–391 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Relling, M. V. et al. Clinical Pharmacogenetics Implementation Consortium guidelines for thiopurine methyltransferase genotype and thiopurine dosing: 2013 update. Clin. Pharmacol. Ther. 93, 324–325 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Derijks, L. J. & Hommes, D. W. Thiopurines in inflammatory bowel disease: new strategies for optimization of pharmacotherapy? Curr. Gastroenterol. Rep. 8, 89–92 (2006).

    Article  PubMed  Google Scholar 

  15. Organ Procurement and Transplantation Network and Scientific Registry of Transplant Recipients 2010 Data Report. Am. J. Transplant. 12 (Suppl. 1), 1–156 (2012).

  16. van Gelder, T. Therapeutic drug monitoring for mycophenolic acid is value for (little) money. Clin. Pharmacol. Ther. 90, 203–204 (2011).

    Article  CAS  PubMed  Google Scholar 

  17. Hesselink, D. A. & van Gelder, T. Genetic and nongenetic determinants of between-patient variability in the pharmacokinetics of mycophenolic acid. Clin. Pharmacol. Ther. 78, 317–321 (2005).

    Article  CAS  PubMed  Google Scholar 

  18. Kuypers, D. R., Naesens, M., Vermeire, S. & Vanrenterghem, Y. The impact of uridine diphosphate-glucuronosyltransferase 1A9 (UGT1A9) gene promoter region single-nucleotide polymorphisms T-275A and C-2152T on early mycophenolic acid dose-interval exposure in de novo renal allograft recipients. Clin. Pharmacol. Ther. 78, 351–361 (2005).

    Article  CAS  PubMed  Google Scholar 

  19. Fukuda, T. et al. UGT1A9, UGT2B7, and MRP2 genotypes can predict mycophenolic acid pharmacokinetic variability in pediatric kidney transplant recipients. Ther. Drug Monit. 34, 671–679 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. van Schaik, R. H. et al. UGT1A9 −275T>A/−2152C>T polymorphisms correlate with low MPA exposure and acute rejection in MMF/tacrolimus-treated kidney transplant patients. Clin. Pharmacol. Ther. 86, 319–327 (2009).

    Article  CAS  PubMed  Google Scholar 

  21. Sánchez-Fructuoso, A. I. et al. The prevalence of uridine diphosphate-glucuronosyltransferase 1A9 (UGT1A9) gene promoter region single-nucleotide polymorphisms T-275A and C-2152T and its influence on mycophenolic acid pharmacokinetics in stable renal transplant patients. Transplant. Proc. 41, 2313–2316 (2009).

    Article  CAS  PubMed  Google Scholar 

  22. Baldelli, S. et al. C-440T/T-331C polymorphisms in the UGT1A9 gene affect the pharmacokinetics of mycophenolic acid in kidney transplantation. Pharmacogenomics 8, 1127–1141 (2007).

    Article  CAS  PubMed  Google Scholar 

  23. Guo, D. et al. Polymorphisms of UGT1A9 and UGT2B7 influence the pharmacokinetics of mycophenolic acid after a single oral dose in healthy Chinese volunteers. Eur. J. Clin. Pharmacol. 69, 843–849 (2013).

    Article  PubMed  Google Scholar 

  24. Lloberas, N. et al. Influence of MRP2 on MPA pharmacokinetics in renal transplant recipients-results of the Pharmacogenomic Substudy within the Symphony Study. Nephrol. Dial. Transplant. 26, 3784–3793 (2011).

    Article  CAS  PubMed  Google Scholar 

  25. Picard, N. et al. The role of organic anion-transporting polypeptides and their common genetic variants in mycophenolic acid pharmacokinetics. Clin. Pharmacol. Ther. 87, 100–108 (2010).

    Article  CAS  PubMed  Google Scholar 

  26. Bouamar, R. et al. Mycophenolic acid-related diarrhea is not associated with polymorphisms in SLCO1B nor with ABCB1 in renal transplant recipients. Pharmacogenet. Genomics 22, 399–407 (2012).

    Article  CAS  PubMed  Google Scholar 

  27. Jacobson, P. A. et al. Genetic determinants of mycophenolate-related anemia and leukopenia after transplantation. Transplantation 91, 309–316 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Woillard, J. B. et al. Risk of diarrhoea in a long-term cohort of renal transplant patients given mycophenolate mofetil: the significant role of the UGT1A8*2 variant allele. Br. J. Clin. Pharmacol. 69, 675–683 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. van Agteren, M. et al. AcylMPAG plasma concentrations and mycophenolic acid-related side effects in patients undergoing renal transplantation are not related to the UGT2B7–840G>A gene polymorphism. Ther. Drug Monit. 30, 439–444 (2008).

    CAS  PubMed  Google Scholar 

  30. Prausa, S. E. et al. UGT genotype may contribute to adverse events following medication with mycophenolate mofetil in pediatric kidney transplant recipients. Clin. Pharmacol. Ther. 85, 495–500 (2009).

    Article  CAS  PubMed  Google Scholar 

  31. Barraclough, K. A., Lee, K. J. & Staatz, C. E. Pharmacogenetic influences on mycophenolate therapy. Pharmacogenomics 11, 369–390 (2010).

    Article  CAS  PubMed  Google Scholar 

  32. Natsumeda, Y. et al. Two distinct cDNAs for human IMP dehydrogenase. J. Biol. Chem. 265, 5292–5295 (1990).

    CAS  PubMed  Google Scholar 

  33. Weimert, N. A., Derotte, M., Alloway, R. R., Woodle, E. S. & Vinks, A. A. Monitoring of inosine monophosphate dehydrogenase activity as a biomarker for mycophenolic acid effect: potential clinical implications. Ther. Drug Monit. 29, 141–149 (2007).

    Article  CAS  PubMed  Google Scholar 

  34. Glander, P. et al. Non-radioactive determination of inosine 5′-monophosphate dehydro-genase (IMPDH) in peripheral mononuclear cells. Clin. Biochem. 34, 543–549 (2001).

    Article  CAS  PubMed  Google Scholar 

  35. Glander, P. et al. Improved assay for the nonradioactive determination of inosine 5′-monophosphate dehydrogenase activity in peripheral blood mononuclear cells. Ther. Drug Monit. 31, 351–359 (2009).

    Article  CAS  PubMed  Google Scholar 

  36. Vethe, N. T. & Bergan, S. Determination of inosine monophosphate dehydrogenase activity in human CD4+ cells isolated from whole blood during mycophenolic acid therapy. Ther. Drug Monit. 28, 608–613 (2006).

    Article  CAS  PubMed  Google Scholar 

  37. Vethe, N. T., Bremer, S., Rootwelt, H. & Bergan, S. Pharmacodynamics of mycophenolic acid in CD4+ cells: a single-dose study of IMPDH and purine nucleotide responses in healthy individuals. Ther. Drug Monit. 30, 647–655 (2008).

    Article  CAS  PubMed  Google Scholar 

  38. Budde, K. et al. Pharmacodynamic monitoring of mycophenolate mofetil. Clin. Chem. Lab. Med. 38, 1213–1216 (2000).

    Article  CAS  PubMed  Google Scholar 

  39. Glander, P. et al. Pre-transplant inosine monophosphate dehydrogenase activity is associated with clinical outcome after renal transplantation. Am. J. Transplant. 4, 2045–2051 (2004).

    Article  CAS  PubMed  Google Scholar 

  40. Glander, P., Hambach, P., Liefeldt, L. & Budde, K. Inosine 5′-monophosphate dehydrogenase activity as a biomarker in the field of transplantation. Clin. Chim. Acta 413, 1391–1397 (2012).

    Article  CAS  PubMed  Google Scholar 

  41. Glander, P. & Budde, K. Target enzyme activity as a biomarker for immunosuppression. Ther. Drug Monit. 32, 257–260 (2010).

    Article  CAS  PubMed  Google Scholar 

  42. Sombogaard, F. et al. Interpatient variability in IMPDH activity in MMF-treated renal transplant patients is correlated with IMPDH type II 3757T>C polymorphism. Pharmacogenet. Genomics 19, 626–634 (2009).

    Article  CAS  PubMed  Google Scholar 

  43. Wang, J. et al. IMPDH1 gene polymorphisms and association with acute rejection in renal transplant patients. Clin. Pharmacol. Ther. 83, 711–717 (2008).

    Article  CAS  PubMed  Google Scholar 

  44. Ohmann, E. L. et al. Genetic polymorphisms influence mycophenolate mofetil-related adverse events in pediatric heart transplant patients. J. Heart Lung Transplant. 29, 509–516 (2010).

    Article  PubMed  Google Scholar 

  45. Molinaro, M. et al. Monitoring of inosine monophosphate dehydrogenase activity and expression during the early period of mycophenolate mofetil therapy in de novo renal transplant patients. Drug Metab. Pharmacokinet. 28, 109–117 (2013).

    Article  CAS  PubMed  Google Scholar 

  46. Shah, S., Harwood, S. M., Döhler, B., Opelz, G. & Yaqoob, M. M. Inosine monophosphate dehydrogenase polymorphisms and renal allograft outcome. Transplantation 94, 486–491 (2012).

    Article  CAS  PubMed  Google Scholar 

  47. Dunn, C. J., Wagstaff, A. J., Perry, C. M., Plosker, G. L. & Goa, K. L. Cyclosporin: an updated review of the pharmacokinetic properties, clinical efficacy and tolerability of a microemulsion-based formulation (neoral)1 in organ transplantation. Drugs 61, 1957–2016 (2001).

    Article  CAS  PubMed  Google Scholar 

  48. Morris, R. G. et al. Comparison of trough, 2-hour, and limited AUC blood sampling for monitoring cyclosporin (Neoral) at day 7 post-renal transplantation and incidence of rejection in the first month. Ther. Drug Monit. 24, 479–486 (2002).

    Article  CAS  PubMed  Google Scholar 

  49. Mahalati, K. et al. Approaching the therapeutic window for cyclosporine in kidney transplantation: a prospective study. J. Am. Soc. Nephrol. 12, 828–833 (2001).

    CAS  PubMed  Google Scholar 

  50. Knight, S. R. & Morris, P. J. The clinical benefits of cyclosporine C2-level monitoring: a systematic review. Transplantation 83, 1525–1535 (2007).

    Article  CAS  PubMed  Google Scholar 

  51. Hesselink, D. A., van Gelder, T. & van Schaik, R. H. The pharmacogenetics of calcineurin inhibitors: one step closer toward individualized immunosuppression? Pharmacogenomics 6, 323–337 (2005).

    Article  CAS  PubMed  Google Scholar 

  52. Bouamar, R. et al. Polymorphisms in CYP3A5, CYP3A4, and ABCB1 are not associated with cyclosporine pharmacokinetics nor with cyclosporine clinical end points after renal transplantation. Ther. Drug Monit. 33, 178–184 (2011).

    CAS  PubMed  Google Scholar 

  53. Staatz, C. E., Goodman, L. K. & Tett, S. E. Effect of CYP3A and ABCB1 single nucleotide polymorphisms on the pharmacokinetics and pharmacodynamics of calcineurin inhibitors: part I. Clin. Pharmacokinet. 49, 141–175 (2010).

    Article  CAS  PubMed  Google Scholar 

  54. Anglicheau, D. et al. Role of P-glycoprotein in cyclosporine cytotoxicity in the cyclosporine-sirolimus interaction. Kidney Int. 70, 1019–1025 (2006).

    Article  CAS  PubMed  Google Scholar 

  55. Hesselink, D. A., Bouamar, R. & van Gelder, T. The pharmacogenetics of calcineurin inhibitor-related nephrotoxicity. Ther. Drug Monit. 32, 387–393 (2010).

    Article  CAS  PubMed  Google Scholar 

  56. Koziolek, M. J., Riess, R., Geiger, H., Thévenod, F. & Hauser, I. A. Expression of multidrug resistance P-glycoprotein in kidney allografts from cyclosporine A-treated patients. Kidney Int. 60, 156–166 (2001).

    Article  CAS  PubMed  Google Scholar 

  57. Hauser, I. A. et al. ABCB1 genotype of the donor but not of the recipient is a major risk factor for cyclosporine-related nephrotoxicity after renal transplantation. J. Am. Soc. Nephrol. 16, 1501–1511 (2005).

    Article  CAS  PubMed  Google Scholar 

  58. Cattaneo, D. et al. ABCB1 genotypes predict cyclosporine-related adverse events and kidney allograft outcome. J. Am. Soc. Nephrol. 20, 1404–1415 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Woillard, J. B. et al. Donor P-gp polymorphisms strongly influence renal function and graft loss in a cohort of renal transplant recipients on cyclosporine therapy in a long-term follow-up. Clin. Pharmacol. Ther. 88, 95–100 (2010).

    Article  PubMed  Google Scholar 

  60. De Meyer, M. et al. Donor age and ABCB1 1199G>A genetic polymorphism are independent factors affecting long-term renal function after kidney transplantation. J. Surg. Res. 178, 988–995 (2012).

    Article  CAS  PubMed  Google Scholar 

  61. Moore, J. et al. Donor ABCB1 variant associates with increased risk for kidney allograft failure. J. Am. Soc. Nephrol. 23, 1891–1899 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Jacobson, P. A. et al. Genetic and clinical determinants of early, acute calcineurin inhibitor-related nephrotoxicity: results from a kidney transplant consortium. Transplantation 93, 624–631 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Llaudó, I. et al. Do drug transporter (ABCB1) SNPs and P-glycoprotein function influence cyclosporine and macrolides exposure in renal transplant patients? Results of the Pharmacogenomic Substudy within the Symphony Study. Transpl. Int. 26, 177–186 (2013).

    Article  CAS  PubMed  Google Scholar 

  64. Crettol, S. et al. Influence of ABCB1 genetic polymorphisms on cyclosporine intracellular concentration in transplant recipients. Pharmacogenet. Genomics 18, 307–315 (2008).

    Article  CAS  PubMed  Google Scholar 

  65. Falck, P. et al. Declining intracellular T-lymphocyte concentration of cyclosporine A precedes acute rejection in kidney transplant recipients. Transplantation 85, 179–184 (2008).

    Article  CAS  PubMed  Google Scholar 

  66. Wallemacq, P. et al. Opportunities to optimize tacrolimus therapy in solid organ transplantation: report of the European consensus conference. Ther. Drug Monit. 31, 139–152 (2009).

    Article  CAS  PubMed  Google Scholar 

  67. Macphee, I. A. et al. Tacrolimus pharmacogenetics: polymorphisms associated with expression of cytochrome p4503A5 and P-glycoprotein correlate with dose requirement. Transplantation 74, 1486–1489 (2002).

    Article  CAS  PubMed  Google Scholar 

  68. Thervet, E. et al. Impact of cytochrome p450 3A5 genetic polymorphism on tacrolimus doses and concentration-to-dose ratio in renal transplant recipients. Transplantation 76, 1233–1235 (2003).

    Article  CAS  PubMed  Google Scholar 

  69. Haufroid, V. et al. The effect of CYP3A5 and MDR1 (ABCB1) polymorphisms on cyclosporine and tacrolimus dose requirements and trough blood levels in stable renal transplant patients. Pharmacogenetics 14, 147–154 (2004).

    Article  CAS  PubMed  Google Scholar 

  70. Jacobson, P. A. et al. Novel polymorphisms associated with tacrolimus trough concentrations: results from a multicenter kidney transplant consortium. Transplantation 91, 300–308 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Zhao, W. et al. Population pharmacokinetics and pharmacogenetics of once daily prolonged-release formulation of tacrolimus in pediatric and adolescent kidney transplant recipients. Eur. J. Clin. Pharmacol. 69, 189–195 (2013).

    Article  CAS  PubMed  Google Scholar 

  72. Wehland, M. et al. Differential impact of the CYP3A5*1 and CYP3A5*3 alleles on pre-dose concentrations of two tacrolimus formulations. Pharmacogenet. Genomics 21, 179–184 (2011).

    CAS  PubMed  Google Scholar 

  73. Hesselink, D. A., Bouamar, R., Elens, L., van Schaik, R. H. & van Gelder, T. The role of pharmacogenetics in the disposition of and response to tacrolimus in solid organ transplantation. Clin. Pharmacokinet. 53, 123–139 (2014).

    Article  CAS  PubMed  Google Scholar 

  74. Barry, A. & Levine, M. A systematic review of the effect of CYP3A5 genotype on the apparent oral clearance of tacrolimus in renal transplant recipients. Ther. Drug Monit. 32, 708–714 (2010).

    Article  CAS  PubMed  Google Scholar 

  75. MacPhee, I. A. et al. The influence of pharmacogenetics on the time to achieve target tacrolimus concentrations after kidney transplantation. Am. J. Transplant. 4, 914–919 (2004).

    Article  CAS  PubMed  Google Scholar 

  76. Haufroid, V. et al. CYP3A5 and ABCB1 polymorphisms and tacrolimus pharmacokinetics in renal transplant candidates: guidelines from an experimental study. Am. J. Transplant. 6, 2706–2713 (2006).

    Article  CAS  PubMed  Google Scholar 

  77. MacPhee, I. A. & Holt, D. W. A pharmacogenetic strategy for immunosuppression based on the CYP3A5 genotype. Transplantation 85, 163–165 (2008).

    Article  CAS  PubMed  Google Scholar 

  78. Thervet, E. et al. Optimization of initial tacrolimus dose using pharmacogenetic testing. Clin. Pharmacol. Ther. 87, 721–726 (2010).

    CAS  PubMed  Google Scholar 

  79. van Gelder, T., van Schaik, R. H. & Hesselink, D. A. Practicability of pharmacogenetics in transplantation medicine. Clin. Pharmacol. Ther. 95, 262–264 (2014).

    Article  CAS  PubMed  Google Scholar 

  80. Wang, D., Guo, Y., Wrighton, S. A., Cooke, G. E. & Sadee, W. Intronic polymorphism in CYP3A4 affects hepatic expression and response to statin drugs. Pharmacogenomics J. 11, 274–286 (2011).

    Article  CAS  PubMed  Google Scholar 

  81. Elens, L. et al. A new functional CYP3A4 intron 6 polymorphism significantly affects tacrolimus pharmacokinetics in kidney transplant recipients. Clin. Chem. 57, 1574–1583 (2011).

    Article  CAS  PubMed  Google Scholar 

  82. Elens, L. et al. Effect of a new functional CYP3A4 polymorphism on calcineurin inhibitors' dose requirements and trough blood levels in stable renal transplant patients. Pharmacogenomics 12, 1383–1396 (2011).

    Article  CAS  PubMed  Google Scholar 

  83. Passey, C. et al. Dosing equation for tacrolimus using genetic variants and clinical factors. Br. J. Clin. Pharmacol. 72, 948–957 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Passey, C. et al. Validation of tacrolimus equation to predict troughs using genetic and clinical factors. Pharmacogenomics 13, 1141–1147 (2012).

    Article  CAS  PubMed  Google Scholar 

  85. Elens, L., Hesselink, D. A., van Schaik, R. H. & van Gelder, T. The CYP3A4*22 allele affects the predictive value of a pharmacogenetic algorithm predicting tacrolimus predose concentrations. Br. J. Clin. Pharmacol. 75, 1545–1547 (2013).

    Article  CAS  PubMed  Google Scholar 

  86. Hesselink, D. A. et al. Genetic polymorphisms of the CYP3A4, CYP3A5, and MDR-1 genes and pharmacokinetics of the calcineurin inhibitors cyclosporine and tacrolimus. Clin. Pharmacol. Ther. 74, 245–254 (2003).

    Article  CAS  PubMed  Google Scholar 

  87. Le Meur, Y. et al. CYP3A5*3 influences sirolimus oral clearance in de novo and stable renal transplant recipients. Clin. Pharmacol. Ther. 80, 51–60 (2006).

    Article  CAS  PubMed  Google Scholar 

  88. Miao, L. Y., Huang, C. R., Hou, J. Q. & Qian, M. Y. Association study of ABCB1 and CYP3A5 gene polymorphisms with sirolimus trough concentration and dose requirements in Chinese renal transplant recipients. Biopharm. Drug Dispos. 29, 1–5 (2008).

    Article  CAS  PubMed  Google Scholar 

  89. Anglicheau, D. et al. Consequences of genetic polymorphisms for sirolimus requirements after renal transplant in patients on primary sirolimus therapy. Am. J. Transplant. 5, 595–603 (2005).

    Article  CAS  PubMed  Google Scholar 

  90. Woillard, J. B. et al. Effect of CYP3A4*22, POR*28, and PPARA rs4253728 on sirolimus in vitro metabolism and trough concentrations in kidney transplant recipients. Clin. Chem. 59, 1761–1769 (2013).

    Article  CAS  PubMed  Google Scholar 

  91. Sam, W. J. et al. Associations of ABCB1 3435C>T and IL-10-1082G>A polymorphisms with long-term sirolimus dose requirements in renal transplant patients. Transplantation 92, 1342–1347 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Gorski, J. C. et al. In vivo effects of interleukin-10 on human cytochrome P450 activity. Clin. Pharmacol. Ther. 67, 32–43 (2000).

    Article  CAS  PubMed  Google Scholar 

  93. Woillard, J. B. et al. Association of sirolimus adverse effects with m-TOR, p70S6K or Raptor polymorphisms in kidney transplant recipients. Pharmacogenet. Genomics 22, 725–732 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Picard, N., Rouguieg-Malki, K., Kamar, N., Rostaing, L. & Marquet, P. CYP3A5 genotype does not influence everolimus in vitro metabolism and clinical pharmacokinetics in renal transplant recipients. Transplantation 91, 652–656 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Kniepeiss, D. et al. The role of CYP3A5 genotypes in dose requirements of tacrolimus and everolimus after heart transplantation. Clin. Transplant. 25, 146–150 (2011).

    Article  CAS  PubMed  Google Scholar 

  96. Schoeppler, K. E., Aquilante, C. L., Kiser, T. H., Fish, D. N. & Zamora, M. R. The impact of genetic polymorphisms, diltiazem, and demographic variables on everolimus trough concentrations in lung transplant recipients. Clin. Transplant. 28, 590–597 (2014).

    Article  CAS  PubMed  Google Scholar 

  97. Moes, D. J. et al. Population pharmacokinetics and pharmacogenetics of everolimus in renal transplant patients. Clin. Pharmacokinet. 51, 467–480 (2012).

    Article  CAS  PubMed  Google Scholar 

  98. Bell, G. C. et al. Development and use of active clinical decision support for preemptive pharmacogenomics. J. Am. Med. Inform. Assoc. 21, e93–e99 (2014).

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Hospital Pharmacy, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, Rotterdam, 3000 CA, Netherlands

    Teun van Gelder

  2. Department of Clinical Chemistry, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, Rotterdam, 3000 CA, Netherlands

    Ron H. van Schaik

  3. Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, Rotterdam, 3000 CA, Netherlands

    Dennis A. Hesselink

Authors
  1. Teun van Gelder
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ron H. van Schaik
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dennis A. Hesselink
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

T.v.G. researched data for the article and wrote the article. All authors reviewed/edited the manuscript before submission.

Corresponding author

Correspondence to Teun van Gelder.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

van Gelder, T., van Schaik, R. & Hesselink, D. Pharmacogenetics and immunosuppressive drugs in solid organ transplantation. Nat Rev Nephrol 10, 725–731 (2014). https://doi.org/10.1038/nrneph.2014.172

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrneph.2014.172

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing