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Editorial

Impacts of High Intra- and Inter-Individual Variability in Tacrolimus Pharmacokinetics and Fast Tacrolimus Metabolism on Outcomes of Solid Organ Transplant Recipients

by
Charat Thongprayoon
1,
Panupong Hansrivijit
2,
Karthik Kovvuru
3,
Swetha R. Kanduri
3,
Tarun Bathini
4,
Aleksandra Pivovarova
5,
Justin R. Smith
5 and
Wisit Cheungpasitporn
3,*
1
Division of Nephrology, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA
2
Department of Internal Medicine, University of Pittsburgh Medical Center Pinnacle, Harrisburg, PA 17105, USA
3
Division of Nephrology, Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
4
Department of Internal Medicine, University of Arizona, Tucson, AZ 85724, USA
5
Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2020, 9(7), 2193; https://doi.org/10.3390/jcm9072193
Submission received: 6 July 2020 / Accepted: 9 July 2020 / Published: 11 July 2020
(This article belongs to the Special Issue Recent Advances and Clinical Outcomes of Kidney Transplantation)

Abstract

:
Tacrolimus is a first-line calcineurin inhibitor (CNI) and an integral part of the immunosuppressive strategy in solid organ transplantation. Being a dose-critical drug, tacrolimus has a narrow therapeutic index that necessitates periodic monitoring to maintain the drug’s efficacy and reduce the consequences of overexposure. Tacrolimus is characterized by substantial intra- and inter-individual pharmacokinetic variability. At steady state, the tacrolimus blood concentration to daily dose ratio (C/D ratio) has been described as a surrogate for the estimation of the individual metabolism rate, where a low C/D ratio reflects a higher rate of metabolism. Fast tacrolimus metabolism (low C/D ratio) is associated with the risk of poor outcomes after transplantation, including reduced allograft function and survival, higher allograft rejection, CNI nephrotoxicity, a faster decline in kidney function, reduced death-censored graft survival (DCGS), post-transplant lymphoproliferative disorders, dyslipidemia, hypertension, and cardiovascular events. In this article, we discuss the potential role of the C/D ratio in a noninvasive monitoring strategy for identifying patients at risk for potential adverse events post-transplant.

1. Introduction

Calcineurin inhibitor (CNI)-based immunosuppression is a regularly used therapeutic regimen in solid organ transplantation (SOT), tacrolimus (also known as FK506) being the front-running CNI [1,2] and mainstay of triple immunosuppressive drug regimens [3]. Before extended-release formulations became available, tacrolimus was traditionally given twice daily [4,5,6,7,8,9,10,11,12,13] (Table 1). Immediate-release formulations have highly variable absorption profiles and absolute bioavailability, ranging from 5 to 93%, with the average being 25 to 30% [14,15,16,17]. The tacrolimus protein binding rate is approximately 99%, and it also extensively binds to red blood cells. Protein binding is noted to be primarily with α1-acid glycoprotein and albumin [16,18]. Tacrolimus undergoes extensive hepatic metabolism, and less than 1% of the unaltered parent drug is eliminated [3].
The narrow therapeutic index of tacrolimus necessitates the frequent monitoring of the whole-blood concentration to achieve optimal therapeutic levels while drug toxicity [17,23,24,25,26]. Even a small variance in the dose or concentration can lead to therapeutic failure. Nonetheless, the therapeutic advantages of tacrolimus outweigh its major disadvantages such as the large inter-patient pharmacokinetic (PK) variability and potential risk of drug interactions with co-administrated medications [27]. While supra-therapeutic levels of tacrolimus can lead to neurotoxicity, nephrotoxicity, hypertension, and post-transplant diabetes, sub-therapeutic levels have been associated with allograft rejection [28].
Tacrolimus is primarily metabolized in the liver and small intestine through cytochrome P450 isoforms 3A4 and 3A5 (CYP3A4/5) [29]. Furthermore, tacrolimus is a substrate for P-glycoprotein (P-gp), a membrane efflux pump that actively transports the drug out of cells, which also contributes significantly to PK variability [30]. Inter-individual PK variability can be affected by the amount of time passed since the transplant, patient demographics (age and race), hepatic and renal function, the hematocrit level, food administration, concomitant medications (corticosteroids, antifungals, calcium channel blockers, etc.), and the genotype for metabolic enzymes [16,31] (Table 2). For instance, the CYP3A5*3 variant minor allele frequency (MAF) is estimated to be as high as 95% among Caucasians, while the African American population carries it at a rate of up to 33% [32]. A few studies have reported that mycophenolate mofetil co-administration may influence the metabolism of tacrolimus by possibly competing for CYP3A [33,34]. Relatedly, corticosteroids induce CYP3A4 and P-gp pathways that may potentially influence tacrolimus metabolism, yet the data are conflicting [35]. Increased tacrolimus levels upon the de-escalation of the dose or withdrawal of steroids have been reported [36,37]. In addition, by influencing the conversion of uridine diphosphoglucuronosyltransferase to the glucuronide metabolite of mycophenolicacid (MPA), tacrolimus may affect mycophenolicacid (MPA) levels [38].

2. Intra-Individual and Inter-Individual Tacrolimus PK Variability

Therapeutic drug monitoring (TDM) is essential for achieving therapeutic trough concentrations. Despite the fact that monitoring blood trough concentrations is an effective method for adjusting tacrolimus oral doses, clinical studies have reported that it may not be valuable for future dosage estimation and may also not be an accurate assessment of overall drug exposure among various individuals [17,23,24,25,26]. It is sometimes challenging to achieve and maintain target tacrolimus trough concentrations despite periodic tacrolimus TDM [3]. Hence, the determination of the area under the curve (AUC) over a dosing interval is generally considered the best indicator of optimal dosing, though multiple blood samples may be required, which, for practical and financial reasons, limits its clinical utility [38].
As discussed earlier, tacrolimus has a narrow therapeutic index and substantial inter-individual PK variability with standard weight-based dosing [56,57]. Moreover, tacrolimus also has a high intra-individual variability (IPV), resulting in sub-therapeutic and supra-therapeutic concentrations despite comparable dosing [25]. The coefficient of variation (CV) serves as a well-established biomarker of adherence in pediatric and adult groups of kidney transplant recipients [58]. It is derived by dividing the standard deviation (SD) of a number of serial pre-dose concentrations by the mean of these tacrolimus measurements. The CV is also utilized to assess IPV [18]. The IPV in the trough blood levels of tacrolimus represented by the CV is also a notable prognostic factor for graft function attributable to T-cell- and humoral-mediated rejection as well as vascular changes [59,60,61,62]. Kaya Aksoy et al., for a cohort of 67 pediatric kidney transplant recipients, reported that a tacrolimus CV cutoff value of 32% is considerably precise in identifying the further development of de novo donor-specific antibody (dnDSA) (AUC 0.713) [63]. During a follow-up period, a tacrolimus CV over 32% is associated with a higher percentage of development of dnDSA; 67% vs. 31% during 6 to 12 months, and 83% vs. 47% after 1 year of transplantation. Shuker et al. described that a high tacrolimus IPV in conjunction with lower tacrolimus pre-dose concentrations at 1 year post-transplantation correlates with adverse outcomes, including allograft rejection, the doubling of serum creatinine, and allograft loss [64]. Similarly, in a study by Rozen-Zvi et al., patients with a combination of low drug level exposure and high tacrolimus time-weighed variability had lower graft survival rates than patients with other exposure and variability combinations [65].
To date, multiple studies have confirmed that in kidney transplant recipients, sub-therapeutic tacrolimus levels or high tacrolimus IPV can result in increased dnDSA formation [25,65,66,67,68,69,70,71]. In the modern era, there has been increasing interest in the identification and validation of genetic variations that contribute to IPV [72,73]. Germline mutations in ATP-binding cassette B1 gene (ABCB1) and CYP3A4/5 probably contribute to interindividual tacrolimus PK variability [3,17,74]. Single nucleotide polymorphisms (SNPs) in CYP3A5 could contribute 40%–50% of inter-individual PK variability [75,76]. Two intragenic CYP3A4 SNPs are hypothesized to cause inter-individual PK variability [72,73]. Genetic variants in drug transporters may also add to tacrolimus’ PK variability. The ABCB1 gene, immensely expressed on hepatocytes and enterocytes, encodes P-gp; ABCB1 SNPs potentially add to inter-individual tacrolimus absorption and nephrotoxicity, respectively [3]. Renal tubular epithelial cells express P-gp, and SNPs have been associated with a variable risk of tacrolimus-induced nephrotoxicity [39,77]. Although genetic variability and environmental factors affect tacrolimus’ IPV, non-adherence is still the prevailing cause of high IPV [18,78,79,80].
Graft function and survival have been associated with tacrolimus trough levels and their variability [57,67,81,82,83]. Eminent studies by Sapir-Pichhadze et al. showed that a higher standard deviation in tacrolimus levels correlates with an increased likelihood of unfavorable endpoints, including allograft rejection, transplant glomerulopathy, and allograft loss [78]. Similar results were reproduced by several other studies [64,79,80,81]. Sablik et al. reported that even though high tacrolimus IPV was not associated with the incidence of chronic active antibody-mediated rejection (ABMR), high tacrolimus IPV, as compared to low IPV, showed a significant association with lower allograft survival in recipients with chronic active ABMR [84].

3. Fast Tacrolimus Metabolizers at Risk

Given its predictive value regarding post-transplant outcomes, there is an increasing interest in analyzing the rate of tacrolimus metabolism [83,85,86,87,88,89,90]. At steady state, the tacrolimus concentration to daily dose ratio (C/D ratio) has been described as a surrogate for the individual rate of tacrolimus metabolism, where a low C/D ratio is indicative of a higher rate of tacrolimus metabolism [88,90,91,92]. The C/D ratio is calculated using the following formula [62,88,93]:
C/D ratio (ng/mL × 1/mg) = blood tacrolimus trough concentration (ng/mL)/daily tacrolimus dose (mg)
Since tacrolimus trough levels and their corresponding doses are routinely recorded, calculating the C/D ratio could be utilized as a valuable tool for tacrolimus metabolism rate estimation. CYP3A5 expressers need higher doses of tacrolimus to reach comparable trough levels, even though CYP3A5 expression alone might not necessarily reflect fast metabolism of tacrolimus [94]. The tacrolimus metabolization phenotype has a fundamental effect on graft survival, which cannot be totally explained by this particular CYP3A5*1 genotype [56,83,95,96]. The tacrolimus C/D ratio might assist in identifying patients who are more susceptible to rapid alterations in tacrolimus blood levels. However, the C/D ratio is only a minor reflection of medication non-adherence, unlike tacrolimus IPV and the time in therapeutic range [25].
The C/D ratio has particularly been studied as a potential prognostic factor for renal allograft function after solid organ transplantation. Allograft function and allograft rejection have been reported to correlate with the C/D ratio [62,85,88]. Fast tacrolimus metabolism (a C/D ratio <1.05 ng/mL/mg) is correlated with inferior outcomes after kidney transplantation secondary to a higher rejection rate and risk of CNI nephrotoxicity (CNIT) [62,88,89] (Table 3). A low immediate-release tacrolimus C/D ratio is linked with higher C2 tacrolimus blood concentrations (2 h after tacrolimus intake) despite comparable trough levels in recipients with high C/D ratios [89]. In kidney and liver transplant recipients, a low C/D ratio strongly correlated with an increased risk of CNIT along with rapid kidney function decline [62,85,87,89,90]. In addition, the C/D ratio is a superior and early predictor of death-censored graft survival (DCGS). In a multivariate analysis, a C/D ratio below 1.05 was associated with death-censored graft loss risk elevation by a factor of 2.26. Tacrolimus clearance fluctuates more in the early post-transplant period owing to changes in gastrointestinal mobility, albumin and hematocrit levels, and steroid dosing [97]. Therefore, it is possible to identify individuals at risk one to three months following transplantation [83]. Both the time-dependent C/D ratio and early C/D ratios play similar roles in predicting the risk of graft loss. Notably, even a single C/D ratio calculated in stable patients three months after kidney transplant predicted outcomes, as it is relatively stable during those postoperative months [62,83]. Recently, Jouve et al. reported that the time-dependent and early tacrolimus C/D ratios appear to be independent predictors of DCGS [83].
Interestingly, while the tacrolimus trough blood concentration was only associated with the onset of de novo hypertension and cardiovascular events, fast-metabolizers are prone to developing more de novo dyslipidemia and insulin requiring diabetes along with de novo hypertension and cardiovascular events [62]. Furthermore, a very recent study showed that fast-metabolizers have a higher risk of developing post-transplant lymphoproliferative disorders (PTLD), although this association calls for further studies to validate the results [98]. The identification of fast metabolizers and optimization of tacrolimus formulations may contribute to beneficial therapeutic strategies in efforts to improve graft survival. With that being said, we highly encourage further studies to investigate the role of the C/D ratio and its association with cardiovascular risks and PTLD [83].
Lastly, exploring the concentrations of tacrolimus metabolites may also be of clinical value in the interpretation of the C/D ratio’s significance: individuals with a high C/D ratio might utilize different metabolic pathways, resulting in variable concentrations of tacrolimus metabolites, yielding divergent safety profiles. Furthermore, the C/D ratio is a surrogate of tacrolimus metabolite concentrations [99,100,101,102]. As reported by the ASERTAA (A Study of Extended Release Tacrolimus in African Americans) study, the C/D ratio varies depending on the tacrolimus formulation (extended-release tacrolimus (ENVARSUS XR®) versus immediate-release tacrolimus (PROGRAF®)) (Table 1) [103]. Using extended-release formulations of the drug will expectedly increase the C/D ratio due to a decreased total daily dose; however, whether this would impact graft survival is still under investigation. Additionally, future studies implementing CNI-free immunosuppression or minimizing tacrolimus and impacts on graft outcomes need to be evaluated among fast metabolizers [104].

4. Conclusions

In summary, the C/D ratio is a simple and valuable clinical tool in identifying patients who might benefit from immunosuppressive regimen adjustment. When patients require higher daily doses of tacrolimus to achieve therapeutic trough levels (i.e., a C/D ratio < 1), they may have a higher risk of subsequent graft loss. A combination of various tacrolimus monitoring strategies including determining the C/D ratio, IPV, and mean pre-dose concentration may identify solid organ transplant recipients at risk for poor outcomes.

Author Contributions

C.T., P.H., and W.C. drafted the manuscript. All authors gave comments on the earlier versions of the manuscript and edited the manuscript. All authors have read and agreed to the published version of the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Group KDIGOTW. KDIGO clinical practice guideline for the care of kidney transplant recipients. Am. J. Transplant. Off. J. Am. Soc. Transplant. Am. Soc. Transpl. Surg. 2009, 9 (Suppl. 3), S1–S155. [Google Scholar] [CrossRef] [PubMed]
  2. Kamińska, D.; Poznański, P.; Kuriata-Kordek, M.; Zielińska, D.; Mazanowska, O.; Kościelska-Kasprzak, K.; Krajewska, M. Conversion From a Twice-Daily to a Once-Daily Tacrolimus Formulation in Kidney Transplant Recipients. Transplant. Proc. 2020. [Google Scholar] [CrossRef] [PubMed]
  3. Zhu, J.; Patel, T.; Miller, J.A.; Torrice, C.D.; Aggarwal, M.; Sketch, M.R.; Alexander, M.D.; Armistead, P.M.; Coghill, J.M.; Grgic, T.; et al. Influence of Germline Genetics on Tacrolimus Pharmacokinetics and Pharmacodynamics in Allogeneic Hematopoietic Stem Cell Transplant Patients. Int. J. Mol. Sci. 2020, 21, 858. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Abecassis, M.M.; Seifeldin, R.; Riordan, M. Patient outcomes and economics of once-daily tacrolimus in renal transplant patients: Results of a modeling analysis. Transplant. Proc. 2008, 40, 1443–1445. [Google Scholar] [CrossRef] [PubMed]
  5. Tinti, F.; Meçule, A.; Poli, L.; Bachetoni, A.; Umbro, I.; Brunini, F.; Barile, M.; Nofroni, I.; Berloco, P.; Mitterhofer, A. Improvement of graft function after conversion to once daily tacrolimus of stable kidney transplant patients. Transplant. Proc. 2010, 42, 4047–4048. [Google Scholar] [CrossRef] [PubMed]
  6. Uchida, J.; Kuwabara, N.; Machida, Y.; Iwai, T.; Naganuma, T.; Kumada, N.; Nakatani, T. Conversion of stable kidney transplant recipients from a twice-daily prograf to a once-daily tacrolimus formulation: A short-term study on its effects on glucose metabolism. Transplant. Proc. 2012, 44, 128–133. [Google Scholar] [CrossRef]
  7. Tsuchiya, T.; Ishida, K.; Ito, S.; Deguchi, T. Effect of conversion from twice-daily to once-daily tacrolimus on glucose intolerance in stable kidney transplant recipients. Transplant. Proc. 2012, 44, 118–120. [Google Scholar] [CrossRef]
  8. Ruangkanchanasetr, P.; Sanohdontree, N.; Supaporn, T.; Sathavarodom, N.; Satirapoj, B. Beta cell function and insulin resistance after conversion from tacrolimus twice-daily to extended-release tacrolimus once-daily in stable renal transplant recipients. Med. Sci. Monit. 2016, 21, 765–774. [Google Scholar] [CrossRef]
  9. Cross, S.A.; Perry, C.M. Tacrolimus Once-Daily Formulation. Drugs 2007, 67, 1931–1943. [Google Scholar] [CrossRef]
  10. First, M.R. First clinical experience with the new once-daily formulation of tacrolimus. Ther. Drug Monit. 2008, 30, 159–166. [Google Scholar] [CrossRef]
  11. Hardinger, K.L.; Park, J.M.; Schnitzler, M.A.; Koch, M.J.; Miller, B.W.; Brennan, D.C. Pharmacokinetics of tacrolimus in kidney transplant recipients: Twice daily versus once daily dosing. Am. J. Transplant. 2004, 4, 621–625. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Alloway, R.; Steinberg, S.; Khalil, K.; Gourishankar, S.; Miller, J.; Norman, D.; Hariharan, S.; Pirsch, J.; Matas, A.; Zaltzman, J. Conversion of stable kidney transplant recipients from a twice daily Prograf-based regimen to a once daily modified release tacrolimus-based regimen. Transplant. Proc. 2005, 37, 867–870. [Google Scholar] [CrossRef] [PubMed]
  13. Alloway, R.; Steinberg, S.; Khalil, K.; Gourishankar, S.; Miller, J.; Norman, D.; Hariharan, S.; Pirsch, J.; Matas, A.; Zaltzman, J. Two years postconversion from a prograf-based regimen to a once-daily tacrolimus extended-release formulation in stable kidney transplant recipients. Transplantation 2007, 83, 1648–1651. [Google Scholar] [CrossRef] [PubMed]
  14. Undre, N.A. Pharmacokinetics of tacrolimus-based combination therapies. Nephrol. Dial. Transplant. 2003, 18 (Suppl. 1), i12–i15. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Wallemacq, P.E.; Verbeeck, R.K. Comparative clinical pharmacokinetics of tacrolimus in paediatric and adult patients. Clin. Pharmacokinet. 2001, 40, 283–295. [Google Scholar] [CrossRef]
  16. Staatz, C.E.; Tett, S.E. Clinical pharmacokinetics and pharmacodynamics of tacrolimus in solid organ transplantation. Clin. Pharmacokinet. 2004, 43, 623–653. [Google Scholar] [CrossRef]
  17. 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. 2014, 53, 123–139. [Google Scholar] [CrossRef]
  18. Shuker, N.; van Gelder, T.; Hesselink, D.A. Intra-patient variability in tacrolimus exposure: Causes, consequences for clinical management. Transplant. Rev. 2015, 29, 78–84. [Google Scholar] [CrossRef]
  19. Burkhard, J.; Ciurea, A.; Gabay, C.; Hasler, P.; Müller, R.; Niedrig, M.; Fehr, J.; Villiger, P.; Visser, L.G.; de Visser, A.W.; et al. Long-term immunogenicity after yellow fever vaccination in immunosuppressed and healthy individuals. Vaccine 2020, 38, 3610–3617. [Google Scholar] [CrossRef]
  20. Kaur, A.; Goggolidou, P. Ulcerative colitis: Understanding its cellular pathology could provide insights into novel therapies. J. Inflamm. 2020, 17, 1–8. [Google Scholar] [CrossRef] [Green Version]
  21. Abu-Sbeih, H.; Wang, Y. Management Considerations for Immune Checkpoint Inhibitor-Induced Enterocolitis Based on Management of Inflammatory Bowel Disease. Inflamm. Bowel Dis. 2020, 26, 662–668. [Google Scholar] [CrossRef] [Green Version]
  22. Bozon, A.; Debourdeau, A.; Boivineau, L. Liver transplantation for fulminant herpes simplex hepatitis in a patient treated with adalimumab for chronic pouchitis. J. Crohn’s Colitis 2020. [Google Scholar] [CrossRef] [PubMed]
  23. Andrews, L.M.; Li, Y.; De Winter, B.C.M.; Shi, Y.Y.; Baan, C.C.; Van Gelder, T.; Hesselink, D.A. Pharmacokinetic considerations related to therapeutic drug monitoring of tacrolimus in kidney transplant patients. Expert Opin. Drug Metab. Toxicol. 2017, 13, 1225–1236. [Google Scholar] [CrossRef] [PubMed]
  24. Brunet, M.; van Gelder, T.; Åsberg, A.; Haufroid, V.; Hesselink, D.A.; Langman, L.; Lemaitre, F.; Marquet, P.; Seger, C.; Shipkova, M.; et al. Therapeutic Drug Monitoring of Tacrolimus-Personalized Therapy: Second Consensus Report. Ther. Drug Monit. 2019, 41, 261–307. [Google Scholar] [CrossRef]
  25. Mendoza Rojas, A.; Hesselink, D.A.; van Besouw, N.M.; Baan, C.C.; van Gelder, T. Impact of low tacrolimus exposure and high tacrolimus intra-patient variability on the development of de novo anti-HLA donor-specific antibodies in kidney transplant recipients. Expert Rev. Clin. Immunol. 2019, 15, 1323–1331. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Ebid, A.-H.; Mohamed, S.; Mira, A.; Saleh, A. Pharmacokinetics of Tacrolimus in Egyptian Liver Transplant Recipients: Role of the Classic Co-variables. J. Adv. Pharm. Res. 2019, 3, 182–193. [Google Scholar] [CrossRef]
  27. Andreu, F.; Colom, H.; Elens, L.; van Gelder, T.; van Schaik, R.H.N.; Hesselink, D.A.; Bestard, O.; Torras, J.; Cruzado, J.M.; Grinyó, J.M.; et al. A New CYP3A5*3 and CYP3A4*22 Cluster Influencing Tacrolimus Target Concentrations: A Population Approach. Clin. Pharmacokinet. 2017, 56, 963–975. [Google Scholar] [CrossRef]
  28. Andrews, L.M.; Hesselink, D.A.; van Gelder, T.; Koch, B.C.P.; Cornelissen, E.A.M.; Brüggemann, R.J.M.; van Schaik, R.H.N.; de Wildt, S.N.; Cransberg, K.; de Winter, B.C.M. A Population Pharmacokinetic Model to Predict the Individual Starting Dose of Tacrolimus Following Pediatric Renal Transplantation. Clin. Pharmacokinet. 2018, 57, 475–489. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  29. Dai, Y.; Hebert, M.F.; Isoherranen, N.; Davis, C.L.; Marsh, C.; Shen, D.D.; Thummel, K.E. Effect of CYP3A5 polymorphism on tacrolimus metabolic clearance in vitro. Drug Metab. Dispos. 2006, 34, 836–847. [Google Scholar] [CrossRef] [Green Version]
  30. Anglicheau, D.; Verstuyft, C.; Laurent-Puig, P.; Becquemont, L.; Schlageter, M.H.; Cassinat, B.; Beaune, P.; Legendre, C.; Thervet, E. Association of the multidrug resistance-1 gene single-nucleotide polymorphisms with the tacrolimus dose requirements in renal transplant recipients. J. Am. Soc. Nephrol. 2003, 14, 1889–1896. [Google Scholar] [CrossRef] [Green Version]
  31. Brooks, E.; Tett, S.E.; Isbel, N.M.; Staatz, C.E. Population Pharmacokinetic Modelling and Bayesian Estimation of Tacrolimus Exposure: Is this Clinically Useful for Dosage Prediction Yet? Clin. Pharmacokinet. 2016, 55, 1295–1335. [Google Scholar] [CrossRef] [PubMed]
  32. Lamba, J.; Hebert, J.M.; Schuetz, E.G.; Klein, T.E.; Altman, R.B. PharmGKB summary: Very important pharmacogene information for CYP3A5. Pharm. Genom. 2012, 22, 555–558. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Staatz, C.E.; Tett, S.E. Clinical pharmacokinetics and pharmacodynamics of mycophenolate in solid organ transplant recipients. Clin. Pharmacokinet. 2007, 46, 13–58. [Google Scholar] [CrossRef] [PubMed]
  34. Picard, N.; Cresteil, T.; Prémaud, A.; Marquet, P. Characterization of a phase 1 metabolite of mycophenolic acid produced by CYP3A4/5. Ther. Drug Monit. 2004, 26, 600–608. [Google Scholar] [CrossRef] [PubMed]
  35. Lam, S.; Partovi, N.; Ting, L.S.; Ensom, M.H. Corticosteroid interactions with cyclosporine, tacrolimus, mycophenolate, and sirolimus: Fact or fiction? Ann. Pharmacother. 2008, 42, 1037–1047. [Google Scholar] [CrossRef] [PubMed]
  36. van Duijnhoven, E.M.; Boots, J.M.; Christiaans, M.H.; Stolk, L.M.; Undre, N.A.; van Hooff, J.P. Increase in tacrolimus trough levels after steroid withdrawal. Transpl. Int. 2003, 16, 721–725. [Google Scholar] [CrossRef] [PubMed]
  37. Squifflet, J.-P.; Vanrenterghem, Y.; Van Hooff, J.; Salmela, K.; Rigotti, P. Safe withdrawal of corticosteroids or mycophenolate mofetil: Results of a large, prospective, multicenter, randomized study. Transplant. Proc. 2002, 34, 1584–1586. [Google Scholar] [CrossRef]
  38. Wallemacq, P.; Armstrong, V.W.; Brunet, M.; Haufroid, V.; Holt, D.W.; Johnston, A.; Kuypers, D.; Le Meur, Y.; Marquet, P.; Oellerich, M.; et al. Opportunities to optimize tacrolimus therapy in solid organ transplantation: Report of the European consensus conference. Ther. Drug Monit. 2009, 31, 139–152. [Google Scholar] [CrossRef] [Green Version]
  39. Hesselink, D.A.; van Schaik, R.H.; van der Heiden, I.P.; van der Werf, M.; Gregoor, P.J.; Lindemans, J.; Weimar, W.; van Gelder, T. Genetic polymorphisms of the CYP3A4, CYP3A5, and MDR-1 genes and pharmacokinetics of the calcineurin inhibitors cyclosporine and tacrolimus. Clin. Pharmacol. Ther. 2003, 74, 245–254. [Google Scholar] [CrossRef]
  40. Gervasini, G.; Garcia, M.; Macias, R.M.; Cubero, J.J.; Caravaca, F.; Benitez, J. Impact of genetic polymorphisms on tacrolimus pharmacokinetics and the clinical outcome of renal transplantation. Transpl. Int. 2012, 25, 471–480. [Google Scholar] [CrossRef]
  41. Provenzani, A.; Notarbartolo, M.; Labbozzetta, M.; Poma, P.; Biondi, F.; Sanguedolce, R.; Vizzini, G.; Palazzo, U.; Polidori, P.; Triolo, F.; et al. The effect of CYP3A5 and ABCB1 single nucleotide polymorphisms on tacrolimus dose requirements in Caucasian liver transplant patients. Ann. Transplant. 2009, 14, 23–31. [Google Scholar] [PubMed]
  42. Goto, M.; Masuda, S.; Kiuchi, T.; Ogura, Y.; Oike, F.; Okuda, M.; Tanaka, K.; Inui, K. CYP3A5*1-carrying graft liver reduces the concentration/oral dose ratio of tacrolimus in recipients of living-donor liver transplantation. Pharmacogenetics 2004, 14, 471–478. [Google Scholar] [CrossRef] [PubMed]
  43. Uesugi, M.; Masuda, S.; Katsura, T.; Oike, F.; Takada, Y.; Inui, K. Effect of intestinal CYP3A5 on postoperative tacrolimus trough levels in living-donor liver transplant recipients. Pharm. Genom. 2006, 16, 119–127. [Google Scholar] [CrossRef] [PubMed]
  44. Chakkera, H.A.; Chang, Y.H.; Bodner, J.K.; Behmen, S.; Heilman, R.L.; Reddy, K.S.; Mulligan, D.C.; Moss, A.A.; Khamash, H.; Katariya, N.; et al. Genetic differences in Native Americans and tacrolimus dosing after kidney transplantation. Transplant. Proc. 2013, 45, 137–141. [Google Scholar] [CrossRef] [PubMed]
  45. Sanghavi, K.; Brundage, R.C.; Miller, M.B.; Schladt, D.P.; Israni, A.K.; Guan, W.; Oetting, W.S.; Mannon, R.B.; Remmel, R.P.; Matas, A.J.; et al. Genotype-guided tacrolimus dosing in African-American kidney transplant recipients. Pharm. J. 2017, 17, 61–68. [Google Scholar] [CrossRef] [Green Version]
  46. Iwasaki, K. Metabolism of tacrolimus (FK506) and recent topics in clinical pharmacokinetics. Drug Metab. Pharmacokinet. 2007, 22, 328–335. [Google Scholar] [CrossRef] [Green Version]
  47. Elens, L.; Capron, A.; Kerckhove, V.V.; Lerut, J.; Mourad, M.; Lison, D.; Wallemacq, P.; Haufroid, V. 1199G>A and 2677G>T/A polymorphisms of ABCB1 independently affect tacrolimus concentration in hepatic tissue after liver transplantation. Pharm. Genom. 2007, 17, 873–883. [Google Scholar] [CrossRef]
  48. López-Montenegro Soria, M.A.; Kanter Berga, J.; Beltrán Catalán, S.; Milara Payá, J.; Pallardó Mateu, L.M.; Jiménez Torres, N.V. Genetic polymorphisms and individualized tacrolimus dosing. Transplant. Proc. 2010, 42, 3031–3033. [Google Scholar] [CrossRef]
  49. Wang, W.-L.; Jin, J.; Zheng, S.-S.; Wu, L.-H.; Liang, T.-B.; Yu, S.-F.; Yan, S. Tacrolimus dose requirement in relation to donor and recipient ABCB1 and CYP3A5 gene polymorphisms in Chinese liver transplant patients. Liver Transpl. 2006, 12, 775–780. [Google Scholar] [CrossRef]
  50. Asano, T.; Nishimoto, K.; Hayakawa, M. Increased tacrolimus trough levels in association with severe diarrhea, a case report. Transplant. Proc. 2004, 36, 2096–2097. [Google Scholar] [CrossRef]
  51. Leroy, S.; Isapof, A.; Fargue, S.; Fakhoury, M.; Bensman, A.; Deschênes, G.; Jacqz-Aigrain, E.; Ulinski, T. Tacrolimus nephrotoxicity: Beware of the association of diarrhea, drug interaction and pharmacogenetics. Pediatr. Nephrol. 2010, 25, 965–969. [Google Scholar] [CrossRef] [PubMed]
  52. Sato, K.; Amada, N.; Sato, T.; Miura, S.; Ohashi, Y.; Sekiguchi, S.; Satomi, S.; Okazaki, H. Severe elevations of FK506 blood concentration due to diarrhea in renal transplant recipients. Clin. Transplant. 2004, 18, 585–590. [Google Scholar] [CrossRef] [PubMed]
  53. Bekersky, I.; Dressler, D.; Mekki, Q.A. Effect of low- and high-fat meals on tacrolimus absorption following 5 mg single oral doses to healthy human subjects. J. Clin. Pharmacol. 2001, 41, 176–182. [Google Scholar] [CrossRef] [PubMed]
  54. Chan, S.; Burke, M.T.; Johnson, D.W.; Francis, R.S.; Mudge, D.W. Tacrolimus Toxicity due to Biliary Obstruction in a Combined Kidney and Liver Transplant Recipient. Case Rep. Transplant. 2017, 2017, 9096435. [Google Scholar] [CrossRef]
  55. Shin, S.H.; Yahng, S.A.; Yoon, J.H.; Lee, S.E.; Cho, B.S.; Kim, Y.J. Hepatic veno-occlusive disease resulting in tacrolimus toxicity after allogeneic hematopoietic stem cell transplantation. Blood Res. 2013, 48, 55–57. [Google Scholar] [CrossRef] [Green Version]
  56. Tron, C.; Lemaitre, F.; Verstuyft, C.; Petitcollin, A.; Verdier, M.C.; Bellissant, E. Pharmacogenetics of Membrane Transporters of Tacrolimus in Solid Organ Transplantation. Clin. Pharmacokinet. 2019, 58, 593–613. [Google Scholar] [CrossRef]
  57. Borra, L.C.; Roodnat, J.I.; Kal, J.A.; Mathot, R.A.; Weimar, W.; van Gelder, T. High within-patient variability in the clearance of tacrolimus is a risk factor for poor long-term outcome after kidney transplantation. Nephrol. Dial. Transplant. 2010, 25, 2757–2763. [Google Scholar] [CrossRef] [Green Version]
  58. Kuypers, D.R.J. Intrapatient Variability of Tacrolimus Exposure in Solid Organ Transplantation: A Novel Marker for Clinical Outcome. Clin. Pharmacol. Ther. 2020, 107, 347–358. [Google Scholar] [CrossRef]
  59. Del Bello, A.; Congy-Jolivet, N.; Danjoux, M.; Muscari, F.; Lavayssière, L.; Esposito, L.; Hebral, A.L.; Bellière, J.; Kamar, N. High tacrolimus intra-patient variability is associated with graft rejection, and de novo donor-specific antibodies occurrence after liver transplantation. World J. Gastroenterol. 2018, 24, 1795–1802. [Google Scholar] [CrossRef]
  60. Vandevoorde, K.; Ducreux, S.; Bosch, A.; Guillaud, O.; Hervieu, V.; Chambon-Augoyard, C.; Poinsot, D.; André, P.; Scoazec, J.Y.; Robinson, P.; et al. Prevalence, Risk Factors, and Impact of Donor-Specific Alloantibodies After Adult Liver Transplantation. Liver Transpl. 2018, 24, 1091–1100. [Google Scholar] [CrossRef] [Green Version]
  61. van der Veer, M.A.A.; Nangrahary, N.; Hesselink, D.A.; Erler, N.S.; Metselaar, H.J.; van Gelder, T.; Darwish Murad, S. High Intrapatient Variability in Tacrolimus Exposure Is Not Associated With Immune-mediated Graft Injury After Liver Transplantation. Transplantation 2019, 103, 2329–2337. [Google Scholar] [CrossRef] [PubMed]
  62. Schütte-Nütgen, K.; Thölking, G.; Steinke, J.; Pavenstädt, H.; Schmidt, R.; Suwelack, B.; Reuter, S. Fast Tac Metabolizers at Risk ⁻ It is Time for a C/D Ratio Calculation. J. Clin. Med. 2019, 8, 587. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Kaya Aksoy, G.; Comak, E.; Koyun, M.; Akbaş, H.; Akkaya, B.; Aydınlı, B.; Uçar, F.; Akman, S. Tacrolimus Variability: A Cause of Donor-Specific Anti-HLA Antibody Formation in Children. Eur. J. Drug Metab. Pharmacokinet. 2019, 44, 539–548. [Google Scholar] [CrossRef] [PubMed]
  64. Shuker, N.; Shuker, L.; van Rosmalen, J.; Roodnat, J.I.; Borra, L.C.; Weimar, W.; Hesselink, D.A.; van Gelder, T. A high intrapatient variability in tacrolimus exposure is associated with poor long-term outcome of kidney transplantation. Transpl. Int. 2016, 29, 1158–1167. [Google Scholar] [CrossRef] [PubMed]
  65. Gatault, P.; Kamar, N.; Büchler, M.; Colosio, C.; Bertrand, D.; Durrbach, A.; Albano, L.; Rivalan, J.; Le Meur, Y.; Essig, M.; et al. Reduction of Extended-Release Tacrolimus Dose in Low-Immunological-Risk Kidney Transplant Recipients Increases Risk of Rejection and Appearance of Donor-Specific Antibodies: A Randomized Study. Am. J. Transplant. 2017, 17, 1370–1379. [Google Scholar] [CrossRef] [PubMed]
  66. Pizzo, H.P.; Ettenger, R.B.; Gjertson, D.W.; Reed, E.F.; Zhang, J.; Gritsch, H.A.; Tsai, E.W. Sirolimus and tacrolimus coefficient of variation is associated with rejection, donor-specific antibodies, and nonadherence. Pediatr. Nephrol. 2016, 31, 2345–2352. [Google Scholar] [CrossRef] [PubMed]
  67. Rodrigo, E.; Segundo, D.S.; Fernández-Fresnedo, G.; López-Hoyos, M.; Benito, A.; Ruiz, J.C.; de Cos, M.A.; Arias, M. Within-Patient Variability in Tacrolimus Blood Levels Predicts Kidney Graft Loss and Donor-Specific Antibody Development. Transplantation 2016, 100, 2479–2485. [Google Scholar] [CrossRef]
  68. Wiebe, C.; Rush, D.N.; Nevins, T.E.; Birk, P.E.; Blydt-Hansen, T.; Gibson, I.W.; Goldberg, A.; Ho, J.; Karpinski, M.; Pochinco, D.; et al. Class II Eplet Mismatch Modulates Tacrolimus Trough Levels Required to Prevent Donor-Specific Antibody Development. J. Am. Soc. Nephrol. 2017, 28, 3353–3362. [Google Scholar] [CrossRef] [Green Version]
  69. Davis, S.; Gralla, J.; Klem, P.; Tong, S.; Wedermyer, G.; Freed, B.; Wiseman, A.; Cooper, J.E. Lower tacrolimus exposure and time in therapeutic range increase the risk of de novo donor-specific antibodies in the first year of kidney transplantation. Am. J. Transplant. 2018, 18, 907–915. [Google Scholar] [CrossRef] [Green Version]
  70. Jung, H.Y.; Kim, S.H.; Seo, M.Y.; Cho, S.Y.; Yang, Y.; Choi, J.Y.; Cho, J.H.; Park, S.H.; Kim, Y.L.; Kim, H.K.; et al. Characteristics and Clinical Significance of De Novo Donor-Specific Anti-HLA Antibodies after Kidney Transplantation. J. Korean Med. Sci. 2018, 33, e217. [Google Scholar] [CrossRef]
  71. Girerd, S.; Schikowski, J.; Girerd, N.; Duarte, K.; Busby, H.; Gambier, N.; Ladrière, M.; Kessler, M.; Frimat, L.; Aarnink, A. Impact of reduced exposure to calcineurin inhibitors on the development of de novo DSA: A cohort of non-immunized first kidney graft recipients between 2007 and 2014. BMC Nephrol. 2018, 19, 232. [Google Scholar] [CrossRef] [PubMed]
  72. Abdel-Kahaar, E.; Winter, S.; Tremmel, R.; Schaeffeler, E.; Olbricht, C.J.; Wieland, E.; Schwab, M.; Shipkova, M.; Jaeger, S.U. The Impact of CYP3A4*22 on Tacrolimus Pharmacokinetics and Outcome in Clinical Practice at a Single Kidney Transplant Center. Front. Genet. 2019, 10, 871. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  73. Oetting, W.S.; Wu, B.; Schladt, D.P.; Guan, W.; Remmel, R.P.; Dorr, C.; Mannon, R.B.; Matas, A.J.; Israni, A.K.; Jacobson, P.A. Attempted validation of 44 reported SNPs associated with tacrolimus troughs in a cohort of kidney allograft recipients. Pharmacogenomics 2018, 19, 175–184. [Google Scholar] [CrossRef] [PubMed]
  74. Birdwell, K.A.; Decker, B.; Barbarino, J.M.; Peterson, J.F.; Stein, C.M.; Sadee, W.; Wang, D.; Vinks, A.A.; He, Y.; Swen, J.J.; et al. Clinical Pharmacogenetics Implementation Consortium (CPIC) Guidelines for CYP3A5 Genotype and Tacrolimus Dosing. Clin. Pharmacol. Ther. 2015, 98, 19–24. [Google Scholar] [CrossRef] [Green Version]
  75. Haufroid, V.; Mourad, M.; Van Kerckhove, V.; Wawrzyniak, J.; De Meyer, M.; Eddour, D.C.; Malaise, J.; Lison, D.; Squifflet, J.P.; Wallemacq, P. The effect of CYP3A5 and MDR1 (ABCB1) polymorphisms on cyclosporine and tacrolimus dose requirements and trough blood levels in stable renal transplant patients. Pharmacogenetics 2004, 14, 147–154. [Google Scholar] [CrossRef]
  76. Press, R.R.; Ploeger, B.A.; den Hartigh, J.; van der Straaten, T.; van Pelt, J.; Danhof, M.; de Fijter, J.W.; Guchelaar, H.J. Explaining variability in tacrolimus pharmacokinetics to optimize early exposure in adult kidney transplant recipients. Ther. Drug Monit. 2009, 31, 187–197. [Google Scholar] [CrossRef]
  77. Hodges, L.M.; Markova, S.M.; Chinn, L.W.; Gow, J.M.; Kroetz, D.L.; Klein, T.E.; Altman, R.B. Very important pharmacogene summary: ABCB1 (MDR1, P-glycoprotein). Pharm. Genom. 2011, 21, 152–161. [Google Scholar] [CrossRef] [Green Version]
  78. Sapir-Pichhadze, R.; Wang, Y.; Famure, O.; Li, Y.; Kim, S.J. Time-dependent variability in tacrolimus trough blood levels is a risk factor for late kidney transplant failure. Kidney Int. 2014, 85, 1404–1411. [Google Scholar] [CrossRef] [Green Version]
  79. van Gelder, T. Within-patient variability in immunosuppressive drug exposure as a predictor for poor outcome after transplantation. Kidney Int. 2014, 85, 1267–1268. [Google Scholar] [CrossRef] [Green Version]
  80. Süsal, C.; Döhler, B. Late intra-patient tacrolimus trough level variability as a major problem in kidney transplantation: A Collaborative Transplant Study Report. Am. J. Transplant. 2019, 19, 2805–2813. [Google Scholar] [CrossRef]
  81. O’Regan, J.A.; Canney, M.; Connaughton, D.M.; O’Kelly, P.; Williams, Y.; Collier, G.; deFreitas, D.G.; O’Seaghdha, C.M.; Conlon, P.J. Tacrolimus trough-level variability predicts long-term allograft survival following kidney transplantation. J. Nephrol. 2016, 29, 269–276. [Google Scholar] [CrossRef] [PubMed]
  82. Knight, S.R. Intrapatient variability in tacrolimus exposure—A useful tool for clinical practice? Transpl. Int. 2016, 29, 1155–1157. [Google Scholar] [CrossRef]
  83. Jouve, T.; Fonrose, X.; Noble, J.; Janbon, B.; Fiard, G.; Malvezzi, P.; Stanke-Labesque, F.; Rostaing, L. The TOMATO Study (Tacrolimus Metabolization in Kidney Transplantation): Impact of the Concentration–Dose Ratio on Death-censored Graft Survival. Transplantation 2020, 104, 1263–1271. [Google Scholar] [CrossRef] [PubMed]
  84. Sablik, K.A.; Clahsen-van Groningen, M.C.; Hesselink, D.A.; van Gelder, T.; Betjes, M.G.H. Tacrolimus intra-patient variability is not associated with chronic active antibody mediated rejection. PLoS ONE 2018, 13, e0196552. [Google Scholar] [CrossRef] [Green Version]
  85. Egeland, E.J.; Robertsen, I.; Hermann, M.; Midtvedt, K.; Størset, E.; Gustavsen, M.T.; Reisæter, A.V.; Klaasen, R.; Bergan, S.; Holdaas, H.; et al. High Tacrolimus Clearance Is a Risk Factor for Acute Rejection in the Early Phase After Renal Transplantation. Transplantation 2017, 101, e273–e279. [Google Scholar] [CrossRef] [Green Version]
  86. Egeland, E.J.; Reisæter, A.V.; Robertsen, I.; Midtvedt, K.; Strøm, E.H.; Holdaas, H.; Hartmann, A.; Åsberg, A. High tacrolimus clearance—A risk factor for development of interstitial fibrosis and tubular atrophy in the transplanted kidney: A retrospective single-center cohort study. Transpl. Int. 2019, 32, 257–269. [Google Scholar] [CrossRef] [PubMed]
  87. Nowicka, M.; Górska, M.; Nowicka, Z.; Edyko, K.; Edyko, P.; Wiślicki, S.; Zawiasa-Bryszewska, A.; Strzelczyk, J.; Matych, J.; Kurnatowska, I. Tacrolimus: Influence of the Posttransplant Concentration/Dose Ratio on Kidney Graft Function in a Two-Year Follow-Up. Kidney Blood Press. Res. 2019, 44, 1075–1088. [Google Scholar] [CrossRef] [PubMed]
  88. Thölking, G.; Fortmann, C.; Koch, R.; Gerth, H.U.; Pabst, D.; Pavenstädt, H.; Kabar, I.; Hüsing, A.; Wolters, H.; Reuter, S.; et al. The tacrolimus metabolism rate influences renal function after kidney transplantation. PLoS ONE 2014, 9, e111128. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  89. Thölking, G.; Schütte-Nütgen, K.; Schmitz, J.; Rovas, A.; Dahmen, M.; Bautz, J.; Jehn, U.; Pavenstädt, H.; Heitplatz, B.; Van Marck, V.; et al. A Low Tacrolimus Concentration/Dose Ratio Increases the Risk for the Development of Acute Calcineurin Inhibitor-Induced Nephrotoxicity. J. Clin. Med. 2019, 8, 1586. [Google Scholar] [CrossRef] [Green Version]
  90. Thölking, G.; Siats, L.; Fortmann, C.; Koch, R.; Hüsing, A.; Cicinnati, V.R.; Gerth, H.U.; Wolters, H.H.; Anthoni, C.; Pavenstädt, H.; et al. Tacrolimus Concentration/Dose Ratio is Associated with Renal Function After Liver Transplantation. Ann. Transplant. 2016, 21, 167–179. [Google Scholar] [CrossRef]
  91. Rančić, N.; Dragojević-Simić, V.; Vavić, N.; Kovačević, A.; Šegrt, Z.; Drašković-Pavlović, B.; Mikov, M. Tacrolimus concentration/dose ratio as a therapeutic drug monitoring strategy: The influence of gender and comedication. Vojnosanit. Pregl. 2015, 72, 813–822. [Google Scholar] [CrossRef]
  92. von Einsiedel, J.; Thölking, G.; Wilms, C.; Vorona, E.; Bokemeyer, A.; Schmidt, H.H.; Kabar, I.; Hüsing-Kabar, A. Conversion from Standard-Release Tacrolimus to MeltDose(®) Tacrolimus (LCPT) Improves Renal Function after Liver Transplantation. J. Clin. Med. 2020, 9, 1654. [Google Scholar] [CrossRef] [PubMed]
  93. Schutte-Nutgen, K.; Tholking, G.; Suwelack, B.; Reuter, S. Tacrolimus—Pharmacokinetic Considerations for Clinicians. Curr. Drug Metab. 2018, 19, 342–350. [Google Scholar] [CrossRef] [PubMed]
  94. Rojas, L.; Neumann, I.; Herrero, M.J.; Bosó, V.; Reig, J.; Poveda, J.L.; Megías, J.; Bea, S.; Aliño, S.F. Effect of CYP3A5*3 on kidney transplant recipients treated with tacrolimus: A systematic review and meta-analysis of observational studies. Pharm. J. 2015, 15, 38–48. [Google Scholar] [CrossRef]
  95. Picard, N.; Bergan, S.; Marquet, P.; van Gelder, T.; Wallemacq, P.; Hesselink, D.A.; Haufroid, V. Pharmacogenetic Biomarkers Predictive of the Pharmacokinetics and Pharmacodynamics of Immunosuppressive Drugs. Ther. Drug Monit. 2016, 38 (Suppl. 1), S57–S69. [Google Scholar] [CrossRef]
  96. Passey, C.; Birnbaum, A.K.; Brundage, R.C.; Oetting, W.S.; Israni, A.K.; Jacobson, P.A. Dosing equation for tacrolimus using genetic variants and clinical factors. Br. J. Clin. Pharmacol. 2011, 72, 948–957. [Google Scholar] [CrossRef]
  97. Bartmann, I.; Schütte-Nütgen, K.; Suwelack, B.; Reuter, S. Early postoperative calculation of the tacrolimus concentration-to-dose ratio does not predict outcomes after kidney transplantation. Transpl. Int. 2020, 33, 689–691. [Google Scholar] [CrossRef]
  98. Bardou, F.N.; Guillaud, O.; Erard-Poinsot, D.; Chambon-Augoyard, C.; Thimonier, E.; Vallin, M.; Boillot, O.; Dumortier, J. Tacrolimus exposure after liver transplantation for alcohol-related liver disease: Impact on complications. Transpl. Immunol. 2019, 56, 101227. [Google Scholar] [CrossRef] [PubMed]
  99. Gonschior, A.K.; Christians, U.; Winkler, M.; Linck, A.; Baumann, J.; Sewing, K.F. Tacrolimus (FK506) metabolite patterns in blood from liver and kidney transplant patients. Clin. Chem. 1996, 42, 1426–1432. [Google Scholar] [CrossRef] [Green Version]
  100. Zegarska, J.; Hryniewiecka, E.; Zochowska, D.; Samborowska, E.; Jazwiec, R.; Borowiec, A.; Tszyrsznic, W.; Chmura, A.; Nazarewski, S.; Dadlez, M.; et al. Tacrolimus Metabolite M-III May Have Nephrotoxic and Myelotoxic Effects and Increase the Incidence of Infections in Kidney Transplant Recipients. Transplant. Proc. 2016, 48, 1539–1542. [Google Scholar] [CrossRef]
  101. Zegarska, J.; Hryniewiecka, E.; Zochowska, D.; Samborowska, E.; Jazwiec, R.; Maciej, K.; Nazarewski, S.; Dadlez, M.; Paczek, L. Evaluation of the Relationship Between Concentrations of Tacrolimus Metabolites, 13-O-Demethyl Tacrolimus and 15-O-Demethyl Tacrolimus, and Clinical and Biochemical Parameters in Kidney Transplant Recipients. Transplant. Proc. 2018, 50, 2235–2239. [Google Scholar] [CrossRef] [PubMed]
  102. Vanhove, T.; de Jonge, H.; de Loor, H.; Oorts, M.; de Hoon, J.; Pohanka, A.; Annaert, P.; Kuypers, D.R.J. Relationship between In Vivo CYP3A4 Activity, CYP3A5 Genotype, and Systemic Tacrolimus Metabolite/Parent Drug Ratio in Renal Transplant Recipients and Healthy Volunteers. Drug Metab. Dispos. 2018, 46, 1507–1513. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  103. Trofe-Clark, J.; Brennan, D.C.; West-Thielke, P.; Milone, M.C.; Lim, M.A.; Neubauer, R.; Nigro, V.; Bloom, R.D. Results of ASERTAA, a Randomized Prospective Crossover Pharmacogenetic Study of Immediate-Release Versus Extended-Release Tacrolimus in African American Kidney Transplant Recipients. Am. J. Kidney Dis. 2018, 71, 315–326. [Google Scholar] [CrossRef] [Green Version]
  104. Thölking, G.; Gillhaus, N.H.; Schütte-Nütgen, K.; Pavenstädt, H.; Koch, R.; Suwelack, B.; Reuter, S. Conversion to Everolimus was Beneficial and Safe for Fast and Slow Tacrolimus Metabolizers After Renal Transplantation. J. Clin. Med. 2020, 9, 328. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Table 1. Pharmacokinetics of available formulations of tacrolimus in the United States.
Table 1. Pharmacokinetics of available formulations of tacrolimus in the United States.
Trade NameActive IngredientOral Dose *Pharmacokinetic ParametersHalf-Life
(h) †,§
MetabolismReferences
Cmax
(ng/mL) †
Tmax
(h) ‡
AUC24
(ng h/mL) †
Astagraf XLExtended-release tacrolimus; once daily0.20 mg/kg26.0 ± 13.73.0 (2–24)372 ± 20231.9 ± 10.5 CYP3A4, 3A5[19]
Envarsus XRExtended-release tacrolimus; once daily0.14 mg/kg11.8 ± 7.28.0 (4–24)138 ± 8031.9 ± 10.5CYP3A4, 3A5[20]
HecoriaTacrolimus; twice daily0.20 mg/kg19.2 ± 10.33.0 (N/A)203 ± 4231.9 ± 10.5CYP3A4, 3A5[21]
PrografTacrolimus; twice daily0.20 mg/kg19.2 ± 10.33.0 (N/A)203 ± 4231.9 ± 10.5CYP3A4, 3A5[22]
Cmax, maximum concentration; Tmax, time-to-peak concentration; AUC24, 24-hour area under curve; N/A, not available. * data obtained from kidney transplant patients. † mean, ± standard deviation. ‡ median (interquartile range). § represents elimination half-life measured by radioactivity.
Table 2. Factors associated with alteration of tacrolimus trough levels.
Table 2. Factors associated with alteration of tacrolimus trough levels.
Factor(s) Reducing Tacrolimus Trough LevelFactor(s) Increasing Tacrolimus Trough Level
Factor(s)ExampleDescriptionReferencesFactor(s)ExampleDescriptionReferences
CYP3A4*1B allele-Results in the hyperactivity of CYP3A4, involved in tacrolimus metabolism[39,40]CYP3A5*3 alleleNative AmericansResults in hypoactivity of CYP3A5, involved in tacrolimus metabolism[41,42,43,44]
CYP3A5*3, CYP3A5*6, CYP3A5*7 variantsAfrican AmericansResults in the hyperactivity of CYP3A5, involved in tacrolimus metabolism[45]CYP3A4 inhibitorsKetoconazole (>90% inhibition);
Cyclosporin A, nifedipine (>40% inhibition); Diltiazem, erythromycin, fluconazole, rifampicin (>10% inhibition)
[46]
ABCB1 genotypeChineseEncodes for p-glycoprotein, a protein responsible for the intestinal excretion of tacrolimus [47,48,49]DiarrheaCase reportsIntestinal epithelial cells may be destroyed, abrogating excretion via P-glycoproteins[50,51,52]
High fat meals-Reduces tacrolimus absorption[53]Biliary obstructionCase reports99% of tacrolimus is excreted via bile. Liver dysfunction or bile secretion defects could result in tacrolimus toxicity[54]
There are insufficient data to determine whether celiac disease, gastroparesis, or inflammatory bowel disease would alter tacrolimus bioavailabilityHepatic dysfunctionCirrhosis, hepatic veno-occlusive disease[55]
Table 3. Poor outcomes associated with fast tacrolimus metabolism (low C/D ratio).
Table 3. Poor outcomes associated with fast tacrolimus metabolism (low C/D ratio).
Reported Poor Outcomes Associated with Fast Tacrolimus Metabolism (Low C/D Ratio)
  • Reduced allograft graft function
  • Allograft rejection
  • CNI nephrotoxicity
  • Faster decline in kidney function
  • Reduced death-censored graft survival
  • Dyslipidemia
  • Hypertension
  • Cardiovascular events
  • Post-transplant lymphoproliferative disorders

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Thongprayoon, C.; Hansrivijit, P.; Kovvuru, K.; Kanduri, S.R.; Bathini, T.; Pivovarova, A.; Smith, J.R.; Cheungpasitporn, W. Impacts of High Intra- and Inter-Individual Variability in Tacrolimus Pharmacokinetics and Fast Tacrolimus Metabolism on Outcomes of Solid Organ Transplant Recipients. J. Clin. Med. 2020, 9, 2193. https://doi.org/10.3390/jcm9072193

AMA Style

Thongprayoon C, Hansrivijit P, Kovvuru K, Kanduri SR, Bathini T, Pivovarova A, Smith JR, Cheungpasitporn W. Impacts of High Intra- and Inter-Individual Variability in Tacrolimus Pharmacokinetics and Fast Tacrolimus Metabolism on Outcomes of Solid Organ Transplant Recipients. Journal of Clinical Medicine. 2020; 9(7):2193. https://doi.org/10.3390/jcm9072193

Chicago/Turabian Style

Thongprayoon, Charat, Panupong Hansrivijit, Karthik Kovvuru, Swetha R. Kanduri, Tarun Bathini, Aleksandra Pivovarova, Justin R. Smith, and Wisit Cheungpasitporn. 2020. "Impacts of High Intra- and Inter-Individual Variability in Tacrolimus Pharmacokinetics and Fast Tacrolimus Metabolism on Outcomes of Solid Organ Transplant Recipients" Journal of Clinical Medicine 9, no. 7: 2193. https://doi.org/10.3390/jcm9072193

APA Style

Thongprayoon, C., Hansrivijit, P., Kovvuru, K., Kanduri, S. R., Bathini, T., Pivovarova, A., Smith, J. R., & Cheungpasitporn, W. (2020). Impacts of High Intra- and Inter-Individual Variability in Tacrolimus Pharmacokinetics and Fast Tacrolimus Metabolism on Outcomes of Solid Organ Transplant Recipients. Journal of Clinical Medicine, 9(7), 2193. https://doi.org/10.3390/jcm9072193

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