A Randomized Controlled Trial Comparing the Efficacy of Cyp3a5 Genotype-Based With Body-Weight-Based Tacrolimus Dosing After Living Donor Kidney Transplantation

Pharmacogenetics Guidelines: Overview and Comparison of the DPWG, CPIC, CPNDS, and RNPGx Guidelines

Many studies have shown that the efficacy and risk of side effects of drug treatment is influenced by genetic variants. Evidence based guidelines are essential for implementing pharmacogenetic knowledge in daily clinical practice to optimize pharmacotherapy of individual patients. A literature search was performed to select committees developing guidelines with recommendations being published in English. The Dutch Pharmacogenetics Working Group (DPWG), the Clinical Pharmacogenetics Implementation Consortium (CPIC), the Canadian Pharmacogenomics Network for Drug Safety (CPNDS), and the French National Network (Réseau) of Pharmacogenetics (RNPGx) were selected. Their guidelines were compared with regard to the methodology of development, translation of genotypes to predicted phenotypes, pharmacotherapeutic recommendations and recommendations on genotyping. A detailed overview of all recommendations for gene-drug combinations is given. The committees have similar methodologies of guideline development. However, the objectives differed at the start of their projects, which have led to unique profiles and strengths of their guidelines. DPWG and CPIC have a main focus on pharmacotherapeutic recommendations for a large number of drugs in combination with a patient’s genotype or predicted phenotype. DPWG, CPNDS and RNPGx also recommend on performing genetic testing in daily clinical practice, with RNPGx even describing specific clinical settings or medical conditions for which genotyping is recommended. Discordances exist, however committees also initiated harmonizing projects. The outcome of a consensus project was to rename “extensive metabolizer (EM)” to “normal metabolizer (NM)”. It was decided to translate a CYP2D6 genotype with one nonfunctional allele (activity score 1.0) into the predicted phenotype of intermediate metabolizer (IM). Differences in recommendations are the result of the methodologies used, such as assessment of dose adjustments of tricyclic antidepressants. In some cases, indication or dose specific recommendations are given for example for clopidogrel, codeine, irinotecan. The following drugs have recommendations on genetic testing with the highest level: abacavir (HLA), clopidogrel (CYP2C19), fluoropyrimidines (DPYD), thiopurines (TPMT), irinotecan (UGT1A1), codeine (CYP2D6), and cisplatin (TPMT). The guidelines cover many drugs and genes, genotypes, or predicted phenotypes. Because of this and their unique features, considering the totality of guidelines are of added value. In conclusion, many evidence based pharmacogenetics guidelines with clear recommendations are available for clinical decision making by healthcare professionals, patients and other stakeholders.

Pharmacogenomics in kidney transplant recipients and potential for integration into practice

WHAT IS KNOWN AND OBJECTIVE

Pharmacogenomic biomarkers are now used in many clinical care settings and represent one of the successes of precision medicine. Genetic variants are associated with pharmacokinetic and pharmacodynamic changes leading to medication adverse effects and changes in clinical response. Actionable pharmacogenomic variants are common in transplant recipients and have implications for medications used in transplant, but yet are not broadly incorporated into practice.

METHODS

From the Clinical Pharmacogenetics Implementation Consortium and Dutch Pharmacogenetics Working Group guidelines, and PharmGKB databases, 12 pharmacogenomic genes with 30 variants were selected and used to create diplotypes and actionable pharmacogenomic phenotypes. A total of 853 kidney allograft recipients who had genomic information available from a genome-wide association study were included.

RESULTS

Each recipient had at least one actionable pharmacogenomic diplotype/phenotype, whereas the majority (58%) had three or four actionable diplotypes/phenotypes and 17.4% had five or more among the 12 genes. The participants carried actionable diplotypes/phenotypes for multiple medications, including tacrolimus, azathioprine, clopidogrel, warfarin, simvastatin, voriconazole, antidepressants and proton-pump inhibitors.

WHAT IS NEW AND CONCLUSION

Pharmacogenomic variants are common in transplant recipients, and transplant recipients receive medications that have actionable variants.

CLINICAL TRIAL

Genomics of Transplantation, clinicaltrials.gov (NCT01714440).

Monitoring the tacrolimus concentration in peripheral blood mononuclear cells of kidney transplant recipients

Aims

Tacrolimus is a critical dose drug and to avoid under‐ and overexposure, therapeutic drug monitoring is standard practice. However, rejection and drug‐related toxicity occur despite whole‐blood tacrolimus pre‐dose concentrations ([Tac]_blood) being on target. Monitoring tacrolimus concentrations at the target site (within peripheral blood mononuclear cells; [Tac]_cells) may better correlate with drug‐efficacy. The aim of this study was to (1) investigate the relationship between [Tac]_blood and [Tac]_cells, (2) identify factors affecting the tacrolimus distribution in cells and whole‐blood, and (3) study the relationship between [Tac]_cells and clinical outcomes after kidney transplantation.

Methods

A total of 175 renal transplant recipients were prospectively followed. [Tac]_blood and [Tac]_cells were determined at Months 3, 6 and 12 post‐transplantation. Patients were genotyped for ABCB1 1199G>A and 3435C>T, CYP3A4 15389C>T, and CYP3A5 6986G>A. Data on rejection and tacrolimus‐related nephrotoxicity and post‐transplant diabetes mellitus were collected.

Results

Correlations between [Tac]_blood and [Tac]_cells were moderate to poor (Spearman's r = 0.31; r = 0.41; r = 0.61 at Months 3, 6 and 12, respectively). The [Tac]_cells/[Tac]_blood ratio was stable over time in most patients (median intra‐patient variability 39.0%; range 3.5%–173.2%). Age, albumin and haematocrit correlated with the [Tac]_cells/[Tac]_blood ratio. CYP3A5 and CYP3A4 genotype combined affected both dose‐corrected [Tac]_blood and [Tac]_cells. ABCB1 was not significantly related to tacrolimus distribution. Neither [Tac]_blood nor [Tac]_cells correlated with clinical outcomes.

Conclusions

The correlation between [Tac]_blood and [Tac]_cells is poor. Age, albumin and haematocrit correlate with the [Tac]_cells/[Tac]_blood ratio, whereas genetic variation in ABCB1, CYP3A4 and CYP3A5 do not. Neither [Tac]_blood nor [Tac]_cells correlated with clinical outcomes.

Predictors of tacrolimus pharmacokinetic variability: current evidences and future perspectives

INTRODUCTION

In kidney transplantation, tacrolimus (TAC) is at the cornerstone of current immunosuppressive strategies. Though because of its narrow therapeutic index, it is critical to ensure that TAC levels are maintained within this sharp window through reactive adjustments. This would allow maximizing efficiency while limiting drug-associated toxicity. However, TAC high intra- and inter-patient pharmacokinetic (PK) variability makes it more laborious to accurately predict the appropriate dosage required for a given patient.

AREAS COVERED

This review summarizes the state-of-the-art knowledge regarding drug interactions, demographic and pharmacogenetics factors as predictors of TAC PK. We provide a scoring index for each association to grade its relevance and we present practical recommendations, when possible for clinical practice.

EXPERT OPINION

The management of TAC concentration in transplanted kidney patients is as critical as it is challenging. Recommendations based on rigorous scientific evidences are lacking as knowledge of potential predictors remains limited outside of DDIs. Awareness of these limitations should pave the way for studies looking at demographic and pharmacogenetic factors as well as gut microbiota composition in order to promote tailored treatment plans. Therapeutic approaches considering patients' clinical singularities may help allowing to maintain appropriate concentration of TAC.

Serum magnesium, hepatocyte nuclear factor 1β genotype and post-transplant diabetes mellitus: a prospective study

BACKGROUND

Retrospective studies suggest that tacrolimus-induced hypomagnesaemia is a risk factor for post-transplant diabetes mellitus (PTDM), but prospective studies are lacking.

METHODS

This was a prospective study with measurements of serum magnesium and tacrolimus at pre-specified time points in the first year after living donor kidney transplantation (KT). The role of single nucleotide polymorphisms (SNPs) in hepatocyte nuclear factor 1β (HNF1β) was also explored because HNF1β regulates insulin secretion and renal magnesium handling. Repeated measurement and regression analyses were used to analyse associations with PTDM.

RESULTS

In our cohort, 29 out of 167 kidney transplant recipients developed PTDM after 1 year (17%). Higher tacrolimus concentrations were significantly associated with lower serum magnesium and increased risk of hypomagnesaemia. Patients who developed PTDM had a significantly lower serum magnesium trajectory than patients who did not develop PTDM. In multivariate analysis, lower serum magnesium, age and body mass index were independent risk factors for PTDM. In recipients, the HNF1β SNP rs752010 G > A significantly increased the risk of PTDM [odds ratio (OR) = 2.56, 95% confidence interval (CI) 1.05-6.23] but not of hypomagnesaemia. This association lost significance after correction for age and sex (OR = 2.24, 95% CI 0.90-5.57). No association between HNF1β SNPs and PTDM was found in corresponding donors.

CONCLUSIONS

A lower serum magnesium in the first year after KT is an independent risk factor for PTDM. The HNF1β SNP rs752010 G > A may add to this risk through an effect on insulin secretion rather than hypomagnesaemia, but its role requires further confirmation.

Beyond Single Nucleotide Polymorphisms: CYP3A5∗3∗6∗7 Composite and ABCB1 Haplotype Associations to Tacrolimus Pharmacokinetics in Black and White Renal Transplant Recipients

Interpatient variability in tacrolimus pharmacokinetics is attributed to metabolism by cytochrome P-450 3A5 (CYP3A5) isoenzymes and membrane transport by P-glycoprotein. Interpatient pharmacokinetic variability has been associated with genotypic variants for both CYP3A5 or ABCB1. Tacrolimus pharmacokinetics was investigated in 65 stable Black and Caucasian post-renal transplant patients by assessing the effects of multiple alleles in both CYP3A5 and ABCB1. A metabolic composite based upon the CYP3A5 polymorphisms: ∗3(rs776746), ∗6(10264272), and ∗7(41303343), each independently responsible for loss of protein expression was used to classify patients as extensive, intermediate and poor metabolizers. In addition, the role of ABCB1 on tacrolimus pharmacokinetics was assessed using haplotype analysis encompassing the single nucleotide polymorphisms: 1236C > T (rs1128503), 2677G > T/A(rs2032582), and 3435C > T(rs1045642). Finally, a combined analysis using both CYP3A5 and ABCB1 polymorphisms was developed to assess their inter-related influence on tacrolimus pharmacokinetics. Extensive metabolizers identified as homozygous wild type at all three CYP3A5 loci were found in 7 Blacks and required twice the tacrolimus dose (5.6 ± 1.6 mg) compared to Poor metabolizers [2.5 ± 1.1 mg (P < 0.001)]; who were primarily Whites. These extensive metabolizers had 2-fold faster clearance (P < 0.001) with 50% lower AUC∗ (P < 0.001) than Poor metabolizers. No differences in C12 h were found due to therapeutic drug monitoring. The majority of blacks (81%) were classified as either Extensive or Intermediate Metabolizers requiring higher tacrolimus doses to accommodate the more rapid clearance. Blacks who were homozygous for one or more loss of function SNPS were associated with lower tacrolimus doses and slower clearance. These values are comparable to Whites, 82% of who were in the Poor metabolic composite group. The ABCB1 haplotype analysis detected significant associations of the wildtype 1236T-2677T-3435T haplotype to tacrolimus dose (P = 0.03), CL (P = 0.023), CL/LBW (P = 0.022), and AUC∗ (P = 0.078). Finally, analysis combining CYP3A5 and ABCB1 genotypes indicated that the presence of the ABCB1 3435 T allele significantly reduced tacrolimus clearance for all three CPY3A5 metabolic composite groups. Genotypic associations of tacrolimus pharmacokinetics can be improved by using the novel composite CYP3A5∗3∗4∗5 and ABCB1 haplotypes. Consideration of multiple alleles using CYP3A5 metabolic composites and drug transporter ABCB1 haplotypes provides a more comprehensive appraisal of genetic factors contributing to interpatient variability in tacrolimus pharmacokinetics among Whites and Blacks.

National survey of physicians' perspectives on pharmacogenetic testing in solid organ transplantation

INTRODUCTION

Our objective was to evaluate physicians' perspectives on the clinical utility of pharmacogenetic (PGx) testing in kidney, liver, heart, and lung transplantation (KLHL-Tx).

METHODS

A 36-question web-based survey was developed and administered to medical and surgical directors of US KLHL-Tx centers.

RESULTS

There were 82 respondents (10% response rate). The majority were men (78%), non-Hispanic whites (70%), medical directors (72%), and kidney transplant physicians (35%). Although 78% of respondents reported having some PGx education, most reported lack of confidence in their PGx knowledge and ability to apply a PGx test. Participants reported mixed views about the clinical utility of PGx testing-most agreed with the efficacy of PGx testing, but not the benefits relative to the risks or standard of care. While 55% reported that testing was available at their institution, only 38% ordered a PGx test in the past year, most commonly thiopurine-S-methyltransferase. Physician-reported barriers to PGx implementation included uncertainty about the clinical value of PGx testing and patient financial burden.

CONCLUSION

Together, our findings suggest prospective PGx research and pilot implementation programs are needed to elucidate the clinical utility and value of PGx in KLHL-Tx. These initiatives should include educational efforts to inform the use of PGx testing.

Protein and calorie restriction may improve outcomes in living kidney donors and kidney transplant recipients

Previously, we and others showed that dietary restriction protects against renal ischemia-reperfusion injury in animals. However, clinical translation of preoperative diets is scarce, and in the setting of kidney transplantation these data are lacking. In this pilot study, we investigated the effects of five days of a preoperative protein and caloric dietary restriction (PCR) diet in living kidney donors on the perioperative effects in donors, recipients and transplanted kidneys. Thirty-five kidney donors were randomized into either the PCR, 30% calorie and 80% protein reduction, or control group without restrictions. Adherence to the diet and kidney function in donors and their kidney recipients were analyzed. Perioperative kidney biopsies were taken in a selected group of transplanted kidneys for gene expression analysis. All donors adhered to the diet. From postoperative day 2 up until month 1, kidney function of donors was significantly better in the PCR-group. PCR-donor kidney recipients showed significantly improved kidney function and lower incidence of slow graft function and acute rejection. PCR inhibited cellular immune response pathways and activated stress-resistance signaling. These observations are the first to show that preoperative dietary restriction induces postoperative recovery benefits in humans and may be beneficial in clinical settings involving ischemia-reperfusion injury.

Pharmacogenetics of immunosuppressant drugs: A new aspect for individualized therapy

In recent years, pharmacogenetics has emerged as an important tool for choosing the right immunosuppressant drug and its appropriate dose. Indeed, pharmacogenetics may exert its action on immunosuppressant drugs at three levels. Pharmacogenetics identifies and studies the genes involved in encoding the proteins involved in drug pharmacokinetics and in encoding the enzymes involved in drug degradation. Pharmacogenetics is also relevant in encoding the enzymes and proteins involved in codifying the transmembrane proteins involved in transmembrane passage favoring the absorption and intracellular action of several immunosuppressants. Pharmacogenetics concern the variability of genes encoding the proteins involved as immunosuppressant triggers in the pharmacodynamic pathways. Of course, not all genes have been discovered and studied, but some of them have been clearly examined and their relevance together with other factors such as age and race has been defined. Other genes on the basis of relevant studies have been proposed as good candidates for future studies. Unfortunately, to date, clear conclusions may be drawn only for those drugs that are metabolized by CYP3A5 and its genotyping before kidney, heart and lung transplantation is recommended. The conclusions of the studies on the recommended candidate genes, together with the development of omics techniques could in the future allow us to choose the right dose of the right immunosuppressant for the right patient.

Interventions to Prevent Nonmelanoma Skin Cancers in Recipients of a Solid Organ Transplant: Systematic Review of Randomized Controlled Trials

BACKGROUND

Organ transplant recipients are at high risk of developing skin cancer. The benefits and harms of interventions to prevent nonmelanoma skin cancer in solid organ transplant recipients have not been summarized.

METHODS

We searched MEDLINE, Embase, and CENTRAL through April 2018. Risk of bias was assessed using the Cochrane tool, and evidence certainty was evaluated using the Grades of Recommendation, Assessment, Development, and Evaluation process. Prespecified outcomes were nonmelanoma skin cancer, clearance and prevention of keratotic skin lesions, and intervention-specific adverse events.

RESULTS

Ninety-two trials (20 012 participants) were included. The evaluated treatments were cancer-specific interventions (acitretin, imiquimod, photodynamic therapy, nicotinamide, topical diclofenac, and selenium) and immunosuppression regimes (azathioprine, mycophenolate mofetil, calcineurin inhibitors, mammalian target of rapamycin [mTOR] inhibitors, belatacept, induction agents, and withdrawal of calcineurin inhibitors or corticosteroids). Effects on nonmelanoma skin cancer were uncertain for photodynamic therapy (3 trials, 93 participants, risk ratio [RR] 1.42 [95% confidence interval (CI), 0.65-3.11]; low certainty evidence), nicotinamide (2 trials, 60 participants), acitretin (2 trials, 61 participants), and imiquimod (1 trial, 20 participants) compared to control. mTOR inhibitors probably reduced skin cancer compared to calcineurin inhibitors (12 trials, 2225 participants, RR 0.62 [95% CI, 0.45-0.85]; moderate certainty evidence). Photodynamic therapy may cause pain at the treatment site (4 trials, 95 patients, RR 17.09 [95% CI, 4.22-69.26]; low certainty evidence).

CONCLUSIONS

There is limited evidence for the efficacy and safety of specific treatments to prevent nonmelanoma skin cancers among solid organ transplant recipients.

Early Tacrolimus Concentrations After Lung Transplant Are Predicted by Combined Clinical and Genetic Factors and Associated With Acute Kidney Injury

Tacrolimus exhibits unpredictable pharmacokinetics (PKs) after lung transplant, partly explained by cytochrome P450 (CYP)-enzyme polymorphisms. However, whether exposure variability during the immediate postoperative period affects outcomes is unknown, and pharmacogenetic dosing may be limited by residual PK variability. We estimated adjusted associations between early postoperative tacrolimus concentrations and acute kidney injury (AKI) and acute cellular rejection (ACR), and identified clinical and pharmacogenetic factors that explain postoperative tacrolimus concentration variability in 484 lung transplant patients. Increasing tacrolimus concentration was associated with higher AKI risk (hazard ratio (HR) 1.54; 95% confidence interval (CI) 1.20-1.96 per 5-mg/dL); and increasing AKI severity (odds ratio 1.29; 95% CI 1.04-1.60 per 5-mg/dL), but not ACR (HR 1.02; 95% CI 0.73-1.42). A model with clinical and pharmacogenetic factors explained 42% of concentration variance compared with 19% for pharmacogenetic factors only. Early tacrolimus exposure was independently associated with AKI after lung transplantation, but not ACR. Clinical factors accounted for substantial residual tacrolimus concentration variability not explained by CYP-enzyme polymorphisms.

Optimization of tacrolimus in kidney transplantation: New pharmacokinetic perspectives

Tacrolimus is the cornerstone of immunosuppressive therapy after kidney transplantation (KT), but its use is complicated by a narrow therapeutic index and high inter- and intra-patient pharmacokinetic variability. There are three available oral formulations of tacrolimus: immediate-release tacrolimus (IR-Tac), extended-release tacrolimus (ER-Tac) and a MeltDose® (LCPT) formulation, the latter favoring a prolonged drug release and increased bioavailability. The time-concentration curves of these formulations are different. Compared with IR-Tac and ER-Tac, LCPT has a relatively flat pharmacokinetic profile with less fluctuation between trough and peak exposures, and a delayed peak concentration. This translates to a more stable delivery of tacrolimus and may alleviate the risk of underexposure and allograft rejection or overexposure and toxicity. The once-daily formulation of both ER-TAC and LCPT may also offer a potential advantage on patient adherence. Fast metabolizers of tacrolimus, the elderly, and human leukocyte antigen-sensitized patients are at risk of poorer outcomes after KT, possibly associated with a different exhibited pharmacokinetics of tacrolimus or different requirements in terms of exposure. Simple, practical strategies are needed to identify patients at risk of suboptimal KT outcomes and those who would benefit from a more proactively personalized approach to tacrolimus treatment. This review aims to increase awareness of the link between the pharmacokinetics of oral tacrolimus formulations and the clinical needs of patients after KT, particularly among those who have clinically significant pharmacokinetic variation of tacrolimus.

Defining a threshold for tacrolimus intra-patient variability associated with late acute cellular rejection in paediatric kidney transplant recipients

BACKGROUND

Late acute cellular rejection (LACR) is associated with poorer graft outcomes and non-adherence. Non-adherence to tacrolimus can be indirectly assessed by the intra-patient variability (IPV) of tacrolimus trough levels. The threshold of IPV associated with rejection is not known.

METHODS

We conducted a case-control study comparing 25 patients with biopsy-proven LACR against 25 stable controls matched for age group, primary diagnosis and time post-transplant. IPV was calculated using coefficient of variance (CV) and mean absolute deviation (MAD) using tacrolimus levels in the preceding 12 months. We also assessed the percentage time for tacrolimus levels < 4 μg/L (Tac < 4) and the concentration/weight-adjusted dose (C/D) ratio as a proxy marker of tacrolimus metaboliser status.

RESULTS

LACR patients had higher CV (median, IQR 44%, 36-61% v. 24%, 19-35%, p < 0.0001) and higher MAD (33%, 25-48% v. 19%, 15-26%, p < 0.0001). The MAD was less affected by outlying tacrolimus results. Receiver operating curve analysis of the MAD resulted in a sensitivity of 76% and specificity of 76% at a threshold of 26% (AUC 0.85, p < 0.05). LACR patients had more Tac < 4 (50% v. 26%, p < 0.05). There was no difference in C/D suggesting that good IPV can be maintained in fast metabolisers. Patients with LACR had significantly increased creatinine at 12-month follow-up despite treatment (108 v. 5 umol/L increase from baseline) and four patients lost their allograft.

CONCLUSIONS

Monitoring of tacrolimus IPV using the MAD may be a clinical marker for LACR. A threshold IPV of 26% can potentially be used as a therapeutic target pending further validation studies.

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

Background: 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, and CYP3A5*3 alleles and the ABCB1 variants 1236C>T, 2677G>T/A, and 3435C>T for their impact on exposure and dose requirement. Relevant clinical outcome measures such as acute rejection within the first year after transplantation, delayed graft function, and renal function at discharge (estimated glomerular filtration rate) were evaluated. Results: Extensive metabolizer (n = 17, CYP3A4*1/*1 carriers with at least one CYP3A5*1 allele) showed significantly higher tacrolimus dose requirement (P = 0.004) compared with 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 (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 with non-expressers again at onset of therapy. Using the log additive genetic model, the area under the curve for the total observation period up to 16 days was significantly associated with the CYP3A5*3 genotype (P = 3.34 × 10-4) as well as with the IM or extensive metabolizer phenotype (P = 1.54 × 10-4), even after adjustment for multiple testing. Heterozygous carriers for CYP3A4*22 showed significantly higher areas under the curve than the CYP3A4*1/*1 genotype in the second week post-transplantation (adjusted P = 0.016). Regarding clinical outcomes, acute rejection was significantly associated with human leukocyte antigen 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 incidende of delayed graft function (OR 7.15, 95% CI 2.23, 30.46, adjusted P = 0.0008) and a lower estimated glomerular filtration rate 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.

Comparison of Tacrolimus Starting Doses Based on CYP3A5 Phenotype or Genotype in Kidney Transplant Recipients

BACKGROUND

Selection of expected phenotypes (ie, expressers/non-expressers) is currently used in CYP3A5*3 genotype-based tacrolimus dosing. The authors assessed whether a dosing regimen based on the 3 CYP3A5 genotypes may reduce the occurrence of inadequate exposure.

METHODS

Tacrolimus whole blood trough levels (C ₀) were retrieved from a retrospective cohort of 100 kidney transplant recipients treated with a starting dose of 0.15 (non-expressers) or 0.30 (expressers) mg/kg/d. The authors evaluated the occurrence of overexposures (12 < C ₀ < 20 ng/mL) or toxic concentrations (C ₀ ≥ 20 ng/mL). These results were used to set up a new strategy based on the 3 distinct CYP3A5 genotypes, which relevance was evaluated in a prospective cohort of 107 patients.

RESULTS

In the retrospective cohort, non-expressers exhibited frequent overexposure (63.6%) or toxic C ₀ (20.8%). Among expressers, none of the homozygous *1 carriers exhibited overexposure contrary to 25% of the heterozygotes. Based on these results, new tacrolimus starting doses were set at 0.10, 0.20, and 0.30 mg/kg/d for CYP3A5*3/*3, CYP3A5*1/*3, and CYP3A5*1/*1 genotypes, respectively. Tacrolimus overexposure was reduced in the CYP3A5*3/*3 group (63.6% vs 40%, P = .0038). None of the heterozygous patients exhibited toxic tacrolimus C ₀. Clinical outcomes were not different between the 2 periods, whatever the genotype. Our results indicate that the best tacrolimus exposure was obtained for doses of 0.10, 0.20, and 0.20 mg/kg/d for CYP3A5*3/3, CYP3A5*1/*3, and CYP3A5*1/*1, respectively.

CONCLUSIONS

Our results confirm that selecting tacrolimus dosing regimen according to the expected phenotype is appropriate, but that lower than currently recommended doses may be preferable.

A Population Pharmacokinetic Model to Predict the Individual Starting Dose of Tacrolimus Following Pediatric Renal Transplantation

Background

Multiple clinical, demographic, and genetic factors affect the pharmacokinetics of tacrolimus in children, yet in daily practice, a uniform body-weight based starting dose is used. It can take weeks to reach the target tacrolimus pre-dose concentration.

Objectives

The objectives of this study were to determine the pharmacokinetics of tacrolimus immediately after kidney transplantation and to find relevant parameters for dose individualization using a population pharmacokinetic analysis.

Methods

A total of 722 blood samples were collected from 46 children treated with tacrolimus over the first 6 weeks after renal transplantation. Non-linear mixed-effects modeling (NONMEM^®) was used to develop a population pharmacokinetic model and perform a covariate analysis. Simulations were performed to determine the optimal starting dose and to develop dosing guidelines.

Results

The data were accurately described by a two-compartment model with allometric scaling for bodyweight. Mean tacrolimus apparent clearance was 50.5 L/h, with an inter-patient variability of 25%. Higher bodyweight, lower estimated glomerular filtration rate, and higher hematocrit levels resulted in lower total tacrolimus clearance. Cytochrome P450 3A5 expressers and recipients who received a kidney from a deceased donor had a significantly higher tacrolimus clearance. The model was successfully externally validated. In total, these covariates explained 41% of the variability in clearance. From the significant covariates, the cytochrome P450 3A5 genotype, bodyweight, and donor type were useful to adjust the starting dose to reach the target pre-dose concentration. Dosing guidelines range from 0.27 to 1.33 mg/kg/day.

Conclusion

During the first 6 weeks after transplantation, the tacrolimus weight-normalized starting dose should be higher in pediatric kidney transplant recipients with a lower bodyweight, those who express the cytochrome P450 3A5 genotype, and those who receive a kidney from a deceased donor.

Therapeutic concentration achievement and allograft survival comparing usage of conventional tacrolimus doses and CYP3A5 genotype-guided doses in renal transplantation patients

AIMS

Although cytochromeP450(CYP)3A5 gene polymorphism affects personalized tacrolimus doses, there is no consensus as to whether CYP3A5 genotypes should be determined to adjust the doses. The aims were to compare the therapeutic ranges and clinical outcomes between the conventional and genotype-guided tacrolimus doses.

METHODS

This randomized controlled study compared 63 cases of the conventional tacrolimus dose group (0.1 mg/kg/day) with 62 cases of the genotype-guided doses group of 0.125, 0.1 and 0.08 mg/kg for CYP3A5*1/*1, *1/*3, and *3/*3 genotypes for the initial 3 days of kidney transplantation. After day 3, dose adjustment occurred in both groups to achieve therapeutic concentrations.

RESULTS

The genotype-guided group had an increased proportion of patients with tacrolimus concentrations in the therapeutic range at the steady state on day 3 (40.3 vs 23.8%, P = .048). A lower proportion of over-therapeutic concentration patients was noted in the genotype-guided group in the CYP3A5*3/*3 genotype (9.7 vs 27%, P = .013). Unexpectedly, more delayed graft functions (DGFs) were in the genotype-guided group (41.9 vs 22.2%, P = .018) especially in the CYP3A5*1/*1 participants who might have had an aggravated DGF by a longer ischaemic time and higher serum donor creatinine levels than in the control group. There were no significant differences of glomerular filtration rates or graft or patient survivals over a median 37-month follow-up period.

CONCLUSIONS

Determination of the CYP3A5 genotype improved therapeutic range achievement. CYP3A5*1/*1 patients who have high risks of DGF should be closely monitored because of an increased risk of DGF and reduced glomerular filtration rate with high tacrolimus doses.

Drug-metabolizing enzymes CYP3A as a link between tacrolimus and vitamin D in renal transplant recipients: is it relevant in clinical practice?

CYP3A enzymes are involved in the metabolism of calcineurin inhibitor tacrolimus as well as vitamin D. In this review, we summarize the clinical aspects of CYP3A-mediated metabolism of tacrolimus and vitamin D with emphasis on the influence of single-nucleotide polymorphisms on tacrolimus disposition. We describe the utility of 4β hydroxycholesterol as a marker of CYP3A activity. Then, we discuss the possible interaction between calcineurin inhibitors and vitamin D in solid organ transplant recipients. Also, we review other mechanisms which may contribute to side effects of calcineurin inhibitors on bone. Lastly, suggestions for future research and clinical perspectives are discussed.

Cases in Precision Medicine: The Role of Pharmacogenetics in Precision Prescribing

Pharmacogenetics may help physicians deliver individualized treatments based on how a person's genes affect a drug's effects and metabolism. This information can help prevent adverse events or improve drug efficacy by enabling the physician to optimize dosage or to avoid a medication with adverse reactions and to prescribe an alternative therapy. This article discusses the current clinical utility of pharmacogenetic testing in the context of a patient who requires anticoagulation with warfarin.

The Number of Donor-Specific IL-21 Producing Cells Before and After Transplantation Predicts Kidney Graft Rejection

Interleukin (IL)-21 supports induction and expansion of CD8⁺ T cells, and can also regulate the differentiation of B cells into antibody-producing plasma cells. We questioned whether the number of circulating donor-specific IL-21 producing cells (pc) can predict kidney transplant rejection, and evaluated this in two different patient cohorts. The first analysis was done on pre-transplantation samples of 35 kidney transplant recipients of whom 15 patients developed an early acute rejection. The second study concerned peripheral blood mononuclear cell (PBMC) samples from 46 patients obtained at 6 months after kidney transplantation of whom 13 developed late rejection. Significantly higher frequencies of donor-specific IL-21 pc were found by Elispot assay in both patients who developed early and late rejection compared to those without rejection. In addition, low frequencies of donor-specific IL-21 pc were associated with higher rejection-free survival. Moreover, low pre-transplant donor-specific IL-21 pc numbers were associated with the absence of anti-HLA antibodies. Donor-reactive IL-21 was mainly produced by CD4⁺ T cells, including CD4⁺ follicular T helper cells. In conclusion, the number of donor-specific IL-21 pc is associated with an increased risk of both early and late rejection, giving it the potential to be a new biomarker in kidney transplantation.

A population pharmacokinetic model to predict the individual starting dose of tacrolimus in adult renal transplant recipients

Aims

The aims of this study were to describe the pharmacokinetics of tacrolimus immediately after kidney transplantation, and to develop a clinical tool for selecting the best starting dose for each patient.

Methods

Data on tacrolimus exposure were collected for the first 3 months following renal transplantation. A population pharmacokinetic analysis was conducted using nonlinear mixed‐effects modelling. Demographic, clinical and genetic parameters were evaluated as covariates.

Results

A total of 4527 tacrolimus blood samples collected from 337 kidney transplant recipients were available. Data were best described using a two‐compartment model. The mean absorption rate was 3.6 h⁻¹, clearance was 23.0 l h^–1 (39% interindividual variability, IIV), central volume of distribution was 692 l (49% IIV) and the peripheral volume of distribution 5340 l (53% IIV). Interoccasion variability was added to clearance (14%). Higher body surface area (BSA), lower serum creatinine, younger age, higher albumin and lower haematocrit levels were identified as covariates enhancing tacrolimus clearance. Cytochrome P450 (CYP) 3A5 expressers had a significantly higher tacrolimus clearance (160%), whereas CYP3A4*22 carriers had a significantly lower clearance (80%). From these significant covariates, age, BSA, CYP3A4 and CYP3A5 genotype were incorporated in a second model to individualize the tacrolimus starting dose: Dosemg=222nghml–1*22.5lh–1*1.0ifCYP3A5*3/*3or1.62ifCYP3A5*1/*3orCYP3A5*1/*1*1.0ifCYP3A4*1or unknownor0.814ifCYP3A4*22*Age56−0.50*BSA1.930.72/1000Both models were successfully internally and externally validated. A clinical trial was simulated to demonstrate the added value of the starting dose model.

Conclusions

For a good prediction of tacrolimus pharmacokinetics, age, BSA, CYP3A4 and CYP3A5 genotype are important covariates. These covariates explained 30% of the variability in CL/F. The model proved effective in calculating the optimal tacrolimus dose based on these parameters and can be used to individualize the tacrolimus dose in the early period after transplantation.

The impact of tacrolimus exposure on extrarenal adverse effects in adult renal transplant recipients

AIMS

Tacrolimus has been associated with notable extrarenal adverse effects (AEs), which are unpredictable and impact patient morbidity. The association between model-predicted tacrolimus exposure metrics and standardized extrarenal AEs in stable renal transplant recipients was investigated and a limited sampling strategy (LSS) was developed to predict steady-state tacrolimus area under the curve over a 12-h dosing period (AUC_ss,0-12h ).

METHODS

All recipients receiving tacrolimus and mycophenolic acid ≥6 months completed a 12-h cross-sectional observational pharmacokinetic-pharmacodynamic study. Patients were evaluated for the presence of individual and composite gastrointestinal, neurological, and aesthetic AEs during the study visit. The associations between AEs and tacrolimus exposure metrics generated from a published population pharmacokinetic model were investigated using a logistic regression analysis in NONMEM 7.3. An LSS was determined using a Bayesian estimation method with the same patients.

RESULTS

Dose-normalized tacrolimus AUC_ss,0-12h and apparent clearance were independently associated with diarrhoea, dyspepsia, insomnia and neurological AE ratio. Dose-normalized tacrolimus maximum concentration was significantly correlated with skin changes and acne. No AE associations were found with trough concentrations. Using limited sampling at 0, 2h; 0, 1, 4h; and 0, 1, 2, 4h provided a precise and unbiased prediction of tacrolimus AUC (root mean squared prediction error < 10%), which was not well characterized using trough concentrations only (root mean squared prediction error >15%).

CONCLUSIONS

Several AEs (i.e. diarrhoea, dyspepsia, insomnia and neurological AE ratio) were associated with tacrolimus dose normalized AUC_ss,0-12h and clearance. Skin changes and acne were associated with dose-normalized maximum concentrations. To facilitate clinical implementation, a LSS was developed to predict AUC_ss,0-12h values using sparse patient data to efficiently assess projected immunosuppressive exposure and potentially minimize AE manifestations.

Clinical aspects of tacrolimus use in paediatric renal transplant recipients

The calcineurin inhibitor tacrolimus, cornerstone of most immunosuppressive regimens, is a drug with a narrow therapeutic window: underexposure can lead to allograft rejection and overexposure can result in an increased incidence of infections, toxicity and malignancies. Tacrolimus is metabolised in the liver and intestine by the cytochrome P450 3A (CYP3A) isoforms CYP3A4 and CYP3A5. This review focusses on the clinical aspects of tacrolimus pharmacodynamics, such as efficacy and toxicity. Factors affecting tacrolimus pharmacokinetics, including pharmacogenetics and the rationale for routine CYP3A5*1/*3 genotyping in prospective paediatric renal transplant recipients, are also reviewed. Therapeutic drug monitoring, including pre-dose concentrations and pharmacokinetic profiles with the available "reference values", are discussed. Factors contributing to high intra-patient variability in tacrolimus exposure and its impact on clinical outcome are also reviewed. Lastly, suggestions for future research and clinical perspectives are discussed.

Immunomics of Renal Allograft Acute T Cell-Mediated Rejection Biopsies of Tacrolimus- and Belatacept-Treated Patients

Supplemental digital content is available in the text.

Background

Belatacept-based therapy in kidney transplant recipient has been shown to increase long-term renal allograft and patient survival compared with calcineurin inhibitor–based therapy, however, with an increased risk of acute T cell-mediated rejection (aTCMR). An improved understanding of costimulation blockade-resistant rejections could lead to a more personalized approach to belatacept therapy. Here, immunomic profiles of aTCMR biopsies of patients treated with either tacrolimus or belatacept were compared.

Methods

Formalin-fixed paraffin-embedded renal transplant biopsies were used for immunohistochemistry and gene expression analysis using the innovative NanoString technique. To validate NanoString, transcriptomic profiles of patients with and without biopsy-proven aTCMR were compared. Biopsies from 31 patients were studied: 14 tacrolimus-treated patients with aTCMR, 11 belatacept-treated patients with aTCMR, and 6 controls without rejection.

Results

A distinct pattern was seen in biopsies with aTCMR compared to negative controls: 78 genes had a higher expression in the aTCMR group (false discovery rate P value <.05 to 1.42e–05). The most significant were T cell-associated genes (CD3, CD8, and CD4; P < 1.98e-04), γ-interferon-inducible genes (CCL5, CXCL9, CXCL11, CXCL10, TBX21; P < 1.33e-04) plus effector genes (GNLY, GZMB, ITGAX; P < 2.82e-03). Immunophenotypical analysis of the classic immune markers of the innate and adaptive immune system was comparable between patients treated with either tacrolimus or belatacept. In addition, the transcriptome of both groups was not significantly different.

Conclusions

In this small pilot study, no difference was found in immunomics of aTCMR biopsies of tacrolimus- and belatacept-treated patients. This suggests that clinically diagnosed aTCMR reflects a final common pathway of allorecognition which is unaffected by the type of immunosuppressive therapy.

A donor and recipient candidate gene association study of allograft loss in renal transplant recipients receiving a tacrolimus-based regimen

This work investigated, in two large cohorts of French renal transplants treated with tacrolimus, the influence of donor and recipient ABCB1, CYP3A4, and CYP3A5 genotypes on the risk of allograft loss. A discovery and a replication population of 330 and 369 adult renal transplant patients, each from a different transplantation center and all receiving a tacrolimus-based immunosuppressive regimen, were retrospectively genotyped. The influence of genetic factors and other known risk factors on allograft loss was investigated using multivariate Cox proportional hazard analyses. The existence of previous transplantations (per unit HR = 1.89 [1.10-3.26] P = .0216) and the donor ABCB1 c.1199GA/AA genotype (GA/AAvs GG: HR = 3.22 [1.14-9.09], P = .0288) were associated with an increased risk of allograft loss in the discovery cohort and with graft loss due to humoral rejection in the replication cohort (per unit HR = 2.26 [1.34-3.81], P = .00229; GA/AAvs GG HR = 3.42 [1.28-9.16], P = .0142). Genotyping the donor for the ABCB1 c.1199 G>A (exon 11, rs2229109) allele may be of interest before prescribing tacrolimus to the recipient, although this polymorphism is rather rare and its effect may be limited to certain mechanisms of graft loss.

Conversion from Twice-Daily Prograf® to Once-Daily Advagraf® in Multi-ethnic Asian Adult Renal Transplant Recipients With or Without Concomitant Use of Diltiazem: Impact of CYP3A5 and MDR1 Genetic Polymorphisms on Tacrolimus Exposure

BACKGROUND AND OBJECTIVES

Tacrolimus is the mainstay of immunosuppression in renal transplantation. Given that once-daily administration improves patient compliance, 1:1 dose conversion from twice-daily Prograf^® to once-daily Advagraf^® is recommended. Although cytochrome P450 (CYP) 3A5 and multi-drug resistance 1 (MDR1) polymorphisms influence tacrolimus concentrations, it is unknown if these impact on conversion. This study investigated the change in the pharmacokinetics of tacrolimus after conversion from Prograf^® to Advagraf^® and examined the impact of CYP3A5 and MDR1 C3435T polymorphisms on those pharmacokinetics.

METHODS

A prospective open-label pharmacokinetic study of 1:1 conversion from Prograf^® to Advagraf^® with or without diltiazem was conducted on 26 stable renal transplant recipients. Blood samples were collected over 24 h during each phase, tacrolimus concentrations were assayed, and noncompartmental pharmacokinetic analysis was performed. All participants were genotyped for CYP3A5*3 and MDR1 C3435T.

RESULTS

After conversion, without diltiazem, the area under the concentration-time curve at steady state from 0 to 24 h after dose administration (AUC_{ss, 0-24}) was significantly reduced [median 224 (range 172-366) vs. 184 (104-347) ng·h/mL, p = 0.006, n = 26]. A decrease in tacrolimus exposure (median 21%) was only evident among CYP3A5 expressors [227 (172-366) vs. 180 (104-347) ng·h/mL, p = 0.014, n = 18], not among non-expressors [215 (197-290) vs. 217 (129-281) ng·h/mL, p = 0.263, n = 8]. In contrast, among CYP3A5 expressors receiving diltiazem, AUC_{ss, 0-24} did not change significantly upon conversion [229 (170-296) vs. 221 (123-342) ng·h/mL, p = 0.575, n = 10]. An independent effect was not evident for MDR1 C3435T polymorphism.

CONCLUSION

The high prevalence of CYP3A5 polymorphism among Asians may lead to a significant reduction in tacrolimus exposure with 1:1 dose conversion of Prograf^® to Advagraf^®. These results advocate for CYP3A5 determination prior to conversion, and suggest that 1:1.25 conversion should be used for CYP3A5 expressors and 1:1 conversion for other patients.

A randomized clinical trial of age and genotype-guided tacrolimus dosing after pediatric solid organ transplantation

BACKGROUND

Tacrolimus pharmacokinetics are influenced by age and CYP3A5 genotype with CYP3A5 expressors (CYP3A5*1/*1 or *1/*3) being fast metabolizers. However, the benefit of genotype-guided dosing in pediatric solid organ transplantation has been understudied.

OBJECTIVE

To determine whether age and CYP3A5 genotype-guided starting dose of tacrolimus result in earlier attainment of therapeutic drug concentrations.

SETTING

Single hospital-based transplant center.

METHODS

This was a randomized, semi-blinded, 30-day pilot trial. Between 2012 and 2016, pediatric patients listed for solid organ transplant were consented and enrolled into the study. Participants were categorized as expressors, CYP3A5*1/*1 or CYP3A5*1/*3, and nonexpressors, CYP3A5*3/*3. Patients were stratified by age (≤ or > 6 years) and randomized (2:1) after transplant to receive genotype-guided (n = 35) or standard (n = 18) starting dose of tacrolimus for 36-48 hours and were followed for 30 days.

RESULTS

Median age at transplant in the randomized cohort was 2.1 (0.75-8.0) years; 24 (45%) were male. Participants in the genotype-guided arm achieved therapeutic concentrations earlier at a median (IQR) of 3.4 (2.5-6.6) days compared to those in the standard dosing arm of 4.7 (3.5-8.6) days (P = 0.049), and had fewer out-of-range concentrations [OR (95% CI) = 0.60 (0.44, 0.83), P = 0.002] compared to standard dosing, with no difference in frequency of adverse events between the two groups.

CONCLUSIONS

CYP3A5 genotype-guided dosing stratified by age resulted in earlier attainment of therapeutic tacrolimus concentrations and fewer out-of-range concentrations.

Pharmacokinetics, Pharmacodynamics and Pharmacogenetics of Tacrolimus in Kidney Transplantation

Background:

Tacrolimus (Tac, or FK506), a calcineurin inhibitor (CNI), is the first-line immu-nosuppressant which consists of the footstone as immunosuppressive regimens in kidney transplantation. However, the drug toxicity and the significant differences of pharmacokinetics (PK) and pharmacodynam-ics (PD) among individuals are hidden troubles for clinical application. Recently, emerging evidences of Tac pharmacogenetics (PG) regarding drug absorption, metabolism, disposition, excretion and response are discovered for better understanding of this drug.

Method:

We reviewed the published articles regarding the Tac PG and its effects on PK and PD in kidney transplantation. In addition, we summarized information on polygenic algorithms.

Results:

The polymorphism of genes encoding metabolic enzymes and transporters related to Tac were largely investigated, but the results were inconsistent. In addition to CYP3A4, CYP3A5 and P-gp (also known as ABCB1), single nucleotide polymorphisms (SNPs) might also affect the PK and PD parameters of Tac.

Conclusion:

The correlation between Tac PK, PD and PG is very complex. Although many factors need to be verified, it is envisaged that thorough understanding of PG may assist clinicians to predict the optimal starting dosage, help adjust the maintenance regimen, as well as identify high risk patients for adverse ef-fects or drug inefficacy

Impact of POR and CYP3A5 Polymorphisms on Trough Concentration to Dose Ratio of Tacrolimus in the Early Post-operative Period Following Kidney Transplantation

BACKGROUND

Tacrolimus, a critical dose drug, is widely used in transplantation. Knowing the contribution of genetic factors, which significantly influence tacrolimus variability, is beneficial in the personalization of its starting dose. The significant impact of CYP3A5*3 polymorphisms on tacrolimus exposure has been reported. Conflicting results of the additional influence of POR*28 polymorphisms on tacrolimus pharmacokinetic interindividual variability have been observed among different populations. The objective of this study was to explore the interaction between POR*28 and CYP3A5*3 polymorphisms and their main effects on tacrolimus trough concentration to dose ratios on day 7 after kidney transplantation.

METHODS

Two hundred sixteen adult kidney transplant recipients participated in this retrospective study. All participants received a twice daily tacrolimus regimen. Blood samples and data were collected on day 7 after transplantation. A 2-way analysis of covariance was performed. Tested covariates were age, hemoglobin, serum albumin, and prednisolone dose.

RESULTS

A 2 × 2 analysis of covariance revealed that the interaction between CYP3A5 polymorphisms (CYP3A5 expresser and CYP3A5 nonexpresser) and POR polymorphisms (POR*28 carrier and POR*28 noncarrier) was not significant (F(1, 209) = 2.473, P = 0.117, (Equation is included in full-text article.)= 0.012). The predicted main effect of CYP3A5 and POR polymorphisms was significant (F(1, 209) = 105.565, P < 0.001, (Equation is included in full-text article.)= 0.336 and F(1, 209) = 4.007, P = 0.047, (Equation is included in full-text article.)= 0.019, respectively). Hemoglobin, age, and steroid dose influenced log C0/dose of tacrolimus (F(1, 209) = 20.612, P < 0.001, (Equation is included in full-text article.)= 0.090; F(1, 209) = 14.360, P < 0.001, (Equation is included in full-text article.)= 0.064; and F(1, 209) = 5.512, P = 0.020, (Equation is included in full-text article.)= 0.026, respectively).

CONCLUSIONS

After adjusting for the influences of hemoglobin, age, and prednisolone dose, significant impacts of the CYP3A5 and POR polymorphisms on tacrolimus exposure were found. The effect of POR*28 and CYP3A5*3 polymorphisms during the very early period after kidney transplantation is independent of each other.

Biomarkers and Pharmacogenomics in Kidney Transplantation

This review is focused on present and future biomarkers, along with pharmacogenomics used in clinical practice for kidney transplantation. It aims to highlight biomarkers that could potentially be used to improve kidney transplant early and long-term graft survival, but also potentially patient co-morbidity. Future directions for improving outcomes are discussed, which include immune tolerance and personalising immunosuppression regimens.

Genotypes associated with tacrolimus pharmacokinetics impact clinical outcomes in lung transplant recipients

Most lung transplantation immunosuppression regimens include tacrolimus. Single nucleotide polymorphisms (SNPs) in genes important to tacrolimus bioavailability and clearance (ABCB1, CYP3A4, and CYP3A5) are associated with differences in tacrolimus pharmacokinetics. We hypothesized that polymorphisms in these genes would impact immunosuppression-related outcomes. We categorized ABCB1, CYP3A4, and CYP3A5 SNPs for 321 lung allograft recipients. Genotype effects on time to therapeutic tacrolimus level, interactions with antifungal medications, concentration to dose (C₀ /D), acute kidney injury, and rejection were assessed using linear models adjusted for subject characteristics and repeat measures. Compared with CYP3A poor metabolizers (PM), time to therapeutic tacrolimus trough was increased by 5.1 ± 1.6 days for CYP3A extensive metabolizers (EM, P < 0.001). In the post-operative period, CYP3A intermediate metabolizers spent 1.2 ± 0.5 days less (P = 0.01) and EM spent 2.1 ± 0.5 days less (P < 0.001) in goal tacrolimus range than CYP3A PM. Azole antifungals interacted with CYP3A genotype in predicting C₀ /D (P < 0.001). Increased acute kidney injury rates were observed in subjects with high ABCB1 function (OR 3.0, 95% CI 1.1-8.6, P = 0.01). Lower rates of acute cellular rejection were observed in subjects with low ABCB1 function (OR 0.36, 95% CI 0.07-0.94, P = 0.02). Recipient genotyping may help inform tacrolimus dosing decisions and risk of adverse clinical outcomes.

Carpe diem-Time to transition from empiric to precision medicine in kidney transplantation

The current immunosuppressive pipeline in kidney transplantation is limited. In part, this is due to excellent one-year allograft outcomes with the current standard of care (ie, calcineurin inhibitor in combination with anti-proliferative agents). Despite this success, a recent Federal government-sponsored systematic review has identified gaps/limits in the evidence of what constitutes optimal calcineurin inhibitor use in the short- and long-term. Moreover, recent empiric approaches to minimize/withdraw/convert from calcineurin inhibitors have come with the price of increased alloreactivity. As the time horizon to replace calcineurin inhibitors on a global scale may be distant, the transplant community should seize the opportunity to develop ways to personalize calcineurin inhibitor immunosuppression to the individual-transitioning from empiricism to precision. The authors argue in this viewpoint that the path to precision will require measures capable of detecting subclinical alloreactivity to define adequacy of immunosuppression, as well as novel genetic analytics to accurately define alloimmune risk at the individual level-both approaches will require validation in clinical trials.

CYP3A5 and ABCB1 polymorphisms in living donors do not impact clinical outcome after kidney transplantation

Aim: To investigate the association between donor CYP3A5 and ABCB1 polymorphisms and tacrolimus (Tac)-induced nephrotoxicity and renal function in kidney transplant recipients. Methods: The CYP3A5 6986A>G and ABCB1 3435C>T polymorphisms were determined in 237 recipients and donors. Results: There was no significant association between Tac-related nephrotoxicity and donor CYP3A5 and ABCB1 genotype. The donor ABCB1 3435C>T polymorphism was associated with estimated glomerular filtration rate on day 7 and month 1. The combined donor–recipient ABCB1 genotype (3435C>T polymorphism) was significantly related with estimated glomerular filtration rate on day 3 and 7 in univariate analysis. However, these differences were no longer statistically significant in multivariate analysis. Conclusion: A genetic analysis of ABCB1 and CYP3A5 of kidney transplant donors is not helpful to improve renal transplant outcomes.

CYP3A pharmacogenetic association with tacrolimus pharmacokinetics differs based on route of drug administration

Tacrolimus is prescribed to the majority of transplant recipients to prevent graft rejection, and although patients are maintained on oral administration, nonoral routes of administration are frequently used in the initial post-transplant period. CYP3A5 genotype is an established predictor of oral tacrolimus dose requirements, and clinical guideline recommendations exist for CYP3A5-guided dose selection. However, the association between CYP3A5 and nonoral tacrolimus administration is currently poorly understood, and differs from the oral tacrolimus relationship. In addition to CYP3A5, other pharmacogenes associated with CYP3A activity, including CYP3A4, CYP3A7 and POR have also been identified as predictors of tacrolimus exposure. This review will describe the current understanding of the relationship between these pharmacogenes and tacrolimus pharmacokinetics after oral and nonoral administration.

Influence of CYP3A5 genetic differences in tacrolimus on quantitative interstitial fibrosis and long-term graft function in kidney transplant recipients

The impact of CYP3A5 polymorphisms on clinical outcomes is controversial. The present study investigated the impact of CYP3A5 genetic differences on the development of interstitial fibrosis (IF) from 0 h to 1 year post-transplantation in biopsy sections from 96 living kidney recipients under the same target trough regimen of tacrolimus. The relationships between CYP3A5 polymorphisms and long-term graft function and death-censored graft survival were also examined. A quantitative analysis of IF was performed using computer-assisted imaging on virtual slides. Percent IF (%IF) in the cortical region at 0 h was defined as the baseline, and increases in the ratio of %IF 1 year post-transplantation were calculated. The relationships between CYP3A5 genetic differences and the development of IF, the incidence of clinical events, and the long-term function and death-censored survival of grafts were assessed. The mean increase in the ratio of %IF from 0 h to 1 year was 1.38 ± 0.74-fold. Despite therapeutic drug monitoring (TDM), trough levels of tacrolimus were lower in carriers with the CYP3A5*1 allele (expressers) than in those with the CTP3A5*3/*3 genotype (non-expressers) throughout the 1-year post-transplantation period. However, CYP3A5 genetic differences were not associated with the development of IF, any clinical events, or the long-term function and survival of grafts. The clinical impact of CYP3A5 genetic differences may be small under the current immunosuppressive regimen consisting of mycophenolate mofetil, steroids, basiliximab, and lower target trough levels of tacrolimus with suitable TDM in a low immunological risk population.

CYP3A5 polymorphisms in renal transplant recipients: influence on tacrolimus treatment

Tacrolimus is a commonly used immunosuppressant after kidney transplantation. It has a narrow therapeutic range and demonstrates wide interindividual variability in pharmacokinetics, leading to potential underimmunosuppression or toxicity. Genetic polymorphism in CYP3A5 enzyme expression contributes to differences in tacrolimus bioavailability between individuals. Individuals carrying one or more copies of the wild-type allele *1 express CYP3A5, which increases tacrolimus clearance. CYP3A5 expressers require 1.5 to 2-fold higher tacrolimus doses compared to usual dosing to achieve therapeutic blood concentrations. Individuals with homozygous *3/*3 genotype are CYP3A5 nonexpressers. CYP3A5 nonexpression is the most frequent phenotype in most ethnic populations, except blacks. Differences between CYP3A5 genotypes in tacrolimus disposition have not translated into differences in clinical outcomes, such as acute rejection and graft survival. Therefore, although genotype-based dosing may improve achievement of therapeutic drug concentrations with empiric dosing, its role in clinical practice is unclear. CYP3A5 genotype may predict differences in absorption of extended-release and immediate-release oral formulations of tacrolimus. Two studies found that CYP3A5 expressers require higher doses of tacrolimus in the extended-release formulation compared to immediate release. CYP3A5 genotype plays a role in determining the impact of interacting drugs, such as fluconazole, on tacrolimus pharmacokinetics. Evidence conflicts regarding the impact of CYP3A5 genotype on risk of nephrotoxicity associated with tacrolimus. Further study is required.

Implementation of Pharmacogenomics in Everyday Clinical Settings

Currently, germline pharmacogenomics (PGx) is successfully implemented within certain specialties in clinical care. With the integration of PGx in pharmacotherapy multiple stakeholders are involved, which are identified in this chapter. Clinically relevant pharmacogenes with their related PGx test are discussed, along with diagnostic test criteria to guide clinicians and policy makers in PGx test selection. The chapter further reviews the similarities and the differences between the guidelines of the Dutch Pharmacogenetics Working Group and the Clinical Pharmacogenetics Implementation Consortium which both support healthcare professionals in understanding PGx test results and help guiding pharmacotherapy by providing evidence-based dosing recommendations. Finally, clinical studies which provide scientific evidence and information on cost-effectiveness supporting clinical implementation of PGx in clinical care are discussed along with the remaining barriers for adoption of PGx testing by healthcare professionals.