Validation of tacrolimus equation to predict troughs using genetic and clinical factors

Assessing the Utility of a Genotype-Guided Tacrolimus Equation in African American Kidney Transplant Recipients: A Single Institution Retrospective Study

Tacrolimus metabolism is heavily influenced by the CYP3A5 genotype, which varies widely among African Americans (AA). We aimed to assess the performance of a published genotype-informed tacrolimus dosing model in an independent set of adult AA kidney transplant (KTx) recipients. CYP3A5 genotypes were obtained for all AA KTx recipients (n = 232) from 2010 to 2019 who met inclusion criteria at a single transplant center in Philadelphia, Pennsylvania, USA. Medical record data were used to calculate predicted tacrolimus clearance using the published AA KTx dosing equation and two modified iterations. Observed and model-predicted trough levels were compared at 3 days, 3 months, and 6 months post-transplant. The mean prediction error at day 3 post-transplant was 3.05 ng/mL, indicating that the model tended to overpredict the tacrolimus trough. This bias improved over time to 1.36 and 0.78 ng/mL at 3 and 6 months post-transplant, respectively. Mean absolute prediction error-a marker of model precision-improved with time to 2.33 ng/mL at 6 months. Limiting genotype data in the model decreased bias and improved precision. The bias and precision of the published model improved over time and were comparable to studies in previous cohorts. The overprediction observed by the published model may represent overfitting to the initial cohort, possibly limiting generalizability.

Impact of CYP3A5 Status on the Clinical and Financial Outcomes Among African American Kidney Transplant Recipients

Pharmacogenetic profiling of transplant recipients demonstrates that the marked variation in the metabolism of immunosuppressive medications, particularly tacrolimus, is related to genetic variants. Patients of African ancestry are less likely to carry loss-of-function (LoF) variants in the CYP3A5 gene and therefore retain a rapid metabolism phenotype and higher clearance of tacrolimus. Patients with this rapid metabolism typically require higher dosing to achieve therapeutic trough concentrations. This study aims to further characterize the impact of CYP3A5 genotype on clinical outcomes and financial expenditure.

Impact of CYP3A5 phenotype on tacrolimus time in therapeutic range and clinical outcomes in pediatric renal and heart transplant recipients

STUDY OBJECTIVE

This study investigated the effect of CYP3A5 phenotype on time in therapeutic range (TTR) of tacrolimus post-transplant in pediatric patients.

DESIGN AND DATA SOURCE

This retrospective study assessed medical records of pediatric kidney and heart recipients with available CYP3A5 genotype for tacrolimus dosing, troughs, and the clinical events (biopsy-proven acute rejection [BPAR] and de novo donor-specific antibodies [dnDSA]).

MEASUREMENTS AND MAIN RESULTS

The primary outcome, mean TTR in the first 90 days post-transplant, was 9.0% (95% CI: -16.1, -1.9) lower in CYP3A5 expressers (p = 0.014) when adjusting for time to therapeutic concentration and organ type. There was no difference between CYP3A5 phenotypes in time to the first clinical event using TTR during the first 90 days. When applying TTR over the first year, there was a significant difference in event-free survival (EFS) which was 50.0% for CYP3A5 expressers/TTR < 35%, 45.5% for expressers/TTR ≥ 35%, 38.1% for nonexpressers/TTR < 35%, and 72.9% for nonexpressers/TTR ≥ 35% (log-rank p = 0.03). A post hoc analysis of EFS identified CYP3A5 expressers had lower EFS compared to nonexpressers in patients with TTR ≥ 35% (p = 0.04) but no difference among patients with TTR < 35% (p = 0.6).

CONCLUSIONS

The relationship between TTR and CYP3A5 phenotype suggests that achieving a TTR ≥ 35% during the first year may be a modifiable factor to attenuate the risk of BPAR and dnDSA.

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.

Assessment of tacrolimus intrapatient variability in stable adherent transplant recipients: Establishing baseline values

The purpose of this study was to determine the intrapatient (within the same patient) variability of tacrolimus in adherent patients. Daily tacrolimus trough levels were obtained at home using dried blood spot technology in kidney and liver transplant recipients. Patients were randomized to receive 3 formulations of tacrolimus, each for two 1-week periods. Adherence was monitored by patient diary, pill counts, and use of the Medication Event Monitoring System (MEMS). Variability was quantified as the coefficient of variation (CV). Comparison of CV between groups was by independent t test or one-way ANOVA as appropriate. The population was found to be adherent with a rate of 99.9% with a mean interval between the evening and morning dose of tacrolimus of 11.86 hours. The median CV for the entire population was 15.2% (range 4.8%-110%). There were no differences in CV by allograft type or tacrolimus formulation. The multivariate analysis did not identify any demographic characteristics associated with a CV > 30%. In a highly adherent population, tacrolimus did not display high intrapatient variability. Given the association between IPV and poor allograft outcomes, future studies are needed to quantitate the influence of adherence and establish target IPV goals.

Identification of genetic variants associated with tacrolimus metabolism in kidney transplant recipients by extreme phenotype sampling and next generation sequencing

An extreme phenotype sampling (EPS) model with targeted next-generation sequencing (NGS) identified genetic variants associated with tacrolimus (Tac) metabolism in subjects from the Deterioration of Kidney Allograft Function (DeKAF) Genomics cohort which included 1,442 European Americans (EA) and 345 African Americans (AA). This study included 48 subjects separated into 4 groups of 12 (AA high, AA low, EA high, EA low). Groups were selected by the extreme phenotype of dose-normalized Tac trough concentrations after adjusting for common genetic variants and clinical factors. NGS spanned >3 Mb of 28 genes and identified 18,661 genetic variants (3,961 previously unknown). A group of 125 deleterious variants, by SIFT analysis, were associated with Tac troughs in EAs (burden test, p=0.008), CYB5R2 was associated with Tac troughs in AAs (SKAT, p=0.00079). In CYB5R2, rs61733057 (increased allele frequency in AAs) was predicted to disrupt protein function by SIFT and PolyPhen2 analysis. The variants merit further validation.

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

CYP3A and CYP2C19 activity in urine in relation to CYP3A4, CYP3A5, and CYP2C19 polymorphisms in Russian peptic ulcer patients taking omeprazole

Background

Proton pump inhibitors (PPIs) are metabolized by cytochrome P450. CYP2C19 is the main isoenzyme for the majority of PPI, whereas CYP3A family is a secondary enzyme for PPI biotransformation.

Purpose

The aim of the study was to find if CYP3A4*22, CYP3A5*3, CYP2C19*2, CYP2C19*3, and CYP2C19*17 genotypes are connected with CYP3A and CYP2C19 activities in Russian peptic ulcer patients taking omeprazole.

Patients and methods

Forty-eight gastric or duodenal ulcer patients (15 men, 33 women; mean age 55.0±15.3 years, age range 18-91 years) from Moscow region of Russia were enrolled. Peripheral venous blood was collected for DNA extraction, and real-time polymerase chain reaction was performed for CYP3A5*3 ^A6986G (rs776746), CYP3A4*22 C>T in intron 6 (rs35599367), CYP2C19*2^G681A (rs4244285), CYP2C19*3^G636A (rs4986893), and CYP2C19*17^C-806T (rs12248560) polymorphism analyses. Urine samples of patients were collected in the morning between 6 and 9 am before food or drug intake. Urine cortisol and 6β-hydroxycortisol concentrations (for CYP3A activity) and omeprazole and 5-hydroxyomeprazole concentrations (for CYP2C19 activity) were measured using high-performance liquid chromatography/mass spectroscopy.

Results

We found a connection between CYP2C19 genotypes and CYP3A activity. Median metabolic ratios 6β-hydroxycortisol/cortisol (25%-75% percentiles) were 2.84 (1.99-4.39) for CYP2C19 extensive metabolizers (EMs), 2.51 (1.86-4.73) for CYP2C19 ultra-rapid metabolizers (UMs), and 1.45 (1.12-2.16) for CYP2C19 intermediate metabolizers (IMs) + poor metabolizers (PMs). A statistically significant difference in CYP3A activity (Mann-Whitney test) was found between CYP2C19 EMs vs CYP2C19 IMs+PMs (p=0.006), between CYP2C19 UMs vs CYP2C19 IMs+PMs (p=0.018), and in multiple comparison Kruskal-Wallis test (p=0.014).

Conclusion

In CYP2C19 IMs+PMs, CYP3A activity was significantly lower than in CYP2C19 EMs and UMs.

Artificial neural network model for predicting the bioavailability of tacrolimus in patients with renal transplantation

The objective of the current study was to explore the role of ABCB1 and CYP3A5 genetic polymorphisms in predicting the bioavailability of tacrolimus and the risk for post-transplant diabetes. Artificial neural network (ANN) and logistic regression (LR) models were used to predict the bioavailability of tacrolimus and risk for post-transplant diabetes, respectively. The five-fold cross-validation of ANN model showed good correlation with the experimental data of bioavailability (r2 = 0.93-0.96). Younger age, male gender, optimal body mass index were shown to exhibit lower bioavailability of tacrolimus. ABCB1 1236 C>T and 2677G>T/A showed inverse association while CYP3A5*3 showed a positive association with the bioavailability of tacrolimus. Gender bias was observed in the association with ABCB1 3435 C>T polymorphism. CYP3A5*3 was shown to interact synergistically in increasing the bioavailability in combination with ABCB1 1236 TT or 2677GG genotypes. LR model showed an independent association of ABCB1 2677 G>T/A with post transplant diabetes (OR: 4.83, 95% CI: 1.22-19.03). Multifactor dimensionality reduction analysis (MDR) revealed that synergistic interactions between CYP3A5*3 and ABCB1 2677 G>T/A as the determinants of risk for post-transplant diabetes. To conclude, the ANN and MDR models explore both individual and synergistic effects of variables in modulating the bioavailability of tacrolimus and risk for post-transplant diabetes.

Genome-wide association study identifies the common variants in CYP3A4 and CYP3A5 responsible for variation in tacrolimus trough concentration in Caucasian kidney transplant recipients

The immunosuppressant tacrolimus (TAC) is metabolized by both cytochrome P450 3A4 (CYP3A4) and CYP3A5 enzymes. It is common for European Americans (EA) to carry two CYP3A5 loss-of-function (LoF) variants that profoundly reduces TAC metabolism. Despite having two LoF alleles, there is still considerable variability in TAC troughs and identifying additional variants in genes outside of the CYP3A5 gene could provide insight into this variability. We analyzed TAC trough concentrations in 1345 adult EA recipients with two CYP3A5 LoF alleles in a genome-wide association study. Only CYP3A4*22 was identified and no additional variants were genome-wide significant. Additional high allele frequency genetic variants with strong genetic effects associated with TAC trough variability are unlikely to be associated with TAC variation in the EA population. These data suggest that low allele frequency variants, identified by DNA sequencing, should be evaluated and may identify additional variants that contribute to TAC pharmacokinetic variability.

Pharmacokinetic considerations related to therapeutic drug monitoring of tacrolimus in kidney transplant patients

INTRODUCTION

Tacrolimus (Tac) is the cornerstone of immunosuppressive therapy after solid organ transplantation and will probably remain so. Excluding belatacept, no new immunosuppressive drugs were registered for the prevention of acute rejection during the last decade. For several immunosuppressive drugs, clinical development halted because they weren't sufficiently effective or more toxic. Areas covered: Current methods of monitoring Tac treatment, focusing on traditional therapeutic drug monitoring (TDM), controversies surrounding TDM, novel matrices, pharmacogenetic and pharmacodynamic monitoring are discussed. Expert opinion: Due to a narrow therapeutic index and large interpatient pharmacokinetic variability, TDM has been implemented for individualization of Tac dose to maintain drug efficacy and minimize the consequences of overexposure. The relationship between predose concentrations and the occurrence of rejection or toxicity is controversial. Acute cellular rejection also occurs when the Tac concentration is within the target range, suggesting that Tac whole blood concentrations don't necessarily correlate with pharmacological effect. Intracellular Tac, the unbound fraction of Tac or pharmacodynamic monitoring could be better biomarkers/tools for adequate Tac exposure - research into this has been promising. Traditional TDM, perhaps following pre-emptive genotyping for Tac-metabolizing enzymes, must suffice for a few years before these strategies can be implemented in clinical practice.

Transplant genetics and genomics

Ever since the discovery of the major histocompatibility complex, scientific and clinical understanding in the field of transplantation has been advanced through genetic and genomic studies. Candidate-gene approaches and recent genome-wide association studies (GWAS) have enabled a deeper understanding of the complex interplay of the donor-recipient interactions that lead to transplant tolerance or rejection. Genetic analysis in transplantation, when linked to demographic and clinical outcomes, has the potential to drive personalized medicine by enabling individualized risk stratification and immunosuppression through the identification of variants associated with immune-mediated complications, post-transplant disease or alterations in drug-metabolizing genes.

Application of Machine-Learning Models to Predict Tacrolimus Stable Dose in Renal Transplant Recipients

Tacrolimus has a narrow therapeutic window and considerable variability in clinical use. Our goal was to compare the performance of multiple linear regression (MLR) and eight machine learning techniques in pharmacogenetic algorithm-based prediction of tacrolimus stable dose (TSD) in a large Chinese cohort. A total of 1,045 renal transplant patients were recruited, 80% of which were randomly selected as the “derivation cohort” to develop dose-prediction algorithm, while the remaining 20% constituted the “validation cohort” to test the final selected algorithm. MLR, artificial neural network (ANN), regression tree (RT), multivariate adaptive regression splines (MARS), boosted regression tree (BRT), support vector regression (SVR), random forest regression (RFR), lasso regression (LAR) and Bayesian additive regression trees (BART) were applied and their performances were compared in this work. Among all the machine learning models, RT performed best in both derivation [0.71 (0.67–0.76)] and validation cohorts [0.73 (0.63–0.82)]. In addition, the ideal rate of RT was 4% higher than that of MLR. To our knowledge, this is the first study to use machine learning models to predict TSD, which will further facilitate personalized medicine in tacrolimus administration in the future.

Pharmacogenetic aspects of the use of tacrolimus in renal transplantation: recent developments and ethnic considerations

INTRODUCTION

Tacrolimus (Tac) is effective in preventing acute rejection but has considerable toxicity and inter-individual variability in pharmacokinetics and pharmacodynamics. Part of this is explained by polymorphisms in genes encoding Tac-metabolizing enzymes and transporters. A better understanding of Tac pharmacokinetics and pharmacodynamics may help to minimize different outcomes amongst transplant recipients by personalizing immunosuppression.

AREAS COVERED

The pharmacogenetic contribution of Tac metabolism will be examined, with a focus on recent discoveries, new developments and ethnic considerations.

EXPERT OPINION

The strongest and most consistent association in pharmacogenetics is between the CYP3A5 genotype and Tac dose requirement, with CYP3A5 expressers having a ~ 40-50% higher dose requirement compared to non-expressers. Two recent randomized-controlled clinical trials using CYP3A5 genotype, however, did not show a decrease in acute rejections nor reduced toxicity. CYP3A4*22, CYP3A4*26, and POR*28 are also associated with Tac dose requirements and may be included to provide the expected improvement of Tac therapy. Studies focusing on the intracellular drug concentrations and on calcineurin inhibitor-induced nephrotoxicity also seem promising. For all studies, however, the ethnic prevalence of genotypes should be taken into account, as this may significantly impact the effect of pre-emptive genotyping.

Genomewide Association Study of Tacrolimus Concentrations in African American Kidney Transplant Recipients Identifies Multiple CYP3A5 Alleles

We previously reported that tacrolimus (TAC) trough blood concentrations for African American (AA) kidney allograft recipients were lower than those observed in white patients. Subtherapeutic TAC troughs may be associated with acute rejection (AR) and AR-associated allograft failure. This variation in TAC troughs is due, in part, to differences in the frequency of the cytochrome P450 CYP3A5*3 allele (rs776746, expresses nonfunctional enzyme) between white and AA recipients; however, even after accounting for this variant, variability in AA-associated troughs is significant. We conducted a genomewide association study of TAC troughs in AA kidney allograft recipients to search for additional genetic variation. We identified two additional CYP3A5 variants in AA recipients independently associated with TAC troughs: CYP3A5*6 (rs10264272) and CYP3A5*7 (rs41303343). All three variants and clinical factors account for 53.9% of the observed variance in troughs, with 19.8% of the variance coming from demographic and clinical factors including recipient age, glomerular filtration rate, anticytomegalovirus drug use, simultaneous pancreas-kidney transplant and antibody induction. There was no evidence of common genetic variants in AA recipients significantly influencing TAC troughs aside from the CYP3A gene. These results reveal that additional and possibly rare functional variants exist that account for the additional variation.

Genotype-guided tacrolimus dosing in African-American kidney transplant recipients

Tacrolimus is dependent on CYP3A5 enzyme for metabolism. Expression of the CYP3A5 enzyme is controlled by several alleles including CYP3A5*1, CYP3A5*3, CYP3A5*6 and CYP3A5*7. African Americans (AAs) have on average higher tacrolimus dose requirements than Caucasians; however, some have requirements similar to Caucasians. Studies in AAs have primarily evaluated the CYP3A5*3 variant; however, there are other common nonfunctional variants in AAs (CYP3A5*6 and CYP3A5*7) that do not occur in Caucasians. These variants are associated with lower dose requirements and may explain why some AAs are metabolically similar to Caucasians. We created a tacrolimus clearance model in 354 AAs using a development and validation cohort. Time after transplant, steroid and antiviral use, age and CYP3A5*1, *3, *6 and *7 alleles were significant toward clearance. This study is the first to develop an AA-specific genotype-guided tacrolimus dosing model to personalize therapy.

Multigene predictors of tacrolimus exposure in kidney transplant recipients

AIM

Determine the effect of the genetic variants beyond CYP3A5*3 on tacrolimus disposition.

PATIENTS & METHODS

We studied genetic correlates of tacrolimus trough concentrations with POR*28, CYP3A4*22 and ABCC2 haplotypes in a large, ethnically diverse kidney transplant cohort (n = 2008).

RESULTS

Subjects carrying one or more CYP3A5*1 alleles had lower tacrolimus trough concentrations (p = 9.2 × 10(-75)). The presence of one or two POR*28 alleles was associated with a 4.63% reduction in tacrolimus trough concentrations after adjusting for CYP3A5*1 and clinical factors (p = 0.037). In subset analyses, POR*28 was significant only in CYP3A5*3/*3 carriers (p = 0.03). The CYP3A4*22 variant and the ABBC2 haplotypes were not associated.

CONCLUSION

This study confirmed that CYP3A5*1 was associated with lower tacrolimus trough concentrations. POR*28 was associated with decreased tacrolimus trough concentrations although the effect was small possibly through enhanced CYP3A4 enzyme activity. CYP3A4*22 and ABCC2 haplotypes did not influence tacrolimus trough concentrations. Original submitted 19 December 2014; Revision submitted 2 April 2015.

Role of pharmacogenomics in dialysis and transplantation

PURPOSE OF REVIEW

Pharmacogenomics is the study of differences in drug response on the basis of individual genetic background. With rapidly advancing genomic technologies and decreased costs of genotyping, the field of pharmacogenomics continues to develop. Application to patients with kidney disease provides growing opportunities for improving drug therapy.

RECENT FINDINGS

Pharmacogenomics studies are lacking in patients with chronic kidney disease and dialysis, but are abundant in the kidney transplant field. A potentially clinically actionable genetic variant exists in the CYP3A5 gene, with the initial tacrolimus dose selection being optimized based on CYP3A5 genotype. Although many pharmacogenomics studies have focused on transplant immunosuppression pharmacokinetics, an expanding literature on pharmacodynamic outcomes, such as calcineurin inhibitor toxicity and new onset diabetes, is providing new information on patients at risk.

SUMMARY

Appropriately powered pharmacogenomics studies with well-defined phenotypes are needed to validate existing studies and unearth new findings in patients with kidney disease, especially the chronic kidney disease and dialysis population.

CYP3A5 and CYP3A4, but not ABCB1 polymorphisms affect tacrolimus dose-adjusted trough concentrations in kidney transplant recipients

BACKGROUND

Tacrolimus (TAC), acting as a calcineurin inhibitor, is an immunosuppressant widely used after kidney transplantation. TAC requires blood concentration monitoring due to large interindividual variability in its pharmacokinetics and a narrow therapeutic index. Since genetic factors are considered responsible for a part of the observed pharmacokinetic variability, hereby SNPs within the CYP3A4, CYP3A5 and ABCB1 genes in kidney transplant patients of Polish Caucasian origin were investigated.

PATIENTS & METHODS

A total of 241 patients treated with TAC through the first year after kidney transplantation were genotyped for the presence of common SNPs: rs776746:A>G (CYP3A5*3), rs35599367:C>T (CYP3A4*22), rs2740574:A>G (CYP3A4*1B) and rs1045642:C>T (ABCB1 3435C>T) using TaqMan(®) assays.

RESULTS

CYP3A5 expressers received significantly higher weight-adjusted TAC doses, and were characterized by markedly lower C0 and dose adjusted C0 values in the course of treatment. CYP3A4*1B was significantly associated with TAC pharmacokinetics in univariate analysis. Impact of the CYP3A4*22 allele was significant only at particular time points, that is, 3 months after transplantation, with marginal significance 6 months after transplantation. The ABCB1 genotype did not influence TAC pharmacokinetics. Multivariate analysis of all the studied loci demonstrated that only the CYP3A5*1 (starting from month 1) and CYP3A4*22 alleles (at 3 and 6 months) were independent predictors of TAC dose-adjusted C0.

CONCLUSION

Our results confirm the impact of the CYP3A4*22 allele on TAC pharmacokinetics, as a second significant genetic factor (in addition to the CYP3A5*1 allele) influencing TAC dose-adjusted blood concentrations in kidney transplant recipients.

Within-patient variability in immunosuppressive drug exposure as a predictor for poor outcome after transplantation

Within-patient variability in immunosuppressive drug exposure is easily identified by measurement of drug concentrations at the outpatient clinic. Fluctuating levels despite a stable drug dose can be observed in a substantial proportion of patients. It has now been shown that this within-patient variability is a predictor for poor long-term outcome after transplantation. Nonadherence most likely is an important determinant of variability, and strategies to tackle nonadherence are being developed.

Pharmacogenetics and immunosuppressive drugs in solid organ transplantation

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

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

Many studies have attempted to explain the interindividual variability observed in drug metabolism by assessing the impact of SNPs in genes implicated in drug absorption, distribution, metabolism and excretion pathways. Particular attention has been paid to the CYP450s. CYP3A4 is the main CYP isoform in human liver and intestine and is involved in the metabolism of many drugs. Its activity, however, is characterized by widespread variation in the general population, which is thought to have a genetic basis. A new CYP3A4 allele (CYP3A4*22; rs35599367 C>T in intron 6) with a frequency of 5-7% in the Caucasian population was recently discovered through its association with low hepatic CYP3A4 expression and CYP3A4 activity, and showing effects on statin, tacrolimus and cyclosporine metabolism. This review will summarize the current literature on phenotypes linked to this new promising CYP3A4 genetic marker SNP and discusses the potential clinical relevance.