Pharmacokinetic differences corroborate observed low tacrolimus dosage in Native American renal transplant patients

The Value of Pharmacogenomics for White and Indigenous Americans after Kidney Transplantation

BACKGROUND

There is a paucity of evidence to inform the value of pharmacogenomic (PGx) results in patients after kidney transplant and how these results differ between Indigenous Americans and Whites. This study aims to identify the frequency of recommended medication changes based on PGx results and compare the pharmacogenomic (PGx) results and patients' perceptions of the findings between a cohort of Indigenous American and White kidney transplant recipients.

METHODS

Thirty-one Indigenous Americans and fifty White kidney transplant recipients were studied prospectively. Genetic variants were identified using the OneOme RightMed PGx test of 27 genes. PGx pharmacist generated a report of the genetic variation and recommended changes. Pre- and post-qualitative patient surveys were obtained.

RESULTS

White and Indigenous American subjects had a similar mean number of medications at the time of PGx testing (mean 13 (SD 4.5)). In the entire cohort, 53% received beta blockers, 30% received antidepressants, 16% anticoagulation, 47% pain medication, and 25% statin therapy. Drug-gene interactions that warranted a clinical action were present in 21.5% of patients. In 12.7%, monitoring was recommended. Compared to the Whites, the Indigenous American patients had more normal CYP2C19 (p = 0.012) and CYP2D6 (p = 0.012) activities. The Indigenous American patients had more normal CYP4F2 (p = 0.004) and lower VKORC (p = 0.041) activities, phenotypes for warfarin drug dosing, and efficacy compared to the Whites. SLC6A4, which affects antidepressant metabolism, showed statistical differences between the two cohorts (p = 0.017); specifically, SLC6A4 had reduced expression in 45% of the Indigenous American patients compared to 20% of the White patients. There was no significant difference in patient perception before and after PGx.

CONCLUSIONS

Kidney transplant recipients had several drug-gene interactions that were clinically actionable; over one-third of patients were likely to benefit from changes in medications or drug doses based on the PGx results. The Indigenous American patients differed in the expression of drug-metabolizing enzymes and drug transporters from the White patients.

Inter-ethnic differences in pharmacokinetics-is there more that unites than divides?

Inter-ethnic variability in pharmacokinetics (PK) has been attributed to several factors ranging from genetic to environmental. It is not clear how current teaching in higher education (HE) reflects what published literature suggests on this subject. This study aims to gain insights into current knowledge about inter-ethnic differences in PK based on reports from published literature and current teaching practices in HE. A systematic literature search was conducted on PubMed and Scopus to identify suitable literature to be reviewed. Insights into inter-ethnic differences in PK teaching among educators in HE and industry were determined using a questionnaire. Thirty-one percent of the studies reviewed reported inter-ethnic differences in PK, of these, 37% of authors suggested genetic polymorphism as possible explanation for the inter-ethnic differences observed. Other factors authors proposed included diet and weight differences between ethnicities. Most respondents (80%) who taught inter-ethnic difference in PK attributed inter-ethnic differences to genetic polymorphism. While genetic polymorphism is one source of variability in PK, the teaching of genetic polymorphism is better associated with interindividual variabilities rather than inter-ethnic differences in PK as there are no genes with PK implications specific to any one ethnic group. Nongenetic factors such as diet, weight, and environmental factors, should be highlighted as potential sources of interindividual variation in the PK of drugs.

Predictive Performance of Published Tacrolimus Population Pharmacokinetic Models in Thai Kidney Transplant Patients

BACKGROUND AND OBJECTIVE

Tacrolimus is a narrow therapeutic index drug with high pharmacokinetic variability, and several tacrolimus population pharmacokinetic (PopPK) models were developed to guide individualized drug dosing. These models, however, may not perform well in other clinical settings. Therefore, we aimed to assess the predictive ability of published tacrolimus PopPK models using a dataset of Thai kidney transplant patients.

METHODS

The external dataset was retrospectively collected from medical records of Bhumibol Adulyadej Hospital, Thailand. Published tacrolimus PopPK models were systematically searched from PubMed, Science Direct, CINAHL Complete, and Scopus databases. Models conducted using a nonlinear mixed-effects approach with covariate resemblance to our external dataset were selected. The external dataset consisted of Thai kidney transplant patients receiving oral immediate- or extended-release tacrolimus formulations twice or once daily, respectively. Accuracy and precision of predicted concentrations were evaluated using mean absolute prediction error (MAPE), root mean square error (RMSE), and goodness of fit plots.

RESULTS

Only three models produced acceptable population predictions with the MAPE of < 50%. By using the Bayesian posthoc estimate of individual pharmacokinetic parameters, all models well performed with the MAPE and RMSE of < 30% and 40%, respectively, except two models; one could not successfully converge and the other substantially underpredicted tacrolimus concentrations.

CONCLUSION

We evaluated ten tacrolimus PopPK models, and eight models resulted in satisfactorily individual predicted tacrolimus concentrations in Thai kidney transplant patients and may be used to aid tacrolimus dose adjustment along with a clinical judgment.

Population Pharmacokinetic Models of Tacrolimus in Adult Transplant Recipients: A Systematic Review

BACKGROUND AND OBJECTIVES

Numerous population pharmacokinetic (PK) models of tacrolimus in adult transplant recipients have been published to characterize tacrolimus PK and facilitate dose individualization. This study aimed to (1) investigate clinical determinants influencing tacrolimus PK, and (2) identify areas requiring additional research to facilitate the use of population PK models to guide tacrolimus dosing decisions.

METHODS

The MEDLINE and EMBASE databases, as well as the reference lists of all articles, were searched to identify population PK models of tacrolimus developed from adult transplant recipients published from the inception of the databases to 29 February 2020.

RESULTS

Of the 69 studies identified, 55% were developed from kidney transplant recipients and 30% from liver transplant recipients. Most studies (91%) investigated the oral immediate-release formulation of tacrolimus. Few studies (17%) explained the effect of drug-drug interactions on tacrolimus PK. Only 35% of the studies performed an external evaluation to assess the generalizability of the models. Studies related variability in tacrolimus whole blood clearance among transplant recipients to either cytochrome P450 (CYP) 3A5 genotype (41%), days post-transplant (30%), or hematocrit (29%). Variability in the central volume of distribution was mainly explained by body weight (20% of studies).

CONCLUSION

The effect of clinically significant drug-drug interactions and different formulations and brands of tacrolimus should be considered for any future tacrolimus population PK model development. Further work is required to assess the generalizability of existing models and identify key factors that influence both initial and maintenance doses of tacrolimus, particularly in heart and lung transplant recipients.

Wuzhi Capsule Dosage Affects Tacrolimus Elimination in Adult Kidney Transplant Recipients, as Determined by a Population Pharmacokinetics Analysis

Purpose

In this study, we aimed to establish a tacrolimus population pharmacokinetic model and better understand the drug-drug interaction between Wuzhi capsule and tacrolimus in Chinese renal transplant recipients.

Patients and Methods

We performed a population pharmacokinetic analysis using a non-linear mixed-effects model to determine the suitable Wuzhi capsule dose in combination with tacrolimus. Data on 1378 tacrolimus steady-state concentrations were obtained from 142 patients who received kidney transplant in Changhai Hospital and Huashan Hospital. Demographic characteristics, laboratory tests, genetic polymorphisms, and co-medications were evaluated.

Results

The one-compartment model best described data. Our final model identified creatinine clearance rate, hematocrit, Wuzhi capsule dose, CYP3A5*3 genetic polymorphisms, and tacrolimus daily dose as significant covariates for tacrolimus clearance, with the value of 14.4 L h^-1, and the between-subject variability (BSV) was 25.4%. The Wuzhi capsule showed a dose-dependent effect on tacrolimus pharmacokinetics, demonstrating a stronger inhibitory effect than inductive effect.

Conclusion

Our model can accurately describe population pharmacokinetics of tacrolimus when combined with different doses of Wuzhi capsule. Additionally, this model can be used for individualizing tacrolimus dose following kidney transplantation.

Pharmacokinetics of a Once Daily Tacrolimus Formulation in First Nations and Caucasian Liver Transplant Recipients

BACKGROUND

Patient ethnicity may influence the pharmacokinetics (PK) of tacrolimus. The Canadian First Nations (FN) constitute a large and increasing segment of the liver transplant population.

OBJECTIVE

To determine whether PK differences exist for a once daily, extended-release formulation of tacrolimus in FN compared to Caucasian (Cauc) liver transplant recipients.

METHODS

Following a 1:1 mg conversion from immediate- to extended-release tacrolimus and achievement of a steady state on the latter formulation, blood samples were drawn at 0, 1, 2, 4, 6, 8 and 24 hours for whole blood tacrolimus levels by commercial immunoassay. CYP3A4 and CYP3A5 allele analyses were performed by polymerase chain reactions.

RESULTS

Nineteen subjects participated in the study (7 FN and 12 Cauc). Unlike Cauc patients, post-conversion Cmin levels did not decrease and were less variable in FN patients. FN patients also had significant shorter Tmax times (1.6±0.2 hours versus 2.8±0.3 hours, p<0.05). Oral clearance, Vd, AUCs, Cmax and Cmin levels were similar in the two cohorts. CYP3A4 genotypes were C/C in both cohorts while the CYP3A5 *1/*3 allele, was present in 2/5 FN and 0/9 Cauc.

CONCLUSIONS

Conversion from immediate- to extended-release tacrolimus results in no significant decrease in Cmin levels, less variable Cmin levels and a shorter time to Tmax in FN compared to Cauc liver transplant recipients.

Model-informed precision dosing to optimise immunosuppressive therapy in renal transplantation

Immunosuppressive therapy is pivotal for sustained allograft and patient survival after renal transplantation. However, optimally balanced immunosuppressive therapy is challenged by between-patient and within-patient pharmacokinetic (PK) variability. This could warrant the application of personalised dosing strategies to optimise individual patient outcomes. Pharmacometrics, the science that investigates the xenobiotic-biotic interplay using computer-aided mathematical modelling, provides options to describe and quantify this PK variability and enables identification of patient characteristics affecting immunosuppressant PK and treatment outcomes. Here, we review and critically appraise the available pharmacometric model-informed dosing solutions for the typical immunosuppressants in modern renal transplantation, to guide their initial and subsequent dosing.

Patient and allograft outcomes after kidney transplant for the Indigenous patients in the United States

Background

The objective is to assess cardiovascular (CV), malignancy, infectious, graft outcomes and tacrolimus levels for the Indigenous patients compared to Whites after kidney transplant (KTx).

Methods

165 Indigenous and 165 White patients matched for the KTx year at Mayo Clinic Arizona from 2007–2015 were studied over a median follow-up of 3 years. Propensity score was calculated to account for baseline differences.

Results

Compared to Whites, Indigenous patients had the following characteristics: younger age, more obesity, diabetes, hypertension, and required dialysis prior to KTx (p<0.01). Indigenous patients had longer hospital stay for KTx, shorter follow-up and lived further from the transplant center (p<0.05). 210 (63.6%) received deceased donor KTx and more Whites received a living donor KTx compared to Indigenous patients (55.2% vs 17.6%, p<0.0001). Post-KTx, there was no difference in the CV event rates. The cumulative incidence of infectious complications was higher among the Indigenous patients (HR 1.81, p = 0.0005, 48.5% vs 38.2%, p = 0.013), with urinary causes as the most common. Malignancy rates were increased among Whites (13.3% vs 3.0%, p = 0.001) with skin cancer being the most common. There was a significant increase in the dose normalized tacrolimus level for the Indigenous patients compared to Whites at 1 months, 3 months, and 1 year post-KTx. After adjustment for the propensity score, there was no statistical difference in infectious or graft outcomes between the two groups but the mean number of emergency room visits and hospitalizations after KTx was significantly higher for Whites compared to Indigenous patients.

Conclusions

Compared to Whites, Indigenous patients have similar CV events, graft outcomes and infectious complications after accounting for baseline differences.

Tacrolimus troughs and genetic determinants of metabolism in kidney transplant recipients: A comparison of four ancestry groups

Tacrolimus trough and dose requirements vary dramatically between individuals of European and African American ancestry. These differences are less well described in other populations. We conducted an observational, prospective, multicenter study from which 2595 kidney transplant recipients of European, African, Native American, and Asian ancestry were studied for tacrolimus trough, doses, and genetic determinants of metabolism. We studied the well-known variants and conducted a CYP3A4/5 gene-wide analysis to identify new variants. Daily doses, and dose-normalized troughs were significantly different between the four groups (P < .001). CYP3A5*3 (rs776746) was associated with higher dose-normalized tacrolimus troughs in all groups but occurred at different allele frequencies and had differing effect sizes. The CYP3A5*6 (rs10264272) and *7 (rs413003343) variants were only present in African Americans. CYP3A4*22 (rs35599367) was not found in any of the Asian ancestry samples. We identified seven suggestive variants in the CYP3A4/5 genes associated with dose-normalized troughs in Native Americans (P = 1.1 × 10^-5 -8.8 × 10^-6 ) and one suggestive variant in Asian Americans (P = 5.6 × 10^-6 ). Tacrolimus daily doses and dose-normalized troughs vary significantly among different ancestry groups. We identified potential new variants important in Asians and Native Americans. Studies with larger populations should be conducted to assess the importance of the identified suggestive variants.

Evaluating tacrolimus pharmacokinetic models in adult renal transplant recipients with different CYP3A5 genotypes

PURPOSE

Numerous studies have been conducted on the population pharmacokinetics of tacrolimus in adult renal transplant recipients. It has been reported that the cytochrome P450 (CYP) 3A5 genotype is an important cause of variability in tacrolimus pharmacokinetics. However, the predictive performance of population pharmacokinetic (PK) models of tacrolimus should be evaluated prior to their implementation in clinical practice. The aim of the study reported here was to test the predictive performance of these published PK models of tacrolimus.

METHODS

A literature search of the PubMed and Web of Science databases ultimately led to the inclusion of eight one-compartment models in our analysis. We collected a total of 1715 trough concentrations from 174 patients. Predictive performance was assessed based on visual and numerical comparison bias and imprecision and by the use of simulation-based diagnostics and Bayesian forecasting.

RESULTS

Of the eight one-compartment models assessed, seven showed better predictive performance in CYP3A5 extensive metabolizers in terms of bias and imprecision. Results of the simulation-based diagnostics also supported the findings. The model based on a Chinese population in 2013 (model 3) showed the best and most stable predictive performance in all the tests and was more informative in CYP3A5 extensive metabolizers. As expected, Bayesian forecasting improved model predictability. Diversity among models and between different CYP3A5 genotypes of the same model was also narrowed by Bayesian forecasting.

CONCLUSIONS

Based on our results, we recommend using model 3 in CYP3A5 extensive metabolizers in clinical practice. All models had a poor predictive performance in CYP3A5 poor metabolizers, and they should be used with caution in this patient population. However, Bayesian forecasting improved the predictability and reduced differences, and thus the models could be applied in this latter patient population for the design of maintenance dose.

External evaluation of published population pharmacokinetic models of tacrolimus in adult renal transplant recipients

AIM

Several tacrolimus population pharmacokinetic models in adult renal transplant recipients have been established to facilitate dose individualization. However, their applicability when extrapolated to other clinical centres is not clear. This study aimed to (1) evaluate model external predictability and (2) analyze potential influencing factors.

METHODS

Published models were screened from the literature and were evaluated using an external dataset with 52 patients (609 trough samples) collected by postoperative day 90 via methods that included (1) prediction-based prediction error (PE%), (2) simulation-based prediction- and variability-corrected visual predictive check (pvcVPC) and normalized prediction distribution error (NPDE) tests and (3) Bayesian forecasting to assess the influence of prior observations on model predictability. The factors influencing model predictability, particularly the impact of structural models, were evaluated.

RESULTS

Sixteen published models were evaluated. In prediction-based diagnostics, the PE% within ±30% was less than 50% in all models, indicating unsatisfactory predictability. In simulation-based diagnostics, both the pvcVPC and the NPDE indicated model misspecification. Bayesian forecasting improved model predictability significantly with prior 2-3 observations. The various factors influencing model extrapolation included bioassays, the covariates involved (CYP3A5*3 polymorphism, postoperative time and haematocrit) and whether non-linear kinetics were used.

CONCLUSIONS

The published models were unsatisfactory in prediction- and simulation-based diagnostics, thus inappropriate for direct extrapolation correspondingly. However Bayesian forecasting could improve the predictability considerably with priors. The incorporation of non-linear pharmacokinetics in modelling might be a promising approach to improving model predictability.

Population pharmacokinetic analysis of tacrolimus in Mexican paediatric renal transplant patients: role of CYP3A5 genotype and formulation

AIMS

The aims of this study were (i) to develop a population pharmacokinetic (PK) model of tacrolimus in a Mexican renal transplant paediatric population (n = 53) and (ii) to test the influence of different covariates on its PK properties to facilitate dose individualization.

METHODS

Population PK and variability parameters were estimated from whole blood drug concentration profiles obtained at steady-state using the non-linear mixed effect modelling software NONMEM® Version 7.2.

RESULTS

Tacrolimus PK profiles exhibited high inter-patient variability (IPV). A two compartment model with first order input and elimination described the tacrolimus PK profiles in the studied population. The relationship between CYP3A5 genotype and tacrolimus CL/F was included in the final model. CL/F in CYP3A5*1/*1 and *1/*3 carriers was approximately 2- and 1.5-fold higher than in CYP3A5*3/*3 carriers (non-expressers), respectively, and explained almost the entire IPV in CL/F. Other covariates retained in the final model were the tacrolimus dose and formulation type. Limustin® showed markedly lower concentrations than the rest of the formulations.

CONCLUSIONS

Population PK modelling of tacrolimus in paediatric renal transplant recipients identified the tacrolimus formulation type as a significant covariate affecting the blood concentrations and confirmed the previously reported significant effect of CYP3A5 genotype on CL/F. It allowed the design of a proposed dosage based on the final model that is expected to help to improve tacrolimus dosing.

Pharmacogenetics in American Indian populations: analysis of CYP2D6, CYP3A4, CYP3A5, and CYP2C9 in the Confederated Salish and Kootenai Tribes

OBJECTIVES

Cytochrome P450 enzymes play a dominant role in drug elimination and variation in these genes is a major source of interindividual differences in drug response. Little is known, however, about pharmacogenetic variation in American Indian and Alaska Native (AI/AN) populations. We have developed a partnership with the Confederated Salish and Kootenai Tribes (CSKT) in northwestern Montana to address this knowledge gap.

METHODS

We resequenced CYP2D6 in 187 CSKT individuals and CYP3A4, CYP3A5, and CYP2C9 in 94 CSKT individuals.

RESULTS

We identified 67 variants in CYP2D6, 15 in CYP3A4, 10 in CYP3A5, and 41 in CYP2C9. The most common CYP2D6 alleles were CYP2D6*4 and *41 (20.86 and 11.23%, respectively). CYP2D6*3, *5, *6, *9, *10, *17, *28, *33, *35, *49, *1xN, *2xN, and *4xN frequencies were less than 2%. CYP3A5*3, CYP3A4*1G, and *1B were detected with frequencies of 92.47, 26.81, and 2.20%, respectively. Allelic variation in CYP2C9 was low: CYP2C9*2 (5.17%) and *3 (2.69%). In general, allele frequencies in CYP2D6, CYP2C9, and CYP3A5 were similar to those observed in European Americans. There was, however, a marked divergence in CYP3A4 for the CYP3A4*1G allele. We also observed low levels of linkage between CYP3A4*1G and CYP3A5*1 in the CSKT. The combination of nonfunctional CYP3A5*3 and putative reduced function CYP3A4*1G alleles may predict diminished clearance of CYP3A substrates.

CONCLUSION

These results highlight the importance of carrying out pharmacogenomic research in AI/AN populations and show that extrapolation from other populations is not appropriate. This information could help optimize drug therapy for the CSKT population.

Genetic differences in Native Americans and tacrolimus dosing after kidney transplantation

Tacrolimus pharmacokinetics vary due to single nucleotide polymorphisms (SNPs) in metabolizing enzymes and membrane transporters that alter drug elimination. Clinically we observed that Native Americans require lower dosages of tacrolimus to attain trough levels similar to Caucasians. We previously demonstrated that Native Americans have decreased oral clearance of tacrolimus, suggesting that Native Americans may have more variant SNPs and, therefore, altered tacrolimus pharmacokinetic parameters. We conducted 12-hour pharmacokinetic studies on 24 adult Native American kidney transplant recipients on stable doses of tacrolimus for at least 1 month posttransplantation. Twenty-four Caucasian kidney transplant recipients were compared as controls. SNPs encoding the genes for the enzymes (CYP3A4, CYP3A5) and transporters (ABCB1, BCRP, and MRP1) were typed using TaqMan. The mean daily tacrolimus dose in the Native Americans was 0.03 ± 0.02 compared with the Caucasians 0.5 ± 0.3 (mg/kg/d; P = .002), with no significant differences in trough levels, (6.7 ± 3.1 vs 7.4 ± 2.1 ng/dL; P = .4). Many Native Americans, but not Caucasians, demonstrated the 3/*3 - C3435T CC and the *3/*3 -G2677T GG genotype combination previously associated with low tacrolimus dosing. Native Americans required significantly lower tacrolimus doses than Caucasians to achieve similar tacrolimus trough levels, in part due to lower tacrolimus clearance from decreased drug metabolism and excretion.