Association of P450 Oxidoreductase Gene Polymorphism with Tacrolimus Pharmacokinetics in Renal Transplant Recipients: A Systematic Review and Meta-Analysis

Effects of CYP3A4*22 and POR*28 variations on the pharmacokinetics of tacrolimus in renal transplant recipients: a meta-analysis of 18 observational studies

PURPOSE

This study aimed to investigate the association between cytochrome P450 (CYP) 3A4*22 and cytochrome P450 oxidoreductase (POR)*28 variations and the pharmacokinetics of tacrolimus.

METHODS

Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science (SCI), MEDLINE, and Embase were systematically searched from inception to August 2022. The outcomes were weight-adjusted daily dose and dose-adjusted trough concentration (C0/Dose).

RESULTS

The study included 2931 renal transplant recipients from 18 publications. Weight-adjusted daily dose of CYP3A4*1/*1 carriers was 0.04 (WMD = 0.04, 95% CI: 0.02 to 0.06), 0.03 (WMD = 0.03, 95% CI: 0.02 to 0.05), 0.02 (WMD = 0.02, 95% CI: 0.01 to 0.03), or 0.02 mg/kg/day (WMD = 0.02, 95% CI: 0.00 to 0.04) higher than CYP3A4*22 carriers in Caucasians at 1 month, 3 months, 6 months, or 12 months post-transplantation. Conversely, C0/Dose was lower for CYP3A4*1/*1 carriers at 3 days (SMD = -0.35, 95% CI: -0.65 to -0.06), 1 month (SMD = -0.67, 95% CI: -1.16 to -0.18), 3 months (SMD = -0.60, 95% CI: -0.89 to -0.31), 6 months (SMD = -0.76, 95% CI: -1.49 to -0.04), or 12 months post-transplantation (SMD = -0.69, 95% CI: -1.37 to 0.00). Furthermore, C0/Dose of POR*1/*1 carriers was 22.64 (WMD = 22.64, 95% CI: 2.54 to 42.74) or 19.41 (ng/ml)/(mg/kg/day) (WMD = 19.41, 95% CI: 9.58 to 29.24) higher than POR*28 carriers in CYP3A5 expressers at 3 days or 7 days post-transplantation, and higher in Asians at 6 months post-transplantation (SMD = 0.96, 95% CI: 0.50 to 1.43).

CONCLUSIONS

CYP3A4*22 variant in Caucasians restrains the metabolism of tacrolimus, while POR*28 variant in CYP3A5 expressers enhances the metabolism of tacrolimus for renal transplant recipients. However, further well-designed prospective studies are necessary to substantiate these conclusions given some limitations.

Importance of Pharmacogenetics and Drug-Drug Interactions in a Kidney Transplanted Patient

Tacrolimus (TAC) is a narrow-therapeutic-range immunosuppressant drug used after organ transplantation. A therapeutic failure is possible if drug levels are not within the therapeutic range after the first year of treatment. Pharmacogenetic variants and drug-drug interactions (DDIs) are involved. We describe a patient case of a young man (16 years old) with a renal transplant receiving therapy including TAC, mycophenolic acid (MFA), prednisone and omeprazole for prophylaxis of gastric and duodenal ulceration. The patient showed great fluctuation in TAC blood concentration/oral dose ratio, as well as pharmacotherapy adverse effects (AEs) and frequent diarrhea episodes. Additionally, decreased kidney function was found. A pharmacotherapeutic follow-up, including pharmacogenetic analysis, was carried out. The selection of the genes studied was based on the previous literature (CYP3A5, CYP3A4, POR, ABCB1, PXR and CYP2C19). A drug interaction with omeprazole was reported and the nephrologist switched to rabeprazole. A lower TAC concentration/dose ratio was achieved, and the patient's condition improved. In addition, the TTT haplotype of ATP Binding Cassette Subfamily B member 1 (ABCB1) and Pregnane X Receptor (PXR) gene variants seemed to affect TAC pharmacotherapy in the studied patient and could explain the occurrence of long-term adverse effects post-transplantation. These findings suggest that polymorphic variants and co-treatments must be considered in order to achieve the effectiveness of the immunosuppressive therapy with TAC, especially when polymedicated patients are involved. Moreover, pharmacogenetics could influence the drug concentration at the cellular level, both in lymphocyte and in renal tissue, and should be explored in future studies.

Developing supervised machine learning algorithms to evaluate the therapeutic effect and laboratory-related adverse events of cyclosporine and tacrolimus in renal transplants

BACKGROUND

Single nucleotide polymorphisms influence the effects of tacrolimus and cyclosporine in renal transplants.

AIM

We set out to use machine learning algorithms (MLAs) to identify variables that predict the therapeutic effects and adverse events following tacrolimus and cyclosporine administration in renal transplant patients.

METHOD

We sampled 120 adult renal transplant patients (on cyclosporine or tacrolimus). Generalized linear model (GLM), support vector machine (SVM), artificial neural network (ANN), Chi-square automatic interaction detection, classification and regression tree, and K-nearest neighbors were the chosen MLAs. The mean absolute error (MAE), relative mean square error (RMSE), and regression coefficient (β) with a 95% confidence interval (CI) were used as the model parameters.

RESULTS

For a stable dose of tacrolimus, the MAEs (RMSEs) of GLM, SVM, and ANN were 1.3 (1.5), 1.3 (1.8), and 1.7 (2.3) mg/day, respectively. GLM revealed that the POR*28 genotype and age significantly predicted the stable dose of tacrolimus as follows: POR*28 (β -1.8; 95% CI -3, -0.5; p = 0.006), and age (β -0.04; 95% CI -0.1, -0.006; p = 0.02). For a stable dose of cyclosporine, MAEs (RMSEs) of 93.2 (103.4), 79.1 (115.2), and 73.7 (91.7) mg/day were observed with GLM, SVM, and ANN, respectively. GLM revealed the following predictors of a stable dose of cyclosporine: CYP3A5*3 (β -80.8; 95% CI -130.3, -31.2; p = 0.001), and age (β -3.4; 95% CI -5.9, -0.9; p = 0.007).

CONCLUSION

We observed that various MLAs could identify significant predictors that were useful to optimize tacrolimus and cyclosporine dosing regimens; yet, the findings must be externally validated.

Impacts of pregnane X receptor and cytochrome P450 oxidoreductase gene polymorphisms on trough concentrations of apixaban in patients with non-valvular atrial fibrillation

PURPOSE

We examined the impact of polymorphisms in genes encoding cytochrome P450 (CYP) 3A5 (gene code CYP3A5), P-glycoprotein (ABCB1), breast cancer resistance protein (ABCG2), cytochrome P450 oxidoreductase (POR), and pregnane X receptor (PXR; NR1I2) on the daily dose-adjusted steady-state trough concentrations (C_0h/D) of apixaban.

METHODS

The analyses included 104 patients with non-valvular atrial fibrillation (NVAF) undergoing AF catheter ablation. The CYP3A5*3; ABCG2 421C > A; ABCB1 1236C > T, 2677G > A/T, 3435C > T, and 2482-2236G > A; NR1I2 11156A > C, 11193T > C, and 8055C > T; and POR*28 genotypes were determined. The combination of the noted NR1I2 genotypes determined the PXR*1B haplotype.

RESULTS

Multiple linear regression analyses demonstrated that decreased creatinine clearance (Ccr) and the PXR*1B/*1B haplotype correlated with increased C_0h/D of apixaban, while the presence of the POR*28 allele correlated with decreased C_0h/D of apixaban (partial R² = 0.168, 0.029, and 0.044, all P < 0.05). The mean (95% CI) of estimated marginal means of apixaban C_0h/D calculated using Ccr as a covariate was the highest in POR*28 noncarriers with PXR*1B/*1B (23.5 [21.0-25.9] ng/mL/[mg/day]) and lowest in POR*28 carriers with other haplotypes (16.6 [15.5-17.7] ng/mL/[mg/day]).

CONCLUSION

The PXR*1B haplotype and POR*28 genotype statuses, which involve genes that impact the expression of multiple drug-metabolizing enzymes and drug-transporters, may have modest effects on the C_0h/D of apixaban, but these effects were found to be small.

Association Studies in Clinical Pharmacogenetics

In recent times, the progress of Clinical Pharmacogenetics has been remarkable [...].

Genetic factors underlying tacrolimus intolerance after liver transplantation

Background

Tacrolimus (FK506) is the cornerstone of immunosuppression after liver transplantation (LT), however, clinically, switching from FK506 to cyclosporine (SFTC) is common in LT patients with tacrolimus intolerance. The aim of this study was to investigate the genetic risk of patients with tacrolimus intolerance.

Methods

A total of 114 LT patients were enrolled in this retrospective study. SNPs were genotyped using Infinium Human Exome-12 v1.2 BeadChip, and genome-wide gene expression levels were profiled using Agilent G4112F array.

Results

SFTC was a potential risk factor of dyslipidemia (OR=4.774[1.122-20.311], p = 0.034) and insulin resistance (IR) (OR=6.25[1.451-26.916], p = 0.014), but did not affect the survival of LT patients. Differential expression analysis showed donor CYP3A5, CYP2C9, CFTR, and GSTP1, four important pharmacogenetic genes were significantly up-regulated in the tacrolimus intolerance group. Twelve SNPs of these four genes were screened to investigate the effects on tacrolimus intolerance. Regression analysis showed donor rs4646450 (OR=3.23 [1.22-8.60] per each A allele, p = 0.01), donor rs6977165 (OR=6.44 [1.09-37.87] per each C allele, p = 0.02), and donor rs776746 (OR=3.31 [1.25-8.81] per each A allele, p = 0.01) were independent risk factors of tacrolimus intolerance.

Conclusions

These results suggested that SFTC was a potential risk factor for dyslipidemia and IR after LT. Besides, rs4646450, rs6977165, and rs776746 of CYP3A5 might be the underlying genetic risks of tacrolimus intolerance. This might help transplant surgeons make earlier clinical decisions about the use of immunosuppression.

Evaluation of Pharmacogenetics of Drug-Metabolizing Enzymes and Drug Efflux Transporter in Renal Transplants Receiving Immunosuppressants

Cytochrome P450 (CYP) enzymes, such as CYP3A4, and CYP3A5, P450 oxidoreductase (POR), peroxisome proliferator activated receptor alpha (PPAR-alpha), and drug transporter (ABCB1) were observed to influence concentrations of immunosuppressants (cyclosporine, everolimus, sirolimus, and tacrolimus) and outcomes in renal transplants. We carried out the present study to evaluate the prevalence and impact of these single nucleotide polymorphisms (SNPs) in adult renal transplants. SNPs were evaluated using commercial TaqMan^® assays. Serum drug concentrations were estimated using immunoassays. One hundred and forty-six patients were recruited. SNPs in CYP3A5*3 were significantly associated with greater dose-adjusted cyclosporine and tacrolimus concentrations. SNPs in POR*28 were observed with significantly lower dose-adjusted concentrations, particularly with cyclosporine and tacrolimus. ABCB1 homozygous polymorphisms were observed with significantly lower time spent in the therapeutic range with cyclosporine and everolimus/sirolimus. Cyclosporine was observed in a significantly greater proportion of patients with elevated GGT, and SNPs in PPAR-alpha were significantly associated with an increased risk of this adverse event. Hypertriglyceridemia with everolimus was significantly associated with POR*28 polymorphisms. There is a need to validate the influence of these SNPs in a prospective study and develop an algorithm predicting the achievement of target concentrations.