CYP3A5 and CYP3A7 genetic polymorphisms affect tacrolimus concentration in pediatric patients with nephrotic range proteinuria

Cytochrome P450 3A gene family and medication in childhood nephrotic syndrome: An update

Background

Nephrotic syndrome (NS) is a renal disease characterized by excessive proteinuria (greater than 3.5 g/dl per 24 h), which results in hypoalbuminemia and leads to hyperlipidemia, edema, and various complications. NS patients typically respond to standard steroid treatment (prednisolone) and are classified as having steroid-sensitive nephrotic syndrome (SSNS). However, patients who do not respond to steroid therapy after 4 weeks are referred to as having steroid-resistant nephrotic syndrome (SRNS). The unequal response to steroid treatment in nephrotic syndrome involved many factors, including genetic, medication, and kidney diseases. The CYP3A gene family is predominantly involved in the metabolism of medications used in the treatment of NS.

Methodology

A systematic literature review was conducted from January 2014 to June 2024 using an extensive electronic search of data related to pediatric nephrotic syndrome and the CYP gene family, including associated polymorphisms. Through this review, we systematically analyze factors that affect the metabolism of medications targeting the CYP3A gene family (including steroidal and non-steroidal drugs) commonly used in the treatment of NS and its comorbidities.

Conclusion

Studies have correlated the relationship between polymorphisms in the CYP3A gene family and medication in NS, with 90 % of the research focusing primarily on post-kidney transplant NS patients. Many studies have reported a correlation between CYP3A gene family polymorphisms and increased tacrolimus (TAC) dosage.

Trends in Precision Medicine and Pharmacogenetics as an Adjuvant in Establishing a Correct Immunosuppressive Therapy for Kidney Transplant: An Up-to-Date Historical Overview

Kidney transplantation is currently the treatment of choice for patients with end-stage kidney diseases. Although significant advancements in kidney transplantation have been achieved over the past decades, the host's immune response remains the primary challenge, often leading to potential graft rejection. Effective management of the immune response is essential to ensure the long-term success of kidney transplantation. To address this issue, immunosuppressives have been developed and are now fully integrated into the clinical management of transplant recipients. However, the considerable inter- and intra-patient variability in pharmacokinetics (PK) and pharmacodynamics (PD) of these drugs represents the primary cause of graft rejection. This variability is primarily attributed to the polymorphic nature (genetic heterogeneity) of genes encoding xenobiotic-metabolizing enzymes, transport proteins, and, in some cases, drug targets. These genetic differences can influence drug metabolism and distribution, leading to either toxicity or reduced efficacy. The main objective of the present review is to report an historical overview of the pharmacogenetics of immunosuppressants, shedding light on the most recent findings and also suggesting how relevant is the research and investment in developing validated NGS-based commercial panels for pharmacogenetic profiling in kidney transplant recipients. These advancements will enable the implementation of precision medicine, optimizing immunosuppressive therapies to improve graft survival and kidney transplanted patient outcomes.

Drug-drug interaction between diltiazem and tacrolimus in relation to CYP3A5 genotype status in Chinese pediatric patients with nephrotic range proteinuria: a retrospective study

Background

Tacrolimus is widely used to treat pediatric nephrotic range proteinuria (NRP). Diltiazem, a CYP3A4/5 inhibitor, is often administered with tacrolimus, affecting its pharmacokinetic profile. The impact of this combination on tacrolimus exposure, particularly in CYP3A5*3 genetic polymorphism, remains unclear in pediatric NRP patients. This study aimed to evaluate the effects of diltiazem on tacrolimus pharmacokinetics, focusing on the CYP3A5*3 polymorphism.

Methods

We conducted a retrospective clinical study involving pediatric NRP patients, divided into two groups: those receiving tacrolimus with diltiazem and those receiving tacrolimus alone. Propensity score matching (PSM) was used to balance the baseline characteristics between the groups. We compared daily dose-adjusted trough concentrations (C0/D) of tacrolimus in both the original and PSM cohorts. The influence of diltiazem on tacrolimus C0/D, stratified by CYP3A5*3 genetic polymorphism, was assessed in a self-controlled case series study.

Results

Before PSM, the tacrolimus C0/D in patients taking diltiazem was significantly higher compared to those with tacrolimus alone (75.84 vs. 56.86 ng/mL per mg/kg, P = 0.034). This finding persisted after PSM (75.84 vs. 46.93 ng/mL per mg/kg, P= 0.028). In the self-controlled case study, tacrolimus C0/D elevated about twofold (75.84 vs. 34.76 ng/mL per mg/kg, P < 0.001) after diltiazem administration. CYP3A5 expressers (CYP3A5*1/*1 and *1/*3) and CYP3A5 non-expressers (CYP3A5*3/*3) experienced a 1.8-fold and 1.3-fold increase in tacrolimus C0/D when combined with diltiazem, respectively.

Conclusion

Diltiazem significantly increased tacrolimus C0/D, with CYP3A5*3 expressers showing higher elevations than non-expressers among pediatric NRP patients. These findings highlight the importance of personalized tacrolimus therapy based on CYP3A5*3 genotypes in pediatric patients taking diltiazem.

A comprehensive Thai pharmacogenomics database (TPGxD-1): Phenotype prediction and variants identification in 942 whole-genome sequencing data

Computational methods analyze genomic data to identify genetic variants linked to drug responses, thereby guiding personalized medicine. This study analyzed 942 whole-genome sequences from the Electricity Generating Authority of Thailand (EGAT) cohort to establish a population-specific pharmacogenomic database (TPGxD-1) in the Thai population. Sentieon (version 201808.08) implemented the GATK best workflow practice for variant calling. We then annotated variant call format (VCF) files using Golden Helix VarSeq 2.5.0 and employed Stargazer v2.0.2 for star allele analysis. The analysis of 63 very important pharmacogenes (VIPGx) reveals 85,566 variants, including 13,532 novel discoveries. Notably, we identified 464 known PGx variants and 275 clinically relevant novel variants. The phenotypic prediction of 15 VIPGx demonstrated a varied metabolic profile for the Thai population. Genes like CYP2C9 (9%), CYP3A5 (45.2%), CYP2B6 (9.4%), NUDT15 (15%), CYP2D6 (47%) and CYP2C19 (43%) showed a high number of intermediate metabolizers; CYP3A5 (41%), and CYP2C19 (9.9%) showed more poor metabolizers. CYP1A2 (52.7%) and CYP2B6 (7.6%) were found to have a higher number of ultra-metabolizers. The functional prediction of the remaining 10 VIPGx genes reveals a high frequency of decreased functional alleles in SULT1A1 (12%), NAT2 (84%), and G6PD (12%). SLCO1B1 reports 20% poor functional alleles, while PTGIS (42%), SLCO1B1 (4%), and TPMT (5.96%) showed increased functional alleles. This study discovered new variants and alleles in the 63 VIPGx genes among the Thai population, offering insights into advancing clinical pharmacogenomics (PGx). However, further validation is needed using other computational and genotyping methods.

Genotypic and phenotypic landscapes of 51 pharmacogenes derived from whole-genome sequencing in a Thai population

Differences in drug responses in individuals are partly due to genetic variations in pharmacogenes, which differ among populations. Here, genome sequencing of 171 unrelated Thai individuals from all regions of Thailand was used to call star alleles of 51 pharmacogenes by Stargazer, determine allele and genotype frequencies, predict phenotype and compare high-impact variant frequencies between Thai and other populations. Three control genes, EGFR, VDR, and RYR1, were used, giving consistent results. Every individual had at least three genes with variant or altered phenotype. Forty of the 51 pharmacogenes had at least one individual with variant or altered phenotype. Moreover, thirteen genes had at least 25% of individuals with variant or altered phenotype including SLCO1B3 (97.08%), CYP3A5 (88.3%), CYP2C19 (60.82%), CYP2A6 (60.2%), SULT1A1 (56.14%), G6PD (54.39%), CYP4B1 (50.00%), CYP2D6 (48.65%), CYP2F1 (46.41%), NAT2 (40.35%), SLCO2B1 (28.95%), UGT1A1 (28.07%), and SLCO1B1 (26.79%). Allele frequencies of high impact variants from our samples were most similar to East Asian. Remarkably, we identified twenty predicted high impact variants which have not previously been reported. Our results provide information that contributes to the implementation of pharmacogenetic testing in Thailand and other Southeast Asian countries, bringing a step closer to personalized medicine.

CYP3A7, CYP3A4, and CYP3A5 genetic polymorphisms in recipients rather than donors influence tacrolimus concentrations in the early stages after liver transplantation

AIM

The purpose of this study was to investigate the effect of CYP3A7, CYP3A4, and CYP3A5 genetic polymorphisms in liver transplant recipients and donors on tacrolimus concentrations in the early stages after liver transplantation.

METHODS

One hundred and thirty-eight liver transplant recipients and matched donors were genotyped for CYP3A7 (rs10211 and rs2257401), CYP3A4 (rs4646437 and rs2242480), and CYP3A5*3 (rs776746) polymorphisms. The relationships between dose-adjusted trough concentrations (C₀/D) of tacrolimus and corresponding genotypes were investigated.

RESULTS

Recipient CYP3A polymorphisms were associated with tacrolimus concentrations. The CYP3A7 rs10211 AA carriers (186.2 vs 90.5, p < 0.001), CYP3A4 rs4646437 CC carriers (184.0 vs 88.8, p < 0.001), CYP3A4*1G rs2242480 CC carriers (189.8 vs 99.7, p < 0.001), and CYP3A5*3 rs776746 GG carriers (197.3 vs 86.0, p < 0.001) had an almost twofold increase in the tacrolimus C₀/D compared to that of the non-carriers. We further investigated the effect of the combination of recipient (intestinal) and donor (hepatic) genotypes on tacrolimus concentrations. Regardless of the genotype of the matched donor, CYP3A7 rs10211, CYP3A4*1G (rs2242480), and CYP3A5*3 (rs776746) polymorphisms of recipients could affect tacrolimus concentrations. For the CYP3A4 rs4646437 polymorphisms, when the donor carried CYP3A4 rs4646437 CC, the recipient CYP3A4 rs4646437 polymorphism was associated with the C₀/D of tacrolimus, and when the donor carried CYP3A4 rs4646437 CT/TT genotype, the recipient CYP3A4 rs4646437 polymorphism also affected on tacrolimus C₀/D, although the effect was not significant.

CONCLUSION

The large inter-individual variation in tacrolimus concentrations in the early stages after liver transplantation is influenced by genetic polymorphisms of CYP3A7, CYP3A4, and CYP3A5. Recipient (intestinal) CYP3A7, CYP3A4, and CYP3A5 polymorphisms seem to contribute more to such variation than donors. Therefore, the detection of CYP3A polymorphisms in recipients could help to predict the tacrolimus starting dose in the early stages after liver transplantation.

Treatment optimization of maintenance immunosuppressive agents in pediatric renal transplant recipients

Introduction: Graft survival in pediatric kidney transplant patients has increased significantly within the last three decades, correlating with the discovery and utilization of new immunosuppressants as well as improvements in patient care. Despite these developments in graft survival for patients, there is still improvement needed, particularly in long-term care in pediatric patients receiving grafts from deceased donor patients. Maintenance immunosuppressive therapies have narrow therapeutic indices and are associated with high inter-individual and intra-individual variability.Areas covered: In this review, we examine the impact of pharmacokinetic variability on renal transplantation and its association with age, genetic polymorphisms, drug-drug interactions, drug-disease interactions, renal insufficiency, route of administration, and branded versus generic drug formulation. Pharmacodynamics are outlined in terms of the mechanism of action for each immunosuppressant, potential adverse effects, and the utility of pharmacodynamic biomarkers.Expert opinion: Acquiring abetter quantitative understanding of immunosuppressant pharmacokinetics and pharmacodynamic components should help clinicians implement treatment regimens to maintain the balance between therapeutic efficacy and drug-related toxicity.

Effect of the Most Relevant CYP3A4 and CYP3A5 Polymorphisms on the Pharmacokinetic Parameters of 10 CYP3A Substrates

Several cytochrome P450 (CYP) CYP3A polymorphisms were associated with reduced enzyme function. We aimed to evaluate the influence of these alleles on the pharmacokinetic parameters (PK) of several CYP3A substrates. We included 251 healthy volunteers who received a single dose of ambrisentan, atorvastatin, imatinib, aripiprazole, fentanyl, amlodipine, donepezil, olanzapine, fesoterodine, or quetiapine. The volunteers were genotyped for CYP3A4 and CYP3A5 polymorphisms by qPCR. To compare the PK across studies, measurements were corrected by the mean of each parameter for every drug and were logarithmically transformed. Neither CYP3A phenotype nor individual CYP3A4 or CYP3A5 polymorphisms were significantly associated with differences in PK. However, regarding the substrates that are exclusively metabolized by CYP3A, we observed a higher normalized AUC (p = 0.099) and a tendency of lower normalized Cl (p = 0.069) in CYP3A4 mutated allele carriers what was associated with diminished drug metabolism capacity. CYP3A4 polymorphisms did not show a pronounced influence on PK of the analysed drugs. If so, their impact could be detectable in a very small percentage of subjects. Although there are few subjects carrying CYP3A4 double mutations, the effect in those might be relevant, especially due to the majority of subjects lacking the CYP3A5 enzyme. In heterozygous subjects, the consequence might be less noticeable due to the high inducible potential of the CYP3A4 enzyme.