Effect of CYP3 A4, CYP3 A5 and ABCB1 gene polymorphisms on the clinical efficacy of tacrolimus in the treatment of nephrotic syndrome

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.

Tacrolimus in the treatment of childhood nephrotic syndrome: Machine learning detects novel biomarkers and predicts efficacy

STUDY OBJECTIVE

The pharmacokinetics and pharmacodynamics of tacrolimus (TAC) vary greatly among individuals, hindering its precise utilization. Moreover, effective models for the early prediction of TAC efficacy in patients with nephrotic syndrome (NS) are lacking. We aimed to identify key factors affecting TAC efficacy and develop efficacy prediction models for childhood NS using machine learning algorithms.

DESIGN

This was an observational cohort study of patients with pediatric refractory NS.

SETTING

Guangzhou Women and Children's Medical Center between June 2013 and December 2018.

PATIENTS

203 patients with pediatric refractory NS were used for model generation and 35 patients were used for model validation.

INTERVENTION

All patients regularly received double immunosuppressive therapy comprising TAC and low-dose prednisone or methylprednisolone. In this observational cohort study of 203 pediatric patients with refractory NS, clinical and genetic variables, including single-nucleotide polymorphism (SNPs), were identified. TAC efficacy was evaluated 3 months after administration according to two different evaluation criteria: response or non-response (Group 1) and complete remission, partial remission, or non-remission (Group 2).

MEASUREMENTS

Logistic regression, extremely random trees, gradient boosting decision trees, random forest, and extreme gradient boosting algorithms were used to develop and validate the models. Prediction models were validated among a cohort of 35 patients with NS.

MAIN RESULTS

The random forest models performed best in both groups, and the area under the receiver operating characteristics curve of these two models was 80.7% (Group 1) and 80.3% (Group 2). These prediction models included urine erythrocyte count before administration, steroid types, and eight SNPs (ITGB4 rs2290460, TRPC6 rs3824934, CTGF rs9399005, IL13 rs20541, NFKBIA rs8904, NFKBIA rs8016947, MAP3K11 rs7946115, and SMARCAL1 rs11886806).

CONCLUSIONS

Two pre-administration models with good predictive performance for TAC response of patients with NS were developed and validated using machine learning algorithms. These accurate models could assist clinicians in predicting TAC efficacy in pediatric patients with NS before utilization to avoid treatment failure or adverse effects.

ABCB1 gene polymorphisms impact the effect of high-dose intravenous methylprednisolone therapy on optic neuritis associated with AQP4-IgG-positive neuromyelitis optica spectrum disorder

WHAT IS KNOWN AND OBJECTIVE

Patients with optic neuritis (ON) have significant individual differences in their response to high-dose intravenous methylprednisolone (HIMP) therapy. This study aims to evaluate the association between gene polymorphisms and the efficacy of HIMP therapy in Chinese Han patients with ON mediated by aquaporin-4 immunoglobulin G antibody (AQP4-IgG) -positive neuromyelitis optica spectrum disorder (NMOSD) or multiple sclerosis (MS).

METHODS

Chinese Han patients with AQP4-IgG⁺ NMOSD-ON or MS-ON were genotyped for four candidate genes: ABCB1 (rs1045642, rs1128503, rs2032582), NR3C1 (rs41423247), TBX21 (rs9910408, rs16947078) and VDR (rs731236, rs1544410, rs7975232, rs2228570). Patients were divided into glucocorticoid resistance (GR) and glucocorticoid sensitivity (GS) groups based on vision acuity (VA) improvement after HIMP treatment. Intergroup comparisons were performed on clinical characteristics, allele and genotype frequencies and haplotype distributions.

RESULTS

A total of 267 patients completed the follow-up, including 120 patients with AQP4-IgG⁺ NMOSD-ON and 147 patients with MS-ON. We observed a significant association between the ABCB1 G2677T/A (rs2032582) polymorphism and glucocorticoid response in AQP4-IgG⁺ NMOSD-ON patients. Changes in VA scores in patients with the GG genotype were significantly lower than those in patients with the T/A T/A genotype (1.07 ± 1.20 vs. 1.77 ± 1.31, p = 0.026). In the GS group, the G allele had a lower frequency than the T/A allele (32.03% vs. 60.16%, p = 0.001). Logistic regression analysis showed that the G2677T/A GG and G T/A genotypes could increase the GR risk 3.53 and 2.67 times compared with the T/A T/A genotype, respectively (OR = 3.534, 95% CI: 1.186-10.527, p = 0.023; OR = 2.675, 95% CI: 1.005-7.123, p = 0.049). In addition, haplotype analysis showed that AQP4-IgG⁺ NMOSD-ON patients with the TAT/TTT haplotype (ABCB1 C3435T-G2677T/A-C1236T) were only 0.54 times more likely to develop GR than those with other haplotypes (OR = 0.542, 95% CI: 0.315-0.932, p = 0.026). However, we did not observe intergroup differences in the MS-ON population.

WHAT IS NEW AND CONCLUSION

Our findings suggest that the G > T/A polymorphism of ABCB1 G2677T/A and the TAT/TTT haplotype played a protective role in HIMP treatment of AQP4-IgG⁺ NMOSD-ON but not MS-ON.

Genetic Polymorphisms and the Clinical Response to Systemic Lupus Erythematosus Treatment Towards Personalized Medicine

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterized by a broad spectrum of clinical manifestations, an aberrant autoimmune response to self-antigens, which affect organs and tissues. There are several immune-pathogenic pathways, but the exact one is still not well known unless it is related to genetics. SLE and other autoimmune diseases are known to be inseparable from genetic factors, not only pathogenesis but also regarding the response to therapy. Seventy-one human studies published in the last 10 years were collected. Research communications, thesis publication, reviews, expert opinions, and unrelated studies were excluded. Finally, 32 articles were included. A polymorphism that occurs on the genes related to drugs pharmacokinetic, such as CYP, OATP, ABC Transporter, UGT, GST or drug-target pharmacodynamics, such as FCGR, TLR, and BAFF, can change the level of gene expression or its activity, thereby causing a variation on the clinical response of the drugs. A study that summarizes gene polymorphisms influencing the response to SLE therapy is urgently needed for personalized medicine practices. Personalized medicine is an effort to provide individual therapy based on genetic profiles, and it gives better and more effective treatments for SLE and other autoimmune disease patients.

Prediction of Tacrolimus Dose/Weight-Adjusted Trough Concentration in Pediatric Refractory Nephrotic Syndrome: A Machine Learning Approach

Purpose

Tacrolimus (TAC) is a first-line immunosuppressant for patients with refractory nephrotic syndrome (NS). However, there is a high inter-patient variability of TAC pharmacokinetics, thus therapeutic drug monitoring (TDM) is required. In this study, we aimed to employ machine learning algorithms to investigate the impact of clinical and genetic variables on the TAC dose/weight-adjusted trough concentration (C₀/D) in Chinese children with refractory NS, and then develop and validate the TAC C₀/D prediction models.

Patients and Methods

The association of 82 clinical variables and 244 single nucleotide polymorphisms (SNPs) with TAC C₀/D in the third month since TAC treatment was examined in 171 children with refractory NS. Extremely randomized trees (ET), gradient boosting decision tree (GBDT), random forest (RF), extreme gradient boosting (XGBoost), and Lasso regression were carried out to establish and validate prediction models, respectively. The best prediction models were validated on a cohort of 30 refractory NS patients.

Results

GBDT algorithm performed best in the whole group (R²=0.444, MSE=591.032, MAE=20.782, MedAE=18.980) and CYP3A5 nonexpresser group (R²=0.264, MSE=477.948, MAE=18.119, MedAE=18.771), while ET algorithm performed best in the CYP3A5 expresser group (R²=0.380, MSE=1839.459, MAE=31.257, MedAE=19.399). These prediction models included 3 clinical variables (ALB0, AGE0, and gender) and 10 SNPs (ACTN4 rs3745859, ACTN4 rs56113315, ACTN4 rs62121818, CTLA4 rs4553808, CYP3A5 rs776746, IL2RA rs12722489, INF2 rs1128880, MAP3K11 rs7946115, MYH9 rs2239781, and MYH9 rs4821478).

Conclusion

The association between the clinical and genetic variables and TAC C₀/D was described, and three TAC C₀/D prediction models integrating clinical and genetic variables were developed and validated using machine learning, which may support individualized TAC dosing.

Study on individualized analgesia guided by CYP3A4/5 polymorphisms in perioperative thoracoscopic surgery

OBJECTIVE

To explore the significance of CYP3A4 and CYP3A5 genetic polymorphisms in achieving personalized fentanyl application in patients undergoing thoracoscopic operation.

METHODS

This was a retrospective study. One hundred patients with lung cancer received thoracoscopic surgery operation under the conditions of general anesthesia. According to the results of individualized analgesia guided by CYP3A4/5 polymorphisms, the patients were assigned into three groups: group I (the wild-type homozygote, the induced dosage of fentanyl: 6 µg/kg, the background infusion rate of patient-controlled intravenous analgesia (PCIA): 2 mL/h), group II (the heterozygote, the induced dosage of fentanyl: 5 µg/kg, the background infusion rate of PCIA: 1.5 mL/h), and group III (the mutant homozygote, the induced dosage of fentanyl: 4 µg/kg, the background infusion rate of PCIA: 1 mL/h). The locking-time was 15 min. A visual analog scale (VAS) score less than 3 points suggested effective analgesia. The times of operation and recovery were examined. Surgical plethysmography index (SPI), blood glucose levels, VAS and bruggemann comfort scale (BCS) scores at different time points were recorded, respectively. Total consumption of fentanyl, the effective time of PCIA compression, and the incidence of adverse drug reactions were also recorded.

RESULTS

There were no statistical differences in SPI, blood glucose level, VAS, BCS scores and incidence of adverse reactions among the three groups. In term of intraoperative, postoperative fentanyl doses and the amount of effective PCA, significant differences were found among the groups (P < 0.05).

CONCLUSION

According to the genotype of CYP3A4/CYP3A5, an individualized application of fentanyl is feasible.

Assessment of the Link of ABCB1 and NR3C1 gene polymorphisms with the prednisolone resistance in pediatric nephrotic syndrome patients of Bangladesh: A genotype and haplotype approach

Introduction

Nephrotic syndrome is a common pediatric kidney disease. Investigations on several genetic polymorphisms revealed an inconsistent influence on the resistance of patients to steroids.

Objectives

This study aimed to identify the association of ABCB1 (1236C > T, 2677G > T, 3435C > T), NR3C1 (rs10482634, rs6877893), and CYP3A5 (CYP3A5*3) gene polymorphism as well as sociodemographic and clinicopathological parameters with the risk of developing prednisolone resistance in pediatric patients with nephrotic syndrome.

Methods

A case-control analysis was performed on 180 nephrotic syndrome patients. Among them, 30 patients were classified as prednisolone resistant group, and 150 were classified as prednisolone sensitive group. Genotyping was performed by the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method.

Results

No significant association of 1236C > T polymorphism with the risk of prednisolone resistance (p > 0.05) was found. The GT heterozygous of 2677G > T was found to be significantly associated with the development of prednisolone resistance (OR = 3.9, p = 0.034). In the case of 3435C > T, a statistically significant association was observed in TC heterozygous and TT mutant homozygous genotypes (OR = 0.38, p = 0.047; OR = 3.06, p = 0.038, respectively) with prednisolone resistance. For rs10482634 polymorphism, the AG heterozygous and AG+GG genotypes were significantly linked with prednisolone resistance (OR = 2.40, p = 0.033; OR = 2.36, p = 0.034, respectively). We found no association with the risk of prednisolone resistance with rs6877893 and CYP3A5*3 polymorphism (p > 0.05). CTC and TGT haplotypes of ABCB1 and GA haplotype of NR3C1 were also associated with the increased risk of pediatric prednisolone resistance (OR = 4.47, p = 0.0003; OR = 2.71, p = 0.03; and OR = 4.22, p = 0.022, consecutively). We also observed the correlation of different sociodemographic and clinicopathological factors with prednisolone resistance in pediatric nephrotic syndrome.

Conclusion

Our findings showed a significant association of ABCB1 and NR3C1 gene polymorphisms with prednisolone resistant pediatric nephrotic syndrome.

Changes of Transporters and Drug-metabolizing Enzymes in Nephrotic Syndrome

BACKGROUND

Drug-metabolizing enzymes and transporters play key roles in drug disposition and drug interactions. The alterations of their expression will influence drug pharmacokinetics and pharmacodynamics. However, the changes in the expression of enzymes and transporters in the disease state are still unclear.

OBJECTIVE

Our study was to investigate the changes in the expression of main enzymes and drug transporters distributed in Adriamycin nephropathy rat liver, kidney, and intestine.

METHODS

An intravenous injection with a single dose of Adriamycin (6mg/kg) was made to establish Adriamycin nephropathy (AN) model and normal groups were injected with normal saline. Serum was collected for lipid metabolism, renal, and hepatic function measurement. The real-time PCR and western blot were applied to determine the mRNA and protein expression of drug enzymes and transporters.

RESULTS

In the kidney, a greater expression of Mdr1, Mrp2, Mrp4 Oat2 and Oct2 mRNA was found in AN rats as compared with control rats. In the liver, the expression of Bcrp mRNA was more doubled or tripled than control groups and downregulation of Mdr1, Mrp2, Mrp4 and Bsep gene expression was found in AN rats. Besides, we observed a downward trend of Cyp1a2, Cyp3a4 and Cyp2c9 mRNA levels in AN groups. In the duodenum, the expression of Mdr1 and Mrp3 mRNA level was decreased, while Bcrp and Mrp2 mRNA were increased.

CONCLUSION

The changes in drug-metabolizing enzymes and transporters expression in AN rats were clarified, which may be beneficial for understanding the altered pharmacokinetics and pharmacodynamics of clinical drugs and reduce unexpected clinical findings for nephropathy patients.

Impact of CYP3A4/5 and ABCB1 polymorphisms on tacrolimus exposure and response in pediatric primary nephrotic syndrome

Aim: To evaluate the impact of CYP3A4*1G, CYP3A5*3 and ABCB1-C3435T polymorphisms on tacrolimus concentrations, efficacy and tolerance in pediatric primary nephrotic syndrome. Methods: Dose-adjusted concentrations (C₀/D), daily dose, frequency and time to relapse, cumulative remission days, and adverse reactions in 65 Chinese patients with various genotypes were retrospectively collected and compared. Results: C₀/D increased in CYP3A4*1/*1, CYP3A5*3/*3 and CYP3A4*1/*1-3A5*3/*3 diplotype carriers by 38.4, 69.7 and 40.9% compared with CYP3A4*1/*1G, CYP3A5*1/*3 and noncarriers, respectively. Recurrence risks were decreased in CYP3A4*1/*1 (0.43 of hazard ratio to *1/*1G) and CYP3A5*3/*3 carriers (0.43 of hazard ratio to *1/*3). None of polymorphisms was linked to adverse reactions. Conclusion: The genotypes of CYP3A4*1G and CYP3A5*3 rather than ABCB1-C3435T potentially predicted tacrolimus exposure and clinical response in pediatric primary nephrotic syndrome.

Genetics of Childhood Steroid Sensitive Nephrotic Syndrome: An Update

Advances in genome science in the last 20 years have led to the discovery of over 50 single gene causes and genetic risk loci for steroid resistant nephrotic syndrome (SRNS). Despite these advances, the genetic architecture of childhood steroid sensitive nephrotic syndrome (SSNS) remains poorly understood due in large part to the varying clinical course of SSNS over time. Recent exome and genome wide association studies from well-defined cohorts of children with SSNS identified variants in multiple MHC class II molecules such as HLA-DQA1 and HLA-DQB1 as risk factors for SSNS, thus stressing the central role of adaptive immunity in the pathogenesis of SSNS. However, evidence suggests that unknown second hit risk loci outside of the MHC locus and environmental factors also make significant contributions to disease. In this review, we examine what is currently known about the genetics of SSNS, the implications of recent findings on our understanding of pathogenesis of SSNS, and how we can utilize these results and findings from future studies to improve the management of children with nephrotic syndrome.