Predisposition to epilepsy-Does the ABCB1 gene play a role?

Effects of genetic polymorphism of drug-metabolizing enzymes on the plasma concentrations of antiepileptic drugs in Chinese population

As a chronic brain disease, epilepsy affects ~50 million people worldwide. The traditional antiepileptic drugs (AEDs) are widely applied but showing various problems. Although the new AEDs have partially solved the problems of traditional AEDs, the current clinical application of traditional AEDs are not completely replaced by new drugs, particularly due to the large individual differences in drug plasma concentrations and narrow therapeutic windows among patients. Therefore, it is still clinically important to continue to treat patients using traditional AEDs with individualized therapeutic plans. To date, our understanding of the molecular and genetic mechanisms regulating plasma concentrations of AEDs has advanced rapidly, expanding the knowledge on the effects of genetic polymorphisms of genes encoding drug-metabolizing enzymes on the plasma concentrations of AEDs. It is increasingly imperative to summarize and conceptualize the clinical significance of recent studies on individualized therapeutic regimens. In this review, we extensively summarize the critical effects of genetic polymorphisms of genes encoding drug-metabolizing enzymes on the plasma concentrations of several commonly used AEDs as well as the clinical significance of testing genotypes related to drug metabolism on individualized drug dosage. Our review provides solid experimental evidence and clinical guidance for the therapeutic applications of these AEDs.

Multi-omic strategies applied to the study of pharmacoresistance in mesial temporal lobe epilepsy

Mesial temporal lobe epilepsy (MTLE) is the most common type of focal epilepsy in adults, and hippocampal sclerosis (HS) is a frequent histopathological feature in patients with MTLE. Pharmacoresistance is present in at least one-third of patients with MTLE with HS (MTLE+HS). Several hypotheses have been proposed to explain the mechanisms of pharmacoresistance in epilepsy, including the effect of genetic and molecular factors. In recent years, the increased knowledge generated by high-throughput omic technologies has significantly improved the power of molecular genetic studies to discover new mechanisms leading to disease and response to treatment. In this review, we present and discuss the contribution of different omic modalities to understand the basic mechanisms determining pharmacoresistance in patients with MTLE+HS. We provide an overview and a critical discussion of the findings, limitations, new approaches, and future directions of these studies to improve the understanding of pharmacoresistance in MTLE+HS. However, it is important to point out that, as with other complex traits, pharmacoresistance to anti-seizure medications is likely a multifactorial condition in which gene-gene and gene-environment interactions play an important role. Thus, studies using multidimensional approaches are more likely to unravel these intricate biological processes.

Towards realizing the vision of precision medicine: AI based prediction of clinical drug response

Accurate and individualized prediction of response to therapies is central to precision medicine. However, because of the generally complex and multifaceted nature of clinical drug response, realizing this vision is highly challenging, requiring integrating different data types from the same individual into one prediction model. We used the anti-epileptic drug brivaracetam as a case study and combine a hybrid data/knowledge-driven feature extraction with machine learning to systematically integrate clinical and genetic data from a clinical discovery dataset (n = 235 patients). We constructed a model that successfully predicts clinical drug response [area under the curve (AUC) = 0.76] and show that even with limited sample size, integrating high-dimensional genetics data with clinical data can inform drug response prediction. After further validation on data collected from an independently conducted clinical study (AUC = 0.75), we extensively explore our model to gain insights into the determinants of drug response, and identify various clinical and genetic characteristics predisposing to poor response. Finally, we assess the potential impact of our model on clinical trial design and demonstrate that, by enriching for probable responders, significant reductions in clinical study sizes may be achieved. To our knowledge, our model represents the first retrospectively validated machine learning model linking drug mechanism of action and the genetic, clinical and demographic background in epilepsy patients to clinical drug response. Hence, it provides a blueprint for how machine learning-based multimodal data integration can act as a driver in achieving the goals of precision medicine in fields such as neurology.

The association between MDR1 C3435T genetic polymorphism and the risk of multidrug-resistant epilepsy in Egyptian children

Background

Epilepsy is a chronic disease affecting about 2% of the population and is considered a serious neurological disease. Despite its good prognosis, 20–30% of epileptic patients were not cured of their seizures even with the many trials of antiepileptic drug (AED) therapy. The resistance mechanism is still unclear, maybe due to the effect of the genetic factors on the bioavailability of the drugs. Consequently, the association between therapy resistance and the presence of a gene called “multidrug resistance 1 (MDR1)” had been proposed. Thus, the present study aimed to understand the relationship between the genetic polymorphism of MDR1C3435T and the resistance to AEDs.

Result

A non-significant association was found between MDR1 C3435T single-nucleotide polymorphism (SNP) and drug-resistant epilepsy. However, there was statistical significance in the association between the drug type and the genotype distribution, in cases that were maintained on sodium valproate and MDR1C3435T genotype.

Conclusion

Possible involvement of the MDR1 gene C 3435T polymorphism with sodium valproate resistance clarifies the importance of genetic variability in response to the drug and may help to find novel genetic therapy for epilepsy, by targeting the biological mechanisms responsible for epilepsy in each specific individual. Future studies with bigger sample sizes and in other racial populations will be necessary.

ABCB1 Polymorphisms and Drug-Resistant Epilepsy in a Tunisian Population

Background

Epilepsy is one of the most common neurological disorders with about 30% treatment failure rate. An interindividual variations in efficacy of antiepileptic drugs (AEDs) make the treatment of epilepsy challenging, which can be attributed to genetic factors such as ATP-Binding Cassette sub-family B, member1 (ABCB1) gene polymorphisms.

Objective

The main objective of the present study is to evaluate the association of ABCB1 C1236T, G2677T, and C3435T polymorphisms with treatment response among Tunisian epileptic patients.

Materials and Methods

One hundred epileptic patients, originated from north of Tunisia, were recruited and categorized into 50 drug-resistant and 50 drug-responsive patients treated with antiepileptic drugs (AEDs) as per the International League Against Epilepsy. DNA of patients was extracted and ABCB1 gene polymorphisms studied using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method.

Results

The C1236T, G2677T, and C3435T polymorphisms were involved into AED resistance. Significant genotypic (C1236T TT (p ≤ 0.001); G2677T TT (p = 0.001); C3435T TT (p ≤ 0.001)) and allelic associations (C1236T T (3.650, p ≤ 0.001); G2677TT (1.801, p = 0.044); C3435T T (4.730, p ≤ 0.001)) with drug resistance epilepsy (DRE) were observed. A significant level of linkage disequilibrium (LD) was also noted between ABCB1 polymorphisms. Patients with the haplotypes CT and TT (C1236T-G2677T); GT, TC, and TT (G2677T-C3435T); CT and TT (C1236T-C3435T); CTT, TTC, TGT, and TTT (C1236T-G2677T-C3435T) were also significantly associated to AED resistance.

Conclusions

The response to antiepileptics seems to be modulated by TT genotypes, T alleles, and the predicted haplotypes for the tested SNPs in our population. Genetic analysis is a valuable tool for predicting treatment response and thus will contribute to personalized medicine for Tunisian epileptic patients.

Clinical reappraisal of the influence of drug-transporter polymorphisms in epilepsy

INTRODUCTION

Although novel antiepileptic drugs (AEDs) have been recently released, the issue of drug resistance in epileptic patients remains unsolved and largely unpredictable. Areas covered: We aim to assess the clinical impact of genetic variations that may influence the efficacy of medical treatment in epilepsy patients. Indeed, many genes, including genes encoding drug transporters (ABCB1), drug targets (SCN1A), drug-metabolizing enzymes (CYP2C9, CYP2C19), and human leucocyte antigen (HLA) proteins, may regulate the mechanisms of drug resistance in epilepsy. This review specifically focuses on the ABC genes, which encode multidrug resistance-associated proteins (MRPs) and may reduce the blood-brain barrier penetration of anticonvulsant AEDs. Expert opinion: Drug resistance remains a crucial problem in epilepsy patients. Pharmacogenomic studies may improve our understanding of drug responses and drug resistance by exploring the impact of gene variants and predicting drug responses and tolerability.

Relationship between ABCB1 3435TT genotype and antiepileptic drugs resistance in Epilepsy: updated systematic review and meta-analysis

Background

Antiepileptic drugs (AEDs) are effective medications available for epilepsy. However, many patients do not respond to this treatment and become resistant. Genetic polymorphisms may be involved in the variation of AEDs response. Therefore, we conducted an updated systematic review and a meta-analysis to investigate the contribution of the genetic profile on epilepsy drug resistance.

Methods

We proceeded to the selection of eligible studies related to the associations of polymorphisms with resistance to AEDs therapy in epilepsy, published from January 1980 until November 2016, using Pubmed and Cochrane Library databases. The association analysis was based on pooled odds ratios (ORs) and 95% confidence intervals (CIs).

Results

From 640 articles, we retained 13 articles to evaluate the relationship between ATP-binding cassette sub-family C member 1 (ABCB1) C3435T polymorphism and AEDs responsiveness in a total of 454 epileptic AEDs-resistant cases and 282 AEDs-responsive cases. We found a significant association with an OR of 1.877, 95% CI 1.213–2.905. Subanalysis by genotype model showed a more significant association between the recessive model of ABCB1 C3435T polymorphism (TT vs. CC) and the risk of AEDs resistance with an OR of 2.375, 95% CI 1.775–3.178 than in the dominant one (CC vs. TT) with an OR of 1.686, 95% CI 0.877–3.242.

Conclusion

Our results indicate that ABCB1 C3435T polymorphism, especially TT genotype, plays an important role in refractory epilepsy. As genetic screening of this genotype may be useful to predict AEDs response before starting the treatment, further investigations should validate the association.

A Prediction Algorithm for Drug Response in Patients with Mesial Temporal Lobe Epilepsy Based on Clinical and Genetic Information

Mesial temporal lobe epilepsy is the most common form of adult epilepsy in surgical series. Currently, the only characteristic used to predict poor response to clinical treatment in this syndrome is the presence of hippocampal sclerosis. Single nucleotide polymorphisms (SNPs) located in genes encoding drug transporter and metabolism proteins could influence response to therapy. Therefore, we aimed to evaluate whether combining information from clinical variables as well as SNPs in candidate genes could improve the accuracy of predicting response to drug therapy in patients with mesial temporal lobe epilepsy. For this, we divided 237 patients into two groups: 75 responsive and 162 refractory to antiepileptic drug therapy. We genotyped 119 SNPs in ABCB1, ABCC2, CYP1A1, CYP1A2, CYP1B1, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4, and CYP3A5 genes. We used 98 additional SNPs to evaluate population stratification. We assessed a first scenario using only clinical variables and a second one including SNP information. The random forests algorithm combined with leave-one-out cross-validation was used to identify the best predictive model in each scenario and compared their accuracies using the area under the curve statistic. Additionally, we built a variable importance plot to present the set of most relevant predictors on the best model. The selected best model included the presence of hippocampal sclerosis and 56 SNPs. Furthermore, including SNPs in the model improved accuracy from 0.4568 to 0.8177. Our findings suggest that adding genetic information provided by SNPs, located on drug transport and metabolism genes, can improve the accuracy for predicting which patients with mesial temporal lobe epilepsy are likely to be refractory to drug treatment, making it possible to identify patients who may benefit from epilepsy surgery sooner.

SCN1A, ABCC2 and UGT2B7 gene polymorphisms in association with individualized oxcarbazepine therapy

AIM

Associations between the effects of SCN1A, SCN2A, ABCC2 and UGT2B7 genetic polymorphisms and oxcarbazepine (OXC) maintenance doses in Han Chinese epileptic patients were investigated.

PATIENTS & METHODS

Genetic polymorphisms were detected in 184 epileptic patients receiving OXC monotherapy by high-resolution melting curve and TaqMan method.

RESULTS

Carriers of the SCN1A IVS5-91G>A, UGT2B7 c.802T>C and ABCC2 c.1249G>A variant alleles required significantly higher OXC maintenance doses than noncarriers (p < 0.05). Corresponding relative ln (concentration-dose ratios) values for SCN1A IVS5-91 variants differed by the genotypic order GG > GA > AA.

CONCLUSION

SCN1A, UGT2B7 and ABCC2 genetic polymorphisms are associated with OXC maintenance doses and may be useful for the personalization of OXC therapy in epileptic patients. Further studies are needed. Original submitted 6 June 2014; Revision submitted 5 September 2014.

The roles of variants in human multidrug resistance (MDR1) gene and their haplotypes on antiepileptic drugs response: a meta-analysis of 57 studies

Objective

Previous studies reported the associations between the ATP-binding cassette sub-family B member 1 (ABCB1, also known as MDR1) polymorphisms and their haplotypes with risk of response to antiepileptic drugs in epilepsy, however, the results were inconclusive.

Methods

The Pubmed, Embase, Web of Science, CNKI and Chinese Biomedicine databases were searched up to July 15, 2014. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using a fixed-effects or random-effects model based on heterogeneity tests. Meta-regression and Galbraith plot analysis were carried out to explore the possible heterogeneity.

Results

A total of 57 studies involving 12407 patients (6083 drug-resistant and 6324 drug-responsive patients with epilepsy) were included in the pooled-analysis. For all three polymorphisms (C3435T, G2677T/A, and C1236T), we observed a wide spectrum of minor allele frequencies across different ethnicities. A significantly decreased risk of AEDs resistance was observed in Caucasian patients with T allele of C3435T variant, which was still significant after adjusted by multiple testing corrections (T vs C: OR=0.83, 95%CI=0.71-0.96, p=0.01). However, no significant association was observed between the other two variants and AEDs resistance. Of their haplotypes in ABCB1 gene (all studies were in Indians and Asians), no significant association was observed with AEDs resistance. Moreover, sensitivity and Cumulative analysis showed that the results of this meta-analysis were stable.

Conclusion

In summary, this meta-analysis demonstrated that effect of C3435T variant on risk of AEDs resistance was ethnicity-dependent, which was significant in Caucasians. Additionally, further studies in different ethnic groups are warranted to clarify possible roles of haplotypes in ABCB1 gene in AEDs resistance, especially in Caucasians.

MDR-1 and MRP2 Gene Polymorphisms in Mexican Epileptic Pediatric Patients with Complex Partial Seizures

Although the Pgp efflux transport protein is overexpressed in resected tissue of patients with epilepsy, the presence of polymorphisms in MDR1/ABCB1 and MRP2/ABCC2 in patients with antiepileptic-drugs resistant epilepsy (ADR) is controversial. The aim of this study was to perform an exploratory study to identify nucleotide changes and search new and reported mutations in patients with ADR and patients with good response (CTR) to antiepileptic drugs (AEDs) in a rigorously selected population. We analyzed 22 samples In Material and Methods, from drug-resistant patients with epilepsy and 7 samples from patients with good response to AEDs. Genomic DNA was obtained from leukocytes. Eleven exons in both genes were genotyped. The concentration of drugs in saliva and plasma was determined. The concentration of valproic acid in saliva was lower in ADR than in CRT. In ABCB1, five reported SNPs and five unreported nucleotide changes were identified; rs2229109 (GA) and rs2032582 (AT and AG) were found only in the ADR. Of six SNPs associated with the ABCC2 that were found in the study population, rs3740066 (TT) and 66744T > A (TG) were found only in the ADR. The strongest risk factor in the ABCB1 gene was identified as the TA genotype of rs2032582, whereas for the ABCC2 gene the strongest risk factor was the T allele of rs3740066. The screening of SNPs in ACBC1 and ABCC2 indicates that the Mexican patients with epilepsy in this study display frequently reported ABCC1 polymorphisms; however, in the study subjects with a higher risk factor for drug resistance, new nucleotide changes were found in the ABCC2 gene. Thus, the population of Mexican patients with AED-resistant epilepsy (ADR) used in this study exhibits genetic variability with respect to those reported in other study populations; however, it is necessary to explore this polymorphism in a larger population of patients with ADR.

Polymorphism of ABCB1/MDR1 C3435T in children and adolescents with partial epilepsy is due to different criteria for drug resistance - preliminary results

Background

The diagnosis of “drug resistance” in epilepsy can be defined and interpreted in various ways. This may be due to discrepant definitions of drug resistance to pharmacotherapy.

The aim of our study was to investigate the relationship between C3435T polymorphism of the MDR1 gene and drug resistance in epilepsy with the consideration of 4 different criteria for qualification to groups sensitive and resistant to applied pharmacotherapy.

Material/Methods

Evaluation of C3435T polymorphism of MDR1/ABCB1 gene was conducted on a group of 82 white children and young adolescents up to 18 years old. While qualifying the patients to the group of sensitive or drug resistant, the following 4 definitions of drug resistance were applied: the ILAE’s, Appleton’s, Siddiqui’s, and Berg’s.

Results

A detailed analysis of genotypes of the MDR1 gene did not show any significant discrepancies between the groups of patients resistant and sensitive to antiepileptic drugs (AEDs) in 4 consecutive comparisons taking into consideration various criteria of sensitivity and resistance to pharmacotherapy.

Conclusions

The obtained results clearly confirm the lack of a connection between the occurrence of drug-resistant epilepsy and C435T polymorphism of the MDR1 gene irrespective of the definition of drug resistance applied to the patient.

Genetic association analysis of ATP binding cassette protein family reveals a novel association of ABCB1 genetic variants with epilepsy risk, but not with drug-resistance

Epilepsy constitutes a heterogeneous group of disorders that is characterized by recurrent unprovoked seizures due to widely different etiologies. Multidrug resistance remains a major issue in clinical epileptology, where one third of patients with epilepsy continue to have seizures. Role of efflux transporters in multidrug resistant epilepsy has been attributed to drug-resistant epilepsy although, with discrepant observation in genetic studies. These discrepancies could be attributed to variety of factors such as variable definition of the anti-epileptic drug (AED)-resistance, variable epilepsy phenotypes and ethnicities among the studies. In the present study we inquired the role of multidrug transporters ABCB1 and ABCG2 variants in determining AED-resistance and susceptibility to epilepsy in three well-characterized cohorts comprising of mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS) (prototype for AED-resistant epilepsy); juvenile myoclonic epilepsy (JME) (prototype for AED-responsive epilepsy); and healthy non-epileptic controls, in 738 subjects of Malayalam speaking south Indian ancestry. ABCB1 and ABCG2 variants were not found to be associated with drug resistance when AED-resistant and AED-responsive cohorts were compared. However, a significant association was observed between ABCB1 (C3435T) rs1045642 and risk of having epilepsy (MTLE-HS and JME pooled cohort; genotypic p-value = 0.0002; allelic p-value = 0.004). This association was seen persistent with MTLE-HS (genotypic p-value = 0.0008; allelic p-value = 0.004) and also with JME (genotypic p-value = 0.01; allelic p-value = 0.05) cohort individually. In-silico functional prediction indicated that ABCB1 rs1045642 has a deleterious impact on protein coding function and in splicing regulation. We conclude that the ABCB1 and ABCG2 variants do not confer to AED-resistance in the study population. However, ABCB1 rs1045642 increases vulnerability to epilepsy with greater tendency for MTLE-HS in south Indian ancestry from Kerala.

The multidrug transporter P-glycoprotein in pharmacoresistance to antiepileptic drugs

This review provides an overview of the knowledge on P-glycoprotein (P-gp) and its role as a membrane transporter in drug resistance in epilepsy and drug interactions. Overexpression of P-gp, encoded by the ABCB1 gene, is involved in resistance to antiepileptic drugs (AEDs), limits gastrointestinal absorption and brain access of AEDs. Although several association studies on ABCB1 gene with drug disposition and disease susceptibility are completed to date, the data remain unclear and incongruous. Although the literature describes other multidrug resistance transporters, P-gp is the main extensively studied drug efflux transporter in epilepsy.

Pharmacogenetics of drug transporters in the enterohepatic circulation

This article summarizes the impact of the pharmacogenetics of drug transporters expressed in the enterohepatic circulation on the pharmacokinetics and pharmacodynamics of drugs. The role of pharmacogenetics in the function of drug transporter proteins in vitro is now well established and evidence is rapidly accumulating from in vivo pharmacokinetic studies, which suggests that genetic variants of drug transporter proteins can translate into clinically relevant phenotypes. However, a large amount of conflicting information on the clinical relevance of drug transporter proteins has so far precluded the emergence of a clear picture regarding the role of drug transporter pharmacogenetics in medical practice. This is very well exemplified by the case of P-glycoprotein (MDR1, ABCB1). The challenge is now to develop pharmacogenetic models with sufficient predictive power to allow for translation into drug therapy. This will require a combination of pharmacogenetics of drug transporters, drug metabolism and pharmacodynamics of the respective drugs.

Pharmacogenomics in neurology: current state and future steps

In neurology, as in any other clinical specialty, there is a need to develop treatment strategies that allow stratification of therapies to optimize efficacy and minimize toxicity. Pharmacogenomics is one such method for therapy optimization: it aims to elucidate the relationship between human genome sequence variation and differential drug responses. Approaches have focused on candidate approaches investigating absorption-, distribution-, metabolism, and elimination (ADME)-related genes (pharmacokinetic pathways), and potential drug targets (pharmacodynamic pathways). To date, however, only few genetic variants have been incorporated into clinical algorithms. Unfortunately, a large number of studies have thrown up contradictory results due to a number of deficiencies, including small sample sizes, inadequate phenotyping, and genotyping strategies. Thus, there still exists an urgent need to establish biomarkers that could help to select for patients with an optimal benefit to risk relationship. Here we review recent advances, and limitations, in pharmacogenomics for agents used in neuroimmunology, neurodegenerative diseases, ischemic stroke, epilepsy, and primary headaches. Further work is still required in all of these areas, which really needs to progress on several fronts, including better standardized phenotyping, appropriate sample sizes through multicenter collaborations and judicious use of new technological advances such as genome-wide approaches, next generation sequencing and systems biology. In time, this is likely to lead to improvements in the benefit-harm balance of neurological therapies, cost efficiency, and identification of new drugs.

Association of ABCB1 gene polymorphisms and their haplotypes with response to antiepileptic drugs: a systematic review and meta-analysis

AIMS

Several studies demonstrated a link between ABCB1 gene variants and the response to treatment in epilepsy, but the results have been inconclusive. Here, we performed the first haplotype meta-analysis to examine the association of haplotypes of ABCB1 common variants with the response to treatment in epilepsy.

MATERIALS & METHODS

We meta-analyzed the studies that evaluated the role of ABCB1 C1236T, G2677T/A and C3435T polymorphisms and their haplotypes in the response to treatment.

RESULTS

Meta-analysis of 23 studies (7067 patients) showed no significant association of ABCB1 alleles, genotypes and haplotypes with the response to treatment in the overall population or in each ethnicity subgroup.

CONCLUSION

Our data suggest that the haplotypes of these loci may not be involved in the response to treatment.