Genetics of antiepileptic drug resistance

Integrative analysis of rs717620 polymorphism in therapeutic response to anti-seizure medications

Background

Previous studies have shown that the rs717620 polymorphism in ABCC2, the gene encoding multidrug resistance protein 2, influences the therapeutic response to anti-seizure medications (ASMs). However, this result is not consistent, and the mechanism by which rs717620 influences ASM responses is unclear.

Aims

The present study evaluated the association between rs717620 genotype and ASM efficacy, and examined the potential mechanisms.

Main

methods: We conducted a literature search of five electronic databases, Embase, Medline, Web of Science, China National Knowledge Infrastructure, and Wanfang, to identify relevant studies on response to ASM therapy among rs717620 genotypes. Expression quantitative trait loci analysis and drug-gene interaction analysis were also performed to assess the underlying mechanisms.

Key findings

The pooled results for 18 studies revealed a significant association between rs717620 genotype and ASM resistance under the recessive model (TT vs. CT + CC: OR = 1.68, 95 % CI = 1.27-2.21, I2 = 3.1 %). A significant association was also found in the Asian population under the recessive model (TT vs. CT + CC: OR = 1.70, 95 % CI = 1.26-2.29, I2 = 29.3 %). Further analysis revealed that rs717620 regulates the expression of ABCC2 in human brain, while drug-gene interaction analysis suggested that ABCC2 interacts with oxcarbazepine and carbamazepine.

Significance

The rs717620 polymorphism influences ASM therapeutic responses by altering brain expression levels of ABCC2.

Personalized antiseizure medication therapy in critically ill adult patients

Precision medicine has the potential to have a significant impact on both drug development and patient care. It is crucial to not only provide prompt effective antiseizure treatment for critically ill patients after seizures start but also have a proactive mindset and concentrate on epileptogenesis and the underlying cause of the seizures or seizure disorders. Critical illness presents different treatment issues compared with the ambulatory population, which makes it challenging to choose the best antiseizure medications and to administer them at the right time and at the right dose. Since there is a paucity of information available on antiseizure medication dosing in critically ill patients, therapeutic drug monitoring is a useful tool for defining each patient's personal therapeutic range and assisting clinicians in decision-making. Use of pharmacogenomic information relating to pharmacokinetics, hepatic metabolism, and seizure etiology may improve safety and efficacy by individualizing therapy. Studies evaluating the clinical implementation of pharmacogenomic information at the point-of-care and identification of biomarkers are also needed. These studies may make it possible to avoid adverse drug reactions, maximize drug efficacy, reduce drug-drug interactions, and optimize medications for each individual patient. This review will discuss the available literature and provide future insights on precision medicine use with antiseizure therapy in critically ill adult patients.

Polymorphisms Affecting the Response to Novel Antiepileptic Drugs

Epilepsy is one of the most frequent chronic neurologic disorders that affects nearly 1% of the population worldwide, especially in developing countries. Currently, several antiepileptic drugs (AEDs) are available for its therapy, and although the prognosis is good for most patients, 20%-30% amongst them do not reach seizure freedom. Numerous factors may explain AED-resistance such as sex, age, ethnicity, type of seizure, early epilepsy onset, suboptimal dosing, poor drug compliance, alcohol abuse, and in particular, genetic factors. Specifically, the interindividual differences in drug response can be caused by single nucleotide polymorphisms (SNPs) in genes encoding for drug efflux transporters, for the brain targets of AEDs, and for enzymes involved in drug metabolism. In this review, we used the PubMed database to retrieve studies that assessed the influence of SNPs on the pharmacokinetic (PK), pharmacodynamic (PD), and efficacy of new antiepileptic drugs. Our results showed that polymorphisms in the ABCB1, ABCC2, UGT1A4, UGT2B7, UGT2B15, CYP2C9, and CYP2C19 genes have an influence on the PK and efficacy of AEDs, suggesting that a genetic pre-evaluation of epileptic patients could help clinicians in prescribing a personalized treatment to improve the efficacy and the safety of the therapy.

Association of SCN1A Gene Polymorphism with Phenytoin Response in Patients with Epilepsy: Relevance of Stratification by the History of Febrile Seizure

AIM: The SCN1A gene encodes the NaV1.1 sodium channel in the central nervous system that serves as the target for phenytoin. Our study aimed to investigate the association of SCN1A polymorphism (SNP rs3812718) with phenytoin response. MATERIALS AND METHODS: A total of 120 epileptic patients who had received phenytoin for at least 1 year were enrolled in the study and genotyped using the TaqMan assay. They were classified into phenytoin-responsive (n = 62) and phenytoin unresponsive groups (n = 58). Patients were also stratified according to the history of febrile seizure (24 in the febrile seizure subgroup; 96 patients in the no history of febrile seizure subgroup) and epilepsy etiology (47 in idiopathic; 73 in the symptomatic + cryptogenic subgroup). RESULTS: The frequency of AA (19% vs. 11.3%) and AG genotypes (43.1% vs. 40.3%) was found to be more frequent in phenytoin unresponsive. GG genotypes dominated in the phenytoin responsive group (37.9% vs. 48.4%) but were not statistically significant (p > 0.05). We identified two variables associated with phenytoin response: the etiology of epilepsy (p = 0.012) and history of febrile seizure (0.014). A significant positive association between the rs3812718 genotype and phenytoin response was found when patients were stratified by a history of febrile seizures. In patients without a history of febrile seizures, the AA genotype had a higher risk of phenytoin unresponsiveness than the GG genotype (p = 0.048; OR 3.73, 95% CI: 1.01–13.78). CONCLUSION: There was no significant association between the rs3812718 polymorphism and phenytoin responsiveness in patients with epilepsy. In the patients without a history of febrile seizure subgroup, AA increased the risk of phenytoin unresponsiveness compared to the GG genotype.

Predictive factors of epilepsy outcome in a sample of Egyptian pre-elderly and elderly population

Background

Elderly people with epilepsy are large, but neglected group. Data on the predictive factors for recurrent seizures in the elderly population are inconclusive or are not known for the majority of patients. This is especially true for the Egyptian population as no specific study was concluded to address this issue before.

Objectives

The aim of this study was to detect the predictive factors of epilepsy outcome in a sample of Egyptian aged population.

Materials and methods

A total of 100 patients aged 50 years or older with epilepsy diagnosed according to International League Against Epilepsy (ILAE) latest definition were included in the study and followed up for 6 months as regards seizure control. All participants were prospectively evaluated for epidemiological, clinical, radiological, electrodiagnostic, and laboratory data.

Results

The outcome was statistically significant affected in relation to absence of medical comorbidities (P = 0.037), seizure etiology (P = 0.007), history of status epilepticus (P <  0.001), MRI brain findings (P = 0.005), EEG changes (P <  0.001), Ca (P = 0.01), and Mg level (P = 0.046).

Conclusion

We conclude that aged Egyptian epileptic population with no medical comorbidities, normal MRI brain, or normal EEG can be predicted to have good outcome of their epilepsy while patients with post stroke epilepsy, abnormal MRI brain, and abnormal EEG, with low serum Ca or Mg level can be predicted to have poor outcome.

The long-term prognosis of epilepsy patients with medically treated over a period of eight years in Turkey

Objective:

The aim of this study was to investigate the effect of demographic and clinical characteristics on temporal changes in seizure control and frequency in medically treated epilepsy patients to guide treatment modalities.

Methods:

We retrospectively analyzed the association between clinical and demographic characteristics and seizure frequency in 1329 epilepsy patients who were followed up at an outpatient clinic for one to eight years, 2008-2015..

Results:

Younger age at first seizure (p = 0.0465) and a long disease duration (p = 0.0406) had a negative effect on seizure control in all the epilepsy patients. Febrile convulsions (FCs) (p > 0.0001), perinatal risk (PNR) (p > 0.0002), a family history of epilepsy (FHE) (p > 0.0016), antiepileptic drug (AED) use (p > 0.001), mental retardation (MR) (p > 0.001), and psychiatric disorders (p > 0.0478) were prognostic indictors of temporal changes in seizure frequency. The presence of PNR (p = 0.0416), age at onset of epilepsy (p = 0.034), central nervous system infection (CNSI) (p = 0.04), and AEDs number (p = 0.0282) were prognostic indicators of not remaining seizure free for one year. In those with partial epilepsy, a trauma history (p = 0.05), a longer epilepsy duration (p = 0.0057), and FHE (p = 0.0466) increased the frequency of seizures, whereas cerebrovascular event (CVE) history decreased the seizure frequency (p = 0.0413). In addition, FHE (p = 0.0438) and psychotic disorders (p = 0.0416) increased generalized seizures frequency.

Conclusion:

In all the epilepsy patients, a younger age at onset and longer duration of epilepsy were associated with a poor prognosis. The presence of PNR, age at onset of epilepsy, CNSI, and AEDs numbers were prognostic indicators of not remaining seizure free for one year. Increasing AEDs number was not effective in controlling seizures in partial epilepsy, but it was effective in controlling seizures in generalized epilepsy.

Pharmacogenomics in epilepsy

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Genetic variation can influence response to antiepileptic drug (AED) treatment through various effector processes.

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Metabolism of many AEDs is mediated by the cytochrome P450 (CYP) family; some of the CYPs have allelic variants that may affect serum AED concentrations.

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‘Precision medicine’ focuses on the identification of an underlying genetic aetiology allowing personalised therapeutic choices.

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Certain human leukocyte antigen, HLA, alleles are associated with an increased risk of idiosyncratic adverse drug reactions.

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New results are emerging from large-scale multinational efforts, likely imminently to add knowledge of value from a pharmacogenetic perspective.

There is high variability in the response to antiepileptic treatment across people with epilepsy. Genetic factors significantly contribute to such variability. Recent advances in the genetics and neurobiology of the epilepsies are establishing the basis for a new era in the treatment of epilepsy, focused on each individual and their specific epilepsy. Variation in response to antiepileptic drug treatment may arise from genetic variation in a range of gene categories, including genes affecting drug pharmacokinetics, and drug pharmacodynamics, but also genes held to actually cause the epilepsy itself.

From a purely pharmacogenetic perspective, there are few robust genetic findings with established evidence in epilepsy. Many findings are still controversial with anecdotal or less secure evidence and need further validation, e.g. variation in genes for transporter systems and antiepileptic drug targets. The increasing use of genetic sequencing and the results of large-scale collaborative projects may soon expand the established evidence.

Precision medicine treatments represent a growing area of interest, focussing on reversing or circumventing the pathophysiological effects of specific gene mutations. This could lead to a dramatic improvement of the effectiveness and safety of epilepsy treatments, by targeting the biological mechanisms responsible for epilepsy in each specific individual.

Whilst much has been written about epilepsy pharmacogenetics, there does now seem to be building momentum that promises to deliver results of use in clinic.

The right and the wrong with epilepsy and her science

This is a commentary and an opinion paper attempting a critical reassessment of the methods and practices of epilepsy research as we see it. The enormous progress in the field of epilepsy in recent years is a cause of celebration. Advances have been made on most fronts, and the position of patients with epilepsy in society has greatly improved. However, there have also been culs‐de‐sac and dead ends of modern science and clinical practice which are also intriguing. It may be true that we can learn more from our mistakes than from our successes. In this opinion paper, we have listed some of the successes and some of the failures of past epilepsy practice, and also areas of current practice and theory which we feel are likely to prove mistaken. The underlying reasons for misdirected practices and theories include, in our view, the influence of fashion, bad science, and the bureaucracies of practice and academic medicine. As a result, some findings are far from objective. Recognition is the first step to remediation, and hopefully future research will minimize some of the pitfalls mentioned in this article and bring the “End of Epilepsy,” as defined and predicted by Oswei Temkin, closer than it is today.

Management of genetic epilepsies: From empirical treatment to precision medicine

Despite the over 20 antiepileptic drugs (AEDs) now licensed for epilepsy treatment, seizures can be effectively controlled in about ∼70% of patients. Thus, epilepsy treatment is still challenging in about one third of patients and this may lead to a severe medically, physically, and socially disabling condition. However, there is clear evidence of heterogeneity of response to existing AEDs and a significant unmet need for effective intervention. A number of studies have shown that polymorphisms may influence the poor or inadequate therapeutic response as well as the occurrence of adverse effects. In addition, the new frontier of genomic technologies, including chromosome microarrays and next-generation sequencing, improved our understanding of the genetic architecture of epilepsies. Recent findings in some genetic epilepsy syndromes provide insights into mechanisms of epileptogenesis, unrevealing the role of a number of genes with different functions, such as ion channels, proteins associated to the vesical synaptic cycle or involved in energy metabolism. The rapid progress of high-throughput genomic sequencing and corresponding analysis tools in molecular diagnosis are revolutionizing the practice and it is a fact that for some monogenic epilepsies the molecular confirmation may influence the choice of the treatment. Moreover, the novel genetic methods, that are able to analyze all known genes at a reasonable price, are of paramount importance to discover novel therapeutic avenues and individualized (or precision) medicine.

Association of SCN1A, SCN2A and ABCC2 gene polymorphisms with the response to antiepileptic drugs in Chinese Han patients with epilepsy

AIM

The purpose of this study was to investigate the potential impact of SCN1A, SCN2A and ABCC2 gene polymorphisms on the response to antiepileptic drugs in Chinese Han patients with epilepsy.

PATIENTS & METHODS

Genetic polymorphisms in the candidate genes were detected in 453 Chinese epileptic patients by high-resolution melting curve and TaqMan methods.

RESULTS

The SCN1A IVS5-91G>A AA genotype and the ABCC2 c.1249G>A GA genotype were significantly associated with carbamazepine/oxcarbamazepine (CBZ/OXC)-resistant epilepsy (p =0.002 and p = 0.036, respectively). The frequencies of haplotypes AA (SCN1A gene) and AC (ABCC2 gene) in drug-resistant patients were significantly higher than those in responsive patients (p = 0.002 and p = 0.005, respectively).

CONCLUSION

This study suggested that SCN1A and ABCC2 polymorphisms may be associated with the response to CBZ/OXC in the Chinese Han population, indicating that they could serve as predictors of drug response. Original submitted 29 January 2014; Revision submitted 30 May 2014.

Health-related quality of life in epilepsy patients receiving anti-epileptic drugs at National Referral Hospitals in Uganda: a cross-sectional study

BACKGROUND

Epilepsy is a devastating disorder that impacts on patients' quality of life, irrespective of use of anti epileptic drugs (AEDs). This study estimates the health-related quality of life (HRQOL) and its associated predictors among epilepsy patients receiving AEDs.

METHODS

A total of 175 epilepsy patients already receiving AED for at least 3 months were randomly selected and interviewed from mental clinics at Mulago and Butabika national referral hospitals in Uganda between May - July 2011. A HRQOL index, the primary outcome, was constructed using items from Quality Of Life in Epilepsy Inventory (QOLIE-31) and the Hospital Anxiety and Depression Scale (HADS) questionnaires. The internal consistency and adequacy of these items was also computed using Cronbach's alpha and Kaiser-Meyer-Olkin tests. Partial correlations were used to evaluate the contribution of the health dimensions (mental, psychological, social, physical functioning and emotional well being) and, multiple linear regressions to determine factors independently associated with HRQOL.

RESULTS

Just about half of the respondents (54%) were males, and nearly two thirds (62%) had received AEDs for at least 12 months. The average age was 26.6 years (SD = 11.1). The overall HRQOL mean score was 58 (SD = 13) on a scale of 0-100. The average scores of different dimensions or subscales ranged from 41 (physical) to 65 (psychological). At least three quarters (75%) of all subscales had good internal consistency and adequacy. The largest variations in the overall HRQOL were explained by social and mental functioning; each accounting for about 30% of the difference in the HRQOL but seizure control features explained a little (6%) variation. Factors negatively associated with HRQOL were poly-therapy (-1.16, p = 0.01) and frequency of seizures (-2.29, p = 0.00). Other factors associated with overall HRQOL included drug side effects, sex, marital status and education. Duration on AEDs was not a significant predictor of HRQOL.

CONCLUSION

The HRQOL for epilepsy patients on AEDs is very low. The predictors of low HRQOL were socio factors (marital status, education) and drug side effects, frequency of seizure, and type of therapy.

Weight change, genetics and antiepileptic drugs

Weight gain caused by antiepileptic drugs (AEDs) constitutes a serious problem in the management of people with epilepsy. AEDs associated with weight gain include sodium valproate, pregabalin and vigabatrin. Excessive weight gain can lead to non-compliance with treatment and to an exacerbation of obesity-related conditions. The mechanisms by which AEDs cause weight gain are not fully understood. It is likely that weight change induced by some AEDs has a genetic underpinning, and recent developments in DNA sequencing technology should speed the understanding, prediction and thus prevention of serious weight change associated with AEDs. This review focuses on the biology of obesity in the context of AEDs. Future directions in the investigations of the mechanism of weight change associated with these drugs and the use of such knowledge in tailoring the treatment of specific patient groups are explored.

RLIP76 Gene Variants are not Associated with Drug Response in Turkish Epilepsy Patients

Approximately 30% of epileptic patients remain untreated, in spite of trials with maximum tolerable doses of more than one drug. The RalA binding protein 1 (RALBP1/RLIP76), a multifunctional, anti-apoptot-ic, multidrug transporter protein, has been proposed as being responsible for the drug resistance mechanism in epilepsy. We have investigated polymorphic differences in the coding regions and exonintron boundaries of the RLIP76 gene, between 146 refractory and 155 non refractory epileptic patients in Turkey, using denaturing high performance liquid chromatography (HPLC) and sequencing analysis techniques. We have detected the following sequence variants: c.160-4G>A, c.187C>G, c.1562-38G>A, c.1670+107G>A, c.1670+93G>A, c.1670+96G>A, c.1670+100C>T, c.1670+130C>T, c.1670+131G>C, c.1670+140 G>C, and found no statistically significant correlation between allele frequencies and drug response status. We conclude that sequence variants of this gene are not involved in drug resistance in epilepsy.

Prognostic factors for medically intractable epilepsy: a systematic review

OBJECTIVE

One third of all epilepsy patients have medically intractable epilepsy. Knowledge of prognostic factors that, in an early therapeutic stage of epilepsy, herald intractability could facilitate patient management. In this systematic review, we examined the evidence for independent prognostic factors of intractability in patients with epilepsy.

METHODS

MEDLINE and EMBASE were searched for cohort studies reporting on prognostic factors for medically intractable epilepsy. After selection of abstracts, full-text articles were obtained and their quality was assessed by two reviewers, using the QUIPS checklist. All independent prognostic factors in the individual studies were summarized.

RESULTS

Eleven cohort studies were included, of which ten hospital-based. Younger age at seizure onset, symptomatic etiology, high initial seizure frequency, medical history, epileptic EEG abnormalities, and failure of previous antiepileptic-drugs (AEDs) were documented as independent prognostic factors of intractability in at least 2 of the 11 studies; none of these factors was reported in all 11 studies. None of the studies considered genetic, neurobiological, or immunological factors. The studies were of moderate quality, mostly because they did not provide a conceptual model for the choice of predictors. Heterogeneity in study design, population, candidate prognostic factors, and outcome definitions precluded statistical pooling.

CONCLUSIONS

While potentially relevant prognosticators of medically intractable epilepsy have been identified, the evidence for these factors is not consistent. There is a need for well-designed prognostic population-based cohort studies that also include pharmacological, genetic, neurobiological, and immunological factors. A valid model for the early prediction of medically intractable epilepsy could improve patient management.

Early predictors of outcome in newly diagnosed epilepsy

Longitudinal studies of newly diagnosed epilepsy in children and adults have identified prognostic factors that allow early identification of patients whose seizures are likely to remain uncontrolled with antiepileptic medication. Results from outcome studies may be subject to bias, depending on the setting (community versus clinic), design (retrospective versus prospective) and characteristics of the patient cohort studied (age, types of epilepsy, specific comorbidities). Nevertheless, factors such as early response to medication, underlying aetiology, and number of seizures prior to initiation of treatment have consistently been found to be predictive of seizure outcomes. Other variables such as age, electroencephalographic findings and the presence or absence of psychiatric co-morbidities have been correlated with outcomes in some analyses. This review has examined studies of seizure outcomes in adults and children with newly diagnosed epilepsy identifying the risk factors that are associated with subsequent refractory epilepsy.

Cerebral expression of drug transporters in epilepsy

Over-expression of drug efflux transporters at the level of the blood-brain barrier (BBB) has been proposed as a mechanism responsible for multidrug resistance. Drug transporters in epileptogenic tissue are not only expressed in endothelial cells at the BBB, but also in other brain parenchymal cells, such as astrocytes, microglia and neurons, suggesting a complex cell type-specific regulation under pathological conditions associated with epilepsy. This review focuses on the cerebral expression patterns of several classes of well-known membrane drug transporters such as P-glycoprotein (Pgp), and multidrug resistance-associated proteins (MRPs) in the epileptogenic brain. Both experimental and clinical evidence of epilepsy-associated cerebral drug transporter regulation and the possible mechanisms underlying drug transporter regulation are discussed. Knowledge of the cerebral expression patterns of drug transporters in normal and epileptogenic brain will provide relevant information to guide strategies attempting to overcome drug resistance by targeting specific transporters.

Neuroimaging for the prediction of response to medical and surgical treatment in epilepsy

INTRODUCTION

Approximately 30% of patients with epilepsy do not respond to adequate medication and are candidates for surgical treatment. Outcome predictors can improve the selection of more suitable treatment options for each patient. Therefore, the authors aimed to review the role of neuroimaging studies in predicting outcomes for both clinical and surgical treatment of epilepsy.

AREAS COVERED

This review analyzes studies that investigated different neuroimaging techniques as predictors of clinical and surgical treatment outcome in epilepsy. Studies involving both structural (i.e., T1-weighted images and diffusion tensor images) and functional MRI (fMRI) were identified, as well as other modalities such as spectroscopy, PET, SPECT and MEG. The authors also evaluated the importance of fMRI in predicting memory outcome after surgical resections in temporal lobe epilepsy.

EXPERT OPINION

The identification of reliable biomarkers to predict response to medical and surgical treatments are much needed in order to provide more adequate patient counseling about prognosis and treatment options individually. Different neuroimaging techniques may provide combined measurements that potentially may become these biomarkers in the near future.

Transporter hypothesis of drug-resistant epilepsy: challenges for pharmacogenetic approaches

Drug resistance in epilepsy is considered a complex and multifactorial problem. Overexpression of efflux transporters at the blood-brain barrier is discussed as one factor that might limit brain penetration and efficacy of antiepileptic drugs. Whereas experimental data render support for this hypothesis, there is still a lack of sufficient clinical evidence indicating a functional role of efflux transporters. Pharmacogenetic analysis has been considered as one approach in the evaluation of a putative link between transporters and drug-resistant epilepsy. However, the likelihood of a multifactorial nature of drug resistance and the complexity of the events regulating transporters pose a major challenge to any attempt at linking selected genetic polymorphisms to the outcome of drug therapy. In this article, the evidence for an impact of efflux transporters on the response to antiepileptic drugs is discussed, focusing in particular on the different issues presenting a challenge for pharmacogenetic approaches in this field.

Update on the Genetic Polymorphisms of Drug-Metabolizing Enzymes in Antiepileptic Drug Therapy

Genetic polymorphisms in the genes that encode drug-metabolizing enzymes are implicated in the inter-individual variability in the pharmacokinetics and pharmaco-dynamics of antiepileptic drugs (AEDs). However, the clinical impact of these polymorphisms on AED therapy still remains controversial. The defective alleles of cytochrome P450 (CYP) 2C9 and/or CYP2C19 could affect not only the pharmacokinetics, but also the pharmacodynamics of phenytoin therapy. CYP2C19 deficient genotypes were associated with the higher serum concentration of an active metabolite of clobazam, N-desmethylclobazam, and with the higher clinical efficacy of clobazam therapy than the other CYP2C19 genotypes. The defective alleles of CYP2C9 and/or CYP2C19 were also found to have clinically significant effects on the inter-individual variabilities in the population pharmacokinetics of phenobarbital, valproic acid and zonisamide. EPHX1 polymorphisms may be associated with the pharmacokinetics of carbamazepine and the risk of phenytoin-induced congenital malformations. Similarly, the UDP-glucuronosyltransferase 2B7 genotype may affect the pharmacokinetics of lamotrigine. Gluthatione S-transferase null genotypes are implicated in an increased risk of hepatotoxicity caused by carbamazepine and valproic acid. This article summarizes the state of research on the effects of mutations of drug-metabolizing enzymes on the pharmacokinetics and pharmacodynamics of AED therapies. Future directions for the dose-adjustment of AED are discussed.