Pharmacoresponse in genetic generalized epilepsy: a genome-wide association study

Drug-resistant juvenile myoclonic epilepsy: A literature review

The ILAE's Task Force on Nosology and Definitions revised in 2022 its definition of juvenile myoclonic epilepsy (JME), the most common idiopathic generalized epilepsy disorder, but this definition may well change again in the future. Although good drug response could almost be a diagnostic criterion for JME, drug resistance (DR) is observed in up to a third of patients. It is important to distinguish this from pseudoresistance, which is often linked to psychosocial problems or psychiatric comorbidities. After summarizing these aspects and the various definitions applied to JME, the present review lists the risk factors for DR-JME that have been identified in numerous studies and meta-analyses. The factors most often cited are absence seizures, young age at onset, and catamenial seizures. By contrast, photosensitivity seems to favor good treatment response, at least in female patients. Current hypotheses on DR mechanisms in JME are based on studies of either simple (e.g., cortical excitability) or more complex (e.g., anatomical and functional connectivity) neurophysiological markers, bearing in mind that JME is regarded as a neural network disease. This research has revealed correlations between the intensity of some markers and DR, and above all shed light on the role of these markers in associated neurocognitive and neuropsychiatric disorders in both patients and their siblings. Studies of neurotransmission have mainly pointed to impaired GABAergic inhibition. Genetic studies have generally been inconclusive. Increasing restrictions have been placed on the use of valproate, the standard antiseizure medication for this syndrome, owing to its teratogenic and developmental risks. Levetiracetam and lamotrigine are prescribed as alternatives, as is vagal nerve stimulation, and there are several other promising antiseizure drugs and neuromodulation methods. The development of better alternative treatments is continuing to take place alongside advances in our knowledge of JME, as we still have much to learn and understand.

Genetic variation supports a causal role for valproate in prevention of ischemic stroke

BACKGROUND

Valproate is a candidate for ischemic stroke prevention due to its anti-atherosclerotic effects in vivo. Although valproate use is associated with decreased ischemic stroke risk in observational studies, confounding by indication precludes causal conclusions.

AIMS

We applied Mendelian randomization to determine whether genetic variants that influence seizure response among valproate users associate with ischemic stroke.

METHODS

We derived a genetic score for valproate response using genome-wide association data of seizure response after valproate intake from the Epilepsy Pharmacogenomics Consortium. We then tested this score among valproate users of the UK Biobank for association with incident and recurrent ischemic stroke using Cox proportional hazard models. As replication, we tested found associations in an independent cohort of valproate users of the Mass General Brigham Biobank.

RESULTS

Among 2150 valproate users (mean 56 years, 54% females), 82 ischemic strokes occurred over a mean 12 year follow-up. Higher valproate response genetic score was associated with higher serum valproate levels (+5.78 µg/ml per 1 standard deviation (SD), 95% confidence interval (CI) (3.45, 8.11)). After adjusting for age and sex, higher valproate response genetic score was associated with lower ischemic stroke risk (hazard ratio (HR) per 1 SD 0.73, 95% CI (0.58, 0.91)) with a halving of absolute risk in the highest compared to the lowest score tertile (4.8% vs 2.5%, p trend = 0.027). Among 194 valproate users with prevalent stroke at baseline, a higher valproate response genetic score was associated with lower recurrent ischemic stroke risk (HR per 1 SD 0.53, 95% CI (0.32, 0.86)) with reduced absolute risk in the highest compared to the lowest score tertile (3/51, 5.9% vs 13/71, 18.3%, p trend = 0.026). The valproate response genetic score was not associated with ischemic stroke among the 427,997 valproate non-users (p = 0.61), suggesting minimal pleiotropy. In 1241 valproate users of the Mass General Brigham Biobank with 99 ischemic stroke events over 6.5 years follow-up, we replicated our observed associations between the valproate response genetic score and ischemic stroke (HR per 1 SD 0.77, 95% CI (0.61, 0.97)).

CONCLUSION

These results demonstrate that a genetically predicted favorable seizure response to valproate is associated with higher serum valproate levels and reduced ischemic stroke risk among valproate users, providing causal support for valproate effectiveness in ischemic stroke prevention. The strongest effect was found for recurrent ischemic stroke, suggesting potential dual-use benefits of valproate for post-stroke epilepsy. Clinical trials will be required in order to identify populations that may benefit most from valproate for stroke prevention.

DATA ACCESS STATEMENT

UK Biobank participant data are available after approval of a research proposal. The weights of the used genetic scores are available in the Supplemental Tables.

Assessment of clinically actionable pharmacogenetic markers to stratify anti-seizure medications

Epilepsy treatment is challenging due to heterogeneous syndromes, different seizure types and higher inter-individual variability. Identification of genetic variants predicting drug efficacy, tolerability and risk of adverse-effects for anti-seizure medications (ASMs) is essential. Here, we assessed the clinical actionability of known genetic variants, based on their functional and clinical significance and estimated their diagnostic predictability. We performed a systematic PubMed search to identify articles with pharmacogenomic (PGx) information for forty known ASMs. Functional annotation of the identified genetic variants was performed using different in silico tools, and their clinical significance was assessed using the American College of Medical Genetics (ACMG) guidelines for variant pathogenicity, level of evidence (LOE) from PharmGKB and the United States-Food and drug administration (US- FDA) drug labelling with PGx information. Diagnostic predictability of the replicated genetic variants was evaluated by calculating their accuracy. A total of 270 articles were retrieved with PGx evidence associated with 19 ASMs including 178 variants across 93 genes, classifying 26 genetic variants as benign/ likely benign, fourteen as drug response markers and three as risk factors for drug response. Only seventeen of these were replicated, with accuracy (up to 95%) in predicting PGx outcomes specific to six ASMs. Eight out of seventeen variants have FDA-approved PGx drug labelling for clinical implementation. Therefore, the remaining nine variants promise for potential clinical actionability and can be improvised with additional experimental evidence for clinical utility.

Genetic variation supports a causal role for valproate in prevention of ischemic stroke

Valproate is a candidate for ischemic stroke prevention due to its anti-atherosclerotic effects in vivo. Although valproate use is associated with decreased ischemic stroke risk in observational studies, confounding by indication precludes causal conclusions. To overcome this limitation, we applied Mendelian randomization to determine whether genetic variants that influence seizure response among valproate users associate with ischemic stroke. We derived a genetic score for valproate response using genome-wide association data of seizure response after valproate intake from the Epilepsy Pharmacogenomics Consortium. We then tested this score among valproate users of the UK Biobank for association with incident and recurrent ischemic stroke using Cox proportional hazard models. Among 2,150 valproate users (mean 56 years, 54% females), 82 ischemic strokes occurred over a mean 12-year follow-up. Higher valproate response genetic score was associated with higher serum valproate levels (+5.78 μg/ml per one SD, 95% CI [3.45, 8.11]). After adjusting for age and sex, higher valproate response genetic score was associated with lower ischemic stroke risk (HR per one SD 0.73, [0.58, 0.91]) with a halving of absolute risk in the highest compared to the lowest score tertile (4.8% vs 2.5%, p-trend=0.027). Among 194 valproate users with prevalent stroke at baseline, a higher valproate response genetic score was associated with lower recurrent ischemic stroke risk (HR per one SD 0.53, [0.32, 0.86]) with reduced absolute risk in the highest compared to the lowest score tertile (3/51, 5.9% vs. 13/71, 18.3%, p-trend=0.026). The valproate response genetic score was not associated with ischemic stroke among the 427,997 valproate non-users (p=0.61), suggesting minimal pleiotropy. In an independent cohort of 1,241 valproate users of the Mass General Brigham Biobank with 99 ischemic stroke events over 6.5 years follow-up, we replicated our observed associations between the valproate response genetic score and ischemic stroke (HR per one SD 0.77, 95% CI: [0.61, 0.97]). These results demonstrate that a genetically predicted favorable seizure response to valproate is associated with higher serum valproate levels and reduced ischemic stroke risk among valproate users, providing causal support for valproate effectiveness in ischemic stroke prevention. The strongest effect was found for recurrent ischemic stroke, suggesting potential dual-use benefits of valproate for post-stroke epilepsy. Clinical trials will be required in order to identify populations that may benefit most from valproate for stroke prevention.

Fighting Epilepsy with Nanomedicines-Is This the Right Weapon?

Epilepsy is a chronic and complex condition and is one of the most common neurological diseases, affecting about 50 million people worldwide. Pharmacological therapy has been, and is likely to remain, the main treatment approach for this disease. Although a large number of new antiseizure drugs (ASDs) has been introduced into the market in the last few years, many patients suffer from uncontrolled seizures, demanding the development of more effective therapies. Nanomedicines have emerged as a promising approach to deliver drugs to the brain, potentiating their therapeutic index. Moreover, nanomedicine has applied the knowledge of nanoscience, not only in disease treatment but also in prevention and diagnosis. In the current review, the general features and therapeutic management of epilepsy will be addressed, as well as the main barriers to overcome to obtain better antiseizure therapies. Furthermore, the role of nanomedicines as a valuable tool to selectively deliver drugs will be discussed, considering the ability of nanocarriers to deal with the less favourable physical-chemical properties of some ASDs, enhance their brain penetration, reduce the adverse effects, and circumvent the concerning drug resistance.

Drug resistance in idiopathic generalized epilepsies: Evidence and concepts

Although approximately 10%-15% of patients with idiopathic generalized epilepsy (IGE)/genetic generalized epilepsy remain drug-resistant, there is no consensus or established concept regarding the underlying mechanisms and prevalence. This review summarizes the recent data and the current hypotheses on mechanisms that may contribute to drug-resistant IGE. A literature search was conducted in PubMed and Embase for studies on mechanisms of drug resistance published since 1980. The literature shows neither consensus on the definition nor a widely accepted model to explain drug resistance in IGE or one of its subsyndromes. Large-scale genetic studies have failed to identify distinct genetic causes or affected genes involved in pharmacokinetics. We found clinical and experimental evidence in support of four hypotheses: (1) "network hypothesis"-the degree of drug resistance in IGE reflects the severity of cortical network alterations, (2) "minor focal lesion in a predisposed brain hypothesis"-minor cortical lesions are important for drug resistance, (3) "interneuron hypothesis"-impaired functioning of γ-aminobutyric acidergic interneurons contributes to drug resistance, and (4) "changes in drug kinetics"-genetically impaired kinetics of antiseizure medication (ASM) reduce the effectiveness of available ASMs. In summary, the exact definition and cause of drug resistance in IGE is unknown. However, published evidence suggests four different mechanisms that may warrant further investigation.

Benchmarking of univariate pleiotropy detection methods applied to epilepsy

Pleiotropy is a widespread phenomenon that may increase insight into the etiology of biological and disease traits. Since genome-wide association studies frequently provide information on a single trait only, only univariate pleiotropy detection methods are applicable, with yet unknown comparative performance. Here, we compared five such methods with respect to their ability to detect pleiotropy, including meta-analysis, ASSET, cFDR, CPBayes, and PLACO, by performing extended computer simulations that varied the underlying etiological model for pleiotropy for a pair of traits, including the number of causal variants, degree of traits' overlap, effect sizes as well as trait prevalence, and varying sample sizes. Our results indicate that ASSET provides the best trade-off between power and protection against false positives. We then applied ASSET to a previously published ILAE consortium dataset on complex epilepsies, comprising genetic generalized epilepsy and focal epilepsy cases and corresponding controls. We identified a novel candidate locus at 17q21.32 and confirmed locus 2q24.3, previously identified to act pleiotropically on both epilepsy subtypes by a mega-analysis. Functional annotation, tissue-specific expression and regulatory function analysis as well as Bayesian co-localization analysis corroborated this result, rendering 17q21.32 a worthwhile candidate for follow-up studies on pleiotropy in epilepsies. This article is protected by copyright. All rights reserved.

Novel and emerging therapeutics for genetic epilepsies

INTRODUCTION

Disease-specific treatments are available only for a minority of patients with genetic epilepsies, while the rest are treated with anticonvulsants, which are ineffective in almost one-third of patients.

AREAS COVERED

Recently approved and the most effective emerging therapeutics under development for the treatment of genetic epilepsies are overviewed after systematic search and analysis of relevant literature.

EXPERT OPINION

New and emerging drugs for genetic epilepsies exploit one of the two approaches: inhibiting hyperactive brain foci through blocking excitatory or augmenting inhibitory neurotransmission, or correcting the underlying genetic defect. The first is limited by insufficient selectivity of available compounds, and the second by imperfection of currently used vectors of genetic material, unselective and transient transgene expression. Besides, the treatment may come too late, after structural abnormalities and epilepsy deterioration takes place. However, with recent improvements, we can expect to see soon gradual decline in the number of patients with therapy-resistant genetic epilepsies.

Treatment outcomes in drug resistant juvenile myoclonic epilepsy: Valproate resistance may not be the end of the road

OBJECTIVE

To determine treatment responses to various antiseizure medicines (ASMs) in patients with drug resistant juvenile myoclonic epilepsy (DRJME) METHODS: We reviewed records of all JME patients attending epilepsy clinics at 5 centers during a 5-year period. We used International Consensus Criteria to diagnose JME and International League Against Epilepsy Criteria to define drug resistance and sustained seizure freedom. We only used broad spectrum medicines which included valproate, lamotrigine, topiramate, levetiracetam, clobazam, phenobarbitone, clonazepam, and zonisamide. We considered an ASM successful if patient achieved seizure freedom within 3 months of attaining maintenance dose.

RESULTS

We studied 116 patients (61 males) with DRJME. At terminal followup, 82 (70.7%) patients had achieved sustained seizure freedom with a mean followup of 3.2 ± 1.3 years after last dose change. In patients where valproate failed as first- or second-line ASM (n=70; 60.3%), 49(70%) became seizure-free. In this group, 33(67%) patients became seizure-free after addition of lamotrigine. Success rate of lamotrigine and valproate combination was 69% as compared to 9% with all other combinations (p = 0.001). In patients who were not exposed to valproate as initial therapy (n=46), 33 (71.7%) became seizure-free, 30 (91%) after adding valproate. At last follow-up, 75 (90%) seizure-free patients were receiving valproate including 45 (55%) patients with a combination of valproate and lamotrigine. Only one of 24 patients became seizure-free after failing valproate and lamotrigine combination.

CONCLUSION

Seizure freedom can be achieved in two-thirds of patients with DRJME. A combination of valproate and lamotrigine is the most effective duotherapy.

Correlation of elevated lamotrigine and levetiracetam serum/plasma levels with toxicity: A long-term retrospective review at an academic medical center

Lamotrigine and levetiracetam are widely used second-generation anti-epileptic drugs. Existing literature indicates that overdose of either drug is typically benign, but neurologic and cardiac toxicity can occur in some cases. In this retrospective study, we analyzed a large dataset of serum/plasma drug levels for lamotrigine and levetiracetam. The data covered 1,930 unique patients (5,046 levels) for lamotrigine and 2,451 patients (4,359 levels) for levetiracetam. We performed detailed chart review on all patients with one or more lamotrigine levels greater than 14.0 mg/L (293 unique patients) and all patients with one or more levetiracetam levels of 80 mg/L or higher (106 unique patients). No deaths directly attributable to lamotrigine or levetiracetam toxicity were reported. For cases with lamotrigine levels greater than 14.0 mg/L, the majority of patients were asymptomatic (55.3 %, n = 162). The most common presenting symptoms were ataxia (14.3 %, n = 42), seizures (14.0 %, n = 41), dizziness (11.9 %, n = 35), and altered mental status (11.6 %, n = 34). There were 12 overdoses (11 intentional) involving lamotrigine, all of which presented with either altered mental status (n = 8) or seizures (n = 4). The highest estimated dose reportedly ingested was 20 g. Cardiac toxicity was observed in two cases involving intentional overdose of lamotrigine. For patients with levetiracetam serum/plasma levels of 80 mg/L or higher, 48 patients (45.3 %) were asymptomatic. Symptomatic patients most commonly presented with seizures (31.1 %, n = 33) and altered mental status (15.1 %, n = 16), and none showed cardiac symptoms. There were only two cases involving intentional levetiracetam overdose, one of which presented with altered mental status after ingestion of 45 g and the other asymptomatic after ingestion of 6 g. Overall, our data is consistent with previous investigations that lamotrigine and levetiracetam toxicity most typically presents with neurologic symptoms and rarely cardiac arrhythmias. Approximately half of the patients with elevated lamotrigine or levetiracetam drug levels are asymptomatic.

Assessing the role of rare genetic variants in drug-resistant, non-lesional focal epilepsy

OBJECTIVE

Resistance to antiseizure medications (ASMs) is one of the major concerns in the treatment of epilepsy. Despite the increasing number of ASMs available, the proportion of individuals with drug-resistant epilepsy remains unchanged. In this study, we aimed to investigate the role of rare genetic variants in ASM resistance.

METHODS

We performed exome sequencing of 1,128 individuals with non-familial non-acquired focal epilepsy (NAFE) (762 non-responders, 366 responders) and were provided with 1,734 healthy controls. We undertook replication in a cohort of 350 individuals with NAFE (165 non-responders, 185 responders). We performed gene-based and gene-set-based kernel association tests to investigate potential enrichment of rare variants in relation to drug response status and to risk for NAFE.

RESULTS

We found no gene or gene set that reached genome-wide significance. Yet, we identified several prospective candidate genes - among them DEPDC5, which showed a potential association with resistance to ASMs. We found some evidence for an enrichment of truncating variants in dominant familial NAFE genes in our cohort of non-familial NAFE and in association with drug-resistant NAFE.

INTERPRETATION

Our study identifies potential candidate genes for ASM resistance. Our results corroborate the role of rare variants for non-familial NAFE and imply their involvement in drug-resistant epilepsy. Future large-scale genetic research studies are needed to substantiate these findings.

Role of Common Genetic Variants for Drug-Resistance to Specific Anti-Seizure Medications

Objective: Resistance to anti-seizure medications (ASMs) presents a significant hurdle in the treatment of people with epilepsy. Genetic markers for resistance to individual ASMs could support clinicians to make better-informed choices for their patients. In this study, we aimed to elucidate whether the response to individual ASMs was associated with common genetic variation. Methods: A cohort of 3,649 individuals of European descent with epilepsy was deeply phenotyped and underwent single nucleotide polymorphism (SNP)-genotyping. We conducted genome-wide association analyses (GWASs) on responders to specific ASMs or groups of functionally related ASMs, using non-responders as controls. We performed a polygenic risk score (PRS) analyses based on risk variants for epilepsy and neuropsychiatric disorders and ASM resistance itself to delineate the polygenic burden of ASM-specific drug resistance. Results: We identified several potential regions of interest but did not detect genome-wide significant loci for ASM-specific response. We did not find polygenic risk for epilepsy, neuropsychiatric disorders, and drug-resistance associated with drug response to specific ASMs or mechanistically related groups of ASMs. Significance: This study could not ascertain the predictive value of common genetic variants for ASM responder status. The identified suggestive loci will need replication in future studies of a larger scale.

Diagnostic and therapeutic approach to drug-resistant juvenile myoclonic epilepsy

INTRODUCTION

Juvenile myoclonic epilepsy (JME), also known as Janz syndrome, is a common form of generalized epilepsy of presumed genetic origin representing up to 10% of all epilepsy cases. Despite adequate anti-seizure medication (ASM) treatment, seizures persist in one-third of JME patients.

AREAS COVERED

A literature search was conducted using Pubmed search on the topics of drug-resistant JME.

EXPERT OPINION

About 30% of JME patients are drug-resistant. Valproate (VPA) is considered the first-choice drug. In women of childbearing potential, levetiracetam (LEV) should represent the first-choice treatment. Alternative monotherapy or add-on therapy should be considered in subjects with resistant seizures after the exclusion of pseudo-drug resistance. The choice of the add-on ASM depends on the predominant seizure type. In subjects with persistent bilateral tonic-clonic seizures, LEV or lamotrigine should be firstly considered. In patients with difficult-to-treat myoclonic seizures, clonazepam or LEV are recommended. In case of persistent absences, ethosuximide should be considered. With appropriate selection and safeguards in place, VPA should remain available as an option in women of childbearing potential whose seizures are resistant to other treatments.

Imputation and Reanalysis of ExomeChip Data Identifies Novel, Conditional and Joint Genetic Effects on Parkinson's Disease Risk

Given that improved imputation software and high-coverage whole genome sequence (WGS)-based haplotype reference panels now enable inexpensive approximation of WGS genotype data, we hypothesised that WGS-based imputation and analysis of existing ExomeChip-based genome-wide association (GWA) data will identify novel intronic and intergenic single nucleotide polymorphism (SNP) effects associated with complex disease risk. In this study, we reanalysed a Parkinson’s disease (PD) dataset comprising 5540 cases and 5862 controls genotyped using the ExomeChip-based NeuroX array. After genotype imputation and extensive quality control, GWA analysis was performed using PLINK and a recently developed machine learning approach (GenEpi), to identify novel, conditional and joint genetic effects associated with PD. In addition to improved validation of previously reported loci, we identified five novel genome-wide significant loci associated with PD: three (rs137887044, rs78837976 and rs117672332) with 0.01 < MAF < 0.05, and two (rs187989831 and rs12100172) with MAF < 0.01. Conditional analysis within genome-wide significant loci revealed four loci (p < 1 × 10⁻⁵) with multiple independent risk variants, while GenEpi analysis identified SNP–SNP interactions in seven genes. In addition to identifying novel risk loci for PD, these results demonstrate that WGS-based imputation and analysis of existing exome genotype data can identify novel intronic and intergenic SNP effects associated with complex disease risk.

[Decision support systems, assistance systems and telemedicine in epileptology]

Hintergrund

Die wissenschaftlichen Erkenntnisse über Epilepsien und deren klinische Implikationen nehmen rasant zu. Für Nichtexperten stellt sich die zunehmende Herausforderung, den Überblick hierüber zu bewahren. Hier setzen Clinical-decision-support-Systeme (CDSS) an, indem sie standard- und expertengetriggertes Wissen zur Diagnostik und Therapie individualisiert und automatisiert liefern. Zudem sind Medizin-Apps und telemedizinische Verfahren zur Diagnostik und Therapie sowie Assistenzsysteme zur Anfallsdetektion bei Epilepsien verfügbar.

Ziel der Arbeit

Es soll ein Überblick über die aktuellen Entwicklungen und Anwendungsmöglichkeiten verfügbarer tele-epileptologischer Methoden gegeben werden.

Material und Methoden

Auf der Basis persönlicher Kenntnis und eines Literaturreviews werden epilepsiespezifische CDSS, Medizin-Apps, Assistenzsysteme sowie telemedizinische Anwendungen charakterisiert und deren klinische Einsatzmöglichkeiten dargestellt.

Ergebnisse und Diskussion

Personen mit Epilepsie könnten aufgrund des chronischen Verlaufs und der Komplexität der Erkrankung und ihrer Folgen von CDSS profitieren. Es erscheint wünschenswert, dass epilepsiespezifische CDSS sowohl für die Behandelnden als auch für Patienten nutzbar werden. Apps für Menschen mit Epilepsie dienen derzeit meist der Verlaufsdokumentation von Anfallsfrequenz, Medikamentencompliance und Nebenwirkungen. Gegenwärtige Anfallsdetektionssysteme erkennen vor allem generalisiert tonisch-klonische Anfälle (GTKA). Ein klinischer Nutzen ist noch nicht hinreichend belegt, erscheint aber wahrscheinlich, insbesondere da GTKA mit dem Risiko eines plötzlichen Todes von Epilepsiepatienten assoziiert sind und Interventionen als wirksam gelten.

Genetic Association of Epilepsy and Anti-Epileptic Drugs Treatment in Jordanian Patients

Purpose

The aim of this study was to investigate the possible effects of single-nucleotide polymorphisms (SNPs) within SLC1A1, SLC6A1, FAM131B, GPLD1, F2, GABRG2, GABRA1, and CACNG5 genes on response to anti-epileptic drugs (AEDs) and the genetic predisposition of epilepsy in Jordanian patients.

Patients and Methods

A total of 299 healthy individuals and 296 pediatric patients from the Jordanian population were recruited. Blood samples are collected, and genotyping was performed using a custom platform array analysis.

Results

The SLC1A1 rs10815018 and FAM131B rs4236482 polymorphisms found to be associated with epilepsy susceptibility. Moreover, SLC1A1 rs10815018 and GPLD1 rs1126617 polymorphisms were associated with generalized epilepsy (GE), while FAM131B rs4236482 is associated with the focal phenotype. Regarding the therapeutic response, the genetic polymorphisms of FAM131B rs4236482, GABRA1 rs2279020, and CACNG5 rs740805 are conferred poor response (resistance) to AEDs. There was no linkage of GLPD1 haplotypes to epilepsy, its subtypes, and treatment responsiveness.

Conclusion

Our findings suggested that SLC1A1, FAM131B, and GPLD1 polymorphisms increasing the risk of generating epilepsy, while FAM131B, GABRA1, and CACNG5 variants may play a role in predicting drug response in patients with epilepsy (PWE).