Somatic mosaicism in focal epilepsies.

PURPOSE OF REVIEW: Over the past decade, it has become clear that brain somatic mosaicism is an important contributor to many focal epilepsies. The number of cases and the range of underlying pathologies with somatic mosaicism are rapidly increasing. This growth in somatic variant discovery is revealing dysfunction in distinct molecular pathways in different focal epilepsies. RECENT FINDINGS: We briefly summarize the current diagnostic yield of pathogenic somatic variants across all types of focal epilepsy where somatic mosaicism has been implicated and outline the specific molecular pathways affected by these variants. We will highlight the recent findings that have increased diagnostic yields such as the discovery of pathogenic somatic variants in novel genes, and new techniques that allow the discovery of somatic variants at much lower variant allele fractions. SUMMARY: A major focus will be on the emerging evidence that somatic mosaicism may contribute to some of the more common focal epilepsies such as temporal lobe epilepsy with hippocampal sclerosis, which could lead to it being re-conceptualized as a genetic disorder.

Familial Mesial Temporal Lobe Epilepsy: Clinical Spectrum and Genetic Evidence for a Polygenic Architecture.

OBJECTIVE: Familial mesial temporal lobe epilepsy (FMTLE) is an important focal epilepsy syndrome; its molecular genetic basis is unknown. Clinical descriptions of FMTLE vary between a mild syndrome with prominent déjà vu to a more severe phenotype with febrile seizures and hippocampal sclerosis. We aimed to refine the phenotype of FMTLE by analyzing a large cohort of patients and asked whether common risk variants for focal epilepsy and/or febrile seizures, measured by polygenic risk scores (PRS), are enriched in individuals with FMTLE. METHODS: We studied 134 families with ≥ 2 first or second-degree relatives with temporal lobe epilepsy, with clear mesial ictal semiology required in at least one individual. PRS were calculated for 227 FMTLE cases, 124 unaffected relatives, and 16,077 population controls. RESULTS: The age of patients with FMTLE onset ranged from 2.5 to 70 years (median = 18, interquartile range = 13-28 years). The most common focal seizure symptom was déjà vu (62% of cases), followed by epigastric rising sensation (34%), and fear or anxiety (22%). The clinical spectrum included rare cases with drug-resistance and/or hippocampal sclerosis. FMTLE cases had a higher mean focal epilepsy PRS than population controls (odds ratio = 1.24, 95% confidence interval = 1.06, 1.46, p = 0.007); in contrast, no enrichment for the febrile seizure PRS was observed. INTERPRETATION: FMTLE is a generally mild drug-responsive syndrome with déjà vu being the commonest symptom. In contrast to dominant monogenic focal epilepsy syndromes, our molecular data support a polygenic basis for FMTLE. Furthermore, the PRS data suggest that sub-genome-wide significant focal epilepsy genome-wide association study single nucleotide polymorphisms are important risk variants for FMTLE. ANN NEUROL 2023;94:825-835.

Lacosamide and pregnancy: Data from spontaneous and solicited reports.

OBJECTIVE: In pregnancy, it is important to balance the risks of uncontrolled epileptic seizures to the mother and fetus against the potential teratogenic effects of antiseizure medications. Data are limited on pregnancy outcomes among patients taking lacosamide (LCM), particularly when taken as monotherapy. The objective of this analysis was to evaluate the pregnancy outcomes of LCM-exposed pregnancies. METHODS: This analysis included all reports in the UCB Pharma pharmacovigilance database of exposure to LCM during pregnancy from spontaneous sources (routine clinical settings) or solicited reports from interventional clinical studies and noninterventional postmarketing studies. Prospective and retrospective reports were analyzed separately. RESULTS: At the data cutoff (August 31, 2021), there were 202 prospective pregnancy cases with maternal exposure to LCM and known outcomes. Among these cases, 44 (21.8%) patients received LCM monotherapy and 158 (78.2%) received LCM polytherapy. Most patients received LCM during the first trimester (LCM monotherapy: 39 [88.6%]; LCM polytherapy: 143 [90.5%]). From the prospective pregnancy cases with maternal LCM exposure, there were 204 reported outcomes (two twin pregnancies occurred in the polytherapy group). The proportion of live births was 84.1% (37/44) in patients who received LCM as monotherapy, and 76.3% (122/160) for LCM polytherapy. The overall proportion of abortions (for any reason) was 15.9% (7/44) with LCM monotherapy, and 22.5% (36/160) with LCM polytherapy. Congenital malformations were reported in 2.3% (1/44) of known pregnancy outcomes with maternal exposure to LCM monotherapy, and 6.9% (11/160) with polytherapy. SIGNIFICANCE: Our preliminary data do not raise major concerns on the use of LCM during pregnancy. Most pregnancies with LCM exposure resulted in healthy live births, and no new safety issues were identified. These findings should be interpreted with caution, as additional data are needed to fully evaluate the safety profile of LCM in pregnancy.

Amygdala enlargement in temporal lobe epilepsy: Histopathology and surgical outcomes.

OBJECTIVES: Amygdala enlargement is detected on magnetic resonance imaging (MRI) in some patients with drug-resistant temporal lobe epilepsy (TLE), but its clinical significance remains uncertain We aimed to assess if the presence of amygdala enlargement (1) predicted seizure outcome following anterior temporal lobectomy with amygdalohippocampectomy (ATL-AH) and (2) was associated with specific histopathological changes. METHODS: This was a case-control study. We included patients with drug-resistant TLE who underwent ATL-AH with and without amygdala enlargement detected on pre-operative MRI. Amygdala volumetry was done using FreeSurfer for patients who had high-resolution T1-weighted images. Mann-Whitney U test was used to compare pre-operative clinical characteristics between the two groups. The amygdala volume on the epileptogenic side was compared to the amygdala volume on the contralateral side among cases and controls. Then, we used a two-sample, independent t test to compare the means of amygdala volume differences between cases and controls. The chi-square test was used to assess the correlation of amygdala enlargement with (1) post-surgical seizure outcomes and (2) histopathological changes. RESULTS: Nineteen patients with and 19 patients without amygdala enlargement were studied. Their median age at surgery was 38 years for cases and 39 years for controls, and 52.6% were male. There were no statistically significant differences between the two groups in their pre-operative clinical characteristics. There were significant differences in the means of volume difference between cases and controls (Diff = 457.2 mm3, 95% confidence interval [CI] 289.6-624.8; p < .001) and in the means of percentage difference (p < .001). However, there was no significant association between amygdala enlargement and surgical outcome (p = .72) or histopathological changes (p = .63). SIGNIFICANCE: The presence of amygdala enlargement on the pre-operative brain MRI in patients with TLE does not affect the surgical outcome following ATL-AH, and it does not necessarily suggest abnormal histopathology. These findings suggest that amygdala enlargement might reflect a secondary reactive process to seizures in the epileptogenic temporal lobe.

Predictive models for starting antiseizure medication withdrawal following epilepsy surgery in adults.

More than half of adults with epilepsy undergoing resective epilepsy surgery achieve long-term seizure freedom and might consider withdrawing antiseizure medications. We aimed to identify predictors of seizure recurrence after starting postoperative antiseizure medication withdrawal and develop and validate predictive models. We performed an international multicentre observational cohort study in nine tertiary epilepsy referral centres. We included 850 adults who started antiseizure medication withdrawal following resective epilepsy surgery and were free of seizures other than focal non-motor aware seizures before starting antiseizure medication withdrawal. We developed a model predicting recurrent seizures, other than focal non-motor aware seizures, using Cox proportional hazards regression in a derivation cohort (n = 231). Independent predictors of seizure recurrence, other than focal non-motor aware seizures, following the start of antiseizure medication withdrawal were focal non-motor aware seizures after surgery and before withdrawal [adjusted hazard ratio (aHR) 5.5, 95% confidence interval (CI) 2.7-11.1], history of focal to bilateral tonic-clonic seizures before surgery (aHR 1.6, 95% CI 0.9-2.8), time from surgery to the start of antiseizure medication withdrawal (aHR 0.9, 95% CI 0.8-0.9) and number of antiseizure medications at time of surgery (aHR 1.2, 95% CI 0.9-1.6). Model discrimination showed a concordance statistic of 0.67 (95% CI 0.63-0.71) in the external validation cohorts (n = 500). A secondary model predicting recurrence of any seizures (including focal non-motor aware seizures) was developed and validated in a subgroup that did not have focal non-motor aware seizures before withdrawal (n = 639), showing a concordance statistic of 0.68 (95% CI 0.64-0.72). Calibration plots indicated high agreement of predicted and observed outcomes for both models. We show that simple algorithms, available as graphical nomograms and online tools (predictepilepsy.github.io), can provide probabilities of seizure outcomes after starting postoperative antiseizure medication withdrawal. These multicentre-validated models may assist clinicians when discussing antiseizure medication withdrawal after surgery with their patients.

Pregnancy, antiseizure medications and unexplained intrauterine foetal death.

OBJECTIVE: To assess the role of antiseizure medication (ASM) regimens and other factors in relation to the occurrence of intrauterine foetal death (IUFD) in pregnant women with epilepsy (WWE) enrolled in the Raoul Wallenberg Australian Pregnancy Register of Antiepileptic Drugs (APR). RESULTS: IUFDs occurred in 70 (3.01 %) of 2,323 prospective pregnancies from WWE with known outcomes in the APR. Factors associated with IUFD occurrence included older maternal age, enrolment in the APR at an earlier stage of pregnancy, history of pregnancies which did not result in livebirths, parental history of foetal malformations, and maternal use of carbamazepine, lamotrigine or ethosuximide. Individual ASM dosages were not associated with IUFD occurrence. Relative to no exposure, the risk of IUFD increased with the increasing number of ASMs used in combination (2 ASMs: relative risk, RR = 5.45 [95 % CI: 0.73-41.80]; 3 ASMs: RR = 10.70 [95 % CI: 1.27-90.17]), >3 ASMs: RR = 10.70 [95 % CI: 1.27-90.17]), but this finding was attenuated after adjusting for other factors implicated in IUFD occurrence. Several ASM pairs were associated with an increased risk of IUFD relative to no exposure, but these associations were lost after accounting for confounders. CONCLUSIONS: Although it is possible that prenatal ASM exposure may increase the risk of IUFD, other non-pharmacological factors are more relevant to the occurrence to IUFD in pregnant WWE.

The Genetics of Epilepsy.

Epilepsy encompasses a group of heterogeneous brain diseases that affect more than 50 million people worldwide. Epilepsy may have discernible structural, infectious, metabolic, and immune etiologies; however, in most people with epilepsy, no obvious cause is identifiable. Based initially on family studies and later on advances in gene sequencing technologies and computational approaches, as well as the establishment of large collaborative initiatives, we now know that genetics plays a much greater role in epilepsy than was previously appreciated. Here, we review the progress in the field of epilepsy genetics and highlight molecular discoveries in the most important epilepsy groups, including those that have been long considered to have a nongenetic cause. We discuss where the field of epilepsy genetics is moving as it enters a new era in which the genetic architecture of common epilepsies is starting to be unraveled.

Rare Genetic Variation and Outcome of Surgery for Mesial Temporal Lobe Epilepsy.

OBJECTIVE: Genetic factors have long been debated as a cause of failure of surgery for mesial temporal lobe epilepsy (MTLE). We investigated whether rare genetic variation influences seizure outcomes of MTLE surgery. METHODS: We performed an international, multicenter, whole exome sequencing study of patients who underwent surgery for drug-resistant, unilateral MTLE with normal magnetic resonance imaging (MRI) or MRI evidence of hippocampal sclerosis and ≥2-year postsurgical follow-up. Patients with either sustained seizure freedom (favorable outcome) or ongoing uncontrolled seizures since surgery (unfavorable outcome) were included. Exomes of controls without epilepsy were also included. Gene set burden analyses were carried out to identify genes with significant enrichment of rare deleterious variants in patients compared to controls. RESULTS: Nine centers from 3 continents contributed 206 patients operated for drug-resistant unilateral MTLE, of whom 196 (149 with favorable outcome and 47 with unfavorable outcome) were included after stringent quality control. Compared to 8,718 controls, MTLE cases carried a higher burden of ultrarare missense variants in constrained genes that are intolerant to loss-of-function (LoF) variants (odds ratio [OR] = 2.6, 95% confidence interval [CI] = 1.9-3.5, p = 1.3E-09) and in genes encoding voltage-gated cation channels (OR = 2.4, 95% CI = 1.4-3.8, p = 2.7E-04). Proportions of subjects with such variants were comparable between patients with favorable outcome and those with unfavorable outcome, with no significant between-group differences. INTERPRETATION: Rare variation contributes to the genetic architecture of MTLE, but does not appear to have a major role in failure of MTLE surgery. These findings can be incorporated into presurgical decision-making and counseling. ANN NEUROL 2022.

Seizure risk in multiple sclerosis patients treated with disease-modifying therapy: A systematic review and network meta-analysis.

BACKGROUND: Multiple sclerosis patients experience 3-6 times more seizures than the general population, but observations vary among studies. Seizure risk in disease-modifying therapy recipients remains unknown. OBJECTIVE: The objective of this study was to compare seizure risk in multiple sclerosis patients receiving disease-modifying therapy versus placebo. METHODS: MEDLINE(OVID), Embase, CINAHL, and ClinicalTrials.gov were searched from database inception until August 2021. Phase 2-3 randomized, placebo-controlled trials reporting efficacy and safety data for disease-modifying therapies were included. Network meta-analysis followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, using Bayesian random effects model for individual and pooled (by drug target) therapies. Main outcome was loge seizure risk ratios [95% credible intervals]. Sensitivity analysis included meta-analysis of non-zero-event studies. RESULTS: A total of 1993 citations and 331 full-texts were screened. Fifty-six included studies (29,388 patients-disease-modifying therapy = 18,909; placebo = 10,479) reported 60 seizures (therapy = 41; placebo = 19). No individual therapy was associated with altered seizure risk ratio. Exceptions were daclizumab (-17.90 [-65.31; -0.65]) and rituximab (-24.86 [-82.71; -1.37]) trending toward lower risk ratio; cladribine (25.78 [0.94; 4.65]) and pegylated interferon-beta-1a (25.40 [0.78; 85.47]) trended toward higher risk ratio. Observations had wide credible intervals. Sensitivity analysis of 16 non-zero-event studies revealed no difference in risk ratio for pooled therapies (l0.32 [-0.94; 0.29]). CONCLUSION: No evidence of association was found between disease-modifying therapy and seizure risk-this informs seizure management in multiple sclerosis patients.

Specific fetal malformations following intrauterine exposure to antiseizure medication.

OBJECTIVE: To investigate in the Australian Pregnancy Register of Antiepileptic Drugs patterns of fetal malformation associated with intrauterine exposure to particular currently available antiseizure medications taken by women with epilepsy. RESULTS: There was statistically significant evidence (P < 0.05) of an increased hazard of fetal malformation associated with exposure to valproate, carbamazepine, topiramate, zonisamide, and with conception after assisted fertilization, but a reduced hazard in the offspring of women who continued to smoke during pregnancy. Valproate exposure was associated with malformations in a wide range of organs and organ systems, carbamazepine and topiramate with hydronephrosis, topiramate also with hypospadias, zonisamide with spina bifida and assisted fertilization with heart and great vessel maldevelopment. CONCLUSIONS: Prenatal valproate exposure appears to interfere with the development of many if not all, fetal tissues. It seems likely that prenatal exposure to carbamazepine and topiramate, and possibly exposure to zonisamide, but also some process related to in vitro fertilization, may more selectively affect the normal development of particular fetal tissues or organs.

Changes over 24 years in a pregnancy register - Teratogenicity and epileptic seizure control.

OBJECTIVES: To trace (i) changes in Australian Pregnancy Register (APR) records concerning antiseizure medications (ASMs) prescribed for women with epilepsy (WWE) over the course of 24 years and correlate the changes with (ii) rates of occurrence of pregnancies involving foetal malformations, (iii) the body organs involved in the malformations, and (iv) freedom from epileptic seizures. RESULTS: Use of valproate and carbamazepine decreased progressively, use of lamotrigine remained relatively static, and the use of levetiracetam increased progressively, whereas the use of topiramate first increased and then fell again, associated with a temporary increase in malformation-associated pregnancy rate. More serious malformations, such as spina bifida, became less frequent, whereas more trivial ones tended to increase, whereas epileptic seizure freedom rates improved. CONCLUSIONS: The increasing use of newer ASMs in pregnant women has been associated with overall advantages in relation to the frequency and severity of foetal malformation and with advantages in relation to freedom from epileptic seizures.

Comorbidities in newly diagnosed epilepsy: Pre-existing health conditions are common and complex across age groups.

OBJECTIVES: People with epilepsy have a higher prevalence of medical and psychiatric comorbidities compared to the general population. Comorbidities are associated with poor epilepsy outcomes, and there have been recommendations for screening and early identification to improve clinical management. Data from 'First Seizure Clinics' (FSCs) with expert epileptological review can inform about disorders already present at the point of diagnosis of epilepsy or unprovoked seizures. Here, we aimed to describe pre-existing conditions with a focus on psychiatric, substance use, cardiac, neurological, and cancer health domains. METHODS: We included 1383 adults who received a new diagnosis of epilepsy or unprovoked seizures at Austin Hospital (AH) or Royal Melbourne Hospital (RMH) (Australia) FSCs from 2000 to 2010. Data were audited from FSC records, primarily detailed interviews undertaken by epileptologists. Logistic regression examined age distribution and other risk factors. RESULTS: The median age at FSC presentation was 37 years (IQR 26-53, range 18-94). Pre-existing conditions were reported by 40 %; from 32 % in the youngest group (18-30 years) to 53 % in the oldest (65+ years). Psychiatric (18 %) and substance use (16 %) disorders were most common, with higher prevalence among patients 18 to 65 years of age compared to those older than 65 years (p < 0.001). Cardiac, neurological, or cancer conditions were reported by 3-6 %, most often amongst those older than 65 years (p < 0.01). Eight percent (n = 112) reported disorders in >1 health domain. The commonest combination was a psychiatric condition with substance use disorder. Of the sixty-two patients reporting this combination, 61 were ≤65 years of age. CONCLUSIONS: Pre-existing health conditions are present in a substantial proportion of patients diagnosed with epilepsy or unprovoked seizures. Disorders are highest amongst elders, but one-third of younger adults also reported positive histories. These are predominantly psychiatric and/or substance use disorders, conditions strongly associated with poor outcomes in the general population. These findings inform post-diagnosis planning and management, as well as research examining post-diagnostic outcomes and associations between comorbidities and epilepsy.

EEG based automated seizure detection - A survey of medical professionals.

Diagnosing and managing seizures presents substantial challenges for clinicians caring for patients with epilepsy. Although machine learning (ML) has been proposed for automated seizure detection using EEG data, there is little evidence of these technologies being broadly adopted in clinical practice. Moreover, there is a noticeable lack of surveys investigating this topic from the perspective of medical practitioners, which limits the understanding of the obstacles for the development of effective automated seizure detection. Besides the issue of generalisability and replicability seen in a small amount of studies, obstacles to the adoption of automated seizure detection remain largely unknown. To understand the obstacles preventing the application of seizure detection tools in clinical practice, we conducted a survey targeting medical professionals involved in the management of epilepsy. Our study aimed to gather insights on various factors such as the clinical utility, professional sentiment, benchmark requirements, and perceived barriers associated with the use of automated seizure detection tools. Our key findings are: I) The minimum acceptable sensitivity reported by most of our respondents (80%) seems achievable based on studies reported from most currently available ML-based EEG seizure detection algorithms, but replication studies often fail to meet this minimum. II) Respondents are receptive to the adoption of ML seizure detection tools and willing to spend time in training. III) The top three barriers for usage of such tools in clinical practice are related to availability, lack of training, and the blackbox nature of ML algorithms. Based on our findings, we developed a guide that can serve as a basis for developing ML-based seizure detection tools that meet the requirements of medical professionals, and foster the integration of these tools into clinical practice.

Ocular motility as a measure of cerebral dysfunction in adults with focal epilepsy.

OBJECTIVE: Using objective oculomotor measures, we aimed to: (1) compare oculomotor performance in patients with drug-resistant focal epilepsy to healthy controls, and (2) investigate the differential impact of epileptogenic focus laterality and location on oculomotor performance. METHODS: We recruited 51 adults with drug-resistant focal epilepsy from the Comprehensive Epilepsy Programs of two tertiary hospitals and 31 healthy controls to perform prosaccade and antisaccade tasks. Oculomotor variables of interest were latency, visuospatial accuracy, and antisaccade error rate. Linear mixed models were performed to compare interactions between groups (epilepsy, control) and oculomotor tasks, and between epilepsy subgroups and oculomotor tasks for each oculomotor variable. RESULTS: Compared to healthy controls, patients with drug-resistant focal epilepsy exhibited longer antisaccade latencies (mean difference = 42.8 ms, P = 0.001), poorer spatial accuracy for both prosaccade (mean difference = 0.4°, P = 0.002), and antisaccade tasks (mean difference = 2.1°, P < 0.001), and more antisaccade errors (mean difference = 12.6%, P < 0.001). In the epilepsy subgroup analysis, left-hemispheric epilepsy patients exhibited longer antisaccade latencies compared to controls (mean difference = 52.2 ms, P = 0.003), while right-hemispheric epilepsy was the most spatially inaccurate compared to controls (mean difference = 2.5°, P = 0.003). The temporal lobe epilepsy subgroup displayed longer antisaccade latencies compared to controls (mean difference = 47.6 ms, P = 0.005). SIGNIFICANCE: Patients with drug-resistant focal epilepsy exhibit poor inhibitory control as evidenced by a high percentage of antisaccade errors, slower cognitive processing speed, and impaired visuospatial accuracy on oculomotor tasks. Patients with left-hemispheric epilepsy and temporal lobe epilepsy have markedly impaired processing speed. Overall, oculomotor tasks can be a useful tool to objectively quantify cerebral dysfunction in drug-resistant focal epilepsy.

Applications for Deep Learning in Epilepsy Genetic Research.

Epilepsy is a group of brain disorders characterised by an enduring predisposition to generate unprovoked seizures. Fuelled by advances in sequencing technologies and computational approaches, more than 900 genes have now been implicated in epilepsy. The development and optimisation of tools and methods for analysing the vast quantity of genomic data is a rapidly evolving area of research. Deep learning (DL) is a subset of machine learning (ML) that brings opportunity for novel investigative strategies that can be harnessed to gain new insights into the genomic risk of people with epilepsy. DL is being harnessed to address limitations in accuracy of long-read sequencing technologies, which improve on short-read methods. Tools that predict the functional consequence of genetic variation can represent breaking ground in addressing critical knowledge gaps, while methods that integrate independent but complimentary data enhance the predictive power of genetic data. We provide an overview of these DL tools and discuss how they may be applied to the analysis of genetic data for epilepsy research.

Interictal and seizure-onset EEG patterns in malformations of cortical development: A systematic review.

OBJECTIVES: Malformations of cortical development (MCDs) are common causes of drug-resistant epilepsy. The mechanisms underlying the associated epileptogenesis and ictogenesis remain poorly elucidated. EEG can help in understanding these mechanisms. We systematically reviewed studies reporting scalp or intracranial EEG features of MCDs to characterise interictal and seizure-onset EEG patterns across different MCD types. METHODS: We conducted a systematic review in accordance with PRISMA guidelines. MEDLINE, PubMed, and Cochrane databases were searched for studies describing interictal and seizure-onset EEG patterns in MCD patients. A classification framework was implemented to group EEG features into 20 predefined patterns, comprising nine interictal (five, scalp EEG; four, intracranial EEG) and 11 seizure-onset (five, scalp EEG; six, intracranial EEG) patterns. Logistic regression was used to estimate the odds ratios (OR) of each seizure-onset pattern being associated with specific MCD types. RESULTS: Our search yielded 1682 studies, of which 27 comprising 936 MCD patients were included. Of the nine interictal EEG patterns, five (three, scalp EEG; two, intracranial EEG) were detected in ≥2 MCD types, while four (rhythmic epileptiform discharges type 1 and type 2 on scalp EEG; repetitive bursting spikes and sporadic spikes on intracranial EEG) were seen only in focal cortical dysplasia (FCD). Of the 11 seizure-onset patterns, eight (three, scalp EEG; five, intracranial EEG) were found in ≥2 MCD types, whereas three were observed only in FCD (suppression on scalp EEG; delta brush on intracranial EEG) or tuberous sclerosis complex (TSC; focal fast wave on scalp EEG). Among scalp EEG seizure-onset patterns, paroxysmal fast activity (OR = 0.13; 95% CI: 0.03-0.53; p = 0.024) and repetitive epileptiform discharges (OR = 0.18; 95% CI: 0.05-0.61; p = 0.036) were less likely to occur in TSC than FCD. Among intracranial EEG seizure-onset patterns, low-voltage fast activity was more likely to be detected in heterotopia (OR = 19.3; 95% CI: 6.22-60.1; p < 0.001), polymicrogyria (OR = 6.70; 95% CI: 2.25-20.0; p = 0.004) and TSC (OR = 4.27; 95% CI: 1.88-9.70; p = 0.005) than FCD. SIGNIFICANCE: Different MCD types can share similar interictal or seizure-onset EEG patterns, reflecting common underlying biological mechanisms. However, selected EEG patterns appear to point to distinct MCD types, suggesting certain differences in their neuronal networks.

Genomic analysis of "microphenotypes" in epilepsy.

Large international consortia examining the genomic architecture of the epilepsies focus on large diagnostic subgroupings such as "all focal epilepsy" and "all genetic generalized epilepsy". In addition, phenotypic data are generally entered into these large discovery databases in a unidirectional manner at one point in time only. However, there are many smaller phenotypic subgroupings in epilepsy, many of which may have unique genomic risk factors. Such a subgrouping or "microphenotype" may be defined as an uncommon or rare phenotype that is well recognized by epileptologists and the epilepsy community, and which may or may not be formally recognized within the International League Against Epilepsy classification system. Here we examine the genetic structure of a number of such microphenotypes and report in particular on two interesting clinical phenotypes, Jeavons syndrome and pediatric status epilepticus. Although no single gene reached exome-wide statistical significance to be associated with any of the diagnostic categories, we observe enrichment of rare damaging variants in established epilepsy genes among Landau-Kleffner patients (GRIN2A) and pediatric status epilepticus patients (MECP2, SCN1A, SCN2A, SCN8A).

Progress report on new antiepileptic drugs: A summary of the Sixteenth Eilat Conference on New Antiepileptic Drugs and Devices (EILAT XVI): II. Drugs in more advanced clinical development.

The Sixteenth Eilat Conference on New Antiepileptic Drugs and Devices (EILAT XVI) was held in Madrid, Spain on May 22-25, 2022 and was attended by 157 delegates from 26 countries representing basic and clinical science, regulatory agencies, and pharmaceutical industries. One day of the conference was dedicated to sessions presenting and discussing investigational compounds under development for the treatment of seizures and epilepsy. The current progress report summarizes recent findings and current knowledge for seven of these compounds in more advanced clinical development for which either novel preclinical or patient data are available. These compounds include bumetanide and its derivatives, darigabat, ganaxolone, lorcaserin, soticlestat, STK-001, and XEN1101. Of these, ganaxolone was approved by the US Food and Drug Administration in March 2022 for the treatment of seizures associated with cyclin-dependent kinase-like 5 deficiency disorder in patients 2 years of age and older.

Progress report on new antiepileptic drugs: A summary of the Sixteenth Eilat Conference on New Antiepileptic Drugs and Devices (EILAT XVI): I. Drugs in preclinical and early clinical development.

The Eilat Conferences have provided a forum for discussion of novel treatments of epilepsy among basic and clinical scientists, clinicians, and representatives from regulatory agencies as well as from the pharmaceutical industry for 3 decades. Initially with a focus on pharmacological treatments, the Eilat Conferences now also include sessions dedicated to devices for treatment and monitoring. The Sixteenth Eilat Conference on New Antiepileptic Drugs and Devices (EILAT XVI) was held in Madrid, Spain, on May 22-25, 2022 and was attended by 157 delegates from 26 countries. As in previous Eilat Conferences, the core of EILAT XVI consisted of a sequence of sessions where compounds under development were presented and discussed. This progress report summarizes preclinical and, when available, phase 1 clinical data on five different investigational compounds in preclinical or early clinical development, namely GAO-3-02, GRT-X, NBI-921352 (formerly XEN901), OV329, and XEN496 (a pediatric granular formulation of retigabine/ezogabine). Overall, the data presented in this report illustrate novel strategies for developing antiseizure medications, including an interest in novel molecular targets, and a trend to pursue potential new treatments for rare and previously neglected severe epilepsy syndromes.

Clinical and EEG factors associated with antiseizure medication resistance in idiopathic generalized epilepsy.

OBJECTIVE: We sought to determine which combination of clinical and electroencephalography (EEG) characteristics differentiate between an antiseizure medication (ASM)-resistant vs ASM-responsive outcome for patients with idiopathic generalized epilepsy (IGE). METHODS: This was a case-control study of ASM-resistant cases and ASM-responsive controls with IGE treated at five epilepsy centers in the United States and Australia between 2002 and 2018. We recorded clinical characteristics and findings from the first available EEG study for each patient. We then compared characteristics of cases vs controls using multivariable logistic regression to develop a predictive model of ASM-resistant IGE. RESULTS: We identified 118 ASM-resistant cases and 114 ASM-responsive controls with IGE. First, we confirmed our recent finding that catamenial epilepsy is associated with ASM-resistant IGE (odds ratio [OR] 3.53, 95% confidence interval [CI] 1.32-10.41, for all study subjects) after covariate adjustment. Other independent factors seen with ASM resistance include certain seizure-type combinations (absence, myoclonic, and generalized tonic-clonic seizures [OR 7.06, 95% CI 2.55-20.96]; absence and generalized tonic-clonic seizures [OR 4.45, 95% CI 1.84-11.34]), as well as EEG markers of increased generalized spike-wave discharges (GSWs) in sleep (OR 3.43, 95% CI 1.12-11.36 for frequent and OR 7.21, 95% CI 1.50-54.07 for abundant discharges in sleep) and the presence of generalized polyspike trains (GPTs; OR 5.49, 95% CI 1.27-38.69). The discriminative ability of our final multivariable model, as measured by area under the receiver-operating characteristic curve, was 0.80. SIGNIFICANCE: Multiple clinical and EEG characteristics independently predict ASM resistance in IGE. To improve understanding of a patient's prognosis, clinicians could consider asking about specific seizure-type combinations and track whether they experience catamenial epilepsy. Obtaining prolonged EEG studies to record the burden of GSWs in sleep and assessing for the presence of GPTs may provide additional predictive value.