Epilepsia最新文献

The early onset epilepsies encompass a heterogeneous group of disorders, some of which result in drug-resistant seizures, developmental delay, psychiatric comorbidities, and sudden death. Advancement in the widespread use of targeted gene panels as well as genome and exome sequencing has facilitated the identification of different causative genes in a subset of these patients. The ability to recognize the genetic basis of early onset epilepsies continues to improve, with de novo coding variants accounting for most of the genetic etiologies identified. Although current disease-specific and disease-modifying therapies remain limited, novel precision medicine approaches, such as small molecules, cell therapy, and other forms of genetic therapies for early onset epilepsies, have created excitement among researchers, clinicians, and caregivers. Here, we summarize the main findings of presentations and discussions on novel therapeutic strategies for targeted treatment of early onset epilepsies that occurred during the Workshop on Neurobiology of Epilepsy (WONOEP XVI, Talloires, France, July 2022). The presentations discussed the use of chloride transporter inhibitors for neonatal seizures, targeting orexinergic signaling for childhood absence epilepsy, targeting energy metabolism in Dravet syndrome, and the role of cannabinoid receptor type 2, reversible acetylcholinesterase inhibitors, cell therapies, and RNA-based therapies in early life epilepsies.

Objective: An accurate evaluation of behavioral responsiveness during and after seizures in people with epilepsy is critical for diagnosis and management. Current methods for assessing behavioral responsiveness are characterized by substantial variation, subjectivity, and limited reliability and reproducibility in ambulatory and epilepsy monitoring unit settings. In this study, we aimed to develop and implement a novel mobile platform for deployment of automated responsiveness testing in epilepsy-the ARTiE Watch-to facilitate standardized, objective assessments of behavioral responsiveness during and after seizures.

Methods: We prospectively recruited patients admitted to the epilepsy monitoring units for diagnostic evaluation and long-term video-electroencephalographic monitoring at Mayo Clinic and Yale New Haven Hospital. Participants wore the ARTiE Watch, a smartwatch paired with custom smartphone software integrated with cloud infrastructure allowing for remote activation of standardized assessment on the participants' smartwatches. The assessment consisted of 18 command prompts that test behavioral responsiveness across motor, language, and memory domains. Upon visually identifying an electrographic seizure during EMU monitoring, the BrainRISE platform was used to deploy the ARTiE Watch behavioral testing sequence. Responsiveness scoring was conducted on smartwatch files.

Results: Eighteen of 56 participants had a total of 39 electrographic seizures assessed with the ARTiE Watch. The 18 subjects with ARTiE Watch-tested seizures had a total of 67 baseline (interictal) ARTiE Watch tests collected for analysis. The analysis showed distinct ARTiE Watch behavioral responsiveness phenotypes: (1) decreased responsiveness across all ARTiE Watch commands during seizure (ictal-postictal) periods compared (to baseline (p < .0001), (2) decreased responsiveness in bilateral tonic-clonic seizures compared to baseline (p < .0001) and compared to focal seizures (p < .0001), and (3) decreased responsiveness during focal impaired awareness seizures compared to baseline (p < .0001) and compared to focal aware seizures (p < .001).

Significance: ARTiE Watch behavioral testing deployed utilizing a mobile cloud-based platform is feasible and can provide standardized, objective behavioral responsiveness assessments during seizures.

Objectives: Late-onset epilepsy has the highest incidence among all age groups affected by epilepsy and often occurs in the absence of known clinical risk factors such as stroke and dementia. There is increasing evidence that brain changes contributing to epileptogenesis likely start years before disease onset, and we aim to relate cognitive and imaging correlates of subclinical brain injury to incident late-onset epilepsy in a large, community-based cohort.

Methods: We studied Offspring Cohort of the Framingham Heart Study participants 45 years or older, who were free of prevalent stroke, dementia, or epilepsy, and had neuropsychological (NP) evaluation and brain magnetic resonance imaging (MRI). Cognitive measures included Visual Reproduction Delayed Recall, Logical Memory Delayed Recall, Similarities, Trail Making Test B minus A (TrTB-TrTA; attention and executive function), and a global measure of cognition derived from principal component analysis. MRI measures included total cerebral brain volume, cortical gray matter volume (CGMV), white matter hyperintensity volume (WMHV), and hippocampal volume. Incident epilepsy was identified through a review of administrative data and medical records. Cox proportional hazards regression models were used for the analyses. All analyses were adjusted for age, sex, and educational level (cognition only).

Results: Among participants who underwent NP testing (n = 2349, 45.81% male), 31 incident epilepsy cases were identified during follow-up. Better performance on the TrTB-TrTA was associated with a lower risk of developing epilepsy (hazard ratio [HR] .25, 95% confidence interval [CI] .08-.73; p = .011). In the subgroup of participants with MRI (n = 2056, 46.01% male), 27 developed epilepsy. Higher WMHV was associated with higher epilepsy risk (HR 1.5, 95%CI 1.01-2.20; p = .042), but higher CGMV (HR .73, 95% CI .57-.93; p = .001) was associated with lower incidence of epilepsy.

Significance: Better performance on the (TrTB-TrTA), a measure of executive function and attention, and higher cortical volumes are associated with lower risk of developing epilepsy. Conversely, higher WMHV, a measure of occult vascular injury, increases the risk. Our study shows that non-invasive tests performed in mid-life may help identify people at risk for developing epilepsy later in life.

Objective: This study was undertaken to study whether high-dose folic acid (>1 mg daily) use is associated with an increased risk of cancer in all women who have given birth and in women with epilepsy. High-dose folic acid supplementation during pregnancy has been linked to increased cancer risk in children born to mothers with epilepsy.

Methods: We identified women with their first pregnancy in Denmark (1997-2017), Norway (2005-2017), and Sweden (2006-2017) using medical birth registers, linking individual data across nationwide health registers and statistical agencies. Exposure was defined as filled prescriptions for high-dose folic acid, considered time-varyingly. The primary outcome was the first malignant cancer diagnosis. Hazard ratios (HRs) of cancer after high-dose folic acid exposure were estimated using Cox proportional hazard models with 95% confidence intervals (CIs), adjusted for confounders including antiseizure medication (ASM) use, and stratified by maternal epilepsy diagnosis. A 6-month time lag was applied, as cancer is unlikely to develop immediately.

Results: With up to 21 years of follow-up, we identified 1 465 785 women who gave birth, including 64 485 (4.4%) exposed to high-dose folic acid. In the exposed group, 755 cancer cases were observed (208 per 100 000 person-years, 95% CI = 193.8-223.5), compared with 18 702 cases in the unexposed group (164 per 100 000 person-years, 95% CI = 161.5-166.2), yielding a 20% increased cancer risk overall (adjusted HR = 1.2, 95% CI = 1.1-1.2). This risk was attenuated after the 6-month lag analysis (adjusted HR = 1.1, 95% CI = 1.04-1.2). The risk for non-Hodgkin lymphoma was increased in all analyses (n = 28, adjusted HR = 2.0, 95% CI = 1.3-2.9). The association between high-dose folic acid use and overall cancer risk was similar in those with epilepsy regardless of ASM use (adjusted HR = 1.3, 95% CI = 1.0-1.8).

Significance: High-dose folic acid use was associated with increased overall cancer risk in women who have given birth, with a consistent association with non-Hodgkin lymphoma, including those with epilepsy, regardless of ASM use.

This report is the first comprehensive update on the activities of existing epilepsy-pregnancy registries since 2010. The primary aim of these registries, which were initiated by independent international research groups some 25 years ago, has been to assess the risk of major congenital malformations (MCMs) in offspring exposed in utero to different antiseizure medications (ASMs). Progress reports are provided here from the five original registries (the International Registry of Antiepileptic Drugs and Pregnancy EURAP, the North American Antiepileptic Drug Pregnancy Registry, the UK and Ireland Epilepsy and Pregnancy Register, the Kerala Registry of Epilepsy and Pregnancy, and the Raoul Wallenberg Australian Pregnancy Register of Antiepileptic Drugs) plus the more recently initiated West China Registry. Since their inception, the registries have published a wealth of data revealing important differences in risks across the most frequently used ASM treatments, thereby facilitating rational management of women with epilepsy who are of childbearing potential. Although the number of pregnancies enrolled in the different registries has more than doubled since the 2010 report, many questions remain. These include outcomes following prenatal exposure to most of the newer ASMs or different ASM combinations, as well as associations with specific MCMs rather than MCMs as a collective. All the registries, therefore, remain active and continue to enroll pregnancies. Administrative health care databases have been utilized more recently for the assessment of MCM risks and other adverse pregnancy outcomes associated with in utero exposure to ASMs. Although these can provide population-based complementary information, they cannot replace the specific epilepsy-pregnancy registries with their more detailed validated individual information. Given the multiple newer ASMs that are increasingly used and the continuing multiple knowledge gaps for the older ASMs, epilepsy-pregnancy registries will continue to play an important role in the future.

Objective: Deep learning methods have shown potential in automating the detection of interictal epileptiform discharges (IEDs) in electroencephalography (EEG). We compared IED detection using our previously trained deep neural network with a group of experts to assess its potential applicability.

Methods: First, we performed clinical validation on an internal data set. Seven experts reviewed all EEG studies. Performance agreement between experts and the network was compared at both the EEG and IED levels. All EEG recordings were also processed with Persyst. Subsequently, we performed external validation, with data from four centers, using a hybrid approach, where detections by the deep neural network were reviewed by an expert. In case of disagreement with the original report, the EEG recording was annotated independently by five experts.

Results: For internal validation we included 22 EEG studies with IEDs and 28 EEG studies from controls. At the EEG level, our network showed performance similar to that of the experts. For individual IED detection, the sensitivities between experts ranged from 20.7%-86.4%, whereas the sensitivity of our network was 82.5% (confidence interval [CI]: 77.7%-87.4%) at 99% specificity and a false detection rate (FDR) of <.2/min, outperforming Persyst, with 64.6% sensitivity (CI: 61.4%-67.9%) at 98% specificity. External validation in 174 EEG studies demonstrated that all 85 EEG recordings classified as normal in the original report were classified correctly, with an FDR of .10/min. Of the 89 EEG studies with IEDs according to the report, 56 were correctly classified (Cohen's κ = .62). Visual analysis of the remaining 33 EEG recordings showed high interobserver variability among the five experts (Fleiss' κ = .13).

Significance: Our deep neural network detects IEDs on par with clinical experts. The external validation in a hybrid approach showed substantial agreement with the original report. Disagreement was due mainly to high interobserver variability. Our deep neural network may support visual EEG analysis and assist in diagnostics, particularly when human resources are limited.

This review systematically analyzes potential biomarker candidates for post-traumatic epilepsy (PTE) in humans who have experienced moderate to severe traumatic brain injury (TBI). Focusing on biomarkers across biofluid-based protein, genetic, neuroimaging, and neurophysiological categories, this review distinguishes between TBI patients who develop PTE and those who do not. The review adheres to established methodologies outlined in the Cochrane Handbook for Systematic Reviews of Interventions. Data presentation follows the Meta-analyses of Observational Studies (MOOSE) and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Medline, Embase, and Web of Science were systematically searched and yielded 7538 records, of which 18 met inclusion criteria (moderate-severe TBI in humans, follow-up of at least 6 months, and no prior history of epilepsy). The review aggregates data from 15 cohort and 3 case-control studies (risk of bias was assessed using the Newcastle-Ottawa Scale). Statistically significant biomarkers were identified, with neurophysiological biomarkers showing the strongest effect size in a two-study meta-analysis. PTE, a severe long-term outcome of TBI affecting 2% to 53% of individuals with TBI, lacks validated biomarkers for forecasting development, crucial for designing preventive clinical trials. A multimodal approach, integrating biofluid-based protein, genetic, neuroimaging, and neurophysiological data, offers a promising strategy to enhance the predictability of PTE development and, potentially, its treatment. The study's protocol is registered in the International Prospective Register of Systematic Reviews PROSPERO (Registration ID: CRD42023470245).

Objective: The cannabinoid cannabidiol has established antiseizure effects in drug-resistant epilepsies such as Dravet syndrome and Lennox-Gastaut syndrome. Amorfrutin 2, honokiol, and magnolol are structurally similar to cannabinoids (cannabis-like drugs) but derive from non-cannabis plants. We aimed to study the antiseizure potential of these compounds in various mouse seizure models. In addition, we aimed to characterize their molecular pharmacology at cannabinoid CB₁ and CB₂ receptors and at T-type calcium channels, which are known targets of the cannabinoids.

Methods: Brain and plasma pharmacokinetic profiles were determined. Antiseizure activity was assessed against hyperthermia-induced seizures in a Scn1a^+/- mouse model of Dravet syndrome. We then elaborated on the most promising compounds in the maximal electroshock (MES) test in mice and the Gabrb3^+/D120N mouse model of Lennox-Gastaut syndrome. Fluorescence-based assays were used to examine modulatory activity at cannabinoid CB₁ and CB₂ receptors and T-type calcium channel subtypes Ca_V3.1, Ca_V3.2, and Ca_V3.3 overexpressed in mammalian cells. Automated patch-clamp electrophysiology was then used to confirm inhibitory activity on Ca_V3.1, Ca_V3.2, and Ca_V3.3 channels.

Results: Magnolol and honokiol had high brain-to-plasma ratios (3.55 and 7.56, respectively), unlike amorfrutin 2 (0.06). Amorfrutin 2 and magnolol but not honokiol significantly increased the body temperature threshold at which Scn1a^+/- mice had a generalized tonic-clonic seizure. Both amorfrutin 2 and magnolol significantly decreased the proportion of mice exhibiting hindlimb extension in the MES test. Furthermore, magnolol reduced the number and duration of atypical absence seizures in Gabrb3^+/D120N mice. The three compounds inhibited all T-type calcium channel subtypes but were without specific activity at cannabinoid receptors.

Significance: We show for the first time that amorfrutin 2 and magnolol display novel antiseizure activity in mouse drug-resistant epilepsy models. Our results justify future drug discovery campaigns around these structural scaffolds that aim to develop novel antiseizure drugs for intractable epilepsies.

Objective: This study was undertaken to determine whether admission to dedicated seizure monitoring units (SMUs) result in reduced health care use (HCU).

Methods: This was a retrospective open cohort study covering the years 2010-2018 of patients residing in Alberta, Canada, who were referred to the Calgary Comprehensive Epilepsy Program and admitted to a level 4 SMU. Patients were required to have ≥3 years pre- and postadmission follow-up. The outcome was the change in trajectory of composite HCU (primary care, specialist outpatient visits, emergency department visits, and hospitalizations) for the 3 years prior to and 3 years following SMU admission using the point of admission as the "index date." Secondary outcomes were HCU limited to specific settings. We excluded the first 30 days following the point of admission to mitigate the confounding admission would have on the postadmission HCU trajectory. We used adjusted restricted maximum likelihood linear and nonlinear effects models to determine trajectories expressed as Canadian dollars.

Results: A total of 315 of 600 (53%) patients met eligibility criteria. Mean age was 40 years (SD = 17.4), 176 (56%) were female, 220 (70%) had focal epilepsy, and 60 (19%) had functional seizures or physiologic seizure mimics without epilepsy as adjudicated by the attending physician at the point of discharge. Mean per person health care costs increased by CAD$341.28 (95% confidence interval [CI] = -25.17 to 707.74) for each successive 6-month interval prior to SMU admission (p = .07). Following admission, mean per person costs decreased by CAD$802.34 (95% CI = 699.62-905.06, p < .001) for each successive 6-month interval up to 3 years postdischarge. Similar trends were noted for primary and specialist care, emergency department, admitted care, and when nonlinear models were applied.

Significance: Admission to an SMU is associated with significant and enduring declines in HCU. Each 6-months following discharge overall HCU declined by a mean of CAD$802.34 and acute inpatient, emergency department, and outpatient physician interactions declined by 25%, 26%, and 18% respectively. Comprehensive epilepsy care not only reduces morbidity and mortality but also reduces cost.