Epilepsia最新文献

Objective: Epilepsy involves significant changes in neural cells during epileptogenesis. Although the molecular mechanism of epileptogenesis remains obscure, changes in gene regulation play a crucial role in the evolution of epilepsy. This study aimed to compare changes in a subset of specific genes during epilepsy development, focusing on the period after the first spontaneous seizure, to identify critical time windows for targeting different regulators.

Methods: Using a rat model of acquired focal neocortical epilepsy induced by tetanus toxin, we characterized gene expression at acute, subacute, and chronic stages (48-72 h, 2 weeks, and 30 days after first spontaneous seizure, respectively), focusing on genes' potential contribution to epilepsy progression.

Results: We observed dynamic changes in the expression of these genes throughout the period after the first spontaneous seizure. Astrocytic reactions primarily occur early, before epilepsy is well established. Changes in Mtor (mammalian target of rapamycin) and Rest (repressor element 1 silencing transcription factor) signaling pathways are highly dynamic and correlated with the progression of epilepsy development. Ccl2 (chemokine C-C-motif ligand) is upregulated at the chronic stage, indicating activation of the neuroinflammatory pathway. Finally, Gabra5 (γ-aminobutyric acidergic signaling) is downregulated at the late stage after epilepsy is established. Surprisingly, changes in the expression of specific genes are linked to the time since the first seizure, rather than seizure frequency or duration.

Significance: These results suggest that the regulation of specific genes is essentially stage-dependent during the development of epilepsy, highlighting the importance of targeting specific genes at appropriate stages of epilepsy development.

Objective: Complex epilepsies such as epileptic and developmental encephalopathies require multidisciplinary care throughout life. A coordinated transition program is therefore essential to provide optimal support for patients leaving pediatric for adult care. The aim of this study is to describe and evaluate our transition program for complex epilepsies, focusing on the last step in this program, that is, the multidisciplinary transition day hospital (MTDH).

Methods: We performed a retrospective observational study including patients with complex epilepsies who underwent the full steps of the transition program at Necker-Enfants Malades Hospital between May 2021 and June 2023, with a follow-up until February 2024. We described the cohort and detailed the interventions performed during the MTDH including medical, medicosocial, educational, daily life abilities, and laboratory and imaging assessments with the participation of one member of the adult team. We evaluated two indicators of our program: (1) the "adult first clinic attendance rate," defined by the percentage of patients attending their first adult clinic; and (2) the "return rate," defined by the percentage of patients who requested a pediatric encounter after their transfer.

Results: Our cohort included 70 patients with a mean age of 19.1 years (interquartile range = 16.3-19.5). Eighty percent had an epilepsy syndrome diagnosis; 72.8% were treated with three or more antiseizure medications. All patients had their appointment at the adult clinic within 6 months of the day hospital, and only two families requested a pediatric encounter after the transfer.

Significance: The transition program is key for an optimal transfer of patients with complex epilepsies to adult care. It requires a comprehensive multidisciplinary approach and provides a complete summary of the medical record. Our program secures a smooth landing in adult care and is a promising model to better manage the challenging transition process, especially in patients with complex epilepsy.

Objective: Behavioral problems in children with new onset epilepsies have been well established in the literature. More recently, the literature indicates the presence of unique behavioral patterns or phenotypes in youth with epilepsy that vary significantly in vulnerability and resilience to behavioral problems. This study contrasts the interpretation of behavioral risk as inferred from cross-sectional versus latent group analytic perspectives, as well as the presence, consistency, stability, and progression of behavioral phenotypes in youth with new onset epilepsy and sibling controls over 3 years.

Methods: Three hundred twelve participants (6-16 years old) were recruited within 6 weeks of their first recognized seizure along with 223 unaffected siblings. Each child's behavior was recorded by parents and teachers frequently over 36 months using the Child Behavior Checklist (CBCL), and each child completed self-report measures of depression symptoms over 36 months. Measures were evaluated cross-sectionally and longitudinally to identify clusters with prototypical behavioral trajectories.

Results: Cross-sectional analyses exhibited a pattern of generalized and undifferentiated behavioral problems compared to sibling controls at baseline and prospectively. In contrast, latent trajectory modeling identified three distinct behavior phenotype clusters across all raters (parents, teachers, and youth) over baseline and longitudinal assessments. CBCL Cluster 1 (~30% of youth with epilepsy) exhibited behavior similar to/better than controls, Cluster 2 (~50%) exhibited moderate behavior issues, and Cluster 3 (~20%) exhibited the most pronounced/problematic behavior, falling into Achenbach's clinically relevant behavior range. Behavior within clusters remained stable and consistent. Teachers' and children's behavior assessments corresponded to these cluster groupings consistently over 36 months. Predictors of cluster membership include seizure syndrome type and social determinants of health.

Significance: This study demonstrates the varying public health perspectives of behavioral risk in youth with epilepsy that result as a function of analytic approach as well as the presence of distinct latent behavioral trajectory phenotypes over time in youth with new onset epilepsy.

Objective: Epilepsy is one of the most prevalent brain diseases. Approximately one third of patients consistently experience drug-resistant epilepsy (DRE), a condition where seizures persist despite the use of antiseizure medications. Exploration of new therapies for DRE is urgently needed. In this single-center, randomized, sham-controlled, crossover clinical trial (NCT05042726), we aimed to investigate the effectiveness and safety of transcranial magnetic continuous theta burst stimulation (cTBS) targeting the cerebellum to treat DRE.

Methods: Patients with DRE for ≥2 years and a seizure frequency of ≥2 seizures per month were enrolled and randomized 1:1 to receive active stimulation followed by sham stimulation or vice versa. The bilateral cerebellum was targeted by navigated cTBS focusing on the cerebellar dentate nucleus, once daily on workdays for 2 weeks. The primary outcomes were the percentage of seizure reduction and 50% responder rate in the per-protocol population within 2 months after treatment.

Results: Forty-four patients were enrolled and randomized; 18 patients in the active stimulation-first group and 20 in the sham stimulation-first group were included in the final analysis. Active cTBS significantly reduced seizures compared to sham stimulation (difference in percentage of seizure reduction between treatments = 25%, 95% confidence interval [CI] = 5%-46%, p = .018). The 50% responder rate after active stimulation was significantly higher than that after sham stimulation (difference in 50% responder rate between treatments = 24%, 95% CI = 11%-40%, p = .029). Adverse events occasionally occurred during active stimulation (moderate headache in 5% of patients, tinnitus in 3% of patients, dizziness in 3% of patients) but resolved spontaneously within days after treatment completion.

Significance: This trial suggested that cTBS targeting the cerebellum was effective and well tolerated in the treatment of DRE. Further studies are warranted to confirm its effectiveness and mechanism.

This study evaluated food preferences and eating behaviors of individuals with Dravet syndrome. Patients diagnosed with Dravet syndrome were recruited, as well as a control group composed of siblings of patients with epilepsy (any form). The Food Preference Questionnaire and the Child Eating Behavior Questionnaire were completed by caregivers along with two open-ended questions regarding eating challenges. Seventy-eight participants (45 with Dravet syndrome and 33 controls) were included. Compared to controls, mean scores for food preference were lower for fruits (p = .000099), meats and fish (p = .00094), and snacks (p = .000027) in Dravet syndrome. People with Dravet syndrome also had less emotional overeating (p = .0085) and food enjoyment (p = .0012), but more slowness in eating (p = .00021) and food fussiness (p = .0064). In a subgroup analysis of only pediatric (age <18 years) patients, similar results were observed for both food preferences and eating habits. In qualitative data, caregivers most commonly reported difficulties with fixation on specific foods. This study demonstrates specific food preferences and challenging eating behaviors in individuals with Dravet syndrome. These data provide potential avenues for nutritional interventions and behavioral therapies to increase the quality of life of patients and their families.

Objective: Blood-brain barrier dysfunction (BBBD) has been linked to various neurological disorders, including epilepsy. This study aims to utilize dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to identify and compare brain regions with BBBD in patients with epilepsy (PWE) and healthy individuals.

Methods: We scanned 50 drug-resistant epilepsy (DRE) patients and 58 control participants from four global specialized epilepsy centers using DCE-MRI. The presence and extent of BBBD were analyzed and compared between PWE and healthy controls.

Results: Both greater brain volume and higher number of brain regions with BBBD were significantly present in PWE compared to healthy controls (p < 10^-7). No differences in total brain volume with BBBD were observed in patients diagnosed with either focal seizures or generalized epilepsy, despite variations in the affected regions. Overall brain volume with BBBD did not differ in PWE with MRI-visible lesions compared with non-lesional cases. BBBD was observed in brain regions suspected to be related to the onset of seizures in 82% of patients (n = 39) and was typically identified in, adjacent to, and/or in the same hemisphere as the suspected epileptogenic lesion (n = 10).

Significance: These findings are consistent with pre-clinical studies that highlight the role of BBBD in the development of DRE and identify microvascular stabilization as a potential therapeutic strategy.

Objective: This study was undertaken to analyze the histology underlying increased T2 signal intensity (iT2SI) in anterior temporal lobe white matter (aTLWM) epilepsy due to hippocampal sclerosis (TLE/HS).

Methods: Twenty-three patients were included: 16 with increased T2 signal in the aTLWM and seven with HS only. Magnetic resonance imaging (MRI) findings were consistent across two neuroradiologists (kappa = .89, p < .001). Quantification of neuronal cells, astrocytes, oligodendrocytes, and vacuolization in the white matter of temporal lobe specimens was performed by immunohistochemistry (neuronal nuclear antigen, glial fibrillary acidic protein, oligodendrocyte transcription factor, and basic myelin protein, respectively). Surgical specimens from TLE/HS patients with and without iT2SI in the aTLWM were compared. Samples of aTLWM were divided into three groups, according to MRI features: G1 = samples of iT2SI, G2 = samples with normal T2 signal intensity from patients without white matter imaging abnormalities, and G3 = samples with normal T2 signal intensity adjacent to areas with iT2SI.

Results: Patients with increased T2 signal had a significantly younger age at epilepsy onset (p < .035). Histological analysis revealed a higher percentage of vacuolar area in these patients (p < .004) along with a lower number of ectopic neurons (p = .042). No significant differences were found in astrocyte or oligodendrocyte counts among groups.

Significance: A higher proportion of vacuoles in regions with iT2SI may be the histopathologic substrate of this signal alteration in the white matter of the temporal lobe in patients with TLE/HS. This method of quantifying vacuoles using digital image analysis proved reliable and cost-effective.

Objective: Anterior temporal lobe resection (ATLR) is an effective treatment for drug-resistant temporal lobe epilepsy (TLE), although language deficits may occur after both left and right ATLR. Functional reorganization of the language network has been observed in the ipsilateral and contralateral hemispheres within 12 months after ATLR, but little is known of longer-term plasticity effects. Our aim was to examine the plasticity of language functions up to a decade after ATLR, in relation to cognitive profiles.

Methods: We examined 24 TLE patients (12 left [LTLE]) and 10 controls across four time points: pre-surgery, 4 months, 12 months, and ~9 years post-ATLR. Participants underwent standard neuropsychological assessments (naming, phonemic, and categorical fluency tests) and a verbal fluency functional magnetic resonance imaging (fMRI) task. Using a flexible factorial design, we analyzed longitudinal fMRI activations from 12 months to ~9 years post-ATLR, relative to controls, with separate analyses for people with hippocampal sclerosis (HS). Change in cognitive profiles was correlated with the long-term change in fMRI activations to determine the "efficiency" of reorganized networks.

Results: LTLE patients had increased long-term engagement of the left extra-temporal and contralateral temporal regions, with better language performance linked to bilateral activation. Those with HS exhibited more widespread bilateral activations. RTLE patients showed plasticity in the left extra-temporal regions, with better language outcomes associated with these areas. Both groups of patients achieved cognitive stability over 9 years, with more than 50% of LTLE patients improving. Older age, longer epilepsy duration, and lower pre-operative cognitive reserve negatively affected long-term language performance.

Significance: Neuroplasticity continues for up to ~9 years post-epilepsy surgery in LTLE and RTLE, with effective language recovery linked to bilateral engagement of temporal and extra-temporal regions. This adaptive reorganization is associated with improved cognitive outcomes, challenging the traditional view of localized surgery effects. These findings emphasize the need for early intervention, tailored pre-operative counseling, and the potential for continued cognitive gains with extended post-ATLR rehabilitation.

Objective: This study was undertaken to develop a machine learning (ML) model to forecast initial seizure onset in neonatal hypoxic-ischemic encephalopathy (HIE) utilizing clinical and quantitative electroencephalogram (QEEG) features.

Methods: We developed a gradient boosting ML model (Neo-GB) that utilizes clinical features and QEEG to forecast time-dependent seizure risk. Clinical variables included cord blood gas values, Apgar scores, gestational age at birth, postmenstrual age (PMA), postnatal age, and birth weight. QEEG features included statistical moments, spectral power, and recurrence quantification analysis (RQA) features. We trained and evaluated Neo-GB on a University of California, San Francisco (UCSF) neonatal HIE dataset, augmenting training with publicly available neonatal electroencephalogram (EEG) datasets from Cork University and Helsinki University Hospitals. We assessed the performance of Neo-GB at providing dynamic and static forecasts with diagnostic performance metrics and incident/dynamic area under the receiver operating characteristic curve (iAUC) analyses. Model explanations were performed to assess contributions of QEEG features and channels to model predictions.

Results: The UCSF dataset included 60 neonates with HIE (30 with seizures). In subject-level static forecasting at 30 min after EEG initiation, baseline Neo-GB without time-dependent features had an area under the receiver operating characteristic curve (AUROC) of .76 and Neo-GB with time-dependent features had an AUROC of .89. In time-dependent evaluation of the initial seizure onset within a 24-h seizure occurrence period, dynamic forecast with Neo-GB demonstrated median iAUC = .79 (interquartile range [IQR] .75-.82) and concordance index (C-index) = .82, whereas baseline static forecast at 30 min demonstrated median iAUC = .75 (IQR .72-.76) and C-index = .69. Model explanation analysis revealed that spectral power, PMA, RQA, and cord blood gas values made the strongest contributions in driving Neo-GB predictions. Within the most influential EEG channels, as the preictal period advanced toward eventual seizure, there was an upward trend in broadband spectral power.

Significance: This study demonstrates an ML model that combines QEEG with clinical features to forecast time-dependent risk of initial seizure onset in neonatal HIE. Spectral power evolution is an early EEG marker of seizure risk in neonatal HIE.

Objective: To investigate phenotypes of comorbidity before and after an epilepsy diagnosis in a national cohort of post-9/11 Service Members and Veterans and explore phenotypic associations with mortality.

Methods: Among a longitudinal cohort of Service Members and Veterans receiving care in the Veterans Health Administration (VHA) from 2002 to 2018, annual diagnoses for 26 conditions associated with epilepsy were collected over 5 years, ranging from 2 years prior to 2 years after the year of first epilepsy diagnosis. Latent class analysis (LCA) was used to identify probabilistic comorbidity phenotypes with distinct health trajectories. Descriptive statistics were used to describe the characteristics of each phenotype. Fine and Gray cause-specific survival models were used to measure mortality outcomes for each phenotype up to 2021.

Results: Six distinct phenotypes were identified: (1) relatively healthy, (2) post-traumatic stress disorder, (3) anxiety and depression, (4) chronic disease, (5) bipolar/substance use disorder, and (6) polytrauma. Accidents were the most common cause of death overall, followed by suicide/mental health and cancer, respectively. Each phenotype exhibited unique associations with mortality and cause of death, highlighting the differential impact of comorbidity patterns on patient outcomes.

Significance: By delineating clinically meaningful epilepsy comorbidity phenotypes, this study offers a framework for clinicians to tailor interventions. Moreover, these data support systems of care that facilitate treatment of epilepsy and comorbidities within an interdisciplinary health team that allows continuity of care. Targeting treatment toward patients with epilepsy who present with specific heightened risks could help mitigate adverse outcomes and enhance overall patient care.