Faculty Bibliography

AIMS/OBJECTIVE:Hippocampal findings are implicated in the pathogenesis of sudden unexplained death in childhood (SUDC), although some studies have identified similar findings in sudden explained death in childhood (SEDC) cases. We blindly reviewed hippocampal histology in SUDC and SEDC controls. METHODS:Hippocampal H&E slides (n=67; 36 SUDC, 31 controls) from clinical and forensic collaborators were evaluated by 9 blinded reviewers: 3 board-certified forensic pathologists, 3 neuropathologists, and 3 dual-certified neuropathologist/forensic pathologists. RESULTS:Among nine reviewers, about 50% of hippocampal sections were rated as abnormal (SUDC 52.5%, controls 53.0%), with no difference by cause of death (COD) (p=0.16) or febrile seizure history (p=0.90). There was little agreement among nine reviewers on whether a slide was within normal range (Fleiss' kappa=0.014, p=0.47). Within reviewer groups, there were no findings more frequent in SUDC compared to controls, with variability in pyramidal neuron and dentate gyrus findings. Across reviewer groups, there was concordance for bilamination and granule cell loss. Neither SUDC (51.2%) nor control (55.9%) slides were considered contributory to determining COD (p=0.41). CONCLUSIONS:The lack of an association of hippocampal findings in SUDC and controls, as well as inconsistency of observations by multiple blinded reviewers, indicates discrepancy with previous studies and an inability to reliably identify hippocampal malformation associated with sudden death (HMASD). These findings underscore a need for larger studies to standardize evaluation of hippocampal findings, identify the range of normal variation and, changes unrelated to SUDC or febrile seizures. Molecular studies may help identify novel immunohistological markers that inform on COD.

Reconstructing intended speech from neural activity using brain-computer interfaces holds great promises for people with severe speech production deficits. While decoding overt speech has progressed, decoding imagined speech has met limited success, mainly because the associated neural signals are weak and variable compared to overt speech, hence difficult to decode by learning algorithms. We obtained three electrocorticography datasets from 13 patients, with electrodes implanted for epilepsy evaluation, who performed overt and imagined speech production tasks. Based on recent theories of speech neural processing, we extracted consistent and specific neural features usable for future brain computer interfaces, and assessed their performance to discriminate speech items in articulatory, phonetic, and vocalic representation spaces. While high-frequency activity provided the best signal for overt speech, both low- and higher-frequency power and local cross-frequency contributed to imagined speech decoding, in particular in phonetic and vocalic, i.e. perceptual, spaces. These findings show that low-frequency power and cross-frequency dynamics contain key information for imagined speech decoding.

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).

OBJECTIVE:Stroke is the most common cause of epilepsy in older age. Subclinical cerebrovascular disease is believed to underlie some of the 30%-50% of late-onset epilepsy without a known cause (Li et al. Epilepsia. 1997;38:1216; Cleary et al. Lancet. 2004;363:1184). We studied the role of modifiable vascular risk factors in predicting subsequent epilepsy among participants ages 45 or older in the Framingham Heart Study (FHS), a longitudinal, community-based study. METHODS:Participants of the Offspring Cohort who attended FHS exam 5 (1991-1995) were included who were at least 45-years-old at that time, had available vascular risk factor data, and epilepsy follow-up (n = 2986, mean age 58, 48% male). Adjudication of epilepsy cases included review of medical charts to exclude seizure mimics and acute symptomatic seizures. The vascular risk factors studied included hypertension, diabetes mellitus, smoking, and hyperlipidemia. The role of the Framingham Stroke Risk Profile score was also investigated. Cox proportional hazards regression models were used for the analyses. RESULTS:Fifty-five incident epilepsy cases were identified during a mean of 19 years of follow-up. Hypertension was associated with a near 2-fold risk (hazard ratio [HR]: 1.93, 95% confidence interval [CI]: 1.10-3.37, p = .022) of developing epilepsy, even after adjustment for prevalent and interim stroke. In secondary analysis, excluding patients with normal blood pressure who were receiving anti-HTN (anti-hypertensive) treatment (n = 2613, 50 incident epilepsy cases) the association was (HR: 2.44, 95% CI: 1.36-4.35, p = .003). SIGNIFICANCE/CONCLUSIONS:Our results offer further evidence that hypertension, a potentially modifiable and highly prevalent vascular risk factor in the general population, increases 2- to 2.5-fold the risk of developing late-onset epilepsy.

OBJECTIVE:The number, unpredictability, and severity of seizures experienced by patients with Dravet syndrome (DS) negatively impact quality of life (QOL) for patients, caregivers, and families. Metrics are needed to assess whether patients with residual seizures have moved meaningfully toward seizure freedom after treatment with new antiseizure medications. METHODS:We evaluated the time required postrandomization for each patient to experience the same number of seizures experienced during baseline (i.e., time-to-nth seizure), using a post hoc time-to-event (TTE) analysis of data from two Phase 3 placebo-controlled trials of adjunctive fenfluramine for DS (Study 1, N = 119; Study 2, N = 87). Patients aged 2-19 years were randomized to placebo or adjunctive fenfluramine (Study 1: .7 mg/kg/day or .2 mg/kg/day; Study 2: .4 mg/kg/day with stiripentol). Data were analyzed by Kaplan-Meier TTE curves and waterfall plots. RESULTS:The proportion of patients who never reached baseline seizure frequency was greater with fenfluramine than with placebo (Study 1: fenfluramine .7 mg/kg/day, 60%; fenfluramine .2 mg/kg/day, 31%; placebo, 13%; Study 2: fenfluramine .4 mg/kg/day, 58%; placebo, 2%). Median time-to-nth seizure was longer after fenfluramine than after placebo (Study 1: fenfluramine .7 mg/kg/day, 13 weeks; .2 mg/kg/day, 10 weeks; placebo, 7 weeks; Study 2: fenfluramine .4 mg/kg/day, 13 weeks; placebo, 5 weeks; p < .001). Longest duration of convulsive seizure-free days was increased in active groups versus the placebo group (Study 1: fenfluramine .7 and .2 mg/kg/day, 25.0 and 15.0 days; placebo, 9.5 days [p = .0001; p = .0352]; Study 2: fenfluramine .4 mg/kg/day, 22.0 days; placebo, 13.0 days [p = .004]). The most common adverse events included decreased appetite, pyrexia, upper respiratory tract infection, diarrhea, and fatigue. SIGNIFICANCE/CONCLUSIONS:These data demonstrate that fenfluramine can significantly reduce day-to-day seizure burden in patients with DS, providing prolonged periods of convulsive seizure-free days, which may help reduce the physical and emotional disease toll while improving health-related QOL for patients and caregivers.

Religious experiences in epilepsy patients have provoked much interest with suggestions that hyperreligiosity is associated with temporal lobe seizures. Extreme varieties of religious behavior may be more frequent in epilepsy patients during ictal activity or during post-ictal psychotic episodes. We report a 75 year-old man with epilepsy who developed a progressive decline in cognition and behavior following a religious conversion 15 years earlier. He subsequently developed religious delusions of increasing severity and symptoms of Capgras syndrome. Brain imaging revealed bilateral posterior cortical atrophy, chronic right parieto-occipital encephalomalacia, and right mesial temporal sclerosis. Electroencephalograms and neuropsychological testing revealed initial right temporal lobe abnormalities followed by progressive frontal and bilateral dysfunction. The case highlights how a history of seizures, superimposed on sensory deprivation and a progressive impairment of right posterior and bilateral anterior brain function, may have contributed to religious conversion, which was followed by dementia and delusions involving religious content.

Brainstem nuclei dysfunction is implicated in sudden unexpected death in epilepsy. In animal models, deficient serotonergic activity is associated with seizure-induced respiratory arrest. In humans, glia are decreased in the ventrolateral medullary pre-Botzinger complex that modulate respiratory rhythm, as well as in the medial medullary raphe that modulate respiration and arousal. Finally, sudden unexpected death in epilepsy cases have decreased midbrain volume. To understand the potential role of brainstem nuclei in sudden unexpected death in epilepsy, we evaluated molecular signalling pathways using localized proteomics in microdissected midbrain dorsal raphe and medial medullary raphe serotonergic nuclei, as well as the ventrolateral medulla in brain tissue from epilepsy patients who died of sudden unexpected death in epilepsy and other causes in diverse epilepsy syndromes and non-epilepsy control cases (n = 15-16 cases per group/region). Compared with the dorsal raphe of non-epilepsy controls, we identified 89 proteins in non-sudden unexpected death in epilepsy and 219 proteins in sudden unexpected death in epilepsy that were differentially expressed. These proteins were associated with inhibition of EIF2 signalling (P-value of overlap = 1.29 × 10^-8, z = -2.00) in non-sudden unexpected death in epilepsy. In sudden unexpected death in epilepsy, there were 10 activated pathways (top pathway: gluconeogenesis I, P-value of overlap = 3.02 × 10^-6, z = 2.24) and 1 inhibited pathway (fatty acid beta-oxidation, P-value of overlap = 2.69 × 10^-4, z = -2.00). Comparing sudden unexpected death in epilepsy and non-sudden unexpected death in epilepsy, 10 proteins were differentially expressed, but there were no associated signalling pathways. In both medullary regions, few proteins showed significant differences in pairwise comparisons. We identified altered proteins in the raphe and ventrolateral medulla of epilepsy patients, including some differentially expressed in sudden unexpected death in epilepsy cases. Altered signalling pathways in the dorsal raphe of sudden unexpected death in epilepsy indicate a shift in cellular energy production and activation of G-protein signalling, inflammatory response, stress response and neuronal migration/outgrowth. Future studies should assess the brain proteome in relation to additional clinical variables (e.g. recent tonic-clonic seizures) and in more of the reciprocally connected cortical and subcortical regions to better understand the pathophysiology of epilepsy and sudden unexpected death in epilepsy.

Studies of epilepsy patients provide insight into the neuroscience of human memory. Patients with remote memory deficits may learn new information but have difficulty recalling events from years past. The processes underlying remote memory impairment are unclear and likely result from the interaction of multiple factors, including hippocampal dysfunction. The hippocampus likely has a continued role in remote semantic and episodic memory storage over time, and patients with mesial temporal lobe epilepsy (TLE) are at particular risk for deficits. Studies have focused on lateralization of remote memory, often with greater impairment in left TLE, which may relate to verbal task demands. Remote memory testing is restricted by methodological limitations. As a result, deficits have been difficult to measure. This review of remote memory focuses on evidence for its underlying neurobiology, theoretical implications for hippocampal function, and methodological difficulties that complicate testing in epilepsy patients.

Objective/UNASSIGNED:Sudden unexpected death in epilepsy (SUDEP) is the leading cause of epilepsy-related mortality. Although lots of effort has been made in identifying clinical risk factors for SUDEP in the literature, there are few validated methods to predict individual SUDEP risk. Prolonged postictal EEG suppression (PGES) is a potential SUDEP biomarker, but its occurrence is infrequent and requires epilepsy monitoring unit admission. We use machine learning methods to examine SUDEP risk using interictal EEG and ECG recordings from SUDEP cases and matched living epilepsy controls. Methods/UNASSIGNED:This multicenter, retrospective, cohort study examined interictal EEG and ECG recordings from 30 SUDEP cases and 58 age-matched living epilepsy patient controls. We trained machine learning models with interictal EEG and ECG features to predict the retrospective SUDEP risk for each patient. We assessed cross-validated classification accuracy and the area under the receiver operating characteristic (AUC) curve. Results/UNASSIGNED:The logistic regression (LR) classifier produced the overall best performance, outperforming the support vector machine (SVM), random forest (RF), and convolutional neural network (CNN). Among the 30 patients with SUDEP [14 females; mean age (SD), 31 (8.47) years] and 58 living epilepsy controls [26 females (43%); mean age (SD) 31 (8.5) years], the LR model achieved the median AUC of 0.77 [interquartile range (IQR), 0.73-0.80] in five-fold cross-validation using interictal alpha and low gamma power ratio of the EEG and heart rate variability (HRV) features extracted from the ECG. The LR model achieved the mean AUC of 0.79 in leave-one-center-out prediction. Conclusions/UNASSIGNED:Our results support that machine learning-driven models may quantify SUDEP risk for epilepsy patients, future refinements in our model may help predict individualized SUDEP risk and help clinicians correlate predictive scores with the clinical data. Low-cost and noninvasive interictal biomarkers of SUDEP risk may help clinicians to identify high-risk patients and initiate preventive strategies.