Faculty Bibliography

We evaluated baseline sudden unexpected death in epilepsy (SUDEP) knowledge and counseling practices among national and international adult neurology trainees with a 12-question online survey. The survey was emailed to all 169 U.S. neurology residency program directors and select international neurology/epilepsy program leaders. Program leaders were asked to distribute the survey link to adult neurology trainees. There were 161 respondents in the U.S. and 171 respondents outside the U.S. The latter were from 25 Latin American, European, Asian, and African countries. More than 90% of all trainees reported familiarity with SUDEP definition. Familiarity with SUDEP risk factors and mitigation measures ranged from 56% to 67% across these groups, with international trainees slightly more familiar with risk factors (67% vs. 61% in U.S.) but less familiar with mitigation measures (56% vs. 63% in U.S.). Approximately half of national (49%) and international (54%) trainees rarely or never counseled patients on SUDEP. Less than half of national (44%) and international (41%) trainees were educated about SUDEP. Many U.S. and adult neurology trainees remain unfamiliar with SUDEP risk factors and mitigation measures. Sudden unexpected death in epilepsy counseling falls below recommended standards. We suggest that worldwide neurology training programs' leaderships consider improving SUDEP education targeted at adult neurology trainees.

OBJECTIVE:To identify the molecular signaling pathways underlying sudden unexpected death in epilepsy (SUDEP) and high-risk SUDEP compared to epilepsy control patients. METHODS:For proteomics analyses, we evaluated the hippocampus and frontal cortex from microdissected post-mortem brain tissue of 12 SUDEP and 14 non-SUDEP epilepsy patients. For transcriptomics analyses, we evaluated hippocampus and temporal cortex surgical brain tissue from mesial temporal lobe epilepsy (MTLE) patients: 6 low-risk and 8 high-risk SUDEP as determined by a short (< 50 seconds) or prolonged (≥ 50 seconds) postictal generalized EEG suppression (PGES) that may indicate severely depressed brain activity impairing respiration, arousal, and protective reflexes. RESULTS:In autopsy hippocampus and cortex, we observed no proteomic differences between SUDEP and non-SUDEP epilepsy patients, contrasting with our previously reported robust differences between epilepsy and non-epilepsy control patients. Transcriptomics in hippocampus and cortex from surgical epilepsy patients segregated by PGES identified 55 differentially expressed genes (37 protein-coding, 15 lncRNAs, three pending) in hippocampus. CONCLUSION/CONCLUSIONS:The SUDEP proteome and high-risk SUDEP transcriptome were similar to other epilepsy patients in hippocampus and frontal cortex, consistent with diverse epilepsy syndromes and comorbidities associated with SUDEP. Studies with larger cohorts and different epilepsy syndromes, as well as additional anatomic regions may identify molecular mechanisms of SUDEP.

BACKGROUND:Many electroencephalography (EEG) based seizure detection paradigms have been developed and validated over the last two decades. The majority of clinical approaches use scalp or intracranial EEG electrodes. Scalp EEG is limited by patient discomfort and short duration of useful EEG signals. Intracranial EEG involves an invasive surgical procedure associated with significant risk making it unsuitable for widespread use as a practical clinical biometric. A less invasive EEG monitoring approach, that is between invasive intracranial procedures and noninvasive methods, would fill the need of a safe, accurate, chronic (ultra-long term) and objective seizure detection method. We present validation of a continuous EEG seizure detection paradigm using human single-channel EEG recordings from subcutaneously placed electrodes that could be used to fulfill this need. METHODS:Ten-minute long sleep, awake and ictal EEG epochs obtained from 21 human subjects with subscalp electrodes and validated against simultaneous iEEG recordings were analyzed by three experienced clinical neurophysiologists. The 201subscalp EEG time series epochs where classified as diagnostic for awake, asleep, or seizure by the clinicians who were blinded to all other information. Seventy of the epochs were classified in this way as representing seizure activity. A subject specific seizure detection algorithm was trained and then evaluated offline for each patient in the data set using the expert consensus classification as the gold standard. RESULTS:The average seizure detection performance of the algorithm across 21 subjects exceeded 90 % accuracy: 97 % sensitivity, 91 % specificity, and 93 % accuracy. For 19 of 21 patient datasets the algorithm achieved 100 % sensitivity. For 15 of 21 patients, the algorithm achieved 100 % specificity. For 13 of 21 patients the algorithm achieved 100 % accuracy. COMPARISON/UNASSIGNED:No comparable published methods are available for subgaleal EEG seizure detection. CONCLUSIONS:These findings suggest that a simple seizure detection algorithm using subcutaneous EEG signals could provide sufficient accuracy and clinical utility for use in a low power, long-term subcutaneous brain monitoring device. Such a device would fill a need for a large number of people with epilepsy who currently have no means for accurately quantifying their seizures thereby providing important information to healthcare providers not currently available.

Image labeling using convolutional neural networks (CNNs) are a template-free alternative to traditional morphometric techniques. We trained a 3D deep CNN to label the hippocampus and amygdala on whole brain 700 μm isotropic 3D MP2RAGE MRI acquired at 7T. Manual labels of the hippocampus and amygdala were used to (i) train the predictive model and (ii) evaluate performance of the model when applied to new scans. Healthy controls and individuals with epilepsy were included in our analyses. Twenty-one healthy controls and sixteen individuals with epilepsy were included in the study. We utilized the recently developed DeepMedic software to train a CNN to label the hippocampus and amygdala based on manual labels. Performance was evaluated by measuring the dice similarity coefficient (DSC) between CNN-based and manual labels. A leave-one-out cross validation scheme was used. CNN-based and manual volume estimates were compared for the left and right hippocampus and amygdala in healthy controls and epilepsy cases. The CNN-based technique successfully labeled the hippocampus and amygdala in all cases. Mean DSC = 0.88 ± 0.03 for the hippocampus and 0.8 ± 0.06 for the amygdala. CNN-based labeling was independent of epilepsy diagnosis in our sample (p = .91). CNN-based volume estimates were highly correlated with manual volume estimates in epilepsy cases and controls. CNNs can label the hippocampus and amygdala on native sub-mm resolution MP2RAGE 7T MRI. Our findings suggest deep learning techniques can advance development of morphometric analysis techniques for high field strength, high spatial resolution brain MRI.

OBJECTIVE:People with epilepsy experience increased rates of sexual dysfunction, often affecting quality of life. Sexual dysfunction may result from the underlying disorder, antiseizure or other medications, or comorbid psychosocial factors. This study evaluated the incidence and clinical associations of sexual dysfunction in adult epilepsy patients. METHODS:89 epilepsy patients 18 years and older admitted to the New York University Comprehensive Epilepsy Center epilepsy monitoring unit between 2016 and 2018 completed a survey on sexual functioning. The survey included demographic, clinical, and sexual functioning information with a validated measure of sexual function (the Arizona Sexual Experiences Scale (ASEX). RESULTS:Of 89 surveys completed, 15 (16.9 %) patients had discussed sexual functioning with a medical professional and 20 (22.5 %) reported sexual dysfunction. For the group, the mean ASEX score was 13.6 (SD 4.8). 59 (66.3 %) participants reported not being asked about sexual health by their doctor or nurse practitioner in the last year. The two independent predictors of sexual dysfunction were self-identifying as overweight/obese (OR 6.1, CI 1.4-26.5, P = 0.02) or taking strong enzyme-inducing antiseizure medications (OR 7.8, CI 1.4-44.9, P = 0.02). Other factors such as age, relationship status, duration of epilepsy, the presence of depression or anxiety, cardiovascular risk factors, and opioid/stimulant use, did not predict sexual dysfunction. SIGNIFICANCE/CONCLUSIONS:Our study showed that sexual dysfunction is common in epilepsy patients but infrequently discussed by medical professionals. Two modifiable risk factors, being overweight or taking strong enzyme-inducing antiseizure medications, were independently associated with sexual dysfunction, suggesting interventions to potentially improve sexual health.

OBJECTIVE:Ataluren is a compound that reads through premature stop codons and increases protein expression by increasing translation without modifying transcription or mRNA stability. We investigated the safety and efficacy of ataluren in children with nonsense variants causing Dravet Syndrome (DS) and CDKL5 Deficiency Syndrome (CDD). METHODS:This single-center double-blind, placebo-controlled crossover trial randomized subjects to receive ataluren or placebo for 12 weeks (period 1), a 4-week washout, then another 12-week treatment (period 2). The primary outcome was ataluren's safety profile. The secondary outcome measures were (1) changes in convulsive and/or drop seizure frequency and (2) changes in minor seizure types during ataluren treatment compared to placebo. Exploratory objectives assessed changes in cognitive, motor, and behavioral function as well as quality of life during ataluren therapy. RESULTS:We enrolled seven subjects with DS and eight subjects with CDD. Three treatment-related adverse events (AE) occurred during the blinded phases. Two subjects withdrew due to AE. Ataluren was not effective in reducing seizure frequency or improving cognitive, motor, or behavioral function or quality of life in subjects with either DS or CDD due to nonsense variants. Limitations included a small sample size and 12-week treatment phase, possibly too short to identify a disease-modifying effect. SIGNIFICANCE/CONCLUSIONS:There was no difference between ataluren and placebo; ataluren is not an effective therapy for seizures or other disorders in children with DS or CDD due to nonsense variants. There were no drug-related serious AE during the double-blind period, consistent with ataluren's favorable safety profile in larger studies. (Funded by Epilepsy Foundation, Dravet Syndrome Foundation, Finding A Cure for Seizures and Epilepsy and PTC Therapeutics, Inc.; ClinicalTrials.gov number, NCT02758626).

OBJECTIVE:To determine the prevalence and associated mortality of well-defined neurologic diagnoses among COVID-19 patients, we prospectively followed hospitalized SARS-Cov-2 positive patients and recorded new neurologic disorders and hospital outcomes. METHODS:We conducted a prospective, multi-center, observational study of consecutive hospitalized adults in the NYC metropolitan area with laboratory-confirmed SARS-CoV-2 infection. The prevalence of new neurologic disorders (as diagnosed by a neurologist) was recorded and in-hospital mortality and discharge disposition were compared between COVID-19 patients with and without neurologic disorders. RESULTS:Of 4,491 COVID-19 patients hospitalized during the study timeframe, 606 (13.5%) developed a new neurologic disorder in a median of 2 days from COVID-19 symptom onset. The most common diagnoses were: toxic/metabolic encephalopathy (6.8%), seizure (1.6%), stroke (1.9%), and hypoxic/ischemic injury (1.4%). No patient had meningitis/encephalitis, or myelopathy/myelitis referable to SARS-CoV-2 infection and 18/18 CSF specimens were RT-PCR negative for SARS-CoV-2. Patients with neurologic disorders were more often older, male, white, hypertensive, diabetic, intubated, and had higher sequential organ failure assessment (SOFA) scores (all P<0.05). After adjusting for age, sex, SOFA-scores, intubation, past history, medical complications, medications and comfort-care-status, COVID-19 patients with neurologic disorders had increased risk of in-hospital mortality (Hazard Ratio[HR] 1.38, 95% CI 1.17-1.62, P<0.001) and decreased likelihood of discharge home (HR 0.72, 95% CI 0.63-0.85, P<0.001). CONCLUSIONS:Neurologic disorders were detected in 13.5% of COVID-19 patients and were associated with increased risk of in-hospital mortality and decreased likelihood of discharge home. Many observed neurologic disorders may be sequelae of severe systemic illness.

Epilepsy is a heterogenous group of disorders defined by recurrent seizure activity due to abnormal synchronized activity of neurons. A growing number of epilepsy cases are believed to be caused by genetic factors and copy number variants (CNV) contribute to up to 5% of epilepsy cases. However, CNVs in epilepsy are usually large deletions or duplications involving multiple neurodevelopmental genes. In patients who underwent seizure focus resection for treatment-resistant epilepsy, whole genome DNA methylation profiling identified 3 main clusters of which one showed strong association with receptor tyrosine kinase (RTK) genes. We identified focal copy number gains involving epidermal growth factor receptor (EGFR) and PDGFRA loci. The dysplastic neurons of cases with amplifications showed marked overexpression of EGFR and PDGFRA, while glial and endothelial cells were negative. Targeted sequencing of regulatory regions and DNA methylation analysis revealed that only enhancer regions of EGFR and gene promoter of PDGFRA were amplified, while coding regions did not show copy number abnormalities or somatic mutations. Somatic focal copy number gains of noncoding regulatory represent a previously unrecognized genetic driver in epilepsy and a mechanism of abnormal activation of RTK genes. Upregulated RTKs provide a potential avenue for therapy in seizure disorders.

OBJECTIVE:To analyze the association between peri-ictal brainstem posturing semiologies with post-ictal generalized electroencephalographic suppression (PGES) and breathing dysfunction in generalized convulsive seizures (GCS). METHODS:Prospective, multicenter analysis of GCS. Ictal brainstem semiology was classified as (1) decerebration: bilateral symmetric tonic arm extension, (2) decortication: bilateral symmetric tonic arm flexion only, (3) hemi-decerebration: unilateral tonic arm extension with contralateral flexion and (4) absence of ictal tonic phase. Post-ictal posturing was also assessed. Respiration was monitored using thoraco-abdominal belts, video and pulse oximetry. RESULTS:= 0.035). CONCLUSIONS:recovery. Peri-ictal brainstem posturing may be surrogate biomarkers for GCS severity identifiable without in-hospital monitoring. CLASSIFICATION OF EVIDENCE/METHODS:This study provides Class III evidence that peri-ictal brainstem posturing is associated with the GCS with more prolonged PGES and more severe breathing dysfunction.

Sudden unexpected death in epilepsy is the leading category of epilepsy-related death and the underlying mechanisms are incompletely understood. Risk factors can include a recent history and high frequency of generalized tonic-clonic seizures, which can depress brain activity postictally, impairing respiration, arousal and protective reflexes. Neuropathological findings in sudden unexpected death in epilepsy cases parallel those in other epilepsy patients, with no implication of novel structures or mechanisms in seizure-related deaths. Few large studies have comprehensively reviewed whole brain examination of such patients. We evaluated 92 North American Sudden unexpected death in epilepsy Registry cases with whole brain neuropathological examination by board-certified neuropathologists blinded to the adjudicated cause of death, with an average of 16 brain regions examined per case. The 92 cases included 61 sudden unexpected death in epilepsy (40 definite, 9 definite plus, 6 probable, 6 possible) and 31 people with epilepsy controls who died from other causes. The mean age at death was 34.4 years and 65.2% (60/92) were male. The average age of death was younger for sudden unexpected death in epilepsy cases than for epilepsy controls (30.0 versus 39.6 years; P = 0.006), and there was no difference in sex distribution respectively (67.3% male versus 64.5%, P = 0.8). Among sudden unexpected death in epilepsy cases, earlier age of epilepsy onset positively correlated with a younger age at death (P = 0.0005) and negatively correlated with epilepsy duration (P = 0.001). Neuropathological findings were identified in 83.7% of the cases in our cohort. The most common findings were dentate gyrus dysgenesis (sudden unexpected death in epilepsy 50.9%, epilepsy controls 54.8%) and focal cortical dysplasia (FCD) (sudden unexpected death in epilepsy 41.8%, epilepsy controls 29.0%). The neuropathological findings in sudden unexpected death in epilepsy paralleled those in epilepsy controls, including the frequency of total neuropathological findings as well as the specific findings in the dentate gyrus, findings pertaining to neurodevelopment (e.g. FCD, heterotopias) and findings in the brainstem (e.g. medullary arcuate or olivary dysgenesis). Thus, like prior studies, we found no neuropathological findings that were more common in sudden unexpected death in epilepsy cases. Future neuropathological studies evaluating larger sudden unexpected death in epilepsy and control cohorts would benefit from inclusion of different epilepsy syndromes with detailed phenotypic information, consensus among pathologists particularly for more subjective findings where observations can be inconsistent, and molecular approaches to identify markers of sudden unexpected death in epilepsy risk or pathogenesis.