Faculty Bibliography

Objective/UNASSIGNED:-related neurodevelopmental disorder in 33 individuals. Methods/UNASSIGNED:using American College of Medical Genetics and Genomics/Association of Molecular Pathology criteria, largely identified via clinical exome sequencing. Genetic reports were reviewed. Clinical data were collected by retrospective chart review and caregiver report including standardized parent report measures. Results/UNASSIGNED:-related disorders to include 33 individuals, aged 2-38 years, both females and males, with 11 different de novo missense variants, most within the nuclear localization signal. The major features of the phenotype include developmental delay/intellectual disability, severe language impairment, motor problems, growth, and musculoskeletal disturbances. Minor features include dysmorphic features, epilepsy, neuropsychiatric diagnoses such as autism spectrum disorder, and cortical visual impairment. Although rare, we report early stroke and premature death with this condition. Conclusions/UNASSIGNED:-related disorders continues to expand as the allelic spectrum and identification of affected males increases.

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.

Rationale: Seizure clusters may be related to Sudden Unexpected Death in Epilepsy (SUDEP). Two or more generalized convulsive seizures (GCS) were captured during video electroencephalography in 7/11 (64%) patients with monitored SUDEP in the MORTEMUS study. It follows that seizure clusters may be associated with epilepsy severity and possibly with SUDEP risk. We aimed to determine if electroclinical seizure features worsen from seizure to seizure within a cluster and possible associations between GCS clusters, markers of seizure severity, and SUDEP risk. Methods: Patients were consecutive, prospectively consented participants with drug-resistant epilepsy from a multi-center study. Seizure clusters were defined as two or more GCS in a 24-h period during the recording of prolonged video-electroencephalography in the Epilepsy monitoring unit (EMU). We measured heart rate variability (HRV), pulse oximetry, plethysmography, postictal generalized electroencephalographic suppression (PGES), and electroencephalography (EEG) recovery duration. A linear mixed effects model was used to study the difference between the first and subsequent seizures, with a level of significance set at p < 0.05. Results: We identified 112 GCS clusters in 105 patients with 285 seizures. GCS lasted on average 48.7 ± 19 s (mean 49, range 2-137). PGES emerged in 184 (64.6%) seizures and postconvulsive central apnea (PCCA) was present in 38 (13.3%) seizures. Changes in seizure features from seizure to seizure such as seizure and convulsive phase durations appeared random. In grouped analysis, some seizure features underwent significant deterioration, whereas others improved. Clonic phase and postconvulsive central apnea (PCCA) were significantly shorter in the fourth seizure compared to the first. By contrast, duration of decerebrate posturing and ictal central apnea were longer. Four SUDEP cases in the cluster cohort were reported on follow-up. Conclusion: Seizure clusters show variable changes from seizure to seizure. Although clusters may reflect epilepsy severity, they alone may be unrelated to SUDEP risk. We suggest a stochastic nature to SUDEP occurrence, where seizure clusters may be more likely to contribute to SUDEP if an underlying progressive tendency toward SUDEP has matured toward a critical SUDEP threshold.

Seizure clusters, an intermediate between single seizure and status epilepticus, are associated with morbidity, impaired quality of life, and premature mortality. The relationship between seizure clusters and sudden unexplained death in epilepsy (SUDEP) is poorly understood. Here, we define seizure clusters; review comorbid psychiatric disorders and memory deficits associated with seizure clusters; and review cases of witnessed SUDEP for which seizure frequency prior to death is available. Patients with a history of seizure clusters have a 2.5 fold increased risk for SUDEP, and one third of patients with monitored in hospital SUDEP experienced a cluster of generalized tonic clonic seizures prior to death. Understanding the effects of seizure frequency and duration on SUDEP risk could yield new insights in SUDEP pathophysiology and new targets for intervention.

Objective: A recent clinical trial with 0.7mg/kg/day of fenfluramine (FFA) showed 62.3% (IC 95%: -47.7%; -72.8%; p<0.001) reduction in convulsive seizure frequency (CSF) compared to placebo. However, the impact of the disease on the patient and their caregivers may depend on other variables. This alternative analysis value the impact of other results.
Method(s): After a baseline period of 6 weeks patients with DS ages 2 to 18 years, was randomized to FFA 0.7 or 0.2mg/kg/day or placebo added. Time to new event (time required to experience the same number of crisis as in the reference period [TTE]) was analyzed. Intervals without crisis and number of days without crisis was analyzed too.
Result(s): 119 patients with DS receiving FFA 0.7mg/kg/day; FFA0.2mg/kg/day; or placebo. TTE was significantly longer in active groups. Placebo: 6 weeks, FFA 0.2mg/kg/day:8 weeks and FFA 0.7mg/kg/day: >12 weeks (p<0.001; ~60% of patients in the FFA 0.7mg/kg/day group never reached their baseline seizure count and were censored). The number of days without crisis was higher in groups treated with FFA: 33 and 20 days without additional crisis counted in the active groups. The longest average without crisis was higher with FFA 0.7mg/kg/day (25 days; p<0.001) and FFA 0.2mg/kg/day (15 days; Px0.035) than with placebo (9.5 days).
Conclusion(s): FFA extended TTE and provided significantly more days without crisis and longer periods without crisis than placebo. Our analysis can help assess the ability of a treatment to reduce the burden of seizures in patients with SD and their caregivers

Sensory input arrives in continuous sequences that humans experience as segmented units, e.g., words and events. The brain's ability to discover regularities is called statistical learning. Structure can be represented at multiple levels, including transitional probabilities, ordinal position, and identity of units. To investigate sequence encoding in cortex and hippocampus, we recorded from intracranial electrodes in human subjects as they were exposed to auditory and visual sequences containing temporal regularities. We find neural tracking of regularities within minutes, with characteristic profiles across brain areas. Early processing tracked lower-level features (e.g., syllables) and learned units (e.g., words), while later processing tracked only learned units. Learning rapidly shaped neural representations, with a gradient of complexity from early brain areas encoding transitional probability, to associative regions and hippocampus encoding ordinal position and identity of units. These findings indicate the existence of multiple, parallel computational systems for sequence learning across hierarchically organized cortico-hippocampal circuits.

Although seizures are common in children, they are often overlooked as a potential cause of death. Febrile and nonfebrile seizures can be fatal in children with or without an epilepsy diagnosis and may go unrecognized by parents or physicians. Sudden unexpected infant deaths, sudden unexplained death in childhood, and sudden unexpected death in epilepsy share clinical, neuropathological, and genetic features, including male predominance, unwitnessed deaths, death during sleep, discovery in the prone position, hippocampal abnormalities, and variants in genes regulating cardiac and neuronal excitability. Additionally, epidemiological studies reveal that miscarriages are more common among individuals with a personal or family history of epilepsy, suggesting that some fetal losses may result from epileptic factors. The spectrum of seizure-related deaths in pediatrics is wide and underappreciated; accurately estimating this mortality and understanding its mechanism in children is critical to developing effective education and interventions to prevent these tragedies.

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).

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.