Faculty Bibliography

BACKGROUND:Tuberous sclerosis complex (TSC) and some focal cortical dysplasias (FCDs) are associated with dysfunctional mTOR signaling, resulting in increased cell growth and ribosomal S6 protein phosphorylation (phospho-S6). mTOR inhibitors can reduce TSC tumor growth and seizure frequency, and preclinical FCD studies indicate seizure suppression. This pilot study evaluated safety of mTOR inhibitor everolimus in treatment resistant (failure of >2 anti-seizure medications) TSC and FCD patients undergoing surgical resection and to assess mTOR signaling and molecular pathways. METHODS AND FINDINGS/RESULTS:We evaluated everolimus in 14 treatment resistant epilepsy patients undergoing surgical resection (4.5 mg/m2 daily for 7 days; n = 4 Active, mean age 18.3 years, range 4-26; n = 10, Control, mean age 13.1, range 3-45). Everolimus was well tolerated. Mean plasma everolimus in Active participants were in target range (12.4 ng/ml). Brain phospho-S6 was similar in Active and Control participants with a lower trend in Active participants, with Ser235/236 1.19-fold (p = 0.67) and Ser240/244 1.15-fold lower (p = 0.66). Histologically, Ser235/236 was 1.56-fold (p = 0.37) and Ser240/244 was 5.55-fold lower (p = 0.22). Brain proteomics identified 11 proteins at <15% false discovery rate associated with coagulation system (p = 1.45x10-9) and acute phase response (p = 1.23x10-6) activation. A weighted gene correlation network analysis (WGCNA) of brain proteomics and phospho-S6 identified 5 significant modules. Higher phospho-S6 correlated negatively with cellular respiration and synaptic transmission and positively with organophosphate metabolic process, nuclear mRNA catabolic process, and neuron ensheathment. Brain metabolomics identified 14 increased features in Active participants, including N-acetylaspartylglutamic acid. Plasma proteomics and cytokine analyses revealed no differences. CONCLUSIONS:Short-term everolimus before epilepsy surgery in TSC and FCD resulted in no adverse events and trending lower mTOR signaling (phospho-S6). Future studies should evaluate implications of our findings, including coagulation system activation and everolimus efficacy in FCD, in larger studies with long-term treatment to better understand molecular and clinical effects. CLINICAL TRIALS REGISTRATION/BACKGROUND:ClinicalTrials.gov NCT02451696.

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.

Importance/UNASSIGNED:Non-communicable chronic diseases (NCDs) such as obesity, type 2 diabetes, heart disease, and cancer were rare among non-western populations with traditional diets and lifestyles. As populations transitioned toward industrialized diets and lifestyles, NCDs developed. Objective/UNASSIGNED:We performed a systematic literature review to examine the effects of diet and lifestyle transitions on NCDs. Evidence Review/UNASSIGNED:We identified 22 populations that underwent a nutrition transition, eleven of which had sufficient data. Of these, we chose four populations with diverse geographies, diets and lifestyles who underwent a dietary and lifestyle transition and explored the relationship between dietary changes and health outcomes. We excluded populations with features overlapping with selected populations or with complicating factors such as inadequate data, subgroups, and different study methodologies over different periods. The selected populations were Yemenite Jews, Tokelauans, Tanushimaru Japanese, and Maasai. We also review transition data from seven excluded populations (Pima, Navajo, Aboriginal Australians, South African Natal Indians and Zulu speakers, Inuit, and Hadza) to assess for bias. Findings/UNASSIGNED:The three groups that replaced saturated fats (SFA) from animal (Yemenite Jews, Maasai) or plants (Tokelau) with refined carbohydrates had negative health outcomes (e.g., increased obesity, diabetes, heart disease). Yemenites reduced SFA consumption by >40% post-transition but men's BMI increased 19% and diabetes increased ~40-fold. Tokelauans reduced fat, dramatically reduced SFA, and increased sugar intake: obesity and diabetes rose. The Tanushimaruans transitioned to more fats and less carbohydrates and used more anti-hypertensive medications; stroke and breast cancer declined while heart disease was stable. The Maasai transitioned to lower fat, SFA and higher carbohydrates and had increased BMI and diabetes. Similar patterns were observed in the seven other populations. Conclusion/UNASSIGNED:The nutrient category most strongly associated with negative health outcomes - especially obesity and diabetes - was sugar (increased 600-650% in Yemenite Jews and Tokelauans) and refined carbohydrates (among Maasai, total carbohydrates increased 39% in men and 362% in women), while increased calories was less strongly associated with these disorders. Across 11 populations, NCDs were associated with increased refined carbohydrates more than increased calories, reduced activity or other factors, but cannot be attributed to SFA or total fat consumption.

BACKGROUND AND OBJECTIVES:We compared heart rate variability (HRV) in sudden unexpected death in epilepsy (SUDEP) cases and living epilepsy controls. METHODS:This international, multicenter, retrospective, nested case-control study examined patients admitted for video-EEG monitoring (VEM) between January 1, 2003, and December 31, 2014, and subsequently died of SUDEP. Time domain and frequency domain components were extracted from 5-minute interictal ECG recordings during sleep and wakefulness from SUDEP cases and controls. RESULTS:= 0.209). CONCLUSIONS:Reduced short-term LFP, which is a validated biomarker for sudden death, was associated with SUDEP. Increased HFP was associated with longer survival and may be cardioprotective in SUDEP. HRV quantification may help stratify individual SUDEP risk. CLASSIFICATION OF EVIDENCE:This study provides Class III evidence that in patients with epilepsy, some measures of HRV are associated with SUDEP.

OBJECTIVE:Network. METHODS:to examine the prevalence of elevated depressive symptoms (PHQ ≥ 10, NDDI-E ≥ 15) and suicidal ideation (PHQ-9 item 9 ≥ 1, NDDI-E item 4 ≥ 2). Multilevel mixed-effects logistic regression models examined associations between ethnicity, elevated depressive symptoms, and suicidal ideation among PWE. Secondary analyses examined correlates of elevated depressive symptoms and suicidal ideation among Hispanic PWE. RESULTS:Of 559 participants, 49.6% (n = 277) were Hispanic. Elevated depressive symptoms were endorsed by 38.1% (n = 213) of all participants (32.5% of Hispanics); suicidal ideation was endorsed by 18.4% (n = 103) of all participants (16.3% of Hispanics). After adjustment for sociodemographic and health attributes, Hispanic PWE had a 44% lower prevalence of elevated depressive symptoms (OR = 0.56, CI 0.37-0.84, p = 0.0056) compared to non-Hispanics but similar rates of suicidal ideation (OR = 0.84, CI 0.45-1.58, p = 0.59). Acculturation measures were available for 256 (92.4%) of Hispanic PWE: language preference was Spanish for 62.9%, 46.1% were foreign-born. Spanish-speaking Hispanics were less likely than English-speaking Hispanics to report elevated depressive symptoms (OR = 0.43, CI 0.19-0.97, p = 0.041); however, Hispanics who reported fair or poor health status had a four-fold higher depression prevalence compared to those who reported excellent or very good health status [reference group] (OR = 4.44, CI 1.50-13.18, p = 0.0071). Of the Hispanics who provided prior 30-day seizure data, ≥1 monthly seizure was independently associated with higher depression prevalence (OR = 3.11, CI 1.29-7.45, p = 0.01). Being foreign-born was not associated with elevated depressive symptoms or suicidal ideation prevalence. CONCLUSIONS:In a large, geographically diverse sample of PWE, elevated depressive symptoms were significantly lower in Hispanics compared to non-Hispanics. Spanish language preference was associated with a lower prevalence of elevated depressive symptoms among Hispanic PWE. Future studies should include acculturation data to better screen for depression and suicidal ideation risk and optimize interventions for Hispanic PWE.

Perception results from the interplay of sensory input and prior knowledge. Despite behavioral evidence that long-term priors powerfully shape perception, the neural mechanisms underlying these interactions remain poorly understood. We obtained direct cortical recordings in neurosurgical patients as they viewed ambiguous images that elicit constant perceptual switching. We observe top-down influences from the temporal to occipital cortex, during the preferred percept that is congruent with the long-term prior. By contrast, stronger feedforward drive is observed during the non-preferred percept, consistent with a prediction error signal. A computational model based on hierarchical predictive coding and attractor networks reproduces all key experimental findings. These results suggest a pattern of large-scale information flow change underlying long-term priors' influence on perception and provide constraints on theories about long-term priors' influence on perception.

Humans form lasting memories of stimuli that were only encountered once. This naturally occurs when listening to a story, however it remains unclear how and when memories are stored and retrieved during story-listening. Here, we first confirm in behavioral experiments that participants can learn about the structure of a story after a single exposure and are able to recall upcoming words when the story is presented again. We then track mnemonic information in high frequency activity (70-200 Hz) as patients undergoing electrocorticographic recordings listen twice to the same story. We demonstrate predictive recall of upcoming information through neural responses in auditory processing regions. This neural measure correlates with behavioral measures of event segmentation and learning. Event boundaries are linked to information flow from cortex to hippocampus. When listening for a second time, information flow from hippocampus to cortex precedes moments of predictive recall. These results provide insight on a fine-grained temporal scale into how episodic memory encoding and retrieval work under naturalistic conditions.

Interictal epileptiform discharges (IEDs) can impair memory. The properties of IEDs most detrimental to memory, however, are undefined. We studied the impact of temporal and spatial characteristics of IEDs on list learning. Subjects completed a memory task during intracranial EEG recordings including hippocampal depth and temporal neocortical subdural electrodes. Subjects viewed a series of objects, and after a distracting task, recalled the objects from the list. The impacts of IED presence, duration, and propagation to neocortex during encoding of individual stimuli were assessed. The effects of IED total number and duration during maintenance and recall periods on delayed recall performance were also determined. The influence of IEDs during recall was further investigated by comparing the likelihood of IEDs preceding correctly recalled items vs. periods of no verbal response. Across 6 subjects, we analyzed 28 hippocampal and 139 lateral temporal contacts. Recall performance was poor, with a median of 17.2% correct responses (range 10.4-21.9%). Interictal epileptiform discharges during encoding, maintenance, and recall did not significantly impact task performance, and there was no significant difference between the likelihood of IEDs during correct recall vs. periods of no response. No significant effects of discharge duration during encoding, maintenance, or recall were observed. Interictal epileptiform discharges with spread to lateral temporal cortex during encoding did not adversely impact recall. A post hoc analysis refining model assumptions indicated a negative impact of IED count during the maintenance period, but otherwise confirmed the above results. Our findings suggest no major effect of hippocampal IEDs on list learning, but study limitations, such as baseline hippocampal dysfunction, should be considered. The impact of IEDs during the maintenance period may be a focus of future research.

Depression is associated with adverse outcomes in epilepsy but is undertreated in this population. Project UPLIFT, a telephone-based depression self-management program, was developed for adults with epilepsy and has been shown to reduce depressive symptoms in English-speaking patients. There remains an unmet need for accessible mental health programs for Hispanic adults with epilepsy. The purpose of this study was to evaluate the feasibility, acceptability, and effects on depressive symptoms of a culturally adapted version of UPLIFT for the Hispanic community. Hispanic patients with elevated depressive symptoms (n = 72) were enrolled from epilepsy clinics in New York City and randomized to UPLIFT or usual care. UPLIFT was delivered in English or Spanish to small groups in eight weekly telephone sessions. Feasibility was assessed by recruitment, retention, and adherence rates and acceptability was assessed by self-reported satisfaction with the intervention. Depressive symptoms (PHQ-9 scores) were compared between study arms over 12 months. The mean age was 43.3±11.3, 71% of participants were female and 67% were primary Spanish speakers. Recruitment (76% consent rate) and retention rates (86-93%) were high. UPLIFT participants completed a median of six out of eight sessions and satisfaction ratings were high, but rates of long-term practice were low. Rates of clinically significant depressive symptoms (PHQ-9 ≥5) were lower in UPLIFT versus usual care throughout follow-up (63% vs. 72%, 8 weeks; 40% vs. 70%, 6 months; 47% vs. 70%, 12 months). Multivariable-adjusted regressions demonstrated statistically significant differences at 6 months (OR = 0.24, 95% CI, 0.06-0.93), which were slightly reduced at 12 months (OR = 0.30, 95% CI, 0.08-1.16). Results suggest that UPLIFT is feasible and acceptable among Hispanic adults with epilepsy and demonstrate promising effects on depressive symptoms. Larger trials in geographically diverse samples are warranted.