Faculty Bibliography

Rett syndrome (RTT) is a rare neurodevelopmental disorder that is usually caused by mutations of the MECP2 gene. Patients with RTT suffer from severe deficits in motor, perceptual and cognitive domains. Electroencephalogram (EEG) has provided useful information to clinicians and scientists, from the very first descriptions of RTT, and yet no reliable neurophysiological biomarkers related to the pathophysiology of the disorder or symptom severity have been identified to date. To identify consistently observed and potentially informative EEG characteristics of RTT pathophysiology, and ascertain areas most worthy of further systematic investigation, here we review the literature for EEG abnormalities reported in patients with RTT and in its disease models. While pointing to some promising potential EEG biomarkers of RTT, our review identify areas of need to realize the potential of EEG including (1) quantitative investigation of promising clinical-EEG observations in RTT, e.g., shift of mu rhythm frequency and EEG during sleep; (2) closer alignment of approaches between patients with RTT and its animal models to strengthen the translational significance of the work (e.g., EEG measurements and behavioral states); (3) establishment of large-scale consortium research, to provide adequate Ns to investigate age and genotype effects.

Background and Purpose/UNASSIGNED:Hospital 30-day readmissions in patients with primary neurological problems are not well characterized. We sought to determine patient characteristics associated with readmission across 3 different inpatient neurology services at New York University Langone Hospital. Methods/UNASSIGNED:We retrospectively reviewed all 30-day readmissions from the General Neurology, Epilepsy, and Stroke services at NYULH Brooklyn and Manhattan campuses from 2016-2017 and compared them to a random sample of non-readmitted neurology patients. We used univariate analyses to compare demographics, clinical characteristics, disease specific metrics, and discharge factors of non-readmitted and readmitted groups and binomial logistic regression to examine specific variables with adjustment for confounders. Results/UNASSIGNED:We included 284 patients with 30-day readmissions and 306 control patients without readmissions matched by discharge location and service. After adjusting for confounders, we found that the following factors were associated with increased readmission risk: a recent hospital encounter increased risk for all services, increased number of medications at discharge, intensive care unit stay, higher length of stay, and prior history of seizure for the General Neurology Service, increased number of medications at discharge for the Epilepsy Service, and active malignancy and higher discharge modified Rankin Scale score for the Stroke Service. Conclusion/UNASSIGNED:This study identifies potential risk factors for readmission in patients across multiple neurology services. Further research is needed to establish whether these risk factors hold across multiple institutions.

Virtual portion tasks have been used to predict food intake in healthy individuals, severity of illness in individuals with anorexia nervosa, and weight loss in bariatric surgery patients. Whether portion creation in response to a recalled interpersonal stress ("recalled stress portions") could be used as a proxy for ad lib intake, after a stressor, remains untested, and the mechanism supporting this relationship is unclear. The present study's goals were: 1) to validate virtual portion tasks as proxies for actual food intake in a stressful context and 2) to test a causal pathway in which these virtual stress portions predict ad lib intake after stress. We proposed that this relationship is mediated by virtual portions created the moment after laboratory stress or rest manipulation (momentary portions), and before the participant actually ate food. At screening, 29 healthy undergraduate white women created virtual portions of eight snacks (apples, olives, potato chips, pretzels, caramel popcorn, milk chocolate) that they typically eat and also portions they recall eating in response to a stressful interpersonal situation. In addition, after a Trier Social Stress Test, or a rest period, on separate days in counterbalanced order, participants created 'momentary' virtual portions of the same snacks presented during screening, and then were given potato chips, mini golden Oreos, and M&Ms to eat. Recalled stress (b = 0.07 ± 0.02, p = 0.003), and momentary stress (b = 0.12 ± 0.02, p = 0.00001), portions of milk chocolate accounted for 29% and 51%, respectively, of the variance in ad lib stress intake of M&Ms. Typical (b = 0.15 ± 0.07, p = 0.03), and momentary rest (b = 0.21 ± 0.06, p = 0.002), portions of chips accounted for 16% and 31%, respectively, of the variance in ad lib rest intake of chips. The causal pathway from recalled stress portion to ad lib stress snack intake was completely mediated by momentary stress portion for milk chocolate and M&Ms (β = 0.04 ± 0.02, z = 2.4, p = 0.0154). These findings illustrate the planning and recall components of eating in response to stress, but not necessarily under rest conditions. This recalled stress virtual portion paradigm has clinical and research value in that it can detect those who overconsume in response to stress.

PURPOSE/OBJECTIVE:By incorporating major developments in genetics, ophthalmology, dermatology, and neuroimaging, to revise the diagnostic criteria for neurofibromatosis type 1 (NF1) and to establish diagnostic criteria for Legius syndrome (LGSS). METHODS:We used a multistep process, beginning with a Delphi method involving global experts and subsequently involving non-NF experts, patients, and foundations/patient advocacy groups. RESULTS:We reached consensus on the minimal clinical and genetic criteria for diagnosing and differentiating NF1 and LGSS, which have phenotypic overlap in young patients with pigmentary findings. Criteria for the mosaic forms of these conditions are also recommended. CONCLUSION/CONCLUSIONS:The revised criteria for NF1 incorporate new clinical features and genetic testing, whereas the criteria for LGSS were created to differentiate the two conditions. It is likely that continued refinement of these new criteria will be necessary as investigators (1) study the diagnostic properties of the revised criteria, (2) reconsider criteria not included in this process, and (3) identify new clinical and other features of these conditions. For this reason, we propose an initiative to update periodically the diagnostic criteria for NF1 and LGSS.

Introduction/UNASSIGNED:Periodontal disease is a chronic, inflammatory bacterial dysbiosis that is associated with both Alzheimer's disease (AD) and Down syndrome. Methods/UNASSIGNED:A total of 48 elderly cognitively normal subjects were evaluated for differences in subgingival periodontal bacteria (assayed by 16S rRNA sequencing) between cerebrospinal fluid (CSF) biomarker groups of amyloid and neurofibrillary pathology. A dysbiotic index (DI) was defined at the genus level as the abundance ratio of known periodontal bacteria to healthy bacteria. Analysis of variance/analysis of covariance (ANOVA/ANCOVA), linear discriminant effect-size analyses (LEfSe) were used to determine the bacterial genera and species differences between the CSF biomarker groups. Results/UNASSIGNED: = 0.02 and 0.01) but not with P-tau. Discussion/UNASSIGNED:We show a selective relationship between periodontal disease bacterial dysbiosis and CSF biomarkers of amyloidosis, but not for tau. Further modeling is needed to establish the direct link between oral bacteria and Aβ.

We studied mortality in tuberous sclerosis complex (TSC) by analyzing data from the Tuberous Sclerosis Alliance Natural History Database of 2233 patients from 18 United States TSC centers. Among 31 decedents with data; mean age of death was 29 years. Cause of death could be determined in 26 cases: 11 definitely related to TSC, 14 possibly related to TSC, and 1 unrelated to TSC. Causes of death included SUDEP in 11 (35.5%; Definite (5), Probable (4), Possible (2)), respiratory conditions in 6 (23.1%; lymphangiomyelomatosis in one), tumors in 3 (11.5%), suicide in 2 (7.7%), cardiopulmonary in 2 (7.7%), shunt malfunction in one, and drowning in one. For SUDEP cases, mean age of epilepsy onset was 7 months and 10/11 were treated with multiple anti-seizure medications (ASMs) at death; 7 had intractable epilepsy and 3 were controlled with ASMs. Patients with TSC and their families should be counseled about ASM adherence and lifestyle factors, and the potential role of nocturnal supervision or seizure detection devices to prevent SUDEP.

Parkinson's disease medication treatment planning is generally based on subjective data obtained through clinical, physician-patient interactions. The Personal KinetiGraphâ„¢ (PKG) and similar wearable sensors have shown promise in enabling objective, continuous remote health monitoring for Parkinson's patients. In this proof-of-concept study, we propose to use objective sensor data from the PKG and apply machine learning to cluster patients based on levodopa regimens and response. The resulting clusters are then used to enhance treatment planning by providing improved initial treatment estimates to supplement a physician's initial assessment. We apply k-means clustering to a dataset of within-subject Parkinson's medication changes-clinically assessed by the MDS-Unified Parkinson's Disease Rating Scale-III (MDS-UPDRS-III) and the PKG sensor for movement staging. A random forest classification model was then used to predict patients' cluster allocation based on their respective demographic information, MDS-UPDRS-III scores, and PKG time-series data. Clinically relevant clusters were partitioned by levodopa dose, medication administration frequency, and total levodopa equivalent daily dose-with the PKG providing similar symptomatic assessments to physician MDS-UPDRS-III scores. A random forest classifier trained on demographic information, MDS-UPDRS-III scores, and PKG time-series data was able to accurately classify subjects of the two most demographically similar clusters with an accuracy of 86.9%, an F1 score of 90.7%, and an AUC of 0.871. A model that relied solely on demographic information and PKG time-series data provided the next best performance with an accuracy of 83.8%, an F1 score of 88.5%, and an AUC of 0.831, hence further enabling fully remote assessments. These computational methods demonstrate the feasibility of using sensor-based data to cluster patients based on their medication responses with further potential to assist with medication recommendations.

INTRODUCTION/BACKGROUND:Flow diverters such as the pipeline embolization device (PED) cause hemodynamic changes of the treated vessel segment. In posterior communicating artery (PcomA), aneurysms' unique anatomic consideration have to be taken in account due to the connection between the anterior and posterior circulation. We hypothesize that in conjunction with PcomA remodeling, there will also be remodeling of the ipsilateral P1 segment of the posterior cerebral artery (PCA) after PED treatment for PcomA aneurysms. METHODS:We retrospectively collected radiological as well as clinical data of PcomA aneurysm patients treated with PED including PcomA and P1 vessel diameters before and after treatment as well as patient and aneurysm characteristics. RESULTS:= 0.042). There were no neurologic complications on LFU. CONCLUSION/CONCLUSIONS:In the treatment of PcomA aneurysms with PED, the P1 segment of the PCA increases in diameter while the PcomA diameter decreases. Our results suggest that this remodeling effect is associated with aneurysm occlusion and decrease of PcomA is hemodynamically compensated for by an increase in the ipsilateral P1 diameter.