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ObjectiveParoxysmal epileptiform abnormalities on electroencephalography (EEG) are the hallmark of epilepsies, but it is uncertain to what extent epilepsy and background EEG oscillations share neurobiological underpinnings. Here, we aimed to assess the genetic correlation between epilepsy and background EEG oscillations.MethodsConfounding factors, including the heterogeneous etiology of epilepsies and medication effects, hamper studies on background brain activity in people with epilepsy. To overcome this limitation, we compared genetic data from a genome-wide association study (GWAS) on epilepsy (n = 12 803 people with epilepsy and 24 218 controls) with that from a GWAS on background EEG (n = 8425 subjects without epilepsy), in which background EEG oscillation power was quantified in four different frequency bands: alpha, beta, delta, and theta. We replicated our findings in an independent epilepsy replication dataset (n = 4851 people with epilepsy and 20 428 controls). To assess the genetic overlap between these phenotypes, we performed genetic correlation analyses using linkage disequilibrium score regression, polygenic risk scores, and Mendelian randomization analyses.ResultsOur analyses show strong genetic correlations of genetic generalized epilepsy (GGE) with background EEG oscillations, primarily in the beta frequency band. Furthermore, we show that subjects with higher beta and theta polygenic risk scores have a significantly higher risk of having generalized epilepsy. Mendelian randomization analyses suggest a causal effect of GGE genetic liability on beta oscillations.SignificanceOur results point to shared biological mechanisms underlying background EEG oscillations and the susceptibility for GGE, opening avenues to investigate the clinical utility of background EEG oscillations in the diagnostic workup of epilepsy.

ObjectiveClassification of epilepsy into types and subtypes is important for both clinical care and research into underlying disease mechanisms. A quantitative, data-driven approach may augment traditional electroclinical classification and shed new light on existing classification frameworks.MethodsWe used latent class analysis, a statistical method that assigns subjects into groups called latent classes based on phenotypic elements, to classify individuals with common familial epilepsies from the Epi4K Multiplex Families study. Phenotypic elements included seizure types, seizure symptoms, and other elements of the medical history. We compared class assignments to traditional electroclinical classifications and assessed familial aggregation of latent classes.ResultsA total of 1120 subjects with epilepsy were assigned to five latent classes. Classes 1 and 2 contained subjects with generalized epilepsy, largely reflecting the distinction between absence epilepsies and younger onset (class 1) versus myoclonic epilepsies and older onset (class 2). Classes 3 and 4 contained subjects with focal epilepsies, and in contrast to classes 1 and 2, these did not adhere as closely to clinically defined focal epilepsy subtypes. Class 5 contained nearly all subjects with febrile seizures plus or unknown epilepsy type, as well as a few subjects with generalized epilepsy and a few with focal epilepsy. Family concordance of latent classes was similar to or greater than concordance of clinically defined epilepsy types.SignificanceQuantitative classification of epilepsy has the potential to augment traditional electroclinical classification by (1) combining some syndromes into a single class, (2) splitting some syndromes into different classes, (3) helping to classify subjects who could not be classified clinically, and (4) defining the boundaries of clinically defined classifications. This approach can guide future research, including molecular genetic studies, by identifying homogeneous sets of individuals that may share underlying disease mechanisms.

Treatment for Angelman syndrome (AS) is currently limited to symptomatic interventions. A mouse model of AS has reduced calcium/calmodulin-dependent kinase II activity due to excessive phosphorylation of specific threonine residues, leading to diminished long-term potentiation. In a rat model of Parkinson disease, levodopa reduced phosphorylation of various proteins, including calcium/calmodulin-dependent kinase II. Further studies demonstrated that AS mice treated with levodopa performed better on rotarod testing than untreated AS mice. We conducted a multi-center double-blind randomized placebo-controlled 1-year trial of levodopa / carbidopa with either 10 or 15 mg/kg/day of levodopa in children with AS. The outcome of this intervention was assessed using either the Bayley Scales of Infant Development or the Mullen Scales of Early Learning, as well as the Vineland Adaptive Behavior Scales, and the Aberrant Behavior Checklist. Of the 78 participants enrolled, 67 participants received study medication (33 on levodopa, 34 on placebo), and 55 participants (29 on levodopa, 26 on placebo) completed the 1-year study. There were no clinically or statistically significant changes in any of the outcome measures over a 1-year period comparing the levodopa and placebo groups. The number of adverse events reported, including the more serious adverse events, was similar in both groups, but none were related to treatment with levodopa. Our data demonstrate that levodopa is well-tolerated by children with AS. However, in the doses used in this study, it failed to improve their neurodevelopment or behavioral outcome.

Gene identification in epilepsy has mainly been limited to large families segregating genes of major effect and de novo mutations in epileptic encephalopathies. Many families that present with common non-acquired focal epilepsies and genetic generalized epilepsies remain unexplained. We assembled a cohort of 'genetically enriched' common epilepsies by collecting and phenotyping families containing multiple individuals with unprovoked seizures. We aimed to determine if specific clinical epilepsy features aggregate within families, and whether this segregation of phenotypes may constitute distinct 'familial syndromes' that could inform genomic analyses. Families with three or more individuals with unprovoked seizures were studied across multiple international centres. Affected individuals were phenotyped and classified according to specific electroclinical syndromes. Families were categorized based on syndromic groupings of affected family members, examined for pedigree structure and phenotypic patterns and, where possible, assigned specific familial epilepsy syndromes. A total of 303 families were assembled and analysed, comprising 1120 affected phenotyped individuals. Of the 303 families, 117 exclusively segregated generalized epilepsy, 62 focal epilepsy, and 22 were classified as genetic epilepsy with febrile seizures plus. Over one-third (102 families) were observed to have mixed epilepsy phenotypes: 78 had both generalized and focal epilepsy features within the same individual (n = 39), or within first or second degree relatives (n = 39). Among the genetic generalized epilepsy families, absence epilepsies were found to cluster within families independently of juvenile myoclonic epilepsy, and significantly more females were affected than males. Of the 62 familial focal epilepsy families, two previously undescribed familial focal syndrome patterns were evident: 15 families had posterior quadrant epilepsies, including seven with occipito-temporal localization and seven with temporo-parietal foci, and four families displayed familial focal epilepsy of childhood with multiple affected siblings that was suggestive of recessive inheritance. The findings suggest (i) specific patterns of syndromic familial aggregation occur, including newly recognized forms of familial focal epilepsy; (ii) although syndrome-specificity usually occurs in multiplex families, the one-third of families with features of both focal and generalized epilepsy is suggestive of shared genetic determinants; and (iii) patterns of features observed across families including pedigree structure, sex, and age of onset may hold clues for future gene identification. Such detailed phenotypic information will be invaluable in the conditioning and interpretation of forthcoming sequencing data to understand the genetic architecture and inter-relationships of the common epilepsy syndromes.

Primary waves produced by large ships in confined waterways can threaten the sustainability and safety of coastal regions near maritime shipping routes, but the present understanding and predictability of primary wave shallow-water characteristics is hindered by a scarcity of available field observations. This study presents hydrodynamic measurements from 296 primary waves observed in 3.5 to 4.4 m mean water depth throughout four deployments on the channel margins of the Savannah River in Georgia, USA. Ship details and tidally varying waterway parameters are paired with pressure and fluid velocity data to investigate relationships between ship characteristics, waterway conditions, and primary wave magnitudes. Findings show that although larger and faster ships tend to produce larger primary waves, there are inconsistencies among the magnitudes of waves generated by similar ship passages. Additionally, depression prediction equations perform well for most observations, but a small group of "atypically-large" primary waves with depressions exceeding 75 cm are consistently underpredicted and require further investigation. Hydrodynamic, waterway, and ship data are made available in the Supplemental Data. [ABSTRACT FROM AUTHOR]

Emerging evidence indicates that epileptic encephalopathies are genetically highly heterogeneous, underscoring the need for large cohorts of well-characterized individuals to further define the genetic landscape. Through a collaboration between two consortia (EuroEPINOMICS and Epi4K/EPGP), we analyzed exome-sequencing data of 356 trios with the "classical" epileptic encephalopathies, infantile spasms and Lennox Gastaut syndrome, including 264 trios previously analyzed by the Epi4K/EPGP consortium. In this expanded cohort, we find 429 de novo mutations, including de novo mutations in DNM1 in five individuals and de novo mutations in GABBR2, FASN, and RYR3 in two individuals each. Unlike previous studies, this cohort is sufficiently large to show a significant excess of de novo mutations in epileptic encephalopathy probands compared to the general population using a likelihood analysis (p = 8.2 × 10(-4)), supporting a prominent role for de novo mutations in epileptic encephalopathies. We bring statistical evidence that mutations in DNM1 cause epileptic encephalopathy, find suggestive evidence for a role of three additional genes, and show that at least 12% of analyzed individuals have an identifiable causal de novo mutation. Strikingly, 75% of mutations in these probands are predicted to disrupt a protein involved in regulating synaptic transmission, and there is a significant enrichment of de novo mutations in genes in this pathway in the entire cohort as well. These findings emphasize an important role for synaptic dysregulation in epileptic encephalopathies, above and beyond that caused by ion channel dysfunction.

BackgroundEpilepsy is a common neurological disorder that affects approximately 50 million people worldwide. Both risk of epilepsy and response to treatment partly depend on genetic factors, and gene identification is a promising approach to target new prediction, treatment, and prevention strategies. However, despite significant progress in the identification of genes causing epilepsy in families with a Mendelian inheritance pattern, there is relatively little known about the genetic factors responsible for common forms of epilepsy and so-called epileptic encephalopathies. Study design The Epilepsy Phenome/Genome Project (EPGP) is a multi-institutional, retrospective phenotype-genotype study designed to gather and analyze detailed phenotypic information and DNA samples on 5250 participants, including probands with specific forms of epilepsy and, in a subset, parents of probands who do not have epilepsy.ResultsEPGP is being executed in four phases: study initiation, pilot, study expansion/establishment, and close-out. This article discusses a number of key challenges and solutions encountered during the first three phases of the project, including those related to (1) study initiation and management, (2) recruitment and phenotyping, and (3) data validation. The study has now enrolled 4223 participants.ConclusionsEPGP has demonstrated the value of organizing a large network into cores with specific roles, managed by a strong Administrative Core that utilizes frequent communication and a collaborative model with tools such as study timelines and performance-payment models. The study also highlights the critical importance of an effective informatics system, highly structured recruitment methods, and expert data review.

The behavior of rip currents with changing bar and gap lengths was tested in a series of laboratory experiments using video-tracked floating drifters. Qualitatively, currents showed strong differences in overall character with changing topography. As narrow gaps became wider, the circulation tended to first travel parallel to the shoreline instead of immediately offshore, although strong offshore-directed flows were found for all topographies. Quantitatively, the width of the rip neck was found to increase slowly when compared to the increasing width of the rip channel. Maximum offshore and longshore velocities showed little dependence on bar or gap lengths, and were found to scale well with the predicted rate of generation of circulation. Finally, volumetric offshore flow rates through the rip channel showed no proportionality with the bar length as predicted by the mass transport hypothesis of rip current strength. DOI: 10.1061/(ASCE)0733-950X(2008)134:1(61) CE Database subject headings: Rip currents; Topography; Drift; Water circulation; Return flow.

This paper describes nonintrusive optical techniques to measure large-scale O(10 m x 10 m) flows in a laboratory wave basin. Numerous drifters with weak positive flotation are tracked discretely and automatically using a video camera mounted near the laboratory ceiling. Processed drifter tracks are used for dense estimates of mean surface currents over the visible area. Examination of the drifter tracks also shows that waves are imaged and therefore basic wave properties may also be estimated, although this requires some further assumptions. These video based flow observations are presumed to have less precision than in situ measurements; however, the density of measurements from the video far exceeds that which can be obtained using fixed instruments, providing the method's major advantage. DOI: 10.1061/(ASCE)0733-950X(2008)134:1(12) CE Database subject headings: Wave measurement: Basins; Laboratory tests; Velocity.

The ocean contains a variety of renewable energy resources, little of which has been exploited. Here, we review both tidal range and tidal stream energy, with a focus on the resource, feedbacks, and environmental interactions. The review covers a wide range of timescales of relevance to tidal energy, from fortnightly (spring-neap) and semi-diurnal variability, down to array, and device-scale turbulence. When simulating the regional tidal energy resource, and to assess environmental impacts, it is necessary to account for feedbacks between the tidal array and the resource itself. We critically review various methods for simulating energy extraction, from insights gained through theoretical studies of "tidal fences" in idealized channels, to realistic three-dimensional model studies with complex geometry and arrays of turbines represented by momentum sinks and additional turbulence due to the presence of rotors and support structures. We discuss how variability can be reduced by developing multiple (aggregated) sites with a consideration of the enhanced phase diversity offered by exploiting less energetic tidal currents. This leads to future research questions that have not yet been explored in depth at first-generation tidal sites in relatively sheltered channels (e.g., the interaction of waves with currents). Such enhanced understanding of real sea conditions, including the effects of wind and waves, leads to our other identified primary future research direction—reduced uncertainties in turbulence predictions, including the development of realistic models that simulate the interaction between ambient turbulence and the turbulence resulting from multiple wakes, and changes to system-wide hydrodynamics, water quality, and sedimentation. [ABSTRACT FROM AUTHOR]

Objective: In patients with medically refractory focal epilepsy, stereotactic‐electroencephalography (SEEG) can aid in localizing epileptogenic regions for surgical treatment. SEEG, however, requires long hospitalizations to record seizures, and ictal interpretation can be incomplete or inaccurate. Our recent work showed that non‐directed resting‐state analyses may identify brain regions as epileptogenic or uninvolved. Our present objective is to map epileptogenic networks in greater detail and more accurately identify seizure‐onset regions using directed resting‐state SEEG connectivity. Methods: In 25 patients with focal epilepsy who underwent SEEG, 2 minutes of resting‐state, artifact‐free, SEEG data were selected and functional connectivity was estimated. Using standard clinical interpretation, brain regions were classified into four categories: ictogenic, early propagation, irritative, or uninvolved. Three non‐directed connectivity measures (mutual information [MI] strength, and imaginary coherence between and within regions) and four directed measures (partial directed coherence [PDC] and directed transfer function [DTF], inward and outward strength) were calculated. Logistic regression was used to generate a predictive model of ictogenicity. Results: Ictogenic regions had the highest and uninvolved regions had the lowest MI strength. Although both PDC and DTF inward strengths were highest in ictogenic regions, outward strengths did not differ among categories. A model incorporating directed and nondirected connectivity measures demonstrated an area under the receiver‐operating characteristic (ROC) curve (AUC) of 0.88 in predicting ictogenicity of individual regions. The AUC of this model was 0.93 when restricted to patients with favorable postsurgical seizure outcomes. Significance: Directed connectivity measures may help identify epileptogenic networks without requiring ictal recordings. Greater inward but not outward connectivity in ictogenic regions at rest may represent broad inhibitory input to prevent seizure generation. [ABSTRACT FROM AUTHOR]