A specific deficit of auditory processing in children with Rolandic Epilepsy and their relatives

Previous research shows that children with Rolandic Epilepsy have deficits of auditory processing. We wanted to confirm the nature of this deficit and whether it aggregates in families. We compared 40 children with Rolandic Epilepsy and 32 unaffected siblings with 99 typically developing children and 71 parents of RE children with 31 healthy adults on a battery of auditory processing tests. We also examined ear advantage in children with RE, their siblings and parents using population norms and measured non-word reading performance. We found a specific deficit for competing words in patients, their siblings and their parents, suggesting that this particular impairment of auditory processing present in children with RE, is heritable and likely to be persistent. Importantly, scores on this subtest in patients and siblings were significantly correlated with non-word reading performance. We saw increased rates of atypical left ear advantage in patients and siblings but no evidence of this in parents. We present these findings as evidence of familial incidence of dichotic listening and ear advantage abnormalities in relatives of children with Rolandic Epilepsy

Investment Planning to Minimize Climate Risk in Agricultural Production

The primary aim of this study is to prioritize investment required for scaling up climate-smart agriculture (CSA) technologies across different districts of Telangana state, which is in the semi-arid region of India. First, we analysed the trade-offs between expected agricultural income and its deviation across districts under drought and normal weather scenarios. The conventional MOTAD model was extended with various climate-smart technologies to assess their role in minimizing the trade-offs under various weather scenarios. A district-level panel dataset on cost of cultivation and crop production for 11 major crops under six different climate-smart technologies and farmers’ traditional practices (FTPs) for five years (2010-11 to 2014-15) has been used. The dataset comprised a collation of official statistics on cost of cultivation, focus group interviews with farmers over the years, and data from experimental plots of Regional Agricultural Research Stations. The analysis reveals that the adoption of CSA technologies is likely to reduce production risk by 16% compared to FTPs while achieving optimum levels of crop income. Under a scenario of higher probability of drought, production risk is likely to increase by 12% in the state under FTPs; the adoption of CSA technologies could reduce the risk by 25%. The study suggests increasing investments in farm ponds and un-puddled machine transplanting in rice to minimize the risk-return trade-offs under a higher drought frequency scenario. Finally, the study generates evidence for policymakers to make informed investment decisions on CSA in order to enhance farming systems resilience across districts in the semi-arid state of Telangana, India

Climate change induced salinity intrusion and its implications for agriculture

An estimated 1.06 million hectare of arable land in Bangladesh and 6.7 million hectares in India is affected by salinity (Rabbani 2013). Salinity intrusion adversely affects the livelihoods of farmers, especially rice cultivators and fisherfolks, vegetations, soil quality, and infrastructure in these areas (Habiba et al. 2014). The net cropped area in coastal Bangladesh has been decreasing over the last few years due to several factors and many studies have identified salinity as the chief cause for yield reduction in coastal agriculture (Baten 2015). Groundwater contamination due to saline water and similar adverse impacts on agriculture and livelihoods are also increasing in coastal India, especially in Kerala, Karnataka, Odisha, and Andhra Pradesh (Naidu et al. 2013). The extent and intensity of salinity in the coming years are likely to increase due to climate change induced saltwater intrusion

Phenotypic and genetic spectrum of epilepsy with myoclonic atonic seizures

Objective We aimed to describe the extent of neurodevelopmental impairments and identify the genetic etiologies in a large cohort of patients with epilepsy with myoclonic atonic seizures (MAE). Methods We deeply phenotyped MAE patients for epilepsy features, intellectual disability, autism spectrum disorder, and attention-deficit/hyperactivity disorder using standardized neuropsychological instruments. We performed exome analysis (whole exome sequencing) filtered on epilepsy and neuropsychiatric gene sets to identify genetic etiologies. Results We analyzed 101 patients with MAE (70% male). The median age of seizure onset was 34 months (range = 6-72 months). The main seizure types were myoclonic atonic or atonic in 100%, generalized tonic-clonic in 72%, myoclonic in 69%, absence in 60%, and tonic seizures in 19% of patients. We observed intellectual disability in 62% of patients, with extremely low adaptive behavioral scores in 69%. In addition, 24% exhibited symptoms of autism and 37% exhibited attention-deficit/hyperactivity symptoms. We discovered pathogenic variants in 12 (14%) of 85 patients, including five previously published patients. These were pathogenic genetic variants in SYNGAP1 (n = 3), KIAA2022 (n = 2), and SLC6A1 (n = 2), as well as KCNA2, SCN2A, STX1B, KCNB1, and MECP2 (n = 1 each). We also identified three new candidate genes, ASH1L, CHD4, and SMARCA2 in one patient each. Significance MAE is associated with significant neurodevelopmental impairment. MAE is genetically heterogeneous, and we identified a pathogenic genetic etiology in 14% of this cohort by exome analysis. These findings suggest that MAE is a manifestation of several etiologies rather than a discrete syndromic entity.Peer reviewe

Core Health Outcomes In Childhood Epilepsy (CHOICE):Protocol for the selection of a core outcome set

This is the final version of the article. Available from BioMed Central via the DOI in this record.BACKGROUND: There is increasing recognition that establishing a core set of outcomes to be evaluated and reported in trials of interventions for particular conditions will improve the usefulness of health research. There is no established core outcome set for childhood epilepsy. The aim of this work is to select a core outcome set to be used in evaluative research of interventions for children with rolandic epilepsy, as an exemplar of common childhood epilepsy syndromes. METHODS: First we will identify what outcomes should be measured; then we will decide how to measure those outcomes. We will engage relevant UK charities and health professional societies as partners, and convene advisory panels for young people with epilepsy and parents of children with epilepsy. We will identify candidate outcomes from a search for trials of interventions for childhood epilepsy, statutory guidance and consultation with our advisory panels. Families, charities and health, education and neuropsychology professionals will be invited to participate in a Delphi survey following recommended practices in the development of core outcome sets. Participants will be able to recommend additional outcome domains. Over three rounds of Delphi survey participants will rate the importance of candidate outcome domains and state the rationale for their decisions. Over the three rounds we will seek consensus across and between families and health professionals on the more important outcomes. A face-to-face meeting will be convened to ratify the core outcome set. We will then review and recommend ways to measure the shortlisted outcomes using clinical assessment and/or patient-reported outcome measures. DISCUSSION: Our methodology is a proportionate and pragmatic approach to expediently produce a core outcome set for evaluative research of interventions aiming to improve the health of children with epilepsy. A number of decisions have to be made when designing a study to develop a core outcome set including defining the scope, choosing which stakeholders to engage, most effective ways to elicit their views, especially children and a potential role for qualitative research.This study is part of Changing Agendas on Sleep, Treatment and Learning in Childhood Epilepsy (CASTLE), which is funded by the National Institute for Health Research (NIHR) Programme Grants for Applied Research RP-PG-0615-20007

Remote and long-term self-monitoring of electroencephalographic and noninvasive measurable variables at home in patients with epilepsy (EEG@HOME) : protocol for an observational study

©Andrea Biondi, Petroula Laiou, Elisa Bruno, Pedro F Viana, Martijn Schreuder, William Hart, Ewan Nurse, Deb K Pal, Mark P Richardson. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 19.03.2021. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be included.Background: Epileptic seizures are spontaneous events that severely affect the lives of patients due to their recurrence and unpredictability. The integration of new wearable and mobile technologies to collect electroencephalographic (EEG) and extracerebral signals in a portable system might be the solution to prospectively identify times of seizure occurrence or propensity. The performances of several seizure detection devices have been assessed by validated studies, and patient perspectives on wearables have been explored to better match their needs. Despite this, there is a major gap in the literature on long-term, real-life acceptability and performance of mobile technology essential to managing chronic disorders such as epilepsy. Objective: EEG@HOME is an observational, nonrandomized, noninterventional study that aims to develop a new feasible procedure that allows people with epilepsy to independently, continuously, and safely acquire noninvasive variables at home. The data collected will be analyzed to develop a general model to predict periods of increased seizure risk. Methods: A total of 12 adults with a diagnosis of pharmaco-resistant epilepsy and at least 20 seizures per year will be recruited at King's College Hospital, London. Participants will be asked to self-apply an easy and portable EEG recording system (ANT Neuro) to record scalp EEG at home twice daily. From each serial EEG recording, brain network ictogenicity (BNI), a new biomarker of the propensity of the brain to develop seizures, will be extracted. A noninvasive wrist-worn device (Fitbit Charge 3; Fitbit Inc) will be used to collect non-EEG biosignals (heart rate, sleep quality index, and steps), and a smartphone app (Seer app; Seer Medical) will be used to collect data related to seizure occurrence, medication taken, sleep quality, stress, and mood. All data will be collected continuously for 6 months. Standardized questionnaires (the Post-Study System Usability Questionnaire and System Usability Scale) will be completed to assess the acceptability and feasibility of the procedure. BNI, continuous wrist-worn sensor biosignals, and electronic survey data will be correlated with seizure occurrence as reported in the diary to investigate their potential values as biomarkers of seizure risk. Results: The EEG@HOME project received funding from Epilepsy Research UK in 2018 and was approved by the Bromley Research Ethics Committee in March 2020. The first participants were enrolled in October 2020, and we expect to publish the first results by the end of 2022. Conclusions: With the EEG@HOME study, we aim to take advantage of new advances in remote monitoring technology, including self-applied EEG, to investigate the feasibility of long-term disease self-monitoring. Further, we hope our study will bring new insights into noninvasively collected personalized risk factors of seizure occurrence and seizure propensity that may help to mitigate one of the most difficult aspects of refractory epilepsy: the unpredictability of seizure occurrenceThis study is funded by Epilepsy Research UK (award 1803). MPR, PFV, and EN are supported by the Epilepsy Foundation of America’s Epilepsy Innovation Institute My Seizure Gauge grant.info:eu-repo/semantics/publishedVersio

Heterogeneity of resting-state EEG features in juvenile myoclonic epilepsy and controls

Abnormal EEG features are a hallmark of epilepsy, and abnormal frequency and network features are apparent in EEGs from people with idiopathic generalized epilepsy in both ictal and interictal states. Here, we characterize differences in the resting-state EEG of individuals with juvenile myoclonic epilepsy and assess factors influencing the heterogeneity of EEG features. We collected EEG data from 147 participants with juvenile myoclonic epilepsy through the Biology of Juvenile Myoclonic Epilepsy study. Ninety-five control EEGs were acquired from two independent studies [Chowdhury et al. (2014) and EU-AIMS Longitudinal European Autism Project]. We extracted frequency and functional network-based features from 10 to 20 s epochs of resting-state EEG, including relative power spectral density, peak alpha frequency, network topology measures and brain network ictogenicity: a computational measure of the propensity of networks to generate seizure dynamics. We tested for differences between epilepsy and control EEGs using univariate, multivariable and receiver operating curve analysis. In addition, we explored the heterogeneity of EEG features within and between cohorts by testing for associations with potentially influential factors such as age, sex, epoch length and time, as well as testing for associations with clinical phenotypes including anti-seizure medication, and seizure characteristics in the epilepsy cohort. P-values were corrected for multiple comparisons. Univariate analysis showed significant differences in power spectral density in delta (2–5 Hz) (P = 0.0007, hedges’ g = 0.55) and low-alpha (6–9 Hz) (P = 2.9 × 10−8, g = 0.80) frequency bands, peak alpha frequency (P = 0.000007, g = 0.66), functional network mean degree (P = 0.0006, g = 0.48) and brain network ictogenicity (P = 0.00006, g = 0.56) between epilepsy and controls. Since age (P = 0.009) and epoch length (P = 1.7 × 10−8) differed between the two groups and were potential confounders, we controlled for these covariates in multivariable analysis where disparities in EEG features between epilepsy and controls remained. Receiver operating curve analysis showed low-alpha power spectral density was optimal at distinguishing epilepsy from controls, with an area under the curve of 0.72. Lower average normalized clustering coefficient and shorter average normalized path length were associated with poorer seizure control in epilepsy patients. To conclude, individuals with juvenile myoclonic epilepsy have increased power of neural oscillatory activity at low-alpha frequencies, and increased brain network ictogenicity compared with controls, supporting evidence from studies in other epilepsies with considerable external validity. In addition, the impact of confounders on different frequency-based and network-based EEG features observed in this study highlights the need for careful consideration and control of these factors in future EEG research in idiopathic generalized epilepsy particularly for their use as biomarkers

Core Health Outcomes in Childhood Epilepsy (CHOICE): Development of a core outcome set using systematic review methods and a Delphi survey consensus.

This is the final version. Available from the publisher via the DOI in this record.OBJECTIVE: Establishing a core set of outcomes to be evaluated and reported in intervention trials aims to improve the usefulness of health research. There is no established core outcome set (COS) for childhood epilepsies. The aim of this study was to select a COS to be used in evaluative research of interventions for children with rolandic epilepsy (RE). METHODS: We followed guidance from the COMET (Core Outcome Measures in Effectiveness Trials) Initiative. First, we identified outcomes that had been measured in research through a systematic review. Second, young people with RE, parents, and professionals were invited to take part in a Delphi survey in which participants rated the importance of candidate outcomes. Last, a face-to-face meeting was convened to seek consensus on which outcomes were critical to include and to ratify the final COS. RESULTS: From 37 eligible papers in the review, we identified and included 48 candidate outcomes in the survey. We sent invitations to 165 people registered to take part in the survey; of these, 102 (62%) completed Round 1, and 80 (78%) completed Round 2 (three young people, 16 parents, 61 professionals). In Round 2 we included four additional outcomes suggested by participants in Round 1. The consensus meeting included two young people, four parents, and nine professionals who were eligible to vote and ratified the COS as 39 outcomes across 10 domains. SIGNIFICANCE: Our methodology was a proportionate and pragmatic approach toward producing a COS for evaluating research on interventions aiming to improve the health of children with RE.National Institute for Health Research (NIHR

The L1624Q Variant in SCN1A Causes Familial Epilepsy Through a Mixed Gain and Loss of Channel Function

Variants of the SCN1A gene encoding the neuronal voltage-gated sodium channel NaV1.1 cause over 85% of all cases of Dravet syndrome, a severe and often pharmacoresistent epileptic encephalopathy with mostly infantile onset. But with the increased availability of genetic testing for patients with epilepsy, variants in SCN1A have now also been described in a range of other epilepsy phenotypes. The vast majority of these epilepsy-associated variants are de novo, and most are either nonsense variants that truncate the channel or missense variants that are presumed to cause loss of channel function. However, biophysical analysis has revealed a significant subset of missense mutations that result in increased excitability, further complicating approaches to precision pharmacotherapy for patients with SCN1A variants and epilepsy. We describe clinical and biophysical data of a familial SCN1A variant encoding the NaV1.1 L1624Q mutant. This substitution is located on the extracellular linker between S3 and S4 of Domain IV of NaV1.1 and is a rare case of a familial SCN1A variant causing an autosomal dominant frontal lobe epilepsy. We expressed wild-type (WT) and L1642Q channels in CHO cells. Using patch-clamp to characterize channel properties at several temperatures, we show that the L1624Q variant increases persistent current, accelerates fast inactivation onset and decreases current density. While SCN1A-associated epilepsy is typically considered a loss-of-function disease, our results put L1624Q into a growing set of mixed gain and loss-of-function variants in SCN1A responsible for epilepsy