Simulation of InSight Plume Induced Surface Cratering and Validation Through Imagery Based 3D Topology Reconstruction

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GWAS meta-analysis of over 29,000 people with epilepsy identifies 26 risk loci and subtype-specific genetic architecture

Epilepsy is a highly heritable disorder affecting over 50 million people worldwide, of which about one-third are resistant to current treatments. Here we report a multi-ancestry genome-wide association study including 29,944 cases, stratified into three broad categories and seven subtypes of epilepsy, and 52,538 controls. We identify 26 genome-wide significant loci, 19 of which are specific to genetic generalized epilepsy (GGE). We implicate 29 likely causal genes underlying these 26 loci. SNP-based heritability analyses show that common variants explain between 39.6% and 90% of genetic risk for GGE and its subtypes. Subtype analysis revealed markedly different genetic architectures between focal and generalized epilepsies. Gene-set analyses of GGE signals implicate synaptic processes in both excitatory and inhibitory neurons in the brain. Prioritized candidate genes overlap with monogenic epilepsy genes and with targets of current antiseizure medications. Finally, we leverage our results to identify alternate drugs with predicted efficacy if repurposed for epilepsy treatment

Heritage Contests: What Can We Learn from Social Movements?

© 2018 Informa UK Limited, trading as Taylor & Francis Group. While contests and conflicts are well recognized in heritage research, analysis of the specific circumstances and dilemmas that individuals and groups face when pursuing heritage goals and partaking in heritage contests can benefit from further methodological work. This paper presents a case and method for incorporating concepts from an emerging interactionist perspective on social movements into heritage research in order to better conceptualize and analyze the interactions and processes through which collective identity and heritage is co-produced. We examine the political and interpretive processes at the heart of heritage research, consider areas in which the language and concepts of social movements addresses existing gaps and disagreements, and identify a set of questions that will open new perspectives on heritage movements and contests. We apply these questions to a heritage contest over the World Heritage site of Pasargadae in Iran, emphasizing how heritage activists advanced their perspectives and claims, eventually leading to the incorporation of Iran’s pre-Islamic heritage within the official Islamic republic discourse

Analysis of shared common genetic risk between amyotrophic lateral sclerosis and epilepsy

Because hyper-excitability has been shown to be a shared pathophysiological mechanism, we used the latest and largest genome-wide studies in amyotrophic lateral sclerosis (n = 36,052) and epilepsy (n = 38,349) to determine genetic overlap between these conditions. First, we showed no significant genetic correlation, also when binned on minor allele frequency. Second, we confirmed the absence of polygenic overlap using genomic risk score analysis. Finally, we did not identify pleiotropic variants in meta-analyses of the 2 diseases. Our findings indicate that amyotrophic lateral sclerosis and epilepsy do not share common genetic risk, showing that hyper-excitability in both disorders has distinct origins

Using common genetic variants to find drugs for common epilepsies

Abstract Better drugs are needed for common epilepsies. Drug repurposing offers the potential of significant savings in the time and cost of developing new treatments. In order to select the best candidate drug(s) to repurpose for a disease, it is desirable to predict the relative clinical efficacy that drugs will have against the disease. Common epilepsy can be divided into different types and syndromes. Different antiseizure medications are most effective for different types and syndromes of common epilepsy. For predictions of antiepileptic efficacy to be clinically translatable, it is essential that the predictions are specific to each form of common epilepsy, and reflect the patterns of drug efficacy observed in clinical studies and practice. These requirements are not fulfilled by previously published drug predictions for epilepsy. We developed a novel method for predicting the relative efficacy of drugs against any common epilepsy, by using its Genome-Wide Association Study summary statistics and drugs’ activity data. The methodological advancement in our technique is that the drug predictions for a disease are based upon drugs’ effects on the function and abundance of proteins, and the magnitude and direction of those effects, relative to the importance, degree and direction of the proteins’ dysregulation in the disease. We used this method to predict the relative efficacy of all drugs, licensed for any condition, against each of the major types and syndromes of common epilepsy. Our predictions are concordant with findings from real-world experience and randomized clinical trials. Our method predicts the efficacy of existing antiseizure medications against common epilepsies; in this prediction, our method outperforms the best alternative existing method: area under receiver operating characteristic curve (mean ± standard deviation) 0.83 ± 0.03 and 0.63 ± 0.04, respectively. Importantly, our method predicts which antiseizure medications are amongst the more efficacious in clinical practice, and which antiseizure medications are amongst the less efficacious in clinical practice, for each of the main syndromes of common epilepsy, and it predicts the distinct order of efficacy of individual antiseizure medications in clinical trials of different common epilepsies. We identify promising candidate drugs for each of the major syndromes of common epilepsy. We screen five promising predicted drugs in an animal model: each exerts a significant dose-dependent effect upon seizures. Our predictions are a novel resource for selecting suitable candidate drugs that could potentially be repurposed for each of the major syndromes of common epilepsy. Our method is potentially generalizable to other complex diseases.</jats:p

Genome-wide mega-analysis identifies 16 loci and highlights diverse biological mechanisms in the common epilepsies

The epilepsies affect around 65 million people worldwide and have a substantial missing heritability component. We report a genome-wide mega-analysis involving 15,212 individuals with epilepsy and 29,677 controls, which reveals 16 genome-wide significant loci, of which 11 are novel. Using various prioritization criteria, we pinpoint the 21 most likely epilepsy genes at these loci, with the majority in genetic generalized epilepsies. These genes have diverse biological functions, including coding for ion-channel subunits, transcription factors and a vitamin-B6 metabolism enzyme. Converging evidence shows that the common variants associated with epilepsy play a role in epigenetic regulation of gene expression in the brain. The results show an enrichment for monogenic epilepsy genes as well as known targets of antiepileptic drugs. Using SNP-based heritability analyses we disentangle both the unique and overlapping genetic basis to seven different epilepsy subtypes. Together, these findings provide leads for epilepsy therapies based on underlying pathophysiology