Major Histocompatibility Complex Class I (MHCI) proteins were first identified in the immune system but are also expressed in neurons and play a role in normal brain development and plasticity. However little is known about how, on a molecular level, MHCI modifies neuronal structure and function. Here we show that MHCI proteins interact with neuronal insulin receptors (IR) and are critical for their signaling. Dendritically expressed MHCI is closely apposed to axonally expressed IR in many brain regions, including hippocampus, and MHCI co- immunoprecipitates with IR from mouse hippocampal lysates. Unexpectedly, genetic reduction of cell surface MHCI in either [beta]2m-/-TAP-/- or Kb-/-Db-/- mice selectively alters antibody binding to an intracellular domain of the β-subunit of IR, which contains key tyrosine residues that are autophosphorylated following ligand binding. This loss of antibody binding can be rescued by co-culturing [beta]2m-/-TAP-/- neurons with wild-type neurons, suggesting MHCI and IR can interact in trans. Furthermore, [beta]2m-/-TAP-/- mice show an increase in basal tyrosine phosphorylation of IR. This increase in basal activation of IR correlates with an increase in synapse density in MHCI-deficient animals specifically in regions where IR are expressed. Together our results demonstrate that endogenous MHCI is a novel regulator of neuronal IR function and synapse number, and suggest that MHCI modifies a key c-terminal signaling domain of IR in neurons

This report represents a summary of the discussions led by the antiseizure treatment working group of the International League Against Epilepsy (ILAE)/American Epilepsy Society (AES) Working Groups joint meeting in London (London Meeting). We review here what is currently known about the pharmacologic characteristics of current models of refractory seizures, both for adult and pediatric epilepsy. In addition, we address how the National Institute of Neurological Disorders and Stroke (NINDS)-funded Anticonvulsant Screening Program (ASP) is evolving to incorporate appropriate animal models in the search for molecules that might be sufficiently novel to warrant further pharmacologic development. We also briefly address what we believe is necessary, going forward, to achieve the goal of stopping seizures in all patients, with a call to arms for funding agencies, the pharmaceutical industry, and basic researchers.

ADP-ribosylation, the addition of poly-ADP ribose (PAR) onto proteins, is a response signal to cellular challenges, such as excitotoxicity or oxidative stress. This process is catalyzed by a group of enzymes referred to as poly(ADP-ribose) polymerases (PARPs). Because the accumulation of proteins with this modification results in cell death, its negative regulation restores cellular homeostasis: a process mediated by poly-ADP ribose glycohydrolases (PARGs) and ADP-ribosylhydrolase proteins (ARHs). Using linkage analysis and exome or genome sequencing, we identified recessive inactivating mutations in ADPRHL2 in six families. Affected individuals exhibited a pediatric-onset neurodegenerative disorder with progressive brain atrophy, developmental regression, and seizures in association with periods of stress, such as infections. Loss of the Drosophila paralog Parg showed lethality in response to oxidative challenge that was rescued by human ADPRHL2, suggesting functional conservation. Pharmacological inhibition of PARP also rescued the phenotype, suggesting the possibility of postnatal treatment for this genetic condition.

Sequencing-based studies have identified novel risk genes associated with severe epilepsies and revealed an excess of rare deleterious variation in less-severe forms of epilepsy. To identify the shared and distinct ultra-rare genetic risk factors for different types of epilepsies, we performed a whole-exome sequencing (WES) analysis of 9,170 epilepsy-affected individuals and 8,436 controls of European ancestry. We focused on three phenotypic groups: severe developmental and epileptic encephalopathies (DEEs), genetic generalized epilepsy (GGE), and non-acquired focal epilepsy (NAFE). We observed that compared to controls, individuals with any type of epilepsy carried an excess of ultra-rare, deleterious variants in constrained genes and in genes previously associated with epilepsy; we saw the strongest enrichment in individuals with DEEs and the least strong in individuals with NAFE. Moreover, we found that inhibitory GABA_A receptor genes were enriched for missense variants across all three classes of epilepsy, whereas no enrichment was seen in excitatory receptor genes. The larger gene groups for the GABAergic pathway or cation channels also showed a significant mutational burden in DEEs and GGE. Although no single gene surpassed exome-wide significance among individuals with GGE or NAFE, highly constrained genes and genes encoding ion channels were among the lead associations; such genes included CACNA1G, EEF1A2, and GABRG2 for GGE and LGI1, TRIM3, and GABRG2 for NAFE. Our study, the largest epilepsy WES study to date, confirms a convergence in the genetics of severe and less-severe epilepsies associated with ultra-rare coding variation, and it highlights a ubiquitous role for GABAergic inhibition in epilepsy etiology.

Objective

Paroxysmal 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.

Methods

Confounding 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.

Results

Our 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.

Significance

Our 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.