Epilepsy Benchmarks Area III: Improved Treatment Options for Controlling Seizures and Epilepsy-Related Conditions Without Side Effects.

The goals of Epilepsy Benchmark Area III involve identifying areas that are ripe for progress in terms of controlling seizures and patient symptoms in light of the most recent advances in both basic and clinical research. These goals were developed with an emphasis on potential new therapeutic strategies that will reduce seizure burden and improve quality of life for patients with epilepsy. In particular, we continue to support the proposition that a better understanding of how seizures are initiated, propagated, and terminated in different forms of epilepsy is central to enabling new approaches to treatment, including pharmacological as well as surgical and device-oriented approaches. The stubbornly high rate of treatment-resistant epilepsy-one-third of patients-emphasizes the urgent need for new therapeutic strategies, including pharmacological, procedural, device linked, and genetic. The development of new approaches can be advanced by better animal models of seizure initiation that represent salient features of human epilepsy, as well as humanized models such as induced pluripotent stem cells and organoids. The rapid advances in genetic understanding of a subset of epilepsies provide a path to new and direct patient-relevant cellular and animal models, which could catalyze conceptualization of new treatments that may be broadly applicable across multiple forms of epilepsies beyond those arising from variation in a single gene. Remarkable advances in machine learning algorithms and miniaturization of devices and increases in computational power together provide an enhanced opportunity to detect and mitigate seizures in real time via devices that interrupt electrical activity directly or administer effective pharmaceuticals. Each of these potential areas for advance will be discussed in turn

DNM1 encephalopathy: A new disease of vesicle fission.

ObjectiveTo evaluate the phenotypic spectrum caused by mutations in dynamin 1 (DNM1), encoding the presynaptic protein DNM1, and to investigate possible genotype-phenotype correlations and predicted functional consequences based on structural modeling.MethodsWe reviewed phenotypic data of 21 patients (7 previously published) with DNM1 mutations. We compared mutation data to known functional data and undertook biomolecular modeling to assess the effect of the mutations on protein function.ResultsWe identified 19 patients with de novo mutations in DNM1 and a sibling pair who had an inherited mutation from a mosaic parent. Seven patients (33.3%) carried the recurrent p.Arg237Trp mutation. A common phenotype emerged that included severe to profound intellectual disability and muscular hypotonia in all patients and an epilepsy characterized by infantile spasms in 16 of 21 patients, frequently evolving into Lennox-Gastaut syndrome. Two patients had profound global developmental delay without seizures. In addition, we describe a single patient with normal development before the onset of a catastrophic epilepsy, consistent with febrile infection-related epilepsy syndrome at 4 years. All mutations cluster within the GTPase or middle domains, and structural modeling and existing functional data suggest a dominant-negative effect on DMN1 function.ConclusionsThe phenotypic spectrum of DNM1-related encephalopathy is relatively homogeneous, in contrast to many other genetic epilepsies. Up to one-third of patients carry the recurrent p.Arg237Trp variant, which is now one of the most common recurrent variants in epileptic encephalopathies identified to date. Given the predicted dominant-negative mechanism of this mutation, this variant presents a prime target for therapeutic intervention

Crisis Standard of Care: Management of Infantile Spasms during COVID‐19

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156180/2/ana25792_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156180/1/ana25792.pd

Delineating the GRIN1 phenotypic spectrum: a distinct genetic NMDA receptor encephalopathy

Objective:To determine the phenotypic spectrum caused by mutations in GRIN1 encoding the NMDA receptor subunit GluN1 and to investigate their underlying functional pathophysiology.Methods:We collected molecular and clinical data from several diagnostic and research cohorts. Functional consequences of GRIN1 mutations were investigated in Xenopus laevis oocytes.Results:We identified heterozygous de novo GRIN1 mutations in 14 individuals and reviewed the phenotypes of all 9 previously reported patients. These 23 individuals presented with a distinct phenotype of profound developmental delay, severe intellectual disability with absent speech, muscular hypotonia, hyperkinetic movement disorder, oculogyric crises, cortical blindness, generalized cerebral atrophy, and epilepsy. Mutations cluster within transmembrane segments and result in loss of channel function of varying severity with a dominant-negative effect. In addition, we describe 2 homozygous GRIN1 mutations (1 missense, 1 truncation), each segregating with severe neurodevelopmental phenotypes in consanguineous families.Conclusions:De novo GRIN1 mutations are associated with severe intellectual disability with cortical visual impairment as well as oculomotor and movement disorders being discriminating phenotypic features. Loss of NMDA receptor function appears to be the underlying disease mechanism. The identification of both heterozygous and homozygous mutations blurs the borders of dominant and recessive inheritance of GRIN1-associated disorders.Johannes R. Lemke (32EP30_136042/1) and Peter De Jonghe (G.A.136.11.N and FWO/ESF-ECRP) received financial support within the EuroEPINOMICS-RES network (www.euroepinomics.org) within the Eurocores framework of the European Science Foundation (ESF). Saskia Biskup and Henrike Heyne received financial support from the German Federal Ministry for Education and Research (BMBF IonNeurONet: 01 GM1105A and FKZ: 01EO1501). Katia Hardies is a PhD fellow of the Institute for Science and Technology (IWT) Flanders. Ingo Helbig was supported by intramural funds of the University of Kiel, by a grant from the German Research Foundation (HE5415/3-1) within the EuroEPINOMICS framework of the European Science Foundation, and additional grants of the German Research Foundation (DFG, HE5415/5-1, HE 5415/6-1), German Ministry for Education and Research (01DH12033, MAR 10/012), and grant by the German chapter of the International League against Epilepsy (DGfE). The project also received infrastructural support through the Institute of Clinical Molecular Biology in Kiel, supported in part by DFG Cluster of Excellence "Inflammation at Interfaces" and "Future Ocean." The project was also supported by the popgen 2.0 network (P2N) through a grant from the German Ministry for Education and Research (01EY1103) and by the International Coordination Action (ICA) grant G0E8614N. Christel Depienne, Caroline Nava, and Delphine Heron received financial support for exome analyses by the Centre National de Genotypage (CNG, Evry, France)

De Novo Mutations in SLC1A2 and CACNA1A Are Important Causes of Epileptic Encephalopathies

Epileptic encephalopathies (EEs) are the most clinically important group of severe early-onset epilepsies. Next-generation sequencing has highlighted the crucial contribution of de novo mutations to the genetic architecture of EEs as well as to their underlying genetic heterogeneity. Our previous whole-exome sequencing study of 264 parent-child trios revealed more than 290 candidate genes in which only a single individual had a de novo variant. We sought to identify additional pathogenic variants in a subset (n = 27) of these genes via targeted sequencing in an unsolved cohort of 531 individuals with a diverse range of EEs. We report 17 individuals with pathogenic variants in seven of the 27 genes, defining a genetic etiology in 3.2% of this unsolved cohort. Our results provide definitive evidence that de novo mutations in SLC1A2 and CACNA1A cause specific EEs and expand the compendium of clinically relevant genotypes for GABRB3. We also identified EEs caused by genetic variants in ALG13, DNM1, and GNAO1 and report a mutation in IQSEC2. Notably, recurrent mutations accounted for 7/17 of the pathogenic variants identified. As a result of high-depth coverage, parental mosaicism was identified in two out of 14 cases tested with mutant allelic fractions of 5%–6% in the unaffected parents, carrying significant reproductive counseling implications. These results confirm that dysregulation in diverse cellular neuronal pathways causes EEs, and they will inform the diagnosis and management of individuals with these devastating disorders

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

Ultra-rare genetic variation in common epilepsies: a case-control sequencing study

BACKGROUND:Despite progress in understanding the genetics of rare epilepsies, the more common epilepsies have proven less amenable to traditional gene-discovery analyses. We aimed to assess the contribution of ultra-rare genetic variation to common epilepsies. METHODS:We did a case-control sequencing study with exome sequence data from unrelated individuals clinically evaluated for one of the two most common epilepsy syndromes: familial genetic generalised epilepsy, or familial or sporadic non-acquired focal epilepsy. Individuals of any age were recruited between Nov 26, 2007, and Aug 2, 2013, through the multicentre Epilepsy Phenome/Genome Project and Epi4K collaborations, and samples were sequenced at the Institute for Genomic Medicine (New York, USA) between Feb 6, 2013, and Aug 18, 2015. To identify epilepsy risk signals, we tested all protein-coding genes for an excess of ultra-rare genetic variation among the cases, compared with control samples with no known epilepsy or epilepsy comorbidity sequenced through unrelated studies. FINDINGS:We separately compared the sequence data from 640 individuals with familial genetic generalised epilepsy and 525 individuals with familial non-acquired focal epilepsy to the same group of 3877 controls, and found significantly higher rates of ultra-rare deleterious variation in genes established as causative for dominant epilepsy disorders (familial genetic generalised epilepsy: odd ratio [OR] 2·3, 95% CI 1·7-3·2, p=9·1 × 10-8; familial non-acquired focal epilepsy 3·6, 2·7-4·9, p=1·1 × 10-17). Comparison of an additional cohort of 662 individuals with sporadic non-acquired focal epilepsy to controls did not identify study-wide significant signals. For the individuals with familial non-acquired focal epilepsy, we found that five known epilepsy genes ranked as the top five genes enriched for ultra-rare deleterious variation. After accounting for the control carrier rate, we estimate that these five genes contribute to the risk of epilepsy in approximately 8% of individuals with familial non-acquired focal epilepsy. Our analyses showed that no individual gene was significantly associated with familial genetic generalised epilepsy; however, known epilepsy genes had lower p values relative to the rest of the protein-coding genes (p=5·8 × 10-8) that were lower than expected from a random sampling of genes. INTERPRETATION:We identified excess ultra-rare variation in known epilepsy genes, which establishes a clear connection between the genetics of common and rare, severe epilepsies, and shows that the variants responsible for epilepsy risk are exceptionally rare in the general population. Our results suggest that the emerging paradigm of targeting of treatments to the genetic cause in rare devastating epilepsies might also extend to a proportion of common epilepsies. These findings might allow clinicians to broadly explain the cause of these syndromes to patients, and lay the foundation for possible precision treatments in the future. FUNDING:National Institute of Neurological Disorders and Stroke (NINDS), and Epilepsy Research UK

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Genome-wide identification and phenotypic characterization of seizure-associated copy number variations in 741,075 individuals

Copy number variants (CNV) are established risk factors for neurodevelopmental disorders with seizures or epilepsy. With the hypothesis that seizure disorders share genetic risk factors, we pooled CNV data from 10,590 individuals with seizure disorders, 16,109 individuals with clinically validated epilepsy, and 492,324 population controls and identified 25 genome-wide significant loci, 22 of which are novel for seizure disorders, such as deletions at 1p36.33, 1q44, 2p21-p16.3, 3q29, 8p23.3-p23.2, 9p24.3, 10q26.3, 15q11.2, 15q12-q13.1, 16p12.2, 17q21.31, duplications at 2q13, 9q34.3, 16p13.3, 17q12, 19p13.3, 20q13.33, and reciprocal CNVs at 16p11.2, and 22q11.21. Using genetic data from additional 248,751 individuals with 23 neuropsychiatric phenotypes, we explored the pleiotropy of these 25 loci. Finally, in a subset of individuals with epilepsy and detailed clinical data available, we performed phenome-wide association analyses between individual CNVs and clinical annotations categorized through the Human Phenotype Ontology (HPO). For six CNVs, we identified 19 significant associations with specific HPO terms and generated, for all CNVs, phenotype signatures across 17 clinical categories relevant for epileptologists. This is the most comprehensive investigation of CNVs in epilepsy and related seizure disorders, with potential implications for clinical practice