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

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

Surpassing the Target: How a Recruitment Campaign Transformed the Participant Accrual Trajectory in the Epilepsy Phenome/Genome Project

Participant recruitment challenges pervade the majority of publicly funded clinical trials. However, little is known about methods for enhancing participant accrual. The Epilepsy Phenome/Genome Project (EPGP), a multicenter study funded by the National Institute of Neurological Disorders and Stroke (NINDS), aimed to enroll a total of 5,250 participants to better understand the genetic causes and phenotypic manifestations of epilepsy. However, similar to other trials, EPGP encountered recruitment challenges, and by the end of its first year, net enrollment was only 48% of the target for that time. To address this, EPGP established a National Participant Recruitment Campaign and began implementing and tracking the enrollment outcomes of a variety of proven and relatively novel recruitment methods. At the conclusion of the project, EPGP had successfully enrolled a total of 5,445 participants, thus surpassing its enrollment target. Data pertaining to EPGP's National Participant Recruitment Campaign was analyzed retrospectively, and the results are reported here, so that other multicenter trials may consider these methods in their recruitment planning and potentially avoid the costly repercussions of participant accrual issues

Return of individual results in epilepsy genomic research: A view from the field

Genomic findings are emerging rapidly in 2 large, closely related epilepsy research consortia: the Epilepsy Phenome/Genome Project and Epi4K. Disclosure of individual results to participants in genomic research is increasingly viewed as an ethical obligation, but strategies for return of results were not included in the design of these consortia, raising complexities in establishing criteria for which results to offer, determining participant preferences, managing the large number of sites involved, and covering associated costs. Here, we describe the challenges faced, alternative approaches considered, and progress to date. Experience from these 2 consortia illustrates the importance, for genomic research in epilepsy and other disorders, of including a specific plan for return of results in the study design, with financial support for obtaining clinical confirmation and providing ongoing support for participants. Participant preferences for return of results should be established at the time of enrollment, and methods for allowing future contacts with participants should be included. In addition, methods should be developed for summarizing meaningful, comprehensible information about findings in the aggregate that participants can access in an ongoing way

Heterozygous HNRNPU variants cause early onset epilepsy and severe intellectual disability

Pathogenic variants in genes encoding subunits of the spliceosome are the cause of several human diseases, such as neurodegenerative diseases. The RNA splicing process is facilitated by the spliceosome, a large RNA-protein complex consisting of small nuclear ribonucleoproteins (snRNPs), and many other proteins, such as heterogeneous nuclear ribonucleoproteins (hnRNPs). The HNRNPU gene (OMIM *602869) encodes the heterogeneous nuclear ribonucleoprotein U, which plays a crucial role in mammalian development. HNRNPU is expressed in the fetal brain and adult heart, kidney, liver, brain, and cerebellum. Microdeletions in the 1q44 region encompassing HNRNPU have been described in patients with intellectual disability (ID) and other clinical features, such as seizures, corpus callosum abnormalities (CCA), and microcephaly. Recently, pathogenic HNRNPU variants were identified in large ID and epileptic encephalopathy cohorts. In this study, we provide detailed clinical information of five novels and review two of the previously published individuals with (likely) pathogenic de novo variants in the HNRNPU gene including three non-sense and two missense variants, one small intragenic deletion, and one duplication. The phenotype in individuals with variants in HNRNPU is characterized by early onset seizures (6/7), severe ID (6/6), severe speech impairment (6/6), hypotonia (6/7), and central nervous system (CNS) (5/6), cardiac (4/6), and renal abnormalities (3/4). In this study, we broaden the clinical and mutational HNRNPU-associated spectrum, and demonstrate that heterozygous HNRNPU variants cause epilepsy, severe ID with striking speech impairment and variable CNS, cardiac, and renal anomalies

The epilepsy phenome/genome project.

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

Quantitative analysis of phenotypic elements augments traditional electroclinical classification of common familial epilepsies

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