Epilepsy is one of the most common neurological disorders and has enormous impact, both medical and social, for the individual as well as for the family. Treatments developed for epilepsy have largely been empirical rather than derived from knowledge of basic mechanisms, because the mechanisms underlying seizure occurrence and epileptogenesis are poorly understood. The Epilepsy Phenome/Genome Project (EPGP) is a large-scale, national, multi-institutional, collaborative research project aimed at advancing our understanding of the genetic basis of the most common forms of idiopathic and cryptogenic epilepsies and a subset of symptomatic epilepsy;i.e. epilepsies that are probably related to genetic predispositions or developmental anomalies rather than endogenous, acquired factors such as CNS infection, head trauma or stroke. The overall strategy of EPGP is to collect detailed, high quality phenotypic information on 3,750 epilepsy patients and 3,000 controls, and to use state-of-the-art genomic and computational methods to identify the contribution of genetic variation to: 1) the epilepsy phenotype, 2) developmental anomalies of the brain, and 3) the varied therapeutic response of patients treated with AEDs. The EPGP Consortium was formed 3 years ago and is comprised of 15 U.S. academic institutions and organized into administrative and scientific cores. Through funding from a planning grant, the Consortium has already planned enrollment protocols, data collection methods, analytical approaches, and much of the infrastructure necessary for carrying out the proposed studies. The application of powerful high-throughput methodologies will permit us to efficiently perform the large- scale genotyping and other analyses described in this application. These studies will allow us to address critical unresolved questions concerning the underlying genomic mechanisms behind the most common forms of epilepsy, which are poorly understood, and to advance our understanding of the genetics of variable drug response. Timely data-sharing and the establishment of patient cell lines through the NINDS Human Genetics Repository will greatly facilitate the work of other epilepsy investigators throughout the country. Importantly, EPGP directly matches one of the high-priority, strategic objectives of NINDS as specified in Benchmark B2 of the Benchmarks for Epilepsy Research: """"""""Organize a national group of scientists to work together in search of genes that might contribute to epilepsy by doing a large screening project that links people with epilepsy to particular gene patterns.""""""""

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project--Cooperative Agreements (U01)
Project #
3U01NS053998-05S2
Application #
8603145
Study Section
Program Officer
Stewart, Randall R
Project Start
2013-01-15
Project End
2014-04-30
Budget Start
2013-01-15
Budget End
2014-04-30
Support Year
5
Fiscal Year
2013
Total Cost
$219,608
Indirect Cost
$1,174
Name
University of California San Francisco
Department
Neurology
Type
Schools of Medicine
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94143
Robbins, Nathaniel M; Larimer, Phillip; Bourgeois, James A et al. (2016) Number of patient-reported allergies helps distinguish epilepsy from psychogenic nonepileptic seizures. Epilepsy Behav 55:174-7
Winawer, Melodie R; Shih, Jerry; Beck, Erin S et al. (2016) Genetic effects on sleep/wake variation of seizures. Epilepsia 57:557-65
Chong, Derek J; Dugan, Patricia; EPGP Investigators (2016) Ictal fear: Associations with age, gender, and other experiential phenomena. Epilepsy Behav 62:153-8
Wietstock, S O; Bonifacio, S L; Sullivan, J E et al. (2016) Continuous Video Electroencephalographic (EEG) Monitoring for Electrographic Seizure Diagnosis in Neonates: A Single-Center Study. J Child Neurol 31:328-32
Broix, Loïc; Jagline, Hélène; L Ivanova, Ekaterina et al. (2016) Mutations in the HECT domain of NEDD4L lead to AKT-mTOR pathway deregulation and cause periventricular nodular heterotopia. Nat Genet 48:1349-1358
Halvorsen, Matt; Petrovski, Slavé; Shellhaas, Renée et al. (2016) Mosaic mutations in early-onset genetic diseases. Genet Med 18:746-9
Fallil, Zianka; Pardoe, Heath; Bachman, Robert et al. (2015) Phenotypic and imaging features of FLNA-negative patients with bilateral periventricular nodular heterotopia and epilepsy. Epilepsy Behav 51:321-7
McGovern, Kathleen; Karn, Catharine Freyer; Fox, Kristen et al. (2015) Surpassing the Target: How a Recruitment Campaign Transformed the Participant Accrual Trajectory in the Epilepsy Phenome/Genome Project. Clin Transl Sci 8:518-25
Epilepsy Phenome/Genome Project Epi4K Consortium (2015) Copy number variant analysis from exome data in 349 patients with epileptic encephalopathy. Ann Neurol 78:323-8
Pardoe, Heath R; Mandelstam, Simone A; Hiess, Rebecca Kucharsky et al. (2015) Quantitative assessment of corpus callosum morphology in periventricular nodular heterotopia. Epilepsy Res 109:40-7

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