The primary goal of the Epi4K Center Without Walls is to increase understanding of the genetic basis of human epilepsy in order to improve the well-being of patients and family members living with these disorders. This improvement will come in the form of better diagnostics, treatments and cures. To accomplish this goal, Epi4K aims to analyze the genomes of a large number of well-phenotyped epilepsy patients and families collected by investigators from several major research groups. A critical aspect of this enterprise, and the main goal of the Epi4K Phenotyping and Clinical Informatics (PCI) Core described here, is to assemble, organize and validate the phenotypic information on all patients proposed for genomic analysis, and to insure that patients'DNA samples are available to the Epi4K Sequencing, Biostatistics and Bioinformatics (SBB) Core when needed. The availability of well-documented, high quality phenotype data is obviously crucial to the success of all four proposed projects in Epi4K, since the detection of meaningful phenotype:genotype associations will depend highly on phenotype validity. However, achieving this goal in Epi4K will require substantial effort for two main reasons. First, the diagnosis and classification of the epilepsies, including clinical characteristics such as seizure type, seizure semiology, therapeutic response, and additional features such as intellectual and neurological deficits, rests primarily on clinica observations, which are prone to subjectivity and often poorly described or interpreted. Second, Epi4K will assemble at least seven different cohorts of patients collected using varied phenotyping methodologies. To address these challenges, we will capitalize on the substantial experience of the PCI Core investigators, all of whom have devoted considerable portions of their careers to developing methods for accurately phenotyping epilepsy. In addition, through the work of the Epilepsy Phenome/Genome Project (EPGP), we have already created data review systems and a highly efficient informatics infrastructure that can be adapted to the needs of Epi4K. With these resources in hand, the PCI Core seeks to accomplish the following specific aims: 1) to establish standards for documentation of epilepsy phenotypes that can be used reliably across different sites for all subjects undergoing genetic analyses in Epi4K;2) to design and implement an informatics infrastructure for an Epi4K Phenotype Data Repository and DNA Sample Tracking System;and 3) to validate the phenotype data associated with every DNA sample submitted for genome analyses.

Public Health Relevance

Epilepsy is one of the most common neurological disorders in humans, affecting up to 3% of the population. Although there is a strong genetic component for epilepsy, there are still only a few genes known. The Epi4K project will identify new genes and genetic pathways in epilepsy and will directly benefit individuals with epilepsy and their families through improved diagnostic, prognostic and recurrence risk information. Epi4K will also advance our understanding of the biological basis of epilepsy, which is essential for the development of new and effective treatments, as well as cures. Disclaimer: Please note that the following critiques were prepared by the reviewers prior to the Study Section meeting and are provided in an essentially unedited form. While there is opportunity for the reviewers to update or revise their written evaluation, based upon the group's discussion, there is no guarantee that individual critiques have been updated subsequent to the discussion at the meeting. Therefore, the critiques may not fully reflect the final opinions of th individual reviewers at the close of group discussion or the final majority opinion of the group. Thus the Resume and Summary of Discussion is the final word on what the reviewers actually considered critical at the meeting.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01NS077276-03
Application #
8533048
Study Section
Special Emphasis Panel (ZNS1-SRB-B (29))
Program Officer
Stewart, Randall R
Project Start
2011-09-30
Project End
2016-08-31
Budget Start
2013-09-01
Budget End
2014-08-31
Support Year
3
Fiscal Year
2013
Total Cost
$702,247
Indirect Cost
$189,381
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
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Liu, Yongzhuang; Li, Bingshan; Tan, Renjie et al. (2014) A gradient-boosting approach for filtering de novo mutations in parent-offspring trios. Bioinformatics 30:1830-6
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