We propose a planning grant titled the Epilepsy Bioinformatics Study (EpiBioS) to develop a bioinformatics approach to identify reliable epilepsy biomarkers, a critical need for a Center without Walls (CwW) focused on antiepileptogenesis (AEG). Biomarkers of epileptogenesis are needed to limit the study population by identifying those patients at highest risk for epilepsy after a potential epileptogenic brain insult, and to stage the epileptogenic process. Biomarkers of epileptogenicity are needed as surrogate markers in Phase II clinical trials, to document prevention or cure. From existing animal and patient data, we hypothesize that the three most promising classes of biomarkers will be derived from longitudinal studies of electroencephalographic (EEG), neuroimaging, and molecular changes occurring during the process of epileptogenesis, and existing after the development of epilepsy. Furthermore, we anticipate that no single reliable biomarker will emerge, but that predictive power will require a combination of biomarkers. To jumpstart the search for biomarkers we will utilize existing bioinformatics platforms to analyze available multimodality data longitudinally collected from patients and animals during development of epilepsy, and with epilepsy, to identify the most likely individual biomarkers, and/or combinations of biomarkers of epileptogenesis and epileptogenicity, and to determine the best animal models for future studies. Anticipated problems will be addressed at semiannual focused workshops. At the end of this granting period we intend to submit three deliverables: 1) identification and validation of the most likely biomarkers using data derived from ongoing animal and human studies;2) comprehensive position papers on strategy and problem solving derived from at least six workshops, and 3) an international, multimodality, interactive, open access, bioinformatics grid available for a large prospective clinical study of biomarkers of epileptogenesis and epileptogenicity. We also intend to use the results of this study to inform investigations into the basic mechanisms of epileptogenesis and the search for novel targets for AEG, essential to the CwW, and anticipate this bioinformatics approach to be the future of biomedical research.

Public Health Relevance

Epilepsy is a common serious disorder of the brain. Because most epilepsy is acquired, there is a great need for interventions that might prevent epilepsy following potential causative brain insults. The search for preventive interventions would be greatly facilitated by the identification of biomarkers that could diagnose individuals who are at risk for epilepsy, and validate prevention. The Epilepsy Bioinformatics Study (EpiBioS) will develop a bioinformatics approach that can he used to identify biomarkers for this purpose.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Exploratory Grants (P20)
Project #
3P20NS080181-02S1
Application #
8724827
Study Section
Special Emphasis Panel (ZNS1-SRB-B (33))
Program Officer
Fureman, Brandy E
Project Start
2012-09-01
Project End
2015-08-31
Budget Start
2013-09-01
Budget End
2014-08-31
Support Year
2
Fiscal Year
2013
Total Cost
$152,000
Indirect Cost
$57,000
Name
University of California Los Angeles
Department
Neurology
Type
Schools of Medicine
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
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Engel Jr, Jerome; Bragin, Anatol; Staba, Richard (2018) Nonictal EEG biomarkers for diagnosis and treatment. Epilepsia Open 3:120-126
Engel Jr, Jerome (2018) The current place of epilepsy surgery. Curr Opin Neurol 31:192-197
Tubi, Meral A; Lutkenhoff, Evan; Blanco, Manuel Buitrago et al. (2018) Early seizures and temporal lobe trauma predict post-traumatic epilepsy: A longitudinal study. Neurobiol Dis :
Kerr, Wesley T; Janio, Emily A; Braesch, Chelsea T et al. (2018) An objective score to identify psychogenic seizures based on age of onset and history. Epilepsy Behav 80:75-83
Frauscher, Birgit; Bartolomei, Fabrice; Kobayashi, Katsuhiro et al. (2017) High-frequency oscillations: The state of clinical research. Epilepsia 58:1316-1329
Kerr, Wesley T; Janio, Emily A; Braesch, Chelsea T et al. (2017) Identifying psychogenic seizures through comorbidities and medication history. Epilepsia 58:1852-1860
Jozwiak, Sergiusz; Becker, Albert; Cepeda, Carlos et al. (2017) WONOEP appraisal: Development of epilepsy biomarkers-What we can learn from our patients? Epilepsia 58:951-961
Kerr, Wesley T; Janio, Emily A; Braesch, Chelsea T et al. (2017) Diagnostic implications of review-of-systems questionnaires to differentiate epileptic seizures from psychogenic seizures. Epilepsy Behav 69:69-74

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