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.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Exploratory Grants (P20)
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Special Emphasis Panel (ZNS1-SRB-B (33))
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Fureman, Brandy E
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University of California Los Angeles
Schools of Medicine
Los Angeles
United States
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Pitkänen, Asla; Engel Jr, Jerome (2014) Past and present definitions of epileptogenesis and its biomarkers. Neurotherapeutics 11:231-41
Engel Jr, Jerome; Dichter, Marc A (2014) Epilepsy. Foreword. Adv Exp Med Biol 813:v-xiii
Savic, Ivanka; Engel Jr, Jerome (2014) Structural and functional correlates of epileptogenesis - does gender matter? Neurobiol Dis 70:69-73
Dedeurwaerdere, Stefanie; Shultz, Sandy R; Federico, Paolo et al. (2014) Workshop on Neurobiology of Epilepsy appraisal: new systemic imaging technologies to study the brain in experimental models of epilepsy. Epilepsia 55:819-28
Hamid, Hamada; Blackmon, Karen; Cong, Xiangyu et al. (2014) Mood, anxiety, and incomplete seizure control affect quality of life after epilepsy surgery. Neurology 82:887-94
Engel Jr, Jerome; Thompson, Paul M; Stern, John M et al. (2013) Connectomics and epilepsy. Curr Opin Neurol 26:186-94