? INFORMATICS AND ANALYTICS CORE The Informatics and Analytics Core (IAC) will centralize an enduring data archive and analytic tools that will allow the broader epilepsy research community to identify and validate biomarkers of epileptogenesis in images, electrophysiology, and molecular/serological/tissue studies. Beyond creating a centralized data repository, the IAC will pioneer innovative standardization/co-registration methods, fully supported by novel image and electrophysiology processing methods to extract candidate biomarkers from the diverse data. Not only will a well-curated and standardized multi-modal data set facilitate the development of models of epileptogenesis, it will also ensure that such models are statistically significant and can be validated. Based on our previous experience with similar multicenter projects, we are confident that our infrastructure will lead to success in this project. The amount of data to be collected in these studies is unprecedented: video-EEG from animals after TBI recorded continuously for 6 months, in addition to prolonged continuous ICU EEG recordings from humans and intermittent sampling of brain images, blood, and tissue data. To analyze these data properly, it requires a diverse, accomplished group of investigators spanning neurology, neuroscience, imaging, mathematics, engineering, and computer science, as well as collecting comprehensive data in parallel from humans and animal models after TBI. The IAC will be seamlessly integrated with Projects 1-3, assisting in collecting data and providing analytic tools that will lead to biomarkers of epileptogenesis. By combining new data capabilities and our powerful, best-in-class, interdisciplinary team, quantitative models of epileptogenesis may be possible. These types of models will enrich preclinical trial populations, expedite interventions to prevent epilepsy after brain insults, and document epilepsy before late seizures occur. Based on previous studies, it is likely that there are reproducible changes in biomarkers, which identify the presence of epilepsy before its overt clinical expression61,71,72. The IAC will bring big data techniques and rigorous analysis to longitudinal data collected from humans and animal models of TBI, epilepsy, and their interaction. It will develop and implement new approaches, including novel graphical methods to visualize multivariable interactions, to quantify phenotype and molecular profiles in these disorders. A first-rate bioinformatics platform, LONI, will focus on TBI and epileptogenesis research. The tools, pipelines, and protocols developed for this proposal will be made available to the epilepsy research community, with the potential to change, long-term, the way that images, video, electrophysiology, proteomics, and metadata are analyzed in these fields. Quantitative and data mining methods will enable investigators to record and analyze gold-standard data and create a shared bioinformatics resource for epilepsy research that will live on long after the end of this project. Perhaps most importantly, the IAC will provide the technical sophistication to tease out the interaction between the complex processes studied in Projects 1-3, integrating multi-modal data in a way that has been beyond the capability of a single laboratory or center. The IAC will provide a lasting and open platform for standardized biomarker research in both TBI and epilepsy as well as engage with and guide the projects that, together, will lead to future clinical trial development. !
? EPIBIOS4RX INFORMATICS AND ANALYTICS CORE A fundamental challenge in discovering treatments and associated biomarkers of epileptogenesis is that this process is likely multifactorial and crosses multiple modalities. Investigators must have access to a large number of high quality, well-curated data points and study subjects in order for biomarker signals to be detectable above the noise inherent in complex phenomena like epileptogenesis, TBI, and conditions of data collection. A central platform is needed to standardize data from different centers and different modalities and to provide tools for searching, viewing, annotating, and analyzing them. The Informatics and Analytics Core (IAC) will centralize an enduring data archive with analytic tools that will allow the broader epilepsy research community to identify and validate biomarkers of epileptogenesis in images, electrophysiology, and molecular/serological/tissue studies.
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|Barker-Haliski, Melissa L; Löscher, Wolfgang; White, H Steve et al. (2017) Neuroinflammation in epileptogenesis: Insights and translational perspectives from new models of epilepsy. Epilepsia 58 Suppl 3:39-47|
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|Fisher, Robert S; Cross, J Helen; D'Souza, Carol et al. (2017) Instruction manual for the ILAE 2017 operational classification of seizure types. Epilepsia 58:531-542|
|Shandra, Oleksii; Moshé, Solomon L; Galanopoulou, Aristea S (2017) Inflammation in Epileptic Encephalopathies. Adv Protein Chem Struct Biol 108:59-84|
|Harte-Hargrove, Lauren C; French, Jacqueline A; Pitkänen, Asla et al. (2017) Common data elements for preclinical epilepsy research: Standards for data collection and reporting. A TASK3 report of the AES/ILAE Translational Task Force of the ILAE. Epilepsia 58 Suppl 4:78-86|
|Kadam, Shilpa D; D'Ambrosio, Raimondo; Duveau, Venceslas et al. (2017) Methodological standards and interpretation of video-electroencephalography in adult control rodents. A TASK1-WG1 report of the AES/ILAE Translational Task Force of the ILAE. Epilepsia 58 Suppl 4:10-27|
|Hernan, Amanda E; Schevon, Catherine A; Worrell, Gregory A et al. (2017) Methodological standards and functional correlates of depth in vivo electrophysiological recordings in control rodents. A TASK1-WG3 report of the AES/ILAE Translational Task Force of the ILAE. Epilepsia 58 Suppl 4:28-39|
|Fisher, Robert S; Cross, J Helen; French, Jacqueline A et al. (2017) Operational classification of seizure types by the International League Against Epilepsy: Position Paper of the ILAE Commission for Classification and Terminology. Epilepsia 58:522-530|
|Nariai, Hiroki; Beal, Jules; Galanopoulou, Aristea S et al. (2017) Scalp EEG Ictal gamma and beta activity during infantile spasms: Evidence of focality. Epilepsia 58:882-892|
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