The Epilepsy Bioinformatics Study (EpiBioS)

癫痫生物信息学研究 (EpiBioS)

• 批准号: 8386757
• 负责人: JEROME NONE ENGEL
• 金额: $ 48.47万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8386757
• 关键词: Address; Animal Model; Animals; Antiepileptogenic; Behavioral; Bioinformatics; Biological Markers; Biomedical Research; Blood; Brain; Brain Diseases; California; Cerebrospinal Fluid; Clinical; Clinical Data; Clinical Research; Clinical Trials; Collaborations; Craniocerebral Trauma; Data; Data Analyses; Development; Diagnosis; Documentation; Educational workshop; Electrophysiology (science); Epilepsy; Epileptogenesis; Fever; Future; Genetic; Grant; Human; Human Resources; Image; Individual; Injury; International; Internet; Intervention; Investigation; Laboratories; Longitudinal Studies; Los Angeles; Measures; Methods; Molecular; Paper; Patients; Pennsylvania; Phase II Clinical Trials; Population Study; Positioning Attribute; Post-Traumatic Epilepsy; Prevention; Preventive Intervention; Problem Solving; Process; Risk; Scalp structure; Seizures; Severities; Staging; Status Epilepticus; Structure; Surrogate Markers; System; Temporal Lobe Epilepsy; Time; Traumatic Brain Injury; Universities; Validation; computing resources; high risk; multimodality; neocortical; neuroimaging; novel; patient population; prevent; programs; prospective; public health relevance; tool

DESCRIPTION (provided by applicant): 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.

描述（由申请人提供）：我们提出一项名为癫痫生物信息学研究（EpiBioS）的计划拨款，以开发一种生物信息学方法来识别可靠的癫痫生物标志物，这是一个专注于抗癫痫发生（AEG）的无壁中心（CwW）的关键需求。需要癫痫发生的生物标志物来限制研究人群，通过识别那些在潜在的癫痫性脑损伤后癫痫风险最高的患者，并分期癫痫发生过程。在II期临床试验中，需要癫痫致性的生物标志物作为替代标志物，以记录预防或治疗。根据现有的动物和患者数据，我们假设三种最有希望的生物标志物将来自脑电图（EEG）、神经影像学和癫痫发生过程中发生的分子变化的纵向研究，以及癫痫发展后存在的分子变化。此外，我们预计不会出现单一可靠的生物标志物，但预测能力将需要生物标志物的组合。为了快速启动生物标志物的搜索，我们将利用现有的生物信息学平台来分析从癫痫发展期间和癫痫患者和动物纵向收集的可用多模态数据，以确定最可能的个体生物标志物和/或癫痫发生和癫痫致性生物标志物的组合，并确定未来研究的最佳动物模型。预计的问题将在每半年一次的重点研讨会上加以解决。在授权期结束时，我们打算提交三个可交付成果：1)鉴定和验证