Biomarkers for epileptogenesis after brain injury

脑损伤后癫痫发生的生物标志物

• 批准号: 8727125
• 负责人: F. Edward DUDEK
• 金额: $ 63.49万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2018-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8727125
• 关键词: Address; Adverse effects; Algorithms; Animals; Anterior; Antiepileptogenic; Appearance; Biological Markers; Brain; Brain Hypoxia-Ischemia; Brain Injuries; Chronic; Clinical; Clinical Research; Clinical Trials; Computer software; Computers; Control Groups; Data; Descriptor; Detection; Development; Devices; Disease; Electroencephalography; Epilepsy; Epileptogenesis; Exhibits; Exposure to; Frequencies; Future; Guidelines; Human; Hypoxia; Incidence; Injury; Knowledge; Lateral; Lesion; Liquid substance; Location; Logistic Models; Logistic Regressions; Modeling; Motor Cortex; Multivariate Analysis; Natural History; Nature; Patients; Percussion; Predictive Value; Rattus; Relative (related person); Reporting; Rice; Rice Rats; Risk; Risk Factors; Sampling; Seizures; Sensitivity and Specificity; Sensory; Severities; Specificity; Staging; Techniques; Telemetry; Testing; Tetanus Toxin; Time; Trauma; Traumatic Brain Injury; Treatment Efficacy; Uncertainty; United States National Institutes of Health; Video Recording; base; clinically relevant; design; experience; improved; injured; innovation; kainate; mature animal; novel; postnatal; preclinical study; predictive modeling; public health relevance; research study; time interval; tool; young adult

DESCRIPTION (provided by applicant): The latent period between brain injury and subsequent epilepsy is months to years in duration, providing a unique window for antiepileptogenic therapy. Recent reports of promising experimental disease-modifying therapies can't advance to clinical trials until three hurdles are overcome: First, quantification f epilepsy is necessary to assess efficacy of interventions, but epilepsy after brain injury is very difficult to quantify: the latency to first seizure is long and variable, and early seizures are ofen subtle, infrequent, and clustered between long inter-cluster intervals. Second, because of the long latency between injury and epilepsy, clinical trials need to be quite prolonged and therefore prohibitively expensive. Third, because ~ 20% of moderately brain-injured patients develop epilepsy, most of the treated patients could not benefit from long-term antiepileptogenic therapy, despite exposure to the risks and side effects. These three hurdles could be overcome with sufficiently accurate biomarkers. We recently demonstrated that early electrographic epileptiform activity is a promising predictor of epilepsy after brain injury induced by kainic aci. Here we propose to address critical knowledge gaps regarding electrographic biomarkers of epileptogenesis. The predictive power of electrographic biomarkers has not been assessed after more clinically relevant injuries such as trauma and hypoxic-ischemic injury. The predictive power of electrographic biomarkers has not been systematically compared to the predictive power of traditional physical descriptors of injury, such as lesion size and location. Furthermore, it has not been determined whether combining electrographic and physical-injury parameters would improve their predictive power. We will employ well-established models of clinical injuries, the lateral fluid percussion (LFP) trauma model and the Rice- Vannucci model of focal hypoxia-ischemia in P30 rats. The incidence of epilepsy in these models is close to the human experience, and thus provides a more rigorous test of the predictive power of these biomarkers than the kainate model. Further, the latency to seizures is sufficiently long in these models to enable testing as to whether the appearance of early electrographic biomarkers is more closely related to the time elapsed since the injury, or to the time remaining prior to the first seizure; he nature of these relationships will significantly impact the design of clinical studies of these biomarkers. In Aim 1, we will use a novel miniature telemetry device for continuous recording of video-EEG together with validated, unbiased computer detection algorithms to quantify early epileptiform activity and seizures in these brain injury models. We will optimize EEG sampling and develop the best predictive model based on epileptiform electrographic activity and injury descriptors, and then prospectively test this model in a second group of animals. In Aim 2, we will use the same approach to test whether early electrographic epileptiform activity and injury descriptors predict the severity of epilepsy, including latency to first seizure and seizure frequency, once epilepsy is fully developed.

描述(申请人提供)：从脑损伤到随后的癫痫发作之间的潜伏期为数月至数年，为抗癫痫治疗提供了一个独特的窗口。最近关于有希望的实验性疾病改变疗法的报道只有克服三个障碍才能进入临床试验：首先，癫痫的量化对于评估干预的有效性是必要的，但脑损伤后的癫痫很难量化：首次癫痫发作的潜伏期很长且可变，早期癫痫发作往往很轻微，不常见，并且在长的簇间间隔之间聚集。其次，由于损伤和癫痫之间的潜伏期很长，临床试验需要相当长的时间，因此成本高得令人望而却步。第三，由于约20%的中度脑损伤患者会发生癫痫，尽管存在风险和副作用，但大多数接受治疗的患者无法从长期的抗癫痫治疗中受益。这三个障碍可以通过足够准确的生物标志物来克服。我们最近证实，早期的脑电癫痫样活动是海人ACI所致脑损伤后癫痫的一个有前景的预测指标。在这里，我们建议解决有关癫痫发生的电信号生物标记物的关键知识空白。在更多临床相关的损伤，如创伤和缺氧缺血损伤后，还没有对电动生物标志物的预测能力进行评估。电信号生物标志物的预测能力还没有系统地与传统的损伤物理描述指标(如损伤大小和位置)的预测能力进行比较。此外， 目前还没有确定将脑电和物理损伤参数结合起来是否会提高它们的预测能力。我们将采用成熟的临床损伤模型，侧向液压冲击(LFP)创伤模型和P30大鼠局灶性缺氧-缺血的莱斯-万努奇模型。在这些模型中，癫痫的发病率接近人类经验，因此提供了比海人模型更严格的对这些生物标志物预测能力的测试。此外，在这些模型中，癫痫发作的潜伏期足够长，从而能够测试早期电信号生物标记物的出现是否与损伤后经过的时间或第一次癫痫发作前的剩余时间更密切相关；这些关系的性质将显著影响对这些生物标记物的临床研究的设计。在目标1中，我们将使用一种新型的微型遥测设备来连续记录视频-脑电，并结合经过验证的、无偏的计算机检测算法来量化这些脑损伤模型中的早期癫痫样活动和癫痫发作。我们将优化脑电采样，开发基于癫痫样电活动和损伤描述符的最佳预测模型，然后在第二组动物中前瞻性地测试该模型。在目标2中，我们将使用相同的方法来测试一旦癫痫完全发展，早期脑电癫痫样活动和损伤描述符是否可以预测癫痫的严重程度，包括首次发作的潜伏期和发作频率。