Biomarkers for epileptogenesis after brain injury

描述（由申请人提供）：脑损伤和后续癫痫之间的潜伏期为数月至数年，为抗癫痫治疗提供了独特的窗口。最近关于有希望的实验性疾病修饰疗法的报道在克服三个障碍之前无法进入临床试验：首先，量化癫痫对于评估干预措施的有效性是必要的，但是脑损伤后的癫痫非常难以量化：首次癫痫发作的潜伏期很长且可变，早期癫痫发作通常是微妙的，罕见的，并且在长的簇间间隔之间聚集。第二，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，因此成本过高。第三，由于约20%的中度脑损伤患者发生癫痫，尽管暴露于风险和副作用，但大多数接受治疗的患者无法从长期抗癫痫治疗中获益。这三个障碍可以通过足够准确的生物标志物来克服。我们最近证明早期电图癫痫样活动是海人藻酸诱导脑损伤后癫痫的一个有希望的预测指标。在这里，我们建议解决关键的知识差距，关于癫痫发生的电图生物标志物。电图生物标志物的预测能力尚未评估后，更临床相关的损伤，如创伤和缺氧缺血性损伤。电图生物标志物的预测能力尚未与损伤的传统物理描述符（如病变大小和位置）的预测能力进行系统比较。此外，委员会认为， 尚未确定结合电图和物理损伤参数是否会提高其预测能力。我们将采用完善的临床损伤模型，侧向液压冲击（LFP）创伤模型和P30大鼠局灶性缺氧缺血的Rice-Vannucci模型。这些模型中癫痫的发病率接近人类经验，因此提供了比红藻氨酸模型更严格的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图生物标志物的出现是否与损伤后经过的时间或首次癫痫发作前剩余的时间更密切相关;这些关系的性质将显著影响这些生物标志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，用于连续记录视频EEG，并使用经过验证的无偏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EEG采样，并根据癫痫样电图活动和损伤描述符开发最佳预测模型，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早期电描记癫痫样活动和损伤描述符是否预测癫痫的严重程度，包括癫痫完全发展后首次癫痫发作的潜伏期和癫痫发作频率。

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.