In vivo methods for preclinical analysis of cognitive therapies for schizophrenia

描述(申请人提供)：精神分裂症是一种破坏性的精神疾病，影响大约1%的全球人口。精神分裂症的症状可分为三类：阳性症状，如幻觉；阴性症状，如社交孤立和不适当的情绪反应；以及认知症状。精神分裂症的认知缺陷包括注意力受损和一种名为工作记忆的基本短期记忆中断。这些基本的认知过程对任务的执行至关重要，精神分裂症患者的这些认知过程的中断是导致精神分裂症患者无法在社会中发挥作用的关键因素。事实上，精神分裂症的认知缺陷已经被认为是这种疾病的核心组成部分。目前可用的治疗精神分裂症的方法可以改善阳性症状，但往往会产生显著的副作用，而且在治疗该疾病的阴性症状和认知症状方面并未被证明有效。作为精神分裂症的一个核心特征，这种疾病的认知缺陷代表着一个主要的未得到满足的医疗需求。寻找治疗精神分裂症认知缺陷的有效方法的挑战之一是缺乏可用于评估候选药物的相关认知过程的标准化测量。通过NIMH方法和改善精神分裂症认知的治疗研究(Matrics)倡议，在确定此类措施以支持对人类患者的临床评估方面取得了重大进展。然而，仍然迫切需要在动物身上开发预测性的相关措施，以支持临床前药物发现努力。特别是，发展啮齿动物的预测分析是至关重要的，因为这些动物物种最适用于早期药物发现。由于啮齿动物和人类的认知过程和行为之间存在着巨大的差距，因此识别映射到人类认知域的啮齿动物行为指标是具有挑战性的。我们正在实施一种新的方法来弥合这一差距，方法是直接记录小鼠在执行行为任务期间的脑细胞(神经元)的活动。我们已经开发了一种技术来测量前额叶皮质(PFC)的神经元活动，这是大脑的一个区域，与精神分裂症受损的认知过程有关。使用这种方法，我们已经定义了在注意状态下出现的小鼠PFC中神经元网络的活动。我们还在两个与精神分裂症相关的小鼠模型中观察到了这些活动的变化。这项提议的目标是将我们的记录技术与复杂的老鼠注意力和工作记忆行为测量相结合。这一进展将使我们能够直接测量候选药物对与这些行为相关的大脑活动基本方面的影响。我们相信，这一进展将为预测人类认知疗法的疗效提供迫切需要的动物方法。这项提案中概述的研究将通过支持发现新的、更有效的疗法而直接造福于大量精神分裂症患者及其家人。该提案还通过提供就业机会和支持设备采购来支持经济刺激的使命。这项提案中概述的研究将支持确定治疗精神分裂症认知缺陷的新疗法，这是一项尚未得到满足的主要医疗需求。因此，这项研究将对包括全球数百万人在内的大量精神分裂症患者及其家人和照顾者产生积极影响。特别是，改善精神分裂症患者的认知结果将有助于患者提高工作表现，更有效地融入社会。

DESCRIPTION (provided by applicant): Schizophrenia is a devastating mental illness that affects approximately 1% of the global population. Symptoms of schizophrenia can be grouped into three categories: positive symptoms, such as hallucinations; negative symptoms, such as social isolation and inappropriate emotional response; and cognitive symptoms. The cognitive deficits in schizophrenia include impaired attention and disruption of an essential type of short term memory called working memory. These fundamental cognitive processes are critical for performance of tasks, and their disruption in schizophrenia is a key factor underlying the inability of schizophrenia patients to function in society. Indeed the cognitive deficits in schizophrenia have been recognized as a core component of the disease. Currently available therapies for schizophrenia can ameliorate the positive symptoms, but often cause significant side effects and have not proven effective at treating the negative and cognitive symptoms of the disease. As a core feature of schizophrenia, the cognitive deficits in this disease represent a major unmet medical need. One of the challenges in discovering effective therapies for the cognitive deficits in schizophrenia has been a lack of standardized measures of the relevant cognitive processes that can be applied to evaluating drug candidates. Significant progress in defining such measures to support clinical assessment of human patients has been achieved through the NIMH Method and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) initiative. However, there remains an urgent need to develop predictive, relevant measures in animals to support preclinical drug discovery efforts. In particular, development of predictive assays in rodents is essential, as these animal species are most applicable to early stage drug discovery. Since there is a huge gap between cognitive processes and behaviors in rodents and humans, it is challenging to identify rodent behavioral measures that map onto human cognitive domains. We are implementing a new approach to bridge this gap by directly recording the activity of brain cells (neurons) in mice during the performance of behavioral tasks. We have developed a technique to measure activity of neurons in the prefrontal cortex (PFC), a region of the brain that has been linked with the cognitive processes that are impaired in schizophrenia. Using this methodology, we have defined activities of networks of neurons in the mouse PFC that arise during states of attention. We have also observed alterations of these activities in two mouse models that bear relevance to schizophrenia. The goal of this proposal is to combine our recording technology with sophisticated mouse behavioral measures of attention and working memory. This development will permit us to directly measure the effects of candidate drugs on basic aspects of brain activity that are relevant to these behaviors. We believe that this advance will provide the urgently needed animal measures for predicting efficacy of cognitive therapies in humans. The research outlined in this proposal will directly benefit the large population of schizophrenia patients and their families by supporting the discovery of new, more effective therapies. This proposal also supports the mission of economic stimulus by providing jobs and supporting equipment purchases. The research outlined in this proposal will support the identification of new therapies for the cognitive deficits in schizophrenia, which are a major unmet medical need. This research will thus have a positive impact on the significant population of schizophrenia patients and their family members and caregivers, which includes many millions of people worldwide. In particular, improving the cognitive outcome in schizophrenia will help patients to improve their job performance and to integrate into society more effectively.