In vivo methods for preclinical analysis of cognitive therapies for schizophrenia

精神分裂症认知疗法临床前分析的体内方法

基本信息

  • 批准号:
    7942830
  • 负责人:
  • 金额:
    $ 53.36万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2009
  • 资助国家:
    美国
  • 起止时间:
    2009-09-30 至 2012-08-31
  • 项目状态:
    已结题

项目摘要

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.
描述(由申请人提供):精神分裂症是一种毁灭性的精神疾病,影响着全球约 1% 的人口。精神分裂症的症状可分为三类:阳性症状,如幻觉;负面症状,例如社交孤立和不适当的情绪反应;和认知症状。精神分裂症的认知缺陷包括注意力受损和一种称为工作记忆的基本短期记忆类型的破坏。这些基本认知过程对于执行任务至关重要,它们对精神分裂症的破坏是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被认为是该疾病的核心组成部分。目前可用的精神分裂症疗法可以改善阳性症状,但通常会引起显着的副作用,并且尚未证明可以有效治疗该疾病的阴性症状和认知症状。作为精神分裂症的核心特征,这种疾病的认知缺陷代表了一个重大的未满足的医疗需求。寻找治疗精神分裂症认知缺陷的有效疗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 改善精神分裂症认知的方法和治疗研究 (MATRICS) 计划,在定义此类措施以支持人类患者临床评估方面取得了重大进展。然而,仍然迫切需要在动物中开发预测性相关措施以支持临床前药物发现工作。特别是,在啮齿动物中开发预测分析至关重要,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巨大差距,因此确定映射到人类认知领域的啮齿动物行为测量具有挑战性。我们正在实施一种新方法,通过直接记录小鼠执行行为任务期间脑细胞(神经元)的活动来弥补这一差距。我们开发了一种技术来测量前额皮质(PFC)神经元的活动,前额皮质是大脑的一个区域,与精神分裂症受损的认知过程有关。使用这种方法,我们定义了小鼠 PFC 中在注意力状态下出现的神经元网络的活动。我们还在两种与精神分裂症相关的小鼠模型中观察到这些活动的变化。该提案的目标是将我们的记录技术与复杂的小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指标。该提案中概述的研究将通过支持发现新的、更有效的疗法,使大量精神分裂症患者及其家人直接受益。该提案还通过提供就业机会和支持设备购买来支持经济刺激的使命。该提案中概述的研究将支持识别精神分裂症认知缺陷的新疗法,这是一个未满足的主要医疗需求。因此,这项研究将对大量精神分裂症患者及其家人和护理人员产生积极影响,其中包括全世界数百万人。特别是,改善精神分裂症的认知结果将有助于患者提高工作绩效并更有效地融入社会。

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Margaret Levin其他文献

Margaret Levin的其他文献

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{{ truncateString('Margaret Levin', 18)}}的其他基金

Electrophysiological Endophenotypes of Schizophrenia in Mouse and Man
小鼠和人精神分裂症的电生理内表型
  • 批准号:
    8517190
  • 财政年份:
    2012
  • 资助金额:
    $ 53.36万
  • 项目类别:
Electrophysiological Endophenotypes of Schizophrenia in Mouse and Man
小鼠和人精神分裂症的电生理内表型
  • 批准号:
    8904718
  • 财政年份:
    2012
  • 资助金额:
    $ 53.36万
  • 项目类别:
Electrophysiological Endophenotypes of Schizophrenia in Mouse and Man
小鼠和人精神分裂症的电生理内表型
  • 批准号:
    8664929
  • 财政年份:
    2012
  • 资助金额:
    $ 53.36万
  • 项目类别:
Electrophysiological Endophenotypes of Schizophrenia in Mouse and Man
小鼠和人精神分裂症的电生理内表型
  • 批准号:
    8238196
  • 财政年份:
    2012
  • 资助金额:
    $ 53.36万
  • 项目类别:

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