Transfer Learning in Mice: improved diagnosis and treatment of Alzheimer disease

最近的估计表明，在活到55岁的人中，十分之一的男性和六分之一的女性将被诊断患有阿尔茨海默病（AD）。这种疾病的特征是显著的认知能力下降和神经病理学，导致个人、家庭和社会失去独立性和重大的心理和经济负担。早期识别AD对于改善疾病结局至关重要，因为中晚期疾病伴有明显的神经元损失和其他病理学，这对有效治疗构成了重大障碍。此外，目前缺乏既能早期识别AD又能在啮齿动物模型（绝大多数神经生物学数据来源于啮齿动物模型）和患有该疾病的人类之间良好转化的行为测定。海马体是一种在AD中早期急剧下降的大脑结构，评估海马体功能的任务是新型认知评估的最佳目标之一。海马体功能的一个独特方面最近才在AD的背景下进行了测试，这是基于证据表明，该系统在将先前学习的信息应用于新问题和情况（称为“迁移学习”）的能力中起着重要作用。迁移学习在海马损伤的人和轻度海马萎缩的老年人中受损（但在标准神经心理学评估中仍然表现良好）。一项小规模的研究甚至表明，迁移学习缺陷预测那些将在2年内发展成AD的人。最近，我们成功地开发了这种人类任务的小鼠类似物，并发现迁移学习对广泛使用的疾病小鼠模型中与年龄相关的AD相关病理学也很敏感。当前提案的首要主题是使用我们最近开发的小鼠迁移学习任务来扩展我们对迁移学习的理解，最终目标是识别与AD病理学相关的早期认知变化，并阻止神经生物学和认知缺陷的进展在一个完善的疾病小鼠模型中。从这些研究中获得的数据应直接转化为早期发现AD患者或有发展AD风险的个体的新途径和上级治疗策略。目的1评价双侧海马损伤对迁移任务的影响，以确定海马是否确实是迁移学习的关键。目标2将扩展我们的初步数据，并在广泛使用的AD小鼠模型中，在整个生命周期的多个时间点，描述与水迷宫性能相关的转移任务性能。此外，目标2将检查在该小鼠模型中的迁移学习缺陷与海马中突触完整性的标记物之间的关系。目标3将为使用小鼠迁移学习作为临床前模型来测试AD治疗提供基础，并确定在AD样病理学发作时开始的治疗方案是否可以停止或减少AD小鼠模型中认知缺陷的进展。

Recent estimates indicate that one in ten men and one in six women who live to 55 years will be diagnosed with Alzheimer's disease (AD). This disease, characterized by marked cognitive decline and neuropathology, leads to loss of independence and significant psychological and financial burdens for individuals, their families, and society. Early identification of AD is essential for improving disease outcomes as mid- and late-stage disease is accompanied by marked neuronal loss and other pathology which present significant barriers for effective treatments. Moreover, there is a current lack of behavioral assays that both identify AD early and that translate well between rodent models, from which the vast majority of the neurobiological data are derived, and humans, who suffer from the disease. The hippocampus is a brain structure that declines early and precipitously in AD, and tasks that assess hippocampal function are among the best targets for novel cognitive assessments. A unique aspect of hippocampal function only recently tested within the context of AD is based on evidence that this system plays an important role in the ability to apply previously learned information to novel problems and situations (referred to as 'transfer learning'). Transfer learning is impaired in humans with hippocampal damage and elderly individuals with mild hippocampal atrophy (but who still perform well on standard neuropsychological assessments). A small scale study has even shown that transfer learning deficits predict those individuals who will progress into AD over a 2 year window. Recently, we successfully developed a mouse analogue of this human task, and found that transfer learning is also sensitive to age-related AD- associated pathology in a widely-used mouse model of the disease. The overarching theme of the current proposal is to extend our understanding of transfer learning using our recently developed mouse transfer learning task, with the ultimate goal of both identifying early cognitive changes associated with AD pathology and halting the progression of neurobiological and cognitive deficits in a well-established mouse model of the disease. The data obtained from these studies should directly translate into novel avenues for the early detection of, and superior treatment strategies for, individuals with or at risk for developing AD. Aim 1 will evaluate the effects of bilateral hippocampal lesions on the transfer task, to determine whether the hippocampus is indeed critical for transfer learning. Aim 2 will expand upon our Preliminary Data and characterize performance on the transfer task in relation to performance on the water maze at multiple timepoints across the lifespan in a widely used mouse model of AD. In addition, Aim 2 will examine the relationship between transfer learning deficits in this mouse model and markers of synaptic integrity in hippocampus. Aim 3 will provide a foundation for using mouse transfer learning as a preclinical model for testing therapies for AD and determine if treatment regimens started at the onset of AD-like pathology can halt or reduce the progression of cognitive deficits in the AD mouse model.