Integrative Network Modeling of Cognitive Resilience to Alzheimer's Disease

项目摘要 阿尔茨海默病（AD）是一种使人衰弱的神经退行性疾病。AD的病理特征是 淀粉样斑块和神经纤维缠结。临床上，AD患者表现为进行性记忆衰退 其次是其他认知领域和日常生活活动的恶化。高龄是最大的 风险因素没有有效的方法可用于预防和/或治疗这种毁灭性疾病。但是，在这方面， 某些老年人（≥ 85岁）的认知能力仍然完好，包括一些有大量 斑块和神经系统缠结负担，这是完全有症状的AD的两个病理标志。的 这些老年人的认知恢复力和预防AD的机制仍然难以捉摸。这 这项提案汇集了来自两个主要AD研究的科学家和死后人脑组织样本， 中心（西奈山伊坎医学院和拉什大学医学中心），旨在 系统地识别和验证遗传变异，基因，蛋白质和分子网络， 对AD风险的认知弹性，并建议建立一个全面的无偏见的信号通路图 对AD的潜在认知恢复力。为此，我们将开发一个AD弹性队列，包括 遗传，转录组和蛋白质组数据在前额叶皮层从大量的大脑在四个 分类：1）非常老（死亡年龄（AoD）≥ 85）AD-复原，2）年轻（AoD < 85）健康，3）非常老（AoD 年龄≥85岁的AD和年龄< 85岁的AD。我们将进行系统遗传学和综合网络生物学 分析大规模高维分子谱数据以识别遗传变异、基因 蛋白质和分子网络的基础认知弹性的AD风险。我们将系统地验证密钥 使用两种不同的分子网络驱动程序对AD的认知弹性进行了研究（C.线虫和 小鼠）模型系统。我们将验证AD弹性分子网络的结构，以建立一个数据- 驱动的，全面的信号通路图潜在的认知弹性AD风险。特别是要 测试增强线粒体功能和免疫能力的假设，以及它们的潜在作用。 分子网络赋予认知弹性。我们的研究不仅将呈现一个全球景观， 遗传变异、mRNA和蛋白质之间的相互作用， 查明可能导致开发新预防措施的关键网络结构和关键驱动因素 在对抗AD方面。

Project Summary Alzheimer's disease (AD) is a debilitating neurodegenerative disorder. Pathologically, AD is characterized by amyloid plaques and neurofibrillary tangles. Clinically, AD patients present with progressive memory decline followed by deterioration of other cognitive domains and activities of daily living. Advanced age is the greatest risk factor. No effective method is available for preventing and/or treating this devastating disease. However, certain individuals of the elder population (≥ 85 years) remain cognitively intact, including some with substantial plaques and neurofibrillary tangle burdens, the two pathological hallmarks for fully symptomatic AD. The mechanisms of cognitive resilience and protection against AD in these elderly persons remain elusive. This proposal brings together scientists and postmortem human brain tissue samples from two major AD-research centers (the Icahn School of Medicine at Mount Sinai and the Rush University Medical Center) and aims to systematically identify and validate genetic variants, genes, proteins, and molecular networks underlying cognitive resilience to AD risk and proposes to build a comprehensive unbiased signaling pathway map underlying cognitive resilience to AD. Towards this end, we will develop an AD resilient cohort comprised of genetic, transcriptomic and proteomic data in the prefrontal cortex from a large number of brains in four categories: 1) very old (age of death (AoD) ≥ 85) AD-resilient, 2) young (AoD < 85) healthy, 3) very old (AoD ≥85) AD and 4) young (AoD < 85) AD. We will perform systems genetics and integrative network biology analyses on the large-scale high-dimensional molecular profiling data to identify genetic variants, genes, proteins, and molecular networks underlying cognitive resilience to AD risk. We will systematically validate key drivers of the molecular networks underlying the cognitive resilience to AD using two diverse (C. elegans and mouse) model systems. We will validate the structures of AD-resilient molecular networks for building a data- driven, comprehensive signaling pathway map underlying cognitive resilience to AD risk. In particular, we will test the hypotheses that enhanced mitochondrial function and immune competence as well as their underlying molecular networks confer cognitive resilience. Our study will not only present a global landscape of the interplays among genetic variants, mRNAs and proteins responsible for cognitive resilience to AD but also pinpoint critical network structures and key drivers that can potentially lead to development of novel prevention strategies in combating AD.