Combine computational prediction, network analysis and genetic screening in C elegans to uncover neurodegenerative causes in Alzheimer's Disease

项目总结 阿尔茨海默病(AD)是痴呆症的主要原因，也是最常见的神经退行性疾病， 影响到美国超过550万人和全球4700万人。尽管社会上存在巨大的 与AD相关的经济成本，目前晚发性AD的遗传原因仍然缺乏特征 阿尔茨海默病也没有治愈方法。 在这个名为“结合计算预测、网络分析和遗传筛选”的项目中，C。 为了揭示阿尔茨海默病(AD)的神经退变原因，我们提出了一种综合的 系统生物学方法无缝地结合了新的计算遗传学预测、网络分析 在线虫中进行强大的基因筛查，以揭示阿尔茨海默病中神经退行性疾病的原因。首先，我们将发展 基于数据驱动的基于网络的系统识别神经退行性候选基因的新方法 利用来自人类的大量表型、基因和基因组数据。第二，我们将识别基因 神经退行性变的途径和分子网络；第三，我们将评估 在各种线虫模型中识别候选基因、遗传修饰物和分子网络 神经退行性变。我们的系统生物学方法充分利用并无缝集成了大量 来自人类的知识和数据，然后指导我们对线虫进行验证性基因筛查。这个 我们项目的输出将是候选因果基因、遗传修饰物和分子网络的列表 神经退行性变，每一种都与支持人类和 线虫。我们的研究将产生大量的数据/知识/假设，可以作为一个开始 为其他人在不同的神经变性动物模型中进行假设驱动的测试提供了参考。我们会 建立全面的神经退行性变基因(NDGenes)知识库，开发互动网络 应用程序将所有数据公之于众。 我们项目的独特而强大的优势是我们能够无缝地将新的计算 线虫基因筛查的预测。我们的项目可能会导致发现保守的基因 以及有助于神经变性易感性或恢复力的调控网络，具有翻译功能 对开发AD和其他神经退行性疾病治疗干预措施的启示。

PROJECT SUMMARY Alzheimer's disease (AD) is the leading cause of dementia and the most common neurodegenerative disorder, affecting over 5.5 million people in United States and 47 million people worldwide. Despite the enormous social economical cost associated with AD, currently the genetic causes for late-onset AD remains poorly characterized and there exist no cures for AD. In this project titled “Combine computational prediction, network analysis, and genetic screening in C. elegans to uncover neurodegenerative causes in Alzheimer’s disease (AD)”, we propose an integrated systems biology approach that seamlessly combines novel computational genetics prediction, network analysis, and robust genetic screening in C. elegans to uncover neurodegenerative causes in AD. First, we will develop novel data-driven network-based systems approach to identify neurodegenerative candidate genes by leveraging large amounts of phenotypic, genetic and genomic data from humans. Second, we will identify genetic pathways and molecular networks underlying neurodegeneration; Third, we will evaluate the causal effects of identified candidate genes, genetic modifiers and molecular networks in a variety of C. elegans models of neurodegeneration. Our systems biology approach fully utilizes and seamlessly integrate vast amounts of knowledge and data from humans, which then guides our confirmatory genetic screening in C. elegans. The output of our project will be lists of candidate causal genes, genetic modifiers and molecular networks for neurodegeneration, each associated with supporting genetic and phenotypic evidence from both humans and C. elegans. Our study will generate large amounts of data/knowledge/hypotheses that could serve as a starting point for others to conduct hypothesis-driven testing in different animal models of neurodegeneration. We will build a comprehensive knowledge base of Neurodegeneration Genes (NDGenes) and develop interactive web applications to make all the data publicly available. The unique and powerful strength of our project is our ability to seamlessly combine novel computational predictions with genetic screening in C. elegans. Our project will likely lead to discovery of the conserved genes and regulatory networks that contribute to susceptibility or resilience to neurodegeneration, with translational implications for the development of therapeutic interventions for AD and other neurodegenerative disorders.