Systems Modeling of Alzheimers Disease in C. elegans

项目总结 阿尔茨海默病(AD)是一种与衰老相关的主要神经疾病，约有530万人患有此病 美国人，美国每年的总成本约为226亿美元。尽管密集地努力描述该法规的特征 AD的病理过程，特别是-淀粉样斑块的产生，目前的干预措施旨在 阻断-淀粉样蛋白聚集对临床症状的影响不大，这表明新的方法 要找到独立于-淀粉样蛋白聚集的危险因素，应进行调查，特别是识别近端 疾病的原因。模式生物的遗传学研究已经证明，在进化上保守的 这些通路调节衰老，而针对这些通路的干预可以极大地扩展哺乳动物 健康寿命和寿命。线虫一直处于模式生物长寿研究的前沿，揭示了 新的基因、途径和分子机制调节衰老和与年龄相关的衰退的速度， 包括认知能力下降。同时，全基因组关联(GWAS)的研究已经暗示了 基因调控改变是AD发病的危险因素。基因调控区的AD风险变异体可能失调 上下文特定的转录输出，有助于AD的易感性，独立于调节和 -淀粉样斑块的生成。我们的假设是，通过定义细胞的基因调控网络在 在衰老和遗传易感性AD神经病理状态下，将有可能推断 细胞接收并解释其产生的基因表达程序的环境信号。这些年龄段- 依赖的转录变化可能在进化的时间尺度上在神经元中保守，并可能 线虫也会导致模型系统中认知能力的下降。我们将利用这一优势 模型系统(简单的遗传学，短寿命，快速老化，学习和记忆的功能分析，以及 分离神经元的转录分析)，结合AD和AD的基因组和遗传学研究的数据 来自人类神经细胞的实验结果，以确定可能有助于 对阿尔茨海默病的易感性。这些基因和基因网络将为制药提供重要的新靶点 阿尔茨海默病发生和发展的干预措施。

PROJECT SUMMARY Alzheimer’s Disease (AD) is a major aging-related neurological disorder that afflicts roughly 5.3 million Americans, with total US annual costs of ~ $226 billion. Despite intensive efforts to characterize the regulation of pathological processes of AD, particularly the generation of -amyloid plaques, current interventions aimed at blocking -amyloid aggregation have only modest effects on clinical symptoms, suggesting that new approaches to find risk factors independent of -amyloid aggregation should be investigated, particularly to identify proximal causes of the disease. Genetic studies in model organisms have demonstrated that evolutionarily conserved pathways modulate aging, and interventions that target these pathways can dramatically extend mammalian healthspan and lifespan. C. elegans has been at the forefront of model organism longevity studies, revealing new genes, pathways, and molecular mechanisms that regulate the rate of aging and age-related declines, including cognitive decline. In parallel, Genome-wide association (GWAS) studies have implicated a role for gene regulatory changes as a risk factor for AD. AD risk variants in gene regulatory regions may dysregulate context-specific transcriptional outputs, contributing to susceptibility to AD independent of the regulation and generation of -amyloid plaques. Our hypothesis is that by defining a cell’s gene regulatory networks during aging and in genetically predisposed AD neuropathological states, it will be possible to both infer the environmental signals the cell receives and explain its resulting program of gene expression. These age- dependent transcriptional changes may be conserved in neurons across evolutionary time scales, and may contribute to cognitive decline in the model system C. elegans, as well. We will leverage the strengths of this model system (simple genetics, short lifespan, rapid aging, functional assays of learning and memory, and transcriptional analysis of isolated neurons), combined with data from genomic and genetic studies of AD and experimental results from human neuronal cells, to identify shared gene regulatory networks that may contribute to the susceptibility to AD. These genes and gene networks will provide important new targets for pharmaceutical interventions for the onset and progression of Alzheimer’s Disease.