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当代阿耳茨海默病研究

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ISSN (Print): 1567-2050
ISSN (Online): 1875-5828

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Research Article

全基因组网络辅助阿尔茨海默病淀粉样成像表型的关联与富集研究

卷 16, 期 13, 2019

页: [1163 - 1174] 页: 12

弟呕挨: 10.2174/1567205016666191121142558

价格: $65

摘要

背景：在机制水平上对阿尔茨海默氏病的病因学知之甚少，基于全基因组网络的遗传学有可能为疾病机制提供新见解。 目的：这项研究旨在通过采用网络辅助策略，探索多种遗传关联信号对AV-45 PET量度（一种著名的阿尔茨海默氏病生物标志物）的集体影响。 方法：首先，我们利用密集模块搜索算法来识别蛋白质-蛋白质相互作用网络中遗传关联信号所丰富的模块。接下来，我们对通过密集模块搜索确定的模块进行了统计评估，包括规范化过程以调整网络中的拓扑偏差，复制测试以确保模块不是随机找到的，以及排列测试以评估模块之间的无偏关联。模块和淀粉样蛋白显像表型。最后，对确定的模块进行了拓扑分析，模块相似性测试和功能丰富性分析。 结果：在全基因组关联分析中，我们确定了24个共有模块，这些模块被强大的遗传信号所丰富。结果不仅验证了先前报道的几种AD基因（APOE，APP，TOMM40，DDAH1，PARK2，ATP5C1，PVRL2，ELAVL1，ACTN1和NRF1），而且还提名了一些尚未在其中进行过研究的新基因（，ABLIM2）。阿尔茨海默氏病，但已显示出与其他神经退行性疾病的关联。 结论：确定的基因，共有模块和丰富的通路可能为阿尔茨海默氏病神经生物学的未来研究提供重要线索，并提出潜在的治疗靶标。

关键词: 阿尔茨海默病，淀粉样蛋白成像表型，全基因组关联，网络分析，路径富集，共识模块，神经退行性疾病。

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