近日，中国科学院北京基因组研究所“百人计划”研究员雷红星开展的“阿尔兹海默症致病机制系统生物网络研究”取得阶段性进展，其研究论文《Concerted Perturbation Observed in a Hub Network in Alzheimer’s Disease》，于2012年7月在《PLoS ONE》杂志发表。该文通过对病人易感脑区的转录组数据以及蛋白质相互作用数据进行整合分析，得到了在阿尔兹海默症中可能起到重要作用的核心网络。该核心网络反映了神经细胞对微环境改变的一种调整机制，为设计更有效的阿尔兹海默症药物提供了理论依据。
阿尔兹海默症（Alzheimer's disease, AD）又称老年痴呆症，是一种进行性发展的致死性神经退行性疾病。其组织病理学特征是细胞外Aβ淀粉样多肽沉淀（俗称老年斑）以及神经元内由tau蛋白引起的神经纤维缠结（neurofibrillary tangles, NFT）。在过去的十年里，全基因组基因芯片技术被广泛应用到AD致病机理的研究中。基于功能富集，通路和网络扰动研究，一些公共芯片数据被反复分析，但是寻找更为可靠的重要扰动基因仍是一个极具挑战性的研究方向。
为此，雷红星研究员及其团队将六个脑区的转录组数据以及蛋白质相互作用数据进行整合分析，得到了每个脑区被显著扰动的子网络。由于这六个显著扰动子网络之间存在着显著的交集，研究人员从中提取出了由136个核心基因构成的核心网络，并从多个层面说明了该核心网络的生物学意义。首先，通过与其他神经退行性疾病的转录组数据进行比较分析，研究人员证实了该核心网络存在着AD特异性的扰动。与此同时，核心基因的表达水平与体现患病严重程度的指标数据（MMSE and NFT scores）之间存在着很强的相关性，这一发现说明了该核心网络在一定程度上能够反应AD的疾病进程。此外，研究人员还证实了该核心网络与老年斑和神经纤维缠结的形成、衰老和基因多态性都密切相关。
通过对该核心网络进行生物学功能的分析，研究人员证实神经细胞和突触活动的降低以及死亡相关信号转导途径的改变是神经细胞对微环境改变的一种适应性调整。这一新的发现对于AD致病机理的研究起到了积极的推动作用，为AD的药物设计开辟了新的思路。（生物谷Bioon.com）
doi:10.1371/journal.pone.0040498
PMC:
PMID:
Concerted Perturbation Observed in a Hub Network in Alzheimer’s Disease
Dapeng Liang, Guangchun Han, Xuemei Feng, Jiya Sun, Yong Duan, Hongxing Lei
Alzheimer’s disease (AD) is a progressive neurodegenerative disease involving the alteration of gene expression at the whole genome level. Genome-wide transcriptional profiling of AD has been conducted by many groups on several relevant brain regions. However, identifying the most critical dys-regulated genes has been challenging. In this work, we addressed this issue by deriving critical genes from perturbed subnetworks. Using a recent microarray dataset on six brain regions, we applied a heaviest induced subgraph algorithm with a modular scoring function to reveal the significantly perturbed subnetwork in each brain region. These perturbed subnetworks were found to be significantly overlapped with each other. Furthermore, the hub genes from these perturbed subnetworks formed a connected hub network consisting of 136 genes. Comparison between AD and several related diseases demonstrated that the hub network was robustly and specifically perturbed in AD. In addition, strong correlation between the expression level of these hub genes and indicators of AD severity suggested that this hub network can partially reflect AD progression. More importantly, this hub network reflected the adaptation of neurons to the AD-specific microenvironment through a variety of adjustments, including reduction of neuronal and synaptic activities and alteration of survival signaling. Therefore, it is potentially useful for the development of biomarkers and network medicine for AD.
