近日,，中國科學(xué)院北京基因組研究所“百人計(jì)劃”研究員雷紅星開展的“阿爾茲海默癥致病機(jī)制系統(tǒng)生物網(wǎng)絡(luò)研究”取得階段性進(jìn)展,，其研究論文《Concerted Perturbation Observed in a Hub Network in Alzheimer’s Disease》,，于2012年7月在《PLoS ONE》雜志發(fā)表,。該文通過對(duì)病人易感腦區(qū)的轉(zhuǎn)錄組數(shù)據(jù)以及蛋白質(zhì)相互作用數(shù)據(jù)進(jìn)行整合分析,，得到了在阿爾茲海默癥中可能起到重要作用的核心網(wǎng)絡(luò),。該核心網(wǎng)絡(luò)反映了神經(jīng)細(xì)胞對(duì)微環(huán)境改變的一種調(diào)整機(jī)制,，為設(shè)計(jì)更有效的阿爾茲海默癥藥物提供了理論依據(jù)。
阿爾茲海默癥（Alzheimer's disease, AD）又稱老年癡呆癥,，是一種進(jìn)行性發(fā)展的致死性神經(jīng)退行性疾病,。其組織病理學(xué)特征是細(xì)胞外Aβ淀粉樣多肽沉淀（俗稱老年斑）以及神經(jīng)元內(nèi)由tau蛋白引起的神經(jīng)纖維纏結(jié)（neurofibrillary tangles, NFT）。在過去的十年里,，全基因組基因芯片技術(shù)被廣泛應(yīng)用到AD致病機(jī)理的研究中,。基于功能富集,，通路和網(wǎng)絡(luò)擾動(dòng)研究,，一些公共芯片數(shù)據(jù)被反復(fù)分析，但是尋找更為可靠的重要擾動(dòng)基因仍是一個(gè)極具挑戰(zhàn)性的研究方向,。
為此,，雷紅星研究員及其團(tuán)隊(duì)將六個(gè)腦區(qū)的轉(zhuǎn)錄組數(shù)據(jù)以及蛋白質(zhì)相互作用數(shù)據(jù)進(jìn)行整合分析，得到了每個(gè)腦區(qū)被顯著擾動(dòng)的子網(wǎng)絡(luò),。由于這六個(gè)顯著擾動(dòng)子網(wǎng)絡(luò)之間存在著顯著的交集，研究人員從中提取出了由136個(gè)核心基因構(gòu)成的核心網(wǎng)絡(luò),，并從多個(gè)層面說明了該核心網(wǎng)絡(luò)的生物學(xué)意義,。首先，通過與其他神經(jīng)退行性疾病的轉(zhuǎn)錄組數(shù)據(jù)進(jìn)行比較分析,，研究人員證實(shí)了該核心網(wǎng)絡(luò)存在著AD特異性的擾動(dòng),。與此同時(shí)，核心基因的表達(dá)水平與體現(xiàn)患病嚴(yán)重程度的指標(biāo)數(shù)據(jù)（MMSE and NFT scores）之間存在著很強(qiáng)的相關(guān)性,，這一發(fā)現(xiàn)說明了該核心網(wǎng)絡(luò)在一定程度上能夠反應(yīng)AD的疾病進(jìn)程,。此外，研究人員還證實(shí)了該核心網(wǎng)絡(luò)與老年斑和神經(jīng)纖維纏結(jié)的形成,、衰老和基因多態(tài)性都密切相關(guān),。
通過對(duì)該核心網(wǎng)絡(luò)進(jìn)行生物學(xué)功能的分析，研究人員證實(shí)神經(jīng)細(xì)胞和突觸活動(dòng)的降低以及死亡相關(guān)信號(hào)轉(zhuǎn)導(dǎo)途徑的改變是神經(jīng)細(xì)胞對(duì)微環(huán)境改變的一種適應(yīng)性調(diào)整,。這一新的發(fā)現(xiàn)對(duì)于AD致病機(jī)理的研究起到了積極的推動(dòng)作用,，為AD的藥物設(shè)計(jì)開辟了新的思路。（生物谷Bioon.com）
doi:10.1371/journal.pone.0040498
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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.
