Zhang C, Zhong X, Yi L, Zhao Z, Zhang Y, Tan G, Zhang Y, Zhang Y, Xu Y, Wu N
Chunlong Zhang, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China,
J Prev Alzheimers Dis. 2023;10(2):267-275. doi: 10.14283/jpad.2023.23.
Previous studies have revealed that there existed epidemic associations between Alzheimer's disease (AD) and many types of tumors, however, the inner biological mechanism connecting these diseases was not clear currently. In this study, we explored the transcriptome associations between AD and glioblastoma multiforme (GBM) that both originate in the brain, using microglia as a bridge, from gene and network levels. Firstly, we extracted human scRNA sequencing datasets from Gene Expression Omnibus (GEO) database, and identified differentially expressed genes within microglia after cell annotation. It was observed that there were 11 common genes shared by AD and GBM dys-regulated genes. Next, we utilized DIAMOnD and Flow Centrality algorithms to identify microglia modules and mediating pathways connecting these two diseases based on global network topology. Among these candidate pathways, the mediating genes FURIN and BACE1 (from SPIKN5 to CSNK1A1) were not only related to the formation of amyloid beta plaques that accumulate in the brain of AD patients, but also involved in cancer biology. Furthermore, the biological explorations of mediating pathways connecting AD and GBM modules reveal inflammatory response, lipid metabolism disorder, and cell proliferation terms. Finally, novel signatures for early AD detection as well as risk models for glioma prognosis were identified based on mediating genes involved in these pathways. In conclusion, this study provided a novel network-based strategy for exploring microglia mediation between AD and GBM and identified candidate signatures for disease detection and prognosis.
先前的研究表明，阿尔茨海默病（AD）与多种类型的肿瘤之间存在流行学关联，然而，目前连接这些疾病的内在生物学机制尚不清楚。在本研究中，我们以小胶质细胞为桥梁，从基因和网络水平探索了均起源于大脑的AD与多形性胶质母细胞瘤（GBM）之间的转录组关联。首先，我们从基因表达综合数据库（GEO）中提取人类单细胞RNA测序数据集，并在细胞注释后鉴定小胶质细胞内的差异表达基因。观察到AD和GBM失调基因共有11个共同基因。接下来，我们利用DIAMOnD和流中心性算法，基于全局网络拓扑结构识别连接这两种疾病的小胶质细胞模块和介导通路。在这些候选通路中，介导基因弗林蛋白酶和β-分泌酶1（从SPIKN5到CSNK1A1）不仅与AD患者大脑中积累的淀粉样β斑块的形成有关，还参与癌症生物学过程。此外，对连接AD和GBM模块的介导通路的生物学探索揭示了炎症反应、脂质代谢紊乱和细胞增殖相关术语。最后，基于参与这些通路的介导基因，确定了AD早期检测的新特征以及胶质瘤预后的风险模型。总之，本研究提供了一种基于网络的新策略，用于探索AD和GBM之间的小胶质细胞介导作用，并确定了疾病检测和预后的候选特征。
