Sun Yan, Lin Jinghan, Zhang Liming
Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin 150000, China.
Ann Transl Med. 2019 Dec;7(24):800. doi: 10.21037/atm.2019.12.59.
Alzheimer's disease (AD) is the most common neurodegenerative condition that affects more than 15 million individuals globally. However, a predictive molecular biomarker to distinguish the different stages of AD patients is still lacking.
A weighted gene co-expression network analysis (WGCNA) was employed to systematically identify the co-expressed gene modules and hub genes connected with AD development based on a microarray dataset (GSE1297) from the Gene Expression Omnibus (GEO) database. An independent validation cohort, GSE28146, was utilized to assess the diagnostic efficiency for distinguishing the different stages of AD. Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) and western blotting analysis were applied to examine the mRNA and protein level of GRIK1, respectively, in AD mice established with the expression of mutant amyloid precursor protein and wild type mice. The morphology of neurons was investigated using phalloidin staining.
We identified 16 co-expressed genes modules, with the pink module showing significant association with all three disease statuses [neurofibrillary tangle (NFT), BRAAK, and mini-mental state examination (MMSE)]. Enrichment analysis specified that these modules were enriched in phosphatidylinositol 3-kinase (PI3K) signaling and ion transmembrane transport. The validation cohort GSE28146 confirmed that six hub genes in the pink module could distinguish severe and non-severe AD patients [area under the curve (AUC) >0.7]. These hub genes might act as a biomarker and help to differentiate diverse pathological stages for AD patients. Finally, one of the hubs, GRIK1, was validated by an animal AD model. The mRNA and protein level of GRIK1 in the AD hippocampus was increased compared with the control group (NC) hippocampus. Phalloidin staining showed that dendritic length of the GRIK1 pCDNA3.1 group was shorter than that of the NC group.
In summary, we systematically recognized co-expressed gene modules and genes related to AD stages, which gave insight into the fundamental mechanisms of AD progression and revealed some probable targets for the treatment of AD.
阿尔茨海默病（AD）是最常见的神经退行性疾病，全球有超过1500万人受其影响。然而，仍缺乏用于区分AD患者不同阶段的预测性分子生物标志物。
基于基因表达综合数据库（GEO）中的一个微阵列数据集（GSE1297），采用加权基因共表达网络分析（WGCNA）系统地识别与AD发展相关的共表达基因模块和枢纽基因。利用一个独立的验证队列GSE28146评估区分AD不同阶段的诊断效率。应用定量实时逆转录聚合酶链反应（qRT-PCR）和蛋白质印迹分析分别检测在表达突变淀粉样前体蛋白的AD小鼠和野生型小鼠中GRIK1的mRNA和蛋白水平。使用鬼笔环肽染色研究神经元的形态。
我们识别出16个共表达基因模块，其中粉色模块与所有三种疾病状态[神经原纤维缠结（NFT）、Braak分期和简易精神状态检查表（MMSE）]均显示出显著关联。富集分析表明这些模块在磷脂酰肌醇3激酶（PI3K）信号传导和离子跨膜转运方面富集。验证队列GSE28146证实粉色模块中的6个枢纽基因能够区分重度和非重度AD患者[曲线下面积（AUC）>0.7]。这些枢纽基因可能作为一种生物标志物，有助于区分AD患者的不同病理阶段。最后，通过动物AD模型验证了其中一个枢纽基因GRIK1。与对照组（NC）海马相比，AD海马中GRIK1的mRNA和蛋白水平升高。鬼笔环肽染色显示GRIK1 pCDNA3.1组的树突长度短于NC组。
总之，我们系统地识别了与AD阶段相关的共表达基因模块和基因，这为深入了解AD进展的基本机制提供了线索，并揭示了一些可能的AD治疗靶点。
