Xue J, Liu J, Geng M, Yue J, He H, Fan J
Beijing Institute of Radiation Medicine, Beijing 100850, China.
Institute of Geriatrics, Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing 100853, China.
Nan Fang Yi Ke Da Xue Xue Bao. 2021 Dec 20;41(12):1752-1762. doi: 10.12122/j.issn.1673-4254.2021.12.01.
To investigate the differential expression gene modules and hub genes associated with Alzheimer's disease (AD) by weighted gene co-expression network analysis (WGCNA) and annotate the biological functions of these modules.
We downloaded transcriptome sequencing data from the GEO database, and according to the correlation of the genes, a gene co-expression network was constructed with the parameter setting of β=8 and a correlation coefficient threshold of 0.85. Pearson correlation test was used to calculate the correlation between the module genes and clinical traits to screen the gene modules significantly associated with AD and identify the hub genes according to the connectivity within modules. GO functional enrichment analysis and KEGG pathway analysis were used to annotate the functions of the modules. A cell model of AD was established in SH-SY5Y cells by Aβ1-42 treatment, and the mRNA expression levels of the hub genes were compared between the Aβ1-42-treated cells and the control cells.
Ten gene co-expression modules were constructed based on the correlations of gene expression, in which the brown (=0.66, < 0.001) and turquoise modules (=-0.68, < 0.001) were significantly correlated with the AD group. Forty-eight genes were identified as the hub genes in the co-expression network. Function annotation revealed that the genes in both modules were mainly enriched in DNA damage and repair pathways and metabolism-related pathways. Differential expression analysis of the genes revealed that the genes DNASE1, TEKT2 and MTSS1L were highly expressed while ACP2, LANCL2 and GMPR2 were lowly expressed in AD group. The results of cell experiment confirmed the up-regulation of DNASE1, TEKT2 and MTSS1L genes and the down-regulation of ACP2, LANCL2, and GMPR2 in Aβ1-42-treated SH-SY5Y cells ( < 0.01).
The brown and turquoise modules are closely correlated with AD. The hub genes including MTSS1L, GMPR2, ACP2, ACTG1 and LANCL2 selected from the modules may participate in AD pathogenesis by regulating DNA damage and repair.
通过加权基因共表达网络分析（WGCNA）研究与阿尔茨海默病（AD）相关的差异表达基因模块和枢纽基因，并对这些模块的生物学功能进行注释。
我们从GEO数据库下载转录组测序数据，根据基因的相关性，以β = 8的参数设置和0.85的相关系数阈值构建基因共表达网络。使用Pearson相关检验计算模块基因与临床特征之间的相关性，以筛选与AD显著相关的基因模块，并根据模块内的连通性鉴定枢纽基因。使用GO功能富集分析和KEGG通路分析对模块的功能进行注释。通过Aβ1-42处理在SH-SY5Y细胞中建立AD细胞模型，并比较Aβ1-42处理的细胞与对照细胞中枢纽基因的mRNA表达水平。
基于基因表达的相关性构建了10个基因共表达模块，其中棕色模块（r = 0.66，P < 0.001）和蓝绿色模块（r = -0.68，P < 0.001）与AD组显著相关。48个基因被鉴定为共表达网络中的枢纽基因。功能注释显示，两个模块中的基因主要富集于DNA损伤和修复途径以及代谢相关途径。基因差异表达分析显示，DNASE1、TEKT2和MTSS1L基因在AD组中高表达，而ACP2、LANCL2和GMPR2低表达。细胞实验结果证实，在Aβ1-42处理的SH-SY5Y细胞中，DNASE1、TEKT2和MTSS1L基因上调，而ACP2、LANCL2和GMPR2基因下调（P < 0.01）。
棕色和蓝绿色模块与AD密切相关。从这些模块中选出的包括MTSS1L、GMPR2、ACP2、ACTG1和LANCL2在内的枢纽基因可能通过调节DNA损伤和修复参与AD的发病机制。
