Identification and validation of oxidative stress and immune-related hub genes in Alzheimer's disease through bioinformatics analysis.
Identification and validation of oxidative stress and immune-related hub genes in Alzheimer's disease through bioinformatics analysis.
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DOI：
10.1038/s41598-023-27977-7
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发表时间：
2023-01-12
影响因子：
4.6
通讯作者：
Sun, Jikui
中科院分区：
文献类型：
--
作者：
Li, Shengjie;Xiao, Jinting;Huang, Chuanjiang;Sun, Jikui
阿尔茨海默病（AD）是老年人痴呆的主要原因。氧化应激和神经炎症在AD的发病机制中发挥重要作用。有必要研究中心基因以开发潜在的治疗靶点和候选生物标志物。在GSE48350数据集中筛选AD中的差异表达基因（DEG）。通过 DEG 与氧化应激相关基因的交叉分析差异表达的氧化应激基因 (DEOSG)。分别通过加权基因共表达网络分析（WGCNA）和蛋白质-蛋白质相互作用（PPI）分析来鉴定与免疫相关的DEOSG和枢纽基因。富集分析由 Gene Ontology 和京都基因和基因组百科全书进行。 Hub 基因的诊断价值通过接受者操作特征分析进行评估，并在 GSE1297 中进行验证。通过 qRT-PCR 分析确定诊断基因的 mRNA 表达。最后，我们构建了药物、转录因子（TF）和诊断基因的 microRNA 网络。在GSE48350中总共筛选了1160个DEG（259个上调和901个下调）。其中 AD 中鉴定出 111 个 DEOSG。此后，我们发现 AD 和对照样本之间的浸润免疫细胞（效应记忆 CD8 T 细胞、活化 B 细胞、记忆 B 细胞、自然杀伤细胞、CD56 明亮自然杀伤细胞、自然杀伤 T 细胞、浆细胞样树突状细胞和中性粒细胞）存在显着差异。通过WGCNA获得了27个基因模块，其中turquoise模块是最相关的模块。我们通过将 turquoise 模块与 DEOSG 相交获得了 66 个与免疫相关的 DEOSG，并通过 PPI 分析鉴定了 15 个枢纽基因。其中，9个枢纽基因（CCK、CNR1、GAD1、GAP43、NEFL、NPY、PENK、SST和TAC1）被鉴定出具有良好的诊断价值，并在GSE1297中得到验证。 qRT-PCR 分析显示 AD 中 SST、NPY、GAP43、CCK 和 PENK 下调，NEFL 上调。最后，我们确定了 76 种治疗药物、152 个 miRNA 靶点和 91 个 TF 调控网络。我们的研究确定了 AD 发病机制中与氧化应激和免疫反应相关的 9 个关键基因。这些发现可能有助于为 AD 提供有希望的候选生物标志物和治疗靶点。
Alzheimer’s disease (AD) is the leading cause of dementia in aged population. Oxidative stress and neuroinflammation play important roles in the pathogenesis of AD. Investigation of hub genes for the development of potential therapeutic targets and candidate biomarkers is warranted. The differentially expressed genes (DEGs) in AD were screened in GSE48350 dataset. The differentially expressed oxidative stress genes (DEOSGs) were analyzed by intersection of DEGs and oxidative stress-related genes. The immune-related DEOSGs and hub genes were identified by weighted gene co-expression network analysis (WGCNA) and protein–protein interaction (PPI) analysis, respectively. Enrichment analysis was performed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. The diagnostic value of hub genes was assessed by receiver operating characteristic analysis and validated in GSE1297. The mRNA expression of diagnostic genes was determined by qRT-PCR analysis. Finally, we constructed the drug, transcription factors (TFs), and microRNA network of the diagnostic genes. A total of 1160 DEGs (259 up-regulated and 901 down-regulated) were screened in GSE48350. Among them 111 DEOSGs were identified in AD. Thereafter, we identified significant difference of infiltrated immune cells (effector memory CD8 T cell, activated B cell, memory B cell, natural killer cell, CD56 bright natural killer cell, natural killer T cell, plasmacytoid dendritic cell, and neutrophil) between AD and control samples. 27 gene modules were obtained through WGCNA and turquoise module was the most relevant module. We obtained 66 immune-related DEOSGs by intersecting turquoise module with the DEOSGs and identified 15 hub genes through PPI analysis. Among them, 9 hub genes (CCK, CNR1, GAD1, GAP43, NEFL, NPY, PENK, SST, and TAC1) were identified with good diagnostic values and verified in GSE1297. qRT-PCR analysis revealed the downregulation of SST, NPY, GAP43, CCK, and PENK and upregulation of NEFL in AD. Finally, we identified 76 therapeutic agents, 152 miRNAs targets, and 91 TFs regulatory networks. Our study identified 9 key genes associated with oxidative stress and immune reaction in AD pathogenesis. The findings may help to provide promising candidate biomarkers and therapeutic targets for AD.
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影响因子：
7.4
作者：
Cheng Q;Chen X;Wu H;Du Y
通讯作者：
Du Y
DOI：
10.1093/brain/aww083
发表时间：
2016-07
期刊：
Brain : a journal of neurology
影响因子：
--
作者：
Aggleton JP;Pralus A;Nelson AJ;Hornberger M
通讯作者：
Hornberger M
影响因子：
4.1
作者：
Eapen, Prasanth M.;Rao, Chamallamudi Mallikarjuna;Nampoothiri, Madhavan
通讯作者：
Nampoothiri, Madhavan
小鼠和人类FOXC1依赖的dandy-walker小脑畸形中的表型结局提出了共同的机制。
影响因子：
7.7
作者：
Haldipur P;Dang D;Aldinger KA;Janson OK;Guimiot F;Adle-Biasette H;Dobyns WB;Siebert JR;Russo R;Millen KJ
通讯作者：
Millen KJ
影响因子：
4.7
作者：
Butterfield DA;Boyd-Kimball D
通讯作者：
Boyd-Kimball D