Wu Qi, Yang Chunli, Huang Cuilan, Lin Zhiying
Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China.
Front Med (Lausanne). 2025 Jan 6;11:1487224. doi: 10.3389/fmed.2024.1487224. eCollection 2024.
Although an intracranial aneurysm (IA) is widespread and fatal, few drugs can be used to prevent its rupture. This study explored the molecular mechanism and potential targets of IA rupture through bioinformatics methods.
The gene expression matrices of GSE13353, GSE122897, and GSE15629 were downloaded. Differentially expressed genes (DEGs) were screened using the limma package. Functional enrichment analysis was performed, and a PPI network was constructed. Furthermore, candidate key genes were identified using the least absolute shrinkage and selection operator (LASSO) regression model, support vector machine-recursive feature elimination (SVM-RFE) analysis, and PPI network analysis. ROC analysis was conducted to further verify the diagnostic value of the key genes.
A total of 334 DEGs were screened, including 175 upregulated genes and 159 downregulated genes. Further functional analysis suggested that the DEGs were enriched in inflammation and immune response pathways. Fourteen hub genes were identified using the two algorithms. The PPI networks of the hub genes were analyzed using the Cytoscape plugin CytoNCA to obtain two key genes (IL10 and Integrin α5 (ITGA5)). The ROC curve analysis showed that the AUC values of IL10 and ITGA5 were 0.801, and 0.786, respectively. In addition, the two key genes were significantly positively correlated with macrophages and Treg (T) cells. The immune score and ESTIMATE score of the ruptured IA group were significantly higher than those of the unruptured IA group.
The increase in IL-10 and ITGA5 may weaken the vascular wall by promoting inflammation in blood vessels and immune cells, which could have a harmful effect on the rupture of IAs.
尽管颅内动脉瘤（IA）普遍存在且具有致命性，但可用于预防其破裂的药物却很少。本研究通过生物信息学方法探讨IA破裂的分子机制和潜在靶点。
下载GSE13353、GSE122897和GSE15629的基因表达矩阵。使用limma软件包筛选差异表达基因（DEG）。进行功能富集分析，并构建蛋白质-蛋白质相互作用（PPI）网络。此外，使用最小绝对收缩和选择算子（LASSO）回归模型、支持向量机-递归特征消除（SVM-RFE）分析和PPI网络分析来确定候选关键基因。进行受试者工作特征（ROC）分析以进一步验证关键基因的诊断价值。
共筛选出334个DEG，其中上调基因175个，下调基因159个。进一步的功能分析表明，这些DEG富集于炎症和免疫反应途径。使用两种算法确定了14个枢纽基因。使用Cytoscape插件CytoNCA分析枢纽基因的PPI网络，以获得两个关键基因（白细胞介素10（IL10）和整合素α5（ITGA5））。ROC曲线分析表明，IL10和ITGA5的曲线下面积（AUC）值分别为0.801和0.786。此外，这两个关键基因与巨噬细胞和调节性T（T）细胞显著正相关。破裂IA组的免疫评分和ESTIMATE评分显著高于未破裂IA组。
IL-10和ITGA5的增加可能通过促进血管和免疫细胞中的炎症来削弱血管壁，这可能对IA的破裂产生有害影响。
