Construction of a diagnostic model for ischemic stroke based on immune-related genes.

IF 1.5 4区医学 Q4 NEUROSCIENCES

Folia neuropathologica Pub Date : 2024-01-01 DOI:10.5114/fn.2024.135846

Yingfeng Weng, Bin Liu, Zhibin Chen, Yangbo Hou, Dan Wu, Lin Ma, Guoyi Li

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引用次数: 0

Abstract

Introduction: This study aimed to screen immune-related marker genes of ischemic stroke (IS).

Material and methods: Two IS-related gene expression datasets were downloaded. The significantly differentially expressed genes (DEGs) and miRNAs (DEMs) between IS and control groups were selected. The differential immune cells were analysed. Weighted gene co-expression network analysis (WGCNA) was applied to analyse immune-related genes, followed by function analysis and interaction network construction. Then, key genes were further screened using optimization algorithm to construct a diagnostic model. Finally, miRNA regulatory network of several key genes was established.

Results: In total 321 DEGs and 140 DEMs were obtained. 11 immune cell types were significantly different between IS and control groups. WGCNA identified two key modules, involving 202 differential immune genes. The greenyellow module was enriched in biological processes and pathways associated with T cells, while the midnightblue module was mainly associated with apoptosis, and inflammatory response-related functions and pathways. Protein interaction network identified 10 hub nodes, such as CD8A, ITGAM and TLR4. LASSO regression selected 8 key feature genes, and a risk score model was established. Key model genes were enriched in 63 GO biological processes, such as microglial cell activation, and B cell apoptotic process, and 3 KEGG pathways, such as negative regulation of nuclear cell cycle DNA replication, and hematopoietic cell lineage. Finally, a total of 25 miRNA-target relationship pairs were obtained.

Conclusions: This study identified some immune-related marker genes and constructed a diagnostic model based on 8 immune-related genes in IS.

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基于免疫相关基因构建缺血性中风诊断模型。

简介：本研究旨在筛选缺血性脑卒中（IS）的免疫相关标记基因：本研究旨在筛选缺血性中风（IS）的免疫相关标记基因：下载两个与 IS 相关的基因表达数据集。材料和方法：下载两个 IS 相关基因表达数据集，筛选出 IS 组和对照组之间存在明显差异表达的基因（DEGs）和 miRNAs（DEMs）。分析差异免疫细胞。应用加权基因共表达网络分析（WGCNA）分析免疫相关基因，然后进行功能分析并构建相互作用网络。然后，利用优化算法进一步筛选关键基因，构建诊断模型。最后，建立了几个关键基因的 miRNA 调控网络：结果：共获得 321 个 DEGs 和 140 个 DEMs。11种免疫细胞类型在IS组和对照组之间存在明显差异。WGCNA 发现了两个关键模块，涉及 202 个差异免疫基因。黄绿色模块富集于与 T 细胞相关的生物过程和通路，而午夜蓝色模块主要与细胞凋亡和炎症反应相关的功能和通路有关。蛋白质相互作用网络确定了 10 个中心节点，如 CD8A、ITGAM 和 TLR4。LASSO 回归筛选出 8 个关键特征基因，并建立了风险评分模型。关键模型基因富集在 63 个 GO 生物过程（如小胶质细胞活化和 B 细胞凋亡过程）和 3 个 KEGG 通路（如核细胞周期 DNA 复制负调控和造血细胞系）中。最后，共获得了 25 对 miRNA-靶标关系：本研究发现了一些免疫相关标记基因，并基于 8 个免疫相关基因构建了 IS 的诊断模型。

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来源期刊

Folia neuropathologica 医学-病理学

CiteScore

2.50

自引率

5.00%

发文量

审稿时长

>12 weeks

期刊介绍： Folia Neuropathologica is an official journal of the Mossakowski Medical Research Centre Polish Academy of Sciences and the Polish Association of Neuropathologists. The journal publishes original articles and reviews that deal with all aspects of clinical and experimental neuropathology and related fields of neuroscience research. The scope of journal includes surgical and experimental pathomorphology, ultrastructure, immunohistochemistry, biochemistry and molecular biology of the nervous tissue. Papers on surgical neuropathology and neuroimaging are also welcome. The reports in other fields relevant to the understanding of human neuropathology might be considered.