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五种免疫基因特征参与川崎病的发生发展和发病机制。

Five immune-gene-signatures participate in the development and pathogenesis of Kawasaki disease.

机构信息

Department of Vascular Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.

Medical College of Nanchang University, Nanchang, Jiangxi, China.

出版信息

Immun Inflamm Dis. 2021 Mar;9(1):157-166. doi: 10.1002/iid3.373. Epub 2020 Nov 14.

Abstract

OBJECTIVE

To screen for immune genes that play a major role in Kawasaki disease and to investigate the pathogenesis of Kawasaki disease through bioinformatics analysis.

METHODS

Kawasaki disease-related datasets GSE18606, GSE68004, and GSE73461 were downloaded from the Gene Expression Omnibus database. Three microarrays were integrated and standardized to include 173 Kawasaki disease samples and 101 normal samples. The samples were analyzed using CIBERSORT to obtain the infiltration of 22 immune cells and analyze the differential immune cells in the samples and correlations. The distribution of the samples was analyzed using principal component analysis (PCA). Immune-related genes were downloaded, extracted from the screened samples and analyzed for differential analysis (different expression genes [DEG]) and weighted gene co-expression network analysis (WGCNA). We constructed coexpression networks, and used the cytohobbe tool in Cytoscape to analyze the coexpression networks and select the immune genes that played a key role in them.

RESULTS

Immune cell infiltration analysis showed that B cells naive, T cells CD8, natural killer (NK) cells activated, and so forth were highly expressed in normal samples. T cells CD4 memory activated, monocytes, neutrophils, and so forth were highly expressed in Kawasaki disease samples. PCA results showed a significant difference in the distribution of normal and Kawasaki disease samples. From the screened samples, 97 upregulated and 103 downregulated immune-related genes were extracted. WGCNA analysis of DEG yielded 10 gene modules, of which the three most relevant to Kawasaki disease were red, yellow, and gray modules. They were associated with cytokine regulation, T-cell activation, presentation of T-cell receptor signaling pathways, and NK cell-mediated cytotoxicity. CXCL8, CCL5, CCR7, CXCR3, and CCR1 were identified as key genes by constructing a coexpression network.

CONCLUSION

Our study shows that we can distinguish normal samples from Kawasaki disease samples based on the infiltration of immune cells, and that CXCL8, CCL5, CCR7, CXCR3, and CCR1 may play important roles in the development of Kawasaki disease.

摘要

目的

筛选在川崎病中起主要作用的免疫基因,并通过生物信息学分析探讨川崎病的发病机制。

方法

从基因表达综合数据库中下载川崎病相关数据集 GSE18606、GSE68004 和 GSE73461。对 3 个微阵列进行整合和标准化,纳入 173 例川崎病样本和 101 例正常样本。采用 CIBERSORT 分析获得样本中 22 种免疫细胞的浸润情况,并分析样本间差异免疫细胞及相关性。采用主成分分析(PCA)分析样本分布。下载免疫相关基因,从筛选的样本中提取,进行差异分析(差异表达基因[DEG])和加权基因共表达网络分析(WGCNA)。构建共表达网络,使用 Cytoscape 中的 cytohobbe 工具分析共表达网络,并选择其中起关键作用的免疫基因。

结果

免疫细胞浸润分析显示,正常样本中 B 细胞初始、T 细胞 CD8、自然杀伤(NK)细胞激活等高度表达,川崎病样本中 T 细胞 CD4 记忆激活、单核细胞、中性粒细胞等高度表达。PCA 结果显示正常和川崎病样本分布有显著差异。从筛选的样本中提取 97 个上调和 103 个下调的免疫相关基因。对 DEG 进行 WGCNA 分析得到 10 个基因模块,其中与川崎病最相关的 3 个模块为红色、黄色和灰色模块,与细胞因子调节、T 细胞激活、T 细胞受体信号通路呈递以及 NK 细胞介导的细胞毒性有关。构建共表达网络,鉴定出 CXCL8、CCL5、CCR7、CXCR3 和 CCR1 为关键基因。

结论

本研究表明,我们可以根据免疫细胞浸润来区分正常样本和川崎病样本,并且 CXCL8、CCL5、CCR7、CXCR3 和 CCR1 可能在川崎病的发生发展中起重要作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/205d/7860604/b8e0ba2833fc/IID3-9-157-g001.jpg

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