原发性干燥综合征致病基因的生物信息学分析

doi:10.3969/j.issn.1004-583X.2024.09.004

摘要/Abstract

摘要：

目的利用生物信息学方法筛选原发性干燥综合征可能的致病基因,以探索可能的发病机制。方法从GEO数据库下载2个基因表达数据集,整合数据集后获取差异表达基因,并对其进行富集分析、蛋白-蛋白相互作用网络(protein-protein interaction, PPI)构建及hub基因筛选。结果共鉴定出29个差异基因(27个上调基因和2个下调基因)。GO富集结果显示这些基因参与淋巴细胞及单核细胞的分化增殖、T细胞活化、细胞-细胞间黏附的正向调节等生物学过程和趋化因子相关的分子功能。KEGG分析主要涉及趋化因子信号通路、造血细胞调控信号通路、B细胞受体信号转导、病毒蛋白与细胞因子及受体相互作用通路。从PPI网络中筛选出5个hub基因MX1、SELL、IFIT1、IFI44L、SAMD9L。结论利用生物信息学分析,确定了MX1、SELL、IFIT1、IFI44L、SAMD9L基因,可能参与了原发性干燥综合征发病。

关键词: 原发性干燥综合征, 生物信息学, 差异基因

Abstract:

Objective To screen for differentially expressed genes (DEGs) associated with primary Sjögren's syndrome(pSS) by bioinformatics and to explore its underlying pathogenesis. Methods Gene expression profiles were downloaded from the GEO database, and DEGs were obtained by integrating the datasets. Furthermore, we explored DEGs’ potential function by GO and KEGG enrichment analysis. Finally, we screened the hub genes of pSS by PPI network analysis. Results A total of 29 DEGs(27 up-regulated and 2 down-regulated) were identified, and the GO enrichment results showed that these genes are involved in lymphocyte and monocyte differentiation and proliferation, T cell activation, positive regulation of cell-cell adhesion, and chemokine-related molecular functions. KEGG analysis mainly involves chemokine signaling pathways, hematopoietic cell regulatory signaling pathways, B cell receptor signaling, viral protein-cytokine and receptor interaction pathways. Five hub genes, including MX1, SELL, IFIT1, IFI44L and SAMD9L were screened from the PPI network.Conclusion The MX1, SELL, IFIT1, IFI44L, and SAMD9L genes were identified and may be involved in pSS pathogenesis.

Key words: primary Sjögren’s syndrome, bioinformatics, DEGs

中图分类号:

R593.2

王赟, 王丹丹. 原发性干燥综合征致病基因的生物信息学分析[J]. 临床荟萃, 2024, 39(9): 792-797.

Wang Yun, Wang Dandan. Bioinformatic analysis of differentially expressed genes of primary Sjögren's syndrome[J]. Clinical Focus, 2024, 39(9): 792-797.

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链接本文: https://huicui.hebmu.edu.cn/CN/10.3969/j.issn.1004-583X.2024.09.004

https://huicui.hebmu.edu.cn/CN/Y2024/V39/I9/792

图/表 4

参考文献 34

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分类	ID	功能	P值	基因数目
GO-BP	GO:0030098	淋巴细胞分化	1.00E-05	6
	GO:0042100	B细胞增殖	1.01E-05	4
	GO:0045621	淋巴细胞分化的正向调节	1.22E-05	4
	GO:1903131	单核细胞分化	2.10E-05	6
	GO:1990266	中性粒细胞迁移	2.30E-05	4
	GO:0022409	细胞-细胞黏附的正向调节	3.93E-05	5
	GO:0046651	淋巴细胞增殖	4.20E-05	5
	GO:0032943	单核细胞增殖	4.41E-05	5
	GO:0042110	T细胞活化	4.44E-05	6
	GO:0045580	T细胞分化的调节	4.64E-05	4
GO-MF	GO:0031735	CCR10趋化因子受体结合	6.24E-06	2
	GO:0048248	CXCR3趋化因子受体结合	2.08E-05	2
	GO:0008009	趋化因子的活动	4.99E-05	3
	GO:0042379	趋化因子受体结合	0.000158	3
	GO:0045236	CXCR趋化因子受体结合	0.000314	2
	GO:0019865	免疫球蛋白结合	0.000517	2
	GO:0023026	MHC II类蛋白复合物结合	0.000714	2
	GO:0023023	MHC蛋白复合物结合	0.001271	2
	GO:0031724	CXCR5趋化因子受体结合	0.00147	1
	GO:0048020	CCR趋化因子受体结合	0.002251	2
KEGG	hsa04640	造血细胞谱系	4.34E-05	4
	hsa04062	趋化因子信号通路	0.000561	4
	hsa04662	B细胞受体信号通路	0.000605	3
	hsa04061	病毒蛋白与细胞因子和细胞因子受体的相互作用	0.001079	3

分类	ID	功能	P值	基因数目
GO-BP	GO:0030098	淋巴细胞分化	1.00E-05	6
	GO:0042100	B细胞增殖	1.01E-05	4
	GO:0045621	淋巴细胞分化的正向调节	1.22E-05	4
	GO:1903131	单核细胞分化	2.10E-05	6
	GO:1990266	中性粒细胞迁移	2.30E-05	4
	GO:0022409	细胞-细胞黏附的正向调节	3.93E-05	5
	GO:0046651	淋巴细胞增殖	4.20E-05	5
	GO:0032943	单核细胞增殖	4.41E-05	5
	GO:0042110	T细胞活化	4.44E-05	6
	GO:0045580	T细胞分化的调节	4.64E-05	4
GO-MF	GO:0031735	CCR10趋化因子受体结合	6.24E-06	2
	GO:0048248	CXCR3趋化因子受体结合	2.08E-05	2
	GO:0008009	趋化因子的活动	4.99E-05	3
	GO:0042379	趋化因子受体结合	0.000158	3
	GO:0045236	CXCR趋化因子受体结合	0.000314	2
	GO:0019865	免疫球蛋白结合	0.000517	2
	GO:0023026	MHC II类蛋白复合物结合	0.000714	2
	GO:0023023	MHC蛋白复合物结合	0.001271	2
	GO:0031724	CXCR5趋化因子受体结合	0.00147	1
	GO:0048020	CCR趋化因子受体结合	0.002251	2
KEGG	hsa04640	造血细胞谱系	4.34E-05	4
	hsa04062	趋化因子信号通路	0.000561	4
	hsa04662	B细胞受体信号通路	0.000605	3
	hsa04061	病毒蛋白与细胞因子和细胞因子受体的相互作用	0.001079	3