Bioinformatics analysis to screen key pathogenic genes in acute exacerbation of chronic obstructive pulmonary disease

doi:10.3877/cma.j.issn.1674-6880.2022.04.001

Abstract

Abstract:

Objective

To screen key pathogenic genes in acute exacerbation of chronic obstructive pulmonary disease (AECOPD) by bioinformatics analysis.

Methods

The GSE60399 dataset was downloaded from the gene expression omnibus (GEO). The dataset included gene data of peripheral blood mononuclear cells (PBMCs) from patients with AECOPD (AECOPD group) versus healthy individuals and patients with stable chronic obstructive pulmonary disease (control group). The differentially expressed genes (DEGs) of PBMCs between the AECOPD group and control group were screened by the GEO2R analysis tool. Gene ontology (GO) analysis and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis were performed to select DEGs using the DAVID 6.8 database. Protein-protein interaction (PPI) network analysis was constructed on DEGs encoded proteins using the STRING online database, and the Cytoscape software was used to screen the top 10 key genes.

Results

A total of 106 DEGs were identified from the GSE60399 dataset, including 94 up-regulated genes and 12 down-regulated genes. GO analysis showed that the 106 DEGs were mainly involved in three biological pathways, six types of cell localization and two types of cell functions. KEGG enrichment analysis showed that the 106 DEGs mainly comprised six KEGG pathways including pertussis, complement system, staphylococcus aureus infection, systemic lupus erythematosus, cell adhesion molecules and American trypanosomiasis. The PPI network screened out 10 key genes, including fibronectin 1 (FN1), vascular endothelial growth factor A (VEGFA), actin-alpha 2 (ACTA2), connective tissue growth factor (CCN2), matrix metalloproteinase 2 (MMP2), jagged 1 (JAG1), normal epithelial cell specific (NES), cytokeratin 19 (KRT19), cadherin 5 (CDH5) and melanoma cell adhesion molecule (MCAM), which were all up-regulated genes.

Conclusion

FN1, VEGFA, ACTA2, CCN2, MMP2, JAG1, NES, KRT19, CDH5 and MCAM are key pathogenic genes in patients with AECOPD, and studies on these genes can further clarify mechanisms of occurrence and development of AECOPD.

Key words: Pulmonary disease, chronic obstructive, Acute exacerbation, Genes, Computational biology

Fang Feng, Huyong Yang, Weiwei Yang, Yu Chen. Bioinformatics analysis to screen key pathogenic genes in acute exacerbation of chronic obstructive pulmonary disease[J]. Chinese Journal of Critical Care Medicine(Electronic Edition), 2022, 15(04): 265-270.

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Figures/Tables 5

References 30

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分类	编码	功能名称	基因数	P值
GO富集生物途径	GO：0001525	血管生成	13	5.12 × 10^-5
GO富集生物途径	GO：0007155	细胞黏附	15	1.92 × 10^-3
GO富集生物途径	GO：0006508	蛋白酶解	14	1.53 × 10^-2
GO富集生物途径	GO：0070062	细胞外泌体	51	5.96 × 10^-10
GO富集生物途径	GO：0005576	胞外区	38	5.97 × 10^-10
GO富集生物途径	GO：0031012	细胞外基质	17	6.25 × 10^-9
GO富集生物途径	GO：0005578	蛋白质细胞外基质	15	1.14 × 10^-7
GO富集生物途径	GO：0005615	胞外区	26	6.82 × 10^-5
GO富集生物途径	GO：0005887	胞膜整体构件	20	4.20 × 10^-2
GO富集生物途径	GO：0004252	丝氨酸型内肽酶活性	14	4.61 × 10^-6
GO富集生物途径	GO：0005509	钙离子结合	19	1.92 × 10^-4
KEGG通路	hsa05133	百日咳	7	3.96 × 10^-3
KEGG通路	hsa04610	补体系统	6	1.02 × 10^-2
KEGG通路	hsa05150	金黄色葡萄球菌感染	6	4.77 × 10^-3
KEGG通路	hsa05322	系统性红斑狼疮	7	2.44 × 10^-2
KEGG通路	hsa04514	细胞黏附分子	7	2.65 × 10^-2
KEGG通路	hsa05142	美洲锥虫病	6	3.40 × 10^-2

分类	编码	功能名称	基因数	P值
GO富集生物途径	GO：0001525	血管生成	13	5.12 × 10^-5
GO富集生物途径	GO：0007155	细胞黏附	15	1.92 × 10^-3
GO富集生物途径	GO：0006508	蛋白酶解	14	1.53 × 10^-2
GO富集生物途径	GO：0070062	细胞外泌体	51	5.96 × 10^-10
GO富集生物途径	GO：0005576	胞外区	38	5.97 × 10^-10
GO富集生物途径	GO：0031012	细胞外基质	17	6.25 × 10^-9
GO富集生物途径	GO：0005578	蛋白质细胞外基质	15	1.14 × 10^-7
GO富集生物途径	GO：0005615	胞外区	26	6.82 × 10^-5
GO富集生物途径	GO：0005887	胞膜整体构件	20	4.20 × 10^-2
GO富集生物途径	GO：0004252	丝氨酸型内肽酶活性	14	4.61 × 10^-6
GO富集生物途径	GO：0005509	钙离子结合	19	1.92 × 10^-4
KEGG通路	hsa05133	百日咳	7	3.96 × 10^-3
KEGG通路	hsa04610	补体系统	6	1.02 × 10^-2
KEGG通路	hsa05150	金黄色葡萄球菌感染	6	4.77 × 10^-3
KEGG通路	hsa05322	系统性红斑狼疮	7	2.44 × 10^-2
KEGG通路	hsa04514	细胞黏附分子	7	2.65 × 10^-2
KEGG通路	hsa05142	美洲锥虫病	6	3.40 × 10^-2

排序	基因名称	节点度
1	FN1	4 973
2	VEGFA	3 581
3	ACTA2	3 249
4	CCN2	2 647
5	MMP2	2 408
6	JAG1	2 304
7	NES	2 286
8	KRT19	1 818
9	CDH5	1 561
10	MCAM	1 442

排序	基因名称	节点度
1	FN1	4 973
2	VEGFA	3 581
3	ACTA2	3 249
4	CCN2	2 647
5	MMP2	2 408
6	JAG1	2 304
7	NES	2 286
8	KRT19	1 818
9	CDH5	1 561
10	MCAM	1 442

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