Bioinformatics analysis of the potential biomarkers for acute respiratory distress syndrome
Bioinformatics analysis of the potential biomarkers for acute respiratory distress syndrome
复制标题
急性呼吸窘迫综合征潜在生物标志物的生物信息学分析。
DOI：
10.1042/bsr20192436
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发表时间：
2020-09-04
影响因子：
4
通讯作者：
Liao, Pinhu
中科院分区：
文献类型：
--
作者：
Liao, Lin;Liao, Pinhu
背景：急性呼吸窘迫综合征（ARDS）是由不受控制的炎症引起的，肺泡巨噬细胞（AM）的激活参与了病理生理过程。本研究旨在确定AM的关键基因和通路，为ARDS的预后和早期干预提供潜在的靶点。方法：从Gene expression Omnibus数据库中获取GSE89953的mRNA表达谱。使用R软件中的LIMMA包识别差异表达基因（deg），使用clusterProfiler包进行功能富集和途径分析。通过STRING数据库和Cytoscape软件构建deg蛋白-蛋白相互作用网络，鉴定中心基因。使用从ProteomeXchange数据集中获得的差异表达蛋白（DEPs）验证Hub基因表达，以筛选潜在的生物标志物。结果：共鉴定出166个基因，其中101个基因上调，65个基因下调。上调的DEGs主要富集于调控ERK1和ERK2级联、响应干扰素γ、细胞趋化和生物过程中的迁移。在KEGG通路分析中，上调的deg主要参与类风湿关节炎、细胞因子-细胞因子受体相互作用、吞噬体、趋化因子信号通路。鉴定的12个枢纽基因包括GZMA、MPO、PRF1、CXCL8、ELANE、GZMB、SELL、APOE、SPP1、JUN、CD247和CCL2。结论：SPP1在deg和dep中均有一致的差异表达。SPP1可能是ARDS的潜在生物标志物。
Background: Acute respiratory distress syndrome (ARDS) is caused by uncontrolled inflammation, and the activation of alveolar macrophages (AM) is involved in pathophysiologic procedures. The present study aimed to identify key AM genes and pathways and try to provide potential targets for prognosis and early intervention in ARDS. Methods: The mRNA expression profile of GSE89953 was obtained from the Gene Expression Omnibus database. The LIMMA package in R software was used to identify differentially expressed genes (DEGs), and the clusterProfiler package was used for functional enrichment and pathway analyses. A protein-protein interaction network of DEGs was constructed to identify hub genes via the STRING database and Cytoscape software. Hub gene expression was validated using differentially expressed proteins (DEPs) obtained from the ProteomeXchange datasets to screen potential biomarkers. Results: A total of 166 DEGs (101 up-regulated and 65 down-regulated) were identified. The up-regulated DEGs were mainly enriched in regulation of the ERK1 and ERK2 cascade, response to interferon-gamma, cell chemotaxis, and migration in biological processes. In the KEGG pathway analysis, up-regulated DEGs were mainly involved in rheumatoid arthritis, cytokine-cytokine receptor interactions, phagosome, and the chemokine signaling pathway. The 12 hub genes identified included GZMA, MPO, PRF1, CXCL8, ELANE, GZMB, SELL, APOE, SPP1, JUN, CD247, and CCL2. Conclusion: SPP1 was consistently differentially expressed in both DEGs and DEPs. SPP1 could be a potential biomarker for ARDS.