Bioinformatics analysis of the potential biomarkers for acute respiratory distress syndrome

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.