Identification of differentially expressed genes and signaling pathways in chronic obstructive pulmonary disease via bioinformatic analysis. Issue 11 (29th September 2019) - Huang, Xinwei; Li, Yunwei; Guo, Xiaoran; Zhu, Zongxin; Kong, Xiangyang; Yu, Fubing; Wang, Qiang
Abstract : Chronic obstructive pulmonary disease (COPD) is a multifactorial and heterogeneous disease that creates public health challenges worldwide. The underlying molecular mechanisms of COPD are not entirely clear. In this study, we aimed to identify the critical genes and potential molecular mechanisms of COPD by bioinformatic analysis. The gene expression profiles of lung tissues of COPD cases and healthy control subjects were obtained from the Gene Expression Omnibus. Differentially expressed genes were analyzed by integration with annotations from Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, followed by construction of a protein‐protein interaction network and weighted gene coexpression analysis. We identified 139 differentially expressed genes associated with the progression of COPD, among which 14 Hub genes were identified and found to be enriched in certain categories, including immune and inflammatory response, response to lipopolysaccharide and receptor for advanced glycation end products binding; in addition, these Hub genes are involved in multiple signaling pathways, particularly hematopoietic cell lineage and cytokine‐cytokine receptor interaction. The 14 Hub genes were positively or negatively associated with COPD by wgcna analysis. The genes CX3CR1, PTGS2, FPR1, FPR2, S100A12, EGR1, CD163, S100A8 and S100A9 were identified to mediate inflammation and injury of the lung, and play critical roles in the pathogenesis of COPD. These findings improve our understanding of the underlying molecular mechanisms of COPD. Abstract : We identified that the CX3CR1, PTGS2, FPR1, FPR2, S100A12, EGR1, CD163, S100A8 and S100A9 genes may mediate inflammation and injury of the lung, and play critical roles in the pathogenesis of chronic obstructive pulmonary disease, through comprehensive bioinformatic analysis of datasets obtained from the Gene Expression Omnibus.