DING Lili, LIU Xuanqi, SUN Xiaolin, GAO Yajing, WU Zhihui, WANG Yongfu. Analysis in relationships of overlapping genes in systemic sclerosis-associated interstitial lung disease, idiopathic pulmonary fibrosis and pulmonary fibrosis model induced by transforming growth factor-β[J]. Journal of Clinical Medicine in Practice, 2022, 26(14): 7-13. DOI: 10.7619/jcmp.20215125
Citation: DING Lili, LIU Xuanqi, SUN Xiaolin, GAO Yajing, WU Zhihui, WANG Yongfu. Analysis in relationships of overlapping genes in systemic sclerosis-associated interstitial lung disease, idiopathic pulmonary fibrosis and pulmonary fibrosis model induced by transforming growth factor-β[J]. Journal of Clinical Medicine in Practice, 2022, 26(14): 7-13. DOI: 10.7619/jcmp.20215125

Analysis in relationships of overlapping genes in systemic sclerosis-associated interstitial lung disease, idiopathic pulmonary fibrosis and pulmonary fibrosis model induced by transforming growth factor-β

  • Objective To analyze the relationships of overlapping genes in systemic sclerosis-associated interstitial lung disease (SSc-ILD), idiopathic pulmonary fibrosis (IPF) and pulmonary fibrosis model induced by transforming growth factor-β (TGF-β) by using bioinformatics technology.
    Methods Relevant gene chip data GSE76808 and GSE135099 of SSc-ILD, IPF and pulmonary fibrosis model induced by TGF-β were obtained from Gene Expression Omnibus (GEO) database. R software was used to analyze the data, and according to the screening conditions of adj. P<0.05 and |logFC|>1, the screened genes were analyzed by gene interaction; Gene Ontology (GO) function annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and visualization for overlapping genes were performed by using R software; protein-protein interaction (PPI) analysis of overlapping genes was performed based on string database; the hub gene was obtained by analysis tool TISIDB and its function was analyzed.
    Results Compared with the normal control group (NC group), there were differentially expressed genes in SSc-ILD, IPF and pulmonary fibrosis model induced by TGF-β. There was PPI existed in 34 overlapping genes down-regulated by SSc-ILD, IPF and pulmonary fibrosis model induced by TGF-β, and hub gene ELAVL1 was obtained. GO enrichment analysis results showed that ELAVL1 gene was not only involved in many post-transcriptional modification processes such as RNA splicing, processing and translation, but also enriched in adenylate activated protein kinase (AMPK) signal pathway.
    Conclusion In SSc-ILD and IPF, the AMPK signal may be abnormal, resulting in increasing of TGF-β, and TGF-β may be involved in the regulation of pulmonary fibrosis by regulating the translocation of ELAVL1 protein (HuR) from nucleus to cytoplasm, but the specific mechanism still needs to be further verified.
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