Potential protein biomarkers for systemic lupus erythematosus determined by bioinformatics analysis. (December 2019)

• Record Type: Journal Article
• Authors: Kong, Jie; Li, Liuxia; Zhimin, Lu; Yan, Jiaxin; Ji, Ding; Chen, Yanfeng; Yuanyuan, Wu; Chen, Xu; Shao, Haiyan; Wang, Jiehua; Da, Zhanyun
• Is Part Of: Computational biology and chemistry. Volume 83(2019)
• Publication Date: 2019-12
• Subjects: Systemic lupus erythematosus -- Bioinformatics -- Differentially expressed genes -- Protein-protein interaction network -- Hubgenes; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2019.107135
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: 90 (82 up- and 8 downregulated) DEGs common to female LN −, female LN + and male LN + using the GSE65391 and GSE49454 gene expression datasets from GEO. The STRING database identified PPI network of 70 (69 up- and 1 downregulated) out of the aforementioned 90 DEGs. Sixteen genes with the highest degree in the PPI network were identified as hubgenes. Abstract: Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disorder, and its pathogenesis in males and in cases without accompanying lupus nephritis (LN − ) is not fully understood. In this study, we identified 90 (82 up- and 8 downregulated) differentially expressed genes (DEGs) common to female LN −, female LN + and male LN + using the GSE65391 and GSE49454 gene expression datasets from Gene Expression Omnibus database (GEO). The protein-protein interaction (PPI) network of 70 DEGs was constructed using STRING and cytoscape, and the Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that the PPI network was significantly enriched in defense response to virus, cytosol, protein binding and measles. Sixteen hubgenes were identified from this PPI network, and Literature Mining Gene Networks molecular of GenCLiP 2.0 showed strong interaction between STAT1, DDX58 and IFIT1. Enrichment analysis of hubgenes in published literature showed the involvement of immune response and interferon-related genes in the pathogenesis of SLE. In addition, the transcription factors STAT1 & 2 and IRF6 & 9 had high Normalized Enrichment Score (NES). The 70 DEGs with PPI network and 16 hubgenes are potential biomarkers of SLE, and can help improve diagnosis and develop individualized therapies.