Screening biomarkers for systemic lupus erythematosus based on single-cell and bulk RNA sequencing

Abstract

Abstract Systemic lupus erythematosus (SLE) is an autoimmune disease. The pathogenesis of SLE remains unclear, and the aim of this study was to identify novel biomarkers of SLE. First, key modules and key cell clusters for the trait of sample grouping were screened by weighted gene coexpression network analysis (WGCNA). The differentially expressed genes (DEGs) between SLE and normal samples in GSE72326 were screened. The candidate genes were obtained by overlapping DEGs, key module genes, and the marker genes of key cell clusters. The random forest algorithm was executed based on candidate genes, and the top 5 genes were selected as the hub genes. In addition, gene set enrichment analysis (GSEA) of hub genes was performed. Finally, expression validation, methylation analysis, and immunoinfiltration analysis were completed. A total of 90 DEGs were obtained between SLE and control samples in the GSE72326 dataset. By random forest analysis, the hub genes (TNFSF13B, FCGR1A, TNFSF10, ISG15, LAP3) were obtained. GSEA revealed that TNFSF13B and FCGR1A were involved in primary immunodeficiency, cytosolic DNA sensing pathway, ribosome, and TNFSF10, ISG15, and LAP3 were related to pyruvate metabolism, complement and coagulation cascade. TNFSF13B, FCGR1A, TNFSF10, ISG15, and LAP3 were identified as hub genes of SLE, which provides a new perspective to study SLE. Purpose: Systemic lupus erythematosus (SLE) is an autoimmune disease. The pathogenesis of SLE remains unclear, and the aim of this study was to identify novel biomarkers of SLE. Patients and methods: First, key modules and key cell clusters for the trait of sample grouping were screened by weighted gene coexpression network analysis (WGCNA). The differentially expressed genes (DEGs) between SLE and normal samples in GSE72326 were screened. The candidate genes were obtained by overlapping DEGs, key module genes, and the marker genes of key cell clusters. The random forest algorithm was executed based on candidate genes, and the top 5 genes were selected as the hub genes. In addition, gene set enrichment analysis (GSEA) of hub genes was performed. Finally, expression validation, methylation analysis, and immunoinfiltration analysis were completed. Results: A total of 90 DEGs were obtained between SLE and control samples in the GSE72326 dataset. By random forest analysis, the hub genes (TNFSF13B, FCGR1A, TNFSF10, ISG15, LAP3) were obtained. GSEA revealed that TNFSF13B and FCGR1A were involved in primary immunodeficiency, cytosolic DNA sensing pathway, ribosome, and TNFSF10, ISG15, and LAP3 were related to pyruvate metabolism, complement and coagulation cascade. Conclusion: TNFSF13B, FCGR1A, TNFSF10, ISG15, and LAP3 were identified as hub genes of SLE, which provides a new perspective to study SLE.