Bioinformatics identification of key candidate genes and pathways associated with systemic lupus erythematosus

Abstract

Objective

Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by autoantibody production and multi-system involvement, but the etiology is largely unclear. This study aimed to elucidate candidate genes and pathways involved in SLE.

Methods

Three original datasets GSE72509, GSE20864, and GSE39088 were downloaded from Gene Expression Omnibus (GEO) and the data were further integrated and analyzed. Subsequently, differentially expressed genes (DEGs) between SLE patients and healthy people were identified. And then we performed gene ontology (GO) function and pathway enrichment analyses of common DEGs, and constructed a protein-protein interaction (PPI) network with STRING database. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was carried out to validate the expression levels of candidate genes in blood samples from SLE patients and healthy controls.

Results

In total, 321 common DEGs were identified in SLE patients compared with healthy controls, including 231 upregulated and 90 downregulated genes. GO function analysis revealed that 321 common DEGs were mainly enriched in innate immune response, defense response, cytokine-mediated signaling pathway, response to interferon-alpha, and I-kappaB kinase/NF-kappaB signaling. Additionally, pathway enrichment analysis indicated that DEGs were mainly enriched in several signaling pathways associated with immune system and apoptosis, including RIG-I-like receptor signaling pathway, antigen processing and presentation, and p53 signaling pathway. The expression levels of candidate genes RPL26L1, FBXW11, FOXO1, and SMAD7 were validated by RT-qPCR analysis.

Conclusions

The four hub genes including RPL26L1, FBXW11, FOXO1, and SMAD7 may play key roles in the pathogenesis and development of SLE. RIG-I-like receptor signaling pathway, antigen processing and presentation pathway, and p53 signaling pathway may be closely implicated in SLE pathogenesis. Collectively, these results may provide valuable novel markers or targets for the diagnosis and treatment of SLE.

Key Points
• Integrated bioinformatics analysis of three profile datasets based on SLE patients and healthy controls was performed and 321 common DEGs were identified.
• The 321 common DEGs were mainly enriched in biological processes related to immune responses and inflammatory responses, including innate immune response, defense response, cytokine-mediated signaling pathway, response to interferon-alpha, I-kappaB kinase/NF-kappaB signaling, whereas the three most significant cellular components were oxidoreductase complex, AIM2 inflammasome complex, and ubiquitin ligase complex.
• KEGG pathway enrichment analysis indicated that common DEGs were mainly enriched in several signaling pathways associated with immune system and apoptosis, including RIG-I-like receptor signaling pathway, antigen processing and presentation, and p53 signaling pathway.
• Candidate genes RPL26L1, FBXW11, FOXO1, and SMAD7 may be closely involved in the pathogenesis and development of SLE and may provide valuable novel markers or targets for the diagnosis and treatment of SLE.

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Acknowledgments

We gratefully thank many researchers for providing technical assistance and all the patients who were enrolled in the study.

Funding

This work was supported by grants from National Natural Science Foundation of China (No. 81501417, No. 81671623) and Science and Technology Planning Project of Guangdong Province, China (2014B020212024).

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Correspondence to Erwei Sun or Yi He.

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The study was approved by the Ethics Committee of The Third Affiliated Hospital of Southern Medical University. Informed consent has been obtained from the patients’ legal guardians.

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Yang, F., Zhai, Z., Luo, X. et al. Bioinformatics identification of key candidate genes and pathways associated with systemic lupus erythematosus. Clin Rheumatol 39, 425–434 (2020). https://doi.org/10.1007/s10067-019-04751-7

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Keywords

  • Bioinformatics analysis
  • Interferon signaling pathway
  • NF-κB signaling pathway
  • RIG-I-like receptor signaling pathway
  • Systemic lupus erythematosus