DNA microarray and high-throughput sequencing have been widely used to identify the differentially expressed genes (DEGs) in systemic lupus erythematosus (SLE). However, the big data from gene microarrays are also challenging to work with in terms of analysis and processing. The presents study combined data from the microarray expression profile (GSE65391) and bioinformatics analysis to identify the key genes and cellular pathways in SLE. Gene ontology (GO) and cellular pathway enrichment analyses of DEGs were performed to investigate significantly enriched pathways. A protein‑protein interaction network was constructed to determine the key genes in the occurrence and development of SLE. A total of 310 DEGs were identified in SLE, including 193 upregulated genes and 117 downregulated genes. GO analysis revealed that the most significant biological process of DEGs was immune system process. Kyoto Encyclopedia of Genes and Genome pathway analysis showed that these DEGs were enriched in signaling pathways associated with the immune system, including the RIG‑I‑like receptor signaling pathway, intestinal immune network for IgA production, antigen processing and presentation and the toll‑like receptor signaling pathway. The current study screened the top 10 genes with higher degrees as hub genes, which included 2'‑5'‑oligoadenylate synthetase 1, MX dynamin like GTPase 2, interferon induced protein with tetratricopeptide repeats 1, interferon regulatory factor 7, interferon induced with helicase C domain 1, signal transducer and activator of transcription 1, ISG15 ubiquitin‑like modifier, DExD/H‑box helicase 58, interferon induced protein with tetratricopeptide repeats 3 and 2'‑5'‑oligoadenylate synthetase 2. Module analysis revealed that these hub genes were also involved in the RIG‑I‑like receptor signaling, cytosolic DNA‑sensing, toll‑like receptor signaling and ribosome biogenesis pathways. In addition, these hub genes, from different probe sets, exhibited significant co‑expressed tendency in multi‑experiment microarray datasets (P<0.01). In conclusion, these key genes and cellular pathways may improve the current understanding of the underlying mechanism of development of SLE. These key genes may be potential biomarkers of diagnosis, therapy and prognosis for SLE.
Keywords: SLE; differentially expressed genes; pathway enrichment analysis; gene ontology; protein-protein interaction network.