Exploring the relationship between systemic lupus erythematosus and osteoporosis based on bioinformatics

Objective This study aimed to explore the relationship between systemic lupus erythematosus (SLE) and osteoporosis (OP) based on bioinformatics. Methods The expression profiles of SLE and OP gene chips were searched through the GEO database, and the differentially expressed genes (DEGs) were screened out to obtain the intersection. Then, the Funrich software was used to predict the upstream miRNAs of the intersection genes, and the miRNA-mRNA relationship network was constructed. Afterward, the String database and Cytoscape software were used to construct the protein interaction network of the intersection genes to screen out the key genes. Finally, the functions and related pathways of key genes were analyzed by using the DAVID database. Results ①A total of 140 intersection genes of SLE and OP were obtained; ②There were 217 miRNAs regulating the intersection genes; ③IL-4, FOS, TLR1, TLR6, CD40LG, CCR1 were the key genes in the protein interaction network; ④The DAVID enrichment analysis mainly covered the positive regulation of cytokine production, the regulation of osteoclast differentiation, macrophage activation and other biological processes, involving Toll-like receptor signaling pathway, T cell receptor signaling pathway, Th1, Th2, and Th17 cells Differentiation, IL-17 signaling pathway. Conclusions SLE and OP still have some highly overlapping differential gene expressions under the background of complex gene networks. The gene functions and signaling pathways involved can simultaneously regulate the two diseases, suggesting that there is a close relationship between the molecular mechanisms of the two diseases, and that it may be a target of drugs that interfere with two diseases at the same time.

Automated summary

Through bioinformatics analysis, this study found that there are highly overlapping differential gene expressions between systemic lupus erythematosus (SLE) and osteoporosis (OP), involving common gene functions and signaling pathways. This suggests a close relationship between the molecular mechanisms of the two diseases.