Identification of Key Genes in Systemic Lupus Erythematosus through integrated bioinformatics

Abstract

Abstract Background：Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with unclear mechanisms, limiting treatment options. Our study identifies potential core genes of SLE and their clinical applicability. Method：Using differential expression and weighted gene co-expression network analysis (WGCNA), we identified novel susceptibility modules and associated core genes. Examination of these genes through KEGG and GO analyses revealed their roles. Diagnostic performance of the core genes was evaluated using column line plot models and Receiver Operating Characteristic (ROC) curves. We also assessed the correlation between core genes and immune infiltration and used Mendelian randomization to determine the causal effect of GYPB on SLE. Results：The gene co-expression network constructed through WGCNA identified 144 key genes associated with SLE. The column line graph model demonstrated strong predictive power for SLE risk, with its diagnostic effectiveness validated by the ROC curve. A causal relationship was established between the top five core genes and immune cell infiltration in SLE. A negative correlation was observed between the gene GYPB and SLE, suggesting that GYPB might serve as a potential therapeutic target. Conclusion：This investigation provides new insights into SLE molecular mechanisms and potential therapeutic avenues.