In the present study, a total of five methods, namely, weighted gene co-expression network analysis (WGCNA), support vector machine-recursive feature elimination (SVM-RFE), random forest (RF), correlation with SLEDAI and differential expressed genes (DEGs) analysis, were initially applied to screen MX2, a potential biomarker for SLE. This evidence concerns the gene MX2 and systemic lupus erythematosus.