Exploration of the shared pathways and common biomarker LY96 in Endometriosis and Systemic lupus erythematosus using integrated bioinformatics analysis

Abstract

Endometriosis (EMS) is a chronic gynecological disorder that affects 5–10% of women of reproductive age, and Systemic lupus erythematosus (SLE) is one of the most prevalent systemic autoimmune diseases. Despite clinical evidence suggesting potential associations between EMS and SLE, the underlying pathogenesis is yet unclear. This article aimed to explore the shared gene signatures and potential molecular mechanisms in EMS and SLE. Microarray data were downloaded from the Gene Expression Omnibus (GEO) database and used to screen for differentially expressed genes (DEGs) in the SLE datasets. A weighted gene co-expression network analysis (WGCNA) was used to identify the co-expression modules of EMS. cytoscape software and three machine learning algorithms were used to determine critical biomarkers, and a diagnostic model was built using the XG-Boost machine learning algorithms. Immune cell infiltration analysis was used to investigate the correlation between immune cell infiltration and common biomarkers of EMS and SLE. Results revealed that shared genes enriched in immune-related pathways and inflammatory responses. The area under the receiver operating characteristic (AUROC) curve and the Precision-Recall (PR) curves showed satisfactory performance of the model. immune cell infiltration analysis showed that the expression of hub genes was closely associated with immune cells. RT-qPCR results indicated that LY96 might be the best biomarker for EMS and SLE.