Abstract
Endometriosis is a complex gynecological condition characterized by abnormal immune responses. This study aims to explore the immunomodulatory effects of monoterpene glycosides from Paeonia lactiflora on endometriosis. Using the ssGSEA algorithm, we assessed immune cell infiltration levels between normal and endometriosis groups. Key targets were identified through differential expression analysis of the GSE51981 dataset. Potential immunomodulatory targets of Paeonia lactiflora compounds were identified through Venn diagram analysis, followed by enrichment and machine learning analyses. A nomogram was developed for predicting endometriosis, while molecular docking explored compound-target interactions. Significant differences in immune cell infiltration were observed, with increased CD8 T cells, cytotoxic cells, and others in endometriosis. Differential expression analysis identified 43 potential targets. Enrichment analysis highlighted pathways involved in immune and inflammatory responses. Machine learning identified SSTR5, CASP3, FABP2, and SYK as critical targets, contributing to a nomogram that demonstrated good predictive performance for endometriosis risk. Molecular docking revealed strong interactions between Paeoniflorigenone and CASP3. Our findings suggest that monoterpene glycosides have therapeutic effects on endometriosis by modulating key immune-related targets and pathways, providing a basis for further investigation into Paeonia lactiflora's potential as a treatment for this condition.