Zhan Jin, Wu Jiajie
Department of Gynaecology, Ningbo Municipal Hospital of Traditional Chinese Medicine, Affiliated Hospital of Zhejiang Chinese Medical University, No.819, Liyuan North Road, Haishu District, Ningbo, Zhejiang Province, 315010, China.
Emergency Department, Ningbo Municipal Hospital of Traditional Chinese Medicine, Affiliated Hospital of Zhejiang Chinese Medical University, Ningbo, Zhejiang Province, China.
Hereditas. 2025 Jan 3;162(1):1. doi: 10.1186/s41065-024-00354-8.
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.
子宫内膜异位症是一种以异常免疫反应为特征的复杂妇科疾病。本研究旨在探讨芍药单萜苷对子宫内膜异位症的免疫调节作用。使用单样本基因集富集分析(ssGSEA)算法,我们评估了正常组和子宫内膜异位症组之间的免疫细胞浸润水平。通过对GSE51981数据集的差异表达分析确定关键靶点。通过维恩图分析确定芍药化合物的潜在免疫调节靶点,随后进行富集和机器学习分析。开发了一种列线图用于预测子宫内膜异位症,同时通过分子对接探索化合物与靶点的相互作用。观察到免疫细胞浸润存在显著差异,子宫内膜异位症中CD8 T细胞、细胞毒性细胞等增加。差异表达分析确定了43个潜在靶点。富集分析突出了参与免疫和炎症反应的途径。机器学习确定促甲状腺激素释放激素受体5(SSTR5)、半胱天冬酶3(CASP3)、脂肪酸结合蛋白2(FABP2)和脾酪氨酸激酶(SYK)为关键靶点,有助于构建对子宫内膜异位症风险具有良好预测性能的列线图。分子对接显示芍药苷元与CASP3之间有强烈的相互作用。我们的研究结果表明,单萜苷通过调节关键的免疫相关靶点和途径对子宫内膜异位症具有治疗作用,为进一步研究芍药治疗这种疾病的潜力提供了依据。