Wang Wei, Chen Haobo, Zhou Qiaochu
Department of Gynecology, Wenzhou Hospital of Integrated Traditional Chinese and Western Medicine, Wenzhou, Zhejiang, People's Republic of China.
Department of Dermatology, Wenzhou Hospital of Integrated Traditional Chinese and Western Medicine, Wenzhou, Zhejiang, People's Republic of China.
J Inflamm Res. 2024 Oct 1;17:6917-6934. doi: 10.2147/JIR.S470087. eCollection 2024.
To date, the cause of recurrent miscarriage (RM) in at least 50% of patients remains unknown. However, no study has explored the correlation between butyrate metabolism-related genes (BMRGs) and RM.
RM-related datasets (GSE165004, GSE111974, GSE73025, and GSE179996) were obtained from the Gene Expression Omnibus (GEO) database. First, 595 differentially expressed genes (DEGs) were identified between the RM and control samples in GSE165004. Subsequently, 213 differentially expressed BMRGs (DE-BMRGs) were identified by considering the intersection of DEGs with BMRGs. The protein-protein interaction (PPI)network of DE-BMRGs contained 156 nodes and 250 edges, and a key module was obtained. In total, four biomarkers (ACTR2, ANXA2, PFN1, and OAS1) were acquired through least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), and random forest (RF). Immune analysis revealed two immune cells and three immune-related gene sets that were significantly different between the RM and control groups, namely, T helper cells, regulatory T cells (Treg), MHC class I, parainflammation, and type I IFN response. In addition, a TF-mRNA network based on the top 100 nodes ranked in the order of connectivity was created, including 100 nodes and 253 edges, such as MTERF2-ACTR2, NKX23-PFN1, STAT1-OAS1, and SP100-ANXA2.
Finally, 3 drugs (withaferin A, N-ethylmaleimide, and etoposide) were predicted to interact with 2 biomarkers (ANXA2 and ACTR2). Eventually, ANXA2 and OAS1 were significantly downregulated, and PFN1 was markedly overexpressed in the RM group, as determined by reverse transcription quantitative polymerase chain reaction (RT-qPCR).
Our findings authenticated four butyrate metabolism-related biomarkers for the diagnosis of RM, providing a scientific reference for further studies on RM treatment.
迄今为止，至少50%的复发性流产（RM）患者的病因仍不清楚。然而，尚无研究探讨丁酸代谢相关基因（BMRGs）与RM之间的相关性。
从基因表达综合数据库（GEO）中获取RM相关数据集（GSE165004、GSE111974、GSE73025和GSE179996）。首先，在GSE165004中鉴定出RM样本与对照样本之间的595个差异表达基因（DEGs）。随后，通过考虑DEGs与BMRGs的交集，鉴定出213个差异表达的BMRGs（DE-BMRGs）。DE-BMRGs的蛋白质-蛋白质相互作用（PPI）网络包含156个节点和250条边，并获得了一个关键模块。通过最小绝对收缩和选择算子（LASSO）、支持向量机递归特征消除（SVM-RFE）和随机森林（RF）总共获得了4个生物标志物（ACTR2、ANXA2、PFN1和OAS1）。免疫分析显示，RM组和对照组之间有两种免疫细胞和三个免疫相关基因集存在显著差异，即辅助性T细胞、调节性T细胞（Treg）、MHC I类、副炎症和I型干扰素反应。此外，基于按连通性排序的前100个节点创建了一个TF-mRNA网络，包括100个节点和253条边，如MTERF2-ACTR2、NKX23-PFN1、STAT1-OAS1和SP100-ANXA2。
最后，预测3种药物（Withaferin A、N-乙基马来酰亚胺和依托泊苷）与2种生物标志物（ANXA2和ACTR2）相互作用。最终，通过逆转录定量聚合酶链反应（RT-qPCR）测定，RM组中ANXA2和OAS1显著下调，PFN1明显过表达。
我们的研究结果验证了4个与丁酸代谢相关的生物标志物可用于RM的诊断，为RM治疗的进一步研究提供了科学参考。
