Differential Gene Expression Analysis and Functional Prediction of Decidual Myeloid-Derived Suppressor Cells in Patients with Unexplained Recurrent Abortion
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摘要:
目的 研究不明原因复发性流产（unexplained recurrent abortion ，URSA）患者蜕膜髓系抑制细胞（myeloid-derived suppressor cells，MDSCs）差异基因表达分析及功能预测。 方法 收集2023年7月至2023年12月在云南省第一人民医院生殖妇科就诊的3例早孕期人工流产孕妇及3例URSA患者的蜕膜组织，利用MACS分选出蜕膜MDSCs细胞，经表达谱基因芯片检测，差异基因表达分析（如DESeq2或edgeR）来识别两组间基因表达的显著变化，并通过P值和多重校正（如FDR）控制假阳性率。富集分析（如GO或KEGG分析）用于评估差异基因在生物通路中的富集情况。应用 SPSS16.0 分析软件进行超几何检验或Fisher精确检验确定其显著性。 结果 与正常妊娠相比，URSA患者蜕膜MDSCs中有163个基因发生显著变化（P < 0.05），其中67个基因上调，96个基因下调。这些基因在细胞成分、生物过程、分子功能、蛋白结合、补体系统信号通路、白细胞相关激活炎症反应通路、蛋白多糖和细胞外基质受体相互作用中富集。PPI网络分析和HUB基因鉴定显示前10的HUB基因中，上调基因只有SPP1、CCL5、C3AR1和TNF，下调基因包括MXRA8、IGFBP5、SPARCL1、SAA1、DCN、COL3A1。HUB基因主要涉及免疫调节、炎症反应及细胞间交互作用。 结论 URSA患者蜕膜中的MDSCs与细胞外基质和其他细胞间的相互作用功能低下，免疫抑制能力下降，促炎反应加强。 Abstract:Objective To investigate the differential gene expression and functional prediction of decidual myeloid‐derived suppressor cells （MDSCs） in patients with unexplained recurrent abortion （URSA）. Methods Decidual tissues were collected from three pregnant women undergoing early pregnancy termination and three URSA patients at the First People's Hospital of Yunnan Province from July 2023 to December 2023. MDSCs were isolated using MACS, followed by gene expression profiling with microarray analysis. Differential gene expression was analyzed using methods such as DESeq2 or edgeR to identify significant changes in gene expression between the two groups, with control of false positive rates through P-values and multiple corrections （e.g., FDR）. Enrichment analysis （e.g., GO or KEGG analysis） was performed to evaluate the enrichment of differential genes in biological pathways. The SPSS 16.0 software was utilized for hypergeometric tests or Fisher's exact tests to determine significance. Results Compared to normal pregnancies, 163 genes showed significant changes in the decidual MDSCs of URSA patients （P < 0.05）, with 67 genes upregulated and 96 genes downregulated. These genes were enriched in cellular components, biological processes, molecular functions, protein binding, complement system signaling pathways, leukocyte-related activation inflammatory response pathways, proteoglycans, and extracellular matrix receptor interactions. PPI network analysis and HUB gene identification showed that among the top 10 HUB genes, only SPP1, CCL5, C3AR1 and TNF were up-regulated, while MXRA8, IGFBP5, SPARCL1, SAA1, DCN and COL3A1 were down-regulated. The HUB gene were mainly involved in immune regulation, inflammatory responses and intercellular interactions. Conclusion MDSCs in the decidual of URSA patients exhibit impaired interactions with the extracellular matrix and other cells, resulting in decreased immunosuppressive capacity and enhanced pro-inflammatory responses. -
图 1 蜕膜MDSCs细胞形态学及分子机制图
注：蜕膜MDSCs分为两种类型M-MDSCs和PMN-MDSCs，在蜕膜界面分别趋化不同的免疫分子。
Figure 1. Cellular morphology and molecular mechanism of MDSCs in uterine decidua
图 3 差异表达基因火山图
注：每个点代表1个基因，共
28264 基因，红／绿色虚线分别代表 P < 0.05且倍数筛选阈值|Fold change| ≥1。蓝色的点代表显著变化基因，其中左侧代表表达下调的基因，右侧代表表达上调的基因。黑色的点表示表达量没有明显变化的基因。Figure 3. Volcano plot of differential gene expression
图 4 差异表达基因热图
注：线的长度则代表距离指标，同簇样本或基因的相似性高（模式相近）。每1行为1张芯片，每1列为1个基因探针，共163个差异表达基因，红色代表上调基因，蓝色代表下调基因。
Figure 4. Heatmap of differentially expressed genes
图 5 差异表达基因GO富集分析柱状图
A：细胞组成富集分析；B：分子功能富集分析；C：生物学过程富集分析；横轴表示功能富集显著性水平（P-Value）的-Log10P 值，纵轴表示 GO term；CC: cellular component; MF：molecular function；BP: biological process。
Figure 5. Histogram of differentially expressed gene GO enrichment analysis
图 6 差异表达基因KEGG富集分析
Figure 6. KEGG enrichment analysis of differentially expressed genes
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