Department of Gynecology and Obstetrics, Shengjing Hospital of China Medical University, Shenyang , Liaoning Province, China.
Key Laboratory of Maternal-Fetal Medicine of Liaoning Province, Shenyang , Liaoning Province, China.
Bioengineered. 2021 Dec;12(1):540-554. doi: 10.1080/21655979.2021.1875707.
Preeclampsia (PE) is an important topic in obstetrics. In this study, we used weighted gene co-expression network analysis (WGCNA) to screen the key modules related to immune cell infiltration and to identify the hub genes for the molecular subtyping of PE. We first downloaded a set of PE transcriptional data (GSE75010; 157 samples: 80 PE and 77 non-PE) from the GEO database. We then analyzed the PE samples and non-PE samples for immune cell infiltration and screened cells with differences in such infiltration. Next, we downloaded the immune-related genes from an immune-related database to screen the expression profile of the immune-related genes. Then, we obtained a candidate gene set by screening the immune-related genes differentially expressed between the two groups. We used WGCNA to construct a weighted co-expression network for these candidate genes, mined co-expression modules, and then calculated the correlation between each module and immune cells with differential infiltration. We screened the modules related to infiltrating immune cells, identified the key modules' hub genes, and determined the key module genes that interacted with each other. Finally, we obtained the hub genes related to the infiltrating immune cells. We classified the preeclampsia patients by unsupervised cluster molecular typing, determined the difference of immune cell infiltration among the different PE subtypes, and calculated the expression of hub genes in these different subtypes. In conclusion, we found 41 hub genes that may be closely related to the molecular typing of PE.
子痫前期（PE）是妇产科领域的一个重要课题。本研究采用加权基因共表达网络分析（WGCNA）筛选与免疫细胞浸润相关的关键模块，并鉴定 PE 分子亚类分型的枢纽基因。我们首先从 GEO 数据库中下载了一组 PE 转录组数据（GSE75010；157 个样本：80 个 PE 和 77 个非 PE）。然后，我们分析了 PE 样本和非 PE 样本的免疫细胞浸润情况，并筛选出具有不同浸润差异的细胞。接下来，我们从免疫相关数据库中下载了免疫相关基因，以筛选免疫相关基因的表达谱。然后，通过筛选两组间差异表达的免疫相关基因，获得候选基因集。我们使用 WGCNA 构建候选基因的加权共表达网络，挖掘共表达模块，并计算每个模块与具有差异浸润的免疫细胞之间的相关性。我们筛选与浸润免疫细胞相关的模块，鉴定关键模块的枢纽基因，并确定与每个模块相互作用的关键模块基因。最后，我们获得了与浸润免疫细胞相关的枢纽基因。我们通过无监督聚类分子分型对子痫前期患者进行分类，确定不同 PE 亚型之间免疫细胞浸润的差异，并计算这些不同亚型中枢纽基因的表达情况。总之，我们发现了 41 个可能与 PE 分子分型密切相关的枢纽基因。
