First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China.
Department of Gynecology and Obstetrics, Gansu Provincial Hospital, Lanzhou, Gansu, China.
PLoS One. 2024 May 8;19(5):e0303471. doi: 10.1371/journal.pone.0303471. eCollection 2024.
Preeclampsia (PE) is a severe complication of unclear pathogenesis associated with pregnancy. This research aimed to elucidate the properties of immune cell infiltration and potential biomarkers of PE based on bioinformatics analysis.
Two PE datasets were imported from the Gene ExpressioOmnibus (GEO) and screened to identify differentially expressed genes (DEGs). Significant module genes were identified by weighted gene co-expression network analysis (WGCNA). DEGs that interacted with key module genes (GLu-DEGs) were analyzed further by Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses. The diagnostic value of the genes was assessed using receiver operating characteristic (ROC) curves and protein-protein interaction (PPI) networks were constructed using GeneMANIA, and GSVA analysis was performed using the MSigDB database. Immune cell infiltration was analyzed using the TISIDB database, and StarBase and Cytoscape were used to construct an RBP-mRNA network. The identified hub genes were validated in two independent datasets. For further confirmation, placental tissue from healthy pregnant women and women with PE were collected and analyzed using both RT-qPCR and immunohistochemistry.
A total of seven GLu-DEGs were obtained and were found to be involved in pathways associated with the transport of sulfur compounds, PPAR signaling, and energy metabolism, shown by GO and KEGG analyses. GSVA indicated significant increases in adipocytokine signaling. Furthermore, single-sample Gene Set Enrichment Analysis (ssGSEA) indicated that the levels of activated B cells and T follicular helper cells were significantly increased in the PE group and were negatively correlated with GLu-DEGs, suggesting their potential importance.
In summary, the results showed a correlation between glutamine metabolism and immune cells, providing new insights into the understandingPE pathogenesis and furnishing evidence for future advances in the treatment of this disease.
子痫前期(PE)是一种与妊娠相关的发病机制尚不清楚的严重并发症。本研究旨在通过生物信息学分析阐明免疫细胞浸润的特性和 PE 的潜在生物标志物。
从基因表达综合数据库(GEO)中导入了两个 PE 数据集,并进行筛选以鉴定差异表达基因(DEGs)。通过加权基因共表达网络分析(WGCNA)鉴定显著模块基因。进一步通过京都基因与基因组百科全书(KEGG)和基因本体论(GO)分析分析与关键模块基因(GLu-DEGs)相互作用的 DEGs。使用接收器工作特征(ROC)曲线评估基因的诊断价值,并使用 GeneMANIA 构建蛋白质-蛋白质相互作用(PPI)网络,使用 MSigDB 数据库进行 GSVA 分析。使用 TISIDB 数据库分析免疫细胞浸润,使用 StarBase 和 Cytoscape 构建 RBP-mRNA 网络。在两个独立的数据集验证鉴定的枢纽基因。为了进一步验证,收集了健康孕妇和 PE 患者的胎盘组织,并使用 RT-qPCR 和免疫组织化学进行分析。
获得了总共 7 个 GLu-DEGs,通过 GO 和 KEGG 分析发现它们涉及与硫化合物转运、PPAR 信号和能量代谢相关的途径。GSVA 表明脂肪细胞因子信号显著增加。此外,单样本基因集富集分析(ssGSEA)表明,PE 组中激活的 B 细胞和滤泡辅助 T 细胞的水平显著增加,与 GLu-DEGs 呈负相关,表明它们的潜在重要性。
总之,结果表明谷氨酰胺代谢与免疫细胞之间存在相关性,为理解 PE 发病机制提供了新的视角,并为该疾病的治疗提供了证据。