Department of Obstetrics and Gynecology, Children's Hospital of Shanxi, Women Health Center of Shanxi, Taiyuan, 030013, Shanxi, People's Republic of China.
Endocrinology and Metabolism Center, Taiyuan Central Hospital, Taiyuan, Shanxi, People's Republic of China.
Arch Gynecol Obstet. 2023 Oct;308(4):1217-1228. doi: 10.1007/s00404-022-06805-9. Epub 2022 Oct 11.
Immune disorders lead to placental dysfunction and fetal growth restriction (FGR), but current research on the immune regulation mechanisms of FGR and the involvement of competing for endogenous RNA (ceRNA) is insufficient. Therefore, this study aimed to construct an immune-related ceRNA network to predict FGR onset risk.
Microarray data from the GEO database was used for gene expression and immune infiltration analyses. Weighted gene co-expression network analysis (WGCNA) was used to screen immune-related module genes with differential expression (DE) in FGR. A ceRNA network was constructed by integrating long non-coding RNA (lncRNA)-mRNA, lncRNA-microRNA (miRNA), and miRNA-mRNA relations. The diagnostic values of key genes in the network and their relationships with immune cell were confirmed in a validation cohort.
By comparing FGR and normal samples, DE mRNAs, miRNAs, lncRNAs, and four types of immune cells with different infiltration levels were obtained. WGCNA then revealed 236 immune-related DE mRNAs that were involved in hormone secretion and immune cell differentiation. Based on co-expression analysis and miRNA prediction, we initially constructed a ceRNA network to screen several immune-related genes as potential diagnostic biomarkers of FGR, whose superior predictive performances were further confirmed by receiver operating characteristic curves. Among them, NEURL1 and ODF3B were found to positively correlate with M1 macrophages and may participate in the immunoregulation of FGR.
From the perspective of ceRNA mechanism, we constructed an immune-related regulatory network for the first time wherein key genes are initially proposed as potential diagnostic biomarkers of FGR to involve in M1 macrophage-mediated immunoregulation.
免疫紊乱可导致胎盘功能障碍和胎儿生长受限（FGR），但目前关于 FGR 的免疫调节机制及竞争内源性 RNA（ceRNA）的研究还不够充分。因此，本研究旨在构建免疫相关的 ceRNA 网络，以预测 FGR 发病风险。
利用 GEO 数据库中的微阵列数据进行基因表达和免疫浸润分析。采用加权基因共表达网络分析（WGCNA）筛选 FGR 中差异表达（DE）的免疫相关模块基因。通过整合长非编码 RNA（lncRNA）-mRNA、lncRNA-微小 RNA（miRNA）和 miRNA-mRNA 关系，构建 ceRNA 网络。在验证队列中验证网络中关键基因的诊断价值及其与免疫细胞的关系。
通过比较 FGR 和正常样本，获得了差异表达的 mRNAs、miRNAs、lncRNAs 和四种不同浸润水平的免疫细胞。WGCNA 进一步揭示了 236 个与免疫相关的 DE mRNAs，这些基因参与了激素分泌和免疫细胞分化。基于共表达分析和 miRNA 预测，我们初步构建了 ceRNA 网络，筛选出几个免疫相关基因作为 FGR 的潜在诊断生物标志物，其预测性能通过接收者操作特征曲线得到进一步验证。其中，NEURL1 和 ODF3B 与 M1 巨噬细胞呈正相关，可能参与 FGR 的免疫调节。
从 ceRNA 机制的角度，我们首次构建了一个免疫相关的调控网络，其中关键基因初步被提出作为 FGR 的潜在诊断生物标志物，参与 M1 巨噬细胞介导的免疫调节。
