Shen Jiayu, Teng Xinyuan, Zhao Jiayao, Feng Yuanling, Wang Liquan
Department of Obstetrics, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009 Hangzhou, Zhejiang, China.
Front Biosci (Landmark Ed). 2023 Jul 4;28(7):132. doi: 10.31083/j.fbl2807132.
Preeclampsia (PE) is a significant cause of maternal and offspring mortality and morbidity. The purpose of this study is to identify the potential diagnostic signatures of autophagy-related genes (ATGs) in pregnancies with preeclampsia.
The expression profile of mRNA was obtained from GSE75010 (placenta samples) and GSE48424 dataset (blood samples). The potential differentially expressed ATGs of PE were screened by R software. The gene-ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, correlation analysis, and protein-protein interactions (PPI) were applied for the differentially expressed ATGs. The diagnostic markers of PE were then screened based on least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination (SVM-RFE). Receiver operating characteristic (ROC) analysis was used to investigate the predictive value of these diagnostic markers. Target miRNAs were predicted based on the miRDB, DIANA-micro T, Targetscan, and miRWalk databases, and were further validated in GSE84260.
A total of 20 differentially expressed ATGs were identified between PE and healthy pregnancies. Functional analysis of differentially expressed ATGs indicated several enriched terms related to autophagy, apoptosis, angiogenesis, inflammation, immune response, hypoxia-inducible factor 1 (HIF-1), forkhead box O (FoxO) and AMP-activated protein kinase (AMPK) signaling pathway. A total of 12 ATGs were recognized based on LASSO and SVM-RFE, which made an excellent distinction in both the placenta tissues (area under the curve [AUC] = 0.903) and the blood samples (AUC = 0.972). Furthermore, four feature ATGs (leptin [], ERO1-like [], phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit beta [], and mitogen-activated protein kinase 8 []) were screened and also shown an excellent diagnostic efficacy (AUC = 0.869 in placenta samples, and AUC = 0.914 in blood samples). Additionally, 81 target miRNAs were predicted according to the 4 feature ATGs. After evaluating the miRNA expression pattern of GSE84260, 11 miRNAs were selected. Finally, a miRNA-mRNA regulatory network was constructed, which may participate in the development of PE.
We established an autophagy-related-gene based signature that may predict pregnancies with PE. And we also constructed a miRNA-mRNA regulatory network, which may deepen our understanding of the molecular mechanism underlying the development of PE.
子痫前期（PE）是孕产妇和子代发病及死亡的重要原因。本研究旨在识别子痫前期妊娠中自噬相关基因（ATG）的潜在诊断特征。
从GSE75010（胎盘样本）和GSE48424数据集（血液样本）获取mRNA表达谱。用R软件筛选PE潜在的差异表达ATG。对差异表达的ATG进行基因本体（GO）富集分析、京都基因与基因组百科全书（KEGG）通路富集分析、相关性分析及蛋白质-蛋白质相互作用（PPI）分析。然后基于最小绝对收缩和选择算子（LASSO）逻辑回归及支持向量机递归特征消除（SVM-RFE）筛选PE的诊断标志物。采用受试者工作特征（ROC）分析研究这些诊断标志物的预测价值。基于miRDB、DIANA-micro T、Targetscan和miRWalk数据库预测靶miRNA，并在GSE84260中进一步验证。
在PE与正常妊娠之间共鉴定出20个差异表达的ATG。差异表达ATG的功能分析表明有几个富集的术语与自噬、凋亡、血管生成、炎症、免疫反应、缺氧诱导因子1（HIF-1）、叉头框O（FoxO）和AMP激活的蛋白激酶（AMPK）信号通路有关。基于LASSO和SVM-RFE共识别出12个ATG，其在胎盘组织（曲线下面积[AUC]=0.903）和血液样本（AUC=0.972）中均有出色的区分能力。此外，筛选出4个特征性ATG（瘦素、ERO1样蛋白、磷脂酰肌醇-4,5-二磷酸3-激酶催化亚基β和丝裂原活化蛋白激酶8），其诊断效能也很出色（胎盘样本中AUC= .869，血液样本中AUC=0.914）。另外，根据4个特征性ATG预测出81个靶miRNA。评估GSE84260的miRNA表达模式后，选择了11个miRNA。最后构建了一个miRNA-mRNA调控网络，其可能参与PE的发生发展。
我们建立了一个基于自噬相关基因的特征，可预测子痫前期妊娠。我们还构建了一个miRNA-mRNA调控网络，这可能加深我们对PE发生发展分子机制的理解。
