Abstract：
BACKGROUND: Intrauterine growth restriction (IUGR) is defined as a fetus that fails to achieve its genetically determined growth potential. The exact molecular mechanisms of placental insufficiency IUGR pathogenesis are a little known. Our goal was to identify key genes and gene co-expression modules related to placental insufficiency IUGR.
METHODS: We used weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis to examine the IUGR dataset GSE114691 from NCBI Gene Expression Omnibus. Core modules and hub nodes of the protein-protein interaction network were identified. A gene network was constructed and genes were classified by WGCNA into different modules. The validation of potential key genes was carried out using additional datasets (GSE12216 and GSE24129).
RESULTS: We identified in GSE114691 539 down regulated genes and 751 up regulated genes in placental tissues characteristic of placental insufficiency IUGR compared with non-IUGR, and defined 76 genes as hub nodes in the protein-protein interaction network. Genes in the key modules of the WGCNA network were most closely associated with placental insufficiency IUGR and significantly enriched in biological process such as cellular metabolic process and macromolecule metabolic process. We identified as key genes TGFB1, LEP, ENG, ITGA5, STAT5A, LYN, GATA3, FPR1, TGFB2, CEBPB, KLF4, FLT1, and PNPLA2. The RNA expression levels of ENG and LEP, as biomarkers, were validated.
CONCLUSIONS: A holistic gene expression profile of placental insufficiency IUGR has been generated and the key genes ENG and LEP has potential to serve as circulating diagnosis biomarkers and therapeutic targets for placental insufficiency IUGR.
METHODS: We used weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis to examine the IUGR dataset GSE114691 from NCBI Gene Expression Omnibus. Core modules and hub nodes of the protein-protein interaction network were identified. A gene network was constructed and genes were classified by WGCNA into different modules. The validation of potential key genes was carried out using additional datasets (GSE12216 and GSE24129).
RESULTS: We identified in GSE114691 539 down regulated genes and 751 up regulated genes in placental tissues characteristic of placental insufficiency IUGR compared with non-IUGR, and defined 76 genes as hub nodes in the protein-protein interaction network. Genes in the key modules of the WGCNA network were most closely associated with placental insufficiency IUGR and significantly enriched in biological process such as cellular metabolic process and macromolecule metabolic process. We identified as key genes TGFB1, LEP, ENG, ITGA5, STAT5A, LYN, GATA3, FPR1, TGFB2, CEBPB, KLF4, FLT1, and PNPLA2. The RNA expression levels of ENG and LEP, as biomarkers, were validated.
CONCLUSIONS: A holistic gene expression profile of placental insufficiency IUGR has been generated and the key genes ENG and LEP has potential to serve as circulating diagnosis biomarkers and therapeutic targets for placental insufficiency IUGR.
摘要：
背景：宫内生长受限（IUGR）被定义为胎儿未能实现其遗传决定的生长潜力。胎盘功能不全IUGR发病机制的确切分子机制鲜为人知。我们的目标是确定与胎盘功能不全IUGR相关的关键基因和基因共表达模块。
方法：我们使用加权基因共表达网络分析（WGCNA）和蛋白质-蛋白质相互作用（PPI）网络分析来检查来自NCBI基因表达综合的IUGR数据集GSE114691。确定了蛋白质-蛋白质相互作用网络的核心模块和枢纽节点。构建了基因网络，并通过WGCNA将基因分类为不同的模块。使用另外的数据集(GSE12216和GSE24129)进行潜在关键基因的验证。
结果：我们在GSE114691中确定了胎盘组织中539个下调基因和751个上调基因，与非IUGR相比，并将76个基因定义为蛋白质-蛋白质相互作用网络中的枢纽节点。WGCNA网络的关键模块中的基因与胎盘功能不全IUGR最密切相关，并且在细胞代谢过程和大分子代谢过程等生物学过程中显著富集。我们确定了关键基因TGFB1，LEP，ENG,ITGA5,STAT5A,LYN,GATA3、FPR1、TGFB2、CEBPB、KLF4、FLT1和PNPLA2。ENG和LEP的RNA表达水平,作为生物标志物，进行了验证。
结论：已经产生了胎盘功能不全IUGR的整体基因表达谱，关键基因ENG和LEP有可能作为胎盘功能不全IUGR的循环诊断生物标志物和治疗靶标。
方法：我们使用加权基因共表达网络分析（WGCNA）和蛋白质-蛋白质相互作用（PPI）网络分析来检查来自NCBI基因表达综合的IUGR数据集GSE114691。确定了蛋白质-蛋白质相互作用网络的核心模块和枢纽节点。构建了基因网络，并通过WGCNA将基因分类为不同的模块。使用另外的数据集(GSE12216和GSE24129)进行潜在关键基因的验证。
结果：我们在GSE114691中确定了胎盘组织中539个下调基因和751个上调基因，与非IUGR相比，并将76个基因定义为蛋白质-蛋白质相互作用网络中的枢纽节点。WGCNA网络的关键模块中的基因与胎盘功能不全IUGR最密切相关，并且在细胞代谢过程和大分子代谢过程等生物学过程中显著富集。我们确定了关键基因TGFB1，LEP，ENG,ITGA5,STAT5A,LYN,GATA3、FPR1、TGFB2、CEBPB、KLF4、FLT1和PNPLA2。ENG和LEP的RNA表达水平,作为生物标志物，进行了验证。
结论：已经产生了胎盘功能不全IUGR的整体基因表达谱，关键基因ENG和LEP有可能作为胎盘功能不全IUGR的循环诊断生物标志物和治疗靶标。
