Li Xue, Fang Yanning
Department of Obstetrics, The First People's Hospital of Jining, Jining, Shandong 272000, P.R. China.
Exp Ther Med. 2019 Sep;18(3):1837-1844. doi: 10.3892/etm.2019.7749. Epub 2019 Jul 8.
Preeclampsia is a complication of pregnancy characterized by new-onset hypertension and proteinuria of gestation, with serious consequences for mother and infant. Although a vast amount of research has been performed on the pathogenesis of preeclampsia, the underlying mechanisms of this multisystemic disease have remained to be fully elucidated. Data were retrieved from Gene Expression Omnibus database GSE40182 dataset. After data preprocessing, differentially expressed genes of placental cells cultured from preeclampsia and normal pregnancy were determined and subjected to Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to identify the associated pathways. Furthermore, functional principal component analysis (FPCA) was used to calculate the corresponding F-value of each gene. In order to further study the key signaling pathways of preeclampsia, an elastic-net regression model and the Mann-Whitney U (MWU) test were used to estimate the weight of the signaling pathways. Finally, a co-expression network was generated and hub genes were identified based on the topological features. A total of 134 pathways with a role in preeclampsia were identified. The gene expression data of placenta cells cultured for different durations were determined and F-values of genes were estimated using the FPCA model. The top 1,000 genes were identified as the differentially expressed genes and subjected to further analysis by elastic-net regression and MWU test. Two key signaling pathways were different between the preeclampsia and control groups, namely hsa05142 Chagas disease and hsa05204 Chemical carcinogenesis. Among the genes involved in these two key pathways, 13 hub genes were identified from the co-expression network. Clustering analysis demonstrated that depending on these hub genes, it was possible to divide the sample into four distinct groups based on different incubation time. The top 3 candidates were Toll-like receptor 2 (TLR2), glutathione S-transferase omega 1 (GSTO1) and mitogen-activated protein kinase 13 (MAPK13). TLR2 and associated pathways are known to be closely associated with preeclampsia, indirectly demonstrating the applicability of the analytic process applied. However, the role of GSTO1 and MAPK13 in preeclampsia has remained poorly investigated, and elucidation thereof may be a worthwhile endeavor. The present study may provide a basis for exploring potential novel genes and pathways as therapeutic targets for preeclampsia.
子痫前期是一种妊娠并发症，其特征为妊娠期新发高血压和蛋白尿，对母婴均有严重影响。尽管针对子痫前期的发病机制已开展了大量研究，但这种多系统疾病的潜在机制仍有待充分阐明。数据取自基因表达综合数据库GSE40182数据集。经过数据预处理后，确定子痫前期和正常妊娠所培养胎盘细胞的差异表达基因，并对其进行京都基因与基因组百科全书（KEGG）富集分析，以识别相关途径。此外，运用功能主成分分析（FPCA）计算每个基因的相应F值。为了进一步研究子痫前期的关键信号通路，使用弹性网络回归模型和曼-惠特尼U（MWU）检验来估计信号通路的权重。最后，构建共表达网络并根据拓扑特征识别枢纽基因。共鉴定出134条与子痫前期相关的途径。确定了不同培养时长的胎盘细胞的基因表达数据，并使用FPCA模型估计基因的F值。将前1000个基因确定为差异表达基因，并通过弹性网络回归和MWU检验进行进一步分析。子痫前期组和对照组之间存在两条关键信号通路差异，即hsa05142恰加斯病和hsa05204化学致癌作用。在这两条关键通路所涉及的基因中，从共表达网络中鉴定出13个枢纽基因。聚类分析表明，根据这些枢纽基因，有可能基于不同的孵育时间将样本分为四个不同的组。排名前三的候选基因是Toll样受体2（TLR2）、谷胱甘肽S-转移酶ω1（GSTO1）和丝裂原活化蛋白激酶13（MAPK13）。已知TLR2及其相关途径与子痫前期密切相关，间接证明了所应用分析过程的适用性。然而，GSTO1和MAPK13在子痫前期中的作用仍研究较少，对其进行阐明可能是一项有价值的工作。本研究可能为探索潜在的新基因和途径作为子痫前期的治疗靶点提供依据。
