Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia 35131, Greece.
Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia 35131, Greece.
Pregnancy Hypertens. 2020 Jan;19:52-60. doi: 10.1016/j.preghy.2019.12.007. Epub 2019 Dec 20.
Preeclampsia (PE) is a serious complication of pregnancy. It is considered a complex condition influenced by maternal genes, environmental factors and a deregulated immune response of the mother, but the etiology is largely unknown. The aim of this study is to identify differentially expressed genes (DEGs) in PE, to help elucidate the identification of the disease etiological mechanisms.
The databases Pubmed and GEO were searched according to PRISMA guidelines for the existence of gene expression data on placental samples from case-control studies. After meta-analysis the identified DEGs were further analyzed with STRING and PANTHER to retrieve interaction networks and overrepresented biochemical pathways.
Only 10 gene expression datasets and articles fulfilled inclusion criteria, containing data on 195 patients and 231 controls, and were analyzed. Meta-analysis identified 629 DEGs to be associated with PE at a False Discovery Rate p-value of 0.01. Network analysis showed few highly interconnected genes involved in innate immunity and signal transduction pathways indicative of a multifaceted disease with etiological heterogeneity. over representation analysis revealed that these genes participate mainly in carbohydrates, amino acids and pyrimidine metabolism, circadian clock system and signal transduction pathways.
This work, combining rigorous methods of meta-analysis and the use of modern bioinformatics tools, proposes the existence of novel, overlooked so far, biochemical pathways and mechanisms to contribute to PE development such as carbohydrate, aminoacids and pyrimidine metabolism. Our findings pave the way for further investigation of the above pathways in experimental efforts to decipher the orchestrating mechanisms for PE development.
子痫前期（PE）是妊娠的严重并发症。它被认为是一种复杂的疾病，受母体基因、环境因素和母体免疫反应失调的影响，但病因在很大程度上尚不清楚。本研究的目的是鉴定 PE 中的差异表达基因（DEGs），以帮助阐明疾病发病机制的鉴定。
根据 PRISMA 指南，在 Pubmed 和 GEO 数据库中搜索了关于病例对照研究中胎盘样本基因表达数据的存在情况。在荟萃分析后，使用 STRING 和 PANTHER 进一步分析鉴定的 DEGs，以检索相互作用网络和过表达的生化途径。
只有 10 个基因表达数据集和文章符合纳入标准，包含了 195 名患者和 231 名对照的数据，并进行了分析。荟萃分析确定了 629 个与 PE 相关的 DEGs，其假发现率 p 值为 0.01。网络分析显示，有几个高度相互关联的基因参与固有免疫和信号转导途径，表明这是一种具有病因异质性的多方面疾病。过表达分析显示，这些基因主要参与碳水化合物、氨基酸和嘧啶代谢、昼夜节律系统和信号转导途径。
这项工作结合了荟萃分析的严格方法和现代生物信息学工具的使用，提出了存在新的、迄今为止被忽视的生化途径和机制，以促进 PE 的发展，如碳水化合物、氨基酸和嘧啶代谢。我们的研究结果为进一步研究上述途径在实验中阐明 PE 发展的协调机制铺平了道路。
