Abstract
Background Preeclampsia (PE) is a multisystemic syndrome which has short- and long-term risk to mothers and children and has pluralistic etiology. Objective This study is aimed at constructing a competitive endogenous RNA (ceRNA) network for pathways most related to PE using a data mining strategy based on weighted gene coexpression network analysis (WGCNA). Methods We focused on pathways involving hypoxia, angiogenesis, and epithelial mesenchymal transition according to the gene set variation analysis (GSVA) scores. The gene sets of these three pathways were enriched by gene set enrichment analysis (GSEA). WGCNA was used to study the underlying molecular mechanisms of the three pathways in the pathogenesis of PE by analyzing the relationship among pathways and genes. The soft threshold power (β) and topological overlap matrix allowed us to obtain 15 modules, among which the red module was chosen for the downstream analysis. We chose 10 hub genes that satisfied ∣log2Fold Change | >2 and had a higher degree of connectivity within the module. These candidate genes were subsequently confirmed to have higher gene significance and module membership in the red module. Coexpression networks were established for the hub genes to unfold the connection between the genes in the red module and PE. Finally, ceRNA networks were constructed to further clarify the underlying molecular mechanism involved in the occurrence of PE. 56 circRNAs, 17 lncRNAs, and 20 miRNAs participated in the regulation of the hub genes. Coagulation factor II thrombin receptor (F2R) and lumican (LUM) were considered the most relevant genes, and ceRNA networks of them were constructed. Conclusion The microarray data mining process based on bioinformatics methods constructed lncRNA and miRNA networks for ten hub genes that were closely related to PE and focused on ceRNAs of F2R and LUM finally. The results of our study may provide insight into the mechanisms underlying PE occurrence.
Highlights
Preeclampsia (PE) is a specific complication of pregnancy that occurs after 20 weeks of gestation and is characterized by new-onset hypertension and proteinuria or other signs or symptoms in the absence of proteinuria [1,2,3,4]
We found that compared with the control group, the upregulated genes in PE mainly participated in biological processes such as the inflammatory response, immune response, and extracellular matrix organization, in pathways including ECM-receptor interaction, cytokine-cytokine receptor interaction, and complement and coagulation cascades (Figure 1(c)), while the downregulated genes participated in biological processes such as the defense response to fungi, killing of cells of other organisms, and potassium ion transmembrane transport, in pathways such as neuroactive ligand-receptor interaction and amyotrophic lateral sclerosis (Figure 1(d))
We found that pathways including hypoxia, angiogenesis, and epithelial mesenchymal transition (EMT) obtained higher gene set variation analysis (GSVA) scores in PE patients and were statistically significant (P value < 0.05, Figure 2(a))
Summary
Preeclampsia (PE) is a specific complication of pregnancy that occurs after 20 weeks of gestation and is characterized by new-onset hypertension and proteinuria or other signs or symptoms in the absence of proteinuria [1,2,3,4]. According to a WHO systematic analysis, hypertensive disorders accounted for 14.0% of maternal deaths [8]. This study is aimed at constructing a competitive endogenous RNA (ceRNA) network for pathways most related to PE using a data mining strategy based on weighted gene coexpression network analysis (WGCNA). We chose 10 hub genes that satisfied ∣ log Fold Change∣ > 2 and had a higher degree of connectivity within the module. CeRNA networks were constructed to further clarify the underlying molecular mechanism involved in the occurrence of PE. The microarray data mining process based on bioinformatics methods constructed lncRNA and miRNA networks for ten hub genes that were closely related to PE and focused on ceRNAs of F2R and LUM . The results of our study may provide insight into the mechanisms underlying PE occurrence
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