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. 2022 Jan 7:2022:5052354.
doi: 10.1155/2022/5052354. eCollection 2022.

ceRNA Network and Functional Enrichment Analysis of Preeclampsia by Weighted Gene Coexpression Network Analysis

Chenxu Wang  1 , Chaofan Yang  2 , Xinying Wang  2 , Guanlun Zhou  3 , Chao Chen  3 , Guorong Han  1
Affiliations

ceRNA Network and Functional Enrichment Analysis of Preeclampsia by Weighted Gene Coexpression Network Analysis

Chenxu Wang et al. Comput Math Methods Med. .

Retraction in

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.

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Conflict of interest statement

All authors report no conflicts of interest. Our study is based on open source data from GEO database, so there are no ethical issues and other conflicts of interest.

Figures

Figure 1
Figure 1
Differentially expressed gene analysis and KEGG enrichment pathway analysis of GSE96985. (a) Volcano plot of the differentially expressed circRNAs, lncRNAs, and mRNAs from GSE96985. (b) Volcano plot of the differentially expressed miRNAs from GSE96985. (c) KEGG pathway enrichment analysis of the upregulated DEmRNAs in PE. These genes are mostly involved in pathways including ECM-receptor interactions, cytokine-cytokine receptor interactions, and complement and coagulation cascades. (d) KEGG pathway analysis of the downregulated genes associated with DEmRNAs in PE patients. These genes mostly participated in pathways such as neuroactive ligand-receptor interaction and amyotrophic lateral sclerosis.
Figure 2
Figure 2
GSVA and GSEA of the GEO microarray GSE96985. (a) GSVA of the GEO microarray GSE96985. (b) GSEA of the GEO microarray GSE96985. (c–e) Heat map of the highly expressed genes in the gene sets enriched by GSEA.
Figure 3
Figure 3
Weighted gene coexpression network analysis (WGCNA) results. (a) Sample dendrogram and clinical trait heat map. (b) Analysis of network topology for various soft-thresholding powers. (c) Clustering dendrograms and modules identified by WGCNA. Colors below the tree are gene modules that correspond to the clusters. (d) Module-trait relationships. Each row corresponds to a module eigengene, each column to a trait. Each cell contains the corresponding correlation and P value. The table is color-coded by correlation according to the color legend. Red represents positive relationships, and blue represents negative relationships. (e) Bubble plot of GO and KEGG pathway terms analyzed from the red module.
Figure 4
Figure 4
Construction of a gene coexpression network centered on the hub genes. (a) Heat map of the gene expression of different samples in the red module. (b) The hub genes in the red module. (c) The expression of the ten hub genes in the PE group (P < 0.05). (d) A gene coexpression network centered by the hub genes in the red module.
Figure 5
Figure 5
ceRNA network of the hub genes. (a, b) ceRNA networks participating in the regulation of the hub genes. (c, d) ceRNA networks of F2R and LUM.
See this image and copyright information in PMC

References

    1. Redman C. W., Sargent I. L. Latest advances in understanding preeclampsia. Science . 2005;308(5728):1592–1594. doi: 10.1126/science.1111726. - DOI - PubMed
    1. American College of Obstetricians and Gynecologists. Hypertension in pregnancy. Report of the American College of Obstetricians and Gynecologists’ task force on hypertension in pregnancy. Obstetrics and Gynecology . 2013;122(5):1122–1131. - PubMed
    1. Homer C. S., Brown M. A., Mangos G., Davis G. K. Non-proteinuric pre-eclampsia: a novel risk indicator in women with gestational hypertension. Journal of Hypertension . 2008;26(2):295–302. doi: 10.1097/HJH.0b013e3282f1a953. - DOI - PubMed
    1. American College of Obstetricians and Gynecologists. ACOG Practice Bulletin No. 202 summary: gestational hypertension and preeclampsia. Obstetrics and Gynecology . 2019;133(1):p. 1. - PubMed
    1. Espinoza J., Romero R., Nien J. K., et al. Identification of patients at risk for early onset and/or severe preeclampsia with the use of uterine artery Doppler velocimetry and placental growth factor. American Journal of Obstetrics and Gynecology . 2007;196(4):326.e1–326.e13. doi: 10.1016/j.ajog.2006.11.002. - DOI - PMC - PubMed

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