Affiliation:
1. Xinjiang Hypertension Institute
Abstract
Abstract
Background: Preeclampsia is a leading cause of maternal mortality and morbidity. Owing to the poor understanding of the pathogenesis of the disease, an effective treatment forpreeclampsia is unavailable. Thus, accurate prediction of preeclampsia continues to be a clinical and research priority. The purpose of our study was to explore whether significant differentially expressed genes (DEGs) in the blood circulation of preeclampsia patients can predict the development of disease and explain the pathogenesis of preeclampsia.
Methods: First, the microarray dataset GSE48424 was downloaded from the Gene Expression Omnibus (GEO) database. GEO2R was used to identify the DEGs. Functional enrichment analyses were performed by the R package. A protein‒protein interaction network (PPI) was constructed, and module analysis was performed using STRING and Cytoscape. R language was used for the visualization of the results. GraphPad Prism was used to generate graphs. logFC (fold change) >0.58 and adj. P values<0.05 were considered statistically significant.
Results: A total of 178 DEGs were obtained, consisting of 121 downregulated genes and 57 upregulated genes. Five tumor-related hub genes were identified and considered to be significant according to scores calculated by Cytoscape. Receiver operating (ROC) curves were generated for diagnosis. Quantitative polymerase chain reaction (qPCR) was used to verify the expression levels of the hub genes.
Conclusion: POU5F1 may be a key tumor-related mRNA in the pathogenesis of
preeclampsia. Thisstudy may provide a theoretical and experimental basis for revealing the pathogenesis of preeclampsia and improving the diagnosis of preeclampsia.
Publisher
Research Square Platform LLC
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