Pre-eclampsia (PE) is a multisystem pregnancy disorder characterized by placental and maternal endothelial dysfunction, and affects approximately 5% to 7% of pregnancies worldwide, leading to significant maternal and neonatal morbidity and mortality. Mounting evidence indicates that placental oxidative stress (OS) plays a critical role in the pathogenesis of PE. However, the specific mechanisms associated with OS during the occurrence and progression of PE remain largely unknown. Thus, we aimed to identify the key molecules associated with OS and explore their potential mechanisms in PE. Transcriptome data were downloaded from the Gene Expression Omnibus database, including 80 PE and 77 normal placental tissues. OS-related genes were identified using the Gene Ontology database. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to analyze the functions and pathways of the OS-related differentially expressed genes (OS-DEGs). Protein-protein interaction networks were constructed using the Search Tool for the Retrieval of Interacting Genes database, and hub genes were screened using molecular complex detection and CytoHubba. Finally, the diagnostic value and drug-gene interactions of the hub genes were evaluated. We identified 470 differentially expressed genes and 43 OS-DEGs. These genes were mainly enriched in OS-related biological processes, the HIF-1 and MAPK signaling pathways. Furthermore, 5 hub genes were identified: VEGFA, CCL2, mitogen-activated protein kinase 8 (MAPK8), HMOX1, and Cytochrome B-245 Beta Chain (CYBB). CYBB and MAPK8 had the highest diagnostic accuracies, with area under the curve values of 0.767 and 0.764, respectively. We predicted 43 potentially targeted drugs for PE treatment. CYBB and MAPK8 may be valuable biomarkers that mediate OS through multiple pathways to promote the occurrence and development of PE. We conclude from our study that OS has involvement in PE, and improved our understanding of OS-related molecular pathways in the pathogenesis of PE.
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http://dx.doi.org/10.1097/MD.0000000000041784 | DOI Listing |
Bioinformatics
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Department of Statistics, Hunan University, Changsha, 410000, China.
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