Ferroptosis-Related Proteins Are Potential Diagnostic Molecular Markers for Patients with Preeclampsia.

Preeclampsia (PE) is the leading cause of maternal and fetal mortality and morbidity. Early and accurate diagnosis is critical to reduce mortality. Placental oxidative stress has been identified as a major pathway to the development of PE. Ferroptosis, a new form of regulated cell death, is associated with iron metabolism and oxidative stress, and has been suspected to play a role in the pathophysiology of PE, although the mechanism is yet to be elucidated. The identification of potential ferroptosis-related biomarkers is of great significance for the early diagnosis and treatment of PE. A gene expression dataset of peripheral blood samples was downloaded from the Gene Expression Omnibus (GEO) dataset. Differentially expressed genes (DEGs) were filtrated with the R package “limma”. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of the DEGs were then conducted. Ferroptosis-related DEGs were screened by overlapping the ferroptosis-related genes with DEGs. The protein−protein interaction (PPI) network was used to identify the key ferroptosis-related DEGs. Enzyme-linked immunosorbent assay (ELISA) was used to validate changes in the selected key ferroptosis-related DEGs. The correlations between the key genes and clinical and pathological characteristics were analyzed. Finally, the diagnostic value of these key genes for PE was confirmed by a receiver operating characteristic (ROC) curve. A total of 5913 DEGs were identified and 45 ferroptosis-related DEGs were obtained. Besides, ferroptosis-related pathways were enriched by KEGG using DEGs. The PPI network showed that p53 and c-Jun were the critical hub genes. ELISA showed that p53 in the serum of PE patients was higher than that of the control group, while c-Jun was lower than that of the control group. Analysis of the clinicopathological features showed that p53 and c-Jun were correlated with the PE characteristics. Finally, based on the area under curve (AUC) values, c-Jun had the superior diagnostic power (AUC = 0.87, p < 0.001), followed by p53 (AUC = 0.75, p < 0.001). Our study identified that two key genes, p53 and c-Jun, might be potential diagnostic biomarkers of PE.