Abstract
BACKGROUND: Lysine crotonylation has been implicated in the pathogenesis of preeclampsia (PE). However, the underlying mechanisms remain unclear. This study aimed to identify crotonylation-related biomarkers in PE through bioinformatics analysis. METHODS: Publicly available datasets, including GSE48424 and GSE149440, were utilized in this study. Candidate biomarkers were identified by intersecting differentially expressed genes (DEGs) from differential expression analysis with key module genes obtained through weighted gene co-expression network analysis (WGCNA). Biomarkers were further refined using expression analysis and machine learning techniques. Functional analysis, immune infiltration analysis, methylation modifications, and construction of molecular regulatory networks were employed to explore the potential mechanisms underlying the involvement of candidate biomarkers in PE pathogenesis. Additionally, associations between the biomarkers and common clinical predictive molecules were examined, and their diagnostic performance for PE was evaluated. RESULTS: A total of 323 candidate genes were identified by intersecting 3,353 DEGs with 402 key module genes. Expression analysis and machine learning algorithms pinpointed DPYD and PRDX3 as biomarkers. DPYD and PRDX3 were identified as lysine crotonylation-related biomarkers in PE. These genes were significantly downregulated in PE and associated with pathways such as olfactory signaling, neutrophil degranulation, and immune microenvironment dysregulation. Both biomarkers demonstrated excellent diagnostic efficacy (AUC > 0.85), outperforming traditional markers like VEGFA. Additionally, DPYD and PRDX3 are associated with oxidative stress and immune dysregulation, which may be the key mechanisms for the development of PE. CONCLUSION: This study identified DPYD and PRDX3 as lysine crotonylation-related biomarkers in PE, providing new insights for the diagnosis and management of the condition.