Identification of potential circadian rhythm-related hub genes and immune infiltration in preeclampsia through bioinformatics analysis

OBJECTIVE: Preeclampsia (PE) is a severe pregnancy complication with unclear molecular mechanisms. Emerging evidence suggests that circadian rhythm disruption contributes to PE pathogenesis. The study aims to identify circadian rhythm-related genes in PE and explore their diagnostic value and immune characteristics. METHODS: Four gene expression datasets (GSE75010, GSE60438, GSE186257, GSE14722) were downloaded from the GEO database. Modules correlated with PE were identified via weighted gene co-expression network analysis (WGCNA). Differential expression was assessed with the limma package in R, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were carried out using clusterProfiler. Diagnostic accuracy was evaluated using Receiver operating characteristic curves in training and validation sets. Immune infiltration was analyzed using CIBERSORT and Single Sample Gene Set Enrichment Analysis algorithms. PE patients were clustered into subtypes with ConsensusClusterPlus. ceRNA and Transcription Factor regulatory networks were constructed using miRTarBase, ENCODE, and NetworkAnalyst. RESULTS: CRH and LEP were identified as circadian rhythm-related hub genes with strong diagnostic value. Molecular subtyping based on their expression revealed two PE subtypes with distinct immune infiltration patterns and biological functions. Regulatory network construction highlighted potential upstream mechanisms. CONCLUSION: This bioinformatics analysis provides preliminary evidence for CRH and LEP as potential circadian rhythm-related diagnostic biomarkers in PE. However, as the findings are derived from limited GEO datasets, they should be interpreted with caution, and large‑scale, multi‑center prospective studies measuring their expression in serum or placental tissues across diverse populations are required to confirm their clinical utility.