Background: Preeclampsia (PE) is a serious pregnancy-related disorder with incompletely understood etiology. The occurrence and development of preeclampsia are closely related to multiple biological regulatory mechanisms, among which circadian rhythm disorders are believed to possibly play an important role in abnormal placental function and immune imbalance. However, systematic research on the expression characteristics of circadian rhythm-related genes in preeclampsia and their potential diagnostic value remains scarce. This study aims to systematically identify the circadian rhythm genes associated with preeclampsia using placental RNA sequencing data, and to evaluate their biological functions and clinical diagnostic potential through comprehensive bioinformatics analysis.

Methods: Placental tissues from 5 PE patients and 6 matched controls were subjected to RNA sequencing. Bioinformatics processing included normalization and differential expression analysis using the limma package, batch-effect correction assessed via principal component analysis (PCA), and identification of circadian rhythm-related differentially expressed genes (CRRDEGs) through Venn analysis. Their expression patterns were displayed with heatmaps. Diagnostic performance was evaluated by generating receiver operating characteristic (ROC) curves and calculating area under the curve (AUC) values using the pROC package. Further functional characterization was conducted via Gene Set Enrichment Analysis (GSEA) and Gene Ontology (GO) enrichment, supported by protein–protein interaction (PPI), mRNA–miRNA, mRNA–transcription factor (TF), and mRNA–drug network analyses. Immune infiltration was examined with ssGSEA and CIBERSORT algorithms.

Results: We identified 373 differentially expressed genes (DEGs), including five CRRDEGs (MTTP, PROK1, UTS2, NKX2-1, and PRKAA2). Among them, PROK1 and NKX2-1 demonstrated high diagnostic accuracy (AUC ≥0.9). GSEA indicated significant enrichment in autophagy, autoimmune thyroid disease, transcriptional activity, and ribosomal pathways. GO analysis highlighted involvement in circadian regulation, calcium response, and lipid homeostasis. Integrated network analysis suggested relevant miRNAs, TFs, and drugs as potential therapeutic targets. Immune infiltration assessment revealed four immune cell subsets with significantly altered abundance in PE.

Conclusions: This study elucidates the role of circadian rhythm-related genes in the pathogenesis of PE and identifies candidate biomarkers and therapeutic targets. Further validation in expanded cohorts and clinical studies is necessary to translate these findings into early diagnostic and interventional strategies.