Abstract
INTRODUCTION: Preeclampsia (PE) and depressive disorder (DD) exhibit clinical comorbidity, yet the molecular mechanisms underlying this association remain poorly understood. METHODS: Differential expression analysis of placental and peripheral blood transcriptomes was performed to identify PE-associated secretory protein genes. A depression-related coexpression network was constructed to obtain DD-related genes. Protein-protein interaction integration and functional enrichment analyses were then applied to identify shared regulatory pathways. Machine learning algorithms were applied to select core diagnostic genes, followed by validation in independent cohorts. A nomogram model was developed, and gene set enrichment, immune cell infiltration analysis, transcription factor regulatory mapping, and molecular docking with plasticizer compounds were conducted. RESULTS: A total of 434 secretory protein genes were associated with PE, whereas the depression-related network identified 1,165 DD-associated genes. Immune-related pathways and extracellular-matrix remodeling emerged as common mechanisms. CLEC3B, CTLA4, and PDPR were identified as core diagnostic genes and showed robust predictive performance in the nomogram model. These genes were enriched in immune-related signaling pathways, including the B-cell receptor and NOD-like receptor pathways. Aberrant proportions of naïve CD4⁺ T cells were observed, and gene expression correlated with specific immune-cell populations. Multiple transcription factors were predicted to regulate the three genes. Molecular docking indicated stable interactions between the encoded proteins and plasticizer compounds, suggesting potential environmental contributions to comorbidity. DISCUSSION: The findings provide molecular evidence linking vascular dysfunction in PE with immune-related mechanisms in DD and highlight potential biomarkers for early diagnosis and therapeutic intervention.