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Molecular signatures of preeclampsia subtypes determined through integrated weighted gene co-expression network analysis and differential gene expression analysis of placental transcriptomics
Journal article   Open access   Peer reviewed

Molecular signatures of preeclampsia subtypes determined through integrated weighted gene co-expression network analysis and differential gene expression analysis of placental transcriptomics

Luhao Han, Fabricio da Silva Costa, Anthony Perkins and Olivia Holland
Frontiers in Cell and Developmental Biology, Vol.13, pp.1-14
2025
DOI: https://doi.org/10.3389/fcell.2025.1635878
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Published VersionCC BY V4.0,  Open Access

Abstract

preeclampsia subtypes pregnancy complications hypertensive disorders of pregnancy placental gene expression transcriptomic analysis
Background: Preeclampsia (PE) is a multisystemic pregnancy syndrome that presents in different clinical subtypes. While placental dysfunction is a critical feature of PE, its contribution to different PE subtypes remains unclear. This study aims to use integrated bioinformatics analysis of placental transcriptomics to investigate subtype-specific molecular mechanisms associated with PE. Methods: A systematic search of the Gene Expression Omnibus (GEO) repository identified two datasets (GSE234729, n = 123; GSE75010, n = 157) for integrated Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis. We constructed co-expression networks and identified gene modules correlated with three PE subtypes (severe, early-onset and late-onset). Differential gene expression analysis was conducted using the “limma” R package. Differentially expressed genes (DEGs) overlapping with PE subtype-correlated WGCNA modules underwent Gene Ontology (GO) enrichment analysis. Consistently dysregulated genes were validated in an additional external dataset (GSE25906) and RT-PCR analysis of placental samples from 21 PE cases and 21 uncomplicated controls. Results: We identified distinct molecular signatures associated with each PE subtype. The green gene module was positively correlated with severe PE (r = 0.63, p = 4e-15), containing 179 DEGs primarily involved in lipid metabolism and hypoxia response processes. Early-onset PE had two highly significant gene modules: the yellow module (r = 0.73, p = 4e-15) with 112 DEGs enriched in biological processes related to gonadotrophin secretion and lipid storage, and the black module (r = −0.55, p = 5e-08) with 47 DEGs significantly enriched in chronic inflammation responses. Late-onset PE showed moderate correlation with the ivory module (r = 0.46, p = 5e-05), containing 23 DEGs enriched in p38MAPK stress-response signalling. Cross-subtype analysis identified 20 consistently dysregulated genes across three PE subtypes, with four upregulated genes (LEP, FSTL3, HTRA4, and HK2) confirmed in the external dataset GSE25906. However, RT-PCR validation showed only moderate upregulation without statistical significance. Conclusion: Though placental dysfunction occurs across all subtypes with a core set of upregulated genes, variation exits in placental gene expression patterns among PE subtypes. Severe and early-onset PE exhibit large molecular perturbations, while late-onset PE presents more subtle alterations. Aberrant placental lipid storage may contribute to disease severity and early manifestation.

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