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pmid:40823529

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 · Olivia Holland

Frontiers in cell and developmental biology · 2025 doi:10.3389/fcell.2025.1635878

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title
Molecular signatures of preeclampsia subtypes determined through integrated weighted gene co-expression network analysis and differential gene expression analysis of placental transcriptomics.
doi
10.3389/fcell.2025.1635878
pmid
40823529
authors array · 4 items
[0]
Luhao Han
[1]
Fabricio da Silva Costa
[2]
Anthony Perkins
[3]
Olivia Holland
journal
Frontiers in cell and developmental biology
year
2025
abstract
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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Differential expression analysis between PE cases and uncomplicated controls was performed using the “limma” R package (Ritchie et al., 2015).
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sections[6] "2.4 Differential expression analysis" paragraph 2
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Differential expression analysis between PE cases and uncomplicated controls was performed using the “limma” R package (Ritchie et al., 2015).
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The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
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Integrated WGCNA and limma differential expression analysis of placental transcriptomic data identified distinct molecular signatures for severe, early-onset, and late-onset preeclampsia.
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We identified distinct molecular signatures associated with each PE subtype.
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sections[15] "3.3.1 Identification of differentially expressed genes" paragraph 2
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We performed differential expression analysis for each dataset using criteria (|log2FC| > 0.5, FDR <0.05).
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sections[15] "3.3.1 Identification of differentially expressed genes" paragraph 2
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In GSE234729 dataset, we identified 953 differentially expressed genes (DEGs) in severe PE, including 457 upregulated genes and 496 downregulated genes.
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sections[15] "3.3.1 Identification of differentially expressed genes" paragraph 2
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Analysis of the GSE75010 dataset revealed 175 DEGs in early-onset PE (103 upregulated and 72 downregulated genes) and 34 DEGs in late-onset PE (26 upregulated and 8 downregulated genes).
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Integrated WGCNA and limma differential expression analysis of placental transcriptomic data identified distinct molecular signatures for severe, early-onset, and late-onset preeclampsia.
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RNA sequencing identifies human placentalIL3RAas a potential predictor of adverse cardiovascular outcomes in patients with severe preeclampsia
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Transcriptional Profiling of Human Placentas from Pregnancies Complicated by Preeclampsia Reveals Disregulation of Sialic Acid Acetylesterase and Immune Signaling Pathways
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40823529", "kind": "science-record", "revision": 4, "content_hash": "sha256:d0ac83b0385970a422f5be54ada268318907bf241b7ad682183bf5da903c0a96", "created_at": "2026-11-01T20:30:55Z", "updated_at": "2026-11-01T22:57:02Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Molecular signatures of preeclampsia subtypes determined through integrated weighted gene co-expression network analysis and differential gene expression analysis of placental transcriptomics.", "doi": "10.3389/fcell.2025.1635878", "pmid": "40823529", "authors": ["Luhao Han", "Fabricio da Silva Costa", "Anthony Perkins", "Olivia Holland"], "journal": "Frontiers in cell and developmental biology", "year": 2025, "abstract": "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.\nMethods: 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.\nResults: 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.\nConclusion: 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.", "claims": [{"id": "claim-method", "statement": "Differential expression analysis between PE cases and uncomplicated controls was performed using the “limma” R package (Ritchie et al., 2015).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40823529", "locator": "sections[6] \"2.4 Differential expression analysis\" paragraph 2", "quote": "Differential expression analysis between PE cases and uncomplicated controls was performed using the “limma” R package (Ritchie et al., 2015)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40823529", "locator": "sections[20] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Integrated WGCNA and limma differential expression analysis of placental transcriptomic data identified distinct molecular signatures for severe, early-onset, and late-onset preeclampsia.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40823529", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We identified distinct molecular signatures associated with each PE subtype."}, {"asset": "source:pmid:40823529", "locator": "sections[15] \"3.3.1 Identification of differentially expressed genes\" paragraph 2", "quote": "We performed differential expression analysis for each dataset using criteria (|log2FC| > 0.5, FDR <0.05)."}, {"asset": "source:pmid:40823529", "locator": "sections[15] \"3.3.1 Identification of differentially expressed genes\" paragraph 2", "quote": "In GSE234729 dataset, we identified 953 differentially expressed genes (DEGs) in severe PE, including 457 upregulated genes and 496 downregulated genes."}, {"asset": "source:pmid:40823529", "locator": "sections[15] \"3.3.1 Identification of differentially expressed genes\" paragraph 2", "quote": "Analysis of the GSE75010 dataset revealed 175 DEGs in early-onset PE (103 upregulated and 72 downregulated genes) and 34 DEGs in late-onset PE (26 upregulated and 8 downregulated genes)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Integrated WGCNA and limma differential expression analysis of placental transcriptomic data identified distinct molecular signatures for severe, early-onset, and late-onset preeclampsia.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:40823529"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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