Using weighted gene co-expression network analysis to identify key genes related to preeclampsia.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40207223", "kind": "science-record", "revision": 3, "content_hash": "sha256:aab648af9b295893e76d2de54e0f201ebd56afb38f7c8485c33a963f664dd07d", "created_at": "2026-11-01T20:30:22Z", "updated_at": "2026-11-01T22:13:52Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Using weighted gene co-expression network analysis to identify key genes related to preeclampsia.", "doi": "10.3389/fimmu.2025.1569591", "pmid": "40207223", "authors": ["Xinyang Shen", "Zhirui Zeng", "Lijia Xie", "Xiaojing Yue", "Zhijian Wang"], "journal": "Frontiers in immunology", "year": 2025, "abstract": "Introduction: The pathogenesis of preeclampsia remains unclear, highlighting the need for the creation of dependable biomarkers. This study aimed to pinpoint genetic risk factors linked to preeclampsia through the utilization of weighted gene co-expression network analysis (WGCNA).\nMethods: A gene expression profile dataset from the placentas of patients with preeclampsia was acquired from the Gene Expression Omnibus (GEO) database and employed as a discovery cohort to construct a WGCNA network. Functional enrichment analysis, pathway analysis, and the construction of protein-protein interaction (PPI) networks were performed on core genes within these modules to pinpoint hub genes. The GSE25906 dataset was utilized as a validation cohort to evaluate the diagnostic significance of the hub genes. Immunohistochemistry assays were employed to validate the protein expression levels of these genes in placental tissues from both preeclampsia and control groups.\nResults: Through WGCNA, 33 co-expression modules were identified, with 4 modules significantly associated with multiple clinical traits (≥3). Among these, 75 core genes were highlighted, predominantly enriched in pathways related to the adaptive immune response and platelet activation. Notably, TYROBP, PLEK, LCP2, HCK, and ITGAM emerged as hub genes with high PPI network scores and strong diagnostic potential, all prominently associated with immunity-related pathways. Protein expression analysis revealed that these genes were downregulated in placental tissues from preeclampsia patients compared to healthy controls.\nDiscussions: TYROBP, PLEK, LCP2, HCK, and ITGAM are closely linked to preeclampsia and hold promise as potential biomarkers for its diagnosis and for advancing the understanding of its pathogenesis.", "claims": [{"id": "claim-method", "statement": "A gene expression profile dataset from the placentas of patients with preeclampsia was acquired from the Gene Expression Omnibus (GEO) database and employed as a discovery cohort to construct a WGCNA network.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40207223", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "A gene expression profile dataset from the placentas of patients with preeclampsia was acquired from the Gene Expression Omnibus (GEO) database and employed as a discovery cohort to construct a WGCNA network."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/supplementary material.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40207223", "locator": "sections[22] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/supplementary material."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Through WGCNA, 33 co-expression modules were identified, with 4 modules significantly associated with multiple clinical traits (≥3).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40207223", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Through WGCNA, 33 co-expression modules were identified, with 4 modules significantly associated with multiple clinical traits (≥3)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Through WGCNA, 33 co-expression modules were identified, with 4 modules significantly associated with multiple clinical traits (≥3).", "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:40207223"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE25906"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE25906"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40207223", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2025.1569591", "sha256": "sha256:60eab6ff5d2177560daae07b6fbd1816ed2eca5174a1ca38d9351ec1516d9ca2", "bytes": 40139, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2025.1569591", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11979283", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE25906", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE25906", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE25906", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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