Bioinformatics analysis combined with untargeted metabolomics reveals lipid metabolism-related genes and their biological markers in chronic spontaneous urticaria.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40901677", "kind": "science-record", "revision": 4, "content_hash": "sha256:a11e25b013374f8d4844e76ef95c989cb376957cb8209f49480748fe8bce953a", "created_at": "2026-11-01T20:31:01Z", "updated_at": "2026-11-01T22:57:08Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics analysis combined with untargeted metabolomics reveals lipid metabolism-related genes and their biological markers in chronic spontaneous urticaria.", "doi": "10.3389/fgene.2025.1550205", "pmid": "40901677", "authors": ["Zhiming Hu", "Qiong Wang", "Yuqi Wang", "Yao Gao", "Jianhua Hao", "Rui Li", "Hua Zhao", "Shuping Guo", "Hongzhou Cui"], "journal": "Frontiers in genetics", "year": 2025, "abstract": "Background: Chronic spontaneous urticaria (CSU) is an immune-driven skin condition with a multifaceted and not yet fully understood pathogenesis. Although substantial research has been conducted, viable therapeutic targets are still scarce. Studies indicate that disruptions in lipid metabolism significantly influence the development of immune-related disorders. Nevertheless, the precise relationship between lipid metabolism and CSU remains underexplored, warranting further investigation.\nMethods: We obtained the GSE72540 and GSE57178 datasets from the Gene Expression Omnibus (GEO) repository. For the GSE72540 dataset, we identified differentially expressed genes (DEGs) and performed weighted gene co-expression network analysis (WGCNA) on them. The identified DEGs were cross-referenced with lipid metabolism-related genes (LMRGs). To identify hub genes, we constructed a protein-protein interaction (PPI) network. These hub genes were validated using the GSE57178 dataset to identify potential diagnostic markers. Additionally, gene set enrichment analysis (GSEA) and receiver operating characteristic (ROC) curve analysis were employed to evaluate their diagnostic potential. In the CSU mouse model, we further validated the expression levels of these hub genes. Finally, untargeted metabolomics was conducted to detect lipid metabolism-related metabolites in the serum of CSU patients.\nResult: Using bioinformatics analysis, three hub genes were identified: SLC2A4, PTGS2, and PLA2G2A. In skin tissues from CSU-like mouse models, the mRNA levels of PTGS2 and PLA2G2A were significantly upregulated compared to the control group. Additionally, untargeted metabolomics revealed 60 distinct lipid metabolites, with a marked increase in arachidonic acid levels observed in the CSU group.\nConclusion: PTGS2 and PLA2G2A are key hub genes for CSU, and arachidonic acid can serve as a potential serum biomarker.", "claims": [{"id": "claim-method", "statement": "In our study, we utilized the “limma” package (version 3.40.6) to perform differential expression analysis, identifying DEGs between skin samples of CSU and healthy.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40901677", "locator": "sections[4] \"2.2 Recognition of differentially expressed genes (DEGs)\" paragraph 2", "quote": "In our study, we utilized the “limma” package (version 3.40.6) to perform differential expression analysis, identifying DEGs between skin samples of CSU and healthy."}], "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 authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40901677", "locator": "sections[35] \"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 authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "PTGS2 and PLA2G2A are key hub genes for CSU, and arachidonic acid can serve as a potential serum biomarker.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40901677", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "PTGS2 and PLA2G2A are key hub genes for CSU, and arachidonic acid can serve as a potential serum biomarker."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "PTGS2 and PLA2G2A are key hub genes for CSU, and arachidonic acid can serve as a potential serum biomarker.", "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:40901677"], "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:GSE57178"], "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:GSE57178"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40901677", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fgene.2025.1550205", "sha256": 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In the CSU mouse model, we further validated the expression levels", "luate their diagnostic potential. In the CSU mouse model, we further validated the expression l", ", and PLA2G2A. In skin tissues from CSU-like mouse models, the mRNA levels of PTGS2 and PLA2G2A", "12 h. After a 1-week adaptation period, the mice were randomly divided into the normal control gro"], "order_basis": "paper_text_order:1317", "id": "assay:1"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["In our study, we utilized the “limma” package (version 3.40.6) to perform differential expression analysis, identifying DEGs between skin samples of CSU and healthy."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}