Identification of key genes and molecular mechanisms of chronic urticaria based on bioinformatics.

{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38558219", "kind": "science-record", "revision": 2, "content_hash": "sha256:21411700eda2d96c090866d78a88b237bcf2899348428c670b9fd411eca9f35e", "created_at": "2026-11-01T19:20:31Z", "updated_at": "2026-11-01T21:32:49Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of key genes and molecular mechanisms of chronic urticaria based on bioinformatics.", "doi": "10.1111/srt.13624", "pmid": "38558219", "authors": ["Haichao Guo", "Lifang Guo", "Li Li", "Na Li", "Xiaoyun Lin", "Yanjun Wang"], "journal": "Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)", "year": 2024, "abstract": "Chronic urticaria (CU) is characterized by persistent skin hives, redness, and itching, enhanced by immune dysregulation and inflammation. Our main objective is identifying key genes and molecular mechanisms of chronic urticaria based on bioinformatics. We used the Gene Expression Omnibus (GEO) database and retrieved two GEO datasets, GSE57178 and GSE72540. The raw data were extracted, pre-processed, and analyzed using the GEO2R tool to identify the differentially expressed genes (DEGs). The samples were divided into two groups: healthy samples and CU samples. We defined cut-off values of log2 fold change ≥1 and p < .05. Analyses were performed in the Kyoto Encyclopaedia of Genes and Genomes (KEGG), the Database for Annotation, Visualization and Integrated Discovery (DAVID), Metascape, Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and CIBERSOFT databases. We obtained 1613 differentially expressed genes. There were 114 overlapping genes in both datasets, out of which 102 genes were up-regulated while 12 were down-regulated. The biological processes included activation of myeloid leukocytes, response to inflammations, and response to organic substances. Moreover, the KEGG pathways of CU were enriched in the Nuclear Factor-Kappa B (NF-kB) signaling pathway, Tumor Necrosis Factor (TNF) signaling pathway, and Janus kinase/signal transducers and activators of transcription (JAK-STAT) signaling pathway. We identified 27 hub genes that were implicated in the pathogenesis of CU, such as interleukin-6 (IL-6), Prostaglandin-endoperoxide synthase 2 (PTGS2), and intercellular adhesion molecule-1 (ICAM1). The complex interplay between immune responses, inflammatory pathways, cytokine networks, and specific genes enhances CU. Understanding these mechanisms paves the way for potential interventions to mitigate symptoms and improve the quality of life of CU patients.", "claims": [{"id": "claim-method", "statement": "The raw data from the GEO datasets were extracted, pre‐processed, and analyzed using the GEO2R tool (https://www.ncbi.nlm.nih.gov/geo/geo2r/) to identify the DEGs. In the GEO2R tool, we adjusted the Benjamini & Hochberg to regulate false discovery rates and test for multiple corrections to eliminate false positives.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38558219", "locator": "sections[4] \"Identification of differentially expressed genes (DEGs)\" paragraph 2", "quote": "The raw data from the GEO datasets were extracted, pre‐processed, and analyzed using the GEO2R tool (https://www.ncbi.nlm.nih.gov/geo/geo2r/) to identify the DEGs. In the GEO2R tool, we adjusted the Benjamini & Hochberg to regulate false discovery rates and test for multiple corrections to eliminate false positives."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Data for this study is available from the corresponding author upon reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38558219", "locator": "sections[22] \"DATA AVAILABILITY STATEMENT\" paragraph 2", "quote": "Data for this study is available from the corresponding author upon reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We obtained and processed all the raw data from the GEO datasets to identify 1613 differentially expressed genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38558219", "locator": "sections[9] \"Identification of DEGs in CU\" paragraph 2", "quote": "We obtained and processed all the raw data from the GEO datasets to identify 1613 differentially expressed genes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "We obtained and processed all the raw data from the GEO datasets to identify 1613 differentially expressed genes.", "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:38558219"], "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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