Identification and analysis of the endoplasmic reticulum stress hub genes in sepsis-associated ARDS.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40849369", "kind": "science-record", "revision": 4, "content_hash": "sha256:aed01b3612df305e48064388a28649723c3fc5a406dc399fdaa64faf89c97f29", "created_at": "2026-11-01T20:30:57Z", "updated_at": "2026-11-01T22:57:04Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and analysis of the endoplasmic reticulum stress hub genes in sepsis-associated ARDS.", "doi": "10.1038/s41598-025-16644-8", "pmid": "40849369", "authors": ["Ling Gao", "Tingting Liu", "Xiaoyan Li"], "journal": "Scientific reports", "year": 2025, "abstract": "Acute respiratory distress syndrome (ARDS) is one of the most common and serious complications in the development of sepsis. Endoplasmic reticulum stress (ERS) plays an important role in the pathophysiologic process of sepsis-associated ARDS. The aim of this study was to identify and analyze hub genes related to ERS in sepsis-associated ARDS using bioinformatics and machine learning algorithms, which may serve as diagnostic markers and therapeutic targets. Based on the GSE32707 dataset from the GEO database, differentially expressed genes (DEGs) between patients with sepsis-associated acute respiratory distress syndrome (ARDS) and healthy controls were identified. A comprehensive evaluation was performed by integrating functional enrichment analysis, immune cell infiltration analysis, and weighted gene co-expression network analysis (WGCNA). By intersecting DEGs, key WGCNA module genes, and ERS-related genes(ERGs), ERS-associated differential genes in sepsis-related ARDS were obtained. Subsequently, three machine learning algorithms-least absolute shrinkage and selection operator (LASSO), random forest (RF), and support vector machine (SVM)-were used to further screen for hub ERS hub genes. The diagnostic value of these hub genes was assessed using receiver operating characteristic (ROC) curve analysis. Finally, their expression levels were validated in clinical samples using RT-qPCR. A total of 438 DEGs and five hub genes-STAT3, HSPB1, YWHAQ, LCN2, and SGK1-were identified.Diagnostic performance analysis demonstrated that all five genes had favorable discriminatory power, indicating their potential clinical utility.Further validation in clinical samples confirmed the reliability of the bioinformatics analysis. RT-qPCR results showed that STAT3 was significantly upregulated, while YWHAQ was significantly downregulated in sepsis-associated ARDS samples compared to healthy controls, with both differences reaching statistical significance. In conclusion, STAT3 and YWHAQ, as ERS-related key genes, not only play pivotal roles in sepsis-associated ARDS but also hold promise as diagnostic biomarkers and potential therapeutic targets.", "claims": [{"id": "claim-method", "statement": "DEGs between sepsis-associated ARDS patients and healthy controls were identified using the limma package in R14,with parameters set at | logFC |> 1 and a P-value < 0.05.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40849369", "locator": "sections[4] \"DEGs analysis in sepsis-associated ARDS\" paragraph 2", "quote": "DEGs between sepsis-associated ARDS patients and healthy controls were identified using the limma package in R14,with parameters set at | logFC |> 1 and a P-value < 0.05."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets analyzed during the current study are available in the Gene Expression Omnibus (GEO) datasets (http://www.ncbi.nlm.nih.gov/geo/). All data are available from the corresponding author on reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40849369", "locator": "sections[25] \"Data availability\" paragraph 2", "quote": "The datasets analyzed during the current study are available in the Gene Expression Omnibus (GEO) datasets (http://www.ncbi.nlm.nih.gov/geo/). All data are available from the corresponding author on reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study identified five ERS-related hub genes—STAT3, HSPB1, YWHAQ, LCN2, and SGK1—and RT-qPCR confirmed significant upregulation of STAT3 and significant downregulation of YWHAQ in sepsis-associated ARDS samples.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40849369", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "A total of 438 DEGs and five hub genes—STAT3, HSPB1, YWHAQ, LCN2, and SGK1—were identified."}, {"asset": "source:pmid:40849369", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "RT-qPCR results showed that STAT3 was significantly upregulated, while YWHAQ was significantly downregulated in sepsis-associated ARDS samples compared to healthy controls, with both differences reaching statistical significance."}, {"asset": "source:pmid:40849369", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Based on the GSE32707 dataset from the GEO database, differentially expressed genes (DEGs) between patients with sepsis-associated acute respiratory distress syndrome (ARDS) and healthy controls were identified."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study identified five ERS-related hub genes—STAT3, HSPB1, YWHAQ, LCN2, and SGK1—and RT-qPCR confirmed significant upregulation of STAT3 and significant downregulation of YWHAQ in sepsis-associated ARDS samples.", "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:40849369"], "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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