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pmid:40503488

Identification of CD19+B Cell as a Diagnostic Biomarker in Sepsis-Induced ARDS.

Xiaoyun Fu · Jiaqi Su · Xinyu Li · Chen Zhang · Xiaoxiao Yu

Journal of inflammation research · 2025 doi:10.2147/JIR.S519346

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:40503488
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science-record
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created_at
2026-11-01T20:30:37Z
updated_at
2026-11-01T22:14:11Z
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paper object · 10 fields
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title
Identification of CD19+B Cell as a Diagnostic Biomarker in Sepsis-Induced ARDS.
doi
10.2147/JIR.S519346
pmid
40503488
authors array · 5 items
[0]
Xiaoyun Fu
[1]
Jiaqi Su
[2]
Xinyu Li
[3]
Chen Zhang
[4]
Xiaoxiao Yu
journal
Journal of inflammation research
year
2025
abstract
Background: Sepsis has a high morbidity and mortality rate in critically ill patients, and acute respiratory distress syndrome (ARDS) is one of its most common outcomes. However, there is still no effective biomarker to predict the risk and outcome of ARDS induced by sepsis. Methods: In this research, the GSE32707 dataset was acquired from the Gene Expression Omnibus (GEO) database and used to identify differentially expressed genes (DEGs). The extracellular protein-related differentially expressed genes (EP-DEGs) were filtered using the Human Protein Atlas (HPA) and UniProt databases. Functional and pathway analyses of the EP-DEGs were conducted through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Additionally, hub genes were identified using STRING, Cytoscape, MCODE, and Cytohubba. The expressions of the hub genes were analyzed in both the training set (GSE32707) and the validation set (GSE66890). The diagnostic potential of lymphocyte subsets was evaluated through ROC curve assessment in the clinical cohort. Results: We identified 86 EP-DEGs from DEGs. These EP-DEGs were found to be significantly enriched in leukocyte mediated immunity. We also identified 5 key extracellular protein genes GNLY, GZMK, CST7, PTPRC and CD19. CD19 expressions were increased in both training and validation sets. ROC curves showed that CD19 expression had a higher accuracy in the diagnosis of sepsis-induced ARDS. Lymphocyte subsets analysis of clinical samples revealed that CD19+B cells were elevated in sepsis-induced ARDS, with CD19+B cell counts demonstrating a higher diagnostic accuracy (AUC = 0.829) for septic-ARDS compared to other lymphocyte subsets. Conclusion: In this study, we employed bioinformatics approaches to identify potential biomarkers for sepsis-induced ARDS and further validated these findings using clinical samples. Our results suggest that peripheral CD19+ B cells could act as a promising biomarker in sepsis-induced ARDS.
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The diagnostic accuracy of indicators was evaluated using receiver operating characteristic (ROC) curve analysis.
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The datasets generated and/or analyzed during this study are available from the corresponding author upon reasonable request.
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Our results suggest that peripheral CD19+ B cells could act as a promising biomarker in sepsis-induced ARDS.
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Our results suggest that peripheral CD19+ B cells could act as a promising biomarker in sepsis-induced ARDS.
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Our results suggest that peripheral CD19+ B cells could act as a promising biomarker in sepsis-induced ARDS.
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Inflammasome-regulated cytokines are critical mediators of lung injury in humans.
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Expression of Neutrophil-related genes in patients with early sepsis-induced ARDS
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[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
limma
order_basis
analysis_only
id
assay:1
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40503488", "kind": "science-record", "revision": 3, "content_hash": "sha256:de699ba219c427c3d0c90d66fd3693f84728a1227e1fbaca64ee6af4d68ae71a", "created_at": "2026-11-01T20:30:37Z", "updated_at": "2026-11-01T22:14:11Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of CD19+B Cell as a Diagnostic Biomarker in Sepsis-Induced ARDS.", "doi": "10.2147/JIR.S519346", "pmid": "40503488", "authors": ["Xiaoyun Fu", "Jiaqi Su", "Xinyu Li", "Chen Zhang", "Xiaoxiao Yu"], "journal": "Journal of inflammation research", "year": 2025, "abstract": "Background: Sepsis has a high morbidity and mortality rate in critically ill patients, and acute respiratory distress syndrome (ARDS) is one of its most common outcomes. However, there is still no effective biomarker to predict the risk and outcome of ARDS induced by sepsis.\nMethods: In this research, the GSE32707 dataset was acquired from the Gene Expression Omnibus (GEO) database and used to identify differentially expressed genes (DEGs). The extracellular protein-related differentially expressed genes (EP-DEGs) were filtered using the Human Protein Atlas (HPA) and UniProt databases. Functional and pathway analyses of the EP-DEGs were conducted through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Additionally, hub genes were identified using STRING, Cytoscape, MCODE, and Cytohubba. The expressions of the hub genes were analyzed in both the training set (GSE32707) and the validation set (GSE66890). The diagnostic potential of lymphocyte subsets was evaluated through ROC curve assessment in the clinical cohort.\nResults: We identified 86 EP-DEGs from DEGs. These EP-DEGs were found to be significantly enriched in leukocyte mediated immunity. We also identified 5 key extracellular protein genes GNLY, GZMK, CST7, PTPRC and CD19. CD19 expressions were increased in both training and validation sets. ROC curves showed that CD19 expression had a higher accuracy in the diagnosis of sepsis-induced ARDS. Lymphocyte subsets analysis of clinical samples revealed that CD19+B cells were elevated in sepsis-induced ARDS, with CD19+B cell counts demonstrating a higher diagnostic accuracy (AUC = 0.829) for septic-ARDS compared to other lymphocyte subsets.\nConclusion: In this study, we employed bioinformatics approaches to identify potential biomarkers for sepsis-induced ARDS and further validated these findings using clinical samples. Our results suggest that peripheral CD19+ B cells could act as a promising biomarker in sepsis-induced ARDS.", "claims": [{"id": "claim-method", "statement": "The diagnostic accuracy of indicators was evaluated using receiver operating characteristic (ROC) curve analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40503488", "locator": "sections[9] \"Statistical Analysis\" paragraph 2", "quote": "The diagnostic accuracy of indicators was evaluated using receiver operating characteristic (ROC) curve analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated and/or analyzed during this study are available from the corresponding author upon reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40503488", "locator": "sections[19] \"Data Sharing Statement\" paragraph 2", "quote": "The datasets generated and/or analyzed during this study are available from the corresponding author upon reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Our results suggest that peripheral CD19+ B cells could act as a promising biomarker in sepsis-induced ARDS.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40503488", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Our results suggest that peripheral CD19+ B cells could act as a promising biomarker in sepsis-induced ARDS."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Our results suggest that peripheral CD19+ B cells could act as a promising biomarker in sepsis-induced ARDS.", "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:40503488"], "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:GSE32707"], "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:GSE32707"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40503488", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.2147/JIR.S519346", "sha256": 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