Analysis of Sepsis Markers and Pathogenesis Based on Gene Differential Expression and Protein Interaction Network.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35190763", "kind": "science-record", "revision": 5, "content_hash": "sha256:01eb0ac9781e35fecf20df21ddaa46c4f75b03542c9c20b485a41f13c923edd4", "created_at": "2026-11-01T17:36:57Z", "updated_at": "2026-11-01T22:05:57Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Analysis of Sepsis Markers and Pathogenesis Based on Gene Differential Expression and Protein Interaction Network.", "doi": "10.1155/2022/6878495", "pmid": "35190763", "authors": ["Jifang Liang", "Weidong Wu", "Xiuzhe Wang", "Wenjing Wu", "Shuxian Chen", "Meini Jiang"], "journal": "Journal of healthcare engineering", "year": 2022, "abstract": "OBJECTIVE: The purpose of the present study is to screen the hub genes associated with sepsis, comprehensively understand the occurrence and progress mechanism of sepsis, and provide new targets for clinical diagnosis and treatment of sepsis.\nMETHODS: The microarray data of GSE9692 and GSE95233 were downloaded from the Gene Expression Omnibus (GEO) database. The dataset GSE9692 contained 29 children with sepsis and 16 healthy children, while the dataset GSE95233 included 102 septic subjects and 22 healthy volunteers. Differentially expressed genes (DEGs) were screened by GEO2R online analysis. The DAVID database was applied to conduct functional enrichment analysis of the DEGs. The STRING database was adopted to acquire protein-protein interaction (PPI) networks.\nRESULTS: We identified 286 DEGs (217 upregulated DEGs and 69 downregulated DEGs) in the dataset GSE9692 and 357 DEGs (236 upregulated DEGs and 121 downregulated DEGs) in the dataset GSE95233. After the intersection of DEGs of the two datasets, a total of 98 co-DEGs were obtained. DEGs associated with sepsis were involved in inflammatory responses such as T cell activation, leukocyte cell-cell adhesion, leukocyte-mediated immunity, cytokine production, immune effector process, lymphocyte-mediated immunity, defense response to fungus, and lymphocyte-mediated immunity. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis suggested that sepsis was connected to bacterial and viral infections. Through PPI network analysis, we screened the most important hub genes, including ITK, CD247, MMP9, CD3D, MMP8, KLRK1, and GZMK.\nCONCLUSIONS: In conclusion, the present study revealed an unbalanced immune response at the transcriptome level of sepsis and identified genes for potential biomarkers of sepsis, such as ITK, CD247, MMP9, CD3D, MMP8, KLRK1, and GZMK.", "claims": [{"id": "claim-method", "statement": "The DEGs were identified using the online tool GEO2R. The screening criteria for DEGs were adjusted P value <0.05 and |log fold change (LogFC) >2.0.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35190763", "locator": "sections[4] \"2.2. Identification of DEGs\" paragraph 2", "quote": "The DEGs were identified using the online tool GEO2R. The screening criteria for DEGs were adjusted P value <0.05 and |log fold change (LogFC) >2.0."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data used to support the findings of this study are available from the corresponding author upon reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35190763", "locator": "sections[13] \"Data Availability\" paragraph 2", "quote": "The data used to support the findings of this study are available from the corresponding author upon reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We identified 286 DEGs (217 upregulated DEGs and 69 downregulated DEGs) in the dataset GSE9692 and 357 DEGs (236 upregulated DEGs and 121 downregulated DEGs) in the dataset GSE95233.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35190763", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We identified 286 DEGs (217 upregulated DEGs and 69 downregulated DEGs) in the dataset GSE9692 and 357 DEGs (236 upregulated DEGs and 121 downregulated DEGs) in the dataset GSE95233."}, {"asset": "source:pmid:35190763", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Differentially expressed genes (DEGs) were screened by GEO2R online analysis."}, {"asset": "source:pmid:35190763", "locator": "sections[8] \"3.1. Identification of DEGs\" paragraph 2", "quote": "The datasets GSE9692 and GSE95233 were selected and downloaded from GEO and were analyzed by GEO2R online tool."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "We identified 286 DEGs (217 upregulated DEGs and 69 downregulated DEGs) in the dataset GSE9692 and 357 DEGs (236 upregulated DEGs and 121 downregulated DEGs) in the dataset GSE95233.", "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:35190763"], "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:GSE95233"], "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:GSE95233"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35190763", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2022/6878495", "sha256": 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METHODS: The microarray data of GSE9692 and GSE95233 were downloaded"], "order_basis": "paper_text_order:326", "id": "assay:1"}, {"role": "analysis", "definition_id": "network_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.7, "evidence": ["protein-protein interaction"], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}