Co-expression network analysis identifies potential candidate hub genes in severe influenza patients needing invasive mechanical ventilation.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36243706", "kind": "science-record", "revision": 3, "content_hash": "sha256:8fb5d60324102a8a9eaf06b39bacf0f95ce13fd17103aefbfceeea219bb3fe3d", "created_at": "2026-11-01T18:15:37Z", "updated_at": "2026-11-01T21:29:13Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Co-expression network analysis identifies potential candidate hub genes in severe influenza patients needing invasive mechanical ventilation.", "doi": "10.1186/s12864-022-08915-9", "pmid": "36243706", "authors": ["Liang Chen", "Jie Hua", "Xiaopu He"], "journal": "BMC genomics", "year": 2022, "abstract": "BACKGROUND: Influenza is a contagious disease that affects people of all ages and is linked to considerable mortality during epidemics and occasional outbreaks. Moreover, effective immunological biomarkers are needed for elucidating aetiology and preventing and treating severe influenza. Herein, we aimed to evaluate the key genes linked with the disease severity in influenza patients needing invasive mechanical ventilation (IMV). Three gene microarray data sets (GSE101702, GSE21802, and GSE111368) from blood samples of influenza patients were made available by the Gene Expression Omnibus (GEO) database. The GSE101702 and GSE21802 data sets were combined to create the training set. Hub indicators for IMV patients with severe influenza were determined using differential expression analysis and Weighted correlation network analysis (WGCNA) from the training set. The receiver operating characteristic curve (ROC) was also used to evaluate the hub genes from the test set's diagnostic accuracy. Different immune cells' infiltration levels in the expression profile and their correlation with hub gene markers were examined using single-sample gene set enrichment analysis (ssGSEA).\nRESULTS: In the present study, we evaluated a total of 447 differential genes. WGCNA identified eight co-expression modules, with the red module having the strongest correlation with IMV patients. Differential genes were combined to obtain 3 hub genes (HLA-DPA1, HLA-DRB3, and CECR1). The identified genes were investigated as potential indicators for patients with severe influenza who required IMV using the least absolute shrinkage and selection operator (LASSO) approach. The ROC showed the diagnostic value of the three hub genes in determining the severity of influenza. Using ssGSEA, it has been revealed that the expression of key genes was negatively correlated with neutrophil activation and positively associated with adaptive cellular immune response.\nCONCLUSION: We evaluated three novel hub genes that could be linked to the immunopathological mechanism of severe influenza patients who require IMV treatment and could be used as potential biomarkers for severe influenza prevention and treatment.", "claims": [{"id": "claim-method", "statement": "The receiver operating characteristic curve (ROC) was also used to evaluate the hub genes from the test set's diagnostic accuracy.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36243706", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The receiver operating characteristic curve (ROC) was also used to evaluate the hub genes from the test set's diagnostic accuracy."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. These data can be found in GSE101702 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE101702), GSE21802 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21802) and GSE111368 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE111368).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36243706", "locator": "sections[20] \"Availability of data and materials\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. These data can be found in GSE101702 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE101702), GSE21802 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21802) and GSE111368 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE111368)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "ROC analysis from the training set showed that area under the ROC curve (AUC) was 0.862 [95% confidence interval (CI) 0.800–0.921] for CECR1, 0.866 (95% CI 0.805–0.919) for HLA-DPA1, and 0.821 (95% CI 0.748–0.886) for HLA-DRB3, accordingly (Fig. 4B).", "kind": "quantitative", "target": {"value": 95.0, "unit": "per cent", "tolerance": null, "source": "ROC analysis from the training set showed that area under the ROC curve (AUC) was 0.862 [95% confidence interval (CI) 0.800–0.921] for CECR1, 0.866 (95% CI 0.805–0.919) for HLA-DPA1, and 0.821 (95% CI 0.748–0.886) for HLA-DRB3, accordingly (Fig. 4B)."}, "evidence": [{"asset": "source:pmid:36243706", "locator": "sections[5] \"Evaluation of hub gene expression and diagnostic value\" paragraph 2", "quote": "ROC analysis from the training set showed that area under the ROC curve (AUC) was 0.862 [95% confidence interval (CI) 0.800–0.921] for CECR1, 0.866 (95% CI 0.805–0.919) for HLA-DPA1, and 0.821 (95% CI 0.748–0.886) for HLA-DRB3, accordingly (Fig. 4B)."}, {"asset": "source:pmid:36243706", "locator": "sections[5] \"Evaluation of hub gene expression and diagnostic value\" paragraph 2", "quote": "Meanwhile, the AUC was 0.700–0.800 for the three hub genes from the test set, suggesting a moderate diagnostic accuracy (Fig. 4D)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "ROC analysis from the training set showed that area under the ROC curve (AUC) was 0.862 [95% confidence interval (CI) 0.800–0.921] for CECR1, 0.866 (95% CI 0.805–0.919) for HLA-DPA1, and 0.821 (95% CI 0.748–0.886) for HLA-DRB3, accordingly (Fig. 4B).", "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:36243706"], "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:GSE101702"], "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:GSE101702"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36243706", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12864-022-08915-9", "sha256": "sha256:014d8990c4ed6bde8bd061d1995c143e09a0b693a712b8adec7b8da588ab29e2", "bytes": 30867, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12864-022-08915-9", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9569050", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE101702", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE101702", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE101702", "version": null, "note": "Publicly available datasets were analyzed in this study. These data can be found in GSE101702 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE101702), GSE21802 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21802) and GSE111368 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE111368).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. 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