Coexpression Network Analysis-Based Identification of Critical Genes Differentiating between Latent and Active Tuberculosis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36411825", "kind": "science-record", "revision": 3, "content_hash": "sha256:a8ab05f1398f7a0501fae036febd21fb2bc6212635c4110f2952835d90f7cb96", "created_at": "2026-11-01T19:00:52Z", "updated_at": "2026-11-01T22:08:08Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Coexpression Network Analysis-Based Identification of Critical Genes Differentiating between Latent and Active Tuberculosis.", "doi": "10.1155/2022/2090560", "pmid": "36411825", "authors": ["Liang Chen", "Jie Hua", "Xiaopu He"], "journal": "Disease markers", "year": 2022, "abstract": "Methods: Three Gene Expression Omnibus (GEO) microarray datasets (GSE19491, GSE98461, and GSE152532) were downloaded, with GSE19491 and GSE98461 then being merged to form a training dataset. Hub genes capable of differentiating between ATB and LTBI were then identified through differential expression analyses and a WGCNA analysis of this training dataset. Receiver operating characteristic (ROC) curves were then used to gauge to the diagnostic accuracy of these hub genes in the test dataset (GSE152532). Gene expression-based immune cell infiltration and the relationship between such infiltration and hub gene expression were further assessed via a single-sample gene set enrichment analysis (ssGSEA).\nResults: In total, 485 differentially expressed genes were analyzed, with the WGCNA approach yielding 8 coexpression models. Of these, the black module was the most closely correlated with ATB. In total, five hub genes (FBXO6, ATF3, GBP1, GBP4, and GBP5) were identified as potential biomarkers associated with LTBI progression to ATB based on a combination of differential expression and LASSO analyses. The area under the ROC curve values for these five genes ranged from 0.8 to 0.9 in the test dataset, and ssGSEA revealed the expression of these genes to be negatively correlated with lymphocyte activity but positively correlated with myeloid and inflammatory cell activity.\nConclusion: The five hub genes identified in this study may play a novel role in tuberculosis-related immunopathology and offer value as novel biomarkers differentiating LTBI from ATB.", "claims": [{"id": "claim-method", "statement": "The diagnostic utility of these hub genes when distinguishing between LTBI and ATB patients was then assessed using receiver operating characteristic (ROC) curves.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36411825", "locator": "sections[7] \"2.5. Hub Gene Screening and Validation\" paragraph 3", "quote": "The diagnostic utility of these hub genes when distinguishing between LTBI and ATB patients was then assessed using receiver operating characteristic (ROC) curves."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. These data can be found in GSE19491(https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE19491), GSE98461(https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE98461), and GSE152532 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36411825", "locator": "sections[16] \"Data Availability\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. These data can be found in GSE19491(https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE19491), GSE98461(https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE98461), and GSE152532 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "In total, five hub genes (FBXO6, ATF3, GBP1, GBP4, and GBP5) were identified as potential biomarkers associated with LTBI progression to ATB based on a combination of differential expression and LASSO analyses.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36411825", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "In total, five hub genes (FBXO6, ATF3, GBP1, GBP4, and GBP5) were identified as potential biomarkers associated with LTBI progression to ATB based on a combination of differential expression and LASSO analyses."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "In total, five hub genes (FBXO6, ATF3, GBP1, GBP4, and GBP5) were identified as potential biomarkers associated with LTBI progression to ATB based on a combination of differential expression and LASSO analyses.", "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:36411825"], "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:GSE152532"], "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:GSE152532"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36411825", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2022/2090560", "sha256": "sha256:0de6b0aa26f2de549beda4f753603070a2472268883f1fc0a9ac0a711acb9def", "bytes": 34069, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/2022/2090560", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9674975", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE152532", "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=GSE152532", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE152532", "version": null, "note": "Publicly available datasets were analyzed in this study. These data can be found in GSE19491(https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE19491), GSE98461(https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE98461), and GSE152532 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. 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