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pmid:35456421
Transcriptional Profiling and Deriving a Seven-Gene Signature That Discriminates Active and Latent Tuberculosis: An Integrative Bioinformatics Approach.
Sudhakar Natarajan · Mohan Ranganathan · Luke Elizabeth Hanna · Srikanth Tripathy
Genes · 2022 doi:10.3390/genes13040616
Paper
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Experiment
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Data
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Analysis
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Execution
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Complete file
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Our integrative analysis aims to identify the transcriptional profiling and gene expression signature that distinguish individuals with active TB (ATB) disease, and those with latent tuberculosis infection (LTBI). In the present study, we reanalyzed a microarray dataset (GSE37250) from GEO database and explored the data for differential gene expression analysis between those with ATB and LTBI derived from Malawi and South African cohorts. We used BRB array tool to distinguish DEGs (differentially expressed genes) between ATB and LTBI. Pathway enrichment analysis of DEGs was performed using DAVID bioinformatics tool. The protein-protein interaction (PPI) network of most upregulated genes was constructed using STRING analysis. We have identified 375 upregulated genes and 152 downregulated genes differentially expressed between ATB and LTBI samples commonly shared among Malawi and South African cohorts. The constructed PPI network was significantly enriched with 76 nodes connected to 151 edges. The enriched GO term/pathways were mainly related to expression of IFN stimulated genes, interleukin-1 production, and NOD-like receptor signaling pathway. Downregulated genes were significantly enriched in the Wnt signaling, B cell development, and B cell receptor signaling pathways. The short-listed DEGs were validated in a microarray data from an independent cohort (GSE19491). ROC curve analysis was done to assess the diagnostic accuracy of the gene signature in discrimination of active and latent tuberculosis. Thus, we have derived a seven-gene signature, which included five upregulated genes FCGR1B, ANKRD22, CARD17, IFITM3, TNFAIP6 and two downregulated genes FCGBP and KLF12, as a biomarker for discrimination of active and latent tuberculosis. The identified genes have a sensitivity of 80-100% and specificity of 80-95%. Area under the curve (AUC) value of the genes ranged from 0.84 to 1. This seven-gene signature has a high diagnostic accuracy in discrimination of active and latent tuberculosis.", "claims": [{"id": "claim-method", "statement": "Class comparison analysis was performed between ATB and LTBI classes, and multivariate permutation test was computed based on 1000 random permutations and a false discovery rate of 1%.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35456421", "locator": "sections[4] \"2.2. 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Both these data can be accessed from Gene Expression Omnibus (GEO) database."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The seven-gene signature discriminated active from latent tuberculosis with 80–100% sensitivity, 80–95% specificity, and AUC values of 0.84 to 1.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35456421", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The identified genes have a sensitivity of 80–100% and specificity of 80–95%. Area under the curve (AUC) value of the genes ranged from 0.84 to 1."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The seven-gene signature discriminated active from latent tuberculosis with 80–100% sensitivity, 80–95% specificity, and AUC values of 0.84 to 1.", "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:35456421"], "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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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE37250", "GSE19491"], "resolved_accessions": ["GSE37250", "GSE19491"], "statements": ["Gene expression dataset GSE37250 can be accessed at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE37250 (accessed date 15 July 2021), and validation data GSE19491 can be accessed at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE19491 (accessed on 19 April 2021). Both these data can be accessed from Gene Expression Omnibus (GEO) database."], "basis": "The paper names GSE37250, GSE19491 in National Center for Biotechnology Information’s (NCBI) Gene Expression Omnibus (GEO) database and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "assets": ["source:pmid:35456421", "data:geo:GSE19491"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE19491"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T17:43:07Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 17116, "completion_tokens": 1861, "cached_tokens": 188}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:35456421", "type": "paper", "label": "pmid:35456421"}, {"id": "source:pmid:35456421", "type": "manuscript", "label": "PMID 35456421 full text"}, {"id": "data:geo:GSE19491", "type": "dataset", "label": "GEO GSE19491"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:35456421", "type": "paper", "label": "pmid:35456421"}, {"id": "source:pmid:35456421", "type": "manuscript", "label": "PMID 35456421 full text"}, {"id": "data:geo:GSE19491", "type": "dataset", "label": "GEO GSE19491"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-35456421", "type": "extraction", "used": ["source:pmid:35456421"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE19491", "type": "accession_resolution", "used": ["data:geo:GSE19491"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:35456421", "parent_hash": "sha256:07f81db87993d3c6e5dc0874a73d7861f1c516e1efa2eb34337a833a01dd614c", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE19491 licence not read", "asset:data:geo:GSE19491 not downloaded", "asset:data:geo:GSE37250 licence not read", "asset:data:geo:GSE37250 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["LTBI). In the present study, we reanalyzed a microarray dataset (GSE37250) from GEO database and exp", "s. The short-listed DEGs were validated in a microarray data from an independent cohort (GSE19491).", "s to visualize and statistically analyze the microarray gene expression data. We used BRB-Array (V 4"], "order_basis": "paper_text_order:449", "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"}]}