Identification and validation of senescence-related genes in circulating endothelial cells of patients with acute myocardial infarction.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36582740", "kind": "science-record", "revision": 3, "content_hash": "sha256:ed1890d126f940b64242fb27fc1833c2928a7ce08eebb6586a4c6f160a0acd9f", "created_at": "2026-11-01T19:01:08Z", "updated_at": "2026-11-01T22:08:28Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and validation of senescence-related genes in circulating endothelial cells of patients with acute myocardial infarction.", "doi": "10.3389/fcvm.2022.1057985", "pmid": "36582740", "authors": ["Jie Xiang", "Jun Shen", "Ling Zhang", "Baopeng Tang"], "journal": "Frontiers in cardiovascular medicine", "year": 2022, "abstract": "Background: Acute myocardial infarction (AMI) is the main clinical cause of death and cardiovascular disease and thus has high rates of morbidity and mortality. The increase in cardiovascular disease with aging is partly the result of vascular endothelial cell senescence and associated vascular dysfunction. This study was performed to identify potential key cellular senescence-related genes (SRGs) as biomarkers for the diagnosis of AMI using bioinformatics.\nMethods: Using the CellAge database, we identified cellular SRGs. GSE66360 and GSE48060 for AMI patients and healthy controls and GSE19322 for mice were downloaded from the Gene Expression Omnibus (GEO) database. The GSE66360 dataset was divided into a training set and a validation set. The GSE48060 dataset was used as another validation set. The GSE19322 dataset was used to explore the evolution of the screened diagnostic markers in the dynamic process of AMI. Differentially expressed genes (DEGs) of AMI were identified from the GSE66360 training set. Differentially expressed senescence-related genes (DESRGs) selected from SRGs and DEGs were analyzed using Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and protein-protein interaction (PPI) networks. Hub genes in DESRGs were selected based on degree, and diagnostic genes were further screened by gene expression and receiver operating characteristic (ROC) curve. Finally, a miRNA-gene network of diagnostic genes was constructed and targeted drug prediction was performed.\nResults: A total of 520 DEGs were screened from the GSE66360 training set, and 279 SRGs were identified from the CellAge database. The overlapping DEGs and SRGs constituted 14 DESRGs, including 4 senescence suppressor genes and 10 senescence inducible genes. The top 10 hub genes, including FOS, MMP9, CEBPB, CDKN1A, CXCL1, ETS2, BCL6, SGK1, ZFP36, and IGFBP3, were screened. Furthermore, three diagnostic genes were identified: MMP9, ETS2, and BCL6. The ROC analysis showed that the respective area under the curves (AUCs) of MMP9, ETS2, and BCL6 were 0.786, 0.848, and 0.852 in the GSE66360 validation set and 0.708, 0.791, and 0.727 in the GSE48060 dataset. In the GSE19322 dataset, MMP9 (AUC, 0.888) and ETS2 (AUC, 0.929) had very high diagnostic values in the early stage of AMI. Finally, based on these three diagnostic genes, we found that drugs such as acetylcysteine and genistein may be targeted for the treatment of age-related AMI.\nConclusion: The results of this study suggest that cellular SRGs might play an important role in AMI. MMP9, ETS2, and BCL6 have potential as specific biomarkers for the early diagnosis of AMI.", "claims": [{"id": "claim-method", "statement": "ROC curve analysis was performed, and the AUCs were calculated using the pROC package in R software to determine the predicted values of the hub genes.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36582740", "locator": "sections[6] \"2.4 Identification of diagnostic genes\" paragraph 2", "quote": "ROC curve analysis was performed, and the AUCs were calculated using the pROC package in R software to determine the predicted values of the hub genes."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in this study are included in the article/Supplementary material, further inquiries can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36582740", "locator": "sections[18] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in this study are included in the article/Supplementary material, further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study identified MMP9, ETS2, and BCL6 as diagnostic genes with potential as specific biomarkers for the early diagnosis of AMI.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36582740", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Furthermore, three diagnostic genes were identified: MMP9, ETS2, and BCL6."}, {"asset": "source:pmid:36582740", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "The results of this study suggest that cellular SRGs might play an important role in AMI. MMP9, ETS2, and BCL6 have potential as specific biomarkers for the early diagnosis of AMI."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study identified MMP9, ETS2, and BCL6 as diagnostic genes with potential as specific biomarkers for the early diagnosis of AMI.", "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:36582740"], "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:GSE19322"], "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:GSE19322"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36582740", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fcvm.2022.1057985", "sha256": 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No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "assets": ["source:pmid:36582740", "data:geo:GSE19322"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE19322"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:21:59Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 14819, "completion_tokens": 1580, "cached_tokens": 264}}, "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:36582740", "type": "paper", "label": "pmid:36582740"}, {"id": "source:pmid:36582740", "type": "manuscript", "label": "PMID 36582740 full text"}, {"id": "data:geo:GSE19322", "type": "dataset", "label": "GEO GSE19322"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:36582740", "type": "paper", "label": "pmid:36582740"}, {"id": "source:pmid:36582740", "type": "manuscript", "label": "PMID 36582740 full text"}, {"id": "data:geo:GSE19322", "type": "dataset", "label": "GEO GSE19322"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-36582740", "type": "extraction", "used": ["source:pmid:36582740"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE19322", "type": "accession_resolution", "used": ["data:geo:GSE19322"], "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:36582740", "parent_hash": "sha256:efdc3d6f94b1dbbabf466b83cf0b09a16f94fa5bc0b1dc38f4cd30d292e24272", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE19322 licence not read", "asset:data:geo:GSE19322 not downloaded", "asset:data:geo:GSE48060 licence not read", "asset:data:geo:GSE48060 not downloaded", "asset:data:geo:GSE66360 licence not read", "asset:data:geo:GSE66360 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.8, "evidence": ["limma"], "order_basis": "analysis_only", "id": "assay:1"}]}