Deciphering the clinical implication of an obesity-related gene signature as the novel biomarker for acute myocardial infarction diagnosis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41461688", "kind": "science-record", "revision": 4, "content_hash": "sha256:08137bd563de74851199da8b43d77c63d914abc2f8acbe8168937868d28bf439", "created_at": "2026-11-01T20:31:26Z", "updated_at": "2026-11-01T22:57:40Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Deciphering the clinical implication of an obesity-related gene signature as the novel biomarker for acute myocardial infarction diagnosis.", "doi": "10.1038/s41598-025-28461-0", "pmid": "41461688", "authors": ["Weixia Dong", "Zixin Xue", "Min Zhang", "Feng Lu", "Shaoping Ji"], "journal": "Scientific reports", "year": 2025, "abstract": "Acute myocardial infarction (AMI) stands as a major contributor to mortality and disability worldwide, with obesity playing a significant role in its development. This study aims to investigate potential biomarkers associated with obesity-related genes (ORGs) in patients with AMI. We downloaded four training gene expression datasets and one validation dataset from the Gene Expression Omnibus (GEO) database, and extracted ORGs from the GeneCards database. Feature genes were identified using machine learning techniques, and their diagnostic potential was evaluated through receiver operating characteristic (ROC) curves. To assess the identified critical pathways, Gene Set Enrichment Analysis (GSEA) was performed. Levels of immune infiltration were analyzed using the CIBERSORT algorithm and single-sample Gene Set Enrichment Analysis (ssGSEA). A signature comprising five genes (IL1RN, TLR2, NFKBIA, MMP9, and ITLN1) was established as a diagnostic biomarker for AMI, achieving an area under the curve (AUC) of 0.924, which was confirmed in the GSE59876 dataset (AUC = 0.825). According to the diagnostic model, comparisons between high- and low-risk groups revealed six distinct immune cell types and thirteen differing immune functions. Validation through reverse transcription quantitative polymerase chain reaction (RT-qPCR) reaffirmed the differential expression of the signature genes in AMI and control samples. Our findings provide crucial insights into the roles of ORGs in AMI and may facilitate the identification of valuable biomarkers for AMI diagnosis.", "claims": [{"id": "claim-method", "statement": "The “limma” package in R was applied for background correction, inter-array normalization, and analysis of differential expression between AMI and control samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41461688", "locator": "sections[3] \"Data acquisition, processing and identification of differentially expressed genes\" paragraph 2", "quote": "The “limma” package in R was applied for background correction, inter-array normalization, and analysis of differential expression between AMI and control samples."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data generated or analyzed during this study are included in this published article. The datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41461688", "locator": "sections[22] \"Data availability\" paragraph 2", "quote": "All data generated or analyzed during this study are included in this published article. The datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A signature comprising five genes (IL1RN, TLR2, NFKBIA, MMP9, and ITLN1) was established as a diagnostic biomarker for AMI, achieving an area under the curve (AUC) of 0.924, which was confirmed in the GSE59876 dataset (AUC = 0.825).", "kind": "quantitative", "target": {"value": 0.825, "unit": "auc", "tolerance": null, "source": "A signature comprising five genes (IL1RN, TLR2, NFKBIA, MMP9, and ITLN1) was established as a diagnostic biomarker for AMI, achieving an area under the curve (AUC) of 0.924, which was confirmed in the GSE59876 dataset (AUC = 0.825)."}, "evidence": [{"asset": "source:pmid:41461688", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "A signature comprising five genes (IL1RN, TLR2, NFKBIA, MMP9, and ITLN1) was established as a diagnostic biomarker for AMI, achieving an area under the curve (AUC) of 0.924, which was confirmed in the GSE59876 dataset (AUC = 0.825)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A signature comprising five genes (IL1RN, TLR2, NFKBIA, MMP9, and ITLN1) was established as a diagnostic biomarker for AMI, achieving an area under the curve (AUC) of 0.924, which was confirmed in the GSE59876 dataset (AUC = 0.825).", "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:41461688"], "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:GSE48060"], "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:GSE48060"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:41461688", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1038/s41598-025-28461-0", "sha256": "sha256:c2971227173579f25ddc8d852b76c5e5b41a39c6cac5a8f53e9305de7d14362e", "bytes": 48618, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1038/s41598-025-28461-0", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC12748819", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE48060", "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=GSE48060", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE48060", "version": null, "note": "All data generated or analyzed during this study are included in this published article. 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