Elucidating the role of KLRD1 in coronary atherosclerosis: harnessing bioinformatics and machine learning to advance understanding.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40448140", "kind": "science-record", "revision": 4, "content_hash": "sha256:39bbc7bb132fb7a57e6a08cf2fa07dccaa605438128645d5498d87274ddd6de5", "created_at": "2026-11-01T20:30:34Z", "updated_at": "2026-11-01T22:56:36Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Elucidating the role of KLRD1 in coronary atherosclerosis: harnessing bioinformatics and machine learning to advance understanding.", "doi": "10.1186/s13019-025-03473-z", "pmid": "40448140", "authors": ["Huan Liang", "Xiao Liang", "Man Zheng", "Shoudong Wang"], "journal": "Journal of cardiothoracic surgery", "year": 2025, "abstract": "BACKGROUND: Atherosclerosis (AS) is increasingly recognized as a chronic inflammatory disease that significantly compromises vascular health and serves as a major contributor to cardiovascular diseases. KLRD1 is a gene that encodes a protein involved in the immune system, specifically in the function of natural killer (NK) cells.\nMETHODS: KLRD1 was identified as a focal point through an integrative analysis of DEGs across multiple datasets (GSE43292 and GSE9820) from the GEO database, aligned with immune-related gene sets from the ImmPort database. Advanced analytical tools, including Lasso regression and SVM-RFE, were employed to refine our gene selection. We further applied GSEA and GSVA to these gene sets, revealing significant enrichment in immune-related pathways. The relationship between KLRD1 expression and immune processes was examined using CIBERSORT and ESTIMATE algorithms to assess tumor microenvironment characteristics, suggesting increased immune cell infiltration associated with higher KLRD1 expression. Validation of these findings was conducted using data from the GSE9820 dataset.\nRESULTS: Among 340 DEGs linked with KLRD1, 13 were identified as hub genes through LASSO and SVM-RFE analyses. Functional assays highlighted KLRD1's role in mononuclear cell differentiation, regulation of cell-cell adhesion, regulation of T cell activation. A Lollipop was created to display the expression patterns of Correlation Coefficient. T cells CD8, Plasma cells, Dendritic cells activated, T cells CD4 memory resting, T cells CD4 memory activated, T cells gamma delta.\nCONCLUSIONS: This research elucidates the complex relationship between KLRD1 and AS, underscoring its potential as a novel biomarker for diagnosing and monitoring the disease.", "claims": [{"id": "claim-method", "statement": "To elucidate the biological functions impacted by differential expression of KLRD1, we applied GSEA using an array of computational tools including limma for differential expression analysis, org.Hs.eg.db for gene annotation, clusterProfiler and enrichplot for visualization of enrichment results.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40448140", "locator": "sections[14] \"GSEA analysis\" paragraph 2", "quote": "To elucidate the biological functions impacted by differential expression of KLRD1, we applied GSEA using an array of computational tools including limma for differential expression analysis, org.Hs.eg.db for gene annotation, clusterProfiler and enrichplot for visualization of enrichment results."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated during and/or analyzed during the current study are available in the appendix.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40448140", "locator": "sections[24] \"Data availability\" paragraph 2", "quote": "The datasets generated during and/or analyzed during the current study are available in the appendix."}], "state": "complete"}, {"id": "claim-target-result", "statement": "KLRD1 was identified as a focal point through an integrative analysis of DEGs across multiple datasets (GSE43292 and GSE9820) from the GEO database, aligned with immune-related gene sets from the ImmPort database.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40448140", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "KLRD1 was identified as a focal point through an integrative analysis of DEGs across multiple datasets (GSE43292 and GSE9820) from the GEO database, aligned with immune-related gene sets from the ImmPort database."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "KLRD1 was identified as a focal point through an integrative analysis of DEGs across multiple datasets (GSE43292 and GSE9820) from the GEO database, aligned with immune-related gene sets from the ImmPort database.", "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:40448140"], "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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