Identification of hub genes in heart failure by integrated bioinformatics analysis and machine learning.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38250028", "kind": "science-record", "revision": 4, "content_hash": "sha256:b132f2308ad2adb65c42006fa5870e3e4bfad4b888d24b7e5b91116455d3320e", "created_at": "2026-11-01T19:20:09Z", "updated_at": "2026-11-01T22:53:29Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of hub genes in heart failure by integrated bioinformatics analysis and machine learning.", "doi": "10.3389/fcvm.2023.1332287", "pmid": "38250028", "authors": ["Tengfei Wang", "Yongyou Sun", "Yingpeng Zhao", "Jinhe Huang", "Ying Huang"], "journal": "Frontiers in cardiovascular medicine", "year": 2023, "abstract": "Objective: To screen feature genes of heart failure patients through machine learning methods, in order to identify characteristic genes driving heart failure and investigate the progression of heart failure.\nMethods: Heart failure patient samples were downloaded from the public database GEO (Gene Expression Omnibus), including the datasets GSE116250, GSE120895, and GSE59867. GSE116250 and GSE120895 were used as the testing set, while GSE59867 was used as the validation set. LASSO regression analysis and SVM-RFE were utilized to identify feature genes.\nResults: Analysis showed that among the differentially expressed genes between normal and heart failure patients, 9 genes were upregulated and 10 genes were downregulated. ROC curve analysis in the training set showed that TAGLN and SGPP2 had AUC values greater than 0.7. Moreover, SDSL and SMTNL2 had even higher AUC values of greater than 0.9. However, further analysis in the validation set showed that only SDSL had an AUC value greater than 0.7. Western blot experiments, RT-PCR, and ISO-induced experiments confirmed that SDSL was highly expressed in heart failure patients and promoted heart failure progression. In addition, SDSL promoted PARP1 expression and knockdown of SDSL expression led to decreased Cleaved-PARP1 expression and reduced cardiomyocyte apoptosis. Conversely, overexpression of SDSL resulted in increased PARP1 expression and myocardial cell apoptosis. These results suggest that elevated expression of SDSL in cardiomyocytes from heart failure patients may be an important factor promoting the occurrence and development of heart failure.\nConclusions: Using machine learning methods and experimental validation, it has been demonstrated that SDSL is a driving gene in patients with heart failure, providing a new treatment direction for clinical treatment.", "claims": [{"id": "claim-method", "statement": "LASSO regression analysis and SVM-RFE were utilized to identify feature genes.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38250028", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "LASSO regression analysis and SVM-RFE were utilized to identify feature genes."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: Gene Expression Omnibus, GSE116250, GSE120895, and GSE59867.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38250028", "locator": "sections[21] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: Gene Expression Omnibus, GSE116250, GSE120895, and GSE59867."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Using machine learning methods and experimental validation, SDSL was identified as a driving gene in patients with heart failure.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38250028", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Using machine learning methods and experimental validation, it has been demonstrated that SDSL is a driving gene in patients with heart failure, providing a new treatment direction for clinical treatment."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Using machine learning methods and experimental validation, SDSL was identified as a driving gene in patients with heart failure.", "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:38250028"], "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:GSE116250"], "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:GSE116250"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38250028", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fcvm.2023.1332287", "sha256": "sha256:80af57887d4e785cbbfd927db4d0b86129cf845f43bc4b703c0ad13d7d6d0a85", "bytes": 34823, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fcvm.2023.1332287", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10796662", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE116250", "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=GSE116250", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE116250", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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Western blot experiments, RT-PCR, and ISO-induced experim"], "order_basis": "paper_text_order:1070", "id": "assay:1"}, {"role": "data_generation", "definition_id": "transfection", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.85, "evidence": ["addition, SDSL promoted PARP1 expression and knockdown of SDSL expression led to decreased Cleaved-"], "order_basis": "paper_text_order:1287", "id": "assay:2"}, {"role": "data_generation", "definition_id": "apoptosis_assay", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["d-PARP1 expression and reduced cardiomyocyte apoptosis. Conversely, overexpression of SDSL resulted", "creased PARP1 expression and myocardial cell apoptosis. These results suggest that elevated express"], "order_basis": "paper_text_order:1384", "id": "assay:3"}, {"role": "analysis", "definition_id": "machine_learning", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["train_classifier", "cross_validate", "roc_auc"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["LASSO regression analysis and SVM-RFE were utilized to identify feature genes."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}