Potential molecular and cellular mechanisms of the effects of cuproptosis-related genes in the cardiomyocytes of patients with diabetic heart failure: a bioinformatics analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38883603", "kind": "science-record", "revision": 4, "content_hash": "sha256:3d78d5da97e08fd5b6b9e6ea4a0958528c19a57fd659fe17594c30a5cfcf2504", "created_at": "2026-11-01T20:28:56Z", "updated_at": "2026-11-01T22:54:30Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Potential molecular and cellular mechanisms of the effects of cuproptosis-related genes in the cardiomyocytes of patients with diabetic heart failure: a bioinformatics analysis.", "doi": "10.3389/fendo.2024.1370387", "pmid": "38883603", "authors": ["Jinhao Chen", "Xu Yang", "Weiwen Li", "Ying Lin", "Run Lin", "Xianzhen Cai", "Baoxin Yan", "Bin Xie", "Jilin Li"], "journal": "Frontiers in endocrinology", "year": 2024, "abstract": "Background: Diabetes mellitus is an independent risk factor for heart failure, and diabetes-induced heart failure severely affects patients' health and quality of life. Cuproptosis is a newly defined type of programmed cell death that is thought to be involved in the pathogenesis and progression of cardiovascular disease, but the molecular mechanisms involved are not well understood. Therefore, we aimed to identify biomarkers associated with cuproptosis in diabetes mellitus-associated heart failure and the potential pathological mechanisms in cardiomyocytes.\nMaterials: Cuproptosis-associated genes were identified from the previous publication. The GSE26887 dataset was downloaded from the GEO database.\nMethods: The consistency clustering was performed according to the cuproptosis gene expression. Differentially expressed genes were identified using the limma package, key genes were identified using the weighted gene co-expression network analysis(WGCNA) method, and these were subjected to immune infiltration analysis, enrichment analysis, and prediction of the key associated transcription factors. Consistency clustering identified three cuproptosis clusters. The differentially expressed genes for each were identified using limma and the most critical MEantiquewhite4 module was obtained using WGCNA. We then evaluated the intersection of the MEantiquewhite4 output with the three clusters, and obtained the key genes.\nResults: There were four key genes: HSDL2, BCO2, CORIN, and SNORA80E. HSDL2, BCO2, and CORIN were negatively associated with multiple immune factors, while SNORA80E was positively associated, and T-cells accounted for a major proportion of this relationship with the immune system. Four enriched pathways were found to be associated: arachidonic acid metabolism, peroxisomes, fatty acid metabolism, and dorsoventral axis formation, which may be regulated by the transcription factor MECOM, through a change in protein structure.\nConclusion: HSDL2, BCO2, CORIN, and SNORA80E may regulate cardiomyocyte cuproptosis in patients with diabetes mellitus-associated heart failure through effects on the immune system. The product of the cuproptosis-associated gene LOXL2 is probably involved in myocardial fibrosis in patients with diabetes, which leads to the development of cardiac insufficiency.", "claims": [{"id": "claim-method", "statement": "Differentially expressed genes were identified using the limma package, key genes were identified using the weighted gene co-expression network analysis(WGCNA) method, and these were subjected to immune infiltration analysis, enrichment analysis, and prediction of the key associated transcription factors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38883603", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Differentially expressed genes were identified using the limma package, key genes were identified using the weighted gene co-expression network analysis(WGCNA) method, and these were subjected to immune infiltration analysis, enrichment analysis, and prediction of the key associated transcription factors."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The dataset (GSE26887) analyzed in this study were downloaded from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/). The list of diabetic heart failure-related genes which was selected as the validation set was downloaded from the GeneCards database (https://www.genecards.org/). Cuproptosis-associated genes were identified from the previous publication “Identification of cuproptosis-related subtypes and development of a prognostic signature in colorectal cancer.” (DOI: 10.1038/s41598-022-22300-2).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38883603", "locator": "sections[23] \"Data availability statement\" paragraph 2", "quote": "The dataset (GSE26887) analyzed in this study were downloaded from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/). The list of diabetic heart failure-related genes which was selected as the validation set was downloaded from the GeneCards database (https://www.genecards.org/). Cuproptosis-associated genes were identified from the previous publication “Identification of cuproptosis-related subtypes and development of a prognostic signature in colorectal cancer.” (DOI: 10.1038/s41598-022-22300-2)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "There were four key genes: HSDL2, BCO2, CORIN, and SNORA80E.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38883603", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "There were four key genes: HSDL2, BCO2, CORIN, and SNORA80E."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "There were four key genes: HSDL2, BCO2, CORIN, and SNORA80E.", "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:38883603"], "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:GSE26887"], "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:GSE26887"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38883603", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fendo.2024.1370387", "sha256": "sha256:6cb4991f67588b386a41e80f41259a5788f87b6670000e58b75dad792d37dca1", "bytes": 64955, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fendo.2024.1370387", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11176466", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE26887", "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=GSE26887", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE26887", "version": null, "note": "The dataset (GSE26887) analyzed in this study were downloaded from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/). The list of diabetic heart failure-related genes which was selected as the validation set was downloaded from the GeneCards database (https://www.genecards.org/). Cuproptosis-associated genes were identified from the previous publication “Identification of cuproptosis-related subtypes and development of a prognostic signature in colorectal cancer.” (DOI: 10.1038/s41598-022-22300-2).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The dataset (GSE26887) analyzed in this study were downloaded from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/). The list of diabetic heart failure-related genes which was selected as the validation set was downloaded from the GeneCards database (https://www.genecards.org/). 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