Identification of differentially expressed genes to predict the risk of heart failure in older patients with hypertrophic cardiomyopathy.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38972072", "kind": "science-record", "revision": 4, "content_hash": "sha256:9e6cd95ec9125993355c414cbb56cd6c5373d2875198e0bdcdaf5626db9589c9", "created_at": "2026-11-01T20:29:02Z", "updated_at": "2026-11-01T22:54:39Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of differentially expressed genes to predict the risk of heart failure in older patients with hypertrophic cardiomyopathy.", "doi": "10.18632/aging.205956", "pmid": "38972072", "authors": ["Hao Dong", "Chufan Yin", "Dongping Xiao", "Yong Tang"], "journal": "Aging", "year": 2024, "abstract": "AIM: Hypertrophic cardiomyopathy (HCM) is a common heart disease. Old people with HCM are at high risk of heart failure (HF). This study aimed to identify differentially expressed genes (DEGs) to evaluate the risk of HF in older patients with HCM.\nMETHODS: GSE89714 and GSE116250 were downloaded from Gene Expression Omnibus (GEO) database, and DEGs were identified by using limma R package with P < 0.05 and logFC> 1 as cut off. Protein-protein interaction (PPI) network, Genome Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed for the identified DEGs. NetworkAnalyst online tool was applied for Gene Set Enrichment Analysis (GSEA) analysis.\nRESULTS: We identified 124 overlap DEGs from the 2 datasets. PPI network showed that COL1A1, COL3A1, COL1A2, BGN, COL5A1, LUM, TGFB2, FMOD, ASPN, and COL14A1 were the top ten genes related to HCM and HF compared with control. Functional and pathway analyses showed that the overlap genes were mainly related to ECM-receptor interaction, ECM organization, Focal adhesion, PI3K-Akt signaling, TGF-beta signaling, and Platelet activation signaling and aggregation. Among the overlap genes, COL5A1 and LUM were significantly upregulated, while TGFB2, FMOD, ASPN, and COL14A1 were significantly downregulated in HF dataset compared with HCM dataset.\nCONCLUSIONS: Bioinformatics-based analysis revealed potential genes associated with HCM and HF, which could be utilized to evaluate the risk of HF in older patients with HCM.", "claims": [{"id": "claim-method", "statement": "The DEGs were analyzed using linear models for microarray analysis R program with P < 0.05 and logFC > 1 as cut off.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38972072", "locator": "sections[3] \"High-throughput sequencing data and differentially expressed genes analysis\" paragraph 2", "quote": "The DEGs were analyzed using linear models for microarray analysis R program with P < 0.05 and logFC > 1 as cut off."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data are available from the corresponding author on request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38972072", "locator": "sections[7] \"Availability of data and materials\" paragraph 2", "quote": "All data are available from the corresponding author on request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study identified 124 overlap DEGs from the HCM and HF datasets, with ten hub genes highlighted by PPI network analysis.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38972072", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We identified 124 overlap DEGs from the 2 datasets."}, {"asset": "source:pmid:38972072", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "PPI network showed that COL1A1, COL3A1, COL1A2, BGN, COL5A1, LUM, TGFB2, FMOD, ASPN, and COL14A1 were the top ten genes related to HCM and HF compared with control."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study identified 124 overlap DEGs from the HCM and HF datasets, with ten hub genes highlighted by PPI network analysis.", "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:38972072"], "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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