Identification of key autophagy-related genes in arrhythmogenic right ventricular cardiomyopathy through gene expression profiling.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39960965", "kind": "science-record", "revision": 3, "content_hash": "sha256:e485c818398f950fdd0ceb5714d2f795f88c9e8088b14076a584cdd25fd75402", "created_at": "2026-11-01T20:30:13Z", "updated_at": "2026-11-01T22:13:39Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of key autophagy-related genes in arrhythmogenic right ventricular cardiomyopathy through gene expression profiling.", "doi": "10.1097/MD.0000000000041430", "pmid": "39960965", "authors": ["Jianrong Yin", "Qiqiang Zhu", "Chunqiang Yu", "Lianhuan Wang", "Rongling Ge", "Lei Wang", "Jin Wang"], "journal": "Medicine", "year": 2025, "abstract": "The purpose of our study is to utilize bioinformatics methods to pinpoint genes linked to autophagy that may influence the progression of arrhythmogenic right ventricular cardiomyopathy (ARVC). By doing so, we hope to enhance the clinical intervention and handling of this cardiac condition by offering more informed guidance. The transcriptomic data corresponding to GSE29819 were accessed via the GEO repository. Utilizing R programming, we analyzed and searched genes associated with autophagy that might be relevant to ARVC. Subsequently, the identified genes underwent protein-protein interaction network and co-expression analysis, while GO and KEGG pathway enrichment analysis was employed to investigate the signaling cascades they may implicate. We intersected the down-regulated genes in GSE29819 with 222 autophagy-related genes, and finally got 12 differentially expressed autophagy-related genes. Examination of the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) indicates that diverse genetic activity plays a role across numerous biological functions and systems. These include cytokine-related genes, lipid metabolism and atherogenesis, nucleotide oligomerization domain-like receptor signaling, chemokine-induced pathway, autophagic genes, apoptosis, natural killer cells-induced cell death, signal transduction involving tumor necrosis factor, and the activation of C-type lectin receptors which may influence the diverse clinical presentations of ARVC. Cytoscape software constructed a protein mutual aid network of common differentially expressed genes, and obtained a Cluster with a high score and 7 key genes, including CCR2, FAS, PRKCD, CASP1, CCL2, NAMPT and TNFSF10. Utilizing bioinformatics methods to identify genes involved in autophagy that exhibit fluctuating expression levels augments our understanding of the intricate aspects of ARVC. At the same time, combined with previous research reports in cardiomyopathy, we can speculate that Fas may affect the occurrence and development of ARVC through tumor necrosis factor signaling pathway mediating apoptosis. These results further illuminate our understanding of the origins and potential treatment focal points for ARVC.", "claims": [{"id": "claim-method", "statement": "For the assessment of differential gene expression, t-tests was applied for the calculation of P-values and their subsequent adjustment using false discovery rate corrections.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39960965", "locator": "sections[7] \"6. 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