ArticleMedicine2025
Identification of key autophagy-related genes in arrhythmogenic right ventricular cardiomyopathy through gene expression profiling.
Article in Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.