ArticleFrontiers in cardiovascular medicine2022
Identification of Key Non-coding RNAs and Transcription Factors in Calcific Aortic Valve Disease.
Article in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- The pro-apoptotic GZMB and anti-apoptotic HAX-1 and DAD-1 genes and gene proteins in human right auricular tissue affected by coronary heart disease and aortic valve stenosis: a pilot study.Journal of molecular histology · 2026Article
- Identification of key ferroptosis-related targets in colorectal cancer: A transcriptomics-driven study via machine learning and AUcell analysis of single-cell RNA-sequencing.Journal of Cancer · 2026Article
- Single-cell analysis reveals the loss of FABP4-positive proliferating valvular endothelial cells relates to functional mitral regurgitation.BMC medicine · 2024Article
- Screening of key genes related to ferroptosis and a molecular interaction network analysis in colorectal cancer using machine learning and bioinformatics.Journal of gastrointestinal oncology · 2023Article
- Comparative analysis of calcified soft tissues revealed shared deregulated pathways.Frontiers in aging neuroscience · 2023Article
- Shared gene characteristics and molecular mechanisms of macrophages M1 polarization in calcified aortic valve disease.Frontiers in cardiovascular medicine · 2022Article
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Authors and funding
9 authors.
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Abstract
Background: Calcific aortic valve disease (CAVD) is one of the most frequently occurring valvular heart diseases among the aging population. Currently, there is no known pharmacological treatment available to delay or reverse CAVD progression. The regulation of gene expression could contribute to the initiation, progression, and treatment of CAVD. Non-coding RNAs (ncRNAs) and transcription factors play essential regulatory roles in gene expression in CAVD; thus, further research is urgently needed. Materials and Methods: The gene-expression profiles of GSE51472 and GSE12644 were obtained from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) were identified in each dataset. A protein-protein-interaction (PPI) network of DEGs was then constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins database, and functional modules were analyzed with ClusterOne plugin in Cytoscape. Furthermore, Gene Ontology-functional annotation and Kyoto Encyclopedia of Genes and Genomes-pathway analysis were conducted for each functional module. Most crucially, ncRNAs and transcription factors acting on each functional module were separately identified using the RNAInter and TRRUST databases. The expression of predicted transcription factors and key genes was validated using GSE51472 and GSE12644. Furthermore, quantitative real-time PCR (qRT-PCR) experiments were performed to validate the differential expression of most promising candidates in human CAVD and control samples. Results: Among 552 DEGs, 383 were upregulated and 169 were downregulated. In the PPI network, 15 functional modules involving 182 genes and proteins were identified. After hypergeometric testing, 45 ncRNAs and 33 transcription factors were obtained. Among the predicted transcription factors, CIITA, HIF1A, JUN, POU2F2, and STAT6 were differentially expressed in both the training and validation sets. In addition, we found that key genes, namely, Conclusion: In this study, we identified functional modules with ncRNAs and transcription factors involved in CAVD pathogenesis. The current results suggest candidate molecules for further research on CAVD.
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