SynthesisMolecular diagnosis & therapy2020
Meta-analysis of Transcriptomic Data Reveals Pathophysiological Modules Involved with Atrial Fibrillation.
Synthesis in Molecular diagnosis & therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed.
- Reviewing Atrial Fibrillation Pathophysiology from a Network Medicine Perspective: The Relevance of Structural Remodeling, Inflammation, and the Immune System.Life (Basel, Switzerland) · 2023Review
- Alterations in cytoskeletal and CaFrontiers in cardiovascular medicine · 2023Article
- Identification of genomic signatures in bone marrow associated with clinical response of CD19 CAR T-cell therapy.Scientific reports · 2022Article
- Evaluation of cellular response toGastroenterology and hepatology from bed to bench · 2022Article
- Review
- Transcriptomic uniqueness and commonality of the ion channels and transporters in the four heart chambers.Scientific reports · 2021Article
- Cardioprotective Role of Heat Shock Proteins in Atrial Fibrillation: From Mechanism of Action to Therapeutic and Diagnostic Target.International journal of molecular sciences · 2021Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAtrial fibrillation (AF) is a complex disease and affects millions of people around the world. The biological mechanisms that are involved with AF are complex and still need to be fully elucidated. Therefore, we performed a meta-analysis of transcriptome data related to AF to explore these mechanisms aiming at more sensitive and reliable results.
methodsTen public transcriptomic datasets were downloaded, analyzed for quality control, and individually pre-processed. Differential expression analysis was carried out for each dataset, and the results were meta-analytically aggregated using the rth ordered p value method. We analyzed the final list of differentially expressed genes through network analysis, namely topological and modularity analysis, and functional enrichment analysis.
resultsThe meta-analysis of transcriptomes resulted in 1197 differentially expressed genes, whose protein-protein interaction network presented 39 hubs-bottlenecks and four main identified functional modules. These modules were enriched for 39, 20, 64, and 10 biological pathways involved with the pathophysiology of AF, especially with the disease's structural and electrical remodeling processes. The stress of the endoplasmic reticulum, protein catabolism, oxidative stress, and inflammation are some of the enriched processes. Among hub-bottlenecks genes, which are highly connected and probably have a key role in regulating these processes, HSPA5, ANK2, CTNNB1, and MAPK1 were identified.
conclusionOur approach based on transcriptome meta-analysis revealed a set of key genes that demonstrated consistent overall changes in expression patterns associated with AF despite data heterogeneity related, among others, to type of tissue. Further experimental investigation of our findings may shed light on the pathophysiology of the disease and contribute to the identification of new therapeutic targets.
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Registered trials
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