ArticleCirculation. Cardiovascular genetics2013
Weighted gene coexpression network analysis of human left atrial tissue identifies gene modules associated with atrial fibrillation.
Article in Circulation. Cardiovascular genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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30 citing papers in PubMed, 46 citations in OpenAlex.
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- Transcriptome and proteome mapping in the sheep atria reveal molecular featurets of atrial fibrillation progression.Cardiovascular research · 2021Article
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- Distinct peripheral blood monocyte and neutrophil transcriptional programs following intracerebral hemorrhage and different etiologies of ischemic stroke.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2021Article
- Gene co-expression network analysis reveals immune cell infiltration as a favorable prognostic marker in non-uterine leiomyosarcoma.Scientific reports · 2021Article
- RCAN1 in cardiovascular diseases: molecular mechanisms and a potential therapeutic target.Molecular medicine (Cambridge, Mass.) · 2020Review
- X-Module: A novel fusion measure to associate co-expressed gene modules from condition-specific expression profiles.Journal of biosciences · 2020Article
- Comprehensive Analysis of Differential Immunocyte Infiltration and Potential ceRNA Networks Involved in the Development of Atrial Fibrillation.BioMed research international · 2020Article
- Atrial fibrillation risk loci interact to modulate Ca2+-dependent atrial rhythm homeostasis.The Journal of clinical investigation · 2019Article
- Differentially expressed genes for atrial fibrillation identified by RNA sequencing from paired human left and right atrial appendages.Physiological genomics · 2019Article
- Macro- and micromechanical remodelling in the fish atrium is associated with regulation of collagen 1 alpha 3 chain expression.Pflugers Archiv : European journal of physiology · 2018Article
- Interplay between cardiac transcription factors and non-coding RNAs in predisposing to atrial fibrillation.Journal of molecular medicine (Berlin, Germany) · 2018Review
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Authors and funding
12 authors at 1 institution in 1 country.
Funding
Abstract
backgroundGenetic mechanisms of atrial fibrillation (AF) remain incompletely understood. Previous differential expression studies in AF were limited by small sample size and provided limited understanding of global gene networks, prompting the need for larger-scale, network-based analyses. METHODS AND
resultsLeft atrial tissues from Cleveland Clinic patients who underwent cardiac surgery were assayed using Illumina Human HT-12 mRNA microarrays. The data set included 3 groups based on cardiovascular comorbidities: mitral valve (MV) disease without coronary artery disease (n=64), coronary artery disease without MV disease (n=57), and lone AF (n=35). Weighted gene coexpression network analysis was performed in the MV group to detect modules of correlated genes. Module preservation was assessed in the other 2 groups. Module eigengenes were regressed on AF severity or atrial rhythm at surgery. Modules whose eigengenes correlated with either AF phenotype were analyzed for gene content. A total of 14 modules were detected in the MV group; all were preserved in the other 2 groups. One module (124 genes) was associated with AF severity and atrial rhythm across all groups. Its top hub gene, RCAN1, is implicated in calcineurin-dependent signaling and cardiac hypertrophy. Another module (679 genes) was associated with atrial rhythm in the MV and coronary artery disease groups. It was enriched with cell signaling genes and contained cardiovascular developmental genes including TBX5.
conclusionsOur network-based approach found 2 modules strongly associated with AF. Further analysis of these modules may yield insight into AF pathogenesis by providing novel targets for functional studies.
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