Circulation Arrhythmia and ElectrophysiologyGenomicsPeer-reviewed journal article
Transcriptomic profiling of atrial fibrillation canine models at disease onset
Francis LeblanciD, Faezeh Vahdati HassaniiD, Laura Liesinger, Xiaoyan QiiD, Patrice NaudiD, Ruth Birner‐GruenbergeriD, Guillaume LettreiD, Stanley NatteliD
Abstract
BackgroundAtrial fibrillation (AF), the most common sustained arrhythmia, is associated with increased morbidity, mortality, and health-care costs. AF develops over many years and is often related to substantial atrial structural and electrophysiological remodeling. AF may lack symptoms at onset and atrial biopsy samples are generally obtained in subjects with advanced disease, so it is difficult to study earlier-stage pathophysiology in humans. MethodsHere, we characterized comprehensively the transcriptomic (miRNAseq and mRNAseq) changes in the left atria of two robust canine AF-models after one week of electrically-maintained AF, without or with ventricular rate-control via atrioventricular node-ablation/ventricular pacing. ResultsOur RNA-sequencing experiments identified thousands of genes that are differentially expressed, including a majority that have never before been implicated in AF. Gene-set enrichment analyses highlighted known (e.g. extracellular matrix structure organization) but also many novel pathways (e.g. muscle structure development, striated muscle cell differentiation) that may play a role in tissue remodeling and/or cellular transdifferentiation. Of interest, we found dysregulation of a cluster of non-coding RNAs, including many microRNAs but also the MEG3 long non-coding RNA orthologue, located in the syntenic region of the imprinted human DLK1-DIO3 locus. Interestingly (in the light of other recent observations), our analysis identified gene-targets of differentially expressed microRNAs at the DLK1-DIO3 locus implicating glutamate signaling in AF pathophysiology. ConclusionsOur results capture molecular events that occur at an early stage of disease development using well-characterized animal models, and may therefore inform future studies that aim to further dissect the causes of AF in humans.
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- 11
- FWCI
- 1.17
- Field percentile
- top 20%
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