Molecular mechanisms underlying atrial remodeling
Bibliographic record
Abstract
Atrial fibrillation (AF) is the most sustained arrhythmia in the population and is associated with increased morbidity and mortality. A variety of cardiac disease entities, including valve disease, cardiomyopathies, hypertension and diabetes increase the risk of AF. However, present drug therapies are ineffective and can even increase the risk of dangerous ventricular tachyarrhythmias. Studies in animal models show that AF is associated with atrial remodeling that favors AF induction and maintenance. The mechanisms of atrial remodeling depend on the underlying pathology. Atrial remodeling caused by atrial tachycardia or AF itself is primarily electrical, associated with changes in the expression and function of ion channels. These changes are reflected in decreased atrial refractory periods, impaired refractoriness adaptation to rate and conduction slowing. Together, these electrical changes increase the incidence of AF. Heart failure (HF), an important cause of AF, induces another type of atrial remodeling. HF-remodeling is characterized by conduction heterogeneity and altered atrial structural properties. In particular, interstitial fibrosis plays a major role in the stabilization of reentry circuits and prolongation of AF duration.Although many studies have described a large number of the changes associated with each form of remodeling, the underlying mechanisms remain poorly understood. The goal of this thesis was to clarify the molecular mechanisms underlying the atrial remodeling associated with AF. In my first study, I put forward the hypothesis that atrial remodeling caused by atrial tachycardia and that resulting from HF differ in terms of the time course and nature of underlying changes in cardiac gene expression. I indeed discovered that the changes in gene expression induced by atrial tachycardia and HF were qualitatively different and evolved differently over time. The changes by atrial tachycardia were limited and showed time-dependent adaptation, whereas the changes induced by HF were qualitatively greater and more varied, and showed qualitative evolution with the development of the pathology. In my second study, I put forward the hypothesis that HF caused by ventricular "tachycardiomyopathy" causes differential gene-expression changes in atria versus ventricles and that these changes evolve over time. This study highlighted the signaling pathways implicated in atrial remodeling like those of MAP kinases, ubiquitin/proteasome systems and apoptosis, along with specific metabolic pathways like the electron-chain transport system and Krebs cycle at the ventricular level.Even though the large-scale study of gene-expression changes allowed us to identify certain signaling systems, they do not detect post-translational alterations. In our third study, I put forward the hypothesis that tachycardia-induced HF causes progressive changes in the proteins involved in different functional groups that play an important role in atrial pathophysiology. My results highlighted proteins linked to oxidative stress, metabolism and contractile proteins.In my final study, I decided to explore a new therapeutic avenue for AF prevention based on the molecular pathophysiology of AF. I had identified the MAP kinase ERK as a particularly important molecule in atrial remodeling caused by myocardial infarction in the rat and I had obtained results implicating a microRNA (miR21) in signaling leading to pathological ERK hyperphosphorylation. I therefore suggested that atrial interstitial fibrosis could be prevented by targeting underlying microRNA-related mechanisms and thereby reduce the inducibility and maintenance of AF caused by HF. My study is not yet completed but the preliminary results suggest beneficial effects of anti-miR21 treatment in preventing AF. In conclusion, my studies indicate the molecular pathophysiology underlying AF and suggest that it can be exploited to develop new therapeutic approaches.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".