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Record W2270107377 · doi:10.1093/cvr/cvw028

Deciphering the fundamental mechanisms of atrial fibrillation: a quest for over a century

2016· editorial· en· W2270107377 on OpenAlexafffund
Stanley Nattel, Dobromir Dobrev

Bibliographic record

VenueCardiovascular Research · 2016
Typeeditorial
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsUniversité de MontréalMcGill UniversityMontreal Heart Institute
FundersCanadian Institutes of Health ResearchDeutsches Zentrum für Herz-Kreislaufforschung
KeywordsAtrial fibrillationCardiologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

Atrial fibrillation (AF), the most frequent clinical arrhythmia, is associated with increased cardiovascular morbidity and mortality, with stroke, myocardial infarction, and heart failure being the most critical complications.1 Presently available drugs for AF therapy have moderate efficacy and important limitations, particularly increasing the risk of life-threatening proarrhythmic events and bleeding complications.1,2 Ablation procedures are moderately effective and relatively safe, but the increasing size of the patient population limits applicability to only a small proportion of patients.1 Therefore, drug therapy is still the mainstay of AF treatment. Although maintenance of sinus rhythm (rhythm control) appears preferable, clinical studies failed to demonstrate clear advantages to rate over rhythm control, likely because current pharmacological approaches do not target the critical determinants of the fundamental mechanisms of AF.3,4 A better mechanistic understanding of the molecular basis of AF is expected to foster the development of safer and more effective treatment approaches. Although the basic mechanisms of AF have been described in the medical literature for over a century, the underlying cellular and molecular mechanisms are incompletely understood.5 It is assumed that independent of the underlying cause, which may be very diverse, ectopic impulse formation (ectopic activity) and re-entry are the two major determinants of AF pathophysiology.2 Re-entry requires a vulnerable substrate and an initiating trigger. The likelihood of re-entry formation is determined by the tissue properties of conduction and refractoriness, with conduction disturbances and short refractoriness making formation of re-entry more likely. Ectopic activity results primarily from Ca2+-handling abnormalities that may cause arrhythmogenic afterdepolarizations.6,7 Changes in atrial structure and function that result from genetic factors, cardiac and non-cardiac diseases, ageing, and from AF itself constitute atrial remodelling, which increases the likelihood of both re-entry and ectopic (triggered) activity.2 Because of the increasing incidence and growing clinical relevance of AF and the very rapid advances in fundamental research during the last few years, Cardiovascular Research initiated a spotlight issue addressing the very recent advances in our understanding of the basic mechanisms promoting the initiation, progression, and maintenance of AF. The first series of articles addresses the role of genetics and epigenetic dysregulation in leading to AF. Disease-causing mutations have provided valuable insights into AF pathophysiology. Tucker et al.8 review the putative role of common genetic variation identified in genome-wide association studies in AF pathophysiology. Although the number of hits have increased to 17 independent susceptibility signals for AF at 14 genomic regions, the mechanisms by which these loci might cause AF remain largely unknown. Bridging the gap between genotype and phenotype, including intermediate phenotypes, remains a major challenge for the functional genomics area, particularly in AF. Histone deacetylases (HDACs) are part of an integrated proteostatic system controlling protein expression, folding, assembly, trafficking, and degradation in normal hearts, and there is now ample evidence for a key role of HDACs in cardiac disease-related remodelling.9 Zhang et al.10 critically evaluate the evidence for a role of HDACs in the regulation of pathological gene expression in arrhythmias, providing a comprehensive overview of the available experimental data on the participation of HDACs in generating the AF substrate and of the therapeutic potential of HDAC inhibition as a means to prevent AF onset and progression. Increased quantities of peri-atrial epicardial adipose tissue are associated with enhanced proarrhythmic risk and the association between obesity and AF is clinically well documented, although the precise mechanistic relationship is less well understood.11 Hatem et al.12 review the current evidence for and potential pathophysiological role of epicardial adipose tissue and secreted adipokines, inflammatory cytokines, and reactive oxygen species in leading to obesity-associated AF-promoting atrial fibrotic remodelling. Although proper visualization of structural remodelling components with imaging technologies is still in its infancy and needs further improvement and refinement, further advances in cardiac imaging are expected to lead to improved identification of specific AF substrates with the potential to lead to tailored anti-AF therapy. The next set of articles reviews the crucial role of Ca2+ signalling, nitroso-redox imbalance, and altered atrial metabolism in AF pathogenesis. As comprehensively summarized by Mesubi and Anderson,13 subcellular region-specific Ca2+-dependent signalling and abnormal Ca2+/calmodulin-dependent protein kinase II (CaMKII) activity play an important role in ion channel dysfunction and AF-related triggered activity, inflammation and extracellular matrix remodelling, as well as cell survival and atrial metabolism. All of these disturbances can precede AF development, potentially contributing to arrhythmia initiation, but can also result from AF itself, thereby contributing to AF maintenance. CaMKII inhibition with small molecules might be a promising antiarrhythmic approach for AF and is currently under investigation in clinical trials. Spatiotemporal changes in reactive oxygen species production due to uncoupling of nitric oxide synthase activity during the evolution of AF are associated with major shifts in nitroso-redox balance, although the specific proteins targeted for redox modification are not established. In their review, Casadei and colleagues14 summarize the regulation of redox second-messenger systems and discuss the recent evidence for alterations in redox regulation in AF, highlighting critical missing links and discussing the strength of clinical evidence for a role of antioxidants in the prevention and treatment of AF. Abnormal atrial metabolism is an emerging contributor to the initiation and progression of AF.15,16 Opacic et al.17 summarize in detail the evolving concepts about the putative role of atrial metabolism and tissue perfusion as potential contributors to the remodelling processes promoting AF development. The final two articles deal with our theoretical understanding of AF and its value as a guide to therapeutic innovation. Guillem et al.18 elegantly review and critically evaluate our current understanding of the theory of AF dynamics and the controversial role of rotors in human AF. The authors provide convincing arguments for the idea that the discrepancies regarding rotor prevalence and stability in the various clinical studies largely result from methodological differences between the approaches used to detect the presence of rotors. Differences in mapping sites (endo- vs. epicardial), resolution of mapping systems, and processing of atrial electrograms might explain different appreciations of the macroscopic mechanisms maintaining AF. Although rotor detection has been reported to successfully guide AF ablation,19 further improvement of mapping technologies and more work by different groups in larger patient cohorts and specific patient subpopulations are needed to better understand the relevance of AF mechanisms to ablation success and to better tailor the interventional treatment of AF. Basic research into AF pathophysiology has been extensive over the past century, with the assumption that improved insights into fundamental arrhythmic and antiarrhythmic mechanisms will help to improve AF detection and management.5 This is the context in which Heijman et al.20 critically analyse the clinical contributions of several decades of research into the basic mechanisms of AF. They evaluate the role of basic research findings in the development of current AF therapy, assess the potential value of recently obtained information in developing new treatment approaches, and consider the challenges in translating basic mechanisms to therapeutic innovation. We feel very privileged to have served as guest editors for this interesting spotlight issue on AF. We are also thankful for the outstanding contributions provided by leading experts that have allowed its realization. Our current knowledge of the fundamental mechanisms leading to the induction, progression, and maintenance of AF is still limited, but is improving very rapidly as evidenced by the content of this series. Despite important obstacles to the translation of basic science results to clinical practice, the advances described in this issue are likely to lead to improved clinical management of this important arrhythmia and ultimately to solutions to the many present challenges in AF control.21 D.D.'s and S.N.'s research is supported by the German Federal Ministry of Education through DZHK (German Center for Cardiovascular Research), the Canadian Institutes of Health Research, and Quebec Heart and Stroke Foundation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.007
Open science0.0010.002
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0070.002

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.

Opus teacher head0.087
GPT teacher head0.411
Teacher spread0.324 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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".

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Citations7
Published2016
Admission routes2
Has abstractyes

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Same venueCardiovascular ResearchSame topicAtrial Fibrillation Management and OutcomesFrench-language works237,207