Integrative human atrial modeling unravels interactive PKA and CaMKII signaling as key determinant of atrial arrhythmogenesis
Bibliographic record
Abstract
Abstract Atrial fibrillation (AF), the most prevalent clinical arrhythmia, is associated with atrial remodeling manifesting as acute and chronic alterations in expression, function, and regulation of atrial electrophysiological and Ca 2+ -handling processes. These AF-induced modifications crosstalk and propagate across spatial scales creating a complex pathophysiological network, which renders AF resistant to existing pharmacotherapies that predominantly target transmembrane ion channels. Developing innovative therapeutic strategies requires a systems approach to disentangle quantitatively the proarrhythmic contributions of individual AF-induced alterations. Here, we built a novel computational framework for simulating electrophysiology and Ca 2+ -handling in human atrial cardiomyocytes and tissues, and their regulation by key upstream signaling pathways (i.e., protein kinase A, PKA, and Ca 2+/ calmodulin-dependent protein kinase II, CaMKII) involved in AF-pathogenesis. Populations of atrial cardiomyocyte models were constructed to determine the influence of subcellular ionic processes, signaling components, and regulatory networks on atrial arrhythmogenesis. Our results reveal a novel synergistic crosstalk between PKA and CaMKII that promotes atrial cardiomyocyte electrical instability and arrhythmogenic triggered activity. Simulations of heterogeneous tissue demonstrate that this cellular triggered activity is further amplified by CaMKII-dependent alterations of tissue properties, further exacerbating atrial arrhythmogenesis. Our analysis positions CaMKII as a key nodal master switch of the adaptive changes and the maladaptive proarrhythmic triggers at the cellular and tissue levels and establishes CaMKII inhibition as potential anti-AF strategy. Collectively, our integrative approach is powerful and instrumental to assemble and reconcile existing knowledge into a systems network for identifying novel anti-AF targets and innovative approaches moving beyond the traditional ion channel-based strategy. Significance statement Despite significant advancement in our understanding of pathological mechanisms and alterations underlying atrial fibrillation (AF), a highly prevalent clinical arrhythmia causing substantial health and socioeconomic burden, development of effective pharmacological therapeutics for AF remains an urgent unmet clinical need. We built a systems framework integrating key processes and their regulatory upstream signaling pathways that are involved in atrial electrophysiology and modified by AF. By simulating populations of single atrial cardiomyocyte models and heterogeneous tissues, our analysis demonstrated synergistic interactions between upstream signaling pathways that promote atrial arrhythmogenesis across spatial scales, added new insight into complex atrial arrhythmia mechanisms, and revealed adaptive and maladaptive alterations caused by AF, thus providing a powerful new tool for identifying innovative therapeutic approaches against AF.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".