Atrial fibrillation (AF) is the most common cardiac arrhythmia (affecting ~1-2% of the general population), resulting in markedly reduced quality of life, and increased mortality, due to a combination of altered hemodynamics, progressive atrial and ventricular dysfunction, and embolic stroke. Patients with sporadic AF episodes (paroxysmal AF) are more amenable to rhythm control treatment, but limitation in current pharmacotherapy causes paroxysmal AF to progress to persistent and chronic AF, characterized by extensive remodeling that facilitates AF maintenance (?AF begets AF?). The development of urgently needed new strategies for AF treatment hinge upon improved understanding of how abnormalities in cellular function (remodeled ion channels, Ca and Na handling, and cellular signaling), together with neurohormonal regulation trigger and sustain arrhythmia in the atria. Understanding the interactions of these complex biochemical and biophysical functions requires quantitative systems models that also integrate over multiple physical scales. To address this complex problem, we aim at developing an integrative and quantitative modeling and simulation framework, incorporating data from experimental sources, to investigate emerging questions in AF. We propose a closely integrated combination of experimental and computational studies that takes advantage of interdisciplinary synergy between Drs. Grandi & Chiamvimonvat at UC Davis and Dr. Dobrev at Universittsklinikum Essen. The project will develop and validate a suite of modeling tools used to investigate mechanistically: (1) how derangements in Ca and Na homeostasis, CaMKII hyperactivation, and ?-adrenergic challenge contribute to cellular afterdepolarizations and triggered activity in early and chronic human AF; (3) the efficacy and safety (AF-selectivity) of antiarrhythmic drugs targeting cardiac Na channels and atrial-specific small conductance Ca-activated K channels, to facilitate rational drug design. We contend that understanding how CaMKII signaling synergizes with ionic and Ca and Na handling remodeling, as well as neurohormonal regulation, may shed mechanistic insight into AF management.
Each aim i ncludes formulation and sensitivity analysis of new models (Dr. Sobie is a consultant), validation studies with human samples, and testing of specific hypotheses. Models and data will be distributed freely and widely via software and database infrastructure supported by Dr. Grandi's lab and scientific networking sites.
Atrial fibrillation (AF), the most common cardiac arrhythmia, affects about ~1-2% of the general population. A complex, progressive disease, it sharply increases the risk of stroke and often coexists with and worsens other severe cardiac diseases, particularly heart failure. This project aims to achieve a better understanding of the mechanisms underlying AF via new research tools, including state-of-the-art computer models, and new experiments in human atrial tissue, which will ultimately lead to improved treatments and outcomes for patients.
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