Abstract
2-deoxy-ATP (dATP) is a myosin activator known to improve cardiac contractile force [1]. In vitro studies have shown that dATP alters the calcium transient profile in addition to the kinetics of the cross-bridge cycle [2]. Furthermore, in vivo studies of transgenic mice with increased production of dATP show elevated left ventricular systolic function [3]. Pulmonary arterial hypertension (PAH) is a rare disease of the pulmonary vasculature in which pressure overload in the right ventricle results in reduced contractile function and right heart failure [4]. We hypothesize that dATP may have a therapeutic effect on PAH-induced heart failure, by improving contractile function and restoring cardiac output and ejection fraction. However, because the effects of dATP cannot easily be assessed experimentally, we propose using a computational multiscale modeling approach to predict cardiac function. By altering parameters in an existing multiscale biventricular cardiac model [5], we were able to reproduce end-systolic and end-diastolic pressures and volumes that reflect the PAH condition, as well as healthy hearts. dATP was simulated by adjusting parameters in the model at the molecular and cellular levels based on experimental data [1], allowing us to predict the effects of dATP on PAH at the organ level. Our results show that the molecular effects of dATP can increase cardiac output and restore ejection fraction in PAH conditions, though at the cost of elevated mean arterial pressure, and may provide a new approach to treating this disease. Our multiscale modeling approach paves the way for further studies map** out cardiovascular mechanics. As novel therapeutics continue to be discovered, their application and mechanism can be further explored through these computational models.
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Garcia, K. et al. (2022). Investigating the Multiscale Impact of Deoxyadenosine Triphosphate (dATP) on Pulmonary Arterial Hypertension (PAH) Induced Heart Failure. In: McCabe, K.J. (eds) Computational Physiology. Simula SpringerBriefs on Computing(), vol 12. Springer, Cham. https://doi.org/10.1007/978-3-031-05164-7_7
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DOI: https://doi.org/10.1007/978-3-031-05164-7_7
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