Complex patterns of subcellular cardiac alternans

Dual regulation by subcellular calcium heterogeneity and heart rate variability on cardiac electromechanical dynamics

Heart rate constantly varies under physiological conditions, termed heart rate variability (HRV), and in clinical studies, low HRV is associated with a greater risk of cardiac arrhythmias. Prior work has shown that HRV influences the temporal patterns of electrical activity, specifically the formation of pro-arrhythmic alternans, a beat-to-beat alternation in the action potential duration (APD), or intracellular calcium (Ca) levels. We previously showed that HRV may be anti-arrhythmic by disrupting APD and Ca alternations in a homogeneous cardiac myocyte. Here, we expand on our previous work, incorporating variation in subcellular Ca handling (also known to influence alternans) into a nonlinear map model of a cardiac myocyte composed of diffusively coupled Ca release units (CRUs). Ca-related parameters and initial conditions of each CRU are varied to mimic subcellular Ca heterogeneity, and a stochastic pacing sequence reproduces HRV. We find that subcellular Ca heterogeneity promotes the formation of spatially discordant subcellular alternans patterns, which decreases whole cell Ca and APD alternation for low and moderate HRV, while high subcellular Ca heterogeneity and HRV both promote electromechanical desynchronization. Finally, we find that for low and moderate HRV, both the specific subcellular Ca-related parameters and the pacing sequences influence measures of electromechanical dynamics, while for high HRV, these measures depend predominantly on the pacing sequence. Our results suggest that pro-arrhythmic subcellular discordant alternans tend to form for low levels of HRV, while high HRV may be anti-arrhythmic due to mitigated influence from subcellular Ca heterogeneity and desynchronization of APD from Ca instabilities.

Two-variable nullcline analysis of ionic general equilibrium predicts calcium homeostasis in ventricular myocytes

Ventricular contraction is roughly proportional to the amount of calcium released from the Sarcoplasmic Reticulum (SR) during systole. While it is rather straightforward to measure calcium levels and contractibility under different physiological conditions, the complexity of calcium handling during systole and diastole has made the prediction of its release at steady state impossible. Here we approach the problem analyzing the evolution of intracellular and extracellular calcium fluxes during a single beat which is away from homeostatic balance. Using an in-silico subcellular model of rabbit ventricular myocyte, we show that the high dimensional nonlinear problem of finding the steady state can be reduced to a two-variable general equilibrium condition where pre-systolic calcium level in the cytosol and in the SR must fulfill simultaneously two different equalities. This renders calcium homeostasis as a problem that can be studied in terms of its equilibrium structure, leading to precise predictions of steady state from single-beat measurements. We show how changes in ion channels modify the general equilibrium, as shocks would do in general equilibrium macroeconomic models. This allows us to predict when an enhanced entrance of calcium in the cell reduces its contractibility and explain why SERCA gene therapy, a change in calcium handling to treat heart failure, might fail to improve contraction even when it successfully increases SERCA expression.

Cardiomyocytes, upon voltage excitation, release calcium, which leads to cell contraction. However, under some pathological conditions, calcium handling is impaired. Recently, SERCA gene therapy, whose aim is to improve Ca²⁺ sequestration by the Sarcoplasmic Reticulum (SR), has failed to improve the prognosis of patients with Heart Failure. This, together with recent counterintuitive results in calcium handling, has highlighted the need for a framework to understand calcium homeostasis across species and pathologies. We show here that the proper framework is a general equilibrium approach of two independent variables. The development of this framework allows us to find a possible mechanism for the failure of SERCA gene therapy even when it manages to increase Ca SERCA expression.