Translating myosin-binding protein C and titin abnormalities to whole-heart function using a novel calcium-contraction coupling model.

Mutations in cardiac myosin-binding protein C (cMyBP-C) or titin may respectively lead to hypertrophic (HCM) or dilated (DCM) cardiomyopathies. The mechanisms leading to these phenotypes remain unclear because of the challenge of translating cellular abnormalities to whole-heart and system function. We developed and validated a novel computer model of calcium-contraction coupling incorporating the role of cMyBP-C and titin based on the key assumptions: 1) tension in the thick filament promotes cross-bridge attachment mechanochemically, 2) with increasing titin tension, more myosin heads are unlocked for attachment, and 3) cMyBP-C suppresses cross-bridge attachment. Simulated stationary calcium-tension curves, isotonic and isometric contractions, and quick release agreed with experimental data. The model predicted that a loss of cMyBP-C function decreases the steepness of the calcium-tension curve, and that more compliant titin decreases the level of passive and active tension and its dependency on sarcomere length. Integrating this cellular model in the CircAdapt model of the human heart and circulation showed that a loss of cMyBP-C function resulted in HCM-like hemodynamics with higher left ventricular end-diastolic pressures and smaller volumes. More compliant titin led to higher diastolic pressures and ventricular dilation, suggesting DCM-like hemodynamics. The novel model of calcium-contraction coupling incorporates the role of cMyBP-C and titin. Its coupling to whole-heart mechanics translates changes in cellular calcium-contraction coupling to changes in cardiac pump and circulatory function and identifies potential mechanisms by which cMyBP-C and titin abnormalities may develop into HCM and DCM phenotypes. This modeling platform may help identify distinct mechanisms underlying clinical phenotypes in cardiac diseases.

Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation.

The complexity of cardiac electrophysiology, involving dynamic changes in numerous components across multiple spatial (from ion channel to organ) and temporal (from milliseconds to days) scales, makes an intuitive or empirical analysis of cardiac arrhythmogenesis challenging. Multiscale mechanistic computational models of cardiac electrophysiology provide precise control over individual parameters, and their reproducibility enables a thorough assessment of arrhythmia mechanisms. This review provides a comprehensive analysis of models of cardiac electrophysiology and arrhythmias, from the single cell to the organ level, and how they can be leveraged to better understand rhythm disorders in cardiac disease and to improve heart patient care. Key issues related to model development based on experimental data are discussed, and major families of human cardiomyocyte models and their applications are highlighted. An overview of organ-level computational modeling of cardiac electrophysiology and its clinical applications in personalized arrhythmia risk assessment and patient-specific therapy of atrial and ventricular arrhythmias is provided. The advancements presented here highlight how patient-specific computational models of the heart reconstructed from patient data have achieved success in predicting risk of sudden cardiac death and guiding optimal treatments of heart rhythm disorders. Finally, an outlook toward potential future advances, including the combination of mechanistic modeling and machine learning/artificial intelligence, is provided. As the field of cardiology is embarking on a journey toward precision medicine, personalized modeling of the heart is expected to become a key technology to guide pharmaceutical therapy, deployment of devices, and surgical interventions.

Increased Chamber Resting Tone Is a Key Determinant of Left Ventricular Diastolic Dysfunction.

BACKGROUND: Twitch-independent tension has been demonstrated in cardiomyocytes, but its role in heart failure (HF) is unclear. We aimed to address twitch-independent tension as a source of diastolic dysfunction by isolating the effects of chamber resting tone (RT) from impaired relaxation and stiffness. METHODS: We invasively monitored pressure-volume data during cardiopulmonary exercise in 20 patients with hypertrophic cardiomyopathy, 17 control subjects, and 35 patients with HF with preserved ejection fraction. To measure RT, we developed a new method to fit continuous pressure-volume measurements, and first validated it in a computational model of loss of cMyBP-C (myosin binding protein-C). RESULTS: In hypertrophic cardiomyopathy, RT (estimated marginal mean [95% CI]) was 3.4 (0.4-6.4) mm Hg, increasing to 18.5 (15.5-21.5) mm Hg with exercise (P<0.001). At peak exercise, RT was responsible for 64% (53%-76%) of end-diastolic pressure, whereas incomplete relaxation and stiffness accounted for the rest. RT correlated with the levels of NT-proBNP (N-terminal pro-B-type natriuretic peptide; R=0.57; P=0.02) and with pulmonary wedge pressure but following different slopes at rest and during exercise (R2=0.49; P<0.001). In controls, RT was 0.0 mm Hg and 1.2 (0.3-2.8) mm Hg in HF with preserved ejection fraction patients and was also exacerbated by exercise. In silico, RT increased in parallel to the loss of cMyBP-C function and correlated with twitch-independent myofilament tension (R=0.997). CONCLUSIONS: Augmented RT is the major cause of LV diastolic chamber dysfunction in hypertrophic cardiomyopathy and HF with preserved ejection fraction. RT transients determine diastolic pressures, pulmonary pressures, and functional capacity to a greater extent than relaxation and stiffness abnormalities. These findings support antimyosin agents for treating HF.