Multiscale characterization of heart failure

Abstract

Dilated cardiomyopathy is a progressive irreversible disease associated with contractile dysfunction and heart failure. During dilated cardiomyopathy, elevated diastolic wall strains trigger mechanotransduction pathways that initiate the addition of sarcomeres in series and an overall increase in myocyte length. At the whole organ level, this results in a chronic dilation of the ventricles, an increase in end diastolic and end systolic volumes, and a decrease in ejection fraction. However, how exactly changes in sarcomere number translate into changes in myocyte morphology, and how these cellular changes translate into ventricular dilation remains incompletely understood. Here we combined a chronic animal study, continuum growth modeling, and machine learning to quantify correlations between sarcomere dynamics, myocyte morphology, and ventricular dilation. In an eight-week long volume overload study of six pigs, we found that the average sarcomere number increased by +3.8%/week, from 47 to 62, resulting in a myocyte lengthening of +3.3%/week, from 85 to 108 μm, while the sarcomere length and myocyte width remained unchanged. At the same time, the average end diastolic volume increased by +6.0%/week. Using continuum growth modeling and Bayesian inference, we correlated alterations on the subcellular, cellular, and organ scales and found that the serial sarcomere number explained 88% of myocyte lengthening, which, in turn, explained 54% of cardiac dilation. Our results demonstrate that sarcomere number and myocyte length are closely correlated and constitute the major determinants of dilated heart failure. We anticipate our study to be a starting point for more sophisticated multiscale models of heart failure. Our study suggests that altering sarcomere turnover-and with it myocyte morphology and ventricular dimensions-could be a potential therapeutic target to attenuate or reverse the progression of heart failure. STATEMENT OF SIGNIFICANCE: Heart failure is a significant global health problem that affects more than 25 million people worldwide and increases in prevalence as the population ages. Heart failure has been studied excessively at various scales; yet, there is no compelling concept to connect knowledge from the subcellular, cellular, and organ level across the scales. Here we combined a chronic animal study, continuum growth modeling, and machine learning to quantify correlations between sarcomere dynamics, myocyte morphology, and ventricular dilation. We found that the serial sarcomere number explained 88% of myocyte lengthening, which, in turn, explained 54% of cardiac dilation. Our results show that sarcomere number and myocyte length are closely correlated and constitute the major determinants of dilated heart failure. This suggests that altering the sarcomere turnover-and with it myocyte morphology and ventricular dimensions-could be a potential therapeutic target to attenuate or reverse heart failure.

Keywords: Bayesian inference; Growth and remodeling; Heart failure; Machine learning; Multiscale modeling; Myocyte; Sarcomere; Uncertainty quantification.

Figure 1:. Bridging the subcellular, cellular, and tissue levels using a multiscale continuum growth model.

We characterize sarcomere numbers and length, myocyte widths and lengths, and end diastolic and systolic volumes in a longitudinal study of volume overload using histology and echocardiography. We quantify the agreement between simulation and experiment in terms of myocyte lengths and end diastolic volumes recorded in six animals throughout a period of eight weeks.

Figure 2:. Changes in histology in response to left ventricular volume overload.

Healthy myocytes, top, at baseline were 85.45±22.30μm long and 13.67±3.73μm wide, made up of 47.50±11.67 sarcomeres with a length of 1.75±0.15μm. Volume overloaded myocytes at week 8, bottom, were 107.75±26.57μm long and 12.98±3.01μm wide, made up of 62.07±16.35 sarcomeres with a length of 1.77±0.11μm.

Figure 3:. Correlating cellular and organ levels.

Illustration of the deformation φ, deformation gradient F = ∇φ = F^e · F^g, elastic tensor F^e, and growth tensor F^g to correlate changes in end diastolic volume to changes in myocyte length ϑ^|| and width ϑ^⊥.

Figure 4:. Growth in myocyte length and width, and simulated and experimental changes in normalized end diastolic volumes.

Gray lines represent uncertainties in myocyte measurements, blue lines uncertainties propagated into end diastolic volume simulations, red lines uncertainties in end diastolic volume measurements, and black lines the median for each case.

Figure 5:. Changes in sarcomere number in response to left ventricular volume overload.

Gray dots represent n = 404 individual measurements of sarcomere numbers, solid gray lines represent their medians, and dashed black lines their 95% confidence intervals. Color contours from black to white highlight the probability density from high to low.

Figure 6:. Changes in sarcomere length in response to left ventricular volume overload.

Gray dots represent n = 930 individual measurements of sarcomere lengths, solid gray lines represent their medians, and dashed black lines their 95% confidence intervals. Color contours from black to white highlight the probability density from high to low.

Figure 7:. Changes in myocyte length in response to left ventricular volume overload.

Gray dots represent n = 460 individual measurements of myocyte lengths, solid gray lines represent their medians, and dashed black lines their 95% confidence intervals. Color contours from black to white highlight the probability density from high to low.

Figure 8:. Changes in myocyte width in response to left ventricular volume overload.

Gray dots represent n = 460 individual measurements of myocyte width, solid gray lines represent their medians, and dashed black lines their 95% confidence intervals. Color contours from black to white highlight the probability density from high to low.

Figure 9:. Changes in end diastolic volume in response to left ventricular volume overload.

Gray dots represent n = 28 individual measurements of end diastolic volume, solid gray lines represent their medians, and dashed black lines their 95% confidence intervals. Color contours from black to white highlight the probability density from high to low.

Figure 10:. Simulation and experiment of myocyte length in response to left ventricular volume overload.

Blue histograms represent simulations, red histograms represent experiments, both with uncertainty; percentage agreement refers to the region shared between both histograms. The average agreement between simulation and experiment was 88%.

Figure 11:. Simulation of end diastolic volumes in response to left ventricular volume overload.

The example shows the growing left ventricle at end diastole from week 0 to week 8, here simulated with the median myocyte length ϑ^|| and myocyte width ϑ^⊥ according to Figure 4.

Figure 12:. Simulation and experiment of normalized end diastolic volume in response to left ventricular volume overload.

Blue histograms represent simulations, red histograms represent experiments, both with uncertainty; percentage agreement refers to the region shared between both histograms. The average agreement between simulation and experiment was 54%.