Heterogeneous HCM Cellular Abnormalities

Updated 7 July 2025

Heterogeneous HCM-induced cellular abnormalities are defined by diverse genetic, metabolic, and mechanical perturbations that disrupt mitochondrial function, sarcomere organization, and tissue remodeling.
Advanced imaging and computational modeling quantify variations in stress patterns, fiber disarray, and contractile dynamics critical for understanding HCM pathophysiology.
These insights inform precision therapies by linking local cellular perturbations to global cardiac dysfunction and guiding targeted modulation of contractility, metabolism, and fibrotic remodeling.

Heterogeneous HCM-Induced Cellular Abnormalities encompass the multifaceted spatial and temporal variations in cellular structure, mechanics, metabolism, and function observed in hypertrophic cardiomyopathy (HCM). These abnormalities arise from the interplay between genetic variants, molecular and metabolic perturbations, mechanical heterogeneity, and tissue remodeling processes. Together, they underlie the phenotypic complexity of HCM—from subtle cellular disarray and energy deficits to disorganized tissue architecture and compromised cardiac performance.

1. Genetic, Metabolic, and Organelle-Level Sources of Heterogeneity

Cellular heterogeneity in HCM is fundamentally shaped by both genetic and non-genetic factors, especially within the mitochondrial compartment. Mitochondria in eukaryotic cells are diverse populations, with individual organelles harboring distinct mitochondrial DNA (mtDNA) variants—this intra-cellular diversity is termed microheteroplasmy, which, through random genetic drift or selection, can evolve into inter-cellular differences (macroheteroplasmy) (Aryaman et al., 2018). Such mtDNA mutations or copy number variations directly impact the expression and function of respiratory chain components.

On the non-genetic front, heterogeneity emerges from differences in respiratory supercomplex assembly, inner membrane architecture (such as cristae structure and cardiolipin content), and fluctuations in mitochondrial membrane potential (Δψ). Collectively, these factors introduce cell-to-cell and organelle-to-organelle "noise," which may manifest more severely in HCM due to the heart’s high energetic demands and its dependence on tightly regulated mitochondrial homeostasis.

These processes can be quantitatively described. The variance in heteroplasmy within a cell population can be modeled by:

$V(h) \approx f_s \cdot \frac{2\mu t}{n} \cdot h_0(1-h_0)$

where $V(h)$ is heteroplasmy variance, $f_s$ is the fraction of unfused mitochondria, $\mu$ is the mitophagy rate, $t$ is time, $n$ is mtDNA copy number, and $h_0$ is initial heteroplasmy. Mitochondrial network fragmentation (high $f_s$ ) and elevated mitophagy amplify genetic differences into phenotypic variability.

Mitochondrial complementation—exchange of soluble gene products via fusion-fission cycles—serves as a buffering mechanism, but has limitations due to restricted diffusion and inner membrane protein mobility, making genotype-phenotype coupling locally strong even amidst global rescue (Aryaman et al., 2018).

2. Mechanical Heterogeneity and Tissue Plasticity

Mechanical heterogeneity, both at the cell and tissue level, significantly influences HCM progression and phenotype (Li et al., 2019). Using a vertex-based model, cellular stiffness is parameterized by a preferred shape index ( $p_0$ ). In a heterogeneous tissue, each cell draws its $p_0$ from a distribution (typically Gaussian), creating a spectrum of mechanical properties.

The tissue-level rigidity is governed by the fraction $f_r$ of "rigid" cells ( $p_0$ below a critical threshold):

$f_r = \int_{-\infty}^{\mu^*} \mathcal{A}_{\mu,\sigma}(p_0) \, dp_0$

where $\mu^* \approx 3.812$ . Notably, collective rigidity emerges at $f_r^* \approx 0.21$ , well below the physical percolation threshold, indicating spatially extended tension networks mediate bulk mechanical states.

This heterogeneity drives the onset of intermediate solid states, impedes or intermittently modulates cellular invasion, and, in the context of HCM, can underpin the paradox where tissues composed of softer (or mixed stiffness) cells become globally rigid. Such tissue-level mechanics may foster aberrant force transmission and altered cell signaling, contributing to disordered cellular alignment and maladaptive remodeling characteristic of HCM.

3. Structural Organization and Disarray of the Sarcomere and Myocardial Fibers

HCM is typified by disruption in the nanoscale and mesoscale organization of cardiomyocytes. Advanced imaging (e.g., small-angle X-ray scattering, SAXS) reveals that myofilament mutations linked to HCM produce decreased lattice ordering in the sarcomere, evidenced by lower scattering intensity ( $I_{1,0}$ ) and increased lattice spacing ( $D_{1,0}$ ), both of which correlate with contractile force (R² ≈ 0.44 and 0.46, respectively) (Javor et al., 2021). The high correlation (R² ≈ 0.81) between these structural parameters indicates their robustness as biomarkers of subcellular disarray.

At the tissue and organ level, fiber disarray emerges as a biomechanical consequence of underlying heterogeneous cellular abnormalities. Multiscale finite element models (MyoFE) integrate molecular-level contractility (via parameters like K–SRx for myosin kinetics) and regional fibrosis (increased stiffness, isotropy) with a stress-based fiber reorientation law:

$\frac{df_0}{dt} = k \left[ \frac{S f_0}{||S f_0||} - f_0 \right]$

where $f_0$ is the local fiber orientation and $S$ is the total (active + passive) stress tensor (Mehri et al., 23 Sep 2024, Mehri et al., 2 Jul 2025). Heterogeneous distributions of hypercontractile, hypocontractile, and fibrotic cells cause spatially variable stress patterns that drive distinct localized remodeling. Notably, simulations demonstrate that fiber disarray is regionally accentuated in the epicardium, reflecting mismatches in stress distribution and aligning with histological and DT-MRI evidence.

4. Heterogeneity in Transport Dynamics and Viscoelasticity

Anomalous and heterogeneous transport ("HAT," Editor's term) is a haLLMark of many biological systems including heart muscle (Waigh et al., 2023). Deviations from normal (Fickian) diffusion are described by a space- and time-dependent mean square displacement:

$\textrm{MSD}(t) \sim D_\alpha(r, t) \, t^{\alpha(r, t)}$

where both $D_\alpha$ and $\alpha$ are local, reflecting environments varying from subdiffusive (α < 1) in fibrotic or crowded zones to intermittent superdiffusive pockets. In HCM, altered cytoskeletal arrangements and regional fibrosis create a landscape of heterogeneous viscoelasticity (Waigh et al., 2023). These processes disrupt proper transport of ions, proteins, and organelles, potentially leading to spatially clustered dysfunctions, regional metabolic impairment, and altered signal transduction.

Experimental approaches such as single-particle tracking, fluorescence correlation spectroscopy, and neural network-based trajectory analysis allow quantification of these variations. Anomalous transport characteristics—such as broadened distributions of $D_\alpha$ or α—may serve as quantitative biomarkers distinguishing pathological from healthy myocardium.

5. Linking Cellular Abnormalities to Organ-Level Function

Cellular heterogeneity in contractile machinery (including altered calcium sensitivity and cross-bridge cycling kinetics) substantially influences pressure-volume relationships and cardiac performance (Regazzoni et al., 9 Nov 2024). Computational models show that the end-systolic pressure–volume relationship (ESPVr) is inherently variable, forming a region or “cloud” modulated by the mechanical and molecular history of contraction. For example, enhanced apparent calcium sensitivity with increased sarcomere length, and accelerated cross-bridge cycling (as seen in HCM), can result in hypercontractile pressure-volume profiles:

$\eta_\text{eff} = \eta_0 (1 + \alpha (SL - SL_0))$

$F(v) = F_\text{max} (1 - v/v_\text{max})$

where $\eta_\text{eff}$ is effective calcium sensitivity, $SL$ is sarcomere length, and $F(v)$ represents force–velocity dependence. These mechanisms account for augmented contractility during ejection, and their dysregulation helps explain both the hyperdynamic and heart failure phenotypes seen in HCM.

6. Computational Tools, Disease Modeling, and Translation

Advanced analytical frameworks, including deep learning-based image analysis and multiscale finite element modeling, facilitate the objective quantification of heterogeneous cellular abnormalities (Mohammadzadeh et al., 30 Jan 2025). The enhanced SarcGraph pipeline, for example, leverages neural network-based z-disc detection and probabilistic ensemble scoring to reliably annotate sarcomere and myofibrillar features from fluorescent imaging data. Extracted metrics—such as sarcomere length, orientation order parameter, and z-disc classification ratio—discriminate between organized, healthy cells and those exhibiting HCM-like disarray.

These high-dimensional features support both supervised (e.g., support vector regression for expert score prediction) and unsupervised (e.g., explainable clustering for unbiased cell classification) analyses. Such computational approaches not only facilitate biological insight but also identify biases in manual scoring, inform objective assessment pipelines, and link cellular organization to gene expression and functional outputs.

At the tissue and organ scale, MyoFE-type modeling unites molecular perturbations with mechanics and hemodynamics, providing a platform to simulate the consequences of targeted interventions (e.g., modulating contractility or fibrotic remodeling) and to design precision therapeutics for HCM.

7. Implications and Prospects for Therapy

The integration of genetic, metabolic, structural, mechanical, and transport-based sources of heterogeneity elucidates the complex phenotype of HCM. The spatially heterogeneous distribution of hypercontractile, hypocontractile, and fibrotic abnormalities drives a cascade leading to fiber disarray, impaired pumping, and increased arrhythmic risk. In addition, regional differences in fiber misalignment (epicardium vs. endocardium) and altered viscoelastic transport properties highlight the need for spatially resolved diagnostics and therapies.

Emerging computational models and quantitative biomarkers from imaging and experimental data are poised to refine disease stratification, predict individual risk, and evaluate targeted interventions. Future strategies may combine modulation of mitochondrial function, contractile kinetics, and fibrosis progression to ameliorate regional heterogeneity and preserve functional myocardial architecture.

In summary, heterogeneous HCM-induced cellular abnormalities are central to disease pathophysiology, spanning the molecular to the tissue level. Multiscale integration of data and advanced modeling approaches reveal how local perturbations amplify into global cardiac dysfunction and inform therapeutic development focused on mitigating adverse remodeling, restoring fiber organization, and improving patient outcomes.