Computational models show that functional remodeling, not anatomy, reshapes physiological determinants of cardiac performance in hypertrophic cardiomyopathy. - Rodero,C; Curran,L; Lanyon,CW; Inglese,P; Qayyum,A; Barrows,RK; Solis-Lemus,JA; Rahmani,S; Strocchi,M; Lee,AWC; Baptiste,TMG; Cicci,L; et al. (J Mol Cell Cardiol, 2026)
Hypertrophic cardiomyopathy (HCM) is a condition characterized by variable patterns of myocardial hypertrophy. Progressive functional remodeling of material properties contributes to symptoms, disease progression, and variability in treatment response. However, it is not clear how these properties interact to determine cardiac performance and response to treatment. We quantified how cardiac anatomy variability, functional remodeling, and pharmacological treatment influence the relative importance of biophysical mechanisms that govern cardiac function. We built five four-chamber electromechanical heart models representing anatomical clusters. We performed global sensitivity analyses on 46 parameters across 32 outputs. We repeated this process 18 times to model different types of functional remodeling and two times to model mavacamten and aficamten. Across all representative HCM phenotypes, sensitivity profiles were preserved. Within the parameter ranges examined, ventricular afterload explained the largest share of variance in hemodynamic outputs across anatomies (up to 69%). Functional remodeling led to shifts in parameter importance, mostly when ventricular stiffness was increased. The modeling of pharmacological treatments led to modest but targeted changes, with mavacamten and aficamten producing comparable effects, particularly for outputs related to arterial pressures. Across major anatomical phenotypes of hypertrophic cardiomyopathy, functional remodeling, rather than anatomy alone, reshaped the relative importance of cellular, myocardial, and loading-related parameters, with the largest shifts under increased ventricular stiffness and under aficamten in obstructive physiology. These hypothesis-generating results suggest that the integration of biomarkers reflecting ventricular-arterial coupling, myocardial stiffness, and contractile state may help anticipate symptoms and treatment response in HCM.