Translational Cardiology in Genetic Cardiomyopathies

Abstract

Translational cardiology applied to genetic cardiomyopathies is a rapidly evolving field that bridges molecular research and clinical practice through a “bench-to-bedside and back” paradigm. Hereditary cardiomyopathies, once classified primarily based on clinical phenotype, are now increasingly understood at the molecular level through the integration of genetics, cellular biology, and experimental modeling. The identification of pathogenic variants in key genes, such as TTN , LMNA , and MYBPC3 , has enabled earlier diagnosis and more accurate familial risk stratification. However, currently available treatments remain largely symptomatic rather than disease-modifying. In recent years, advances in both in vitro models—including induced pluripotent stem cell (iPSC)-derived cardiomyocytes, cardiac organoids, and engineered heart tissues—and in vivo systems, such as zebrafish, murine, porcine, and nonhuman primate models, have significantly enhanced our understanding of the molecular and cellular mechanisms underlying contractile dysfunction and arrhythmogenesis. These platforms provide powerful tools for the development and preclinical testing of next-generation therapeutic strategies. A notable example of successful translation is mavacamten, a selective cardiac myosin inhibitor that has demonstrated clinical efficacy in obstructive hypertrophic cardiomyopathy. In parallel, emerging therapeutic approaches—including gene therapies (e.g., AAV- and mRNA-based platforms), RNA-targeting strategies (such as antisense oligonucleotides, siRNA, and exon skipping), and advanced gene-editing technologies (including CRISPR, base editing, and prime editing)—offer promising avenues for the correction of causal genetic defects. The multimodal integration of genomic, omics, imaging, and biomarker data, increasingly supported by artificial intelligence, is reshaping paradigms of early diagnosis and predictive medicine. Looking ahead, the convergence of advanced experimental models, gene-based therapies, and digital twin technologies holds the potential to enable truly precise, personalized, and preventive cardiology.