Multi-Omics and Deep Phenotyping in Hypertrophic Cardiomyopathy: Toward Precision Therapy

Background: Hypertrophic cardiomyopathy (HCM) is a genetically heterogeneous myocardial disorder characterized by left ventricular hypertrophy, myofibrillar disarray, and diastolic dysfunction. Although traditionally considered a monogenic disease caused by sarcomeric mutations, emerging evidence highlights substantial phenotypic variability and involvement of complex gene-environment interactions. Conventional treatment strategies are largely symptom-based and do not address the underlying molecular mechanisms. Multi-omics approaches combined with deep phenotyping offer a transformative framework for dissecting the biological complexity of HCM and identifying actionable targets for precision therapy. Methods and Results: This review integrates data from genomics, transcriptomics, proteomics, metabolomics, and epigenomics to define molecular endotypes of HCM across patient subgroups. Next-generation sequencing has expanded the known spectrum of pathogenic and modifier variants, while transcriptomic and proteomic profiling reveals dysregulation in calcium signaling, energy metabolism, extracellular matrix remodeling, and immune pathways. Metabolomic analysis uncovers alterations in fatty acid oxidation, ketone utilization, and mitochondrial energetics that correlate with symptom severity and arrhythmia risk. Advanced imaging techniques, machine learning–based clustering, and wearable biosensors contribute to high-resolution phenotyping. Integration of omics and phenotypic data identifies candidate biomarkers and therapeutic targets including AMPK, HDACs, TGF-β, and mTOR signaling axes. Early trials of mechanism-based therapies such as mavacamten and metabolic modulators show promise in altering disease trajectory. Conclusion: Multi-omics and deep phenotyping provide a powerful lens through which to redefine hypertrophic cardiomyopathy as a systems-level disease with distinct molecular subtypes.