ArticleComputers in biology and medicine2024
Modeling cardiomyocyte signaling and metabolism predicts genotype-to-phenotype mechanisms in hypertrophic cardiomyopathy.
Article in Computers in biology and medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Clinical spectrum, cardiac phenotypes, and outcomes of FHL1-related cardiomyopathies: a systematic review.BMC cardiovascular disorders · 2026Pooled it
- Immature and mature myocardium in the pathophysiology of hypertrophic cardiomyopathy.Journal of molecular and cellular cardiology plus · 2026Review
- Systems modelling of mitochondrial dynamics in different exercise regimes.The Journal of physiology · 2026Article
- Digital twins in hypertrophic cardiomyopathy from sarcomeric mutation to predictive personalized care.Annals of medicine and surgery (2012) · 2026Article
- Systems modeling and uncertainty quantification of AMP-activated protein kinase signaling.NPJ systems biology and applications · 2025Article
- Metabolic regulation for the treatment of ischemic heart disease with stem cells and extracellular vesicles.NPJ cardiovascular health · 2025Review
- The Evolution of Systems Biology and Systems Medicine: From Mechanistic Models to Uncertainty Quantification.Annual review of biomedical engineering · 2025Review
- Cardiac Myosin Inhibitors in Hypertrophic Cardiomyopathy: Clinical Advances and Therapeutic Prospects.Drug design, development and therapy · 2025Review
- Deciphering Oxidative Stress in Cardiovascular Disease Progression: A Blueprint for Mechanistic Understanding and Therapeutic Innovation.Antioxidants (Basel, Switzerland) · 2024Review
- Redox Homeostasis and Molecular Biomarkers in Precision Therapy for Cardiovascular Diseases.Antioxidants (Basel, Switzerland) · 2024Review
- DynProfiler: a Python package for comprehensive analysis and interpretation of signaling dynamics leveraged by deep learning techniques.Bioinformatics advances · 2024Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Familial hypertrophic cardiomyopathy (HCM) is a significant precursor of heart failure and sudden cardiac death, primarily caused by mutations in sarcomeric and structural proteins. Despite the extensive research on the HCM genotype, the complex and context-specific nature of many signaling and metabolic pathways linking the HCM genotype to phenotype has hindered therapeutic advancements for patients. Here, we have developed a computational model of HCM encompassing cardiomyocyte signaling and metabolic networks and their associated interactions. Utilizing a stochastic logic-based ODE approach, we linked cardiomyocyte signaling to the metabolic network through a gene regulatory network and post-translational modifications. We validated the model against published data on activities of signaling species in the HCM context and transcriptomes of two HCM mouse models (i.e., R403Q-αMyHC and R92W-TnT). Our model predicts that HCM mutation induces changes in metabolic functions such as ATP synthase deficiency and a transition from fatty acids to carbohydrate metabolism. The model indicated major shifts in glutamine-related metabolism and increased apoptosis after HCM-induced ATP synthase deficiency. We predicted that the transcription factors STAT, SRF, GATA4, TP53, and FoxO are the key regulators of cardiomyocyte hypertrophy and apoptosis in HCM in alignment with experiments. Moreover, we identified shared (e.g., activation of PGC1α by AMPK, and FHL1 by titin) and context-specific mechanisms (e.g., regulation of Ca2+ sensitivity by titin in HCM patients) that may control genotype-to-phenotype transition in HCM across different species or mutations. We also predicted potential combination drug targets for HCM (e.g., mavacamten plus ROS inhibitors) preventing or reversing HCM phenotype (i.e., hypertrophic growth, apoptosis, and metabolic remodeling) in cardiomyocytes. This study provides new insights into mechanisms linking genotype to phenotype in familial hypertrophic cardiomyopathy and offers a framework for assessing new treatments and exploring variations in HCM experimental models.
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Registered trials
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