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Systems analysis of the familial cardiomyopathy signaling network

Familial cardiomyopathy is a precursor of heart failure and sudden cardiac death. Over the past several decades, researchers have discovered numerous gene mutations primarily in sarcomeric and cytoskeletal proteins causing two different disease phenotypes: hypertrophic (HCM) and dilated (DCM) cardiomyopathies. However, molecular mechanisms linking genotype to phenotype remain unclear. Here, we employ a systems approach by integrating experimental findings into a cohesive signaling network to scrutinize genotype to phenotype mechanisms. We developed a predictive model of the HCM/DCM signaling network utilizing a logic-based differential equations approach and evaluated model performance in predicting experimental data from four contexts (HCM, DCM, pressure overload, and volume overload). The model has an overall prediction accuracy of 83.8% with higher accuracy in the HCM context (90%) compared with DCM (75%). Global sensitivity analysis identified key reactions of the signaling network, with calcium activation of myofilament force development and calcium-calmodulin kinase signaling ranking the highest. We performed a structural revision analysis to identify missing interactions in HCM/DCM signaling and found some potential reactions controlling calcium regulatory proteins. Combination pharmacotherapy analysis predicted that downregulation of signaling components such as calcium, titin and its associated proteins, growth factor receptors, and PI3K-AKT could inhibit myocyte growth in HCM. In DCM, PI3K-AKT-NFAT downregulation combined with upregulation of Ras/ERK12 or titin or Gq protein could attenuate cardiac remodeling. The influence of existing medications on cardiac growth in HCM and DCM contexts was simulated by the model. This HCM/DCM signaling model demonstrates utility in investigating genotype to phenotype mechanisms in familial cardiomyopathy.