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Published on: January 18, 2019
Genotype-Dependent Effects of Mechanical Stretch and GATA4-Targeted Compound 3i-1262 in Cardiomyopathy
Saana Pohjavaara1, Sini M Kinnunen1, Heikki Ruskoaho1
1Drug Research Program and Division of Pharmacology and Pharmacotherapy, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland.
Insights
Patient-derived heart cells reveal how genetic mutations in hypertrophic (HCM) and dilated (DCM) cardiomyopathies alter cellular responses to mechanical stress. These findings highlight the potential of hiPSC-cardiomyocytes for disease modeling and drug discovery.
Area of Science:
- Cardiovascular Biology
- Stem Cell Biology
- Genetics
Background:
- Genetic cardiomyopathies, including hypertrophic (HCM) and dilated (DCM), cause heart failure, but current treatments primarily manage symptoms.
- Patient-derived human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes offer a model to investigate genotype-specific disease mechanisms and drug responses.
Purpose of the Study:
- To investigate how MYBPC3 (HCM) and LMNA (DCM) mutations affect hiPSC-cardiomyocyte responses to mechanical stretch and a GATA4-targeted compound.
- To assess the utility of patient-derived hiPSC-cardiomyocytes for modeling cardiomyopathy pathophysiology and for drug discovery.
Main Methods:
- hiPSC-cardiomyocytes from healthy individuals and patients with MYBPC3 or LMNA mutations were subjected to cyclic mechanical stretch.
- Gene expression (qPCR) and protein levels (Western blotting) of hypertrophy-associated, mechanosensitive, and metabolism-related markers were analyzed.
- The effect of the GATA4-targeted compound 3i-1262 on cellular responses was evaluated.
Main Results:
- HCM and DCM cardiomyocytes showed distinct basal gene expression profiles compared to controls.
- Mechanical stretch differentially regulated specific genes (NPPB, MYH7, NPPA) in control, HCM, and DCM cardiomyocytes.
- The compound 3i-1262 demonstrated limited efficacy in modulating stretch-induced gene expression in patient-derived cells.
Conclusions:
- Cardiomyopathy-associated mutations significantly influence gene and protein expression and cellular responses to mechanical stimuli.
- Patient-derived hiPSC-cardiomyocytes are valuable tools for understanding cardiomyopathy pathogenesis and for identifying potential therapeutic targets.
- The study underscores the importance of genotype-specific approaches in cardiomyopathy research and drug development.
Abstract:
Genetic hypertrophic and dilated cardiomyopathies (HCM and DCM, respectively) are characterised by structural and functional abnormalities that can lead to heart failure. However, current therapies mainly reduce symptoms. Patient-derived human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes provide a valuable platform to study genotype-specific pathophysiology and pharmacology. We subjected hiPSC-cardiomyocytes from healthy individuals and from patients carrying pathogenic MYBPC3 (HCM) or LMNA (DCM) mutations to cyclic mechanical stretch, with or without the GATA4-targeted anti-hypertrophic compound 3i-1262, and assessed hypertrophy-associated, mechanosensitive and metabolism-related genes by qPCR, and hypertrophy-related proteins by Western blotting. Compared to control, HCM cardiomyocytes displayed higher basal expression of NPPB and MYH7, whereas DCM cardiomyocytes exhibited lower basal expression of NPPB and NPPA. Mechanical stretching induced NPPB and MYH7 upregulation in control cardiomyocytes, delayed MYH7 upregulation in HCM cardiomyocytes and NPPA downregulation in DCM cardiomyocytes. Other mechanosensitive genes, such as GAL, CSRP3 and SLC16A9, also exhibited genotype- and time-dependent regulation. In control cardiomyocytes, 3i-1262 produced limited modulation of stretch-induced gene expression but showed little or no effect in patient-derived cardiomyocytes. These findings demonstrate that cardiomyopathy mutations influence gene and protein expression, responses to mechanical stretch and 3i-1262, underscoring the value of patient-derived hiPSC-cardiomyocytes in disease modelling and drug discovery.
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