J Pei1,2,3, M Schuldt4, E Nagyova5, J van der Velden4, F W Asselbergs6,7,8,9, M Harakalova10,11, Z Gu12, S El Bouhaddani12, L Yiangou13, M Jansen14, J J A Calis1,2, L M Dorsch4, C Snijders Blok1, N A M van den Dungen5, N Lansu5, B J Boukens15, I R Efimov16, M Michels17, M C Verhaar2,3, R de Weger18, A Vink18, F G van Steenbeek1,2,19, A F Baas14, R P Davis13, H W Uh12, D W D Kuster4, C Cheng2,3,16, M Mokry1,2,5,20. 1. Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, University of Utrecht, 3584 CT, Utrecht, The Netherlands. 2. Regenerative Medicine Utrecht (RMU), University Medical Center Utrecht, University of Utrecht, 3584 CT, Utrecht, The Netherlands. 3. Department of Nephrology and Hypertension, DIG-D, UMC Utrecht, University of Utrecht, Utrecht, The Netherlands. 4. Department of Physiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. 5. Laboratory of Clinical Chemistry and Hematology, UMC Utrecht, Utrecht, The Netherlands. 6. Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, University of Utrecht, 3584 CT, Utrecht, The Netherlands. f.w.asselbergs@umcutrecht.nl. 7. Health Data Research UK and Institute of Health Informatics, University College London, London, UK. f.w.asselbergs@umcutrecht.nl. 8. Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK. f.w.asselbergs@umcutrecht.nl. 9. Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Room E03.818, P.O. Box 85500, 3508 GA, Utrecht, The Netherlands. f.w.asselbergs@umcutrecht.nl. 10. Division Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, University of Utrecht, 3584 CT, Utrecht, The Netherlands. m.harakalova@umcutrecht.nl. 11. Regenerative Medicine Utrecht (RMU), University Medical Center Utrecht, University of Utrecht, 3584 CT, Utrecht, The Netherlands. m.harakalova@umcutrecht.nl. 12. Department of Biostatistics and Research Support, UMC Utrecht, University of Utrecht, Utrecht, The Netherlands. 13. Department of Anatomy and Embryology, LUMC, Leiden, The Netherlands. 14. Department of Genetics, Division of Laboratories, Pharmacy and Biomedical Genetics, UMC Utrecht, University of Utrecht, Utrecht, The Netherlands. 15. Department of Medical Biology, AMC, Amsterdam, The Netherlands. 16. Department of Biomedical Engineering, GWU, Washington, DC, USA. 17. Department of Cardiology, Thoraxcentre, Erasmus Medical Centre, Rotterdam, The Netherlands. 18. Department of Pathology, UMC Utrecht, University of Utrecht, Utrecht, The Netherlands. 19. Department of Clinical Sciences, Faculty of Veterinary Medicine, University of Utrecht, Utrecht, The Netherlands. 20. Division of Paediatrics, UMC Utrecht, University of Utrecht, Utrecht, The Netherlands.
Abstract
BACKGROUND: Hypertrophic cardiomyopathy (HCM) is the most common genetic disease of the cardiac muscle, frequently caused by mutations in MYBPC3. However, little is known about the upstream pathways and key regulators causing the disease. Therefore, we employed a multi-omics approach to study the pathomechanisms underlying HCM comparing patient hearts harboring MYBPC3 mutations to control hearts. RESULTS: Using H3K27ac ChIP-seq and RNA-seq we obtained 9310 differentially acetylated regions and 2033 differentially expressed genes, respectively, between 13 HCM and 10 control hearts. We obtained 441 differentially expressed proteins between 11 HCM and 8 control hearts using proteomics. By integrating multi-omics datasets, we identified a set of DNA regions and genes that differentiate HCM from control hearts and 53 protein-coding genes as the major contributors. This comprehensive analysis consistently points toward altered extracellular matrix formation, muscle contraction, and metabolism. Therefore, we studied enriched transcription factor (TF) binding motifs and identified 9 motif-encoded TFs, including KLF15, ETV4, AR, CLOCK, ETS2, GATA5, MEIS1, RXRA, and ZFX. Selected candidates were examined in stem cell-derived cardiomyocytes with and without mutated MYBPC3. Furthermore, we observed an abundance of acetylation signals and transcripts derived from cardiomyocytes compared to non-myocyte populations. CONCLUSIONS: By integrating histone acetylome, transcriptome, and proteome profiles, we identified major effector genes and protein networks that drive the pathological changes in HCM with mutated MYBPC3. Our work identifies 38 highly affected protein-coding genes as potential plasma HCM biomarkers and 9 TFs as potential upstream regulators of these pathomechanisms that may serve as possible therapeutic targets.
BACKGROUND: Hypertrophic cardiomyopathy (HCM) is the most common genetic disease of the cardiac muscle, frequently caused by mutations in MYBPC3. However, little is known about the upstream pathways and key regulators causing the disease. Therefore, we employed a multi-omics approach to study the pathomechanisms underlying HCM comparing patient hearts harboring MYBPC3 mutations to control hearts. RESULTS: Using H3K27ac ChIP-seq and RNA-seq we obtained 9310 differentially acetylated regions and 2033 differentially expressed genes, respectively, between 13 HCM and 10 control hearts. We obtained 441 differentially expressed proteins between 11 HCM and 8 control hearts using proteomics. By integrating multi-omics datasets, we identified a set of DNA regions and genes that differentiate HCM from control hearts and 53 protein-coding genes as the major contributors. This comprehensive analysis consistently points toward altered extracellular matrix formation, muscle contraction, and metabolism. Therefore, we studied enriched transcription factor (TF) binding motifs and identified 9 motif-encoded TFs, including KLF15, ETV4, AR, CLOCK, ETS2, GATA5, MEIS1, RXRA, and ZFX. Selected candidates were examined in stem cell-derived cardiomyocytes with and without mutated MYBPC3. Furthermore, we observed an abundance of acetylation signals and transcripts derived from cardiomyocytes compared to non-myocyte populations. CONCLUSIONS: By integrating histone acetylome, transcriptome, and proteome profiles, we identified major effector genes and protein networks that drive the pathological changes in HCM with mutated MYBPC3. Our work identifies 38 highly affected protein-coding genes as potential plasma HCM biomarkers and 9 TFs as potential upstream regulators of these pathomechanisms that may serve as possible therapeutic targets.
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