Multi-omics integration identifies key upstream regulators of pathomechanisms in hypertrophic cardiomyopathy due to truncating MYBPC3 mutations

J. Pei, M. Schuldt, E. Nagyova, Z. Gu, S. el Bouhaddani, L. Yiangou, M. Jansen, J. J.A. Calis, L. M. Dorsch, C. Snijders Blok, N. A.M. van den Dungen, N. Lansu, B. J. Boukens, I. R. Efimov, M. Michels, M. C. Verhaar, R. de Weger, A. Vink, F. G. van Steenbeek, A. F. BaasR. P. Davis, H. W. Uh, D. W.D. Kuster, C. Cheng, M. Mokry, J. van der Velden, F. W. Asselbergs*, M. Harakalova

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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.

Original languageEnglish
Article number61
JournalClinical epigenetics
Volume13
Issue number1
DOIs
Publication statusPublished - Dec 2021

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