Multi-Omic Architecture of Obstructive Hypertrophic Cardiomyopathy

被引:14
|
作者
Garmany, Ramin [2 ,3 ]
Bos, J. Martijn [3 ,4 ,5 ]
Tester, David J. [3 ]
Giudicessi, John R. [4 ]
dos Remedios, Cristobal G. [10 ]
Dasari, Surendra [6 ]
Nagaraj, Nagaswaroop K. [6 ]
Nair, Asha A. [6 ]
Johnson, Kenneth L. [7 ]
Ryan, Zachary C. [7 ]
Maleszewski, Joseph J. [4 ,8 ]
Ommen, Steve R. [4 ]
Dearani, Joseph A. [9 ]
Ackerman, Michael J. [1 ,3 ,4 ,5 ]
机构
[1] Mayo Clin, Mayo Clin Windland Smith Rice Genet Heart Rhythm C, Windland Smith Rice Sudden Death Genom Lab, Guggenheim 501,200 First St SW, Rochester, MN 55905 USA
[2] Mayo Clin, Mayo Clin Grad Sch Biomed Sci, Mayo Clin Med Scientist Training Program, Alix Sch Med, Rochester, MN USA
[3] Windland Smith Rice Sudden Death Genom Lab, Dept Mol Pharmacol & Expt Therapeut, Rochester, MN USA
[4] Windland Smith Rice Genet Heart Rhythm Clin, Dept Cardiovasc Med, Rochester, MN USA
[5] Windland Smith Rice Genet Heart Rhythm Clin, Dept Pediat & Adolescent Med, Div Pediat Cardiol, Rochester, MN USA
[6] Mayo Clin, Dept Quantitat Hlth Sci, Div Computat Biol, Rochester, MN USA
[7] Mayo Clin, Prote Core, Rochester, MN USA
[8] Mayo Clin, Dept Lab Med & Pathol, Rochester, MN USA
[9] Mayo Clin, Dept Cardiovasc Surg, Rochester, MN USA
[10] Victor Chang Cardiac Res Inst, Mechanobiol Lab, Darlinghurst, Australia
来源
关键词
cardiomyopathy; hypertrophic; gene expression profiling; genotype; humans; proteomics; TRANSGENIC RABBIT MODEL; CARDIAC-HYPERTROPHY; KAPPA-B; PACKAGE; DISEASE; ACTIVATION; RESOLUTION; INSIGHTS; FIBROSIS; RNA;
D O I
10.1161/CIRCGEN.122.003756
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background: Hypertrophic cardiomyopathy (HCM) is characterized by asymmetric left ventricular hypertrophy. Currently, hypertrophy pathways responsible for HCM have not been fully elucidated. Their identification could serve as a nidus for the generation of novel therapeutics aimed at halting disease development or progression. Herein, we performed a comprehensive multi-omic characterization of hypertrophy pathways in HCM.Methods: Flash-frozen cardiac tissues were collected from genotyped HCM patients (n=97) undergoing surgical myectomy and tissue from 23 controls. RNA sequencing and mass spectrometry-enabled deep proteome and phosphoproteomic assessment were performed. Rigorous differential expression, gene set enrichment, and pathway analyses were performed to characterize HCM-mediated alterations with emphasis on hypertrophy pathways.Results: We identified transcriptional dysregulation with 1246 (8%) differentially expressed genes and elucidated downregulation of 10 hypertrophy pathways. Deep proteomic analysis identified 411 proteins (9%) that differed between HCM and controls with strong dysregulation of metabolic pathways. Seven hypertrophy pathways were upregulated with antagonistic upregulation of 5 of 10 hypertrophy pathways shown to be downregulated in the transcriptome. Most upregulated hypertrophy pathways encompassed the rat sarcoma-mitogen-activated protein kinase signaling cascade. Phosphoproteomic analysis demonstrated hyperphosphorylation of the rat sarcoma-mitogen-activated protein kinase system suggesting activation of this signaling cascade. There was a common transcriptomic and proteomic profile regardless of genotype.Conclusions: At time of surgical myectomy, the ventricular proteome, independent of genotype, reveals widespread upregulation and activation of hypertrophy pathways, mainly involving the rat sarcoma-mitogen-activated protein kinase signaling cascade. In addition, there is a counterregulatory transcriptional downregulation of the same pathways. Rat sarcoma-mitogen-activated protein kinase activation may serve a crucial role in hypertrophy observed in HCM.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] Diploid genome architecture revealed by multi-omic data of hybrid mice
    Han, Zhijun
    Cui, Kairong
    Placek, Katarzyna
    Hong, Ni
    Lin, Chengqi
    Chen, Wei
    Zhao, Keji
    Jin, Wenfei
    GENOME RESEARCH, 2020, 30 (08) : 1097 - 1106
  • [2] MONET: Multi-omic module discovery by omic selection
    Rappoport, Nimrod
    Safra, Roy
    Shamir, Ron
    PLOS COMPUTATIONAL BIOLOGY, 2020, 16 (09)
  • [3] Genetic prediction of multi-omic traits
    Koch, Linda
    NATURE REVIEWS GENETICS, 2023, 24 (06) : 346 - 346
  • [4] Multi-omic studies on the pathogenesis of Sepsis
    Tong, Hongjie
    Zhao, Yuhang
    Cui, Ying
    Yao, Jiali
    Zhang, Tianlong
    JOURNAL OF TRANSLATIONAL MEDICINE, 2025, 23 (01)
  • [5] A multi-omic future for microbiome studies
    Janet K. Jansson
    Erin S. Baker
    Nature Microbiology, 1 (5)
  • [6] A multi-omic resource of mouse neutrophils
    Neff, Ellen P.
    LAB ANIMAL, 2021, 50 (09) : 239 - 239
  • [7] Multi-omic network signatures of disease
    Gibbs, David L.
    Gralinski, Lisa
    Baric, Ralph S.
    McWeeney, Shannon K.
    FRONTIERS IN GENETICS, 2014, 4
  • [8] Editorial: Multi-omic data integration
    Nardini, Christine
    Dent, Jennifer
    Tieri, Paolo
    FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY, 2015, 3
  • [9] A multi-omic future for microbiome studies
    Jansson, Janet K.
    Baker, Erin S.
    NATURE MICROBIOLOGY, 2016, 1 (05)
  • [10] Cardiotoxicity of Chemotherapy: A Multi-OMIC Perspective
    Ma, Yan
    Grootaert, Mandy O. J.
    Sewduth, Raj N.
    JOURNAL OF XENOBIOTICS, 2025, 15 (01)