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Individualized interactomes for network-based precision medicine in hypertrophic cardiomyopathy with implications for other clinical pathophenotypes

Author

Listed:
  • Bradley A. Maron

    (Brigham and Women’s Hospital and Harvard Medical School)

  • Rui-Sheng Wang

    (Brigham and Women’s Hospital and Harvard Medical School
    Brigham and Women’s Hospital and Harvard Medical School)

  • Sergei Shevtsov

    (Brigham and Women’s Hospital and Harvard Medical School)

  • Stavros G. Drakos

    (University of Utah School of Medicine
    University of Utah School of Medicine)

  • Elena Arons

    (Brigham and Women’s Hospital and Harvard Medical School)

  • Omar Wever-Pinzon

    (University of Utah School of Medicine)

  • Gordon S. Huggins

    (Tufts Medical Center)

  • Andriy O. Samokhin

    (Brigham and Women’s Hospital and Harvard Medical School)

  • William M. Oldham

    (Brigham and Women’s Hospital and Harvard Medical School)

  • Yasmine Aguib

    (Imperial College of London
    The Magdi Yacoub Heart Center)

  • Magdi H. Yacoub

    (Imperial College of London
    The Magdi Yacoub Heart Center)

  • Ethan J. Rowin

    (Tufts Medical Center)

  • Barry J. Maron

    (Tufts Medical Center)

  • Martin S. Maron

    (Tufts Medical Center)

  • Joseph Loscalzo

    (Brigham and Women’s Hospital and Harvard Medical School
    Brigham and Women’s Hospital and Harvard Medical School)

Abstract

Progress in precision medicine is limited by insufficient knowledge of transcriptomic or proteomic features in involved tissues that define pathobiological differences between patients. Here, myectomy tissue from patients with obstructive hypertrophic cardiomyopathy and heart failure is analyzed using RNA-Seq, and the results are used to develop individualized protein-protein interaction networks. From this approach, hypertrophic cardiomyopathy is distinguished from dilated cardiomyopathy based on the protein-protein interaction network pattern. Within the hypertrophic cardiomyopathy cohort, the patient-specific networks are variable in complexity, and enriched for 30 endophenotypes. The cardiac Janus kinase 2-Signal Transducer and Activator of Transcription 3-collagen 4A2 (JAK2-STAT3-COL4A2) expression profile informed by the networks was able to discriminate two hypertrophic cardiomyopathy patients with extreme fibrosis phenotypes. Patient-specific network features also associate with other important hypertrophic cardiomyopathy clinical phenotypes. These proof-of-concept findings introduce personalized protein-protein interaction networks (reticulotypes) for characterizing patient-specific pathobiology, thereby offering a direct strategy for advancing precision medicine.

Suggested Citation

  • Bradley A. Maron & Rui-Sheng Wang & Sergei Shevtsov & Stavros G. Drakos & Elena Arons & Omar Wever-Pinzon & Gordon S. Huggins & Andriy O. Samokhin & William M. Oldham & Yasmine Aguib & Magdi H. Yacoub, 2021. "Individualized interactomes for network-based precision medicine in hypertrophic cardiomyopathy with implications for other clinical pathophenotypes," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-21146-y
    DOI: 10.1038/s41467-021-21146-y
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    Cited by:

    1. Sepideh Sadegh & James Skelton & Elisa Anastasi & Andreas Maier & Klaudia Adamowicz & Anna Möller & Nils M. Kriege & Jaanika Kronberg & Toomas Haller & Tim Kacprowski & Anil Wipat & Jan Baumbach & Dav, 2023. "Lacking mechanistic disease definitions and corresponding association data hamper progress in network medicine and beyond," Nature Communications, Nature, vol. 14(1), pages 1-15, December.

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