An integrative model of cardiometabolic traits identifies two types of metabolic syndrome

  1. Amit Frishberg
  2. Inge van den Munckhof
  3. Rob ter Horst
  4. Kiki Schraa
  5. Leo AB Joosten
  6. Joost HW Rutten
  7. Adrian C Iancu
  8. Ioana M Dregoesc
  9. Bogdan A Tigu
  10. Mihai G Netea
  11. Niels Peter Riksen  Is a corresponding author
  12. Irit Gat-Viks  Is a corresponding author
  1. Tel Aviv University, Israel
  2. Radboud University Medical Center, Netherlands
  3. University of Medicine and Pharmacy, Romania

Abstract

Human diseases arise in a complex ecosystem composed of disease mechanisms and the whole-body state. However, the precise nature of the whole-body state and its relations with disease remain obscure. Here we map similarities among clinical parameters in normal physiological settings, including a large collection of metabolic, hemodynamic and immune parameters, and then use the mapping to dissect phenotypic states. We find that the whole-body state is faithfully represented by a quantitative two-dimensional model. One component of the whole-body state represents 'metabolic syndrome' (MetS) – a conventional way to determine the cardiometabolic state. The second component is decoupled from the classical MetS, suggesting a novel 'non-classical MetS' that is characterized by dozens of parameters, including dysregulated lipoprotein parameters (e.g. high LDL- cholesterol and low free cholesterol in small HDL particles) and attenuated cytokine responses of PBMCs to ex vivo stimulations. Both components are associated with disease, but differ in their particular associations, thus opening new avenues for improved personalized diagnosis and treatment. These results provide a practical paradigm to describe whole-body states and to dissect complex disease within the ecosystem of the human body.

Data availability

Both the obesity cohort and the normal BMI cohort were part of the Human Functional Genomics Project (www.humanfunctionalgenomics.org) and has been previously published.The coronary-atherosclerosis cohort was collected as part of the HORIZON 2020 European Research Program - "REPROGRAM: Targeting epigenetic REPROGRamming of innate immune cells in Atherosclerosis Management and other chronic inflammatory diseases".SLE sequencing public datasets used in our analysis: GSE65391, GSE49454.

Article and author information

Author details

  1. Amit Frishberg

    Life Sciences, Tel Aviv University, Tel-Aviv, Israel
    Competing interests
    The authors declare that no competing interests exist.
  2. Inge van den Munckhof

    Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  3. Rob ter Horst

    Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  4. Kiki Schraa

    Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  5. Leo AB Joosten

    Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6166-9830
  6. Joost HW Rutten

    Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  7. Adrian C Iancu

    Department of Cardiology, University of Medicine and Pharmacy, Cluj-Napoca, Romania
    Competing interests
    The authors declare that no competing interests exist.
  8. Ioana M Dregoesc

    Department of Cardiology, University of Medicine and Pharmacy, Cluj-Napoca, Romania
    Competing interests
    The authors declare that no competing interests exist.
  9. Bogdan A Tigu

    Department of Cardiology, University of Medicine and Pharmacy, Cluj-Napoca, Romania
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9397-0791
  10. Mihai G Netea

    Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  11. Niels Peter Riksen

    Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands
    For correspondence
    niels.riksen@radboudumc.nl
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9197-8124
  12. Irit Gat-Viks

    Life Sciences, Tel Aviv University, Tel-Aviv, Israel
    For correspondence
    iritgv@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5431-6444

Funding

European Commission (637885)

  • Amit Frishberg
  • Irit Gat-Viks

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Edward D Janus, University of Melbourne, Australia

Version history

  1. Received: August 2, 2020
  2. Accepted: January 27, 2021
  3. Accepted Manuscript published: January 28, 2021 (version 1)
  4. Version of Record published: February 25, 2021 (version 2)

Copyright

© 2021, Frishberg et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Amit Frishberg
  2. Inge van den Munckhof
  3. Rob ter Horst
  4. Kiki Schraa
  5. Leo AB Joosten
  6. Joost HW Rutten
  7. Adrian C Iancu
  8. Ioana M Dregoesc
  9. Bogdan A Tigu
  10. Mihai G Netea
  11. Niels Peter Riksen
  12. Irit Gat-Viks
(2021)
An integrative model of cardiometabolic traits identifies two types of metabolic syndrome
eLife 10:e61710.
https://doi.org/10.7554/eLife.61710

Share this article

https://doi.org/10.7554/eLife.61710

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