Literature DB >> 33507147

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

Amit Frishberg1, Inge van den Munckhof2, Niels P Riksen2, Irit Gat-Viks1, Rob Ter Horst2, Kiki Schraa2, Leo Ab Joosten2, Joost Hw Rutten2, Adrian C Iancu3, Ioana M Dregoesc3, Bogdan A Tigu4,5, Mihai G Netea2,6.   

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. low free cholesterol in small high-density lipoproteins) and attenuated cytokine responses of immune cells 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.
© 2021, Frishberg et al.

Entities:  

Keywords:  cardiometabolic disease; computational biology; computational modeling; human; medicine; metabolic syndrome; multi-omics data; phenotypic states; systems biology

Mesh:

Year:  2021        PMID: 33507147      PMCID: PMC7906604          DOI: 10.7554/eLife.61710

Source DB:  PubMed          Journal:  Elife        ISSN: 2050-084X            Impact factor:   8.140


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