4.7 Article

Multiplatform metabolomics for an integrative exploration of metabolic syndrome in older men

Journal

EBIOMEDICINE
Volume 69, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.ebiom.2021.103440

Keywords

Metabolic syndrome; Metabolomics; Deep phenotyping; Lipidomics; Metabolic signature

Funding

  1. Canadian Institutes of Health Research (CIHR) [MOP-62842]
  2. Fonds de recherche du Quebec (FRQ) [2020-VICO-279753]
  3. Quebec Network for Research on Aging, a thematic network - Fonds de Recherche du Quebec Sante (FRQS)
  4. Merck-Frost Chair - La Fondation de l'Universite de Sherbrooke
  5. MetaboHUB French infrastructure [ANR-INBS-0010]

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The study used a multiplatform metabolomics and lipidomics untargeted strategy to characterize metabolic perturbations in MetS, identifying significant changes and defining a comprehensive MetS signature for future clinical applications. This approach provides insights into the systemic alterations of metabolism in MetS, contributing to better diagnostic methods for the syndrome.
Background: Metabolic syndrome (MetS), a cluster of factors associated with risks of developing cardiovascular diseases, is a public health concern because of its growing prevalence. Considering the combination of concomitant components, their development and severity, MetS phenotypes are largely heterogeneous, inducing disparity in diagnosis. Methods: A case/control study was designed within the NuAge longitudinal cohort on aging. From a 3-year follow-up of 123 stable individuals, we present a deep phenotyping approach based on a multiplatform metabolomics and lipidomics untargeted strategy to better characterize metabolic perturbations in MetS and define a comprehensive MetS signature stable over time in older men. Findings: We characterize significant changes associated with MetS, involving modulations of 476 metabolites and lipids, and representing 16% of the detected serum metabolome/lipidome. These results revealed a systemic alteration of metabolism, involving various metabolic pathways (urea cycle, amino-acid, sphingoand glycerophospholipid, and sugar metabolisms...) not only intrinsically interrelated, but also reflecting environmental factors (nutrition, microbiota, physical activity...). Interpretation: These findings allowed identifying a comprehensive MetS signature, reduced to 26 metabolites for future translation into clinical applications for better diagnosing MetS. All authors had full access to the full data in the study and accept responsibility to submit for publication. (C) 2021 The Author(s). Published by Elsevier B.V.

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