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

• Published in: EBioMedicine Vol. 69; p. 103440
• Main Authors: Comte, Blandine, Monnerie, Stéphanie, Brandolini-Bunlon, Marion, Canlet, Cécile, Castelli, Florence, Chu-Van, Emeline, Colsch, Benoit, Fenaille, François, Joly, Charlotte, Jourdan, Fabien, Lenuzza, Natacha, Lyan, Bernard, Martin, Jean-François, Migné, Carole, Morais, José A., Pétéra, Mélanie, Poupin, Nathalie, Vinson, Florence, Thevenot, Etienne, Junot, Christophe, Gaudreau, Pierrette, Pujos-Guillot, Estelle
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.07.2021; Elsevier
• Subjects: Deep phenotyping; Food and Nutrition; Human health and pathology; Life Sciences; Lipidomics; Metabolic signature; Metabolic syndrome; Metabolomics; Quantitative Methods; Research Paper; Metabolic signature; Metabolomics; Deep phenotyping; Lipidomics; Metabolic syndrome
• ISSN: 2352-3964; 2352-3964
• DOI: 10.1016/j.ebiom.2021.103440

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. 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. 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, sphingo- and glycerophospholipid, and sugar metabolisms…) not only intrinsically interrelated, but also reflecting environmental factors (nutrition, microbiota, physical activity…). These findings allowed identifying a comprehensive MetS signature, reduced to 26 metabolites for future translation into clinical applications for better diagnosing MetS. The NuAge Study was supported by a research grant from the Canadian Institutes of Health Research (CIHR; MOP-62842). The actual NuAge Database and Biobank, containing data and biologic samples of 1,753 NuAge participants (from the initial 1,793 participants), are supported by the Fonds de recherche du Québec (FRQ; 2020-VICO-279753), the Quebec Network for Research on Aging, a thematic network funded by the Fonds de Recherche du Québec - Santé (FRQS) and by the Merck-Frost Chair funded by La Fondation de l'Université de Sherbrooke. All metabolomics and lipidomics analyses were funded and performed within the metaboHUB French infrastructure (ANR-INBS-0010). All authors had full access to the full data in the study and accept responsibility to submit for publication.