The Plasma Oxylipin Signature Provides a Deep Phenotyping of Metabolic Syndrome Complementary to the Clinical Criteria
C. Dalle, Jérémy Tournayre, Malwina Mainka, Alicja Basiak-Rasała, Mélanie Pétéra, Sophie Lefèvre‐Arbogast, Jessica Dalloux-Chioccioli, Mélanie Deschasaux, Lucie Lécuyer, Emmanuelle Kesse‐Guyot, Léopold Fezeu, Serge Herçberg, Pilar Galán, Cécilia Samieri, Katarzyna Zatońska, Philip C. Calder, Mads F. Hjorth, Arne Astrup, Andrzej Mazur, Justine Bertrand‐Michel, Nils Helge Schebb, Andrzej Szuba, Mathilde Touvier, John W. Newman, Cécile Gladine
Abstract
Metabolic syndrome (MetS) is a complex condition encompassing a constellation of cardiometabolic abnormalities. Oxylipins are a superfamily of lipid mediators regulating many cardiometabolic functions. Plasma oxylipin signature could provide a new clinical tool to enhance the phenotyping of MetS pathophysiology. A high-throughput validated mass spectrometry method, allowing for the quantitative profiling of over 130 oxylipins, was applied to identify and validate the oxylipin signature of MetS in two independent nested case/control studies involving 476 participants. We identified an oxylipin signature of MetS (coined OxyScore), including 23 oxylipins and having high performances in classification and replicability (cross-validated AUCROC of 89%, 95% CI: 85–93% and 78%, 95% CI: 72–85% in the Discovery and Replication studies, respectively). Correlation analysis and comparison with a classification model incorporating the MetS criteria showed that the oxylipin signature brings consistent and complementary information to the clinical criteria. Being linked with the regulation of various biological processes, the candidate oxylipins provide an integrative phenotyping of MetS regarding the activation and/or negative feedback regulation of crucial molecular pathways. This may help identify patients at higher risk of cardiometabolic diseases. The oxylipin signature of patients with metabolic syndrome enhances MetS phenotyping and may ultimately help to better stratify the risk of cardiometabolic diseases.