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Lipidomic profiling identifies signatures of metabolic risk

BACKGROUND: Metabolic syndrome (MetS), the clustering of metabolic risk factors, is associated with cardiovascular disease risk. We sought to determine if dysregulation of the lipidome may contribute to metabolic risk factors. METHODS: We measured 154 circulating lipid species in 658 participants fr...

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Detalles Bibliográficos
Autores principales: Yin, Xiaoyan, Willinger, Christine M., Keefe, Joshua, Liu, Jun, Fernández-Ortiz, Antonio, Ibáñez, Borja, Peñalvo, José, Adourian, Aram, Chen, George, Corella, Dolores, Pamplona, Reinald, Portero-Otin, Manuel, Jove, Mariona, Courchesne, Paul, van Duijn, Cornelia M., Fuster, Valentín, Ordovás, José M., Demirkan, Ayşe, Larson, Martin G., Levy, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6938899/
https://www.ncbi.nlm.nih.gov/pubmed/31877415
http://dx.doi.org/10.1016/j.ebiom.2019.10.046
Descripción
Sumario:BACKGROUND: Metabolic syndrome (MetS), the clustering of metabolic risk factors, is associated with cardiovascular disease risk. We sought to determine if dysregulation of the lipidome may contribute to metabolic risk factors. METHODS: We measured 154 circulating lipid species in 658 participants from the Framingham Heart Study (FHS) using liquid chromatography-tandem mass spectrometry and tested for associations with obesity, dysglycemia, and dyslipidemia. Independent external validation was sought in three independent cohorts. Follow-up data from the FHS were used to test for lipid metabolites associated with longitudinal changes in metabolic risk factors. RESULTS: Thirty-nine lipids were associated with obesity and eight with dysglycemia in the FHS. Of 32 lipids that were available for replication for obesity and six for dyslipidemia, 28 (88%) replicated for obesity and five (83%) for dysglycemia. Four lipids were associated with longitudinal changes in body mass index and four were associated with changes in fasting blood glucose in the FHS. CONCLUSIONS: We identified and replicated several novel lipid biomarkers of key metabolic traits. The lipid moieties identified in this study are involved in biological pathways of metabolic risk and can be explored for prognostic and therapeutic utility.