2026-06-14T10:38:25Zhttps://repisalud.isciii.es/rest/oai/request
oai:repisalud.isciii.es:20.500.12105/92872024-09-27T09:34:22Zcom_20.500.12105_19604com_20.500.12105_2051col_20.500.12105_19605
Repisalud author Yin, Xiaoyan author Willinger, Christine M author Keefe, Joshua author Liu, Jun author Fernandez-Ortiz, Antonio author Ibáñez, Borja author Peñalvo, Jose L author Adourian, Aram author Chen, George author Corella, Dolores author Pamplona, Reinald author Portero-Otin, Manuel author Jove, Mariona author Courchesne, Paul author van Duijn, Cornelia M author Fuster, Valentin author Ordovas, Jose M author Demirkan, Ayşe author Larson, Martin G author Levy, Daniel funder National Institutes of Health (Estados Unidos) funder NIH - National Heart, Lung, and Blood Institute (NHLBI) (Estados Unidos) funder Centro Nacional de Investigaciones Cardiovasculares Carlos III (España) funder Banco Santander funder Instituto de Salud Carlos III funder Fundación ProCNIC funder Ministerio de Ciencia, Innovación y Universidades (España) funder AstraZeneca funder United States Department of Agriculture funder Ministerio de Economía y Competitividad (España) funder Unión Europea. Fondo Europeo de Desarrollo Regional (FEDER/ERDF) funder Government of Catalonia (España) 2020-03-19T11:33:12Z 2020-03-19T11:33:12Z 2020-01 EBioMedicine. 2020; 51:102520 10.1016/j.ebiom.2019.10.046 2352-3964 23523964 EBioMedicine 31877415 http://hdl.handle.net/20.500.12105/9287 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. eng Biomarker Cardiovascular disease Dysglycemia Dyslipidemia Metabolic risk Metabolic syndrome Lipidomic profiling identifies signatures of metabolic risk journal article 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 URL https://repisalud.isciii.es/bitstreams/bf71d8ad-8147-46ca-a722-e9c9eb14eed1/download File MD5 18aaef4f5e207b8763dc55755a5b3ed6 596467 application/pdf LipidomicProfilingIdentifiesSignatures_2020.pdf URL https://repisalud.isciii.es/bitstreams/0a88686a-0128-4001-9d65-2fcb784810a5/download File MD5 42f4e639b293fc6191a9aea1057107f9 1051548 application/pdf LipidomicProfilingIdentifiesSignatures_2020_SupplMat.pdf URL https://repisalud.isciii.es/bitstreams/bab08340-303c-4e89-aad7-2fa33190b3a7/download File MD5 a6d95f86cc293366f711fbbc79581e12 60972 text/plain LipidomicProfilingIdentifiesSignatures_2020.pdf.txt URL https://repisalud.isciii.es/bitstreams/1988755b-c305-49b1-be44-5b40ef3d365d/download File MD5 16f06db7960eaf42a30efc3c4519059b 28779 text/plain LipidomicProfilingIdentifiesSignatures_2020_SupplMat.pdf.txt