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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...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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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 |
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author | 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 |
author_facet | 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 |
author_sort | Yin, Xiaoyan |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6938899 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-69388992020-01-06 Lipidomic profiling identifies signatures of metabolic risk 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 EBioMedicine Research paper 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. Elsevier 2019-12-24 /pmc/articles/PMC6938899/ /pubmed/31877415 http://dx.doi.org/10.1016/j.ebiom.2019.10.046 Text en Published by Elsevier B.V. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research paper 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 Lipidomic profiling identifies signatures of metabolic risk |
title | Lipidomic profiling identifies signatures of metabolic risk |
title_full | Lipidomic profiling identifies signatures of metabolic risk |
title_fullStr | Lipidomic profiling identifies signatures of metabolic risk |
title_full_unstemmed | Lipidomic profiling identifies signatures of metabolic risk |
title_short | Lipidomic profiling identifies signatures of metabolic risk |
title_sort | lipidomic profiling identifies signatures of metabolic risk |
topic | Research paper |
url | 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 |
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