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 from...
| Main Authors: | , , , , , , , , , , , , , , , , , , , |
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| Formato: | Journal article |
| Idioma: | English |
| Publicado: |
Elsevier
2019
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| _version_ | 1826307170572959744 |
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| author | Yin, X Willinger, CM Keefe, J Liu, J Fernández-Ortiz, A Ibáñez, B Peñalvo, J Adourian, A Chen, G Corella, D Pamplona, R Portero-Otin, M Jove, M Courchesne, P Van Duijn, CM Fuster, V Ordovás, JM Demirkan, A Larson, MG Levy, D |
| author_facet | Yin, X Willinger, CM Keefe, J Liu, J Fernández-Ortiz, A Ibáñez, B Peñalvo, J Adourian, A Chen, G Corella, D Pamplona, R Portero-Otin, M Jove, M Courchesne, P Van Duijn, CM Fuster, V Ordovás, JM Demirkan, A Larson, MG Levy, D |
| author_sort | Yin, X |
| collection | OXFORD |
| 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. |
| first_indexed | 2024-03-07T06:58:55Z |
| format | Journal article |
| id | oxford-uuid:ff12f2c9-8f8c-4d5e-8f9f-f7d05938e636 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T06:58:55Z |
| publishDate | 2019 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | oxford-uuid:ff12f2c9-8f8c-4d5e-8f9f-f7d05938e6362022-03-27T13:41:48ZLipidomic profiling identifies signatures of metabolic riskJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:ff12f2c9-8f8c-4d5e-8f9f-f7d05938e636EnglishSymplectic Elements at OxfordElsevier2019Yin, XWillinger, CMKeefe, JLiu, JFernández-Ortiz, AIbáñez, BPeñalvo, JAdourian, AChen, GCorella, DPamplona, RPortero-Otin, MJove, MCourchesne, PVan Duijn, CMFuster, VOrdovás, JMDemirkan, ALarson, MGLevy, DBACKGROUND: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. |
| spellingShingle | Yin, X Willinger, CM Keefe, J Liu, J Fernández-Ortiz, A Ibáñez, B Peñalvo, J Adourian, A Chen, G Corella, D Pamplona, R Portero-Otin, M Jove, M Courchesne, P Van Duijn, CM Fuster, V Ordovás, JM Demirkan, A Larson, MG Levy, D 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 |
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