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Metabolomic and lipidomic assessment of the metabolic syndrome in Dutch middle-aged individuals reveals novel biological signatures separating health and disease
BACKGROUND: We aimed to identify novel metabolite and lipid signatures connected with the metabolic syndrome in a Dutch middle-aged population. METHODS: 115 individuals with a metabolic syndrome score ranging from 0 to 5 [50 cases of the metabolic syndrome (score ≥ 3) and 65 controls] were enrolled...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6373335/ https://www.ncbi.nlm.nih.gov/pubmed/30830468 http://dx.doi.org/10.1007/s11306-019-1484-7 |
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author | Surowiec, Izabella Noordam, Raymond Bennett, Kate Beekman, Marian Slagboom, P. Eline Lundstedt, Torbjörn van Heemst, Diana |
author_facet | Surowiec, Izabella Noordam, Raymond Bennett, Kate Beekman, Marian Slagboom, P. Eline Lundstedt, Torbjörn van Heemst, Diana |
author_sort | Surowiec, Izabella |
collection | PubMed |
description | BACKGROUND: We aimed to identify novel metabolite and lipid signatures connected with the metabolic syndrome in a Dutch middle-aged population. METHODS: 115 individuals with a metabolic syndrome score ranging from 0 to 5 [50 cases of the metabolic syndrome (score ≥ 3) and 65 controls] were enrolled from the Leiden Longevity Study, and LC/GC–MS metabolomics and lipidomics profiling were performed on fasting plasma samples. Data were analysed with principal component analysis and orthogonal projections to latent structures (OPLS) to study metabolite/lipid signatures associated with the metabolic syndrome. In addition, univariate analyses were done with linear regression, adjusted for age and sex, for the study of individual metabolites/lipids in relation to the metabolic syndrome. RESULTS: Data was available on 103 metabolites and 223 lipids. In the OPLS model with metabolic syndrome score (Y-variable), 9 metabolites were negatively correlated and 26 metabolites (mostly acylcarnitines, amino acids and keto acids) were positively correlated with the metabolic syndrome score. In addition, a total of 100 lipids (mainly triacylglycerides) were positively correlated and 10 lipids from different lipid classes were negatively correlated with the metabolic syndrome score. In the univariate analyses, the metabolic syndrome (score) was associated with multiple individual metabolites (e.g., valeryl carnitine, pyruvic acid, lactic acid, alanine) and lipids [e.g., diglyceride(34:1), diglyceride(36:2)]. CONCLUSION: In this first study on metabolomics/lipidomics of the metabolic syndrome, we identified multiple novel metabolite and lipid signatures, from different chemical classes, that were connected to the metabolic syndrome and are of interest to cardiometabolic disease biology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11306-019-1484-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6373335 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-63733352019-03-15 Metabolomic and lipidomic assessment of the metabolic syndrome in Dutch middle-aged individuals reveals novel biological signatures separating health and disease Surowiec, Izabella Noordam, Raymond Bennett, Kate Beekman, Marian Slagboom, P. Eline Lundstedt, Torbjörn van Heemst, Diana Metabolomics Original Article BACKGROUND: We aimed to identify novel metabolite and lipid signatures connected with the metabolic syndrome in a Dutch middle-aged population. METHODS: 115 individuals with a metabolic syndrome score ranging from 0 to 5 [50 cases of the metabolic syndrome (score ≥ 3) and 65 controls] were enrolled from the Leiden Longevity Study, and LC/GC–MS metabolomics and lipidomics profiling were performed on fasting plasma samples. Data were analysed with principal component analysis and orthogonal projections to latent structures (OPLS) to study metabolite/lipid signatures associated with the metabolic syndrome. In addition, univariate analyses were done with linear regression, adjusted for age and sex, for the study of individual metabolites/lipids in relation to the metabolic syndrome. RESULTS: Data was available on 103 metabolites and 223 lipids. In the OPLS model with metabolic syndrome score (Y-variable), 9 metabolites were negatively correlated and 26 metabolites (mostly acylcarnitines, amino acids and keto acids) were positively correlated with the metabolic syndrome score. In addition, a total of 100 lipids (mainly triacylglycerides) were positively correlated and 10 lipids from different lipid classes were negatively correlated with the metabolic syndrome score. In the univariate analyses, the metabolic syndrome (score) was associated with multiple individual metabolites (e.g., valeryl carnitine, pyruvic acid, lactic acid, alanine) and lipids [e.g., diglyceride(34:1), diglyceride(36:2)]. CONCLUSION: In this first study on metabolomics/lipidomics of the metabolic syndrome, we identified multiple novel metabolite and lipid signatures, from different chemical classes, that were connected to the metabolic syndrome and are of interest to cardiometabolic disease biology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11306-019-1484-7) contains supplementary material, which is available to authorized users. Springer US 2019-02-12 2019 /pmc/articles/PMC6373335/ /pubmed/30830468 http://dx.doi.org/10.1007/s11306-019-1484-7 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Article Surowiec, Izabella Noordam, Raymond Bennett, Kate Beekman, Marian Slagboom, P. Eline Lundstedt, Torbjörn van Heemst, Diana Metabolomic and lipidomic assessment of the metabolic syndrome in Dutch middle-aged individuals reveals novel biological signatures separating health and disease |
title | Metabolomic and lipidomic assessment of the metabolic syndrome in Dutch middle-aged individuals reveals novel biological signatures separating health and disease |
title_full | Metabolomic and lipidomic assessment of the metabolic syndrome in Dutch middle-aged individuals reveals novel biological signatures separating health and disease |
title_fullStr | Metabolomic and lipidomic assessment of the metabolic syndrome in Dutch middle-aged individuals reveals novel biological signatures separating health and disease |
title_full_unstemmed | Metabolomic and lipidomic assessment of the metabolic syndrome in Dutch middle-aged individuals reveals novel biological signatures separating health and disease |
title_short | Metabolomic and lipidomic assessment of the metabolic syndrome in Dutch middle-aged individuals reveals novel biological signatures separating health and disease |
title_sort | metabolomic and lipidomic assessment of the metabolic syndrome in dutch middle-aged individuals reveals novel biological signatures separating health and disease |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6373335/ https://www.ncbi.nlm.nih.gov/pubmed/30830468 http://dx.doi.org/10.1007/s11306-019-1484-7 |
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