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The metabolomic profile associated with clustering of cardiovascular risk factors—A multi-sample evaluation

BACKGROUND: A clustering of cardiovascular risk factors is denoted the metabolic syndrome (MetS), but the mechanistic underpinnings of this clustering is not clear. Using large-scale metabolomics, we aimed to find a metabolic profile common for all five components of MetS. METHODS AND FINDINGS: 791...

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Autores principales: Lind, Lars, Sundström, Johan, Elmståhl, Sölve, Dekkers, Koen F., Smith, J. Gustav, Engström, Gunnar, Fall, Tove, Ärnlöv, Johan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9477278/
https://www.ncbi.nlm.nih.gov/pubmed/36107885
http://dx.doi.org/10.1371/journal.pone.0274701
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author Lind, Lars
Sundström, Johan
Elmståhl, Sölve
Dekkers, Koen F.
Smith, J. Gustav
Engström, Gunnar
Fall, Tove
Ärnlöv, Johan
author_facet Lind, Lars
Sundström, Johan
Elmståhl, Sölve
Dekkers, Koen F.
Smith, J. Gustav
Engström, Gunnar
Fall, Tove
Ärnlöv, Johan
author_sort Lind, Lars
collection PubMed
description BACKGROUND: A clustering of cardiovascular risk factors is denoted the metabolic syndrome (MetS), but the mechanistic underpinnings of this clustering is not clear. Using large-scale metabolomics, we aimed to find a metabolic profile common for all five components of MetS. METHODS AND FINDINGS: 791 annotated non-xenobiotic metabolites were measured by ultra-performance liquid chromatography tandem mass spectrometry in five different population-based samples (Discovery samples: EpiHealth, n = 2342 and SCAPIS-Uppsala, n = 4985. Replication sample: SCAPIS-Malmö, n = 3978, Characterization samples: PIVUS, n = 604 and POEM, n = 501). MetS was defined by the NCEP/consensus criteria. Fifteen metabolites were related to all five components of MetS (blood pressure, waist circumference, glucose, HDL-cholesterol and triglycerides) at a false discovery rate of <0.05 with adjustments for BMI and several life-style factors. They represented different metabolic classes, such as amino acids, simple carbohydrates, androgenic steroids, corticosteroids, co-factors and vitamins, ceramides, carnitines, fatty acids, phospholipids and metabolonic lactone sulfate. All 15 metabolites were related to insulin sensitivity (Matsuda index) in POEM, but only Palmitoyl-oleoyl-GPE (16:0/18:1), a glycerophospholipid, was related to incident cardiovascular disease over 8.6 years follow-up in the EpiHealth sample following adjustment for cardiovascular risk factors (HR 1.32 for a SD change, 95%CI 1.07–1.63). CONCLUSION: A complex metabolic profile was related to all cardiovascular risk factors included in MetS independently of BMI. This profile was also related to insulin sensitivity, which provide further support for the importance of insulin sensitivity as an important underlying mechanism in the clustering of cardiovascular risk factors.
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spelling pubmed-94772782022-09-16 The metabolomic profile associated with clustering of cardiovascular risk factors—A multi-sample evaluation Lind, Lars Sundström, Johan Elmståhl, Sölve Dekkers, Koen F. Smith, J. Gustav Engström, Gunnar Fall, Tove Ärnlöv, Johan PLoS One Research Article BACKGROUND: A clustering of cardiovascular risk factors is denoted the metabolic syndrome (MetS), but the mechanistic underpinnings of this clustering is not clear. Using large-scale metabolomics, we aimed to find a metabolic profile common for all five components of MetS. METHODS AND FINDINGS: 791 annotated non-xenobiotic metabolites were measured by ultra-performance liquid chromatography tandem mass spectrometry in five different population-based samples (Discovery samples: EpiHealth, n = 2342 and SCAPIS-Uppsala, n = 4985. Replication sample: SCAPIS-Malmö, n = 3978, Characterization samples: PIVUS, n = 604 and POEM, n = 501). MetS was defined by the NCEP/consensus criteria. Fifteen metabolites were related to all five components of MetS (blood pressure, waist circumference, glucose, HDL-cholesterol and triglycerides) at a false discovery rate of <0.05 with adjustments for BMI and several life-style factors. They represented different metabolic classes, such as amino acids, simple carbohydrates, androgenic steroids, corticosteroids, co-factors and vitamins, ceramides, carnitines, fatty acids, phospholipids and metabolonic lactone sulfate. All 15 metabolites were related to insulin sensitivity (Matsuda index) in POEM, but only Palmitoyl-oleoyl-GPE (16:0/18:1), a glycerophospholipid, was related to incident cardiovascular disease over 8.6 years follow-up in the EpiHealth sample following adjustment for cardiovascular risk factors (HR 1.32 for a SD change, 95%CI 1.07–1.63). CONCLUSION: A complex metabolic profile was related to all cardiovascular risk factors included in MetS independently of BMI. This profile was also related to insulin sensitivity, which provide further support for the importance of insulin sensitivity as an important underlying mechanism in the clustering of cardiovascular risk factors. Public Library of Science 2022-09-15 /pmc/articles/PMC9477278/ /pubmed/36107885 http://dx.doi.org/10.1371/journal.pone.0274701 Text en © 2022 Lind et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Lind, Lars
Sundström, Johan
Elmståhl, Sölve
Dekkers, Koen F.
Smith, J. Gustav
Engström, Gunnar
Fall, Tove
Ärnlöv, Johan
The metabolomic profile associated with clustering of cardiovascular risk factors—A multi-sample evaluation
title The metabolomic profile associated with clustering of cardiovascular risk factors—A multi-sample evaluation
title_full The metabolomic profile associated with clustering of cardiovascular risk factors—A multi-sample evaluation
title_fullStr The metabolomic profile associated with clustering of cardiovascular risk factors—A multi-sample evaluation
title_full_unstemmed The metabolomic profile associated with clustering of cardiovascular risk factors—A multi-sample evaluation
title_short The metabolomic profile associated with clustering of cardiovascular risk factors—A multi-sample evaluation
title_sort metabolomic profile associated with clustering of cardiovascular risk factors—a multi-sample evaluation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9477278/
https://www.ncbi.nlm.nih.gov/pubmed/36107885
http://dx.doi.org/10.1371/journal.pone.0274701
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