Body fat free mass is associated with the serum metabolite profile in a population-based study.

<h4>Objective</h4>To characterise the influence of the fat free mass on the metabolite profile in serum samples from participants of the population-based KORA (Cooperative Health Research in the Region of Augsburg) S4 study.<h4>Subjects and methods</h4>Analyses were based on...

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Autores principales: Carolin Jourdan, Ann-Kristin Petersen, Christian Gieger, Angela Döring, Thomas Illig, Rui Wang-Sattler, Christa Meisinger, Annette Peters, Jerzy Adamski, Cornelia Prehn, Karsten Suhre, Elisabeth Altmaier, Gabi Kastenmüller, Werner Römisch-Margl, Fabian J Theis, Jan Krumsiek, H-Erich Wichmann, Jakob Linseisen
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Publicado: Public Library of Science (PLoS) 2012
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spelling oai:doaj.org-article:37bdaf6b0f1d448987062f75c622eb552021-11-18T07:14:10ZBody fat free mass is associated with the serum metabolite profile in a population-based study.1932-620310.1371/journal.pone.0040009https://doaj.org/article/37bdaf6b0f1d448987062f75c622eb552012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22761945/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Objective</h4>To characterise the influence of the fat free mass on the metabolite profile in serum samples from participants of the population-based KORA (Cooperative Health Research in the Region of Augsburg) S4 study.<h4>Subjects and methods</h4>Analyses were based on metabolite profile from 965 participants of the S4 and 890 weight-stable subjects of its seven-year follow-up study (KORA F4). 190 different serum metabolites were quantified in a targeted approach including amino acids, acylcarnitines, phosphatidylcholines (PCs), sphingomyelins and hexose. Associations between metabolite concentrations and the fat free mass index (FFMI) were analysed using adjusted linear regression models. To draw conclusions on enzymatic reactions, intra-metabolite class ratios were explored. Pairwise relationships among metabolites were investigated and illustrated by means of Gaussian graphical models (GGMs).<h4>Results</h4>We found 339 significant associations between FFMI and various metabolites in KORA S4. Among the most prominent associations (p-values 4.75 × 10(-16)-8.95 × 10(-06)) with higher FFMI were increasing concentrations of the branched chained amino acids (BCAAs), ratios of BCAAs to glucogenic amino acids, and carnitine concentrations. For various PCs, a decrease in chain length or in saturation of the fatty acid moieties could be observed with increasing FFMI, as well as an overall shift from acyl-alkyl PCs to diacyl PCs. These findings were reproduced in KORA F4. The established GGMs supported the regression results and provided a comprehensive picture of the relationships between metabolites. In a sub-analysis, most of the discovered associations did not exist in obese subjects in contrast to non-obese subjects, possibly indicating derangements in skeletal muscle metabolism.<h4>Conclusion</h4>A set of serum metabolites strongly associated with FFMI was identified and a network explaining the relationships among metabolites was established. These results offer a novel and more complete picture of the FFMI effects on serum metabolites in a data-driven network.Carolin JourdanAnn-Kristin PetersenChristian GiegerAngela DöringThomas IlligRui Wang-SattlerChrista MeisingerAnnette PetersJerzy AdamskiCornelia PrehnKarsten SuhreElisabeth AltmaierGabi KastenmüllerWerner Römisch-MarglFabian J TheisJan KrumsiekH-Erich WichmannJakob LinseisenPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 6, p e40009 (2012)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Carolin Jourdan
Ann-Kristin Petersen
Christian Gieger
Angela Döring
Thomas Illig
Rui Wang-Sattler
Christa Meisinger
Annette Peters
Jerzy Adamski
Cornelia Prehn
Karsten Suhre
Elisabeth Altmaier
Gabi Kastenmüller
Werner Römisch-Margl
Fabian J Theis
Jan Krumsiek
H-Erich Wichmann
Jakob Linseisen
Body fat free mass is associated with the serum metabolite profile in a population-based study.
description <h4>Objective</h4>To characterise the influence of the fat free mass on the metabolite profile in serum samples from participants of the population-based KORA (Cooperative Health Research in the Region of Augsburg) S4 study.<h4>Subjects and methods</h4>Analyses were based on metabolite profile from 965 participants of the S4 and 890 weight-stable subjects of its seven-year follow-up study (KORA F4). 190 different serum metabolites were quantified in a targeted approach including amino acids, acylcarnitines, phosphatidylcholines (PCs), sphingomyelins and hexose. Associations between metabolite concentrations and the fat free mass index (FFMI) were analysed using adjusted linear regression models. To draw conclusions on enzymatic reactions, intra-metabolite class ratios were explored. Pairwise relationships among metabolites were investigated and illustrated by means of Gaussian graphical models (GGMs).<h4>Results</h4>We found 339 significant associations between FFMI and various metabolites in KORA S4. Among the most prominent associations (p-values 4.75 × 10(-16)-8.95 × 10(-06)) with higher FFMI were increasing concentrations of the branched chained amino acids (BCAAs), ratios of BCAAs to glucogenic amino acids, and carnitine concentrations. For various PCs, a decrease in chain length or in saturation of the fatty acid moieties could be observed with increasing FFMI, as well as an overall shift from acyl-alkyl PCs to diacyl PCs. These findings were reproduced in KORA F4. The established GGMs supported the regression results and provided a comprehensive picture of the relationships between metabolites. In a sub-analysis, most of the discovered associations did not exist in obese subjects in contrast to non-obese subjects, possibly indicating derangements in skeletal muscle metabolism.<h4>Conclusion</h4>A set of serum metabolites strongly associated with FFMI was identified and a network explaining the relationships among metabolites was established. These results offer a novel and more complete picture of the FFMI effects on serum metabolites in a data-driven network.
format article
author Carolin Jourdan
Ann-Kristin Petersen
Christian Gieger
Angela Döring
Thomas Illig
Rui Wang-Sattler
Christa Meisinger
Annette Peters
Jerzy Adamski
Cornelia Prehn
Karsten Suhre
Elisabeth Altmaier
Gabi Kastenmüller
Werner Römisch-Margl
Fabian J Theis
Jan Krumsiek
H-Erich Wichmann
Jakob Linseisen
author_facet Carolin Jourdan
Ann-Kristin Petersen
Christian Gieger
Angela Döring
Thomas Illig
Rui Wang-Sattler
Christa Meisinger
Annette Peters
Jerzy Adamski
Cornelia Prehn
Karsten Suhre
Elisabeth Altmaier
Gabi Kastenmüller
Werner Römisch-Margl
Fabian J Theis
Jan Krumsiek
H-Erich Wichmann
Jakob Linseisen
author_sort Carolin Jourdan
title Body fat free mass is associated with the serum metabolite profile in a population-based study.
title_short Body fat free mass is associated with the serum metabolite profile in a population-based study.
title_full Body fat free mass is associated with the serum metabolite profile in a population-based study.
title_fullStr Body fat free mass is associated with the serum metabolite profile in a population-based study.
title_full_unstemmed Body fat free mass is associated with the serum metabolite profile in a population-based study.
title_sort body fat free mass is associated with the serum metabolite profile in a population-based study.
publisher Public Library of Science (PLoS)
publishDate 2012
url https://doaj.org/article/37bdaf6b0f1d448987062f75c622eb55
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