title: Body fat free mass is associated with the serum metabolite profile in a population-based study.
abstract: OBJECTIVE
  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.
  
  
  METHODS
  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).
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors: Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
authors: Carolin
authors: C
authors: Jourdan
authors: Ann-Kristin
authors: AK
authors: Petersen
authors: Christian
authors: C
authors: Gieger
authors: Angela
authors: A
authors: Döring
authors: Thomas
authors: T
authors: Illig
authors: Rui
authors: R
authors: Wang-Sattler
authors: Christa
authors: C
authors: Meisinger
authors: Annette
authors: A
authors: Peters
authors: Jerzy
authors: J
authors: Adamski
authors: Cornelia
authors: C
authors: Prehn
authors: Karsten
authors: K
authors: Suhre
authors: Elisabeth
authors: E
authors: Altmaier
authors: Gabi
authors: G
authors: Kastenmüller
authors: Werner
authors: W
authors: Römisch-Margl
authors: Fabian J
authors: FJ
authors: Theis
authors: Jan
authors: J
authors: Krumsiek
authors: H-Erich
authors: HE
authors: Wichmann
authors: Jakob
authors: J
authors: Linseisen
mesh_terms: D000273:Adipose Tissue; D000368:Aged; D001774:Blood Chemical Analysis; D001823:Body Composition; D006801:Humans; D055432:Metabolomics; D008875:Middle Aged