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Population-level analysis to determine parameters that drive variation in the plasma metabolite profiles

Journal article
Authors M. Al-Majdoub
K. Herzog
Bledar Daka
M. Magnusson
L. Råstam
Ulf Lindblad
P. Spégel
Published in Metabolites
Volume 8
Issue 4
ISSN 2218-1989
Publication year 2018
Published at Institute of Medicine, School of Public Health and Community Medicine
Language en
Links dx.doi.org/10.3390/metabo8040078
Keywords Acylcarnitines, Branched-chain amino acids, Glomerular filtration rate, Insulin resistance, Metabolomics
Subject categories Environmental medicine

Abstract

The plasma metabolome is associated with multiple phenotypes and diseases. However, a systematic study investigating clinical determinants that control the metabolome has not yet been conducted. In the present study, therefore, we aimed to identify the major determinants of the plasma metabolite profile. We used ultra-high performance liquid chromatography (UHPLC) coupled to quadrupole time of flight mass spectrometry (QTOF-MS) to determine 106 metabolites in plasma samples from 2503 subjects in a cross-sectional study. We investigated the correlation structure of the metabolite profiles and generated uncorrelated metabolite factors using principal component analysis (PCA) and varimax rotation. Finally, we investigated associations between these factors and 34 clinical covariates. Our results suggest that liver function, followed by kidney function and insulin resistance show the strongest associations with the plasma metabolite profile. The association of specific phenotypes with several components may suggest multiple independent metabolic mechanisms, which is further supported by the composition of the associated factors. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.

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