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Metabolite patterns predicting sex and age in participants of the Karlsruhe Metabolomics and Nutrition (KarMeN) study

Rist, Manuela J.; Roth, Alexander; Frommherz, Lara; Weinert, Christoph H.; Krüger, Ralf; Merz, Benedikt; Bunzel, Diana; Mack, Carina; Egert, Björn; Bub, Achim; Görling, Benjamin 1,2; Tzvetkova, Pavleta 1,2; Luy, Burkhard ORCID iD icon 1,2; Hoffmann, Ingrid; Kulling, Sabine E.; Watzl, Bernhard
1 Institut für Biologische Grenzflächen (IBG), Karlsruher Institut für Technologie (KIT)
2 Institut für Organische Chemie (IOC), Karlsruher Institut für Technologie (KIT)


Physiological and functional parameters, such as body composition, or physical fitness are known to differ between men and women and to change with age. The goal of this study was to investigate how sex and age-related physiological conditions are reflected in the metabolome of healthy humans and whether sex and age can be predicted based on the plasma and urine metabolite profiles.
n the cross-sectional KarMeN (Karlsruhe Metabolomics and Nutrition) study 301 healthy men and women aged 18–80 years were recruited. Participants were characterized in detail applying standard operating procedures for all measurements including anthropometric, clinical, and functional parameters. Fasting blood and 24 h urine samples were analyzed by targeted and untargeted metabolomics approaches, namely by mass spectrometry coupled to one- or comprehensive two-dimensional gas chromatography or liquid chromatography, and by nuclear magnetic resonance spectroscopy. This yielded in total more than 400 analytes in plasma and over 500 analytes in urine. Predictive modelling was applied on the metabolomics data set using different machine learning algorithms.
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Verlagsausgabe §
DOI: 10.5445/IR/1000073937
Veröffentlicht am 13.03.2018
DOI: 10.1371/journal.pone.0183228
Zitationen: 125
Web of Science
Zitationen: 120
Zitationen: 144
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Biologische Grenzflächen (IBG)
Institut für Organische Chemie (IOC)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2017
Sprache Englisch
Identifikator ISSN: 1932-6203
KITopen-ID: 1000073937
HGF-Programm 47.02.04 (POF III, LK 01) Zellpopul.auf Biofunk.Oberflächen IBG-4
Erschienen in PLoS one
Verlag Public Library of Science (PLoS)
Band 12
Heft 8
Seiten Art.Nr. e0183228
Vorab online veröffentlicht am 16.08.2017
Nachgewiesen in Dimensions
Web of Science
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