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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. In 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. Based on metabolite profiles from urine and plasma, it was possible to identify metabolite patterns which classify participants according to sex with > 90% accuracy. Plasma metabolites important for the correct classification included creatinine, branched-chain amino acids, and sarcosine. Prediction of age was also possible based on metabolite profiles for men and women, separately. Several metabolites important for this prediction could be identified including choline in plasma and sedoheptulose in urine. For women, classification according to their menopausal status was possible from metabolome data with > 80% accuracy. The metabolite profile of human urine and plasma allows the prediction of sex and age with high accuracy, which means that sex and age are associated with a discriminatory metabolite signature in healthy humans and therefore should always be considered in metabolomics studies.

Scope: L-carnitine has been advertised as a fat-lowering and performance-enhancing supplement, although scientific evidence for its effectiveness is lacking. The uptake of about 1-2 g of L-carnitine per day may result in the formation of metabolites like trimethylamine-N-oxide (TMAO), which in turn may be converted to potential carcinogens or promote the development of cardiovascular diseases., Methods and Results: To assess whether an L-carnitine supplementation changes overall metabolism or causes the formation of previously unknown metabolites, we analyzed plasma samples from Fischer 344 rats originating from a previous study using a multi-platform metabolomics approach comprising LC-MS/MS and GC×GC-MS methods. Despite an intake of up to 352 mg L-carnitine/kg body weight/day for 1 year, plasma concentrations of only 29 out of 359 metabolites were significantly influenced, the induced concentration changes being often comparatively small. Nevertheless, a clear dose-response relationship and a substantial concentration increase were observed for TMAO, i.e. a tenfold higher TMAO level was measured in the high-dose group when compared to the control (2.5 versus 25.0 μM)., Conclusion: Although L-carnitine supplementation did not cause large changes in the plasma metabolome, a higher risk for cardiovascular disease due to chronically elevated TMAO plasma concentrations cannot be excluded., (© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)