Metabolomics of prolonged fasting in humans reveals new catabolic markers
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Fasting is one of the simplest metabolic challenges that can be performed in humans. We here report for the first time a comprehensive analysis of the human “fasting metabolome” obtained from analysis of plasma and urine samples in a small cohort of healthy volunteers, using nuclear magnetic resonance (NMR), gas chromatography- and liquid chromatography-mass spectrometry (GC-MS and LC-MS). Intra- and inter-individual variation of metabolites was on measurement of four overnight fasting samples collected from each volunteer over a four week period. One additional sample per volunteer was collected following a prolonged fasting period of 36 h. Amongst a total of 377 quantified entities in plasma around 44% were shown to change significantly in concentration when volunteers extended fasting from 12 to 36 h. In addition to known markers (plasma free fatty acids, glycerol, ketone bodies) that reflect changes in the body’s fuel management under fasting conditions a wide range of “new” entities such as α-aminobutyrate as well as other amino and keto acids were identified as fasting markers. Based on multiple correlations amongst the metabolites and selected hormones in plasma such as leptin or insulin-like-growth-factor-1 (IGF-1), a robust metabolic network with coherent regulation of a wide range of metabolites could be identified. The metabolomics approach described here demonstrates the plasticity of human metabolism and identifies new and robust markers of the fasting state.
KeywordsFasting response Metabolite profiling Subject variability
This study was funded by the European Nutrigenomics Organisation, an EC funded Network of Excellence, grant No: FOOD-2004-506360. We kindly thank all members of the NuGO PPS Study for excellent cooperation and productive scientific discussions. We specifically would like to thank Karen Ross and Lynn Pirie for their help with the sample preparation work, Barbara Gelhaus, Mark Philo, Ronny Scheundel, Hermine Kienberger and Johanna Welzhofer for excellent technical assistance.
- Crosley, L. K., Duthie, S. J., Polley, A. C., Bouwman, F. G., Heim, C., Mulholland, F., et al. (2009). Variation in protein levels obtained from human blood cells and biofluids for platelet, peripheral blood mononuclear cell, plasma, urine and saliva proteomics. Genes and Nutrition, 4, 95–102.PubMedCrossRefGoogle Scholar
- Laforet, P., Acquaviva-Bourdain, C., Rigal, O., Brivet, M., Penisson-Besnier, I., Chabrol, B., et al. (2009). Diagnostic assessment and long-term follow-up of 13 patients with Very Long-Chain Acyl-Coenzyme A dehydrogenase (VLCAD) deficiency. Neuromuscular Disorders, 19, 324–329.PubMedCrossRefGoogle Scholar
- Linsel-Nitschke, P., Jansen, H., Aherrarhou, Z., Belz, S., Mayer, B., Lieb, W., et al. (2009). Macrophage cholesterol efflux correlates with lipoprotein subclass distribution and risk of obstructive coronary artery disease in patients undergoing coronary angiography. Lipids in Health and Disease, 8, 14.PubMedCrossRefGoogle Scholar
- R Development Core Team. (2009). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.Google Scholar
- Zhao, X., Peter, A., Fritsche, J., Elcnerova, M., Fritsche, A., Haring, H. U., et al. (2009). Changes of the plasma metabolome during an oral glucose tolerance test: Is there more than glucose to look at? American Journal of Physiology. Endocrinology and Metabolism, 296, E384–E393.PubMedCrossRefGoogle Scholar