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Targeted metabolomics profiles are strongly correlated with nutritional patterns in women |
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| Authors: | Cristina Menni Guangju Zhai Alexander MacGregor Cornelia Prehn Werner Römisch-Margl Karsten Suhre Jerzy Adamski Aedin Cassidy Thomas Illig Tim D. Spector Ana M. Valdes |
| Affiliation: | 1. Department of Twin Research & Genetic Epidemiology, King’s College London, St Thomas Hospital, London, SE17EH, UK 2. Faculty of Medicine, Memorial University of Newfoundland, St John’s, NL, Canada 3. Norwich Medical School, University of East Anglia, Norwich, UK 4. Helmholtz Zentrum München, Institute of Experimental Genetics, Genome Analysis Center, Neuherberg, Germany 5. Helmholtz Zentrum München, Institute of Bioinformatics and Systems Biology, Neuherberg, Germany 6. Department of Physiology and Biophysics, Weill Cornell Medical College in Qatar, Education City, Qatar Foundation, Doha, State of Qatar 7. Faculty of Biology, Ludwig-Maximilians-Universit?t, Gro?haderner Str. 2, Planegg-Martinsried, Germany 8. Lehrstuhl für Experimentelle Genetik, Technische Universit?t München, Freising-Weihenstephan, Germany 10. Hannover Unified Biobank, Hannover Medical School, Hannover, Germany 9. Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany |
| Abstract: | Nutrition plays an important role in human metabolism and health. Metabolomics is a promising tool for clinical, genetic and nutritional studies. A key question is to what extent metabolomic profiles reflect nutritional patterns in an epidemiological setting. We assessed the relationship between metabolomic profiles and nutritional intake in women from a large cross-sectional community study. Food frequency questionnaires (FFQs) were applied to 1,003 women from the TwinsUK cohort with targeted metabolomic analyses of serum samples using the Biocrates Absolute-IDQ? Kit p150 (163 metabolites). We analyzed seven nutritional parameters: coffee intake, garlic intake and nutritional scores derived from the FFQs summarizing fruit and vegetable intake, alcohol intake, meat intake, hypo-caloric dieting and a “traditional English” diet. We studied the correlation between metabolite levels and dietary intake patterns in the larger population and identified for each trait between 14 and 20 independent monozygotic twins pairs discordant for nutritional intake and replicated results in this set. Results from both analyses were then meta-analyzed. For the metabolites associated with nutritional patterns, we calculated heritability using structural equation modelling. 42 metabolite nutrient intake associations were statistically significant in the discovery samples (Bonferroni P < 4 × 10?5) and 11 metabolite nutrient intake associations remained significant after validation. We found the strongest associations for fruit and vegetables intake and a glycerophospholipid (Phosphatidylcholine diacyl C38:6, P = 1.39 × 10?9) and a sphingolipid (Sphingomyeline C26:1, P = 6.95 × 10?13). We also found significant associations for coffee (confirming a previous association with C10 reported in an independent study), garlic intake and hypo-caloric dieting. Using the twin study design we find that two thirds the metabolites associated with nutritional patterns have a significant genetic contribution, and the remaining third are solely environmentally determined. Our data confirm the value of metabolomic studies for nutritional epidemiologic research. |
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