| Title |
Targeted metabolomics profiles are strongly correlated with nutritional patterns in women
|
|---|---|
| Published in |
Metabolomics, October 2012
|
| DOI | 10.1007/s11306-012-0469-6 |
| Pubmed ID | |
| 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 |
| 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. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 166 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 3 | 2% |
| Netherlands | 1 | <1% |
| France | 1 | <1% |
| United Kingdom | 1 | <1% |
| Brazil | 1 | <1% |
| Argentina | 1 | <1% |
| Japan | 1 | <1% |
| Unknown | 157 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 43 | 26% |
| Researcher | 32 | 19% |
| Student > Master | 16 | 10% |
| Student > Doctoral Student | 14 | 8% |
| Student > Bachelor | 10 | 6% |
| Other | 25 | 15% |
| Unknown | 26 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 40 | 24% |
| Medicine and Dentistry | 25 | 15% |
| Biochemistry, Genetics and Molecular Biology | 20 | 12% |
| Chemistry | 12 | 7% |
| Nursing and Health Professions | 7 | 4% |
| Other | 28 | 17% |
| Unknown | 34 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 April 2013.
All research outputs
#2,057,347
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Outputs from Metabolomics
#90
of 1,290 outputs
Outputs of similar age
#14,439
of 172,675 outputs
Outputs of similar age from Metabolomics
#1
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