Biomarkers of individual foods, and separation of diets using untargeted LC-MS-based plasma metabolomics in a randomized controlled trial
Research output: Contribution to journal › Journal article
Scope: Self-reported dietary intake does not represent an objective unbiased assessment. We investigate the effect of the New Nordic Diet (NND) versus Average Danish Diet (ADD) on plasma metabolic profiles to identify biomarkers of compliance and metabolic effects.
Methods and Results: In a 26-week controlled dietary intervention study, 146 subjects followed either NND, a predominantly organic diet high in fruit, vegetables, whole grains, and fish, or ADD, a diet higher in imported and processed foods. Fasting plasma samples were analyzed with untargeted UPLC-QTOF. We demonstrate that supervised machine learning with feature selection can separate NND and ADD samples with an average test set performance of up to 0.88 Area Under the Curve. The NND plasma metabolome was characterized by diet related metabolites such as pipecolic acid betaine (whole grain), trimethylamine oxide and prolyl hydroxyproline (both fish intake) while theobromine (chocolate) and proline betaine (citrus) were associated with ADD. Amino acid (i.e., indolelactic acid and hydroxy-3-methylbutyrate) and fat metabolism (butyryl carnitine) characterized ADD while NND was associated with higher concentrations of polyunsaturated phosphatidylcholines.
Conclusions: The plasma metabolite profiles were predictive of dietary patterns and reflected good compliance while indicating effects of potential health benefit, including changes in fat metabolism and glucose utilization. This article is protected by copyright. All rights reserved.
|Journal||Molecular Nutrition & Food Research|
|Number of pages||10|
|Publication status||Published - 2019|
- Faculty of Science - Untargeted metabolomics, LC-MS, Plasma, Biomarker patterns, Compliance