1.
Metabolic Effects of a 24-Week Energy-Restricted Intervention Combined with Low or High Dairy Intake in Overweight Women: An NMR-Based Metabolomics Investigation.
Zheng, H, Lorenzen, JK, Astrup, A, Larsen, LH, Yde, CC, Clausen, MR, Bertram, HC
Nutrients. 2016;(3):108
Abstract
We investigated the effect of a 24-week energy-restricted intervention with low or high dairy intake (LD or HD) on the metabolic profiles of urine, blood and feces in overweight/obese women by NMR spectroscopy combined with ANOVA-simultaneous component analysis (ASCA). A significant effect of dairy intake was found on the urine metabolome. HD intake increased urinary citrate, creatinine and urea excretion, and decreased urinary excretion of trimethylamine-N-oxide (TMAO) and hippurate relative to the LD intake, suggesting that HD intake was associated with alterations in protein catabolism, energy metabolism and gut microbial activity. In addition, a significant time effect on the blood metabolome was attributed to a decrease in blood lipid and lipoprotein levels due to the energy restriction. For the fecal metabolome, a trend for a diet effect was found and a series of metabolites, such as acetate, butyrate, propionate, malonate, cholesterol and glycerol tended to be affected. Overall, even though these effects were not accompanied by a higher weight loss, the present metabolomics data reveal that a high dairy intake is associated with endogenous metabolic effects and effects on gut microbial activity that potentially impact body weight regulation and health. Moreover, ASCA has a great potential for exploring the effect of intervention factors and identifying altered metabolites in a multi-factorial metabolomic study.
2.
Discovery and validation of urinary exposure markers for different plant foods by untargeted metabolomics.
Andersen, MB, Kristensen, M, Manach, C, Pujos-Guillot, E, Poulsen, SK, Larsen, TM, Astrup, A, Dragsted, L
Analytical and bioanalytical chemistry. 2014;(7):1829-44
Abstract
While metabolomics is increasingly used to investigate the food metabolome and identify new markers of food exposure, limited attention has been given to the validation of such markers. The main objectives of the present study were to (1) discover potential food exposure markers (PEMs) for a range of plant foods in a study setting with a mixed dietary background and (2) validate PEMs found in a previous meal study. Three-day weighed dietary records and 24-h urine samples were collected three times during a 6-month parallel intervention study from 107 subjects randomized to two distinct dietary patterns. An untargeted UPLC-qTOF-MS metabolomics analysis was performed on the urine samples, and all features detected underwent strict data analyses, including an iterative paired t test and sensitivity and specificity analyses for foods. A total of 22 unique PEMs were identified that covered 7 out of 40 investigated food groups (strawberry, cabbages, beetroot, walnut, citrus, green beans and chocolate). The PEMs reflected foods with a distinct composition rather than foods eaten more frequently or in larger amounts. We found that 23 % of the PEMs found in a previous meal study were also valid in the present intervention study. The study demonstrates that it is possible to discover and validate PEMs for several foods and food classes in an intervention study with a mixed dietary background, despite the large variability in such a dataset. Final validation of PEMs for intake of foods should be performed by quantitative analysis.