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.

Lipoprotein profiling of human blood by 1H nuclear magnetic resonance (NMR) spectroscopy is a rapid and promising approach to monitor health and disease states in medicine and nutrition. However, lack of standardization of measurement protocols has prevented the use of NMR-based lipoprotein profiling in metastudies. In this study, a standardized NMR measurement protocol was applied in a ring test performed across three different laboratories in Europe on plasma and serum samples from 28 individuals. Data was evaluated in terms of (i) spectral differences, (ii) differences in LPD predictions obtained using an existing prediction model, and (iii) agreement of predictions with cholesterol concentrations in high- and low-density lipoproteins (HDL and LDL) particles measured by standardized clinical assays. ANOVA-simultaneous component analysis (ASCA) of the ring test spectral ensemble that contains methylene and methyl peaks (1.4–0.6 ppm) showed that 97.99% of the variance in the data is related to subject, 1.62% to sample type (serum or plasma), and 0.39% to laboratory. This interlaboratory variation is in fact smaller than the maximum acceptable intralaboratory variation on quality control samples. It is also shown that the reproducibility between laboratories is good enough for the LPD predictions to be exchangeable when the standardized NMR measurement protocol is followed. With the successful implementation of this protocol, which results in reproducible prediction of lipoprotein distributions across laboratories, a step is taken toward bringing NMR more into scope of prognostic and diagnostic biomarkers, reducing the need for less efficient methods such as ultracentrifugation or high-performance liquid chromatography (HPLC).

The metabolic composition of plasma is affected by time passed since the last meal and by individual variation in metabolite clearance rates. Rat plasma in fed and fasted states was analyzed with liquid chromatography quadrupole-time-of-flight mass spectrometry (LC-QTOF) for an untargeted investigation of these metabolite patterns. The dataset was used to investigate the effect of data preprocessing on biomarker selection using three different softwares, MarkerLynxTM, MZmine, XCMS along with a customized preprocessing method that performs binning of m/z channels followed by summation through retention time. Direct comparison of selected features representing the fed or fasted state showed large differences between the softwares. Many false positive markers were obtained from custom data preprocessing compared with dedicated softwares while MarkerLynxTM provided better coverage of markers. However, marker selection was more reliable with the gap filling (or peak finding) algorithms present in MZmine and XCMS. Further identification of the putative markers revealed that many of the differences between the markers selected were due to variations in features representing adducts or daughter ions of the same metabolites or of compounds from the same chemical subclasses, e.g., lyso-phosphatidylcholines (LPCs) and lyso-phosphatidylethanolamines (LPEs). We conclude that despite considerable differences in the performance of the preprocessing tools we could extract the same biological information by any of them. Carnitine, branched-chain amino acids, LPCs and LPEs were identified by all methods as markers of the fed state whereas acetylcarnitine was abundant during fasting in rats.

This study presents representative population-based data on gluten intake in Danish adults. Total gluten intake decreased with increasing age.

In order to investigate exposure end effect markers of fruit and fruit fibre intake we investigated how fresh apple or apple-pectin affects the urinary metabolome of rats. Twenty-four Fisher 344 male rats were randomized into three groups and fed a standard diet with different supplementations added in two of the groups (7% apple-pectin or 10 g raw apple). After 24 days of feeding, 24 h urine was collected and analyzed by UPLC-QTOF-MS in positive and negative ionization mode. Metabolites that responded to the apple or pectin diets were selected and classified as either potential exposure or effect markers based on the magnitude and pattern of their response. An initial principal component analysis (PCA) of all detected metabolites showed a clear separation between the groups and during marker identification several new apple and/or pectin markers were found. Quinic acid, m-coumaric acid and (-)epicatechin were identified as exposure markers of apple intake whereas hippuric acid behaved as an effect marker. Pyrrole-2-carboxylic acid and 2-furoylglycine behaved as pectin exposure markers while 2-piperidinone was recognized as a potential pectin effect marker. None of them has earlier been related to intake of pectin or other fibre products. We discuss these new potential exposure and effect markers and their interpretation.