Glyphosate (N-[phosphonomethyl]-glycine) is the most widely used herbicide worldwide. Due to health concerns about glyphosate exposure, its continued use is controversially discussed. Biomonitoring is an important tool in safety evaluation and this study aimed to determine exposure to glyphosate and its metabolite AMPA, in association with food consumption data, in participants of the cross-sectional KarMeN study (Germany). Glyphosate and AMPA levels were measured in 24-h urine samples from study participants (n = 301). For safety evaluation, the intake of glyphosate and AMPA was calculated based on urinary concentrations and checked against the EU acceptable daily intake (ADI) value for glyphosate. Urinary excretion of glyphosate and/or AMPA was correlated with food consumption data. 8.3% of the participants (n = 25) exhibited quantifiable concentrations (> 0.2 µg/L) of glyphosate and/or AMPA in their urine. In 66.5% of the samples, neither glyphosate (< 0.05 µg/L) nor AMPA (< 0.09 µg/L) was detected. The remaining subjects (n = 76) showed traces of glyphosate and/or AMPA. The calculated glyphosate and/or AMPA intake was far below the ADI of glyphosate. Significant, positive associations between urinary glyphosate excretion and consumption of pulses, or urinary AMPA excretion and mushroom intake were observed. Despite the widespread use of glyphosate, the exposure of the KarMeN population to glyphosate and AMPA was found to be very low. Based on the current risk assessment of glyphosate by EFSA, such exposure levels are not expected to pose any risk to human health. The detected associations with consuming certain foods are in line with reports on glyphosate and AMPA residues in food.

Branched-chain amino acids (BCAA) in plasma are discussed as risk factors for the onset of several diseases. Information about the contribution of the overall diet to plasma BCAA concentrations is controversial. Our objective was to investigate which dietary pattern is associated with plasma BCAA concentrations and whether other additional nutrients besides BCAA further characterize this dietary pattern. Based on the cross-sectional KarMeN study, fasting plasma amino acid (AA) concentrations, as well as current and habitual dietary intake were assessed in 298 healthy individuals. Using reduced rank regression, we derived a habitual dietary pattern that explained 32.5% of plasma BCAA variation. This pattern was high in meat, sausages, sauces, eggs, and ice cream but low in nuts, cereals, mushrooms, and pulses. The age, sex, and energy intake adjusted dietary pattern score was associated with an increase in animal-based protein together with a decrease in plant-based protein, dietary fiber, and an unfavorable fatty acid composition. Besides BCAA, alanine, lysine and the aromatic AA were positively associated with the dietary pattern score as well. All of these factors were reported to be associated with risk of type 2 diabetes and cardiovascular diseases before. Our data suggest that rather than the dietary intake of BCAA, the overall dietary pattern that contributes to high BCAA plasma concentrations may modulate chronic diseases risk.

Banana is one of the most widely consumed fruits in the world. However, information regarding its health effects is scarce. Biomarkers of banana intake would allow a more accurate assessment of its consumption in nutrition studies. Using an untargeted metabolomics approach, we aimed to identify the banana-derived metabolites present in urine after consumption, including new candidate biomarkers of banana intake. A randomized controlled study with a crossover design was performed on 12 healthy subjects (6 men, 6 women, mean ± SD age: 30.0 ± 4.9 y; mean ± SD BMI: 22.5 ± 2.3 kg/m²). Subjects underwent 2 dietary interventions: 1) 250 mL control drink (Fresubin 2 kcal fiber, neutral flavor; Fresenius Kabi), and 2) 240 g banana + 150 mL control drink. Twenty-four-hour urine samples were collected and analyzed with ultra-performance liquid chromatography coupled to a quadrupole time-of-flight MS and 2-dimensional GC-MS. The discovered biomarkers were confirmed in a cross-sectional study [KarMeN (Karlsruhe Metabolomics and Nutrition study)] in which 78 subjects (mean BMI: 22.8; mean age: 47 y) were selected reflecting high intake (126–378 g/d), low intake (47.3–94.5 g/d), and nonconsumption of banana. The confirmed biomarkers were examined singly or in combinations, for established criteria of validation for biomarkers of food intake. We identified 33 potentially bioactive banana metabolites, of which 5 metabolites, methoxyeugenol glucuronide (MEUG-GLUC), dopamine sulfate (DOP-S), salsolinol sulfate, xanthurenic acid, and 6-hydroxy-1-methyl-1,2,3,4-tetrahydro-β-carboline sulfate, were confirmed as candidate intake biomarkers. We demonstrated that the combination of MEUG-GLUC and DOP-S performed best in predicting banana intake in high (AUC_test = 0.92) and low (AUC_test = 0.87) consumers. The new biomarkers met key criteria establishing their current applicability in nutrition and health research for assessing the occurrence of banana intake. Our metabolomics study in healthy men and women revealed new putative bioactive metabolites of banana and a combined biomarker of intake. These findings will help to better decipher the health effects of banana in future focused studies. This study was registered at clinicaltrials.gov as NCT03581955 and with the Ethical Committee for the Protection of Human Subjects Sud-Est 6 as CPP AU 1251, IDRCB 2016-A0013–48; the KarMeN study was registered with the German Clinical Trials Register (DRKS00004890). Details about the study can be obtained from https://www.drks.de.

It is consensus in the metabolomics community that standardized protocols should be followed for sample handling, storage and analysis, as it is of utmost importance to maintain constant measurement conditions to identify subtle biological differences. The aim of this work, therefore, was to systematically investigate the influence of freezing procedures and storage temperatures and their effect on NMR spectra as a potentially disturbing aspect for NMR-based metabolomics studies. Urine samples were collected from two healthy volunteers, centrifuged and divided into aliquots. Urine aliquots were frozen either at −20 °C, on dry ice, at −80 °C or in liquid nitrogen and then stored at −20 °C, −80 °C or in liquid nitrogen vapor phase for 1–5 weeks before NMR analysis. Results show spectral changes depending on the freezing procedure, with samples frozen on dry ice showing the largest deviations. The effect was found to be based on pH differences, which were caused by variations in CO₂ concentrations introduced by the freezing procedure. Thus, we recommend that urine samples should be frozen at −20 °C and transferred to lower storage temperatures within one week and that freezing procedures should be part of the publication protocol.

Background: Soy isoflavones belong to the group of phytoestrogens and are associated with beneficial health effects but are also discussed to have adverse effects. Isoflavones are intensively metabolized by the gut microbiota leading to metabolites with altered estrogenic potency. The population is classified into different isoflavone metabotypes based on individual metabolite profiles. So far, this classification was based on the capacity to metabolize daidzein and did not reflect genistein metabolism. We investigated the microbial metabolite profile of isoflavones considering daidzein and genistein. Methods: Isoflavones and metabolites were quantified in the urine of postmenopausal women receiving a soy isoflavone extract for 12 weeks. Based on these data, women were clustered in different isoflavone metabotypes. Further, the estrogenic potency of these metabotypes was estimated. Results: Based on the excreted urinary amounts of isoflavones and metabolites, the metabolite profiles could be calculated, resulting in 5 metabotypes applying a hierarchical cluster analysis. The metabotypes differed in part strongly regarding their metabolite profile and their estimated estrogenic potency.