BackgroundExcessive sugar consumption is a public health concern. Allulose, a low-calorie sugar with similar functional properties to sucrose, offers potential metabolic benefits. Animal and limited human studies suggest it may stimulate glucagon-like peptide-1 (GLP-1) secretion, improve glucose regulation, and support weight management. However, evidence to substantiate these effects in humans remains scarce. ObjectiveThe primary aim of this study, the low-calorie sweetener intervention study allulose (LisA), was to assess differences in the postprandial GLP-1 profile (primary outcome) between an acute intake of allulose and aspartame interventions in healthy adults. Secondary goals included exploratively assessing potential subacute adaptation effects over a 4-week consumption period and evaluating a comprehensive set of parameters as hypothesis-generating findings for future large-scale research. MethodsWe conducted a randomized, double-blind, placebo-controlled, crossover trial in healthy adults. Participants daily consumed either 3 allulose-sweetened or aspartame-sweetened beverages for 4 weeks in crossover, with a washout in between. Standardized inpatient procedures were conducted at the study baseline and at the beginning and end of each intervention phase. The primary outcome is the postprandial profile of GLP-1. Secondary outcomes include further parameters of gut hormone secretion, insulin sensitivity (Matsuda Index), body composition (body impedance analysis), subjective satiety (visual analog scales), and gastrointestinal tolerance. We also assess multiomic endpoints, including sugaromics and gut microbiome composition. The primary outcome will be analyzed using the incremental area under the curve with a 2-tailed paired t test. All further outcomes (including peak and total area under the curve for GLP-1) will be assessed using linear mixed models. ResultsA total of 10 participants (4 female and 6 male; mean age 31.2, SD 6.8 years; BMI 25.1, SD 2.6 kg/m2) completed all study procedures. The sample collection phase was successfully concluded in November 2023. Data processing and statistical analysis for the primary outcome are expected to be completed by June 2026. ConclusionsThe comprehensive study protocol, integrating a rigorous crossover design with multiomic analysis, is poised to provide confirmatory evidence for the acute GLP-1 effects of allulose and generate valuable mechanistic hypotheses regarding its subacute metabolic and gut health effects. The findings will contribute to the evidence base required for evaluating allulose’s potential role in public health sugar reduction strategies. Trial RegistrationGerman Clinical Trials Register DRKS00028521; https://drks.de/search/en/trial/DRKS00028521 International Registered Report Identifier (IRRID)DERR1-10.2196/81857

Heart rate recovery (HRR) indicates post-exercise autonomic regulation and serves as a marker of cardiorespiratory fitness and mortality risk. Autonomic and metabolic recovery are both integral to post-exercise homeostasis, yet how HRR relates to metabolic recovery remains unclear. To address this gap, we analyzed data from a randomized crossover trial in 17 healthy, physically active young men, each performing 30 min of both moderate- and vigorous-intensity ergometer cycling. Plasma samples collected before exercise and at multiple recovery time points were analyzed using UPLC–MS/MS–based untargeted metabolomics, covering more than 1000 metabolites. HRR was calculated using a monoexponential decay model, and associations were examined using linear mixed models. Individuals with faster HRR exhibited significantly lower post-exercise levels across a range of lipid metabolites, particularly acylcarnitines. These associations were stronger for HRR than VO₂peak and were statistically significant only in the later recovery period (90–180 min post-exercise), exclusively following vigorous-intensity exercise. Our findings suggest that HRR reflects post-exercise lipid metabolism under conditions of high metabolic demand. The observed metabolite patterns are indicative of differences in β-oxidation, lipid accumulation, reliance on ω-oxidation, and mitochondrial turnover, and are consistent with more efficient post-exercise lipid metabolism. HRR may provide a simple marker of metabolic or cardiorespiratory fitness and could be relevant for monitoring exercise responses and assessing cardiometabolic health. However, confirmation in larger and more diverse cohorts is required. The trial was registered on October 5, 2017, at the German Clinical Trials Register under the registration number DRKS00009743 (Universal Trial Number of WHO: U1111-1200–2530).

Background:Although a high intake of plant foods is often considered healthy, some plant foods can be detrimental to health. Reliable dietary assessment is crucial to examine the relationship between diet and disease. Current dietary assessment methods rely on self-reported intake data, which are subject to bias. Objective measurement using biomarkers of food intake could mitigate this problem. However, single biomarkers of food intake have limitations as well. Combining several biomarkers of food intake into a multibiomarker panel could attenuate these limitations and allow for an accurate, objective dietary assessment. Objective:The PLAENTI study aims to validate a multibiomarker panel for the assessment of quantity and quality of plant foods in the diet. Methods:PLAENTI is a randomized controlled trial with 4 arms in a parallel design. Metabolically healthy adults (≥18 years old) were enrolled in the study. The study consisted of 1 week of run-in, with a standardized diet low in healthful plant foods for all participants; 2 weeks of a dietary intervention according to the assigned arm; and 1 week of washout, during which participants returned to their habitual diet. During the intervention, the participants' diet consisted of either a low, medium, or high proportion of healthful plant foods or a high proportion of unhealthful plant foods in the diet according to the assigned arm. The arm that received a high proportion of healthful plant foods served as the control. All food was provided based on energy-adjusted menu plans. During the visits, anthropometry and body composition were assessed, and blood samples were collected. Throughout the study, participants collected multiple urine samples (24-hour urine, evening and morning spot urine) and stool samples. Blood and urine samples will be analyzed by liquid chromatography-mass spectrometry to determine biomarker levels for the validation of a multibiomarker panel. Results:After receiving approval from the ethics committee, recruitment began, and the first screening visit took place in November 2023. Between January and August 2024, of the 66 enrolled participants, 59 (31 female, 28 male) successfully completed the study, and their urine, blood, and stool samples are available for analysis. PLAENTI was conducted in 5 waves with a maximum of 16 participants enrolled in each wave. The mean age of the study population was 45.5 (SD 18.4) years, the mean BMI was 24.8 (SD-3.9) kg/m², and the mean total energy expenditure was 2464 (SD 440) kcal. Conclusions:PLAENTI was conducted in a highly controlled and standardized manner, yielding samples and data that will be used to examine whether the quantity and quality of plant foods in the diet can be assessed using a multibiomarker panel. Successful validation of the multibiomarker panel would enable its application for objective dietary assessment.

Exercise metabolomics research has revealed significant exercise-induced metabolic changes and identified several exerkines as mediators of physiological adaptations to exercise. However, the effect of exercise intensity on metabolic changes and circulating exerkine levels remains to be examined. This study compared the metabolic responses to moderate-intensity and vigorous-intensity aerobic exercise. A two-period crossover trial was conducted under controlled conditions at the Max Rubner-Institute in Karlsruhe, Germany. Seventeen young, healthy, and physically active men performed 30 min moderate-intensity (50

Biomarkers of food intake (BFIs) have emerged as a promising objective tool to complement traditional self-reported dietary assessment in nutritional research, with the potential to reduce systematic errors and improve accuracy. The development of comprehensive and robust quantification methods for BFIs is essential for widespread application. However, existing methods typically cover only a moderate number of BFIs per method, hindering their wide application in the field. In this study, we present the development and validation of a method for simultaneous quantification of 80 BFIs in urine reflecting 27 foods. The method utilizes a simple sample preparation procedure, followed by separation using both high-performance liquid chromatography (HPLC) on a C18 column and a hydrophilic interaction chromatography (HILIC) column, combined with tandem mass spectrometry in positive and negative mode (HPLC-MS/MS) (individual runs: 6 min). The working range for each analyte was determined in urine samples from a non-randomized, non-blinded nutritional intervention study. The method was validated with respect to selectivity, linearity, robustness, matrix effects, recovery, accuracy, and precision. In total, 44 BFIs could be absolutely quantified without or with only limitations at low concentrations, while 36 BFIs could only be measured semi-quantitatively, including 16 BFIs with limited validation data due to uncertainties. The 80 BFIs represent 27 foods (6 semi-quantitative) frequently consumed in European diets, including 24 plant-derived and 3 animal-derived items. The future implementation of this large-scale BFI quantification method in nutritional studies is expected to demonstrate the benefits of routinely measuring BFIs to improve the accuracy of dietary assessment.

This abstract introduces the ongoing project “PlantIntake” and the accompanying validation study that will start in January 2024—current status and goals will be presented at the conference. PlantIntake, a JPI-funded project, aims to improve dietary assessment of plant foods, which currently relies on self-reported intake data that are prone to bias. High levels of plant foods in the diet are generally considered healthful, but there are also plant foods that are detrimental to health. Plant-based diet indices (PDIs), developed in the United States, have improved the understanding of the associations between plant food intake and health/disease outcomes. Within PlantIntake, European PDIs will be derived to suit European dietary habits and will include aspects of variety and processing. For dietary assessment, objective measurements are desired and may be achieved with biomarkers of food intake or respective panels of them. Such multi-biomarker panels (MBMPs) are an approach to overcome the limitations of single biomarkers to obtain a more robust dietary assessment. This approach is in line with the trend in epidemiology to look at dietary patterns rather than individual foods. An inventory of putative biomarkers of plant food intake was compiled as a basis for the development of a wide-coverage targeted metabolomics method for the analysis of blood and urine samples. By applying this metabolomics method to samples from European dietary studies available within the consortium, MBMPs reflecting plant food intake and adherence to European PDIs will be developed and subsequently validated in a controlled intervention study. In a 2-week intervention period, 60 participants will be randomized into four groups. Three of these groups will receive a diet low, medium, and high in healthful plant foods, while the fourth group will receive a diet high in unhealthful plant foods. The derived MBMPs will be validated for their reliability in assessing the quantity and quality of plant food intake. In addition, the effect of confounders (e.g., age and sex), as well as dose- and time-response aspects on biomarker concentrations, will be investigated.

INTRODUCTION:In metabolomics, the investigation of associations between the metabolome and one trait of interest is a key research question. However, statistical analyses of such associations are often challenging. Statistical tools enabling resilient verification and clear presentation are therefore highly desired. OBJECTIVES:Our aim is to provide a contribution for statistical analysis of metabolomics data, offering a widely applicable open-source statistical workflow, which considers the intrinsic complexity of metabolomics data. METHODS:We combined selected R packages tailored for all properties of heterogeneous metabolomics datasets, where metabolite parameters typically (i) are analyzed in different matrices, (ii) are measured on different analytical platforms with different precision, (iii) are analyzed by targeted as well as non-targeted methods, (iv) are scaled variously, (v) reveal heterogeneous variances, (vi) may be correlated, (vii) may have only few values or values below a detection limit, or (viii) may be incomplete. RESULTS:The code is shared entirely and freely available. The workflow output is a table of metabolites associated with a trait of interest and a compact plot for high-quality results visualization. The workflow output and its utility are presented by applying it to two previously published datasets: one dataset from our own lab and another dataset taken from the repository MetaboLights. CONCLUSION:Robustness and benefits of the statistical workflow were clearly demonstrated, and everyone can directly re-use it for analysis of own data.

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.

Background On the national level, nutritional monitoring requires the assessment of reliable representative dietary intake data. To achieve this, standardized tools need to be developed, validated, and kept up-to-date with recent developments in food products and the nutritional behavior of the population. Recently, the human intestinal microbiome has been identified as an essential mediator between nutrition and host health. Despite growing interest in this connection, only a few associations between the microbiome, nutrition, and health have been clearly established. Available studies paint an inconsistent picture, partly due to a lack of standardization. Objective First, we aim to verify if food consumption, as well as energy and nutrient intake of the German population, can be recorded validly by means of the dietary recall software GloboDiet, which will be applied in the German National Nutrition Monitoring. Second, we aim to obtain high-quality data using standard methods on the microbiome, combined with dietary intake data and additional fecal sample material, and to also assess the functional activity of the microbiome by measuring microbial metabolites. Methods Healthy female and male participants aged between 18 and 79 years were recruited. Anthropometric measurements included body height and weight, BMI, and bioelectrical impedance analysis. For validation of the GloboDiet software, current food consumption was assessed with a 24-hour recall. Nitrogen and potassium concentrations were measured from 24-hour urine collections to enable comparison with the intake of protein and potassium estimated by the GloboDiet software. Physical activity was measured over at least 24 hours using a wearable accelerometer to validate the estimated energy intake. Stool samples were collected in duplicate for a single time point and used for DNA isolation and subsequent amplification and sequencing of the 16S rRNA gene to determine microbiome composition. For the identification of associations between nutrition and the microbiome, the habitual diet was determined using a food frequency questionnaire covering 30 days. Results In total, 117 participants met the inclusion criteria. The study population was equally distributed between the sexes and 3 age groups (18-39, 40-59, and 60-79 years). Stool samples accompanying habitual diet data (30-day food frequency questionnaire) are available for 106 participants. Current diet data and 24-hour urine samples for the validation of GloboDiet are available for 109 participants, of which 82 cases also include physical activity data. Conclusions We completed the recruitment and sample collection of the ErNst study with a high degree of standardization. Samples and data will be used to validate the GloboDiet software for the German National Nutrition Monitoring and to compare microbiome composition and nutritional patterns. Trial Registration German Register of Clinical Studies DRKS00015216; https://drks.de/search/de/trial/DRKS00015216 International Registered Report Identifier (IRRID) DERR1-10.2196/42529

Introduction: Endurance exercise alters whole-body as well as skeletal muscle metabolism and physiology, leading to improvements in performance and health. However, biological mechanisms underlying the body’s adaptations to different endurance exercise protocols are not entirely understood.Methods: We applied a multi-platform metabolomics approach to identify urinary metabolites and associated metabolic pathways that distinguish the acute metabolic response to two endurance exercise interventions at distinct intensities. In our randomized crossover study, 16 healthy, young, and physically active men performed 30 min of continuous moderate exercise (CME) and continuous vigorous exercise (CVE). Urine was collected during three post-exercise sampling phases (U01/U02/U03: until 45/105/195 min post-exercise), providing detailed temporal information on the response of the urinary metabolome to CME and CVE. Also, fasting spot urine samples were collected pre-exercise (U00) and on the following day (U04). While untargeted two-dimensional gas chromatography-mass spectrometry (GC×GC-MS) led to the detection of 608 spectral features, 44 metabolites were identified and quantified by targeted nuclear magnetic resonance (NMR) spectroscopy or liquid chromatography-mass spectrometry (LC-MS).Results: 104 urinary metabolites showed at least one significant difference for selected comparisons of sampling time points within or between exercise trials as well as a relevant median fold change >1.5 or <0.6¯ (NMR, LC-MS) or >2.0 or <0.5 (GC×GC-MS), being classified as either exercise-responsive or intensity-dependent. Our findings indicate that CVE induced more profound alterations in the urinary metabolome than CME, especially at U01, returning to baseline within 24 h after U00. Most differences between exercise trials are likely to reflect higher energy requirements during CVE, as demonstrated by greater shifts in metabolites related to glycolysis (e.g., lactate, pyruvate), tricarboxylic acid cycle (e.g., cis-aconitate, malate), purine nucleotide breakdown (e.g., hypoxanthine), and amino acid mobilization (e.g., alanine) or degradation (e.g., 4-hydroxyphenylacetate).Discussion: To conclude, this study provided first evidence of specific urinary metabolites as potential metabolic markers of endurance exercise intensity. Future studies are needed to validate our results and to examine whether acute metabolite changes in urine might also be partly reflective of mechanisms underlying the health- or performance-enhancing effects of endurance exercise, particularly if performed at high intensities.

Although lifestyle-based interventions are the most effective to prevent metabolic syndrome (MetS), there is no definitive agreement on which nutritional approach is the best. The aim of the present retrospective analysis was to identify a multivariate model linking energy and macronutrient intake to the clinical features of MetS. Volunteers at risk of MetS (F = 77, M = 80) were recruited in four European centres and finally eligible for analysis. For each subject, the daily energy and nutrient intake was estimated using the EPIC questionnaire and a 24-h dietary recall, and it was compared with the dietary reference values. Then we built a predictive model for a set of clinical outcomes computing shifts from recommended intake thresholds. The use of the ridge regression, which optimises prediction performances while retaining information about the role of all the nutritional variables, allowed us to assess if a clinical outcome was manly dependent on a single nutritional variable, or if its prediction was characterised by more complex interactions between the variables. The model appeared suitable for shedding light on the complexity of nutritional variables, which effects could be not evident with univariate analysis and must be considered in the framework of the reciprocal influence of the other variables.

Recent studies focused on modulating factors of paraoxonase-1 (PON1) activity. In some studies the association between pro-inflammatory markers and PON1 activity was examined, but so far no population-based investigations on this issue have been conducted. The present study investigated the relationships between the pro-inflammatory markers tumor necrosis factor (TNF)-α, leptin, interleukin (IL)-6, and high-sensitive C-reactive protein (hs-CRP) and paraoxonase and arylesterase, two hydrolytic activities of PON1, in the population-based Bavarian Food Consumption Survey II. Based on 504 participants (217 men, 287 women), the relationship between the pro-inflammatory markers and the outcomes paraoxonase and arylesterase activities were investigated using multivariable linear models. Circulating plasma levels of leptin (P-value < 0.0001), hs-CRP (P-value = 0.031) and IL-6 (P-value = 0.045) were significantly non-linearly associated with arylesterase activity. Leptin levels were also significantly associated with paraoxonase activity (P-value = 0.024) independently from confounding factors, including high-density lipoprotein (HDL) cholesterol. With increasing levels of these inflammatory parameters, arylesterase and paraoxonase activities increased; however, at higher levels (> 75th percentile) the activities reached a plateau or even decreased somewhat. After Bonferroni-Holm correction, only leptin remained non-linearly but significantly associated with arylesterase activity (adjusted overall P-value < 0.0001). Neither age nor sex nor obesity modified the associations. No association was found between TNF-α and paraoxonase or arylesterase activity. The present findings suggest that in persons with very high levels of inflammation, PON1 activity may be impaired, a fact that might subsequently be accompanied by a higher risk for cardiometabolic diseases. Whether or not the measurement of PON1 activity in combination with a lipid profile and certain inflammatory markers could improve the prediction of cardiometabolic diseases in middle-aged individuals from the general population should be evaluated in clinical studies.

Cardiorespiratory fitness (CRF) represents a strong predictor of all-cause mortality and is strongly influenced by regular physical activity (PA). However, the biological mechanisms involved in the body’s adaptation to PA remain to be fully elucidated. The aim of this study was to systematically examine the relationship between CRF and plasma metabolite patterns in 252 healthy adults from the cross-sectional Karlsruhe Metabolomics and Nutrition (KarMeN) study. CRF was determined by measuring the peak oxygen uptake during incremental exercise. Fasting plasma samples were analyzed by nuclear magnetic resonance spectroscopy and mass spectrometry coupled to one- or two-dimensional gas chromatography or liquid chromatography. Based on this multi-platform metabolomics approach, 427 plasma analytes were detected. Bi- and multivariate association analyses, adjusted for age and menopausal status, showed that CRF was linked to specific sets of metabolites primarily indicative of lipid metabolism. However, CRF-related metabolite patterns largely differed between sexes. While several phosphatidylcholines were linked to CRF in females, single lyso-phosphatidylcholines and sphingomyelins were associated with CRF in males. When controlling for further assessed clinical and phenotypical parameters, sex-specific CRF tended to be correlated with a smaller number of metabolites linked to lipid, amino acid, or xenobiotics-related metabolism. Interestingly, sex-specific CRF explanation models could be improved when including selected plasma analytes in addition to clinical and phenotypical variables. In summary, this study revealed sex-related differences in CRF-associated plasma metabolite patterns and proved known associations between CRF and risk factors for cardiometabolic diseases such as fat mass, visceral adipose tissue mass, or blood triglycerides in metabolically healthy individuals. Our findings indicate that covariates like sex and, especially, body composition have to be considered when studying blood metabolic markers related to CRF.

AbstractDiet is the only source of the essential branched-chain amino acids (BCAA) isoleucine, leucine and valine. High plasma concentrations of these amino acids are discussed as risk factors for the onset of several diseases such as type 2 diabetes mellitus (T2D) or cardiovascular diseases (CVD). Information about the contribution of the overall diet to plasma levels of these amino acids is controversial. Our objective was to investigate which dietary pattern is associated with plasma BCAA concentrations in a healthy population and which other additional nutrients besides isoleucine, leucine and valine, such as other amino acids, may contribute to the diseases risk.The Karlsruhe Metabolomics and Nutrition (KarMeN) study is a cross-sectional study aiming to determine the impact of a number of factors on the human metabolome in healthy men and women aged 18 and 80 years. In our study, fasting plasma amino acid concentrations as well as current and habitual dietary intake were assessed in 298 apparently healthy individuals, 171 men (57.4%) and 127 women (42.6%) with a mean age of 44.5 and 51.6 years, respectively. All reported foods were summarized into 35 food groups. Dietary patterns were derived that explain as much variation as possible in plasma BCAA concentrations using reduced rank regression. The first derived current dietary pattern covering the diet of the past 24 hours, showed 19.2% of explained variance for BCAA plasma concentrations, whereas the first habitual dietary pattern, covering a period of more than 4 weeks, explained 32.5%. For further analysis, we focused on the first derived habitual dietary pattern. 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 and at the same a decrease in plant-based protein, dietary fibre and an unfavorable fatty acid composition. Amino acids alanine, lysine and the aromatic amino acids phenylalanine, tyrosine, and tryptophan were positively associated with the dietary pattern score as well. All of these factors were reported to be associated with risk of T2D and CVD.Our data suggest that rather than the dietary intake of BCAA, the overall dietary pattern contributing to high BCAA plasma concentrations may modulate the chronic diseases risk.

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.

LebensmittelchemieVolume 74, Issue S1 p. S1-019-S1-019 Poster der 71. Arbeitstagung des Regionalverbands Bayern (9.–10. März 2020, Würzburg) Massenspektrometrische Bestimmung des Konjugationsmusters von Estrogenen im Plasma gesunder Frauen: Neuer Ansatzpunkt für epidemiologische Studien zu estrogenabhängigen Krankheiten Lisa Markert, Lisa Markert Lehrstuhl für Lebensmittelchemie, Universität Würzburg, Am Hubland, 97074 WürzburgSearch for more papers by this authorCarolin Kleider, Carolin Kleider Lehrstuhl für Lebensmittelchemie, Universität Würzburg, Am Hubland, 97074 WürzburgSearch for more papers by this authorAchim Bub, Achim Bub Max Rubner-Institut, Haid-und-Neu-Str. 9, 76131 KarlsruheSearch for more papers by this authorSabine Kulling, Sabine Kulling Max Rubner-Institut, Haid-und-Neu-Str. 9, 76131 KarlsruheSearch for more papers by this authorLeane Lehmann, Leane Lehmann Lehrstuhl für Lebensmittelchemie, Universität Würzburg, Am Hubland, 97074 WürzburgSearch for more papers by this author Lisa Markert, Lisa Markert Lehrstuhl für Lebensmittelchemie, Universität Würzburg, Am Hubland, 97074 WürzburgSearch for more papers by this authorCarolin Kleider, Carolin Kleider Lehrstuhl für Lebensmittelchemie, Universität Würzburg, Am Hubland, 97074 WürzburgSearch for more papers by this authorAchim Bub, Achim Bub Max Rubner-Institut, Haid-und-Neu-Str. 9, 76131 KarlsruheSearch for more papers by this authorSabine Kulling, Sabine Kulling Max Rubner-Institut, Haid-und-Neu-Str. 9, 76131 KarlsruheSearch for more papers by this authorLeane Lehmann, Leane Lehmann Lehrstuhl für Lebensmittelchemie, Universität Würzburg, Am Hubland, 97074 WürzburgSearch for more papers by this author First published: 05 May 2020 https://doi.org/10.1002/lemi.202051019AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume74, IssueS1Supplement: Vorträge und Poster der 71. Arbeitstagung des Regionalverbands BayernMarch 2020Pages S1-019-S1-019 RelatedInformation

Knowledge on metabolites distinguishing the metabolic response to acute physical exercise between fit and less fit individuals could clarify mechanisms and metabolic pathways contributing to the beneficial adaptations to exercise. By analyzing data from the cross-sectional KarMeN (Karlsruhe Metabolomics and Nutrition) study, we characterized the acute effects of a standardized exercise tolerance test on urinary metabolites of 255 healthy women and men. In a second step, we aimed to detect a urinary metabolite pattern associated with the cardiorespiratory fitness (CRF), which was determined by measuring the peak oxygen uptake (VO2peak) during incremental exercise. Spot urine samples were collected pre- and post-exercise and 47 urinary metabolites were identified by nuclear magnetic resonance (NMR) spectroscopy. While the univariate analysis of pre-to-post-exercise differences revealed significant alterations in 37 urinary metabolites, principal component analysis (PCA) did not show a clear separation of the pre- and post-exercise urine samples. Moreover, both bivariate correlation and multiple linear regression analyses revealed only weak relationships between the VO2peak and single urinary metabolites or urinary metabolic pattern, when adjusting for covariates like age, sex, menopausal status, and lean body mass (LBM). Taken as a whole, our results show that several urinary metabolites (e.g., lactate, pyruvate, alanine, and acetate) reflect acute exercise-induced alterations in the human metabolism. However, as neither pre- and post-exercise levels nor the fold changes of urinary metabolites substantially accounted for the variation of the covariate-adjusted VO2peak, our results furthermore indicate that the urinary metabolites identified in this study do not allow to draw conclusions on the individual’s physical fitness status. Studies investigating the relationship between the human metabolome and functional variables like the CRF should adjust for confounders like age, sex, menopausal status, and LBM.

Docosahexaenoic acid (DHA) has been reported to have a positive impact on many diet-related disease risks, including metabolic syndrome. Although many DHA-enriched foods have been marketed, the impact of different food matrices on the effect of DHA is unknown. As well, the possibility to enhance DHA effectiveness through the co-administration of other bioactives has seldom been considered. We evaluated DHA effects on the serum metabolome administered to volunteers at risk of metabolic syndrome as an ingredient of three different foods. Foods were enriched with DHA alone or in combination with oat beta-glucan or anthocyanins and were administered to volunteers for 4 weeks. Serum samples collected at the beginning and end of the trial were analysed by NMR-based metabolomics. Multivariate and univariate statistical analyses were used to characterize modifications in the serum metabolome and to evaluate bioactive-bioactive and bioactive-food matrix interactions. DHA administration induces metabolome perturbation that is influenced by the food matrix and the co-presence of other bioactives. In particular, when co-administered with oat beta-glucan, DHA induces a strong rearrangement in the lipoprotein profile of the subjects. The observed modifications are consistent with clinical results and indicate that metabolomics represents a possible strategy to choose the most appropriate food matrices for bioactive enrichment.

Differences in resting energy expenditure (REE) between men and women mainly result from sex-related differences in lean body mass (LBM). So far, a little is known about whether REE and LBM are reflected by a distinct human metabolite profile. Therefore, we aimed to identify plasma and urine metabolite patterns that are associated with REE and LBM of healthy subjects.