Association of ultra-processed foods intake with untargeted metabolomics profiles in adolescents and young adults in the DONALD cohort study.

BACKGROUND: High consumption of ultra-processed foods (UPF) continues to draw significant public health interest due to the associated negative health outcomes. Metabolomics can contribute to the understanding of the biological mechanisms through which UPFs may influence health. OBJECTIVES: To investigate urine and plasma metabolomic biomarkers of UPF intake in adolescents and young adults. METHODS: We used data from the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study to investigate cross-sectional associations of UPF intake with concentrations of urine metabolites in adolescents using 3-d weighed dietary records (3d-WDR) and 24-h urine samples (n = 339), and associations of repeatedly assessed UPF intake with concentrations of circulating plasma metabolites in young adults with 3 to 6 3d-WDRs within 5 y preceding blood measurement (n = 195). Urine and plasma samples were analyzed using mass spectrometry-based metabolomics. Biosample-specific metabolite patterns were determined using robust sparse principal components analysis. Multivariable linear regression models were applied to assess the associations of UPF consumption (as a percentage of total food intake in g/d) with concentrations of individual metabolites and metabolite pattern scores. RESULTS: The median proportion of UPF intake was 22.0% (interquartile range, IQR: 12.3, 32.9) in adolescents and 23.2% (IQR: 16.0, 31.6) in young adults. We identified 42 and 6 UPF intake-associated metabolites in urine and plasma samples, respectively. One urinary metabolite pattern, "xenobiotics and amino acids" (ß = 0.042, 95% confidence interval, [CI]: 0.014, 0.070) and one plasma metabolite pattern, "lipids, xenobiotics, and amino acids" (ß = 0.074, 95% CI: 0.031, 0.117) showed positive association with UPF intake. Both patterns shared 29 metabolites, mostly of xenobiotic metabolism. CONCLUSIONS: We identified urine and plasma metabolites associated with UPF intake in adolescents and young adults, which may represent some of the biological mechanisms through which UPFs may influence metabolism and health.

Dietary Patterns Are Associated with Serum Metabolite Patterns and Their Association Is Influenced by Gut Bacteria among Older German Adults.

BACKGROUND: Although dietary intakes and dietary intake patterns (DPs) have been associated with single metabolites, it is unclear whether DPs are also reflected in specific metabolite patterns (MPs). Moreover, the influence of groups of gut bacteria on the relationship between DPs and MPs is underexplored. OBJECTIVES: We aimed to investigate the association of DPs and serum MPs and also the modifying effect of the gut bacteria compositional patterns (BCPs). METHODS: This is a cross-sectional investigation among 225 individuals (median age: 63 y; 53% women) from the European Prospective Investigation into Cancer and Nutrition study. Dietary intakes were assessed by three 24-h dietary recalls, gut bacteria composition was quantified by 16S rRNA gene sequencing, and the serum metabolome was profiled by an untargeted approach. We identified DPs and BCPs by the treelet transform analysis. We modeled associations between DPs and 8 previously published MPs and the modifying effect of BCPs by fitting generalized linear models using DataSHIELD R. RESULTS: We identified 5 DPs and 7 BCPs. The "bread, margarine, and processed meat" and "fruiting vegetables and vegetable oils" DPs were positively associated with the "amino acids" (ß = 0.35; 95% CI: 0.02, 0.69; P = 0.03) and "fatty acids" MPs (ß = 0.45; 95% CI: 0.16, 0.74; P = 0.01), respectively. The "tea and miscellaneous" was inversely associated with the "amino acids" (ß = -0.28; 95% CI: -0.52, -0.05; P = 0.02) and "amino acid derivatives" MPs (ß = -0.21; 95% CI: -0.39, -0.02; P = 0.03). One BCP negatively modified the association between the "bread, margarine, and processed meat" DP and the "amino acids" MP (P-interaction = 0.01). CONCLUSIONS: In older German adults, DPs are reflected in MPs, and the gut bacteria attenuate 1 DP-MP association. These MPs should be explored as biomarkers of these jointly consumed foods while taking into account a potentially modifying role of the gut bacteria.

Metabolite Patterns in Human Myeloid Hematopoiesis Result from Lineage-Dependent Active Metabolic Pathways.

Assessment of hematotoxicity from environmental or xenobiotic compounds is of notable interest and is frequently assessed via the colony forming unit (CFU) assay. Identification of the mode of action of single compounds is of further interest, as this often enables transfer of results across different tissues and compounds. Metabolomics displays one promising approach for such identification, nevertheless, suitability with current protocols is restricted. Here, we combined a hematopoietic stem and progenitor cell (HSPC) expansion approach with distinct lineage differentiations, resulting in formation of erythrocytes, dendritic cells and neutrophils. We examined the unique combination of pathway activity in glycolysis, glutaminolysis, polyamine synthesis, fatty acid oxidation and synthesis, as well as glycerophospholipid and sphingolipid metabolism. We further assessed their interconnections and essentialness for each lineage formation. By this, we provide further insights into active metabolic pathways during the differentiation of HSPC into different lineages, enabling profound understanding of possible metabolic changes in each lineage caused by exogenous compounds.

Diagnostic Performance of Sex-Specific Modified Metabolite Patterns in Urine for Screening of Prediabetes.

Aims/Hypothesis: Large-scale prediabetes screening is still a challenge since fasting blood glucose and HbA1c as the long-standing, recommended analytes have only moderate diagnostic sensitivity, and the practicability of the oral glucose tolerance test for population-based strategies is limited. To tackle this issue and to identify reliable diagnostic patterns, we developed an innovative metabolomics-based strategy deviating from common concepts by employing urine instead of blood samples, searching for sex-specific biomarkers, and focusing on modified metabolites. Methods: Non-targeted, modification group-assisted metabolomics by liquid chromatography-mass spectrometry (LC-MS) was applied to second morning urine samples of 340 individuals from a prediabetes cohort. Normal (n = 208) and impaired glucose-tolerant (IGT; n = 132) individuals, matched for age and BMI, were randomly divided in discovery and validation cohorts. ReliefF, a feature selection algorithm, was used to extract sex-specific diagnostic patterns of modified metabolites for the detection of IGT. The diagnostic performance was compared with conventional screening parameters fasting plasma glucose (FPG), HbA1c, and fasting insulin. Results: Female- and male-specific diagnostic patterns were identified in urine. Only three biomarkers were identical in both. The patterns showed better AUC and diagnostic sensitivity for prediabetes screening of IGT than FPG, HbA1c, insulin, or a combination of FPG and HbA1c. The AUC of the male-specific pattern in the validation cohort was 0.889 with a diagnostic sensitivity of 92.6% and increased to an AUC of 0.977 in combination with HbA1c. In comparison, the AUCs of FPG, HbA1c, and insulin alone reached 0.573, 0.668, and 0.571, respectively. Validation of the diagnostic pattern of female subjects showed an AUC of 0.722, which still exceeded the AUCs of FPG, HbA1c, and insulin (0.595, 0.604, and 0.634, respectively). Modified metabolites in the urinary patterns include advanced glycation end products (pentosidine-glucuronide and glutamyl-lysine-sulfate) and microbiota-associated compounds (indoxyl sulfate and dihydroxyphenyl-gamma-valerolactone-glucuronide). Conclusions/Interpretation: Our results demonstrate that the sex-specific search for diagnostic metabolite biomarkers can be superior to common metabolomics strategies. The diagnostic performance for IGT detection was significantly better than routinely applied blood parameters. Together with recently developed fully automatic LC-MS systems, this opens up future perspectives for the application of sex-specific diagnostic patterns for prediabetes screening in urine.

Sex-Specific Relationship between the Cardiorespiratory Fitness and Plasma Metabolite Patterns in Healthy Humans-Results of the KarMeN Study.

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.

The Association between Alcohol Consumption and Serum Metabolites and the Modifying Effect of Smoking.

Alcohol consumption is an important lifestyle factor that is associated with several health conditions and a behavioral link with smoking is well established. Metabolic alterations after alcohol consumption have yet to be comprehensively investigated. We studied the association of alcohol consumption with metabolite patterns (MPs) among 2433 individuals from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study, and a potential modification by smoking. Alcohol consumption was self-reported through dietary questionnaires and serum metabolites were measured by a targeted approach. The metabolites were summarized as MPs using the treelet transform analysis (TT). We fitted linear models with alcohol consumption continuously and in five categories. We stratified the continuously modelled alcohol consumption by smoking status. All models were adjusted for potential confounders. Among men, alcohol consumption was positively associated with six MPs and negatively associated with one MP. In women, alcohol consumption was inversely associated with one MP. Heavy consumers differed from other consumers with respect to the "Long and short chain acylcarnitines" MP. Our findings suggest that long and short chain acylcarnitines might play an important role in the adverse effects of heavy alcohol consumption on chronic diseases. The relations seem to depend on gender and smoking status.