Exploring the Association between Habitual Food Intake and the Urine and Blood Metabolome in Adolescents and Young Adults: A Cohort Study.

SCOPE: Habitual diet may be reflected in metabolite profiles that can improve accurate assessment of dietary exposure and further enhance our understanding of their link to health conditions. The study aims to explore the relationship of habitual food intake with blood and urine metabolites in adolescents and young adults. METHODS: The study population comprises 228 participants (94 males and 134 females) of the DONALD study. Dietary intake is assessed by yearly repeated 3d-food records. Habitual diet is estimated as the average consumption of 23 food groups in adolescence. Using an untargeted metabolomics approach, the study quantifies 2638 metabolites in plasma and 1407 metabolites in urine. In each sex, unique diet-metabolite associations using orthogonal projection to latent structures (oPLS) and random forests (RF) is determined. RESULTS: Six metabolites in agreement between oPLS and RF in urine, one in female (vanillylmandelate to processed/other meat) and five in males (indole-3-acetamide, and N6-methyladenosine to eggs; hippurate, citraconate/glutaconate, and X - 12111 to vegetables) are observed. No association in blood in agreement is observed. CONCLUSION: A limited reflection of habitual food group intake by single metabolites in urine and not in blood is observed. The explored biomarkers should be confirmed in additional studies.

Associations of BMI and Body Fat with Urine Metabolome in Adolescents Are Sex-Specific: A Cross-Sectional Study.

Epidemiologic studies examining the relationship between body composition and the urine metabolome may improve our understanding of the role of metabolic dysregulation in body composition-related health conditions. Previous studies, mostly in adult populations, have focused on a single measure of body composition, body mass index (BMI), and sex-specific associations are rarely explored. We investigate sex-specific associations of two measures of body composition-BMI and body fat (BF)-with the urine metabolome in adolescents. In 369 participants (age 16-18, 49% female) of the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study, we examined sex-specific associations of these two measures of body composition, BMI and BF, and 1407 (467 unknown) 24 h urine metabolites analyzed by untargeted metabolomics cross-sectionally. Missing metabolites were imputed. We related metabolites (dependent variable) to BMI and BF (independent variable) separately using linear regression. The models were additionally adjusted for covariates. We found 10 metabolites associated with both BMI and BF. We additionally found 11 metabolites associated with only BF, and nine with only BMI. None of these associations was in females. We observed a strong sexual dimorphism in the relationship between body composition and the urine metabolome.

Blood Metabolomic Profiling Confirms and Identifies Biomarkers of Food Intake.

Metabolomics can be a tool to identify dietary biomarkers. However, reported food-metabolite associations have been inconsistent, and there is a need to explore further associations. Our aims were to confirm previously reported food-metabolite associations and to identify novel food-metabolite associations. We conducted a cross-sectional analysis of data from 849 participants (57% men) of the PopGen cohort. Dietary intake was obtained using FFQ and serum metabolites were profiled by an untargeted metabolomics approach. We conducted a systematic literature search to identify previously reported food-metabolite associations and analyzed these associations using linear regression. To identify potential novel food-metabolite associations, datasets were split into training and test datasets and linear regression models were fitted to the training datasets. Significant food-metabolite associations were evaluated in the test datasets. Models were adjusted for covariates. In the literature, we identified 82 food-metabolite associations. Of these, 44 associations were testable in our data and confirmed associations of coffee with 12 metabolites, of fish with five, of chocolate with two, of alcohol with four, and of butter, poultry and wine with one metabolite each. We did not identify novel food-metabolite associations; however, some associations were sex-specific. Potential use of some metabolites as biomarkers should consider sex differences in metabolism.

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.