Exploring the association between habitual food intake and the urine and blood metabolome in adolescents and young adults: a cohort study

Cohort profile update-overview of over 35 years of research in the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study

PURPOSE

To provide an update on the cohort profile of the DOrtmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study, including objectives, study design, methods and description of the comprehensive data pool, as well as to summarize the most important research findings of recent years.

METHODS

In 1985, the open (dynamic) cohort started to collect information on diet, growth, development, and metabolism of healthy children and adolescents in Dortmund, Germany. Detailed data are collected annually during infancy, childhood, and adolescence of the participants, including a 3-day weighed dietary record, a 24-h urine sample, anthropometric and medical examinations as well as interviews on lifestyle.

RESULTS

Even if the basic examination modules have not changed since the start over 35 years ago, the DONALD study has been continuously further developed by introducing new modules. As such, participants are also invited for follow-up examinations during adulthood since 2005, including an additional fasting blood withdrawal. Overall, 2375 (♂: 1177; ♀: 1198) participants were recruited in the DONALD study between 1985 and 2022. Data from ~ 30,700 anthropometric measurements, ~ 19,200 dietary records, ~ 10,600 24-h urine and ~ 1300 blood samples are available from an observation period of over 35 years.

CONCLUSION

The DONALD study provides a large data pool for longitudinal studies on nutrition, growth, and health in childhood and adolescence, its impact on the development of diseases in early adult life as well as dietary intake trends over more than three decades.

Recovery of 400 Chemicals with Three Extraction Methods for Low Volumes of Human Plasma Quantified by Instrumental Analysis and In Vitro Bioassays

Human biomonitoring studies are important for understanding adverse health outcomes caused by exposure to chemicals. Complex mixtures of chemicals detected in blood - the blood exposome - may serve as proxies for systemic exposure. Ideally, several analytical methods are combined with in vitro bioassays to capture chemical mixtures as diverse as possible. How many and which (bio)analyses can be performed is limited by the sample volume and compatibility of extraction and (bio)analytical methods. We compared the extraction efficacy of three extraction methods using pooled human plasma spiked with >400 organic chemicals. Passive equilibrium sampling (PES) with polydimethylsiloxane (PDMS) followed by solid phase extraction (PES + SPE), SPE alone (SPE), and solvent precipitation (SolvPrec) were compared for chemical recovery in LC-HRMS and GC-HRMS as well as effect recovery in four mammalian cell lines (AhR-CALUX, SH-SY5Y, AREc32, PPARγ-BLA). The mean chemical recoveries were 38% for PES + SPE, 27% for SPE, and 61% for SolvPrec. PES + SPE enhanced the mean chemical recovery compared to SPE, especially for neutral hydrophobic chemicals. PES + SPE and SolvPrec had effect recoveries of 100-200% in all four cell lines, outperforming SPE, which had 30-100% effect recovery. Although SolvPrec has the best chemical recoveries, it does not remove matrix like inorganics or lipids, which might pose problems for some (bio)analytical methods. PES + SPE is the most promising method for sample preparation in human biomonitoring as it combines good recoveries with cleanup, enrichment, and potential for high throughput.

The gut-derived metabolites as mediators of the effect of healthy nutrition on the brain

Nutrition is now well recognized to be an environmental factor which positively or negatively influences the risk to develop neurological and psychiatric disorders. The gut microbiota has recently been shown to be an important actor mediating the relationship between environmental factors, including nutrition, and brain function. While its composition has been widely studied and associated with the risk of brain diseases, the mechanisms underlying the relationship between the gut and brain diseases remain to be explored. The wide range of bioactive molecules produced by the gut microbiota, called gut-derived metabolites (GDM), represent new players in the gut to brain interactions and become interesting target to promote brain health. The aim of this narrative review is to highlight some GDMs of interest that are produced in response to healthy food consumption and to summarize what is known about their potential effects on brain function. Overall, GDMs represent future useful biomarkers for the development of personalized nutrition. Indeed, their quantification after nutritional interventions is a useful tool to determine individuals' ability to produce microbiota-derived bioactive compounds upon consumption of specific food or nutrients. Moreover, GDMs represent also a new therapeutic approach to counteract the lack of response to conventional nutritional interventions.

Exploring the association of physical activity with the plasma and urine metabolome in adolescents and young adults

BACKGROUND

Regular physical activity elicits many health benefits. However, the underlying molecular mechanisms through which physical activity influences overall health are less understood. Untargeted metabolomics enables system-wide mapping of molecular perturbations which may lend insights into physiological responses to regular physical activity. In this study, we investigated the associations of habitual physical activity with plasma and urine metabolome in adolescents and young adults.

METHODS

This cross-sectional study included participants from the DONALD (DOrtmund Nutritional and Anthropometric Longitudinally Designed) study with plasma samples n = 365 (median age: 18.4 (18.1, 25.0) years, 58% females) and 24 h urine samples n = 215 (median age: 18.1 (17.1, 18.2) years, 51% females). Habitual physical activity was assessed using a validated Adolescent Physical Activity Recall Questionnaire. Plasma and urine metabolite concentrations were determined using ultra-high-performance liquid chromatography-tandem mass spectroscopy (UPLC-MS/MS) methods. In a sex-stratified analysis, we conducted principal component analysis (PCA) to reduce the dimensionality of metabolite data and to create metabolite patterns. Multivariable linear regression models were then applied to assess the associations between self-reported physical activity (metabolic equivalent of task (MET)-hours per week) with single metabolites and metabolite patterns, adjusted for potential confounders and controlling the false discovery rate (FDR) at 5% for each set of regressions.

RESULTS

Habitual physical activity was positively associated with the "lipid, amino acids and xenometabolite" pattern in the plasma samples of male participants only (β = 1.02; 95% CI: 1.01, 1.04, p = 0.001, adjusted p = 0.042). In both sexes, no association of physical activity with single metabolites in plasma and urine and metabolite patterns in urine was found (all adjusted p > 0.05).

CONCLUSIONS

Our explorative study suggests that habitual physical activity is associated with alterations of a group of metabolites reflected in the plasma metabolite pattern in males. These perturbations may lend insights into some of underlying mechanisms that modulate effects of physical activity.

Replication and mediation of the association between the metabolome and clinical markers of metabolic health in an adolescent cohort study

Metabolomics-derived metabolites (henceforth metabolites) may mediate the relationship between modifiable risk factors and clinical biomarkers of metabolic health (henceforth clinical biomarkers). We set out to study the associations of metabolites with clinical biomarkers and a potential mediation effect in a population of young adults. First, we conducted a systematic literature review searching for metabolites associated with 11 clinical biomarkers (inflammation markers, glucose, blood pressure or blood lipids). Second, we replicated the identified associations in a study population of n = 218 (88 males and 130 females, average age of 18 years) participants of the DONALD Study. Sex-stratified linear regression models adjusted for age and BMI and corrected for multiple testing were calculated. Third, we investigated our previously reported metabolites associated with anthropometric and dietary factors mediators in sex-stratified causal mediation analysis. For all steps, both urine and blood metabolites were considered. We found 41 metabolites in the literature associated with clinical biomarkers meeting our inclusion criteria. We were able to replicate an inverse association of betaine with CRP in women, between body mass index and C-reactive protein (CRP) and between body fat and leptin. There was no evidence of mediation by lifestyle-related metabolites after correction for multiple testing. We were only able to partially replicate previous findings in our age group and did not find evidence of mediation. The complex interactions between lifestyle factors, the metabolome, and clinical biomarkers warrant further investigation.