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Projekt Druckansicht

Das Food Metabolom als neues Konzept zur Erhebung der Ernährungsexposition bei Kindern

Fachliche Zuordnung Ernährungswissenschaften
Epidemiologie und Medizinische Biometrie/Statistik
Förderung Förderung von 2018 bis 2024
Projektkennung Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 406710821
 
Erstellungsjahr 2024

Zusammenfassung der Projektergebnisse

Objective dietary assessment is crucial to understand diet-disease associations; however, it is challenging in children to apply food related questionnaires. Biomarkers measured in urine may offer a complementary or alternate approach. The aim of the present project was to identify and validate biomarkers associated with dietary intake of children and adolescents in large European cohort studies. Therefore, the FOODMETCH project comprehensively studied the food metabolome as the totality of metabolites linked to diet. In total, 2400 urine samples that had been repeatedly collected from children and adolescents of the IDE- FICS/I.Family (morning urine samples) and DONALD cohort (24-h urine samples) were analyzed with untargeted metabolomics using high-resolution liquid chromatography-mass spectrometry from our collaboration partner at International Agency for Research on Cancer (IARC) Lyon. Untargeted metabolomics analysis yielded several thousand signals found in urine samples. These signals were further linked with dietary data from 24-h dietary recalls and food frequency questionnaire data (IDEFICS/IFamily), and 3-d weighted dietary records (DONALD cohort). Multivariate modelling with Unbiased Variable selection algorithms and linear mixed models were used to identify metabolites linked to acute and habitual food intake. In a second step, signals linked to diet were annotated. Reproducibility and sources of variation of food metabolites were studied using data from repeated sample collections. Finally, we assessed the association between dietary metabolites with measures of obesity and cardiometabolic risk using longitudinal cohort data. With this approach, potential biomarkers were identified and replicated for intake of sweet and fatty snacks, fruit and vegetables and sweetened beverages. Many of the mass spectrometry features that were linked to dietary intakes remained unknown; however, we provide their information in supplementary materials of the manuscripts for use in future studies. We identified three metabolites from caffeine metabolism linked to chocolate intake in children consistently in both cohorts. Their reproducibility in urine samples over two and four years ranged from intraclass correlation coefficients 0.23 to 0.55. Of them, xanthosine that was positively linked to chocolate intake was inversely associated with BMI z-score in the IDEFICS/I.Family study. For fruits and vegetables, ten metabolites were identified in IDEFICS/I.Family of which hippuric acid could also be identified and replicated in the DONALD cohort. Hippuric acid concentration was not associated with cardiometabolic risk markers. Other biomarkers of fruit and vegetable intake, such as ferulic acid 4-O-glucuronide and ferulic acid 4-O-sulfate that were found to be linked to orange intake in IDEFICS/I.Family were inversely associated with plasma glucose. Several metabolites of known and unknown identity for intake of sweetened beverages and total added sugars could be found in the DONALD cohort, such as urinary saccharine and acesulfame for low and no calorie sweetened beverages intake, and urinary sucrose for added sugar intake that were also positively associated to measures of adiposity. The FOODMETCH project was one of a kind. It combined explorative untargeted metabolomics with repeated data and biosamples from longitudinal cohort studies. Using cohorts of children was another unique strength of this project, as biomarkers of food intake had been understudied in children, where they would be very useful. With the approach of the FOODMETCH project, we confirmed that novel biomarkers can not only be found through experimental feeding studies, but also cost-efficiently through already existing biobanks in cohort studies. Future studies should focus on improvement of identification and annotation of mass spectrometry features from untargeted metabolomics, and in depth validate the potential biomarkers of food intake discovered in FOODMETCH.

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