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

dietary biomarkers metabolite patterns metabolites metabolomics ultra-processed foods

Journal

The Journal of nutrition
ISSN: 1541-6100
Titre abrégé: J Nutr
Pays: United States
ID NLM: 0404243

Informations de publication

Date de publication:
25 Sep 2024
Historique:
received: 02 08 2024
revised: 16 09 2024
accepted: 22 09 2024
medline: 28 9 2024
pubmed: 28 9 2024
entrez: 27 9 2024
Statut: aheadofprint

Résumé

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. To investigate urine and plasma metabolomic biomarkers of UPF intake in adolescents and young adults. 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. 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" (β = 0.042, 95% confidence interval, [CI]: 0.014, 0.070) and one plasma metabolite pattern, "lipids, xenobiotics, and amino acids" (β = 0.074, 95% CI: 0.031, 0.117) showed positive association with UPF intake. Both patterns shared 29 metabolites, mostly of xenobiotic metabolism. 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.

Sections du résumé

BACKGROUND 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 OBJECTIVE
To investigate urine and plasma metabolomic biomarkers of UPF intake in adolescents and young adults.
METHODS 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 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" (β = 0.042, 95% confidence interval, [CI]: 0.014, 0.070) and one plasma metabolite pattern, "lipids, xenobiotics, and amino acids" (β = 0.074, 95% CI: 0.031, 0.117) showed positive association with UPF intake. Both patterns shared 29 metabolites, mostly of xenobiotic metabolism.
CONCLUSIONS 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.

Identifiants

pubmed: 39332770
pii: S0022-3166(24)01040-X
doi: 10.1016/j.tjnut.2024.09.023
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper

Auteurs

Samuel Muli (S)

Unit of Nutritional Epidemiology, Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany.

Annika Blumenthal (A)

Unit of Nutritional Epidemiology, Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany.

Christina-Alexandra Conzen (CA)

Unit of Nutritional Epidemiology, Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany.

Maike Elena Benz (ME)

Unit of Nutritional Epidemiology, Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany.

Ute Alexy (U)

Unit of Nutritional Epidemiology, Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany.

Matthias Schmid (M)

Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), University Hospital Bonn, Bonn, Germany.

Pekka Keski-Rahkonen (P)

International Agency for Research on Cancer (IARC), Lyon, France.

Anna Floegel (A)

Section of Dietetics, Faculty of Agriculture and Food Sciences, Hochschule Neubrandenburg, Neubrandenburg, Germany.

Ute Nöthlings (U)

Unit of Nutritional Epidemiology, Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany. Electronic address: noethlings@uni-bonn.de.

Classifications MeSH