Metabolomics signatures of sweetened beverages and added sugar are related to anthropometric measures of adiposity in young individuals: results from a cohort study.

Metabolite biomarkers added sugar adiposity metabolomics sweetened beverages

Journal

The American journal of clinical nutrition
ISSN: 1938-3207
Titre abrégé: Am J Clin Nutr
Pays: United States
ID NLM: 0376027

Informations de publication

Date de publication:
24 Jul 2024
Historique:
received: 26 01 2024
revised: 11 07 2024
accepted: 22 07 2024
medline: 27 7 2024
pubmed: 27 7 2024
entrez: 26 7 2024
Statut: aheadofprint

Résumé

The associations of sweetened beverages (SBs) and added sugar (AS) intake with adiposity are still debated. Metabolomics could provide insights into the mechanisms linking their intake to adiposity. We aimed (1) to identify metabolomics biomarkers of intake of low and no-calorie sweetened beverages (LNCSB), sugar-sweetened beverages (SSB), and AS, and (2) to investigate their associations with body mass index, body fat percentage, and waist circumference. We analyzed three datasets from the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) cohort study, of children who provided two urine samples (n = 297), adolescents who provided a single urine sample (n = 339), and young adults who provided a single plasma sample (n = 195). Urine and plasma were analyzed by untargeted metabolomics. Dietary intakes were assessed using 3-day weighed dietary records. The random forest, partial least squares, and least absolute shrinkage and selection operator were jointly employed for metabolite selection. We examined associations of intakes with metabolites and anthropometric measures using linear and mixed-effects regression. In adolescents, LNCSB were positively associated with acesulfame, β = 0.0012, 95% confidence interval, CI (0.0006, 0.0019) and saccharin β = 0.0009, 95% CI (0.0002, 0.0015). In children, the association was observed with saccharin β = 0.0016, 95% CI (0.0005, 0.0027). In urine and plasma, SSB were positively associated with 1-methylxanthine, β = 0.0005, 95% CI (0.0003, 0.0008), β = 0.0010, 95% CI (0.0004, 0.0015) and 5-acetylamino-6-amino-3-methyluracil, β = 0.0005, 95% CI (0.0002, 0.0008), β = 0.0009, 95% CI (0.0003, 0.0014), respectively. AS was associated with urinary sucrose, β = 0.0095, 95% CI (0.0069, 0.0121) in adolescents. Some of the food-related metabolic profiles were also associated with adiposity measures. We identified SBs- and AS-related metabolites, which may be important for understanding the interplay between these intakes and adiposity in young individuals.

Sections du résumé

BACKGROUND BACKGROUND
The associations of sweetened beverages (SBs) and added sugar (AS) intake with adiposity are still debated. Metabolomics could provide insights into the mechanisms linking their intake to adiposity.
OBJECTIVES OBJECTIVE
We aimed (1) to identify metabolomics biomarkers of intake of low and no-calorie sweetened beverages (LNCSB), sugar-sweetened beverages (SSB), and AS, and (2) to investigate their associations with body mass index, body fat percentage, and waist circumference.
METHODS METHODS
We analyzed three datasets from the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) cohort study, of children who provided two urine samples (n = 297), adolescents who provided a single urine sample (n = 339), and young adults who provided a single plasma sample (n = 195). Urine and plasma were analyzed by untargeted metabolomics. Dietary intakes were assessed using 3-day weighed dietary records. The random forest, partial least squares, and least absolute shrinkage and selection operator were jointly employed for metabolite selection. We examined associations of intakes with metabolites and anthropometric measures using linear and mixed-effects regression.
RESULTS RESULTS
In adolescents, LNCSB were positively associated with acesulfame, β = 0.0012, 95% confidence interval, CI (0.0006, 0.0019) and saccharin β = 0.0009, 95% CI (0.0002, 0.0015). In children, the association was observed with saccharin β = 0.0016, 95% CI (0.0005, 0.0027). In urine and plasma, SSB were positively associated with 1-methylxanthine, β = 0.0005, 95% CI (0.0003, 0.0008), β = 0.0010, 95% CI (0.0004, 0.0015) and 5-acetylamino-6-amino-3-methyluracil, β = 0.0005, 95% CI (0.0002, 0.0008), β = 0.0009, 95% CI (0.0003, 0.0014), respectively. AS was associated with urinary sucrose, β = 0.0095, 95% CI (0.0069, 0.0121) in adolescents. Some of the food-related metabolic profiles were also associated with adiposity measures.
CONCLUSIONS CONCLUSIONS
We identified SBs- and AS-related metabolites, which may be important for understanding the interplay between these intakes and adiposity in young individuals.

Identifiants

pubmed: 39059709
pii: S0002-9165(24)00644-0
doi: 10.1016/j.ajcnut.2024.07.021
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024. Published by Elsevier Inc.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no competing interest.

Auteurs

Samuel Muli (S)

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

Maike E Schnermann (ME)

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

Mira Merdas (M)

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

Jodi Rattner (J)

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

David Achaintre (D)

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

Ines Perrar (I)

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

Jantje Goerdten (J)

Department of Epidemiological Methods and Etiological Research, Leibniz Institute for Prevention Research and Epidemiology (BIPS), Bremen, Germany.

Ute Alexy (U)

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

Augustin Scalbert (A)

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

Matthias Schmid (M)

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

Anna Floegel (A)

Department of Epidemiological Methods and Etiological Research, Leibniz Institute for Prevention Research and Epidemiology (BIPS), Bremen, Germany; Section of Dietetics, Faculty of Agriculture and Food Sciences, Hochschule Neubrandenburg, Neubrandenburg, Germany.

Pekka Keski-Rahkonen (P)

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

Kolade Oluwagbemigun (K)

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

Ute Nöthlings (U)

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

Classifications MeSH