Association of three different dietary patterns with the metabolomic profiles of children: the BiomarKid project

Abstract Background and aims Metabolomics offers a promising approach to objectively assess food intake and nutrition-related health risks. Three different dietary patterns (DPs) associated with cardiometabolic health were previously identified at 2 years of age in the EU Childhood Obesity Project and were used as reference patterns for longitudinal scoring throughout childhood: “Core foods” DP (CORE), rich in vegetables, fruits, fish, meat, and olive oil; “Animal protein sources” DP (PROT), high in white meat, processed meat, flavoured milk, snacks, fish, and vegetables; and “Poor-quality fats and sugars” DP (F&S), high in soft cheese, butter, added sugars, and juices. This study aimed to identify metabolomic signatures of these DPs. Methods Targeted liquid chromatography-tandem mass spectrometry quantified 236 metabolites in blood samples collected at ages 5.5 and 8 years from 421 children, with 156 children contributing samples at both timepoints. Associations between DPs and metabolite levels were assessed using adjusted linear mixed models. Metabolite set enrichment analysis (MSEA) was conducted across 23 distinct sets of related metabolites. Results Forty-eight metabolites associated with DPs, although they did not remain significant after false discovery rate correction. Five showed associations with multiple DPs. For example, LPC a C22:6 showed associations with opposite effect directions for CORE and F&S (β = 0.108, p = 0.038, q = 0.539; β=− 0.140, p = 0.025, q = 0.484, respectively). The ratio PC aa C40:5/PC aa C40:6 was negatively associated with CORE (β=− 0.207, p = 3.81 × 10 − 5 , q = 0.016) and positively with F&S (β = 0.136, p = 0.020, q = 0.463). CORE and F&S showed opposite directions in seven of the eight metabolite groups significant in the MSEA. A group of phosphatidylcholines containing polyunsaturated fatty acids (including DHA) was positively associated with PROT (NES: 1.837, p = 0.001, q = 0.017). Conclusions Distinct metabolite groups were associated with adherence to specific dietary patterns in children. Consistent findings across metabolite classes and dietary components suggest biologically plausible metabolomic signatures that require confirmation in independent cohorts.

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Journal
European Journal of Nutrition
Published
2026-09-12
DOI
https://doi.org/10.1007/s00394-026-04098-1
Primary Topic
Metabolomics and Mass Spectrometry Studies
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article
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0.00

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article

Association of three different dietary patterns with the metabolomic profiles of children: the BiomarKid project

Dariusz Gruszfeld, Hans Demmelmair, Klaus Kratochwill, Joaquín Escribano et al.
European Journal of Nutrition
Metabolomics and Mass Spectrometry Studies
article

Association of three different dietary patterns with the metabolomic profiles of children: the BiomarKid project

Dariusz Gruszfeld, Hans Demmelmair, Klaus Kratochwill, Joaquín Escribano, Verónica Luque, Gabi Kastenmüller, Natàlia Ferré, Elvira Verduci, Jeannie Horak, Irina Gheorghita, Lara Vehovec, Berthold Koletzko, Mariona Gispert-Llauradó, Veit Grote
article en

Abstract

Abstract Background and aims Metabolomics offers a promising approach to objectively assess food intake and nutrition-related health risks. Three different dietary patterns (DPs) associated with cardiometabolic health were previously identified at 2 years of age in the EU Childhood Obesity Project and were used as reference patterns for longitudinal scoring throughout childhood: “Core foods” DP (CORE), rich in vegetables, fruits, fish, meat, and olive oil; “Animal protein sources” DP (PROT), high in white meat, processed meat, flavoured milk, snacks, fish, and vegetables; and “Poor-quality fats and sugars” DP (F&S), high in soft cheese, butter, added sugars, and juices. This study aimed to identify metabolomic signatures of these DPs. Methods Targeted liquid chromatography-tandem mass spectrometry quantified 236 metabolites in blood samples collected at ages 5.5 and 8 years from 421 children, with 156 children contributing samples at both timepoints. Associations between DPs and metabolite levels were assessed using adjusted linear mixed models. Metabolite set enrichment analysis (MSEA) was conducted across 23 distinct sets of related metabolites. Results Forty-eight metabolites associated with DPs, although they did not remain significant after false discovery rate correction. Five showed associations with multiple DPs. For example, LPC a C22:6 showed associations with opposite effect directions for CORE and F&S (β = 0.108, p = 0.038, q = 0.539; β=− 0.140, p = 0.025, q = 0.484, respectively). The ratio PC aa C40:5/PC aa C40:6 was negatively associated with CORE (β=− 0.207, p = 3.81 × 10 − 5 , q = 0.016) and positively with F&S (β = 0.136, p = 0.020, q = 0.463). CORE and F&S showed opposite directions in seven of the eight metabolite groups significant in the MSEA. A group of phosphatidylcholines containing polyunsaturated fatty acids (including DHA) was positively associated with PROT (NES: 1.837, p = 0.001, q = 0.017). Conclusions Distinct metabolite groups were associated with adherence to specific dietary patterns in children. Consistent findings across metabolite classes and dietary components suggest biologically plausible metabolomic signatures that require confirmation in independent cohorts.

European Journal of NutritionVol. 65(7)
Generalitat de Catalunya (ES), Chulalongkorn University (TH), University of Milan (IT), Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico (IT), Helmholtz Zentrum München (DE), LMU Klinikum (DE), German Center for Pediatric and Adolescent Rheumatology (DE), Ospedale Maggiore (IT), Children's Memorial Health Institute (PL), Institute for Research in Biomedicine (ES), Hospital Universitari Sant Joan de Reus (ES), Universitat Rovira i Virgili (ES), Medical University of Vienna (AT), Ludwig-Maximilians-Universität München (DE)
Institut d'Investigació Sanitària Pere Virgili, European Commission, Bundesministerium für Bildung und Forschung, Generalitat de Catalunya, Österreichische Forschungsförderungsgesellschaft, Universitat Rovira i Virgili, National Institutes of Health, Instituto de Salud Carlos III, FP7 Food, Agriculture and Fisheries, Biotechnology
Zero hunger
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Metabolomics and Mass Spectrometry Studies
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