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dc.contributor.authorRundblad, Amanda
dc.contributor.authorChristensen, Jacob J.
dc.contributor.authorHustad, Kristin S.
dc.contributor.authorBastani, Nasser E.
dc.contributor.authorOttestad, Inger
dc.contributor.authorHolven, Kirsten B.
dc.contributor.authorUlven, Stine M.
dc.date.accessioned2023-03-14T06:03:05Z
dc.date.available2023-03-14T06:03:05Z
dc.date.issued2023
dc.identifier.citationGenes & Nutrition. 2023 Mar 10;18(1):3
dc.identifier.urihttp://hdl.handle.net/10852/101419
dc.description.abstractBackground Metabotyping is a novel concept to group metabolically similar individuals. Different metabotypes may respond differently to dietary interventions; hence, metabotyping may become an important future tool in precision nutrition strategies. However, it is not known if metabotyping based on comprehensive omic data provides more useful identification of metabotypes compared to metabotyping based on only a few clinically relevant metabolites. Aim This study aimed to investigate if associations between habitual dietary intake and glucose tolerance depend on metabotypes identified from standard clinical variables or comprehensive nuclear magnetic resonance (NMR) metabolomics. Methods We used cross-sectional data from participants recruited through advertisements aimed at people at risk of type 2 diabetes mellitus (n = 203). Glucose tolerance was assessed with a 2-h oral glucose tolerance test (OGTT), and habitual dietary intake was recorded with a food frequency questionnaire. Lipoprotein subclasses and various metabolites were quantified with NMR spectroscopy, and plasma carotenoids were quantified using high-performance liquid chromatography. We divided participants into favorable and unfavorable clinical metabotypes based on established cutoffs for HbA1c and fasting and 2-h OGTT glucose. Favorable and unfavorable NMR metabotypes were created using k-means clustering of NMR metabolites. Results While the clinical metabotypes were separated by glycemic variables, the NMR metabotypes were mainly separated by variables related to lipoproteins. A high intake of vegetables was associated with a better glucose tolerance in the unfavorable, but not the favorable clinical metabotype (interaction, p = 0.01). This interaction was confirmed using plasma concentrations of lutein and zeaxanthin, objective biomarkers of vegetable intake. Although non-significantly, the association between glucose tolerance and fiber intake depended on the clinical metabotypes, while the association between glucose tolerance and intake of saturated fatty acids and dietary fat sources depended on the NMR metabotypes. Conclusion Metabotyping may be a useful tool to tailor dietary interventions that will benefit specific groups of individuals. The variables that are used to create metabotypes will affect the association between dietary intake and disease risk.
dc.language.isoeng
dc.rightsThe Author(s); licensee BioMed Central Ltd.
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleAssociations between dietary intake and glucose tolerance in clinical and metabolomics-based metabotypes
dc.typeJournal article
dc.date.updated2023-03-14T06:03:06Z
dc.creator.authorRundblad, Amanda
dc.creator.authorChristensen, Jacob J.
dc.creator.authorHustad, Kristin S.
dc.creator.authorBastani, Nasser E.
dc.creator.authorOttestad, Inger
dc.creator.authorHolven, Kirsten B.
dc.creator.authorUlven, Stine M.
dc.identifier.cristin2138285
dc.identifier.doihttps://doi.org/10.1186/s12263-023-00721-6
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.type.versionPublishedVersion
cristin.articleid3


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