Abstract
Assessment of dietary intake remains a large challenge in nutrition studies. The application of food intake biomarkers is a promising approach to complement widely used self-reported intake assessments and to improve accuracy. The development of metabolomics has enabled the discovery of many potential food intake biomarkers, but their applications are still limited. We aim to develop a semi-quantitative LC-MS/MS procedure to analyze a panel of plasma metabolites reflecting dietary exposure in a wide context. Our approach relies on a multi-analyte targeted LC-MS/MS method using a LC-QTRAP and commercially available reference compounds. A panel of 347 metabolites was selected, representing dietary intake (fruits and vegetables, coffee, tea, heat-treated food, wholegrain cereals, berries, cruciferous vegetables, and seafood) and key metabolites in the endogenous metabolism (fatty acids, amino acids, cholesterol metabolism, Krebs cycle, bile acids, and microbial metabolism) which are affected by specific diets, as well as lifestyle exposures, such as smoking and alcohol consumption. The application of this panel will help in assessing dietary exposures and their relationships to health outcomes. We will present the status of the work.
Author Contributions
Conceptualization, R.L. and O.S.; methodology, M.A. and R.G.-D.; software, S.N.; validation, M.A.; formal analysis, G.D.P. and M.A.; data curation, S.N.; writing—original draft preparation, S.N.; writing—review and editing, M.A., O.S. and R.L.; funding acquisition, R.G.-D. and R.L. All authors have read and agreed to the published version of the manuscript.
Funding
S.N. received funding from Formas (Dnr: 2019-02201) under the umbrella of the European Joint Programming Initiative “A Healthy Diet for a Healthy Life” (JPI HDHL) and of the ERA-NET Cofund HDHL INTIMIC (GA N° 727565 of the EU Horizon 2020 Research and Innovation Programme). R.G.-D. is recipient of a “Miguel Servet” fellowship (CP21/00120) funded by “Instituto de Salud Carlos III”. R.L. is funded by the Swedish Research Council (no 2019-12064).
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Data sharing is not applicable to this abstract.
Conflicts of Interest
The authors declare no conflict of interest.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).