Literature DB >> 36152148

Discovery of Food Intake Biomarkers Using Metabolomics.

Leticia Lacalle-Bergeron1, David Izquierdo-Sandoval1, Juan V Sancho1, Tania Portolés2.   

Abstract

Due to the high impact of diet exposure on health, it is crucial the generation of robust data of regular dietary intake, hence improving the accuracy of dietary assessment. The metabolites derived from individual food or group of food have great potential to become biomarkers of food intake (BFIs) and provide more objective food consumption measurements.Herein, it is presented an untargeted metabolomic workflow for the discovery BFIs in blood and urine samples, from the study design to the biomarker identification. Samples are analyzed by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). A wide variety of compounds are covered by separate analyses of medium to nonpolar molecules and polar metabolites based on two LC separations as well as both positive and negative electrospray ionization. The main steps of data treatment of the comprehensive data sets and statistical analysis are described, as well as the principal considerations for the BFI identification.
© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Biomarkers of food intake; Dietary assessment; Ion mobility; LC-HRMS; Plasma metabolites; Untargeted metabolomics; Urinary metabolites

Mesh:

Substances:

Year:  2023        PMID: 36152148     DOI: 10.1007/978-1-0716-2699-3_4

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  7 in total

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Review 3.  The role of metabolomics in determination of new dietary biomarkers.

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Review 5.  Analytical techniques for metabolomic studies: a review.

Authors:  Karen Segers; Sven Declerck; Debby Mangelings; Yvan Vander Heyden; Ann Van Eeckhaut
Journal:  Bioanalysis       Date:  2019-12       Impact factor: 2.681

Review 6.  The importance of experimental design and QC samples in large-scale and MS-driven untargeted metabolomic studies of humans.

Authors:  Warwick B Dunn; Ian D Wilson; Andrew W Nicholls; David Broadhurst
Journal:  Bioanalysis       Date:  2012-09       Impact factor: 2.681

7.  LipidCCS: Prediction of Collision Cross-Section Values for Lipids with High Precision To Support Ion Mobility-Mass Spectrometry-Based Lipidomics.

Authors:  Zhiwei Zhou; Jia Tu; Xin Xiong; Xiaotao Shen; Zheng-Jiang Zhu
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  7 in total

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