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Review
. 2021 Dec 1;12(6):2333-2357.
doi: 10.1093/advances/nmab054.

Nutritional Metabolomics and the Classification of Dietary Biomarker Candidates: A Critical Review

Talha Rafiq  1   2 , Sandi M Azab  3   4 , Koon K Teo  2   5   6 , Lehana Thabane  5 , Sonia S Anand  2   5   6 , Katherine M Morrison  7 , Russell J de Souza  2   5 , Philip Britz-McKibbin  3
Affiliations
Review

Nutritional Metabolomics and the Classification of Dietary Biomarker Candidates: A Critical Review

Talha Rafiq et al. Adv Nutr. .

Abstract

Recent advances in metabolomics allow for more objective assessment of contemporary food exposures, which have been proposed as an alternative or complement to self-reporting of food intake. However, the quality of evidence supporting the utility of dietary biomarkers as valid measures of habitual intake of foods or complex dietary patterns in diverse populations has not been systematically evaluated. We reviewed nutritional metabolomics studies reporting metabolites associated with specific foods or food groups; evaluated the interstudy repeatability of dietary biomarker candidates; and reported study design, metabolomic approach, analytical technique(s), and type of biofluid analyzed. A comprehensive literature search of 5 databases (PubMed, EMBASE, Web of Science, BIOSIS, and CINAHL) was conducted from inception through December 2020. This review included 244 studies, 169 (69%) of which were interventional studies (9 of these were replicated in free-living participants) and 151 (62%) of which measured the metabolomic profile of serum and/or plasma. Food-based metabolites identified in ≥1 study and/or biofluid were associated with 11 food-specific categories or dietary patterns: 1) fruits; 2) vegetables; 3) high-fiber foods (grain-rich); 4) meats; 5) seafood; 6) pulses, legumes, and nuts; 7) alcohol; 8) caffeinated beverages, teas, and cocoas; 9) dairy and soya; 10) sweet and sugary foods; and 11) complex dietary patterns and other foods. We conclude that 69 metabolites represent good candidate biomarkers of food intake. Quantitative measurement of these metabolites will advance our understanding of the relation between diet and chronic disease risk and support evidence-based dietary guidelines for global health.

Keywords: dietary biomarkers; food exposures; metabolomics; nutrition; omics.

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Figures

FIGURE 1
FIGURE 1
PRISMA flow diagram of the literature search process. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.
FIGURE 2
FIGURE 2
Metabolites identified from (A) fruits, (B) vegetables and high-fiber (grain-rich) foods and (C) seafood by number of studies, type of study design, and type of biofluid.
FIGURE 3
FIGURE 3
Metabolites identified from (A) meats, pulses, legumes, and nuts, (B) alcohol, and (C) dealcoholized red wine by number of studies, type of study design, and type of biofluid. 1Metabolites in lower concentration compared to control.
FIGURE 4
FIGURE 4
Metabolites identified from (A) dairy-based foods, teas, cocoas, (B) coffee, and (C) sweet and sugary foods by number of studies, type of study design, and type of biofluid.
FIGURE 5
FIGURE 5
Metabolites identified from dietary patterns and other foods by number of studies, type of study design, and type of biofluid. DASH, Dietary Approaches to Stop Hypertension Trial.
FIGURE 6
FIGURE 6
Number of publications in nutritional metabolomics. Note: Data presented are based on the inclusion criteria of this review.
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