The foodomics approach for discovering biomarkers of food consumption in nutrition studies

Bordoni, Alessandra; Capozzi, Francesco

doi:10.1016/j.cofs.2015.07.005

Cited by 14 publications

(3 citation statements)

References 39 publications

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“…Such methods are known to suffer from relatively large systematic and random measurement errors, which may hamper discovery of potentially existing diet-disease relations or detect spurious associations (25,26). Metabolomics has become a valuable tool for identifying metabolites that could objectively reflect specific food exposures (27)(28)(29) or dietary patterns (30)(31)(32). Thus, it may provide a complement to self-reported dietary assessments and help to improve understanding of disease-related metabolic processes influenced by diet (33)(34)(35).…”

Section: Introductionmentioning

confidence: 99%

Plasma metabolites associated with healthy Nordic dietary indexes and risk of type 2 diabetes—a nested case-control study in a Swedish population

Shi

Brunius

Johansson

et al. 2018

The American Journal of Clinical Nutrition

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Section: Introductionmentioning

confidence: 99%

Plasma metabolites associated with healthy Nordic dietary indexes and risk of type 2 diabetes—a nested case-control study in a Swedish population

Shi

Brunius

Johansson

et al. 2018

The American Journal of Clinical Nutrition

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“…In fact, the intrinsic metabolome of food is different from what is detected after digestion and metabolization by the gut microbiota. [28,29] For this reason, in the last decade, NMR together with advanced chemometric tools has been employed for identifying urinary and blood metabolite profiles able to discriminate among food intake associated to specific dietary intervention. [30][31][32][33][34][35][36][37] From this point of view, NMR-based foodomics has been also suggested as one of the methods for gathering scientific evidence from clinical trials in dietary intervention studies, by discovering dietary biomarkers.…”

Section: Nuclear Magnetic Resonance (Nmr) and Green Foodomicsmentioning

confidence: 99%

The NMR added value to the green foodomics perspective: Advances by machine learning to the holistic view on food and nutrition

Picone

Mengucci

Capozzi

2022

Magnetic Reson in Chemistry

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Food is a complex matter, literally. From production to functionalization, from nutritional quality engineering to predicting effects on health, the interest in finding an efficient physicochemical characterization of food has boomed in recent years. The sheer complexity of characterizing food and its interaction with the human organism has however made the use of data driven approaches in modeling a necessity. High‐throughput techniques, such as nuclear magnetic resonance (NMR) spectroscopy, are well suited for omics data production and, coupled with machine learning, are paving a promising way of modeling food–human interaction. The foodomics approach sets the framework for omic data integration in food studies, in which NMR experiments play a key role. NMR data can be used to assess nutritional qualities of food, helping the design of functional and sustainable sources of nutrients; detect biomarkers of intake and study how they impact the metabolism of different individuals; study the kinetics of compounds in foods or their by‐products to detect pathological conditions; and improve the efficiency of in silico models of the metabolic network.

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“…It has been estimated that the various foods consumed by humans contain more than 25,000 compounds [24], with concentrations that can differ by several orders of magnitude. In practice, food composition tables do not reflect properly the content of nutrients/bioactives introduced with the diet [25].…”

Section: The Food-intrinsic Metabolomementioning

confidence: 99%

NMR-Based Metabolomics: The Foodome and the Assessment of Dietary Exposure as a Key Step to Evaluate the Effect of Diet on Health

Capozzi¹

2018

Modern Magnetic Resonance

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NMR-based metabolomics has gained important insight into the associations between the metabolic status and health, as metabolomics signatures are found in blood, urine, stools, or saliva, differentiating healthy subjects from those affected by diseases or disorders. Although health status has been linked to diet, a measurable fingerprint is rarely found within the metabolome, demonstrating that the diet is curing or, at least, is modifying the subject metabolome away from or closer to a healthy status. The success in finding the correlation between the metabolome and a diet-related disease has, as the main obstacle, the inability to characterize the actual diet followed by the subject. Thus, a big scientific effort has been launched to find metabolite patterns which are characterizing precisely the personal food consumption in order to classify people according to their actual diet. Most of the studies based on NMR-metabolomics are focused on finding biomarkers within the dietary exposome, e.g., originating from food or gut microbiota, without a specific focus on the endogenous metabolome. The main drawback in such approach is a combination of: (i) the actual composition of the meal, (ii) the bioaccessibility of bioactive compounds, and (iii) the processing capability of the gut microbiota. In this chapter, these three aspects are illustrated, where NMR spectroscopy (effectively or potentially) gains relevant information in the discovery of biomarkers for the true food consumption, as a preliminary step in successful "dietary effect studies."

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The foodomics approach for discovering biomarkers of food consumption in nutrition studies

Cited by 14 publications

References 39 publications

Plasma metabolites associated with healthy Nordic dietary indexes and risk of type 2 diabetes—a nested case-control study in a Swedish population

Plasma metabolites associated with healthy Nordic dietary indexes and risk of type 2 diabetes—a nested case-control study in a Swedish population

The NMR added value to the green foodomics perspective: Advances by machine learning to the holistic view on food and nutrition

NMR-Based Metabolomics: The Foodome and the Assessment of Dietary Exposure as a Key Step to Evaluate the Effect of Diet on Health

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