Metabolomic‐Based Approach to Identify Biomarkers of Apple Intake

McNamara, A.; Collins, Cassandra; Harsha, P.S.C. Sri; González-­Peña, Diana; Gibbons, Helena; McNulty, Breige; Nugent, Anne P.; Walton, Janette; Flynn, Albert

doi:10.1002/mnfr.201901158

Cited by 19 publications

(8 citation statements)

References 48 publications

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“…Measurements for biomarkers are available: citrate, hippurate, and proline betaine [ 19 ]. Full details on the study design and its participants are provided in [ 10 ]. While our model does not include study participants’ demographics it is worth noting that future work could examine how to incorporate information such as age and sex, as needed.…”

Section: Resultsmentioning

confidence: 99%

multiMarker: software for modelling and prediction of continuous food intake using multiple biomarkers measurements

et al. 2021

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Background Metabolomic biomarkers offer potential for objective and reliable food intake assessment, and there is growing interest in using biomarkers in place of or with traditional self-reported approaches. Ongoing research suggests that multiple biomarkers are associated with single foods, offering great sensitivity and specificity. However, currently there is a dearth of methods to model the relationship between multiple biomarkers and single food intake measurements. Results Here, we introduce multiMarker, a web-based application based on the homonymous R package, that enables one to infer the relationship between food intake and two or more metabolomic biomarkers. Furthermore, multiMarker allows prediction of food intake from biomarker data alone. multiMarker differs from previous approaches by providing distributions of predicted intakes, directly accounting for uncertainty in food intake quantification. Usage of both the R package and the web application is demonstrated using real data concerning three biomarkers for orange intake. Further, example data is pre-loaded in the web application to enable users to examine multiMarker’s functionality. Conclusion The proposed software advance the field of Food Intake Biomarkers providing researchers with a novel tool to perform continuous food intake quantification, and to assess its associated uncertainty, from multiple biomarkers. To facilitate widespread use of the framework, multiMarker has been implemented as an R package and a Shiny web application.

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Section: Resultsmentioning

confidence: 99%

multiMarker: software for modelling and prediction of continuous food intake using multiple biomarkers measurements

et al. 2021

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“…The most common method used in clinical medicine to rapidly assess changes in magnesium status is the measurement of serum magnesium concentrations, but serum levels have little correlation with systemic magnesium levels or concentrations in specific tissues [10] . Some researchers have also chosen to use metabolites of foods as markers of certain nutrient intakes [66] . Some researchers use subjective dietary recall for dietary assessment [67] .…”

Section: Prospectivementioning

confidence: 99%

Changes in the urinary proteome of rats after short-term intake of magnesium threonate

Shen,

Yang,

Wang

et al. 2023

Preprint

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Magnesium is an important mineral in living organisms and has multiple functions in the human body, wherein it plays an important therapeutic and preventive role in a variety of diseases. In the present study, urine samples of rats before and after gavage of magnesium threonate were collected, and the urinary proteome was identified using the LC-MS/MS technique and analyzed using various databases. The results illustrated that the urinary proteome of rats was significantly altered after short-term intake of magnesium supplements and that the differential proteins and the biological functions were related to magnesium. This study innovatively establishes a method to study nutrients from the perspective of urine proteomics. This work demonstrates that the urinary proteome is capable of reflecting the effects of nutrient intake on the organism in a more systematic and comprehensive manner and has the potential to provide clues for clinical nutrition research and practice.

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“…Another food item that has been subject to NMR foodomics studies is apple. McNamara et al [41] employed NMR metabolomics to analyze urine samples were collected 0, 2, 4 and 24 h after intake of apple, and NMR revealed that apple intake was associated with a pronounced increase in urinary concentration of xylose as well as acetylsalicylate. Xylose is among the main sugars found in apple, and the study demonstrates the potential of NMR foodomics in biomarker discovery.…”

Section: Specific Dietary Itemsmentioning

confidence: 99%

NMR foodomics in the assessment of diet and effects beyond nutrients

Bertram

2022

Current Opinion in Clinical Nutrition &Amp; Metabolic Care

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Purpose of reviewThis review provides an overview of most recent research studies employing nuclear magnetic resonance (NMR)-based metabolomics in the assessment of effects of diet and food ingestion.Recent findingsNMR metabolomics is a useful tool in the elucidation of specific diets, for example, the Mediterranean diet, the New Nordic diet types, and also for comparing vegan, vegetarian and omnivore diets where specific diet-linked metabolite perturbations have been identified. Another core area where NMR metabolomics is employed involves research focused on examining specific food components or ingredients, including dietary fibers and other functional components. In several cases, NMR metabolomics has aided to document how specific food components exert effects on the metabolic activity of the gut microbiota. Research has also demonstrated the potential use of NMR metabolomics in assessing diet quality and interactions between specific food components such as meat and diet quality. The implications of these findings are important as they address that background diet can be decisive for if food items turn out to exert either harmful or health-promoting effects.SummaryNMR metabolomics can provide important mechanistic insight and aid to biomarker discovery with implications for compliance and food registration purposes.

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Metabolomic‐Based Approach to Identify Biomarkers of Apple Intake

Cited by 19 publications

References 48 publications

multiMarker: software for modelling and prediction of continuous food intake using multiple biomarkers measurements

multiMarker: software for modelling and prediction of continuous food intake using multiple biomarkers measurements

Changes in the urinary proteome of rats after short-term intake of magnesium threonate

NMR foodomics in the assessment of diet and effects beyond nutrients

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