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Scope: The objectives are to develop a metabolomic-based model capable of classifying individuals into dietary patterns and to investigate the reproducibility of the model., Methods and Results: K-means cluster analysis is employed to derive dietary patterns using metabolomic data. Differences across the dietary patterns are examined using nutrient biomarkers. The model is used to assign individuals to a dietary pattern in an independent cohort, A-DIET Confirm (n = 175) at four time points. The stability of participants to a dietary pattern is assessed. Four dietary patterns are derived: moderately unhealthy, convenience, moderately healthy, and prudent. The moderately unhealthy and convenience patterns has lower adherence to the alternative healthy eating index (AHEI) and the alternative mediterranean diet score (AMDS) compared to the moderately healthy and prudent patterns (AHEI = 24.5 and 22.9 vs 26.7 and 28.4, p < 0.001). The dietary patterns are replicated in A-DIET Confirm, with good reproducibility across four time points. The stability of participants' dietary pattern membership ranged from 25.0% to 61.5%., Conclusion: The multivariate model classifies individuals into dietary patterns based on metabolomic data. In an independent cohort, the model classifies individuals into dietary patterns at multiple time points furthering the potential of such an approach for nutrition research., (© 2021 The Authors. Molecular Nutrition & Food Research published by Wiley-VCH GmbH.)

Scope: There is an increased interest in developing biomarkers of food intake to address some of the limitations associated with self-reported data. The objective is to identify biomarkers of apple intake, examine dose-response relationships, and agreement with self-reported data., Methods and Results: Metabolomic data from three studies are examined: an acute intervention, a short-term intervention, and a free-living cohort study. Fasting and postprandial urine samples are collected for analysis by 1 H-NMR and liquid chromatography-mass spectrometry (LC-MS). Calibration curves are developed to determine apple intake and classify individuals into categories of intake. Multivariate analysis of data reveals that levels of multiple metabolites increase significantly post-apple consumption, compared to the control food-broccoli. In the dose-response study, urinary xylose, epicatechin sulfate, and 2,6-dimethyl-2-(2-hydroxyethyl)-3,4-dihydro-2H-1-benzopyran increase as apple intake increases. Urinary xylose concentrations in a free-living cohort perform poorly at an individual level but are capable of ranking individuals in categories of intake., Conclusion: Urinary xylose exhibits a dose-response relationship with apple intake and performs well as a ranking biomarker in the population study. Other potential biomarkers are identified and future work will combine these with xylose in a biomarker panel which may allow for a more objective determination of individual intake., (© 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Scope: Fish intake is reported to be associated with certain health benefits; however, accurate assessment of fish intake is still problematic. The objective of this study is to identify fish intake biomarkers and examine relationships with health parameters in a free-living population., Methods and Results: In the NutriTech study, ten participants randomized into the fish group consume increasing quantities of fish for 3 days per week for 3 weeks. Urine is analyzed by NMR spectroscopy. Trimethylamine-N-oxide (TMAO), dimethylamine, and dimethyl sulfone are identified and display significant dose-response with intake (p < 0.05). Fish consumption yields a greater increase in urinary TMAO compared to red meat. Biomarker-derived fish intake is calculated in the National Adult Nutrition Survey cross-sectional study. However, the correlation between fish intake and TMAO (r = 0.148, p < 0.01) and that between fish intake and calculated fish intake (r = 0.142, p < 0.01) are poor. In addition, TMAO shows significantly positive correlation with serum insulin and insulin resistance in males and the relationship is more pronounced for males with high dietary fat intake., Conclusion: Urinary TMAO displays a strong dose-response relationship with fish intake; however, use of TMAO alone is insufficient to determine fish intake in a free-living population., (© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Scope: This study examines to what extent plasma linoleic acid (LA) is modified by adiposity, and explores any association between plasma LA, demographics, dietary intakes, markers of metabolic health, and haplotypes of the fatty acid desaturase (FADS) 1/2 genes., Methods and Results: A total of 820 participants with fasting blood samples from the Irish National Adult Nutrition Survey are studied. Plasma fatty acids are determined using GC-MS. Fifteen SNPs of FADS 1/2 genes are genotyped. Plasma LA decreases, while γ-linoleic acid and dihomo-γ-linoleic acid increases in overweight/obese participants (p ≤ 0.002). Participants in the highest quartile of plasma LA show decreased plasma markers of de novo lipogenesis, insulin resistance, and of inflammation (TNF-α, PAI-1) (p ≤ 0.005). Adiposity (waist circumference and body fat) is strongly inversely associated with plasma LA accounting for 11.8% of variance observed, which is followed by FADS1/2 haplotypes (3.9%), quantity and quality of carbohydrate intakes (3.8%), dietary PUFA intakes (3.7%), systolic blood pressure (3.6%), and age (3.2%)., Conclusion: Plasma LA is inversely associated with adiposity, followed by haplotypes of FADS1/2 genes, carbohydrate intakes, and dietary PUFA intakes. The association observed between plasma LA and adiposity may be linked to decreased de novo lipogenesis, insulin resistance, and inflammation., (© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Scope: There is a dearth of studies demonstrating the use of dietary biomarkers for determination of food intake. The objective of this study was to develop calibration curves for use in quantifying citrus intakes in an independent cohort., Methods and Results: Participants (n = 50) from the NutriTech food-intake study consumed standardized breakfasts for three consecutive days over three consecutive weeks. Orange juice intake decreased over the weeks. Urine samples were analyzed by NMR-spectroscopy and proline betaine was quantified and normalized to osmolality. Calibration curves were developed and used to predict citrus intake in an independent cohort; the Irish National Adult Nutrition Survey (NANS) (n = 565). Proline betaine displayed a dose-response relationship to orange juice intake in 24 h and fasting samples (p < 0.001). In a test set, predicted orange juice intakes displayed excellent agreement with true intake. There were significant associations between predicted intake measured in 24 h and fasting samples and true intake (r = 0.710-0.919). Citrus intakes predicted for the NANS cohort demonstrated good agreement with self-reported intake and this agreement improved following normalization to osmolality., Conclusion: The developed calibration curves successfully predicted citrus intakes in an independent cohort. Expansion of this approach to other foods will be important for the development of objective intake measurements., (© 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Scope: Classification of subjects into dietary patterns generally relies on self-reporting dietary data which are prone to error. The aim of the present study was to develop a model for objective classification of people into dietary patterns based on metabolomic data., Methods and Results: Dietary and urinary metabolomic data from the National Adult Nutrition Survey (NANS) was used in the analysis (n = 567). Two-step cluster analysis was applied to the urinary data to identify clusters. The subsequent model was used in an independent cohort to classify people into dietary patterns. Two distinct dietary patterns were identified. Cluster 1 was characterized by significantly higher intakes of breakfast cereals, low fat and skimmed milks, potatoes, fruit, fish and fish dishes (p < 0.05) representing a "healthy" cluster. Cluster 2 had significantly higher intakes of chips/processed potatoes, meat products, savory snacks and high-energy beverages (p < 0.05) representing an "unhealthy cluster". Classification was supported by significant differences in nutrient status (p < 0.05). Validation in an independent group revealed that 94% of subjects were correctly classified., Conclusion: The model developed was capable of classifying individuals into dietary patterns based on metabolomics data. Future applications of this approach could be developed for rapid and objective assignment of subjects into dietary patterns., (© 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Scope: Using pattern analysis, we investigated the relationship between plasma fatty acid patterns, dietary intake, and biomarkers of metabolic health using data from the Irish National Adult Nutrition Survey., Methods and Results: Plasma fatty acid patterns were derived from 26 plasma fatty acids using k-means cluster analysis. Four clusters were identified, each with a distinct fatty acid profile. Cluster 1 included high proportions of linoleic acid (LA) and low proportions of stearic acid (SA); cluster 2 was higher in n-3 polyunsaturated fatty acids and SA; the profile of cluster 3 was higher in very-long-chain saturated fatty acid (VLCSFA) and lower in α-linolenic acid (ALA) (cluster 3); while cluster 4 was higher in fatty acids related to de novo lipogenesis and 20:3n-6 and lower in LA (cluster 4). In general, cluster 4 was associated with adverse metabolic profile and higher metabolic risk (p < 0.033). Clusters 2 and 3 were associated with healthier and protective phenotypes (p < 0.033)., Conclusion: Distinct fatty acid patterns were identified which were related to demographics, dietary habits, and metabolic profile. A pattern higher in VLCSFA and lower in ALA was associated with healthier metabolic outcome., (© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)