Now showing 1 - 3 of 3
  • Publication
    Estimation of chicken intake using metabolomics derived markers
    Background: Improved assessment of meat intake using metabolomics derived markers can provide objective data and could be helpful in clarifying proposed associations between meat intake and health.Objective: The objective was to identify novel markers of chicken intake using a metabolomics approach, and use markers to determine intake in an independent cohort. Methods: Ten participants (age, 62 y; BMI, 28.25 Kg/m2) in NutriTech Food Intake Study (NCT01684917) consumed increased amounts of chicken from 88 to 290 g/day over three weeks. Urine and blood samples were analyzed by NMR and MS, respectively. Multivariate data analysis was performed to identify markers associated with chicken intake. A calibration curve was built based on dose response association using NutriTech data. Bland and Altman analysis evaluated the agreement between reported and calculated chicken intake in National Adult Nutrition Survey (NANS) cohort. Results: Multivariate data analysis of postprandial and fasting urine samples collected in NutriTech revealed good discrimination between high (290 g/day) and low (88 g/day)  chicken intakes. Urinary metabolite profiles showed differences in metabolite levels between low and high chicken intakes. Examining metabolite profiles revealed guanidoacetate significantly increased from 1.47 to 3.66 mmol/L following increasing chicken intake from 88 to 290 g/day (P < 0.01). Using a calibration curve developed from NutriTech study, chicken intake was calculated in NANS, where chicken consumers had higher guanidoacetate excretion (0.70 mmol/L) than non-consumers (0.47 mmol/L) (P < 0.01). Bland and Altman analysis revealed good agreement between reported and calculated intakes with a bias of -30.2g/day. Plasma metabolite analysis demonstrated that 3-methylhistidine (3-Meth-His) was a more suitable indicator of chicken intake compared with 1-methylhistidine (1-Meth-His). Conclusions: Guanidoacetate was successfully identified and confirmed as a marker of chicken intake, and importantly its measurement in fasting urine samples could be used to determine chicken intake in a free-living population.
    Scopus© Citations 22  552
  • Publication
    Metabolomic-based identification of clusters that reflect dietary patterns
    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 and fish, 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.
    Scopus© Citations 24  697
  • Publication
    Demonstration of the utility of biomarkers for dietary intake assessment; proline betaine as an example
    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 24h 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 24h 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.
      843Scopus© Citations 57