3 years ago

Metabolomic-based identification of clusters that reflect dietary patterns

Metabolomic-based identification of clusters that reflect dietary patterns
Breige A. McNulty, Lorraine Brennan, Michael J. Gibney, Janette Walton, Helena Gibbons, Albert Flynn, Anne P. Nugent, Eibhlin Carr
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. The identification of dietary patterns generally relies on self-reporting dietary data which are prone to error. Using urinary metabolomics data, an objective dietary pattern classification model was developed. Two distinct dietary pattern clusters were identified, cluster one representing a healthy dietary pattern and cluster two representing an unhealthy dietary pattern.

Publisher URL: http://onlinelibrary.wiley.com/resolve/doi

DOI: 10.1002/mnfr.201601050

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