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Report

Teaser, summary, work performed and final results

Periodic Reporting for period 3 - A-DIET (Metabolomics based biomarkers of dietary intake- new tools for nutrition research)

Teaser

Summary

The current approaches for assessing dietary intake have a number of well documented limitations and can be influenced by random and systematic errors. Examples of such methods include 24-hour recalls, food records and food frequency questionnaires. The inaccuracy associated with dietary assessment is one of the main stumbling blocks in assessing the links between diet and health. These poor estimates of dietary exposure are a critical problem in the field of nutritional epidemiology. The overarching objective of A-DIET is to develop strategies for assessment of dietary intake.

A-DIET aims to develop novel strategies, using a combined approach of metabolomic biomarker data and dietary data to enhance accuracy of dietary assessment. The development of a dietary assessment tool will be the ultimate output of the project which will be used to obtain an accurate assessment of dietary intake and subsequently will allow investigations into relationships between diet, health and disease. Such a tool will allow an accurate assessment of dietary intake and will be able to (1) estimate dietary intake based on biomarker and dietary data and (2) classify people into a dietary pattern based on biomarker profiles. Statistical methods have been identified and will be developed in order to achieve this, which will be reported on in the next period.

Such advances will allow epidemiologists to examine the relationship between diet and health and develop clear public health messages with regard to diet and health. At the halfway stage, A-DIET has already led to a number of advancements in dietary biomarker identification and has demonstrated for the first time the possibility of estimating food intake from a urinary biomarker level. These concepts and methods are game changing in the field of food intake biomarkers.

Work performed

At the midterm point significant progress has been made towards the objectives set out in A-DIET. Three human intervention studies were proposed for the successful completion of the project, with two completed. The first study (Discovery study) (WP1), involved recruiting participants (n=20, 8 males and 12 females) with the aim of identifying novel dietary biomarkers of 10 commonly consumed foods through a dietary intervention. A number of putative biomarkers of commonly consumed foods have been identified using metabolomics approaches that were established in the group combined with statistical methods.

The second study (WP1), the Validation study is also complete (n=61). The aim of this study is to validate the putative biomarkers identified in the Discovery study using a targeted metabolomics approach. The third study (WP2), CONFIRM study is currently underway and will be used to examine dietary patterns.

In addition, data became available in the research group that enabled us to test the utility of the biomarkers in determination of food intake in a proof of concept study (POC), which resulted in a publication in a peer-reviewed journal. The study was extremely successful as using a urinary biomarker to determine food intake. Using a controlled dietary intervention approach participants consumed standardized breakfasts where the intake of orange juice decreased over a 3 week period. Calibration curves were constructed with the urinary proline betaine concentration against the known orange juice intake (g/day). Excellent agreement was observed between estimated intakes and actual intakes with the agreement assessed through Bland and Altman analysis. A correlation of 0.92 was reported between actual intake and predicted intake, again highlighting the high level of agreement. Further to this, the ability of the biomarker to estimate intake was tested in an independent cross sectional study. Using the calibration curves determined in the controlled intervention study the intake (g/day) was estimated from the urinary concentration of proline betaine. There was excellent agreement between the self-reported intake and the estimated intake from the biomarker.
The significance of this study lies with the fact that it clearly demonstrates how biomarkers may be used in a larger cohort/population setting to estimate food intake. In addition, a second POC study developed a method that allows us to objectively classify people into dietary patterns based on their metabolomics data; using a cross sectional study design the metabolomics data was used to derive a model which could classify subjects into either a healthy dietary pattern or an unhealthy dietary pattern. The healthy dietary pattern was characterised by higher intakes of breakfast cereals and porridge, low fat and skimmed milks, fruit and fish , while the unhealthy dietary pattern was classified by higher intakes of chips and processed potatoes, savoury snacks and meat products. Furthermore, the dietary patterns were supported by significant differences in blood parameters such as higher folate and 25(OH)-vitamin D in the healthy dietary pattern. The developed model was then tested in an independent study and it was found that it had a high correct classification rate. Further development of the model to include a more diverse range of biomarkers and more dietary patterns would be an important next step. These POC studies clearly demonstrate concepts for dietary assessment and on the whole are game changing for the field of food intake biomarkers.

WP3 has also progressed significantly at the midterm point. The overall objectives of this WP are to develop methods and a tool for integration of dietary and biomarker data that will be freely available to the wider scientific community. Methods have been identified to successfully combine dietary and biomarker data. A review paper of such methods is currently in preparation.
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Final results

The methods developed in the proof of concept studies undertaken clearly demonstrate these concepts for dietary assessment and on the whole are beyond the state of the art for the field of food intake and biomarkers.
The ultimate output from A-DIET will be a dietary assessment tool which will allow accurate assessment of dietary intake. The tool will be able to estimate dietary intake based on biomarker and dietary data and classify people into a dietary pattern based on biomarker profiles. We have made significant progress in achieving this goal.