Background

Diets predominantly consisting of plant-based foods are generally associated with lower risk for non-communicable diseases. However, emerging data indicate that unhealthful plant-based dietary patterns are related with raised disease risk.

In order to investigate diet-health associations, accurate information on food intake is necessary. Traditional assessment methods depend on self-reported data, which are prone to measurement error and bias. Specifically, plant-based foods are frequently misreported.

Biomarkers for food intake have been suggested as objective measures for food intake and shown potential. However, issues remain with specificity of biomarkers, and variability of metabolism. Multi-biomarker panels are a novel approach to improve the robustness of dietary assessment.

In PlantIntake, we focus on the plant components of mixed diets. The project considers the need for robust and high throughput tools to assess the quantity and quality of the whole range of plant food consumption, and improve or unmask diet-disease relationships.

Our goal is to derive and validate multi-biomarker panels for total, healthful and unhealthful plant-based food intake, and to explore the potential of combining biomarkers with self-reported data to improve the accuracy of the assessment of plant food intake.

Objectives

PlantIntake aims to improve the dietary assessment of plant food intake.

As a measure for plant-based dietary patterns, we will derive European plant-based diet indices (ePDIs) reflecting the quantity and quality of plant-based foods in a mixed diet.

For use in this project, but also afterwards other scientists in the biomarker field, we will develop a wide-coverage targeted analytical method for about 100 candidate intake biomarkers of plant foods and food groups.

Using samples and data from three European nutrition studies and applying the newly developed analytical method, we will derive multi-biomarker panels reflecting the quality of plant-based diet and validate them in an intervention study specifically performed for this purpose.

To further improve the accuracy of the assessment of plant food intake, we will explore the potential of combining biomarkers with self-reported data.

Workplan

The work plan of PlantIntake is organised in 4 scientific work packages (WPs) and 1 WP for coordination, data management, and dissemination.

WP1: Knowledge-based approach for the selection of biomarkers to reflect the intake of European plant-based dietary patterns

WP1 will provide

  • European plant-based diet indices (ePDIs) confirmed by associations with health outcomes,
  • a web-based tool for calculation of ePDIs,
  • an up-to-date list of validated biomarkers related to plant food intake.

This work package is lead by HMGU.

WP2: Biomarker quantification and machine learning to define parsimonious multi-biomarker panels

This WP will provide a wide-coverage targeted analytical method, that will be applied in 3 intervention (A-DIET) and cohort studies (KarMeN and B Cube). From this, new parsimonious multi-biomarker panels for assessing multiple dimensions of plant food intake will be developed.
This work package is lead by INRAE.

WP3: Validation of the multi-biomarker panels taking into account potential confounders

Work in this WP will validate that multi-biomarker panels reflect the quantity and quality of the plant-based part of the diet as described by the different indices. Also, it will generate knowledge on the applicability of alternative urine sampling strategies in nutrition studies. For this purpose, a specifically designed intervention study (acronym: PLAENTI) will be performed.
This work package is lead by MRI.

WP4: Combining biomarkers and self-reported data for improved accuracy of dietary assessment of plant food intake

Demonstration of how the multi-biomarker panel could be used to validate self-reported data and combined with self-reported data (calibration approach or composite intake score).
This work package is lead by UCD.

WP5: Coordination, data management, and dissemination (MRI, UCD, HMGU, INRAE, UBx, U_Cam)

Ensure/facilitate the successful realisation of the project.
This work package is lead by MRI.

 

To reach the goals of this project, our consortium has access to data and biosamples from 4 different studies: A-DIET (UCD, Ireland), KarMeN (MRI, Germany), B cube (UBx, France), and EPIC-Norfolk (U_Cam, UK). Taken together, we expect that the tools developed in this project will help improve our understanding of diet-health associations enabling more reliable dietary recommendations.

Expected Outcome

PlantIntake will develop and provide to the research community among others

  • a wide-coverage targeted analytical method that is robust and cost-effective to detect biomarkers of plant food intake in blood and urine
  • an easy-to-use web-based application to calculate ePDIs
  • Tools for improved assessment of plant food intake, such as
  • Multi-biomarker panels for healthful and unhealthful plant-based dietary patterns
  • Combinations of biomarkers with self-reported data (e.g. calibration equations, composite intake scores)

Taken together, we expect that the tools developed in this project will help improve our understanding of diet-health associations enabling more reliable dietary recommendations.

Duration:

Project Start:
1.5.2022

Project End:
30.4.2025

Project coordinator name:
Manuela Rist

Project coordinator country:
Germany

Project coordinator organization:
Max Rubner-Institut – Federal Research
Institute of Nutrition and Food (MRI)