Metabotyping for the development of tailored dietary advice solutions in a European population: the Food4Me study

Clare B. O'Donovan, Marianne C. Walsh, Clara Woolhead, Hannah Forster, Carlos Celis-Morales, Rosalind Fallaize, Anna L. Macready, Cyril F. M. Marsaux, Santiago Navas-Carretero, S. Rodrigo San-Cristobal, Silvia Kolossa, Lydia Tsirigoti, Christina Mvrogianni, Christina P. Lambrinou, George Moschonis, Magdalena Godlewska, Agnieszka Surwillo, Iwona Traczyk, Christian A. Drevon, Hannelore DanielYannis Manios, J. Alfredo Martinez, Wim H. M. Saris, Julie A. Lovegrove, John C. Mathers, Michael J. Gibney, Eileen R. Gibney, Lorraine Brennan*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

13 Citations (Web of Science)

Abstract

Traditionally, personalised nutrition was delivered at an individual level. However, the concept of delivering tailored dietary advice at a group level through the identification of metabotypes or groups of metabolically similar individuals has emerged. Although this approach to personalised nutrition looks promising, further work is needed to examine this concept across a wider population group. Therefore, the objectives of this study are to: (1) identify metabotypes in a European population and (2) develop targeted dietary advice solutions for these metabotypes. Using data from the Food4Me study (n 1607), k-means cluster analysis revealed the presence of three metabolically distinct clusters based on twenty-seven metabolic markers including cholesterol, individual fatty acids and carotenoids. Cluster 2 was identified as a metabolically healthy metabotype as these individuals had the highest Omega-3 Index (6.56 (sd 1.29) %), carotenoids (2. 15 (sd 0.71) mu m) and lowest total saturated fat levels. On the basis of its fatty acid profile, cluster 1 was characterised as a metabolically unhealthy cluster. Targeted dietary advice solutions were developed per cluster using a decision tree approach. Testing of the approach was performed by comparison with the personalised dietary advice, delivered by nutritionists to Food4Me study participants (n 180). Excellent agreement was observed between the targeted and individualised approaches with an average match of 82 % at the level of delivery of the same dietary message. Future work should ascertain whether this proposed method could be utilised in a healthcare setting, for the rapid and efficient delivery of tailored dietary advice solutions.

Original languageEnglish
Pages (from-to)561-569
Number of pages9
JournalBritish Journal of Nutrition
Volume118
Issue number8
DOIs
Publication statusPublished - 28 Oct 2017

Keywords

  • Personalised nutrition
  • Dried blood spots
  • Cluster analyses
  • Metabotyping
  • Targeted nutrition
  • PERSONALIZED NUTRITION
  • CLUSTER-ANALYSIS
  • ASTHMA PHENOTYPES
  • IDENTIFICATION
  • CLASSIFICATION
  • BIOMARKERS
  • MODEL

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