PreprintCited by 33Nutrition, Genetics, and DiseaseMetabolomics and Mass Spectrometry StudiesDiet, Metabolism, and Disease

Personalised REsponses to DIetary Composition Trial (PREDICT): an intervention study to determine inter-individual differences in postprandial response to foods

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Berry, Sarah, Drew, David, Linenberg, Inbar, Wolf, Jonathan, Hadjigeorgiou, George, Davies, Richard, Khatib, Haya Al, Hart, Deborah +11 more·2020

Abstract

The Personalised REsponses to DIetary Composition Trial (PREDICT) was a single-arm, single-blind intervention study that utilized both standardized “test” meals and captured “free-living” non-standardized food consumption, to predict an individual’s metabolic response to foods based on the person’s characteristics (including their metabolomic and gut microbiome profiles), meal composition (macronutrients and energy content) and meal context (including time of day, sleep and exercise). The initial study commenced in June 2018 and targeted 1,000 generally healthy participants between the ages of 18 and 65 years for enrollment in the United Kingdom, and recruited from the existing and ongoing TwinsUK research cohort and the general population. In December 2018, an independent trial mirroring the UK protocol was launched in parallel at Massachusetts General Hospital to serve as a US-based validation cohort including 100 healthy individuals in the general population. The overall objective of these trials was to predict glucose, insulin, lipid and other postprandial responses to foods based on the individual’s characteristics, including molecular biomarkers and lifestyle factors as well as the nutritional composition of the food. The studies, collectively termed PREDICT 1, were completed in May 2019. The study has delivered highly-dimensional multi-omic data from which the predictors of individual postprandial responses have been determined. These findings will be used to design personalized dietary interventions focused on key health outcomes. This protocol is registered with the US National Institutes of Health trial registry, ClinicalTrials.gov: NCT03479866.

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  • The analysis may partly explain why observational epidemiological studies have shown strong correlations between foods with high glycemic loads and weight gain, as consumption of such foods could lead to glucose dips and subsequent hunger.

    “Our analysis may partly explain why observational epidemiological ((27)(28)) studies have shown strong correlations between foods with high glycemic loads (such as potatoes and sugar sweetened beverages (29)) and weight gain – as consumption of such foods could lead to glucose dips and subsequent hunger.”

    From Postprandial glycaemic dips predict appetite and energy intake in healthy individuals (2021) · cites this paper as [29]

    The Introduction (page unavailable) links postprandial glucose dysregulation with obesity, supporting a broad connection between glucose responses and weight. The Outcomes section describes measuring responses to test meals, but our copy does not report strong observational correlations between high-glycemic-load foods and weight gain or show that glucose dips lead to hunger. (LLM, conf=0.74)

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Research works printed but not linked: 2

  1. Tebani, A. & Bekri, S. Paving the Way to Precision Nutrition Through Metabolomics. Front Nutr 6, 41 (2019).
  2. van Hees, V.T., et al. Estimating sleep parameters using an accelerometer without sleep diary. Sci Rep 8, 12975 (2018).

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Authors
Berry, S., Drew, D., Linenberg, I., Wolf, J., Hadjigeorgiou, G., Davies, R., Khatib, H. A., Hart, D., Surdulescu, G., Yarand, D., Nessa, A., Sheedy, A., Vijay, A., Asnicar, F., Segata, N., Chan, A., Franks, P., Valdes, A., & Spector, T.
Affiliations
  • King's College London (GB)
  • Harvard University (US)
  • ZOE (United Kingdom) (GB)
  • King's College London
  • University of Nottingham (GB)
  • University of Trento (IT)
  • Lund University (SE)
Published
2020-01-14
OpenAlex
W3117445042
Cited by
33
References
0
Citations by year
2026: 2 · 2025: 7 · 2024: 5 · 2023: 9 · 2022: 3 · 2021: 6 · 2020: 1
Type
posted content
Language
en
Open access
Funders
Massachusetts General Hospital
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diet, Metabolism, and Disease
Keywords
personalized nutrition, glycemic response, insulin response, lipid response, gut microbiota, metabolomics, macronutrient composition, meal context, sleep, physical activity, dietary intervention, biomarkers

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