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Postprandial glycaemic dips predict appetite and energy intake in healthy individuals

Abstract

Understanding how to modulate appetite in humans is key to developing successful weight loss interventions. Here, we showed that postprandial glucose dips 2–3 h after a meal are a better predictor of postprandial self-reported hunger and subsequent energy intake than peak glucose at 0–2 h and glucose incremental area under the blood glucose curve at 0–2 h. We explore the links among postprandial glucose, appetite and subsequent energy intake in 1,070 participants from a UK exploratory and US validation cohort, who consumed 8,624 standardized meals followed by 71,715 ad libitum meals, using continuous glucose monitors to record postprandial glycaemia. For participants eating each of the standardized meals, the average postprandial glucose dip at 2–3 h relative to baseline level predicted an increase in hunger at 2–3 h (r = 0.16, P < 0.001), shorter time until next meal (r = −0.14, P < 0.001), greater energy intake at 3–4 h (r = 0.19, P < 0.001) and greater energy intake at 24 h (r = 0.27, P < 0.001). Results were directionally consistent in the US validation cohort. These data provide a quantitative assessment of the relevance of postprandial glycaemia in appetite and energy intake modulation.

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Fig. 1: Average glycaemic responses to standardized breakfasts illustrating the key measures used in the study (n = 1,070, m = 8,624).
Fig. 2: Postprandial measures according to the top and bottom quartiles of the 2–3 h glucose dip (n = 763, m = 5,667; UK n = 685, m = 5,667; US validation cohort n = 78, m = 602).
Fig. 3: Differences in postprandial measures across repeated meals within individuals (n = 1,053, m = 6,428; UK n = 958, m = 5,928; US validation cohort n = 95, m = 500).

Data availability

The data used for analysis in this study are held by the Department of Twin Research at King’s College London. The data can be released to bona fide researchers using our normal procedures overseen by the Wellcome Trust and its guidelines as part of our core funding. We receive around 100 requests per year for our datasets and have a meeting three times a month with independent members to assess proposals. Application is via https://twinsuk.ac.uk/resources-for-researchers/access-our-data/. Data must be anonymized and conform to General Data Protection Regulation standards. Source data are provided with this paper.

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Acknowledgements

We thank the participants of the PREDICT 1 study. We thank the staff of Zoe Global, the Department of Twin Research and Massachusetts General Hospital for their tireless work in contributing to the running of the study and data collection. We thank Abbott for their support with using their CGMs. This work was supported by Zoe Global Ltd and Massachusetts General Hospital and the Translational and Clinical Research Center. It also received support from grants from the Wellcome Trust (no. 212904/Z/18/Z) and Medical Research Council (MRC)/British Heart Foundation Ancestry and Biological Informative Markers for Stratification of Hypertension (no. MR/M016560/1). P.W.F. was supported in part by grants from the European Research Council (no. CoG-2015_681742_NASCENT), Swedish Research Council, Novo Nordisk Foundation and the Swedish Foundation for Strategic Research (IRC award). A.M.V. was supported by the National Institute for Health Research (NIHR) Nottingham Biomedical Research Centre. TwinsUK is funded by the Wellcome Trust, MRC, European Union, Chronic Disease Research Foundation, Zoe Global Ltd and the NIHR-funded BioResource, Clinical Research Facility and Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London. The sponsor, Zoe Global Ltd, was directly involved in study design, data collection and analysis for this manuscript. Zoe Global Ltd, the Wellcome Trust and NIHR funded this study.

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Authors

Contributions

J.W., G.H. and T.D.S. obtained the funding. P.W. and A.M.V. designed the study and developed its concept. S.E.B., P.W.F., D.A.D., H.A.K., L.H.N., A.T.C., R.O.D. and G.F. collected the data. P.W. and A.M.V. analysed the data. S.E.B., P.W.F., H.A.K., D.A.D., G.H., J.W. and I.L. coordinated the study. P.W., J.B. and A.M.V. wrote the manuscript. All authors reviewed and revised the final manuscript.

Corresponding author

Correspondence to Ana M. Valdes.

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Competing interests

T.D.S., S.E.B., A.M.V., P.W.F. and A.T.C. are consultants to Zoe Global. J.W., G.H., H.A.K, P.W. and I.L. are or have been employees of Zoe Global. J.B. is a member of the Zoe Global scientific advisory board. The other authors declare no conflicts of interest.

Additional information

Peer review information Nature Metabolism thanks Jennie C Brand-Miller, Lisa Chow and Hao Wang for their contribution to the peer review of this work. Primary Handling Editors: Pooja Jha; Isabella Samuelson.

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Extended data

Extended Data Fig. 1

Consort diagram of study participants and meals.

Extended Data Fig. 2 Distributions of key measures.

Distribution of key outcomes studied in the (A) UK cohort studied. Source data

Extended Data Fig. 3 Distributions of key measures.

Distribution of key outcomes studied in the (B) US cohort studied. Source data

Supplementary information

Reporting Summary

Supplementary Tables

Supplementary Tables 1–5

Source data

Source Data Fig. 2

Raw data used to generate Fig. 2.

Source Data Fig. 3

Raw data used to generate Fig. 3 and Supplementary Table 5.

Source Data Extended Data Fig. 2

Raw data used to generate Extended Data Fig. 2.

Source Data Extended Data Fig. 3

Raw data used to generate extended Data Fig. 3.

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Wyatt, P., Berry, S.E., Finlayson, G. et al. Postprandial glycaemic dips predict appetite and energy intake in healthy individuals. Nat Metab 3, 523–529 (2021). https://doi.org/10.1038/s42255-021-00383-x

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