Heterogeneity in glucose response curves during an oral glucose tolerance test and associated cardiometabolic risk

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We aimed to examine heterogeneity in glucose response curves during an oral glucose tolerance test with multiple measurements and to compare cardiometabolic risk profiles between identified glucose response curve groups.
We analyzed data from 1,267 individuals without diabetes from five studies in Denmark, the Netherlands and the USA. Each study included between 5 and 11 measurements at different time points during a 2-h oral glucose tolerance test,
resulting in 9,602 plasma glucose measurements. Latent class trajectories with a cubic specification for time were fitted to identify different patterns of plasma glucose change during the oral glucose tolerance test. Cardiometabolic risk
factor profiles were compared between the identified groups. Using latent class trajectory analysis, five glucose response curves were identified. Despite similar fasting and 2-h values, glucose peaks and peak times varied greatly between groups, ranging from 7–12 mmol/L, and 35–70 min. The group with the lowest and earliest plasma glucose peak had the lowest estimated cardiovascular risk, while the group with the most delayed plasma glucose peak and the highest 2-h value had the highest estimated risk. One group, with normal fasting and 2-h values, exhibited an unusual profile, with the highest glucose peak and the highest proportion of smokers and men. The heterogeneity in glucose response curves and the distinct cardiometabolic risk profiles may reflect different underlying physiologies. Our results warrant more detailed studies to identify the source of the heterogeneity across the different phenotypes and whether these differences play a role in the development of type 2 diabetes and cardiovascular disease.
Original languageEnglish
Issue number2
Pages (from-to)427-434
Number of pages8
Publication statusPublished - 2017

    Research areas

  • Faculty of Science - Oral glucose tolerance test, Glucose response curve, Cardiometabolic risk, Latent class trajectory analysis

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