Metabolite ratios as potential biomarkers for type 2 diabetes: a DIRECT study

Sophie Molnos, Simone Wahl, Mark Haid, E Marelise W Eekhoff, René Pool, Anna Floegel, Joris Deelen, Daniela Much, Cornelia Prehn, Michaela Breier, Harmen H Draisma, Nienke van Leeuwen, Annemarie M C Simonis-Bik, Anna Jonsson, Gonneke Willemsen, Wolfgang Bernigau, Rui Wang-Sattler, Karsten Suhre, Annette Peters, Barbara ThorandChristian Herder, Wolfgang Rathmann, Michael Roden, Christian Gieger, Mark H H Kramer, Diana van Heemst, Helle K Pedersen, Valborg Gudmundsdottir, Matthias B Schulze, Tobias Pischon, Eco J C de Geus, Heiner Boeing, Dorret I Boomsma, Anette G Ziegler, P. Eline Slagboom, Sandra Hummel, Marian Beekman, Harald Grallert, Søren Brunak, Mark I McCarthy, Ramneek Gupta, Ewan R Pearson, Jerzy Adamski, Leen M 't Hart

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Abstract

AIMS/HYPOTHESIS: Circulating metabolites have been shown to reflect metabolic changes during the development of type 2 diabetes. In this study we examined the association of metabolite levels and pairwise metabolite ratios with insulin responses after glucose, glucagon-like peptide-1 (GLP-1) and arginine stimulation. We then investigated if the identified metabolite ratios were associated with measures of OGTT-derived beta cell function and with prevalent and incident type 2 diabetes.

METHODS: We measured the levels of 188 metabolites in plasma samples from 130 healthy members of twin families (from the Netherlands Twin Register) at five time points during a modified 3 h hyperglycaemic clamp with glucose, GLP-1 and arginine stimulation. We validated our results in cohorts with OGTT data (n = 340) and epidemiological case-control studies of prevalent (n = 4925) and incident (n = 4277) diabetes. The data were analysed using regression models with adjustment for potential confounders.

RESULTS: There were dynamic changes in metabolite levels in response to the different secretagogues. Furthermore, several fasting pairwise metabolite ratios were associated with one or multiple clamp-derived measures of insulin secretion (all p < 9.2 × 10(-7)). These associations were significantly stronger compared with the individual metabolite components. One of the ratios, valine to phosphatidylcholine acyl-alkyl C32:2 (PC ae C32:2), in addition showed a directionally consistent positive association with OGTT-derived measures of insulin secretion and resistance (p ≤ 5.4 × 10(-3)) and prevalent type 2 diabetes (ORVal_PC ae C32:2 2.64 [β 0.97 ± 0.09], p = 1.0 × 10(-27)). Furthermore, Val_PC ae C32:2 predicted incident diabetes independent of established risk factors in two epidemiological cohort studies (HRVal_PC ae C32:2 1.57 [β 0.45 ± 0.06]; p = 1.3 × 10(-15)), leading to modest improvements in the receiver operating characteristics when added to a model containing a set of established risk factors in both cohorts (increases from 0.780 to 0.801 and from 0.862 to 0.865 respectively, when added to the model containing traditional risk factors + glucose).

CONCLUSIONS/INTERPRETATION: In this study we have shown that the Val_PC ae C32:2 metabolite ratio is associated with an increased risk of type 2 diabetes and measures of insulin secretion and resistance. The observed effects were stronger than that of the individual metabolites and independent of known risk factors.

Original languageEnglish
Pages (from-to)117-129
Number of pages13
JournalDiabetologia
Volume61
Issue number1
DOIs
Publication statusPublished - 1 Jan 2018

Keywords

  • Epidemiology
  • Insulin secretion
  • Journal Article
  • Metabolomics
  • Prediction of diabetes
  • Type 2 diabetes

Cohort Studies

  • Netherlands Twin Register (NTR)

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