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

Diabetologia. 2018 Jan;61(1):117-129. doi: 10.1007/s00125-017-4436-7. Epub 2017 Oct 25.

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.

Keywords: Epidemiology; Insulin secretion; Metabolomics; Prediction of diabetes; Type 2 diabetes.

MeSH terms

  • Arginine / metabolism
  • Biomarkers / blood*
  • Biomarkers / metabolism*
  • Blood Glucose / metabolism
  • Diabetes Mellitus, Type 2 / blood*
  • Diabetes Mellitus, Type 2 / metabolism*
  • Female
  • Glucagon-Like Peptide 1 / metabolism
  • Glucose / metabolism
  • Glucose Tolerance Test
  • Humans
  • Insulin / metabolism
  • Male
  • Risk Factors

Substances

  • Biomarkers
  • Blood Glucose
  • Insulin
  • Glucagon-Like Peptide 1
  • Arginine
  • Glucose