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  4. Metabolite ratios as potential biomarkers for type 2 diabetes: a DIRECT study
 
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Metabolite ratios as potential biomarkers for type 2 diabetes: a DIRECT study
File(s)
Molnos-2018(MetaboliteRatios&T2D).pdf (549.08 KB)
Published version
Author(s)
Molnos, Sophie
Wahl, Simone
Haid, Mark
Eekhoff, E Marelise W
Pool, René
more
Type
Journal Article
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.
Date Issued
2017-10-25
Date Acceptance
2017-07-28
Citation
Diabetologia, 2017, 61 (1), pp.117-129
URI
http://hdl.handle.net/10044/1/58119
DOI
https://www.dx.doi.org/10.1007/s00125-017-4436-7
ISSN
0012-186X
Publisher
Springer Verlag
Start Page
117
End Page
129
Journal / Book Title
Diabetologia
Volume
61
Issue
1
Copyright Statement
© The Author(s) 2017.

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/28936587
PII: 10.1007/s00125-017-4436-7
Subjects
Epidemiology
Insulin secretion
Metabolomics
Prediction of diabetes
Type 2 diabetes
Publication Status
Published
Coverage Spatial
Germany
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