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Postprandial metabolite profiles associated with type 2 diabetes clearly stratify individuals with impaired fasting glucose

INTRODUCTION: Fasting metabolite profiles have been shown to distinguish type 2 diabetes (T2D) patients from normal glucose tolerance (NGT) individuals. OBJECTIVES: We investigated whether, besides fasting metabolite profiles, postprandial metabolite profiles associated with T2D can stratify individ...

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Detalles Bibliográficos
Autores principales: Li-Gao, Ruifang, de Mutsert, Renée, Rensen, Patrick C. N., van Klinken, Jan Bert, Prehn, Cornelia, Adamski, Jerzy, van Hylckama Vlieg, Astrid, den Heijer, Martin, le Cessie, Saskia, Rosendaal, Frits R., Willems van Dijk, Ko, Mook-Kanamori, Dennis O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5727148/
https://www.ncbi.nlm.nih.gov/pubmed/29249917
http://dx.doi.org/10.1007/s11306-017-1307-7
Descripción
Sumario:INTRODUCTION: Fasting metabolite profiles have been shown to distinguish type 2 diabetes (T2D) patients from normal glucose tolerance (NGT) individuals. OBJECTIVES: We investigated whether, besides fasting metabolite profiles, postprandial metabolite profiles associated with T2D can stratify individuals with impaired fasting glucose (IFG) by their similarities to T2D. METHODS: Three groups of individuals (age 45–65 years) without any history of IFG or T2D were selected from the Netherlands Epidemiology of Obesity study and stratified by baseline fasting glucose concentrations (NGT (n = 176), IFG (n = 186), T2D (n = 171)). 163 metabolites were measured under fasting and postprandial states (150 min after a meal challenge). Metabolite profiles specific for a high risk of T2D were identified by LASSO regression for fasting and postprandial states. The selected profiles were utilised to stratify IFG group into high (T2D probability ≥ 0.7) and low (T2D probability ≤ 0.5) risk subgroups. The stratification performances were compared with clinically relevant metabolic traits. RESULTS: Two metabolite profiles specific for T2D (n(fasting) = 12 metabolites, n(postprandial) = 4 metabolites) were identified, with all four postprandial metabolites also being identified in the fasting state. Stratified by the postprandial profile, the high-risk subgroup of IFG individuals (n = 72) showed similar glucose concentrations to the low-risk subgroup (n = 57), yet a higher BMI (difference: 3.3 kg/m(2) (95% CI 1.7–5.0)) and postprandial insulin concentrations (21.5 mU/L (95% CI 1.8–41.2)). CONCLUSION: Postprandial metabolites identified T2D patients as good as fasting metabolites and exhibited enhanced signals for IFG stratification, which offers a proof of concept that metabolomics research should not focus on the fasting state alone. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11306-017-1307-7) contains supplementary material, which is available to authorized users.