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Postprandial metabolite profiles associated with type 2 diabetes clearly stratify individuals with impaired fasting glucose
Authors:Ruifang Li-Gao  Renée de Mutsert  Patrick C. N. Rensen  Jan Bert van Klinken  Cornelia Prehn  Jerzy Adamski  Astrid van Hylckama Vlieg  Martin den Heijer  Saskia le Cessie  Frits R. Rosendaal  Ko Willems van Dijk  Dennis O. Mook-Kanamori
Affiliation:1.Department of Clinical Epidemiology,Leiden University Medical Center,Leiden,The Netherlands;2.Division of Endocrinology, Department of Medicine,Leiden University Medical Center,Leiden,The Netherlands;3.Einthoven Laboratory for Experimental Vascular Medicine,Leiden University Medical Center,Leiden,The Netherlands;4.Institute of Experimental Genetics, Genome Analysis Center,Helmholtz Zentrum München,Neuherberg,Germany;5.German Center for Diabetes Research,Neuherberg,Germany;6.Lehrstul für Experimentelle Genetik,Technische Universit?t München,Freising-Weihenstephan,Germany;7.Department of Medical Statistics and Bioinformatics,Leiden University Medical Center,Leiden,The Netherlands;8.Department of Human Genetics,Leiden University Medical Center,Leiden,The Netherlands;9.Department of Public Health and Primary Care,Leiden University Medical Center,Leiden,The Netherlands
Abstract:

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 (nfasting = 12 metabolites, npostprandial = 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/m2 (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.
Keywords:
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