Novel Biomarkers for Pre-diabetes Identified by Metabolomics

Overview

Journal Mol Syst Biol

Specialty Molecular Biology

Date 2012 Sep 27

PMID 23010998

Citations 320

Authors

Rui Wang-Sattler

Zhonghao Yu

Christian Herder

Ana C Messias

Anna Floegel

Ying He

Katharina Heim

Monica Campillos

Christina Holzapfel

Barbara Thorand

Harald Grallert

Tao Xu

Erik Bader

Cornelia Huth

Kirstin Mittelstrass

Angela Doring

Christa Meisinger

Christian Gieger

Cornelia Prehn

Werner Roemisch-Margl

Maren Carstensen

Lu Xie

Hisami Yamanaka-Okumura

Guihong Xing

Uta Ceglarek

Joachim Thiery

Guido Giani

Heiko Lickert

Xu Lin

Yixue Li

Heiner Boeing

Hans-Georg Joost

Martin Hrabe de Angelis

Wolfgang Rathmann

Karsten Suhre

Holger Prokisch

Annette Peters

Thomas Meitinger

Michael Roden

H-Erich Wichmann

Tobias Pischon

Jerzy Adamski

Thomas Illig

Affiliations

Soon will be listed here.

Abstract

Type 2 diabetes (T2D) can be prevented in pre-diabetic individuals with impaired glucose tolerance (IGT). Here, we have used a metabolomics approach to identify candidate biomarkers of pre-diabetes. We quantified 140 metabolites for 4297 fasting serum samples in the population-based Cooperative Health Research in the Region of Augsburg (KORA) cohort. Our study revealed significant metabolic variation in pre-diabetic individuals that are distinct from known diabetes risk indicators, such as glycosylated hemoglobin levels, fasting glucose and insulin. We identified three metabolites (glycine, lysophosphatidylcholine (LPC) (18:2) and acetylcarnitine) that had significantly altered levels in IGT individuals as compared to those with normal glucose tolerance, with P-values ranging from 2.4×10(-4) to 2.1×10(-13). Lower levels of glycine and LPC were found to be predictors not only for IGT but also for T2D, and were independently confirmed in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort. Using metabolite-protein network analysis, we identified seven T2D-related genes that are associated with these three IGT-specific metabolites by multiple interactions with four enzymes. The expression levels of these enzymes correlate with changes in the metabolite concentrations linked to diabetes. Our results may help developing novel strategies to prevent T2D.

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