Molecular Systems Biology (Sep 2012)
Novel biomarkers for pre‐diabetes identified by metabolomics
- 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 Döring,
- 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 Hrabé de Angelis,
- Wolfgang Rathmann,
- Karsten Suhre,
- Holger Prokisch,
- Annette Peters,
- Thomas Meitinger,
- Michael Roden,
- H‐Erich Wichmann,
- Tobias Pischon,
- Jerzy Adamski,
- Thomas Illig
Affiliations
- Rui Wang‐Sattler
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München
- Zhonghao Yu
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München
- Christian Herder
- German Diabetes Center, Institute for Clinical Diabetology, Leibniz Center for Diabetes Research at Heinrich Heine University
- Ana C Messias
- Institute of Structural Biology, Helmholtz Zentrum München
- Anna Floegel
- Department of Epidemiology, German Institute of Human Nutrition Potsdam‐Rehbruecke
- Ying He
- Shanghai Center for Bioinformation Technology
- Katharina Heim
- Institute of Human Genetics, Helmholtz Zentrum München
- Monica Campillos
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München
- Christina Holzapfel
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München
- Barbara Thorand
- Institute of Epidemiology II, Helmholtz Zentrum München
- Harald Grallert
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München
- Tao Xu
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München
- Erik Bader
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München
- Cornelia Huth
- Institute of Epidemiology II, Helmholtz Zentrum München
- Kirstin Mittelstrass
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München
- Angela Döring
- Institute of Epidemiology I, Helmholtz Zentrum München
- Christa Meisinger
- Institute of Epidemiology II, Helmholtz Zentrum München
- Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Zentrum München
- Cornelia Prehn
- Genome Analysis Center, Institute of Experimental Genetics, Helmholtz Zentrum München
- Werner Roemisch‐Margl
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München
- Maren Carstensen
- German Diabetes Center, Institute for Clinical Diabetology, Leibniz Center for Diabetes Research at Heinrich Heine University
- Lu Xie
- Shanghai Center for Bioinformation Technology
- Hisami Yamanaka‐Okumura
- Department of Clinical Nutrition, Institute of Health Biosciences, University of Tokushima Graduate School
- Guihong Xing
- Benxi Diabetes Clinic, Benxi Central Hospital
- Uta Ceglarek
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig
- Joachim Thiery
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig
- Guido Giani
- German Diabetes Center, Institute of Biometrics and Epidemiology, Leibniz Center for Diabetes Research at Heinrich Heine University
- Heiko Lickert
- Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München
- Xu Lin
- Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences
- Yixue Li
- Shanghai Center for Bioinformation Technology
- Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition Potsdam‐Rehbruecke
- Hans‐Georg Joost
- Department of Epidemiology, German Institute of Human Nutrition Potsdam‐Rehbruecke
- Martin Hrabé de Angelis
- Genome Analysis Center, Institute of Experimental Genetics, Helmholtz Zentrum München
- Wolfgang Rathmann
- German Diabetes Center, Institute of Biometrics and Epidemiology, Leibniz Center for Diabetes Research at Heinrich Heine University
- Karsten Suhre
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München
- Holger Prokisch
- Institute of Human Genetics, Helmholtz Zentrum München
- Annette Peters
- Institute of Epidemiology II, Helmholtz Zentrum München
- Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München
- Michael Roden
- German Diabetes Center, Institute for Clinical Diabetology, Leibniz Center for Diabetes Research at Heinrich Heine University
- H‐Erich Wichmann
- Institute of Epidemiology I, Helmholtz Zentrum München
- Tobias Pischon
- Department of Epidemiology, German Institute of Human Nutrition Potsdam‐Rehbruecke
- Jerzy Adamski
- Genome Analysis Center, Institute of Experimental Genetics, Helmholtz Zentrum München
- Thomas Illig
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München
- DOI
- https://doi.org/10.1038/msb.2012.43
- Journal volume & issue
-
Vol. 8,
no. 1
pp. 1 – 11
Abstract
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.
Keywords