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-MarglMaren 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

Research output: Contribution to journalArticle

359 Citations (Scopus)


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.

Original languageEnglish
Article number615
JournalMolecular Systems Biology
Publication statusPublished - 2012
Externally publishedYes



  • early diagnostic biomarkers
  • IGT
  • metabolomics
  • prediction
  • T2D

ASJC Scopus subject areas

  • Medicine(all)
  • Immunology and Microbiology(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • Computational Theory and Mathematics
  • Information Systems
  • Applied Mathematics

Cite this

Wang-Sattler, R., Yu, Z., Herder, C., Messias, A. C., Floegel, A., He, Y., Heim, K., Campillos, M., Holzapfel, C., Thorand, B., Grallert, H., Xu, T., Bader, E., Huth, C., Mittelstrass, K., Döring, A., Meisinger, C., Gieger, C., Prehn, C., ... Illig, T. (2012). Novel biomarkers for pre-diabetes identified by metabolomics. Molecular Systems Biology, 8, [615].