Identification of Serum Metabolites Associated With Risk of Type 2 Diabetes Using a Targeted Metabolomic Approach
- Anna Floegel1⇓,
- Norbert Stefan2,
- Zhonghao Yu3,
- Kristin Mühlenbruch4,
- Dagmar Drogan1,
- Hans-Georg Joost5,
- Andreas Fritsche2,
- Hans-Ulrich Häring2,
- Martin Hrabě de Angelis6,
- Annette Peters7,
- Michael Roden8,9,
- Cornelia Prehn6,
- Rui Wang-Sattler3,
- Thomas Illig3,10,
- Matthias B. Schulze4,
- Jerzy Adamski6,
- Heiner Boeing1 and
- Tobias Pischon1,11
- 1Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- 2Department of Internal Medicine IV, Divisions of Endocrinology, Diabetology, Nephrology, Vascular Disease, and Clinical Chemistry, University of Tübingen, Tübingen, Germany
- 3Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- 4Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- 5Department of Pharmacology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- 6Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- 7Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- 8Institute of Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- 9Department of Metabolic Diseases, University Clinics, Düsseldorf, Germany
- 10Hannover Unified Biobank, Hannover Medical School, Hannover, Germany
- 11Molecular Epidemiology Group, Max Delbrück Center for Molecular Medicine (MDC) Berlin-Buch, Berlin, Germany
- Corresponding author: Anna Floegel, .
Metabolomic discovery of biomarkers of type 2 diabetes (T2D) risk may reveal etiological pathways and help to identify individuals at risk for disease. We prospectively investigated the association between serum metabolites measured by targeted metabolomics and risk of T2D in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam (27,548 adults) among all incident cases of T2D (n = 800, mean follow-up 7 years) and a randomly drawn subcohort (n = 2,282). Flow injection analysis tandem mass spectrometry was used to quantify 163 metabolites, including acylcarnitines, amino acids, hexose, and phospholipids, in baseline serum samples. Serum hexose; phenylalanine; and diacyl-phosphatidylcholines C32:1, C36:1, C38:3, and C40:5 were independently associated with increased risk of T2D and serum glycine; sphingomyelin C16:1; acyl-alkyl-phosphatidylcholines C34:3, C40:6, C42:5, C44:4, and C44:5; and lysophosphatidylcholine C18:2 with decreased risk. Variance of the metabolites was largely explained by two metabolite factors with opposing risk associations (factor 1 relative risk in extreme quintiles 0.31 [95% CI 0.21–0.44], factor 2 3.82 [2.64–5.52]). The metabolites significantly improved T2D prediction compared with established risk factors. They were further linked to insulin sensitivity and secretion in the Tübingen Family study and were partly replicated in the independent KORA (Cooperative Health Research in the Region of Augsburg) cohort. The data indicate that metabolic alterations, including sugar metabolites, amino acids, and choline-containing phospholipids, are associated early on with a higher risk of T2D.
- Received April 22, 2012.
- Accepted July 22, 2012.
- © 2012 by the American Diabetes Association.
Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.