title: Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach.
abstract: 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.
authors.affiliation: Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany. anna.floegel@dife.de
authors.forename: Anna
authors.initials: A
authors.lastname: Floegel
authors.forename: Norbert
authors.initials: N
authors.lastname: Stefan
authors.forename: Zhonghao
authors.initials: Z
authors.lastname: Yu
authors.forename: Kristin
authors.initials: K
authors.lastname: Mühlenbruch
authors.forename: Dagmar
authors.initials: D
authors.lastname: Drogan
authors.forename: Hans-Georg
authors.initials: HG
authors.lastname: Joost
authors.forename: Andreas
authors.initials: A
authors.lastname: Fritsche
authors.forename: Hans-Ulrich
authors.initials: HU
authors.lastname: Häring
authors.forename: Martin
authors.initials: M
authors.lastname: Hrabě de Angelis
authors.forename: Annette
authors.initials: A
authors.lastname: Peters
authors.forename: Michael
authors.initials: M
authors.lastname: Roden
authors.forename: Cornelia
authors.initials: C
authors.lastname: Prehn
authors.forename: Rui
authors.initials: R
authors.lastname: Wang-Sattler
authors.forename: Thomas
authors.initials: T
authors.lastname: Illig
authors.forename: Matthias B
authors.initials: MB
authors.lastname: Schulze
authors.forename: Jerzy
authors.initials: J
authors.lastname: Adamski
authors.forename: Heiner
authors.initials: H
authors.lastname: Boeing
authors.forename: Tobias
authors.initials: T
authors.lastname: Pischon
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000097:blood*; D003924:Diabetes Mellitus, Type 2 / Q000097:blood*; D005260:Female; D005998:Glycine / Q000097:blood; D006601:Hexoses / Q000097:blood; D006801:Humans; D007328:Insulin / Q000378:metabolism; D007333:Insulin Resistance; D000078790:Insulin Secretion; D008297:Male; D055432:Metabolomics; D008875:Middle Aged; D010649:Phenylalanine / Q000097:blood; D010713:Phosphatidylcholines / Q000097:blood; D012306:Risk; D044967:Serum / Q000378:metabolism*; D013109:Sphingomyelins / Q000097:blood
chemical_list: D015415:Biomarkers; D006601:Hexoses; D007328:Insulin; D010713:Phosphatidylcholines; D013109:Sphingomyelins; D010649:Phenylalanine; D005998:Glycine