title: α-Hydroxybutyric Acid Is a Selective Metabolite Biomarker of Impaired Glucose Tolerance.
abstract: Plasma metabolites that distinguish isolated impaired glucose tolerance (iIGT) from isolated impaired fasting glucose (iIFG) may be useful biomarkers to predict IGT, a high-risk state for the development of type 2 diabetes.
  
  
  
  Targeted metabolomics with 23 metabolites previously associated with dysglycemia was performed with fasting plasma samples from subjects without diabetes at time 0 of an oral glucose tolerance test (OGTT) in two observational cohorts: RISC (Relationship Between Insulin Sensitivity and Cardiovascular Disease) and DMVhi (Diabetes Mellitus and Vascular Health Initiative). Odds ratios (ORs) for a one-SD change in the metabolite level were calculated using multiple logistic regression models controlling for age, sex, and BMI to test for associations with iIGT or iIFG versus normal. Selective biomarkers of iIGT were further validated in the Botnia study.
  
  
  
  α-Hydroxybutyric acid (α-HB) was most strongly associated with iIGT in RISC (OR 2.54 [95% CI 1.86-3.48], P value 5E-9) and DMVhi (2.75 [1.81-4.19], 4E-5) while having no significant association with iIFG. In Botnia, α-HB was selectively associated with iIGT (2.03 [1.65-2.49], 3E-11) and had no significant association with iIFG. Linoleoyl-glycerophosphocholine (L-GPC) and oleic acid were also found to be selective biomarkers of iIGT. In multivariate IGT prediction models, addition of α-HB, L-GPC, and oleic acid to age, sex, BMI, and fasting glucose significantly improved area under the curve in all three cohorts.
  
  
  
  α-HB, L-GPC, and oleic acid were shown to be selective biomarkers of iIGT, independent of age, sex, BMI, and fasting glucose, in 4,053 subjects without diabetes from three European cohorts. These biomarkers can be used in predictive models to identify subjects with IGT without performing an OGTT.
authors.affiliation: Metabolon, Inc., Durham, NC jcobb@metabolon.com.
authors.forename: Jeff
authors.initials: J
authors.lastname: Cobb
authors.affiliation: Metabolon, Inc., Durham, NC.
authors.forename: Andrea
authors.initials: A
authors.lastname: Eckhart
authors.affiliation: Department of Statistics, Bioinformatics Research Center, North Carolina State University, Raleigh, NC.
authors.forename: Alison
authors.initials: A
authors.lastname: Motsinger-Reif
authors.affiliation: Vhi Healthcare, Dublin, Ireland.
authors.forename: Bernadette
authors.initials: B
authors.lastname: Carr
authors.affiliation: Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Malmö, Sweden.
authors.forename: Leif
authors.initials: L
authors.lastname: Groop
authors.affiliation: CNR Institute of Clinical Physiology, Pisa, Italy.
authors.forename: Ele
authors.initials: E
authors.lastname: Ferrannini
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000378:metabolism*; D001786:Blood Glucose / Q000378:metabolism; D015331:Cohort Studies; D005215:Fasting; D005260:Female; D018149:Glucose Intolerance / Q000378:metabolism*; D005951:Glucose Tolerance Test; D006801:Humans; D006885:Hydroxybutyrates / Q000378:metabolism*; D008297:Male; D055432:Metabolomics; D008875:Middle Aged; D015999:Multivariate Analysis; D019301:Oleic Acid / Q000378:metabolism; D011236:Prediabetic State / Q000378:metabolism*; D011446:Prospective Studies
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D006885:Hydroxybutyrates; D019301:Oleic Acid; C031570:2-hydroxybutyric acid