title: Use of multiple metabolic and genetic markers to improve the prediction of type 2 diabetes: the EPIC-Potsdam Study.
abstract: OBJECTIVE
  We investigated whether metabolic biomarkers and single nucleotide polymorphisms (SNPs) improve diabetes prediction beyond age, anthropometry, and lifestyle risk factors.
  
  
  METHODS
  A case-cohort study within a prospective study was designed. We randomly selected a subcohort (n = 2,500) from 26,444 participants, of whom 1,962 were diabetes free at baseline. Of the 801 incident type 2 diabetes cases identified in the cohort during 7 years of follow-up, 579 remained for analyses after exclusions. Prediction models were compared by receiver operatoring characteristic (ROC) curve and integrated discrimination improvement.
  
  
  RESULTS
  Case-control discrimination by the lifestyle characteristics (ROC-AUC: 0.8465) improved with plasma glucose (ROC-AUC: 0.8672, P < 0.001) and A1C (ROC-AUC: 0.8859, P < 0.001). ROC-AUC further improved with HDL cholesterol, triglycerides, gamma-glutamyltransferase, and alanine aminotransferase (0.9000, P = 0.002). Twenty SNPs did not improve discrimination beyond these characteristics (P = 0.69).
  
  
  CONCLUSIONS
  Metabolic markers, but not genotyping for 20 diabetogenic SNPs, improve discrimination of incident type 2 diabetes beyond lifestyle risk factors.
authors.affiliation: Public Health Nutrition Unit, Technische Universität München, Freising, Germany. matthias.schulze@wzw.tum.de
authors.forename: Matthias B
authors.initials: MB
authors.lastname: Schulze
authors.forename: Cornelia
authors.initials: C
authors.lastname: Weikert
authors.forename: Tobias
authors.initials: T
authors.lastname: Pischon
authors.forename: Manuela M
authors.initials: MM
authors.lastname: Bergmann
authors.forename: Hadi
authors.initials: H
authors.lastname: Al-Hasani
authors.forename: Erwin
authors.initials: E
authors.lastname: Schleicher
authors.forename: Andreas
authors.initials: A
authors.lastname: Fritsche
authors.forename: Hans-Ulrich
authors.initials: HU
authors.lastname: Häring
authors.forename: Heiner
authors.initials: H
authors.lastname: Boeing
authors.forename: Hans-Georg
authors.initials: HG
authors.lastname: Joost
mesh_terms: D000410:Alanine Transaminase / Q000097:blood; D019540:Area Under Curve; D015415:Biomarkers / Q000097:blood*; D001786:Blood Glucose / Q000378:metabolism; D016022:Case-Control Studies; D008076:Cholesterol, HDL / Q000097:blood; D015331:Cohort Studies; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000453:epidemiology / Q000235:genetics*; D005819:Genetic Markers; D005838:Genotype; D005858:Germany; D006442:Glycated Hemoglobin / Q000378:metabolism*; D006801:Humans; D020641:Polymorphism, Single Nucleotide; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012372:ROC Curve; D018570:Risk Assessment; D005723:gamma-Glutamyltransferase / Q000097:blood
chemical_list: D000410:Alanine Transaminase; D015415:Biomarkers; D001786:Blood Glucose; D008076:Cholesterol, HDL; D005819:Genetic Markers; D006442:Glycated Hemoglobin; D005723:gamma-Glutamyltransferase