title: Fasting proinsulin concentrations predict the development of type 2 diabetes.
abstract: OBJECTIVE
  The development of specific assays allows the different molecules in the proinsulin processing pathway to be measured separately. 32,33 Split proinsulin is the predominant form of proinsulin and accounts for the disproportionate hyperproinsulinemia seen in individuals with prevalent type 2 diabetes. This study was established to examine whether the concentration of this molecule predicts diabetes.
  
  
  METHODS
  A population-based longitudinal cohort study was conducted in Ely, Cambridgeshire. At baseline, 1,122 individuals completed a 75-g oral glucose tolerance test (OGTT). At the 4.5-year follow-up study, repeat OGTTs were performed on 937 of the cohort of 1,071 individuals who had been nondiabetic at baseline.
  
  
  RESULTS
  A total of 26 people progressed to diabetes as determined by the OGTTs. The risk of progression was strongly related to the fasting glucose concentration (relative risk [RR] comparing top with bottom quartile 17.6 [95% CI 2.4-130.4]) and fasting 32,33 split proinsulin (RR 16.4 [2.2-121.9]), but less strongly to the fasting insulin (RR 4.41 [1.5-12.9]) or intact proinsulin (RR 5.2 [1.5-17.3]). In multivariate analyses, these associations were independent of age, sex, BMI, and baseline glucose tolerance category. Subjects in the top quartile for fasting glucose and total proinsulin with a family history of diabetes were a high-risk subgroup (incidence 65.8 per 1,000 person-years of follow-up [pyfu]); 30% of them progressed to diabetes at follow-up.
  
  
  CONCLUSIONS
  Fasting 32,33 split proinsulin independently predicts the development of diabetes. This prediction was better than that observed for either the insulin or intact proinsulin concentrations. The combination of family history, fasting glucose, and total proinsulin identified a subgroup of individuals at high risk of progression who might benefit from targeted interventions.
authors.affiliation: Department of Community Medicine, University of Cambridge, England, U.K. njw1004@medschl.cam.ac.uk
authors.forename: N J
authors.initials: NJ
authors.lastname: Wareham
authors.forename: C D
authors.initials: CD
authors.lastname: Byrne
authors.forename: R
authors.initials: R
authors.lastname: Williams
authors.forename: N E
authors.initials: NE
authors.lastname: Day
authors.forename: C N
authors.initials: CN
authors.lastname: Hales
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000097:blood; D015992:Body Mass Index; D015331:Cohort Studies; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000175:diagnosis*; D018450:Disease Progression; D004739:England; D005215:Fasting; D005260:Female; D018149:Glucose Intolerance / Q000097:blood / Q000175:diagnosis*; D005951:Glucose Tolerance Test; D006801:Humans; D007328:Insulin / Q000097:blood*; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011384:Proinsulin / Q000097:blood*; D011498:Protein Precursors / Q000097:blood; D012044:Regression Analysis
chemical_list: D015415:Biomarkers; D007328:Insulin; D011498:Protein Precursors; C070703:proinsulin, des(31,32)-; D011384:Proinsulin