title: IA-2 autoantibodies predict impending type I diabetes in siblings of patients.
abstract: OBJECTIVE
  Multiple islet autoantibody positivity is currently believed to best predict progression to Type I (insulin-dependent) diabetes mellitus. We compared its predictive value with that of positivity for a particular type of islet autoantibody, directed against the IA-2 antigen.
  
  
  METHODS
  Autoantibodies against islet cell cytoplasm (ICA), insulin (IAA), GAD (GADA) and IA-2 (IA-2A) were measured at initial sampling in 1724 non-diabetic siblings (median age [range]:16 [0-39] years) of Type I diabetic patients with a median follow-up of 50 months.
  
  
  RESULTS
  On initial sampling 11% of siblings were positive for one antibody type or more and 2.1% for three of more types. During follow-up, 27 antibody-positive siblings developed diabetes. Using survival analysis, the risk for clinical onset within 5 years was 34% in subjects positive for three or more types compared with 13% in those with one type or more. Progression to diabetes amounted to 12% within 5 years among siblings positive for IAA, 20% for ICA, 19% for GADA but 59% for IA-2A (p<0.001 vs absence of the respective antibody). IA-2A were detected in 1.7% of all siblings and in 56% of the prediabetic subjects on first sampling. Initial positivity for two or three antibody markers was associated with a higher progression rate in IA-2A positive as compared to IA-2A negative siblings (p=0.001). In absence of IA-2A initial positivity for another antibody (IAA, ICA or GADA) conferred a low (<10% within 5 years) risk of diabetes compared to subjects lacking this antibody.
  
  
  CONCLUSIONS
  In siblings of Type I diabetic patients, IA-2A positivity is a more direct predictor of impending clinical onset than multiple antibody positivity per se. Assessment of IA-2A status allows us to select subjects with homogeneously high risk of diabetes for participation in prevention trials.
authors.affiliation: Diabetes Research Centre, Free University of Brussels, Belgium.
authors.forename: K
authors.initials: K
authors.lastname: Decochez
authors.forename: I H
authors.initials: IH
authors.lastname: De Leeuw
authors.forename: B
authors.initials: B
authors.lastname: Keymeulen
authors.forename: C
authors.initials: C
authors.lastname: Mathieu
authors.forename: R
authors.initials: R
authors.lastname: Rottiers
authors.forename: I
authors.initials: I
authors.lastname: Weets
authors.forename: E
authors.initials: E
authors.lastname: Vandemeulebroucke
authors.forename: I
authors.initials: I
authors.lastname: Truyen
authors.forename: L
authors.initials: L
authors.lastname: Kaufman
authors.forename: F C
authors.initials: FC
authors.lastname: Schuit
authors.forename: D G
authors.initials: DG
authors.lastname: Pipeleers
authors.forename: F K
authors.initials: FK
authors.lastname: Gorus
mesh_terms: D000293:Adolescent; D000328:Adult; D001323:Autoantibodies / Q000032:analysis*; D002648:Child; D002675:Child, Preschool; D003922:Diabetes Mellitus, Type 1 / Q000235:genetics* / Q000276:immunology*; D005260:Female; D005968:Glutamate Decarboxylase / Q000276:immunology; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007330:Insulin Antibodies; D007527:Isoenzymes / Q000276:immunology; D008137:Longitudinal Studies; D008297:Male; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D018570:Risk Assessment
chemical_list: D001323:Autoantibodies; C096322:ICA512 autoantibody; D007330:Insulin Antibodies; D007527:Isoenzymes; D005968:Glutamate Decarboxylase