Autoantibody‐defined risk for Type 1 diabetes mellitus in a general population of schoolchildren: results of the Karlsburg Type 1 Diabetes Risk Study after 18 years. Issue 8 (23rd January 2015) - Till, A.‐M.; Kenk, H.; Rjasanowski, I.; Wassmuth, R.; Walschus, U.; Kerner, W.; Schlosser, M.
Abstract Aims To investigate the occurrence of diabetes‐associated autoantibodies and cumulative Type 1 diabetes risk over 18 years in a general population of schoolchildren. Methods In the Karlsburg Type 1 Diabetes Risk Study, 11 986 schoolchildren from north‐eastern Germany without a family history of diabetes were screened for glutamic acid decarboxylase antibodies, insulinoma‐associated antigen‐2 antibodies and insulin autoantibodies by radioligand binding assay. Those children found to be autoantibody‐positive were invited to follow‐up examinations and HLA‐DQB1 genotyping, and were followed for progression to Type 1 diabetes. Results At first follow‐up, 119 children had single and 36 children had multiple autoantibodies. Of the multiple autoantibody‐positive children, 33 had at least one diabetes‐associated HLA‐DQB1 allele (*02 and/or *0302). A total of 26 children progressed to Type 1 diabetes, of whom 22 had multiple autoantibodies. The male‐to‐female ratio of those who progressed to Type 1 diabetes was 1.6. The positive predictive value of multiple autoantibodies was 61.1% compared with only 23.7% for diabetes‐associated HLA‐DQB1 genotypes among all those who were autoantibody‐positive. The cumulative risk was 59.7% after 10 years and 75.1% after 18 years for children with multiple autoantibodies compared with 1.2 and 22.6%, respectively, for children with single autoantibodies (P<0.001). Among the three examined autoantibodies, insulinoma‐associated antigen‐2 antibodies conferred the highest risk. Conclusions The diabetes risk in schoolchildren with multiple autoantibodies was similar to the risk reported in other studies for genetically preselected probands; thus, a combined autoantibody‐based screening could effectively identify at‐risk individuals from the general population for future intervention trials.