Insulin and Insulin-Receptor Autoantibodies in Children With Newly Diagnosed IDDM Before Insulin Therapy

Abstract

Twenty-nine children, aged 1–15 yr, with newly diagnosed insulin-dependent diabetes mellitus (IDDM) had sera taken before insulin therapy to be examined for the presence of insulin-receptor antibodies by measuring the inhibition of binding of radiolabeled insulin to IM-9 lymphocytes in both whole serum and purified IgG fractions. Groups of children with long-standing IDDM and autoimmune endocrine disease as well as a normal control group were studied. A positive result, defined as binding ≥2 SD below the mean zero standard, was found in 3 (10.3%) of the 29 newly diagnosed diabetic patients. As a group, they showed significantly greater binding inhibition than the normal control group for both whole serum and purified IgG (onetailed t test, P < .05 and P < .002, respectively). Insulin autoantibodies were also measured by a sensitive radioimmunoassay technique. A positive result, defined as binding ≥3 SD above the normal control pooled sera, was found in 9 (37.5%) of 24 of the newly diagnosed IDDM group tested. All 3 subjects positive for insulin-receptor antibodies were also positive for insulin autoantibodies, whereas 6 of the 21 receptor-antibody—negative subjects were positive for insulin autoantibodies (Fisher's exact test, P = .0415). This suggests the possibility that the presence of insulin autoantibodies is a prerequisite for the development of insulin-receptor antibodies, i.e., as an anti-idiotypic response. Insulin-receptor antibodies and insulin autoantibodies may play a currently undefined pathophysiologic role in the development of IDDM. Conversely, these may represent epiphenomena of the disease process itself or may indicate a predilection for development of the disease. Taken together with other markers associated with IDDM, e.g., HLA haplotype and islet cell antibodies, it may prove possible in the future to define a select population at risk for the development of the disease and/or to predict the clinical course in individual cases.