TSH Receptor Antibody Heterogeneity in Children and Adolescents With Graves' Disease

Graves' Disease

Autoimmune thyroid disease, Children and Adolescents, TSH Receptor Antibodies

Graves' disease, the most common form of hyperthyroidism in children, is caused by Thyrotropin (TSH) Receptor Antibodies (TRAbs) that mimic the action of TSH. The disease leads to significant morbidity in children both due to the prolonged course of antithyroid medication often required for sustained immunological remission and the high risk of relapse when medication is withdrawn. The ability to predict which patients are most likely to fail medical management would greatly improve the choice of therapy. In the past, large goiter size, age at diagnosis, increased biochemical severity, and decreased body mass index have all been associated with a poorer prognosis, but these clinical indicators lack sensitivity and specificity. Preliminary data suggest that the new TRAb assays are both sensitive and specific for the measurement of TRAbs in children with Graves' disease. In addition, variation in these antibodies over time is not the same in all patients. The goal of this proposal will be to prospectively follow children with newly diagnosed Graves' disease and use microarray technology to determine if there are genes whose expression differ in patients who respond to medical therapy versus those who will need more definitive therapy earlier in their disease.

In the present grant proposal, we plan to utilize two new assays (binding and bioassay) in order to identify additional predictors of Graves' disease and apply them to a well characterized group of patients with Graves' disease followed prospectively. More specifically, we plan to further investigate the antibodies by measuring lambda: kappa light chain antibody ratios in pediatric patients. We will assess epitope heterogeneity by using novel chimeric proteins in which specific portions of the TSH receptor have been replaced with the closely related LH receptor. We will utilize microarray technology to determine if there are differences in gene expression profiles in responders versus non responders. It is hoped that these methods will lead to an improved ability to follow disease progression and to monitor efficacy of therapy.

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