Untangling thyroid autoimmunity through modeling and simulation.

Thyroid autoimmunity is characterized by a large number of identified factors, and determining the relative importance of genetics and environment, for instance, can be difficult. In addition, the definition and progression of the individual diseases can also be challenging, and questions such as "when to begin treatment" or even "should treatment be begun" can be problematic. One approach to handling situations in which there are many factors is utilizing mathematical modeling. In a model, quantities that are clinically measurable are related through equations, based on known and inferred relationships between the systems involved. ations where these relationships are complicated, the resulting simulations can provide information not previous recognized as logically resulting from those relationships. One advantage of this approach is that patient-specific parameter estimates can be used to personalize disease monitoring and treatment. In this paper, models involving Hashimoto's (autoimmune) thyroiditis, Graves' disease, and the roles of leptin, vitamin D, and adipose tissue are described. In the case of Hashimoto's, a model consisting of a system of differential equations is presented which allows a patient specific description of the progression of the disease. The conditions leading to Hashitoxicosis are also described through that model. The patient specific model of the treatment of Graves' disease is also described. Finally, the roles of the inflammatory adipokines, especially leptin, and vitamin D is explored as it relates to the initiation of thyroid autoimmunity. The result of this approach is an enhanced view of the initiation and progression of autoimmunity in the thyroid.