Simulation Model for Hashimoto Autoimmune Thyroiditis Disease

Abstract

Hashimoto's Thyroiditis (HT) is a pathology which often causes a gradual thyroid insufficiency in affected patients due to the autoimmune destruction of this gland. The cellular immune response mediated by T helper lymphocytes TH1 and TH17 can induce the HT disease. In this pathologic condition, there is an imbalance between the TH17 and Treg lymphocytes as well as a gut microbiota dysfunction. The objective of this work was to describe the interactions of the cell subpopulations that participate in HT. To achieve this goal, we generated a mathematical model that allowed the simulation of different scenarios for the dynamic interaction between thyroid cells, the immune system, and the gut microbiota. We used a hypothetical-deductive design of mathematical modeling based on a system of ordinary differential equations, where the state variables are the TH1, TH17 and Treg lymphocytes, the thyrocytes and the bacteria from gut microbiota. This work generated a compartmental model of the cellular immune response occurring in the thyroid gland. It was observed that TH1 and TH17 lymphocytes could increase the immune cells activity, as well as activate effector cells directly and trigger the apoptosis and inflammation processes of healthy thyrocytes indirectly. Likewise, the model showed that a reduction in Treg lymphocytes could increase the activity of TH17 lymphocytes when an imbalance of the gut microbiota composition occurred. The numerical results highlight the TH1, TH17 and bacterial balance of the gut microbiota activities as important factors for the development of Hashimoto’s Autoimmune Thyroiditis disease.

Prediction models constructed for Hashimoto’s thyroiditis risk based on clinical and laboratory factors

“…In addition, for optimal machine learning modeling that distinguishes thyroid cancer from HT disease, other clinical characteristics and laboratory test data should be taken into account. Considering that HT is an autoimmune disease, lymphocytes and intestinal microbiota should be meaningful risk factors for clinical reference ( 33 ).…”

“…According to a 2019 study, thyroid antibodies and hormones were involved in establishing a machine learning model for the quantitative and convenient diagnosis of HT distinguished from the Graves’ disease ( 32 ), but these factors were not comprehensive enough. Recent studies on HT found that mathematical modeling highlighted T helper lymphocytes TH1, TH17, and the bacterial balance of the gut microbiota activities as risk factors for HT development ( 33 ).…”

Hashimoto’s Thyroiditis and Gut Microbiota

“…Чилийские исследователи продемонстрировали в своей работе различные сценарии динамического взаимодействия между клетками ЩЖ, иммунной системой и МК с помощью гипотетико-дедуктивной схемы математического моделирования. Результаты их исследования подчеркивают, что Т-хелперные лимфоциты Th1, Th17, которые способны повышать активность иммунных клеток, а также напрямую активировать эффекторные клетки и опосредованно запускать процессы апоптоза и воспаления здоровых тироцитов, а также бактериальный баланс активности МК, являются важными факторами развития АИТ [36]. повышение концентрации зонулина, что связано с воспалительным процессом в кишечнике у пациентов с АИТ [17].…”

Dynamic changes in the histomorphological structure of the thyroid gland of rats against the background of experimental autoimmune thyroiditis

“…To date, there are many ways to model the autoimmune process in the thyroid gland. It primarily uses various forms of thyroglobulin (antigen) mixed with full Adjuvant Freund, which are administered to rabbits, mice, and rats [12][13][14][15][16][17][18][19][20][21][22][23][24]. As an antigen, thyroid homogenate is used allogeneically or xenogenically.…”