Thyroid Hormone Biomonitoring: A Review on Their Metabolism and Machine-Learning Based Analysis on Effects of Endocrine Disrupting Chemicals

Abstract

The thyroid is an essential endocrine organ in human body, and thyroid hormones (THs) are pivotal signaling molecules and mediators in various physiological processes. THs, particularly in their free form, play a critical role in regulating body temperature and in the metabolism of lipid and glucose, making the maintenance of TH levels crucial for human health. THs undergo a series of metabolic processes, producing TH metabolites (THMs). THMs are significant in endocrine regulation, such as 3,5-diiothyronine (3,5-T2) and 3-iodothyronamine (3-T1AM), which exhibit activities akin to THs. The production and distribution of THMs are intricately linked to the function of specific organs and tissues, highlighting the need for advanced research into the determination and mechanisms of THMs in body. Exposure to endocrine disrupting chemicals (EDCs) can significantly affect the levels of thyroid stimulating hormone (TSH) and THs. This review utilizes machine learning to analyze epidemiological data, identifying potential EDCs that pose risks of hyperthyroidism and hypothyroidism. Additionally, it delves into the toxicological mechanisms of these EDCs, examining their effects on TH production, binding processes, related proteins, and metabolic enzymes. This approach effectively bridges the gap between epidemiological studies and toxicological researches, laying the groundwork for future research trends. By integrating epidemiological studies with machine learning, this review offers insightful perspectives on the potential risks associated with chemical exposure and underscores the necessity for further research in understanding the impact of EDCs on TH metabolism and TH-related health effects.

The impact of environmental factors and contaminants on thyroid function and disease from fetal to adult life: current evidence and future directions

“…It should also be mentioned that in the near future machine learning will be of great help to identify chemicals that interfere with the endocrine system. A recent study has highlighted using these techniques a few new chemicals predicted to interfere with the TSH receptor ( 104 ).…”