Bioinformatics and Connectivity Map Analysis Suggest Viral Infection as a Critical Causative Factor of Hashimoto's Thyroiditis

Targeting the aryl hydrocarbon receptor with FICZ regulates IL-2 and immune infiltration to alleviate Hashimoto's thyroiditis in mice

Hashimoto's thyroiditis (HT) is the most frequent autoimmune disorder. Growing work points to the involvement of aryl hydrocarbon receptor (AhR), a ligand-dependent transcription factor, in the regulation of immune homeostasis. However, the roles of AhR and its ligands in HT remains unclear. In this study, we leveraged public human database analyses to postulate that the AhR expression was predominantly in thyroid follicular cells, correlating significantly with the thyroid infiltration levels of multiple immune cells in HT patients. Using a thyroglobulin-induced HT mouse model and in vitro thyroid follicular epithelial cell cultures, we found a significant downregulation of AhR expression in thyrocytes both in vivo and in vitro. Conversely, activating AhR by FICZ, a natural AhR ligand, mitigated inflammation and apoptosis in thyrocytes in vitro and conferred protection against HT in mice. RNA sequencing (RNA-seq) of thyroid tissues indicated that AhR activation moderated HT-associated immune or inflammatory signatures. Further, immunoinfiltration analysis indicated that AhR activation regulated immune cell infiltration in the thyroid of HT mice, such as suppressing cytotoxic CD8+ T cell infiltration and promoting anti-inflammatory M2 macrophage polarization. Concomitantly, the expression levels of interleukin-2 (IL-2), a lymphokine that downregulates immune responses, were typically decreased in HT but restored upon AhR activation. In silico validation substantiated the binding interaction between AhR and IL-2. In conclusion, targeting the AhR with FICZ regulates IL-2 and immune infiltration to alleviate experimental HT, shedding new light on the therapeutic intervention of this prevalent disease.

An AI Approach to Identifying Novel Therapeutics for Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a chronic autoimmune disorder that has a significant impact on quality of life and work capacity. Treatment of RA aims to control inflammation and alleviate pain; however, achieving remission with minimal toxicity is frequently not possible with the current suite of drugs. This review aims to summarise current treatment practices and highlight the urgent need for alternative pharmacogenomic approaches for novel drug discovery. These approaches can elucidate new relationships between drugs, genes, and diseases to identify additional effective and safe therapeutic options. This review discusses how computational approaches such as connectivity mapping offer the ability to repurpose FDA-approved drugs beyond their original treatment indication. This review also explores the concept of drug sensitisation to predict co-prescribed drugs with synergistic effects that produce enhanced anti-disease efficacy by involving multiple disease pathways. Challenges of this computational approach are discussed, including the availability of suitable high-quality datasets for comprehensive analysis and other data curation issues. The potential benefits include accelerated identification of novel drug combinations and the ability to trial and implement established treatments in a new index disease. This review underlines the huge opportunity to incorporate disease-related data and drug-related data to develop methods and algorithms that have strong potential to determine novel and effective treatment regimens.