Gut microbiota and autoimmune thyroid disease: a bidirectional Mendelian randomization study and mediation analysis

Area of Science:

• Investigates the intersection of gut microbiota, immune system, and autoimmune thyroid disease (AITD).
• Utilizes advanced genetic and statistical methodologies for causal inference in complex biological systems.

Background:

• The gut microbiota (GM) significantly impacts immune function and health, but its role in AITD is not well understood.
• Autoimmune thyroid diseases (AITD), including Graves' disease and Hashimoto's thyroiditis, are common immune-mediated conditions.
• Understanding the GM-AITD connection could offer novel therapeutic targets.

Purpose of the Study:

• To determine the causal relationship between specific gut microbiota (GM) and autoimmune thyroid disease (AITD).
• To explore the potential pathogenic or protective roles of GM in Graves' disease and Hashimoto's thyroiditis.
• To identify immune cell phenotypes that mediate the effects of GM on AITD.

Main Methods:

• Employed bidirectional Mendelian randomization (MR) analysis using pooled genome-wide association study (GWAS) data.
• Analyzed 211 GM traits, 731 immune cell phenotypes, and data for Hashimoto's thyroiditis and Graves' disease.
• Utilized multivariable MR and sensitivity analyses to confirm causal links and mediating effects.

Main Results:

• Identified 7 gut microbial taxa positively associated with AITD and 14 taxa negatively associated.
• Revealed specific mediating roles of immune cell phenotypes in the GM-AITD relationship.
• Highlighted protective effects of *Actinobacteria* on Hashimoto's thyroiditis via myeloid dendritic cells and facilitating effects of *Bifidobacterium* on Graves' disease through specific T cell subsets.

Conclusions:

• Provides evidence for causal links between distinct gut microbial taxa and AITD.
• Identifies specific immune cell phenotypes as key mediators in the gut microbiota-thyroid autoimmunity axis.
• Suggests potential for targeted gut microbiota modulation in managing AITD.