Microbiome in Graves Disease Hypothyroidism: Insights from Integrated Analysis for Clinicians Original paper

What was studied?

This original research investigated the gut microbiome in Graves disease hypothyroidism through an integrated analysis of fecal microbiota and metabolome profiles in patients with Graves’ disease (GD) and hypothyroidism (HT) compared to healthy controls. Using 16S rRNA gene sequencing for microbial composition and untargeted liquid chromatography-mass spectrometry for metabolomics, the study aimed to identify distinct microbial and metabolic signatures, explore correlations between microbiota, metabolites, and clinical thyroid indicators (e.g., TSH, FT3, FT4, TRAb), and uncover potential pathways linking gut dysbiosis to thyroid dysfunction. Functional predictions via PICRUSt and pathway enrichment with KEGG highlighted microbial roles in metabolism, while OPLS-DA and Spearman correlations elucidated group differences and interactions.

Who was studied?

The study enrolled 90 participants from Shanghai Tenth People’s Hospital, including 30 patients with newly diagnosed GD (mean age ~40 years, predominantly female), 30 with HT (similar demographics), and 30 age- and sex-matched healthy controls without thyroid disorders or recent antibiotic use. GD was diagnosed based on hyperthyroidism symptoms, elevated FT3/FT4, suppressed TSH, and positive TRAb; HT by hypothyroidism symptoms, reduced FT3/FT4, elevated TSH, and positive TPOAb/TgAb. Exclusion criteria included pregnancy, other autoimmune diseases, gastrointestinal disorders, or probiotic/antibiotic use within three months to minimize confounders affecting the microbiome.

Most important findings

The gut microbiome in Graves disease hypothyroidism showed reduced alpha diversity (Shannon index) in both GD and HT groups compared to controls, with beta diversity (Bray-Curtis) indicating distinct clustering. At the phylum level, Firmicutes dominated, but Bacteroidetes were depleted in disease groups; genus-level shifts included decreased Bacteroides and Prevotella in GD and HT, increased Enterococcus and Veillonella in GD, and elevated Ruminococcus in HT. These alterations suggest dysbiosis contributing to immune dysregulation, relevant for a microbiome signatures database where depleted Bacteroides (anti-inflammatory, SCFA producers) and enriched Enterococcus (potential pathogens) could serve as markers for GD, while Ruminococcus overabundance might signal HT. Metabolomics identified 120 differential metabolites, with GD showing enriched bile acids (e.g., cholic acid) and amino acids (e.g., L-tryptophan), HT displaying depleted fatty acids (e.g., oleic acid) and increased steroids. Correlations revealed Bacteroides positively linked to anti-inflammatory metabolites like indole-3-acetic acid, negatively to TRAb in GD; network analysis highlighted clusters where microbiota influenced thyroid hormones via metabolic pathways like tryptophan and bile acid metabolism.

Key implications

These findings imply that clinicians could use gut microbiome profiling as a non-invasive tool for early detection and monitoring of GD and HT, integrating fecal biomarkers like Bacteroides depletion or bile acid elevation into diagnostic panels to complement thyroid function tests. Therapeutically, targeting dysbiosis via probiotics (e.g., Bacteroides-enriched) or fecal microbiota transplantation might modulate immune responses and metabolic pathways, potentially alleviating symptoms or preventing progression. For clinical practice, this bridges microbiome research by suggesting personalized interventions based on signatures, such as tryptophan supplementation for GD to counteract indole pathway disruptions. Future longitudinal studies should validate causality, perhaps through Mendelian randomization, to refine microbiome-based therapies and expand databases for precision medicine in endocrinology.