Integrative analysis of gut microbiome and host transcriptome reveal novel molecular signatures in Hashimoto's...

Hashimoto's thyroiditis (HT) is an autoimmune disorder with unclear molecular mechanisms. While current diagnosis is well-established, understanding of the gut-thyroid axis in HT remains limited. This study aimed to uncover novel molecular signatures in HT by integrating gut metagenome and host transcriptome data (miRNA/mRNA), potentially elucidating disease pathogenesis and identifying new therapeutic targets.

We recruited 31 early HT patients and 30 healthy controls in a two-stage study (discovery and validation). Blood and fecal samples underwent RNA and metagenomic sequencing, respectively. Integrative analysis included differential expression, weighted correlation network, correlation and random forest analyses. Regression models and ROC curve analysis were used to evaluate the significance of identified molecular signatures in HT.

Integrative analysis revealed subtle changes in gut microbiota diversity and composition in early HT, increased abundance of Bacillota_A and Spirochaetota at the phylum level, and significant differences in 24 genera and 67 species. Ecological network analysis indicated an imbalance in the gut microbiota with reduced inhibitory interactions against pathogenic genera in HT. Functional analysis showed changes in infection- and immune-related pathways. Three characteristic species (Salaquimonas_sp002400845, Clostridium_AI_sp002297865, and Enterocloster_citroniae) were identified as most relevant to HT. Analysis of miRNA and mRNA expression profiles uncovered pathways related to immune response, inflammation, infection, metabolism, proliferation, and thyroid cancer in HT. Based on correlations with HT and interactions between them, six characteristic RNAs (hsa-miR-548aq-3p, hsa-miR-374a-5p, GADD45A, IRS2, SMAD6, WWTR1) were identified. Furthermore, our study uncovered significant gut microbiota-host transcriptome interactions in HT, revealing enrichment in metabolic, immune, and cancer-related pathways, particularly with strong associations among those 9 key molecular signatures. The validation stage confirmed improved HT classification accuracy by combining these signatures (AUC = 0.95, ACC = 0.85), suggesting their potential significance in understanding HT pathogenesis.

Our study reveals novel molecular signatures linking gut microbiome and host transcriptome in HT, providing new insights into the disease pathogenesis. These findings not only enhance our understanding of the gut-thyroid axis but also suggest potential new directions for therapeutic interventions in HT.