Unraveling the connection between Hashimoto's Thyroiditis and non-alcoholic fatty liver disease: exploring the role of CD4central memory T cells through integrated genetic approaches.

PURPOSE

Exploring the connection between Hashimoto's thyroiditis (HT) and non-alcoholic fatty liver disease (NAFLD) through integrated genetic approaches.

METHODS

We utilized integrated genetic approaches, such as single-cell RNA sequencing (scRNA-seq) data analysis, Mendelian Randomization (MR), colocalization analysis, cell communication, and metabolic analyses, to investigate potential correlations between HT and NAFLD.

RESULTS

Through the integrated analysis of scRNA-seq data from individuals with HT, NAFLD, and healthy controls, we observed an upregulation in the proportion of CD4central memory (CD4CM) T cells among T cells in both diseases. A total of 63 differentially expressed genes (DEGs) were identified in the CD4CM cells after the differential analysis. By using MR, 8 DEGs (MAGI3, CSGALNACT1, CAMK4, GRIP1, TRAT1, IL7R, ERN1, and MB21D2) were identified to have a causal relationship with HT, and 4 DEGs (MAGI3, RCAN3, DOCK10, and SAMD12) had a causal relationship with NAFLD. MAGI3 was found to be causally linked to both HT and NAFLD. Therefore, MAGI3 was designated as the marker gene. Reverse MR and Steiger filtering showed no evidence of reverse causality. Colocalization analyses further indicated close links between MAGI3 and HT as well as NAFLD. Finally, based on the expression levels of MAGI3, we stratified CD4CM cells into two subsets: MAGI3CD4CM cells and MAGI3CD4CM cells. Functional analyses revealed significant differences between the two subsets, potentially related to the progression of the two diseases.

CONCLUSION

This study delves into the potential connections between HT and NAFLD through integrated genetic methods. Our research reveals an elevated proportion of CD4CM cells within T cells in both HT and NAFLD. Through MR and colocalization analysis, we identify specific genes causally linked to HT and NAFLD, such as MAGI3. Ultimately, based on MAGI3 expression levels, we categorize CD4CM cells into MAGI3CD4CM cells and MAGI3CD4CM cells, uncovering significant differences between them through functional analyses.