Identification of BTK as an immune-related biomarker for Hashimoto's thyroiditis by integrated bioinformatic analysis

Hashimoto's thyroiditis (HT) is one of the most common autoimmune disorders characterized by diffuse enlargement of the thyroid gland, lymphocyte infiltration, and thyroid-specific autoantibodies. Cellular and humoral immune disorders have been implicated in the development of HT. However, little is known regarding the role of immune-related molecules in HT. This study was aimed to identify key immune-related biomarkers in HT by using bioinformatic analysis.

Integration of the sequencing data from HT and normal control (NC) in the GSA and GTEx databases yielded a dataset named NGS. The GSE138198 dataset from the GEO database was downloaded as a validation set. WGCNA analysis was performed to identify key modules associated with HT. Lasso regression analysis (LASSO) and random forest (RF) were performed to determine potential diagnostic biomarkers. The potential value was assessed by using receiver operating characteristic (ROC) curve analysis. CIBERSORT algorithm was used to evaluate the infiltration of immune cells in HT and NC samples. The transcript levels of verified genes from expanded samples were detected by quantitative real-time PCR.

A total of 1,401 differentially expressed genes (DEGs) were identified in HT patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated that these DEGs were predominantly enriched in immune-related pathways. Furthermore, 192 immune-related genes were identified in HT through the intersection of WGCNA modules, DEGs, and the IRGs. Among them, two upregulated genes ((Bruton's tyrosine kinase, BTK) and CD19) showed the potential diagnostic value for HT by using machine learning. The ROC curve analysis revealed that BTK had a higher diagnostic value than CD19 across two datasets. Intriguingly, only BTK expression was upregulated in the peripheral blood mononuclear cells of HT patients, and was significantly positively correlated with the serum levels of thyroid autoantibodies. Further studies confirmed a significant positive correlation between BTK and increased proportions of plasma cells in HT patients.

This study identified BTK was significantly increased in HT patients, which might be the involved in the pathogenesis of HT by regulating plasma cells and represented a potential immune-related biomarker of HT.