Proteomics and transcriptomics combined reveal specific immunological markers in autoimmune thyroid disease - Chen, Xia; Chen, Hui (Frontiers in Immunology, 2025)
ObjectiveThe pathogenesis of AITD remains unclear to date. This study employs a combination of proteomics and transcriptomics analysis to identify and validate specific immune response markers in patients with hyperthyroidism and hypothyroidism, thereby providing a scientific basis for the clinical diagnosis and treatment of AITD.MethodsBy collecting serum and whole blood tissue samples from patients with hyperthyroidism, hypothyroidism, and healthy controls, this study utilizes a combination of transcriptomics and proteomics to analyze changes in immune-related signaling molecules in patients. Specific biomarkers were identified, and the ELISA method was employed to determine the expression levels of these clinical markers and their correlation with clinical features of the patients, ultimately establishing a predictive model.ResultsTranscriptomic and proteomic analyses were conducted to identify differentially expressed genes and proteins in patients with hyperthyroidism and hypothyroidism compared to healthy controls. Enrichment analysis revealed that these differentially expressed genes and proteins are primarily associated with immune function, antigen-antibody binding, and alterations in immune cells. Through the combined analysis of transcriptomics and proteomics, key genes IGHG3, ISG15, and ZNF683 were identified. ELISA results from clinical patient serum samples indicated that the levels of IGHG3 were significantly higher in both the hyperthyroid and hypothyroid groups compared to the control group (P<0.05). Additionally, the serum levels of ISG15 in the hyperthyroid group were greater than those in both the control and hypothyroid groups (P<0.05), while the serum levels of ZNF683 in the hypothyroid group exceeded those in the control and hyperthyroid groups (P<0.05). Furthermore, all three biomarkers correlated with the thyroid function of the patients. Prediction models for hyperthyroid and hypothyroid patients were constructed using IGHG3, ISG15, and ZNF683, demonstrating good performance metrics and decision effect.ConclusionIn patients with hyperthyroidism and hypothyroidism, significant changes primarily occur in immune function and immune cells when compared to healthy individuals. Key signaling molecules were identified: ISG15 for hyperthyroidism, ZNF683 for hypothyroidism, and IGHG3 common to both conditions. These findings provide new biomarkers for the diagnosis and monitoring of clinical patients, thereby offering a scientific basis for research on AITD and personalized treatment approaches.