Proteomic analysis of thyroid tissue reveals enhanced catabolic activity in Graves' disease compared to toxic multinodular goitre.
Duygu Temiz KaradağBerrin CetinarslanMurat KasapNuh Zafer CanturkGurler AkpinarZeynep CanturkIlhan TarkunTurgay SimsekAlev SelekPublished in: Cell biochemistry and function (2021)
Graves' disease (GD) and toxic multinodular goitre (TMNG) are the most common thyroid diseases which mainly lead to thyrotoxicosis, however, the underlying mechanism of distinct clinical presentations remains unclear. Protein extracts from the thyroid tissue specimens of the patients with GD and TMNG were subjected to Difference Gel Electrophoresis (DIGE). Differentially regulated protein spots were determined by image analysis, and the spots displaying statistically significant differences were identified by Matrix-Assisted Laser Desorption Ionization Time of Flight Mass Spectrometer (MALDI-TOF) followed by MASCOT search. Western blot analysis was used to verify changes occurring at the protein levels. The identified proteins were classified based on their functions in metabolic pathways using bioinformatics algorithms. Fifteen proteins showed significant alterations in abundance between the two disease groups. Bioinformatic analysis revealed the differentially regulated proteins were particularly related to catabolism, oxidative stress and especially energy utilization pathways, including glycolysis, proteolysis, ketone body catabolism and other energy metabolism-related pathways. SIGNIFICANCE OF THE STUDY: Previously, GD has been the subject of many studies that performed the proteomics approaches in the orbital tissue samples or tear. This is one of the very few studies that investigate the changes in the proteome of thyroid tissue in GD. We demonstrated mainly the upregulation of catabolic activity-related proteins in patients with GD compared to TMNG. Although it remains to be elucidated, some of these proteins can be used as markers for GD or have a role in the pathogenesis of the disease. Our study contributes the increasing data over time by providing new biomarker candidates for GD.