Thyroid follicular cell-derived GDF15 attenuates inflammation and lipid dysregulation in Hashimoto's thyroiditis

Endoplasmic reticulum stress in Hashimoto’s thyroiditis: a candidate amplification node linking thyroid-specific vulnerability and immune dysregulation

A testable positive-feedback perspective in which thyrocyte ERS injury and immune effector amplification may mutually reinforce one another is proposed, in which thyrocyte ERS injury and immune effector amplification may mutually reinforce one another.

Spatial transcriptomic analysis identifies a necroptosis-prone thyroid follicular cell state in Hashimoto’s thyroiditis

This study provides a multimodal characterization of necroptosis in HT, showing that the inflammatory immune microenvironment is associated with TFC loss and activation of an RIPK3-MLKL-predominant necroptosis-related program, without detectable upregulation of total or phosphorylated RIPK1.

Comparative systemic inflammatory marker patterns across Hashimoto’s thyroiditis, Graves’ disease, and non-autoimmune goiter

Introduction: Autoimmune thyroid diseases (AITDs), including Hashimoto’s thyroiditis (HT) and Graves’ disease (GD), are characterized by immune-mediated thyroid dysfunction. However, whether systemic inflammatory burden differs among thyroid disease phenotypes remains unclear.Methods: In this cross-sectional study, 100 adult patients (HT n=60, GD n=11, goiter n=29) were evaluated. Serum C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), neutrophil-to-lymphocyte ratio (NLR), and procalcitonin levels were compared among groups using the Kruskal–Wallis test with Bonferroni-adjusted post-hoc analyses. General linear models adjusted for age, sex, and disease duration were applied. Associations between inflammatory markers and thyroid parameters were assessed using Spearman correlation analysis.Results: CRP (p=0.638), ESR (p=0.135), and NLR (p=0.466) did not differ significantly among the three thyroid phenotypes. Although statistically significant differences in procalcitonin levels were observed between groups (p=0.031), lower measurable values were observed in the Graves’ disease group, and this difference remained significant after adjustment for confounders (adjusted p=0.041). Correlation analyses demonstrated generally weak associations between inflammatory markers and thyroid autoantibodies, with only a modest correlation between procalcitonin and TRAb reaching statistical significance (r=0.22, p=0.048).Conclusions: Routine systemic inflammatory markers do not meaningfully distinguish autoimmune from non-autoimmune thyroid disease phenotypes. Although procalcitonin demonstrated a phenotype-related difference, its clinical relevance remains uncertain. These findings support the concept that autoimmune thyroid diseases predominantly reflect localized rather than systemic inflammatory activation.

Peripheral blood inflammatory indices across thyroid functional states in Graves’ disease: associations with liver biochemical abnormalities and hyperthyroid relapse

Background Graves’ disease is an organ-specific autoimmune disorder driven by thyrotropin receptor antibody (TRAb) and accompanied by persistent immune and inflammatory activation. Peripheral blood inflammatory indices are readily available and have been increasingly used to assess inflammation in autoimmune diseases. However, their clinical significance in Graves’ disease across different thyroid functional states is unknown. Methods In this retrospective study, 687 patients with Graves’ disease were enrolled. Five peripheral blood inflammatory indices were calculated, including the neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and pan-immune-inflammation value (PIV). Patients were stratified and compared according to thyroid functional status. Because sex distribution differed among the groups, sex-adjusted median regression models were additionally fitted, and group-by-sex interactions were examined. Correlation analysis, logistic regression, and receiver operating characteristic (ROC) curve analysis were used to evaluate associations of these indices with clinical characteristics, liver biochemical abnormalities, and hyperthyroid relapse. The outcome models were internally validated using bootstrap resampling and repeated 10-fold cross-validation. Results Sex distribution differed significantly among the thyroid functional groups. After adjustment for sex, MLR, SIRI, and PIV remained significantly higher in the overt hyperthyroid group than in the subclinical hyperthyroid and euthyroid groups. In patients with overt hyperthyroidism, MLR was positively correlated with age, FT3, FT4, ALT, and AST (rs = 0.152–0.206, all P < 0.05). Multivariable logistic regression identified TRAb, hemoglobin, and standardized MLR as independent factors associated with liver biochemical abnormalities, and the resulting model showed limited-to-moderate discrimination (apparent AUC, 0.703; optimism-corrected AUC, 0.692; cross-validated AUC, 0.680). Among the five inflammatory indices, PIV showed the highest individual discrimination for hyperthyroid relapse (AUC, 0.734). The TRAb–PIV model showed relatively good internal discrimination (apparent AUC, 0.815; optimism-corrected AUC, 0.805; cross-validated AUC, 0.788). Conclusion Compared with NLR and SII, the monocyte-containing indices MLR, SIRI, and PIV showed clearer differences across thyroid functional states in Graves’ disease and may provide complementary inflammation-related information. Among them, MLR was associated with liver biochemical abnormalities, whereas PIV showed potential adjunctive value for hyperthyroid relapse risk assessment.

Exosome in Hashimoto’s thyroiditis: from pathogenesis to diagnostic and therapeutic potential

Extracellular vesicles at the immune–metabolic crossroads of Hashimoto’s thyroiditis and diabetes mellitus

This review compares how EVs remodel the immune microenvironment in HT, type 2 diabetes mellitus (T2DM), and related disease contexts, with attention to donor cells, cargo, recipient pathways, biomarkers, and therapeutic implications.