Analysis of risk factors and predictive modelling of biomarkers in subclinical hypothyroidism and implications for levothyroxine therapy in disease management

Hypothyroidism is associated with elevated levels of inflammatory cytokines, but very few comprehensive studies have involved a wide range of inflammatory markers, particularly in subclinical hypothyroidism (SH).This study was designed to evaluate the expression of various circulating inflammatory markers and adhesion proteins in patients with subclinical hypothyroidism (SH) and overt hypothyroidism (OH), and their comparison to healthy subjects, while particularly focusing on patients with SH.A cohort of 139 hypothyroid patients and 60 healthy individuals were analysed, using immunological markers to identify significant predictors of SH. Circulating levels of inflammatory markers were quantified, and logistic regression analyses were conducted to identify significant predictors of SH. ROC curve analysis was used to determine the predictive accuracy of key markers. A subset of SH patients was treated with levothyroxine for six months. Real-time PCR was used to assess mRNA expression. Univariate and multivariate logistic regression analyses revealed that IL-1β, IL-6, and ICAM-1 were the best predictive markers of inflammation in SH. These three demonstrated high predictive accuracies in receiver operating characteristic (ROC) curve analysis, with specific cut-off values established for identifying SH patients at risk of inflammation. Additionally, real-time mRNA expression analysis indicated activation of the inflammasome complex in the PBMCs of both OH and SH patients, with the degree of expression correlating with hypothyroidism.IL-1β, IL-6, and ICAM-1 serve as reliable biomarkers for the early detection of inflammation in SH. The activation of the inflammasome complex further supports the need for early intervention with levothyroxine in SH patients to mitigate inflammatory progression.