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Abstract Background Uric acid was found to have a positive correlation with thyroid nodules in the cross-sectional studies recently. We aimed to conduct a retrospective cohort study to investigate whether uric acid is a risk factor for the development of thyroid nodules. Methods We reviewed the data of individuals who attended the medical check-ups in our hospital from 2010 to 2019. A total of 6587 adults without thyroid nodules at baseline were enrolled in this study. Logistic regression with or without restricted cubic spline function was used to investigate the non-linear or linear association between uric acid and thyroid nodules, respectively. Results Baseline characteristics showed that subjects mainly consisted of the healthy, young population. After fully adjusting for the potential confounders, such as age, sex, metabolic and inflammatory indicators, hepatic and renal function, a logistic restricted cubic spline regression model suggested that uric acid had a significant association (P = 0.028) with the development of thyroid nodules, but the association was not non-linear (P = 0.516). The results indicate that the association between them is linear, which was demonstrated by a logistic regression model, in which the odds ratio of uric acid per 100 mmol/L was 1.137 (P = 0.004). Age, sex, diastolic blood pressure, fasting blood sugar, and blood monocyte were found to be risk factors for thyroid nodules as well. Conclusion Uric acid is an independent risk factor for the formation of thyroid nodules. This finding warrants attention to this risk factor in apparently healthy adults.

Background. Some studies have demonstrated that inflammation is highly associated with the prevalence of thyroid nodules (TNs). However, more confounders, such as metabolic diseases, should be adjusted. Methods. A clinical study collecting 2722 subjects was conducted to confirm the association between inflammation and TNs. The underlying mechanism was investigated in combination with bioinformatics analysis. Results. In the clinical study, propensity score matching was used to match metabolic parameters and other confounders, and it is observed that subjects with high inflammation had a higher prevalence of TNs and thyroid-stimulating hormone (TSH) than those with low inflammation. After further matching TNs, it is found that inflammation was positively associated with TSH, which was also demonstrated in a population without TNs. In bioinformatics study, inflammation did not promote TNs formation directly. Instead, it inhibited the synthesis of thyroid hormone, which might be the cause of the elevated TSH coexisting with inflammation. Conclusion. Inflammation promotes the development of TNs disease, probably due to its indirect effect through inhibiting the synthesis of thyroid hormone, which results in the elevation of TSH.

Purpose. Several commercial tests have been used for the classification of indeterminate thyroid nodules in cytology. However, the geographic inconvenience and high cost confine their widespread use. This study aims to develop a classifier for conveniently clinical utility. Methods. Gene expression data of thyroid nodule tissues were collected from three public databases. Immune-related genes were used to construct the classifier with stacked denoising sparse autoencoder. Results. The classifier performed well in discriminating malignant and benign thyroid nodules, with an area under the curve of 0.785 [0.638–0.931], accuracy of 92.9% [92.7–93.0%], sensitivity of 98.6% [95.9–101.3%], specificity of 58.3% [30.4–86.2%], positive likelihood ratio of 2.367 [1.211–4.625], and negative likelihood ratio of 0.024 [0.003–0.177]. In the cancer prevalence range of 20–40% for indeterminate thyroid nodules in cytology, the range of negative predictive value of this classifier was 37–61%, and the range of positive predictive value was 98–99%. Conclusion. The classifier developed in this study has the superb discriminative ability for thyroid nodules. However, it needs validation in cytologically indeterminate thyroid nodules before clinical use.

Background. Metabolic syndrome (MS) and its components have been demonstrated to facilitate the prevalence of thyroid nodules (TNs). The underlying pathogenesis needs to be elucidated. Methods. A total of 2722 subjects, who underwent health checkup in our institute from December 2014 to November 2018, were retrospectively and randomly collected. After exclusion, 2068 subjects were chosen, and their anthropic and clinical data were collected. Results. After matching age, gender, uric acid (UA), and creatinine (Cr) by propensity score matching (PSM), subjects with MS had higher prevalence of TNs than those without MS, as well as higher thyroid-stimulating hormone (TSH) and inflammatory levels, indicated by the higher white blood cell (WBC), lymphocyte (LY), and monocyte/high-density lipoprotein (Mo/HDL). After matching age, gender, UA, Cr, TSH, free triiodothyronine (FT3), thyroxine (FT4), WBC, NE, LY, Mo, NE/LY, LY/Mo, and Mo/HDL by PSM, no significant difference of the prevalence of TNs was found between MS and non-MS groups. Step logistic regression suggested glucose intolerance (GI), among all the components of MS, was an independent impact factor of TNs and was considered to contribute most to the formation of TNs. The prevalence of TNs was higher in the GI group after matching age, gender, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting blood sugar (FBS), UA, Cr, triglyceride (TG), cholesterol (CHOL), HDL, and low-density lipoprotein (LDL). Conclusions. Patients with MS have a higher prevalence of TNs, probably due to the elevated TSH and inflammatory levels in vivo. Among the components of MS, glucose intolerance contributes most to the development of TNs.