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Clinical and Immunological Aspects in Hashimoto's Thyroiditis.

ABSTRACT: We propose to establish the relationship between the clinical, functional and immunological parameters in a cohort of women with Hashimoto's thyroiditis. The study included 68 patients between 19 and 70 who were hospitalized for two years in the Endocrinology Clinic of the Hospital in Timisoara. The thyroidal dimensions and the aspects of the thyroidal stroma were shown by echography examinations. The functional parameters like the serum TSH and free T4 concentrations were determined by chemiluminescent methods. The immunological investigations (antithyroglobulin and antiperoxidase antibodies) were performed by the ELISA method. Comparisons were performed by the t test and the Pearson correlation analysis. The correlation between the aspects of thyroidal stroma and thyroid function revealed hypothyroidism in most cases with moderate (++) or severe (+++) echogenity. Another researched aspect was that of correlation of the serum levels of TSH with the thyroidal dimension. The following correlations were obtained: r= - 0.14 in patients with clinical hypothyroidism and r= - 0.3055 in those with subclinical hypothyroidism. The Pearson coefficients for the level of TSH in um and those of the antiperoxidase antibodies, according to clinical and functional categories, revealed the following results: r= - 0.1580 in patients with clinical hypothyroidism and r= - 0.1961 in those with subclinical hypothyroidism. Patients with clinical hypothroidism have significant higher serum level of TSH as compared with those of the patients with subclinical hypothyroidism (p=0.0001). We established a relation between the severe hypoechogenity and hypothyroidism status in patients with positive serum antibodies (r= 0.5695).

SUBMITTER: Rosca A

PROVIDER: S-EPMC6156970 | biostudies-other | 2003 Dec

REPOSITORIES: biostudies-other

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Clinical and Immunological Aspects in Hashimoto's Thyroiditis.

Rosca Adriana A Dumitrascu Victor V Grecu Daniela D Zosin Ioana I David Mihaela M

EJIFCC 20031202 3

We propose to establish the relationship between the clinical, functional and immunological parameters in a cohort of women with Hashimoto's thyroiditis. The study included 68 patients between 19 and 70 who were hospitalized for two years in the Endocrinology Clinic of the Hospital in Timisoara. The thyroidal dimensions and the aspects of the thyroidal stroma were shown by echography examinations. The functional parameters like the serum TSH and free T4 concentrations were determined by chemilum ...[more]

PMID: 30275810

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Project description:BackgroundHashimoto's thyroiditis (HT) frequently occurs among autoimmune diseases and may simultaneously appear with thyroid cancer. However, it is difficult to diagnose HT at an early stage just by clinical symptoms. Thus, it is urgent to integrate multiple clinical and laboratory factors for the early diagnosis and risk prediction of HT.MethodsWe recruited 1,303 participants, including 866 non-HT controls and 437 diagnosed HT patients. 44 HT patients also had thyroid cancer. Firstly, we compared the difference in thyroid goiter degrees between controls and patients. Secondly, we collected 15 factors and analyzed their significant differences between controls and HT patients, including age, body mass index, gender, history of diabetes, degrees of thyroid goiter, UIC, 25-(OH)D, FT3, FT4, TSH, TAG, TC, FPG, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol. Thirdly, logistic regression analysis demonstrated the risk factors for HT. For machine learning modeling of HT and thyroid cancer, we conducted the establishment and evaluation of six models in training and test sets.ResultsThe degrees of thyroid goiter were significantly different among controls, HT patients without cancer (HT-C), and HT patients with thyroid cancer (HT+C). Most factors had significant differences between controls and patients. Logistic regression analysis confirmed diabetes, UIC, FT3, and TSH as important risk factors for HT. The AUC scores of XGBoost, LR, SVM, and MLP models indicated appropriate predictive power for HT. The features were arranged by their importance, among which, 25-(OH)D, FT4, and TSH were the top three high-ranking factors.ConclusionsWe firstly analyzed comprehensive factors of HT patients. The proposed machine learning modeling, combined with multiple factors, are efficient for thyroid diagnosis. These discoveries will extensively promote precise diagnosis, personalized therapies, and reduce unnecessary cost for thyroid diseases.

Project description:ObjectiveHashimoto's thyroiditis, also known as chronic lymphocytic thyroiditis, is a common autoimmune thyroiditis, which mostly occurs in young and middle-aged women. It can be manifested as hyperthyroidism in the early stage; hypothyroidism may appear with the progression of the disease. Studies have shown that multiple factors such as heredity, environment, and autoimmunity are involved in the pathogenesis, but the specific mechanism is not clear. In our study, we tried to find key genes and potential molecular mechanisms of Hashimoto's thyroiditis to provide new ideas for the therapeutic targets of Hashimoto's thyroiditis.MethodGSE138198 and GSE54958 were downloaded from the GEO database, and two datasets were combined for analysis. The combined data were normalized to identify the differentially expressed genes (DEGs), and GO and KEGG enrichment analyses were performed. Protein-protein interaction (PPI) networks and hub genes between DEGs were identified. We also used the miRWalk database to identify regulatory miRNAs associated with expressions of DEGs.ResultWe identified 182 DEGs (160 upregulated and 22 downregulated) between Hashimoto's disease patients and the healthy control group. GO analysis showed that DEGs were mostly concentrated in detection of chemical stimulus involved in sensory perception, intermediate filament cytoskeleton, and olfactory receptor activity. KEGG pathway analysis showed that DEGs were mainly related to olfactory transduction. Some members of the KRTAP family and HTR5A, KNG1, DRD3, HTR1D, TAS2R16, INSL5, TAS2R42, and GRM7 are the most important hub genes in the PPI network. In addition, we recognized that OTUD4, LLPH, and ECHDC1 were the most important hub genes in the miRNA-target gene network.ConclusionIn this study, a series of bioinformatics analyses of DEGs were performed to identify the key genes and pathways associated with Hashimoto's thyroiditis. These genes and pathways provide a more detailed understanding of the pathogenesis of Hashimoto's disease and provide new ideas for the therapeutic targets of Hashimoto's thyroiditis.

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Clinical and Immunological Aspects in Hashimoto's Thyroiditis.

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Clinical and Immunological Aspects in Hashimoto's Thyroiditis.

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