Journal of Thyroid Research最新文献

Introduction: Thyroid cancer is the third most common cancer that occurs in children and adolescents. Papillary thyroid carcinoma (PTC) is the most common type of thyroid malignancy. Although the mortality rate of thyroid malignancy in children is usually low, the disease recurrence is higher in children with more severe clinical presentation than in adults. This study aimed to determine the demographic and clinicopathological characteristics and outcome of pediatric and adolescent patients with thyroid malignancy in Indonesia.

Methods: The retrospective study included all patients diagnosed with thyroid carcinoma aged <20 years, from January 1, 2015, to December 31, 2019. Twenty-nine subjects fulfilled the inclusion and exclusion criteria. We retrieved baseline characteristics, pathology features, TSH and fT4 status, radioactive iodine therapy data, and patients' outcomes. Then, data were analyzed using the chi-square or Fisher's exact method.

Results: We identified 29 eligible subjects, including 3 boys and 26 girls. The most common type of thyroid carcinoma was PTC (96.5%), and follicular type (31%) was the predominant variant of PTC. Lymph node involvement occurred in 24% of patients, while distant metastasis occurred in 17.2% of patients with PTC. Twenty-four (82.7%) patients had stage 1 disease. Disease recurrence was recorded in 31% of patients during the study period with a median follow-up time of 24 months.

Conclusion: PTC is the most frequent type of thyroid carcinoma among children and adolescents. This malignancy has a low mortality rate, but the recurrence rate remains high among younger patients than adults even during a short-term follow-up analysis. Distant metastasis and lymph node involvement are commonly found in this age group.

Background: The aim of this study was to identify germline mutation of the RET (rearranged during transfection) gene in patients with medullary thyroid carcinoma (MTC) and their first-degree relatives to find presymptomatic carriers for possible prophylactic thyroidectomy. Methods/Patients. We examined all six hot spot exons (exons 10, 11, 13, and 14-16) of the RET gene by PCR and bidirectional Sanger sequencing in 45 Iranian patients with MTC (either sporadic or familial form) from 7 unrelated kindred and 38 apparently sporadic cases. First-degree relatives of RET positive cases were also genotyped for index mutation. Moreover, presymptomatic carriers were referred to the endocrinologist for further clinical management and prophylactic thyroidectomy if needed.

Results: Overall, the genetic status of all of the participants was determined by RET mutation screening, including 61 affected individuals, 22 presymptomatic carriers, and 29 genetically healthy subjects. In 37.5% (17 of 45) of the MTC referral index patients, 8 distinct RET germline mutations were found, including p.C634R (35.3%), p.M918T (17.6%), p.C634Y (11.8%), p.C634F (5.9%), p.C611Y (5.9%), p.C618R (5.9%), p.C630R (5.9%), p.L790F (5.9%), and one uncertain variant p.V648I (5.9%). Also, we found a novel variant p.H648R in one of our apparently sporadic patients.

Conclusion: RET mutation detection is a promising/golden screening test and provides an accurate presymptomatic diagnostic test for at-risk carriers (the siblings and offspring of the patients) to consider prophylactic thyroidectomy. Thus, according to the ATA recommendations, the screening of the RET proto-oncogene is indicated for patients with MTC.

Micronutrients are involved in various vital cellular metabolic processes including thyroid hormone metabolism. This study aimed to investigate the correlation between serum levels of micronutrients and their effects on thyroid parameters. The correlation of serum levels of micronutrients and thyroid markers was studied in a group of 387 healthy individuals tested for thyroid markers (T4, T3, FT4, FT3, TSH, anti-TPO, RT3, and anti-Tg) and their micronutrient profile at Vibrant America Clinical Laboratory. The subjects were rationalized into three groups (deficient, normal, or excess levels of micronutrients), and the levels of their thyroid markers were compared. According to our results, deficiency of vitamin B2, B12, B9 and Vit-D25[OH] (p < 0.05) significantly affected thyroid functioning. Other elemental micronutrients such as calcium, copper, choline, iron, and zinc (p < 0.05) have a significant correlation with serum levels of free T3. Amino acids asparagine (r = 0.1765, p < 0.001) and serine (r = 0.1186, p < 0.05) were found to have a strong positive correlation with TSH. Valine, leucine, and arginine (p < 0.05) also exhibited a significant positive correlation with serum levels of T4 and FT4. No other significant correlations were observed with other micronutrients. Our study suggests strong evidence for the association of the levels of micronutrients with thyroid markers with a special note on the effect of serum levels of certain amino acids.

Graves's disease and thyroiditis induce hyperthyroidism, the causes of which remain unclear, although they are involved with genetic and environmental factors. We aimed to evaluate polygenetic variants for hyperthyroidism risk and their interaction with metabolic parameters and nutritional intakes in an urban hospital-based cohort. A genome-wide association study (GWAS) of participants with (cases; n = 842) and without (controls, n = 38,799) hyperthyroidism was used to identify and select genetic variants. In clinical and lifestyle interaction with PRS, 312 participants cured of hyperthyroidism were excluded. Single nucleotide polymorphisms (SNPs) associated with gene-gene interactions were selected by hyperthyroidism generalized multifactor dimensionality reduction. Polygenic risk scores (PRSs) were generated by summing the numbers of selected SNP risk alleles. The best gene-gene interaction model included tumor-necrosis factor (TNF)_rs1800610, mucin 22 (MUC22)_rs1304322089, tribbles pseudokinase 2 (TRIB2)_rs1881145, cytotoxic T-lymphocyte-associated antigen 4 (CTLA4)_rs231775, lipoma-preferred partner (LPP)_rs6780858, and human leukocyte antigen (HLA)-J_ rs767861647. The PRS of the best model was positively associated with hyperthyroidism risk by 1.939-fold (1.317-2.854) after adjusting for covariates. PRSs interacted with age, metabolic syndrome, and dietary inflammatory index (DII), while hyperthyroidism risk interacted with energy, calcium, seaweed, milk, and coffee intake (P < 0.05). The PRS impact on hyperthyroidism risk was observed in younger (<55 years) participants and adults without metabolic syndrome. PRSs were positively associated with hyperthyroidism risk in participants with low dietary intakes of energy (OR = 2.74), calcium (OR = 2.84), seaweed (OR = 3.43), milk (OR = 2.91), coffee (OR = 2.44), and DII (OR = 3.45). In conclusion, adults with high PRS involved in inflammation and immunity had a high hyperthyroidism risk exacerbated under low intakes of energy, calcium, seaweed, milk, or coffee. These results can be applied to personalized nutrition in a clinical setting.

Purpose: We hypothesized that innate immune response pathways might be involved in thyroid carcinogenesis. To investigate this hypothesis, we aimed at analyzing the expression of several receptors and molecules in the innate immune system in papillary thyroid carcinoma (PTC) and anaplastic thyroid carcinoma (ATC) tissues.

Methods: Of the surgically resected specimens, 11 ATC tissues, 25 PTC tissues, and 8 nodular hyperplasia (NH) tissues were selected and examined for the expression of toll-like receptor (TLR) 2, TLR3, TLR4, TLR5, TLR7, TLR9, the myeloid differentiation primary response gene 88 (MyD88), and toll-interleukin-1 receptor domain-containing adaptor inducing INF-β (TRIF) by immunohistochemistry (IHC).

Results: Several TLRs were expressed in each tissue. TLR3 was strongly expressed in all tissues. In contrast, TLR4 was not detected in any tissues. While TLR5 was moderately expressed in NH but significantly reduced in PTC and ATC, TLR9 was absent in NH tissue but moderately expressed in both PTC and ATC. On MyD88 expression, no significant difference was found between PTC and ATC. TRIF was significantly upregulated in PTC and ATC compared to NH. Surprisingly, PTC and ATC tissues exhibited similar expression patterns of TLRs, MyD88, and TRIF.

Conclusion: These data suggest the involvement of the innate immune system in both PTC and ATC. Specifically, TLR3-mediated TRIF activation was confirmed in PTC and ATC. This provides new insight into thyroid carcinogenesis.

Thyroid hormone (TH) perturbation is a common medical problem. Because of substantial public health impact, prior researchers have studied hyper- and hypothyroidism in animal models. Although most prior research focused on in utero and/or developmental effects, changes in circulating TH levels are commonly seen in elderly individuals: approximately 20% of persons older than 80 years have clinically impactful hypothyroidism and up to 5% have clinical hyperthyroidism, with women being more often affected than men. TH disease model methodology in mice have varied but usually focus on a single sex, and the impact(s) of TH perturbation on the adult brain are not well understood. We administered thyroxine to middle-aged (13 to 14 months) male and female mice to model hyperthyroidism and TH-lowering drugs propylthiouracil (PTU) and methimazole, to induce hypothyroidism. These pharmacological agents are used commonly in adult humans. Circulating TH-level changes were observed when thyroxine was dosed at 20 µg/mL in drinking water for two weeks. By contrast, PTU and methimazole did not elicit a consistent reproducible effect until two months of treatment. No substantial changes in TH levels were detected in brain tissues of treated animals; however, pronounced changes in gene expression, specifically for TH-processing transcripts, were observed following the treatment with thyroxine. Our study indicated a robust compensatory mechanism by which the brain tissue/cells minimize the TH fluctuation in CNS by altering gene expression. Neurobehavioral changes were related to the TH perturbation and suggested potential associations between cognitive status and hyper- and hypothyroidism.

Background: Primary hypothyroidism is characterized by reduced quality of life (QoL). Although thyrotropin (TSH) is utilized as the primary indicator of thyroid disease and treatment adequacy, no simple correlation between QoL and TSH has been shown. This study aimed to investigate changes in clinically relevant predictors during initiation of levothyroxine (L-T4) therapy and their ability to predict improvement in QoL.

Method: Quality of life was measured in patients with newly diagnosed hypothyroidism, during the initial 12 months of L-T4 therapy, by the thyroid-related patient-reported outcome questionnaire, ThyPRO-39. The main outcome measures were the Composite QoL scale and the Tiredness and Emotional Susceptibility subscales (0-100, higher scores worse). Clinical variables (resting energy expenditure (REE), body composition, thyroid function, L-T4 dose, and cognitive function tests) were evaluated as predictors of improvement in QoL by univariate and multiple regression analysis.

Results: Thirty-seven hypothyroid patients with a baseline median TSH of 30 mU/l and a median QoL score of 29 were included. After twelve months of L-T4 treatment, the ThyPRO-39 QoL score had significantly improved to a median score of 14, while REE per kg fat-free mass (FFM) increased significantly from a mean of 26.5 to 28.7 kcal/day/kg (p < 0.001). Change in ThyPRO-39 was not associated with a change in REE/FFM (unstandardized coefficient (USC): 0.09 with confidence interval (CI): -1.93 to 2.11, p=0.93) but was positively predicted by baseline body mass index (BMI) (USC: 1.54 with CI: 0.59 to 2.49, (p=0.002), without association with weight loss (USC: 0.33 with CI: -1.21 to 1.27, p=0.96).

Conclusion: Improvement in QoL as measured by ThyPRO-39 after initiation of L-T4 therapy for hypothyroidism was not associated with changes in REE. High baseline BMI, but not weight loss during therapy, was associated with improvement in QoL. This trail is registered with www.Clinicaltrials.gov (registration no. https://clinicaltrials.gov/ct2/show/NCT02891668).

[This retracts the article DOI: 10.1155/2014/649502.].

Introduction: This meta-analysis was conducted to estimate the prevalence of hypothyroidism among pregnant women in India.

Methods: We searched PubMed, Web of Science, Scopus, Google Scholar, and Shodhganga (Indian thesis repository) for observational studies, providing prevalence of hypothyroidism among pregnant women in India. Systematic study selection and data extraction procedures were followed. Quality assessment of each study was done using JBI critical appraisal checklist. The random effects model was used for pooling the effect sizes. Publication bias was assessed using the funnel plot and rank correlation test. I ² statistics was used to measure heterogeneity across the studies. Heterogeneity in the pooled estimates was further explored with subgroup analyses and meta-regression analysis.

Results: Sixty-one studies were found eligible and included in this review. The pooled estimate of the prevalence of hypothyroidism in pregnant women was 11.07% (95% CI: 8.79-13.84, I ² = 99%). Pooled prevalence estimates of subclinical and overt hypothyroidism are 9.51% (95% CI: 7.48-12.04, I ² = 98%) and 2.74% (95% CI: 2.08-3.58, I ² = 94%).

Conclusion: We documented 11.07% pooled prevalence of hypothyroidism in pregnant women in India.

Objective: This study investigates the potential of an artificial intelligence (AI) methodology, the radial basis function (RBF) artificial neural network (ANN), in the evaluation of thyroid lesions. Study Design. The study was performed on 447 patients who had both cytological and histological evaluation in agreement. Cytological specimens were prepared using liquid-based cytology, and the histological result was based on subsequent surgical samples. Each specimen was digitized; on these images, nuclear morphology features were measured by the use of an image analysis system. The extracted measurements (41,324 nuclei) were separated into two sets: the training set that was used to create the RBF ANN and the test set that was used to evaluate the RBF performance. The system aimed to predict the histological status as benign or malignant.

Results: The RBF ANN obtained in the training set has sensitivity 82.5%, specificity 94.6%, and overall accuracy 90.3%, while in the test set, these indices were 81.4%, 90.0%, and 86.9%, respectively. Algorithm was used to classify patients on the basis of the RBF ANN, the overall sensitivity was 95.0%, the specificity was 95.5%, and no statistically significant difference was observed.

Conclusion: AI techniques and especially ANNs, only in the recent years, have been studied extensively. The proposed approach is promising to avoid misdiagnoses and assists the everyday practice of the cytopathology. The major drawback in this approach is the automation of a procedure to accurately detect and measure cell nuclei from the digitized images.