Change in Thyroid Hormone Metabolite Concentrations Across Different Thyroid States

Optimizing Levothyroxine Replacement: A Precision Dosage Model for Post-Thyroidectomy Patients

Background

Thyroidectomy is commonly performed for benign or malignant thyroid tumors, often resulting in hypothyroidism. Levothyroxine (LT4) supplementation is crucial to maintain hormone levels within the normal range and suppress TSH for cancer control. However, determining the optimal dosage remains challenging, leading to uncertain outcomes and potential side effects.

Methods

We analyzed clinical examination data from 510 total thyroidectomy patients, including demographic information, blood tests, and thyroid function. Using R, we applied data preprocessing techniques and identified 274 samples with 98 variables. Principal Component Analysis, correlation analysis, and regression analysis were conducted to identify factors associated with optimal LT4 dosage.

Results

The analysis revealed that only eight variables significantly influenced the final satisfactory dosage of LT4 in tablets: Benign0/Malignant1 (benign or malignant), BQB (electrophoretic albumin ratio), TP (total protein), FDP (fibrin degradation products), TRAB_1 (thyroid-stimulating hormone receptor antibody), PT (prothrombin time), MONO# (monocyte count), and HCV0C (hepatitis C antibody). The resulting predictive model was: .

Conclusion

Parameters such as benign/malignant status, TRAB_1, and BQB ratio during medication can serve as observational indicators for postoperative LT4 dosage. The calculated linear model can predict the LT4 dosage for patients after thyroidectomy, leading to improved treatment effectiveness and conserving medical resources.

Multi-view progression diagnosis of thyroid cancer by integrating platelet transcriptomes and blood routine tests

Thyroid cancer is the most common type of endocrine system cancer. The pre-cancer and early stages are usually benign or slowly growing, and do not need invasive treatments. This study investigated the challenging classification task of four classes of samples, i.e., normal controls (N), thyroid adenomas (TA), papillary thyroid cancers (PTC) and metastasized papillary thyroid cancers (MPTC). We proposed a multi-view progression diagnosis framework ThyroidBloodTest to integrate the two views of RNAseq platelet transcriptomes (View-T) and blood routine (View-B) features. Platelet transcriptome represented the molecular-level information, while the blood routine features were easy to obtain in the clinical practice. Eleven feature selection algorithms and seven classifiers were evaluated for both views. The experimental data suggested the importance of choosing appropriate data analysis algorithms and feature engineering techniques like principal component analysis (PCA). The best ThyroidBloodTest model achieved Acc = 0.8750 for the four-class classification of the N/TA/PTC/MPTC samples based on the integrated feature space of View-T and View-B. The cellular localization cytosol and three post-translational modification types acetylation/phosphorylation/ubiquitination were observed to be enriched in the proteins encoded by the View-T biomarkers. The numbers of different immune cells also contributed positively to the progression diagnosis of thyroid cancer. The proposed multi-view prediction model demonstrated the necessity of integrating both platelet transcriptomes and blood routine tests for the progression diagnosis of thyroid cancer.

Advance in the Correlation between Diabetic Nephropathy and Abnormal Serum Thyroid Hormone Levels in Patients

This study was developed to explore the correlation between diabetic nephropathy (DN) and abnormal serum thyroid hormone (TH) levels in patients, which can provide a reference for disease prevention and control in patients with DN. DN is the most serious complication of diabetes. The mortality rate of diabetic patients with DN is approximately 30 times higher than that of diabetic patients without DN. DN leads to high blood sugar, which causes vascular dysfunction in patients, causes cardiovascular disease, aggravates the disease and disease complexity, and thus increases the mortality of patients. DN patients often have oxidative stress and even fibrosis in severe cases. TH has a potential renal protective effect and can also regulate glucose metabolism and improve abnormal glucose tolerance and insulin resistance. Abnormal serum TH levels increase the risk of DN. Normal thyroid function plays an important role in regulating the physiological functions of the human body. Hormonal disorders promote the development of diabetes mellitus (DM) into DN. The pathogenesis, clinical manifestations, detection, and treatment methods of DN were reviewed in this study. The research progress of the influence of TH on DN was analyzed. This study is conducive to clinical research on DN and provides a reference.

Hormonal Crosstalk Between Thyroid and Breast Cancer

Differentiated thyroid cancer and breast cancer account for a significant portion of endocrine-related malignancies and predominately affect women. As hormonally responsive tissues, the breast and thyroid share endocrine signaling. Breast cells are responsive to thyroid hormone signaling and are affected by altered thyroid hormone levels. Thyroid cells are responsive to sex hormones, particularly estrogen, and undergo protumorigenic processes upon estrogen stimulation. Thyroid and sex hormones also display significant transcriptional crosstalk that influences oncogenesis and treatment sensitivity. Obesity-related adipocyte alterations-adipocyte estrogen production, inflammation, feeding hormone dysregulation, and metabolic syndromes-promote hormonal alterations in breast and thyroid tissues. Environmental toxicants disrupt endocrine systems, including breast and thyroid homeostasis, and influence pathologic processes in both organs through hormone mimetic action. In this brief review, we discuss the hormonal connections between the breast and thyroid and perspectives on hormonal therapies for breast and thyroid cancer. Future research efforts should acknowledge and further explore the hormonal crosstalk of these tissues in an effort to further understand the prevalence of thyroid and breast cancer in women and to identify potential therapeutic options.

3,5-T2-an Endogenous Thyroid Hormone Metabolite as Promising Lead Substance in Anti-Steatotic Drug Development?

Thyroid hormones, their metabolites, and synthetic analogues are potential anti-steatotic drug candidates considering that subclinical and manifest hypothyroidism is associated with hepatic lipid accumulation, non-alcoholic fatty liver disease, and its pandemic sequelae. Thyromimetically active compounds stimulate hepatic lipogenesis, fatty acid beta-oxidation, cholesterol metabolism, and metabolic pathways of glucose homeostasis. Many of these effects are mediated by T3 receptor β1-dependent modulation of transcription. However, rapid non-canonical mitochondrial effects have also been reported, especially for the metabolite 3,5-diiodothyronine (3,5-T2), which does not elicit the full spectrum of “thyromimetic” actions inherent to T3. Most preclinical studies in rodent models of obesity and first human clinical trials are promising with respect to the antisteatotic hepatic effects, but potent agents exhibit unwanted thyromimetic effects on the heart and/or suppress feedback regulation of the hypothalamus-pituitary-thyroid-periphery axis and the fine-tuned thyroid hormone system. This narrative review focuses on 3,5-T2 effects on hepatic lipid and glucose metabolism and (non-)canonical mechanisms of action including its mitochondrial targets. Various high fat diet animal models with distinct thyroid hormone status indicate species- and dose-dependent efficiency of 3,5-T2 and its synthetic analogue TRC150094. No convincing evidence has been presented for their clinical use in the prevention or treatment of obesity and related metabolic conditions.

Changes in Thyroid Metabolites after Liothyronine Administration: A Secondary Analysis of Two Clinical Trials That Incorporated Pharmacokinetic Data

We examined relationships between thyroid hormone (TH) metabolites in humans by measuring 3,5-diiodothyronine (3,5-T2) and 3-iodothyronamine (3-T1AM) levels after liothyronine administration. In secondary analyses, we measured 3,5-T2 and 3-T1AM concentrations in stored samples from two clinical trials. In 12 healthy volunteers, THs and metabolites were documented for 96 h after a single dose of 50 mcg liothyronine. In 18 patients treated for hypothyroidism, levothyroxine therapy was replaced by daily dosing of 30–45 mcg liothyronine. Analytes were measured prior to the administration of liothyronine weekly for 6 weeks, and then hourly for 8 h after the last liothyronine dose of the study. In the weekly samples from the hypothyroid patients, 3,5-T2 was higher by 0.033 nmol/L with each mcg/dL increase in T4 and 0.24 nmol/L higher with each ng/dL increase in FT4 (p-values = 0.007, 0.0365). In hourly samples after the last study dose of liothyronine, patients with T3 values higher by one ng/dL had 3-T1AM values that were lower by 0.004 nmol/L (p-value = 0.0473); patients with 3,5-T2 higher by one nmol/L had 3-T1AM values higher by 2.45 nmol/L (p-value = 0.0044). The positive correlations between weekly trough levels of 3,5-T2 and T4/FT4 during liothyronine therapy may provide insight into 3,5-T2 production, possibly supporting some production of 3,5-T2 from endogenous T4, but not from exogenous liothyronine. In hourly sampling after liothyronine administration, the negative correlation between T3 levels and 3-T1AM, but positive correlation between 3,5-T2 levels and 3-T1AM could support the hypothesis that 3-T1AM production occurs via 3,5-T2 with negative regulation by T3.