The homeostatic set point of the hypothalamus-pituitary-thyroid axis--maximum curvature theory for personalized euthyroid targets

Three candidate SNPs show associations with thyroid-stimulating hormone in euthyroid subjects: Tehran thyroid study

Objectives

Previous studies have shown interindividual variation in free thyroxine (FT4) serum levels and thyroid stimulating hormone (TSH) in healthy persons. Genetic factors mainly determine this variation, and genome-wide association studies have increased the number of thyroid function-associated variants. The present study investigates the association of candidate variants with FT4 and TSH in a euthyroid Iranian population.

Method

A total of 2931 unrelated euthyroid subjects (FT4 10.29-21.88 pmol/L; TSH 0.32-10 mIU/L, thyroid peroxidase antibody TPOAb < 33 IU/mL in men and < 35 IU/mL in women), with available genotypes were chosen from the Tehran Thyroid Study (TTS), to examine the impact of selected SNPs on thyroid hormone under the additive genetic model. In order to evaluate regional associations with FT4 and TSH levels, a haplotype analysis was done.

Results

We identified a strong association between the rs4338740-C allele and TSH in the adjusted model (β = -0.095, P-value = 0.0004). Also, findings indicated that rs4954192 ACMSD and rs4445669 CADM1 correlated with normal TSH levels (P-value = 0.011, P-value = 0.014, respectively). Haplotype analysis revealed that two haplotypes were significantly associated with TSH levels in euthyroid individuals. The ACGA and AC haplotypes on chromosomes 8 and 14 were significantly correlated with normal TSH levels, respectively (P-value = 0.014, P-value = 0.016).

Conclusions

This is the first genetic association study with TSH and FT4 reference values in an Iranian population. Our findings indicate that a few gene variants associated with the reference values of TSH in other populations are also associated with the reference values of TSH in Iranians.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-023-01383-2.

Biological variation of serum thyrotropin and thyroid hormones concentrations determined at 8-week intervals for 1 year in clinically healthy cats

BACKGROUND

Cats commonly develop thyroid disease but little is known about the long-term biological variability of serum thyroid hormone and thyrotropin (thyroid-stimulating hormone; TSH) concentrations.

OBJECTIVES

We aimed to determine the long-term biological variation of thyroid hormones and TSH in clinically healthy cats.

METHODS

A prospective, observational study was carried out. Serum samples for analysis of total thyroxine (T4, by radioimmunoassay [RIA] and homogenous enzyme immunoassay [EIA]), triiodothyronine (T3 ), free T4 (by dialysis), and TSH were obtained every 8 weeks for 1 year from 15 healthy cats, then frozen until single-batch analysis. Coefficients of variation (CV) within individual cats (CV I ) and among individual cats (CV G ), as well as the variation between duplicates (ie, analytical variation [CV A ]) were determined with restricted maximum likelihood estimation. The indices of individuality (IoI) and reference change values (RCVs) for each hormone were calculated.

RESULTS

Some thyroid hormones showed similar (total T4 by EIA) or greater (TSH) interindividual relative to intraindividual variation resulting in intermediate to high IoI, consistent with previous studies evaluating the biological variation of these hormones weekly for 5-6 weeks. By contrast, total T4 (by RIA) and free T4 had a low IoI. Total T3 had a high ratio ofCV A toCV I ; therefore, interindividual variation could not be distinguished from analytical variation. No seasonal variability in the hormones could be demonstrated.

CONCLUSIONS

Clinicians might improve the diagnosis of feline thyroid disease by establishing baseline concentrations for analytes with intermediate-high IoI (total T4, TSH) for individual cats and applying RCVs to subsequent measurements.

Fast Track Treatment of Hypothyroidism with Levothyroxine: Reaching Homeostasis within Four Weeks

With the current clinical method for the treatment of hypothyroidism the target for the optimum individual values for free thyroxine concentrations [FT4] and thyrotropine concentrations [TSH] of the specific patient are unknown. This situation leads to unnecessary long experimental medication administration that can take a period of sometimes one year. In this article a method will be described where hypothyroid patients are characterized with weekly measured FT4 and TSH concentrations during the first three weeks of synthetic thyroxine or levothyroxine (L-T4) treatment to predict their optimum [FT4] and belonging [TSH] endpoint for a euthyroid homeostatic state. The treatment with levothyroxine will start for all patients with a reference dose of 100 µg, which can be adjusted by the treating physician to a more safe and appropriate dose for the individual which is monitored with weekly thyroid function tests to observe the progress. After three weeks all characteristics of the patient can be inferred from the measured data. The final titration target together with the individual thyroxine half life can be calculated. With the known characteristics and the L-T4 titration target the clinician or treating physician has an instrument to reduce the experimental treatment burden for the patient from one year to a maximum of four weeks.

Refining personalized diagnosis, treatment and exploitation of hypothyroidism related to solid nonthyroid cancer

Hypothyroidism in the setting of cancer is a puzzling entity due to the dual role of the thyroid hormones (TH) in cancer – promoting versus inhibitory – and the complexity of the hypothyroidism itself. The present review provides a comprehensive overview of the personalized approach to hypothyroidism in patients with solid nonthyroid cancer, focusing on current challenges, unmet needs and future perspectives. Major electronic databases were searched from January 2011 until March 2022. The milestones of the refinement of such a personalized approach are prompt diagnosis, proper TH replacement and development of interventions and/or pharmaceutical agents to exploit hypothyroidism or, on the contrary, TH replacement as an anticancer strategy. Further elucidation of the dual role of TH in cancer – especially of the interference of TH signaling with the hallmarks of cancer – is anticipated to inform decision-making and optimize patient selection.

Personalized reference intervals: from theory to practice

Using laboratory test results for diagnosis and monitoring requires a reliable reference to which the results can be compared. Currently, most reference data is derived from the population, and patients in this context are considered members of a population group rather than individuals. However, such reference data has limitations when used as the reference for an individual. A patient's test results preferably should be compared with their own, individualized reference intervals (RI), i.e. a personalized RI (prRI).The prRI is based on the homeostatic model and can be calculated using an individual's previous test results obtained in a steady-state situation and estimates of analytical (CV_A) and biological variation (BV). BV used to calculate the prRI can be obtained from the population (within-subject biological variation, CV_I) or an individual's own data (within-person biological variation, CV_P). Statistically, the prediction interval provides a useful tool to calculate the interval (i.e. prRI) for future observation based on previous measurements. With the development of information technology, the data of millions of patients is stored and processed in medical laboratories, allowing the implementation of personalized laboratory medicine. PrRI for each individual should be made available as part of the laboratory information system and should be continually updated as new test results become available.In this review, we summarize the limitations of population-based RI for the diagnosis and monitoring of disease, provide an outline of the prRI concept and different approaches to its determination, including statistical considerations for deriving prRI, and discuss aspects which must be further investigated prior to implementation of prRI in clinical practice.

Minor perturbations of thyroid homeostasis and major cardiovascular endpoints—Physiological mechanisms and clinical evidence

It is well established that thyroid dysfunction is linked to an increased risk of cardiovascular morbidity and mortality. The pleiotropic action of thyroid hormones strongly impacts the cardiovascular system and affects both the generation of the normal heart rhythm and arrhythmia. A meta-analysis of published evidence suggests a positive association of FT4 concentration with major adverse cardiovascular end points (MACE), but this association only partially extends to TSH. The risk for cardiovascular death is increased in both subclinical hypothyroidism and subclinical thyrotoxicosis. Several published studies found associations of TSH and FT4 concentrations, respectively, with major cardiovascular endpoints. Both reduced and elevated TSH concentrations predict the cardiovascular risk, and this association extends to TSH gradients within the reference range. Likewise, increased FT4 concentrations, but high-normal FT4 within its reference range as well, herald a poor outcome. These observations translate to a monotonic and sensitive effect of FT4 and a U-shaped relationship between TSH and cardiovascular risk. Up to now, the pathophysiological mechanism of this complex pattern of association is poorly understood. Integrating the available evidence suggests a dual etiology of elevated FT4 concentration, comprising both ensuing primary hypothyroidism and a raised set point of thyroid function, e. g. in the context of psychiatric disease, chronic stress and type 2 allostatic load. Addressing the association between thyroid homeostasis and cardiovascular diseases from a systems perspective could pave the way to new directions of research and a more personalized approach to the treatment of patients with cardiovascular risk.

Redefinition of Successful Treatment of Patients With Hypothyroidism. Is TSH the Best Biomarker of Euthyroidism?

In recent years evidence has accumulated supporting a revised view of the nature of euthyroidism and the biomarkers of thyroid function. Within the normal range, variations in thyroid hormone levels are associated with variations in clinical parameters and outcomes. There are therefore no readily identified individually specific optimum levels of thyroid hormones for any individual. Levels around the middle of the normal population range may best reflect euthyroidism. These levels may have evolutionary advantages on the basis that adverse outcomes often increase with divergence from such levels, and physiological processes tend to minimise such inter-individual and intra-individual divergence. In populations of predominantly untreated individuals, levels of thyroid hormones and in particular levels of free thyroxine (FT4) correlate more often with clinical parameters than do levels of thyrotropin (TSH). Levels of thyroid hormones may therefore be regarded as the best available biomarkers of euthyroidism and dysthyroidism. It follows that 'subclinical hypothyroidism' (normal FT4/raised TSH levels), rather than being an accurate marker of peripheral tissue hypothyroidism is more a marker of decreased thyroid reserve and prognosis. The recent evidence suggests that treatment of hypothyroxinemia, regardless of the TSH level, and monitoring therapy using FT4 and/or triiodothyronine levels, depending on the replacement regime, may result in more successful treatment of hypothyroidism than relying on thyrotropin levels for patient selection and subsequent treatment monitoring. The equivalents of mid-range levels of thyroid hormones (especially FT4), adjusted by individual comorbidity concerns, may be rational general replacement targets. These implications of the new evidence may create opportunities for novel trials of thyroid replacement therapy.

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.

Biological variation of thyroid function biomarkers over 24 hours

BACKGROUND

Thyroid-stimulating hormone (TSH), triiodothyronine (T3), thyroxine (T4), free T3 (FT3), and free T4 (FT4) are used to diagnose thyroid diseases and monitor treatment effects. Reliable biological variation (BV) data is required to ensure accurate clinical decisions.

METHODS

Blood samples were collected from 31 healthy subjects at 00:00, 04:00, 08:00, 12:00, 16:00, and 20:00; each sample was analyzed twice for TSH, T3, T4, FT3, and FT4. After outlier exclusion, normality assessment, and variance homogeneity, sex-stratified BV, including within-subject (CV_I) and between-subject (CV_G), was defined using nested ANOVA.

RESULTS

Concentrations of five biomarkers were significantly different between sexes. The CV_I and CV_G estimates were 34.54% and 34.43% for TSH, 5.89% and 14.18% for T3, 4.48% and 14.96% for T4, 5.37% and 11.23% for FT3, and 3.57% and 8.03% for FT4, respectively. The individual indexes (IIs) of all the biomarkers (except TSH) were ≤ 0.63. Males had lower CV_Is and IIs than females.

CONCLUSION

CV_I estimates of all hormones, except TSH, were lower than those reported on the BV website, showing low IIs and differences between sexes. We provide updated data on the short-term BV of thyroid function biomarkers according to sex and complement BV data of thyroid function biomarkers.

Reinterpreting patterns of variation in human thyroid function: An evolutionary ecology perspective

Thyroid hormone reference intervals—used to determine normal thyroid function —currently don’t take into account many significant factors that can cause variation in thyroid hormone levels. These factors include age, sex, ethnicity, season, time of day, iodine content in the diet, socioeconomic status, stress levels, body composition, immune status, menstrual cycle phase, and overall health status. This paper shows how early life experiences as well as short term stressors may affect variation in thyroid function. These are energetic challenges to which the thyroid physiology can respond to. Our investigation shows that much variation in thyroid function is natural. It may result from a complex interplay of evolutionary, genetic, developmental, and physiological factors in response to energetic challenges in the environment, beyond what is currently considered in biomedicine. A new research agenda for thyroid health should explore the way that diversity in thyroid function has evolved as a response to different contexts people live in—like focusing on how people’s metabolisms adapt to the energetic requirements of their environments.

Two hundred million people worldwide experience some form of thyroid disorder, with women being especially at risk. However, why human thyroid function varies between populations, individuals, and across the lifespan has attracted little research to date. This limits our ability to evaluate the conditions under which patterns of variation in thyroid function are best understood as ‘normal’ or ‘pathological’. In this review, we aim to spark interest in research aimed at understanding the causes of variation in thyroid phenotypes. We start by assessing the biomedical literature on thyroid imbalance to discuss the validity of existing reference intervals for diagnosis and treatment across individuals and populations. We then propose an evolutionary ecological framework for understanding the phylogenetic, genetic, ecological, developmental, and physiological causes of normal variation in thyroid function. We build on this approach to suggest testable predictions for how environmental challenges interact with individual circumstances to influence the onset of thyroid disorders. We propose that dietary changes, ecological disruptions of co-evolutionary processes during pregnancy and with pathogens, emerging infections, and exacerbated stress responses can contribute to explaining the onset of thyroid diseases. For patients to receive the best personalized care, research into the causes of thyroid variation at multiple levels is needed.

Psychometric properties of the thyroid-specific quality of life questionnaire ThyPRO in Singaporean patients with Graves' disease

Background

Graves’ disease is the most common cause of hyperthyroidism. It results in accelerated tissue metabolism with multi-organ involvement ranging from cardiovascular to neuropsychological function. This results in a negative impact on the quality of life (QOL) of the individual patient. We aim to evaluate the psychometric properties of ThyPRO, a Thyroid-related Patient Reported Outcome questionnaire, and validate its use in our multi-ethnic Asian patients with Graves’ hyperthyroidism.

Methods

Forty-seven consecutive Graves’ hyperthyroidism patients answered the ThyPRO questionnaire at baseline and at 4 months after treatment initiation. Data were recorded for thyroid related symptoms and signs, thyroid function tests and thyroid volume. We analyzed the internal consistency using Cronbach’s alpha, construct validity by evaluating relationship between clinical variables and ThyPRO scales, ceiling and floor effects, and responsiveness of ThyPRO to treatment based on Cohen’s effect size.

Results

Correlations between individual scale scores and free thyroxine concentrations were moderate and statistically significant: 0.21–0.64 (p <  0.05). There was high internal consistency between the items in this instrument, Cronbach’s alpha > 0.7 for all scales. ThyPRO was responsive to the changes in QOL after treatment (Effect Size: 0.20–0.77) in 9 of the 14 scales including the hyperthyroid symptoms and psychosocial scales (Tiredness, Cognitive complaints, Anxiety, Emotional susceptibility, Impact on Social, Daily and Sex life).

Conclusion

This study provides evidence that ThyPRO has satisfactory measurement properties in hyperthyroid Graves’ disease patients in Singapore population with the potential to complement clinical care.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41687-021-00309-x.

Profiling retrospective thyroid function data in complete thyroidectomy patients to investigate the HPT axis set point (PREDICT-IT)

BACKGROUND

The homeostatic euthyroid set point of the hypothalamus-pituitary-thyroid axis of any given individual is unique and oscillates narrowly within substantially broader normal population ranges of circulating free thyroxine (FT4) and thyroid-stimulating hormone (TSH), otherwise termed 'thyroid function test (TFT)'. We developed a mathematical algorithm codenamed Thyroid-SPOT that effectively reconstructs the personalized set point in open-loop situations and evaluated its performance in a retrospective patient sample.

METHODS

We computed the set points of 101 patients who underwent total thyroidectomy for non-functioning thyroid disease using Thyroid-SPOT on each patient's own serial post-thyroidectomy TFT. Every predicted set point was compared against its respective healthy pre-operative euthyroid TFT per individual and their separation (i.e. predicted-observed TFT) quantified.

RESULTS

Bland-Altman analysis to measure the agreement between each pair of an individual's predicted and actual set points revealed a mean difference in FT4 and TSH of + 3.03 pmol/L (95% CI 2.64, 3.43) and - 0.03 mIU/L (95% CI - 0.25, 0.19), respectively. These differences are small compared to the width of the reference intervals. Thyroid-SPOT can predict the euthyroid set point remarkably well, especially for TSH with a 10-16-fold spread in magnitude between population normal limits.

CONCLUSION

Every individual's equilibrium euthyroid set point is unique. Thyroid-SPOT serves as an accurate, precise and reliable targeting system for optimal personalized restoration of euthyroidism. This algorithm can guide clinicians in L-thyroxine dose titrations to resolve persistent dysthyroid symptoms among challenging cases harbouring "normal TFT" within the laboratory ranges but differing significantly from their actual euthyroid set points.

Short-term biological variation of serum thyroid hormones concentrations in clinically healthy cats

Thyroid disease is common in cats, but little is known about the biologic variability of serum thyroid hormone concentrations and its impact on diagnostic utility in either healthy cats or cats with thyroid disease. The purpose of this study was to determine the biological variation, index of individuality, and reference change values for thyroid hormones and thyroid-stimulating hormone (TSH) in clinically healthy cats. Serum samples for analysis of total thyroxine (T₄), triiodothyronine (T₃), free T₄ by dialysis, and TSH were obtained weekly for 6 wk from 10 healthy cats, then frozen until single-batch analyzed. Data were evaluated for outliers, and we determined the CV within individual cats (CV_I) and between individual cats (CV_G) for each hormone and the variation between duplicates or analytical variation (CV_A). The index of individuality and reference change values for each hormone were then calculated. Serum concentrations of total T₄, free T₄, T₃, and TSH all showed greater variation between cats (CV_G) than within cats (CV_I). Total and free T₄ had an intermediate index of individuality (1.1 and 1.2, respectively), suggesting that these hormones would be best evaluated by a combination of their population-based reference intervals and reference change values. Serum TSH concentrations had high index of individuality (1.8), suggesting this hormone would be best evaluated with reference change values rather than the population-based reference interval. Total T₃ also had a high calculated index of individuality (1.8); however, T₃ had high ratio of analytical variation (CV_A) to within cat variation (CV_I), so RCV could not be accurately calculated. This study demonstrates that clinically normal cats show considerable interindividual biological variation in serum thyroid hormone and TSH concentrations, whereas the intraindividual variability in hormone concentrations is much narrower. This suggests that for all serum thyroid hormones, but especially serum TSH and T₃ concentrations, comparing individual cat's hormone results to a population-based reference interval may be misleading, especially in those with early or subclinical thyroid disease. Clinicians might improve the diagnosis of feline thyroid disease by establishing baseline concentrations of T₄, free T₄, T₃, and TSH for individual cats (ideally when healthy) and applying reference change values to subsequent measurements.

Liganded T3 receptor β2 inhibits the positive feedback autoregulation of the gene for GATA2, a transcription factor critical for thyrotropin production

The serum concentration of thyrotropin (thyroid stimulating hormone, TSH) is drastically reduced by small increase in the levels of thyroid hormones (T3 and its prohormone, T4); however, the mechanism underlying this relationship is unknown. TSH consists of the chorionic gonadotropin α (CGA) and the β chain (TSHβ). The expression of both peptides is induced by the transcription factor GATA2, a determinant of the thyrotroph and gonadotroph differentiation in the pituitary. We previously reported that the liganded T3 receptor (TR) inhibits transactivation activity of GATA2 via a tethering mechanism and proposed that this mechanism, but not binding of TR with a negative T3-responsive element, is the basis for the T3-dependent inhibition of the TSHβ and CGA genes. Multiple GATA-responsive elements (GATA-REs) also exist within the GATA2 gene itself and mediate the positive feedback autoregulation of this gene. To elucidate the effect of T3 on this non-linear regulation, we fused the GATA-REs at -3.9 kb or +9.5 kb of the GATA2 gene with the chloramphenicol acetyltransferase reporter gene harbored in its 1S-promoter. These constructs were co-transfected with the expression plasmids for GATA2 and the pituitary specific TR, TRβ2, into kidney-derived CV1 cells. We found that liganded TRβ2 represses the GATA2-induced transactivation of these reporter genes. Multi-dimensional input function theory revealed that liganded TRβ2 functions as a classical transcriptional repressor. Then, we investigated the effect of T3 on the endogenous expression of GATA2 protein and mRNA in the gonadotroph-derived LβT2 cells. In this cell line, T3 reduced GATA2 protein independently of the ubiquitin proteasome system. GATA2 mRNA was drastically suppressed by T3, the concentration of which corresponds to moderate hypothyroidism and euthyroidism. These results suggest that liganded TRβ2 inhibits the positive feedback autoregulation of the GATA2 gene; moreover this mechanism plays an important role in the potent reduction of TSH production by T3.

Challenges in Interpreting Thyroid Stimulating Hormone Results in the Diagnosis of Thyroid Dysfunction

The pituitary hormone, thyrotropin (TSH), is regarded as the primary biomarker for evaluating thyroid function and is useful in guiding treatment with levothyroxine for patients with hypothyroidism. The amplified response of TSH to slight changes in thyroid hormone levels provides a large and easily measured signal in the routine care setting. Laboratories provide reference ranges with upper and lower cutoffs for TSH to define normal thyroid function. The upper limit of the range, used to diagnose subclinical (mild) hypothyroidism, is itself a matter for debate, with authoritative guidelines recommending treatment to within the lower half of the range. Concomitant diseases, medications, supplements, age, gender, ethnicity, iodine status, time of day, time of year, autoantibodies, heterophilic antibodies, smoking, and other factors influence the level of TSH, or the performance of current TSH assays. The long-term prognostic implications of small deviations of TSH from the reference range are unclear. Correction of TSH to within the reference range does not always bring thyroid and other biomarkers into range and will not always resolve the patient's symptoms. Overt hypothyroidism requires intervention with levothyroxine. It remains important that physicians managing a patient with symptoms suggestive of thyroid disease consider all of the patient's relevant disease, lifestyle, and other factors before intervening on the basis of a marginally raised TSH level alone. Finally, these limitations of TSH testing mitigate against screening the population for the undoubtedly substantial prevalence of undiagnosed thyroid disease, until appropriately designed randomised trials have quantified the benefits and harms from this approach.

Individualised requirements for optimum treatment of hypothyroidism: complex needs, limited options

Levothyroxine (LT4) therapy has a long history, a well-defined pharmacological profile and a favourable safety record in the alleviation of hypothyroidism. However, questions remain in defining the threshold for the requirement of treatment in patients with subclinical hypothyroidism, assessing the dose adequacy of the drug, and selecting the best treatment mode (LT4 monotherapy versus liothyronine [LT3]/LT4 combinations) for subpopulations with persisting complaints. Supplied as a prodrug, LT4 is enzymatically converted into the biologically more active thyroid hormone, triiodothyronine (T3). Importantly, tetraiodothyronine (T4) to T3 conversion efficiency may be impaired in patients receiving LT4, resulting in a loss of thyroid-stimulating hormone (TSH)-mediated feed-forward control of T3, alteration of the interlocking equilibria between serum concentrations of TSH, free thyroxine (FT4), and free triiodothyonine (FT3), and a decrease in FT3 to FT4 ratios. This downgrades the value of the TSH reference system derived in thyroid health for guiding the replacement dose in the treatment situation. Individualised conditionally defined setpoints may therefore provide appropriate biochemical targets to be clinically tested, together with a stronger focus on clinical presentation and future endpoint markers of tissue thyroid state. This cautionary note encompasses the use of aggregated statistical data from clinical trials which are not safely applicable to the individual level of patient care under these circumstances.

Hyperthyroidism in the personalized medicine era: the rise of mathematical optimization

Thyroid over-activity or hyperthyroidism constitutes a significant morbidity afflicting the world. The current medical practice of dose titration of anti-thyroid drug (ATD) treatment for hyperthyroidism is relatively archaic, being based on arbitrary and time-consuming trending of thyroid function that requires multiple clinic monitoring visits before an optimal dose is found. This prompts a re-examination into more deterministic and efficient treatment approaches in the present personalized medicine era. Our research project seeks to develop a personalized medicine model that facilitates optimal drug dosing via the titration regimen. We analysed 49 patients' data consisting of drug dosage, time period and serum free thyroxine (FT4). Ordinary differential equation modelling was applied to describe the dynamic behaviour of FT4 concentration. With each patient's data, an optimization model was developed to determine parameters of synthesis rate, decay rate and IC₅₀. We derived the closed-form time- and dose-dependent solution which allowed explicit estimates of personalized predicted FT4. Our equation system involving time, drug dosage and FT4 can be solved for any variable provided the values of the other two are known. Compared against actual FT4 data within a tolerance, we demonstrated the feasibility of predicting the FT4 subsequent to any prescribed dose of ATD with favourable accuracy using the initial three to five patient-visits' data respectively. This proposed mathematical model may assist clinicians in rapid determination of optimal ATD doses within allowable prescription limits to achieve any desired FT4 within a specified treatment period to accelerate the attainment of euthyroid targets.

A data driven diagnosis tool for thyroid hormones

Thyroid hormones play a significant role in human health. Understanding their dynamics is crucial to diagnoses and maintaining the well-being of the thyroid. In this work we propose a data driven algorithm to detect a fixed point and a limit cycle in real data for thyroid hormones. This algorithm finds the maximum frequency point (fixed point) and extracts a smooth ellipse (limit cycle) from the data. These features characterize various data sets and provide interesting insights to differentiate healthy from malfunctioning thyroid data. This scheme which is backed by a solid dynamical analysis determines the size, orientation and location of a detected limit cycle and provides information about the behavior of the thyroid in its various normal and abnormal conditions. This algorithm does not require tuning any ad-hoc parameters. This approach could lead to an effective way of implementing a personal treatment strategy, and a control system to improve the performance of the thyroid.

Mathematical Modeling of the Pituitary-Thyroid Feedback Loop: Role of a TSH-T3-Shunt and Sensitivity Analysis

Despite significant progress in assay technology, diagnosis of functional thyroid disorders may still be a challenge, as illustrated by the vague upper limit of the reference range for serum thyrotropin (TSH). Diagnostical problems also apply to subjects affected by syndrome T, i.e., those 10% of hypothyroid patients who continue to suffer from poor quality of life despite normal TSH concentrations under substitution therapy with levothyroxine (L-T₄). In this paper, we extend a mathematical model of the pituitary-thyroid feedback loop in order to improve the understanding of thyroid hormone homeostasis. In particular, we incorporate a TSH-T₃-shunt inside the thyroid, whose existence has recently been demonstrated in several clinical studies. The resulting extended model shows good accordance with various clinical observations, such as a circadian rhythm in free peripheral triiodothyronine (FT₃). Furthermore, we perform a sensitivity analysis of the derived model, revealing the dependence of TSH and hormone concentrations on different system parameters. The results have implications for clinical interpretation of thyroid tests, e.g., in the differential diagnosis of subclinical hypothyroidism.

Population correlations do not support the existence of set points for blood levels of calcium or glucose - a new model for homeostasis

The prevailing teaching regarding homeostasis, and in particular endocrine homeostasis, includes the fundamental concept of a "set point," which represents a target or optimum level defended by physiological control mechanisms. Analogies for the description and teaching of this concept have included thermostats and cruise controls. We previously demonstrated that such a set-point model of regulation implies that in population data of parameter set point/controlling hormone levels, correlations between the parameter and its controlling hormone must be in the direction of the response of the parameter to its controlling hormone, and that in thyroid homeostasis this relationship is not observed. In this work we similarly examined population correlations, extracted from the literature, for the parameters glucose and calcium, and their controlling hormones. We found 10 correlations. Most were highly significant (P < 0.01). All were in the direction of the response of the controlling hormone to the parameter. Therefore, none were consistent with the pattern implied by a set-point model of regulation. Instead all were consistent with an "equilibrium point" model of regulation, whereby ambient levels have no particular connotation to the individual, and result passively from the interplay of physiological processes. We conclude that glucose and calcium regulation, like thyroid regulation, are not centered on set points. This may reflect a general property of homeostasis. We provide an alternative mechanistic analogy, without a set point, for the heuristic description and teaching, of homeostasis.

Advances in applied homeostatic modelling of the relationship between thyrotropin and free thyroxine

INTRODUCTION

The relationship between pituitary TSH and thyroid hormones is central to our understanding of thyroid physiology and thyroid function testing. Here, we generated distribution patterns by using validated tools of thyroid modelling.

METHODS

We simulated patterns of individual set points under various conditions, based on a homeostatic model of thyroid feedback control. These were compared with observed data points derived from clinical trials.

RESULTS

A random mix of individual set points was reconstructed by simulative modelling with defined structural parameters. The pattern displayed by the cluster of hypothetical points resembled that observed in a natural control group. Moderate variation of the TSH-FT4 gradient over the functional range introduced further flexibility, implementing a scenario of adaptive set points. Such a scenario may be a realistic possibility for instance in treatment where relationships and equilibria between thyroid parameters are altered by various influences such as LT4 dose and conversion efficiency.

CONCLUSIONS

We validated a physiologically based homeostatic model that permits simulative reconstruction of individual set points. This produced a pattern resembling the observed data under various conditions. Applied modelling, although still experimental at this stage, shows a potential to aid our physiological understanding of the interplay between TSH and thyroid hormones. It should eventually benefit personalised clinical decision making.

High Resolution Free Triiodothyronine-Thyrotropin (FT3-TSH) Responses to a Single Oral Dose of Liothyronine in Humans: Evidence of Distinct Inter-Individual Differences Unraveled Using an Electrical Network Model

The effects of a single oral dose of liothyronine (L-T3) on thyroid stimulating hormone (TSH) and other related thyroid system parameters are partly understood despite therapeutic use of this hormone over many decades. We characterize individualized responses of the hypothalamus-pituitary-thyroid (HPT) axis and its related temporal hormonal profile using an electrical network model. Based on thyroid hormone responses from blood samples using a single 50 μg oral dose of liothyronine in healthy persons with a normal operating euthyroid feedback HPT system, we derived an equivalent electrical circuit model for the system's responses. The mathematical model was tested with a circuit simulator and validated with individualized clinical data. This signal processing technique makes the evaluation of bioequivalence and bioavailability of various preparations of liothyronine at an individualized level a feasible endeavor for clinical application.

Relational Stability in the Expression of Normality, Variation, and Control of Thyroid Function

Thyroid hormone concentrations only become sufficient to maintain a euthyroid state through appropriate stimulation by pituitary thyroid-stimulating hormone (TSH). In such a dynamic system under constant high pressure, guarding against overstimulation becomes vital. Therefore, several defensive mechanisms protect against accidental overstimulation, such as plasma protein binding, conversion of T4 into the more active T3, active transmembrane transport, counter-regulatory activities of reverse T3 and thyronamines, and negative hypothalamic-pituitary-thyroid feedback control of TSH. TSH has gained a dominant but misguided role in interpreting thyroid function testing in assuming that its exceptional sensitivity thereby translates into superior diagnostic performance. However, TSH-dependent thyroid disease classification is heavily influenced by statistical analytic techniques such as uni- or multivariate-defined normality. This demands a separation of its conjoint roles as a sensitive screening test and accurate diagnostic tool. Homeostatic equilibria (set points) in healthy subjects are less variable and do not follow a pattern of random variation, rather indicating signs of early and progressive homeostatic control across the euthyroid range. In the event of imminent thyroid failure with a reduced FT4 output per unit TSH, conversion efficiency increases in order to maintain FT3 stability. In such situations, T3 stability takes priority over set point maintenance. This suggests a concept of relational stability. These findings have important implications for both TSH reference limits and treatment targets for patients on levothyroxine. The use of archival markers is proposed to facilitate the homeostatic interpretation of all parameters.

The Relationship between Population T4/TSH Set Point Data and T4/TSH Physiology

Context. Population studies of the distribution of T4/TSH set points suggest a more complex inverse relationship between T4 and TSH than that suggested by physiological studies. The reasons for the similarities and differences between the curves describing these relationships are unresolved. Methods. We subjected the curve, derived from empiric data, describing the TSH suppression response to T4, and the more mathematically derived curve describing the T4 response to TSH, to the different possible models of population variation. The implied consequences of these in terms of generating a population distribution of T4/TSH equilibrium points (a “population curve”) were generated and compared to the empiric population curve. The physiological responses to primary hypothyroidism and hyperthyroidism were incorporated into the analysis. Conclusions. Though the population curve shows a similarly inverse relationship, it is describing a different relationship than the curve describing the suppression of TSH by T4. The population curve is consistent with the physiological studies of the TSH response to T4 and implies a greater interindividual variation in the positive thyroid T4 response to TSH than in the central inhibitory TSH response to T4. The population curve in the dysthyroid states is consistent with known physiological responses to these states.

A Review of the Phenomenon of Hysteresis in the Hypothalamus-Pituitary-Thyroid Axis

The existence of a phase of prolonged suppression of TSH despite normalization of serum thyroid hormones over a variable period of time during the recovery of thyrotoxicosis has been documented in literature. Conversely, a temporary elevation of TSH despite attainment of euthyroid levels of serum thyroid hormones following extreme hypothyroidism has also been observed. This rate-independent lag time in TSH recovery is an evidence of a "persistent memory" of the history of dysthyroid states the hypothalamus-pituitary-thyroid (HPT) axis has encountered after the thyroid hormone perturbations have faded out, a phenomenon termed "hysteresis." Notwithstanding its perplexing nature, hysteresis impacts upon the interpretation of thyroid function tests with sufficient regularity that clinicians risk misdiagnosing and implementing erroneous treatment out of ignorance of this aspect of thyrotropic biology. Mathematical modeling of this phenomenon is complicated but may allow the euthyroid set point to be predicted from thyroid function data exhibiting strong hysteresis effects. Such model predictions are potentially useful for clinical management. Although the molecular mechanisms mediating hysteresis remain elusive, epigenetics, such as histone modifications, are probably involved. However, attempts to reverse the process to hasten the resolution of the hysteretic process may not necessarily translate into improved physiology or optimal health benefits. This is not unexpected from teleological considerations, since hysteresis probably represents an adaptive endocrinological response with survival advantages evolutionarily conserved among vertebrates with a HPT system.

Homeostatic Control of the Thyroid-Pituitary Axis: Perspectives for Diagnosis and Treatment

The long-held concept of a proportional negative feedback control between the thyroid and pituitary glands requires reconsideration in the light of more recent studies. Homeostatic equilibria depend on dynamic inter-relationships between thyroid hormones and pituitary thyrotropin (TSH). They display a high degree of individuality, thyroid-state-related hierarchy, and adaptive conditionality. Molecular mechanisms involve multiple feedback loops on several levels of organization, different time scales, and varying conditions of their optimum operation, including a proposed feedforward motif. This supports the concept of a dampened response and multistep regulation, making the interactions between TSH, FT4, and FT3 situational and mathematically more complex. As a homeostatically integrated parameter, TSH becomes neither normatively fixed nor a precise marker of euthyroidism. This is exemplified by the therapeutic situation with l-thyroxine (l-T4) where TSH levels defined for optimum health may not apply equivalently during treatment. In particular, an FT3-FT4 dissociation, discernible FT3-TSH disjoint, and conversion inefficiency have been recognized in l-T4-treated athyreotic patients. In addition to regulating T4 production, TSH appears to play an essential role in maintaining T3 homeostasis by directly controlling deiodinase activity. While still allowing for tissue-specific variation, this questions the currently assumed independence of the local T3 supply. Rather it integrates peripheral and central elements into an overarching control system. On l-T4 treatment, altered equilibria have been shown to give rise to lower circulating FT3 concentrations in the presence of normal serum TSH. While data on T3 in tissues are largely lacking in humans, rodent models suggest that the disequilibria may reflect widespread T3 deficiencies at the tissue level in various organs. As a consequence, the use of TSH, valuable though it is in many situations, should be scaled back to a supporting role that is more representative of its conditional interplay with peripheral thyroid hormones. This reopens the debate on the measurement of free thyroid hormones and encourages the identification of suitable biomarkers. Homeostatic principles conjoin all thyroid parameters into an adaptive context, demanding a more flexible interpretation in the accurate diagnosis and treatment of thyroid dysfunction.