Population data evidence of interdependence of the limbs of hormonal feedback loops.

The fundamental models underlying hormonal physiological regulation and homeostasis remain poorly understood. We aimed to derive quantitative evidence regarding these models from the study of population data of balance points of different parameters and their respective controlling hormones. We studied the slopes of correlations between concentrations of circulating free thyroxine and thyrotropin, calcium and parathyroid hormone, haemoglobin and erythropoietin, and glucose and insulin in such population data, as well as the slopes of the limbs of various feedback loops estimated empirically and by reverse engineering of the population data. We used computer simulations to model the factors that influence the slopes derived from the population data, and then matched these simulations with the empirically derived slopes. Our simulations showed that changes to the population distribution of feedback loop limbs may alter the slopes of correlations within population data in specific ways. Non-random (interdependent) associations of the limbs of feedback loops may also have this effect, as well as producing discrepancies between the slopes of feedback limb loops determined experimentally and the same slopes determined by derivation from population data. Our corresponding empirical findings were consistent with the presence of such interdependence in the free thyroxine/thyrotropin, haemoglobin/erythropoietin and glucose /insulin systems. The glucose/insulin data provided evidence consistent with increasing interdependence with age in childhood. Our findings therefore provide strong evidence that the interdependence of the limbs of feedback loops is a general feature of endocrine homeostatic regulation. This interdependence potentially bestows evolutionary homeostatic and regulatory advantages.

Physiological linkage of thyroid and pituitary sensitivities.

OBJECTIVES: The sensitivities of the pituitary to thyroxine feedback, and the thyroid to thyrotropin stimulation determine the free thyroxine /thyrotropin feedback loop and can be described mathematically by two curves. It is not well understood how the two curves combine in a healthy population with normal thyroid function to express the individual balance points that are observed. This study was directed at this issue testing the possibilities of random combination and directed linkage between the two curves. METHODS: We reverse-engineered two sets of population data, on the assumption of independent combinations of thyroid and pituitary sensitivities, to obtain estimates of the curve describing thyroid sensitivity. Sensitivity studies were performed. RESULTS: No analysis resulted in a physiologically feasible estimate of the curve describing thyroid sensitivity. There was evidence of linkage of the two curves in terms of their combination throughout the normal range. Thyroid response curves reflecting a low free thyroxine response to thyrotropin tended to be combined in individuals with thyrotropin curves reflecting a high thyrotropin response to free thyroxine, and vice versa. CONCLUSIONS: Thyroid and pituitary sensitivities are linked, being combined in individuals in a non-random directed pattern. Direct mutual interaction may contribute to this linkage. This linkage precludes the derivation of the curves describing these sensitivities from population data of the free thyroxine and thyrotropin relationship and complicates their derivation by physiological experimentation. This linkage and probable interaction may also bestow evolutionary advantage by minimising inter-individual variation in free thyroxine levels and by augmenting homeostasis.

The application of new concepts of the assessment of the thyroid state to pregnant women.

Recently proposed concepts regarding the nature and assessment of the thyroid state have provided a model more consistent with empiric evidence. It now appears likely that there are no such entities as thyroid set points and individual euthyroidism. Rather than there being discrete thyroid states, peripheral organ parameters are associated with thyroid function in a continuous manner. Thyroid hormone levels and, in particular, levels of free thyroxine now appear to be superior to thyrotropin levels as indicators of the thyroid state. Complicating the assessment of the correlations of the thyroid state with pregnancy outcomes are the contribution of the placenta to maternal thyroid function, fetal thyroid development, the multiple potential pathways to any particular outcome, the likely presence of small critical periods of time, the differing genetics of fetal and maternal tissues, and the unreliability of thyroid hormone assays. Nevertheless, there is no apparent reason for there to be a change in pregnancy to the basic principles of thyroid hormone action. The relationships between mild abnormalities of the thyroid state and pregnancy outcomes and the value of treating such mild abnormalities remain uncertain and controversial. The evidence suggests that further investigation of these clinical questions might better be based on thyroid hormone, particularly free thyroxine, levels. In the investigation of borderline low thyroid states, the categories of subclinical hypothyroidism and isolated hypothyroxinemia might both be abandoned with attention being directed to low free thyroxine levels regardless of the thyroid-stimulating hormone (TSH) levels. For these changes to occur, there would ideally be improvements in the assays for free thyroxine in pregnancy. The evidence suggests that, just as in the non-pregnant situation, pregnancy guidelines based on thyrotropin levels may need revision.

Modeling total predation to avoid perverse outcomes from cat control in a data-poor island ecosystem.

Data hungry, complex ecosystem models are often used to predict the consequences of threatened species management, including perverse outcomes. Unfortunately, this approach is impractical in many systems, which have insufficient data to parameterize ecosystem interactions or reliably calibrate or validate such models. Here we demonstrate a different approach, using a minimum realistic model to guide decisions in data- and resource-scarce systems. We illustrate our approach with a case-study in an invaded ecosystem from Christmas Island, Australia, where there are concerns that cat eradication to protect native species, including the red-tailed tropicbird, could release meso-predation by invasive rats. We use biophysical constraints (metabolic demand) and observable parameters (e.g. prey preferences) to assess the combined cat and rat abundances which would threaten the tropicbird population. We find that the population of tropicbirds cannot be sustained if predated by 1607 rats (95% credible interval (CI) [103, 5910]) in the absence of cats, or 21 cats (95% CI [2, 82]) in the absence of rats. For every cat removed from the island, the bird's net population growth rate improves, provided that the rats do not increase by more than 77 individuals (95% CI [30, 174]). Thus, in this context, one cat is equivalent to 30-174 rats. Our methods are especially useful for on-the-ground predator control in the absence of knowledge of predator-predator interactions, to assess whether 1) the current abundance of predators threatens the prey population of interest, 2) managing one predator species alone is sufficient to protect the prey species given potential release of another predator, and 3) control of multiple predator species is needed to meet the conservation goal. Our approach demonstrates how to use limited information for maximum value in data-poor systems, by shifting the focus from predicting future trajectories, to identifying conditions which threaten the conservation goal. This article is protected by copyright. All rights reserved.

Thyroid testing paradigm switch from thyrotropin to thyroid hormones-Future directions and opportunities in clinical medicine and research.

PURPOSE: Recently published papers have demonstrated that particularly in untreated individuals, clinical parameters more often associate with thyroid hormone, particularly free thyroxine (FT4), levels than with thyrotropin (TSH) levels. Clinical and research assessments of the thyroid state of peripheral tissues would therefore be more precise if they were based on FT4 levels rather than on TSH levels. In this paper we describe implications of, and opportunities provided by, this discovery. CONCLUSIONS: The FT4 level may be the best single test of thyroid function. The addition of free triiodothyronine (FT3) and TSH levels would further enhance test sensitivity and distinguish primary from secondary thyroid dysfunction respectively. There are opportunities to reconsider testing algorithms. Additional potential thyroidology research subjects include the peripheral differences between circulating FT4 and FT3 action, and outcomes in patients on thyroid replacement therapy in terms of thyroid hormone levels. Previously performed negative studies of therapy for subclinical thyroid dysfunction could be repeated using thyroid hormone levels rather than TSH levels for subject selection and the monitoring of treatment. Studies of outcomes in older individuals with treatment of high normal FT4 levels, and pregnant women with borderline high or low FT4 levels would appear to be the most likely to show positive results. There are fresh indications to critically re-analyse the physiological rationale for the current preference for TSH levels in the assessment of the thyroid state of the peripheral tissues. There may be opportunities to apply these research principles to analogous parameters in other endocrine systems.

Clinical Parameters Are More Likely to Be Associated with Thyroid Hormone Levels than with Thyrotropin Levels: A Systematic Review and Meta-Analysis.

Background: Though the functional states of other endocrine systems are not defined on the basis of levels of controlling hormones, the assessment of thyroid function is based on levels of the controlling hormone thyrotropin (TSH). We, therefore, addressed the question as to whether levels of thyroid hormones [free thyroxine (fT4), total triiodothyronine (TT3)/free triiodothyronine (fT3)], or TSH levels, within and beyond the reference ranges, provide the better guide to the range of clinical parameters associated with thyroid status. Methods: A PubMed/MEDLINE search of studies up to October 2019, examining associations of levels of thyroid hormones and TSH, taken simultaneously in the same individuals, with clinical parameters was performed. We analyzed atrial fibrillation, other cardiac parameters, osteoporosis and fracture, cancer, dementia, frailty, mortality, features of the metabolic syndrome, and pregnancy outcomes. Studies were assessed for quality by using a modified Newcastle-Ottawa score. Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines were followed. A meta-analysis of the associations was performed to determine the relative likelihood of fT4, TT3/fT3, and TSH levels that are associated with the clinical parameters. Results: We identified 58 suitable articles and a total of 1880 associations. In general, clinical parameters were associated with thyroid hormone levels significantly more often than with TSH levels-the converse was not true for any of the clinical parameters. In the 1880 considered associations, fT4 levels were significantly associated with clinical parameters in 50% of analyses. The respective frequencies for TT3/fT3 and TSH levels were 53% and 23% (p < 0.0001 for both fT4 and TT3/fT3 vs. TSH). The fT4 and TT3/fT3 levels were comparably associated with clinical parameters (p = 0.71). More sophisticated statistical analyses, however, indicated that the associations with TT3/fT3 were not as robust as the associations with fT4. Conclusions: Thyroid hormones levels, and in particular fT4 levels, seem to have stronger associations with clinical parameters than do TSH levels. Associations of clinical parameters with TSH levels can be explained by the strong negative population correlation between thyroid hormones and TSH. Clinical and research components of thyroidology currently based on the measurement of the thyroid state by reference to TSH levels warrant reconsideration.

GHOST: Recovering Historical Signal from Heterotachously Evolved Sequence Alignments.

Molecular sequence data that have evolved under the influence of heterotachous evolutionary processes are known to mislead phylogenetic inference. We introduce the General Heterogeneous evolution On a Single Topology (GHOST) model of sequence evolution, implemented under a maximum-likelihood framework in the phylogenetic program IQ-TREE (http://www.iqtree.org). Simulations show that using the GHOST model, IQ-TREE can accurately recover the tree topology, branch lengths, and substitution model parameters from heterotachously evolved sequences. We investigate the performance of the GHOST model on empirical data by sampling phylogenomic alignments of varying lengths from a plastome alignment. We then carry out inference under the GHOST model on a phylogenomic data set composed of 248 genes from 16 taxa, where we find the GHOST model concurs with the currently accepted view, placing turtles as a sister lineage of archosaurs, in contrast to results obtained using traditional variable rates-across-sites models. Finally, we apply the model to a data set composed of a sodium channel gene of 11 fish taxa, finding that the GHOST model is able to elucidate a subtle component of the historical signal, linked to the previously established convergent evolution of the electric organ in two geographically distinct lineages of electric fish. We compare inference under the GHOST model to partitioning by codon position and show that, owing to the minimization of model constraints, the GHOST model offers unique biological insights when applied to empirical data.

Population data provide evidence against the presence of a set point for hemoglobin levels or tissue oxygen delivery.

Hemoglobin levels are believed to be regulated as per a set point model of regulation. This model of regulation, by which specific levels of a parameter are targeted and defended by physiological systems, implies a particular population correlation between the parameter and its controlling hormone. Empirical population correlations of other parameters and their controlling hormones, have denied the presence of such set point-based regulation. To assess if hemoglobin is regulated according to a set point model we performed a systematic search of PubMed/MEDLINE and Web of Science identifying relevant reports published up to November 2018. Population hemoglobin/erythropoietin level correlations were retrieved, and these empirically derived correlations were compared with the positive correlation implied by a set point model of regulation. Authors of papers containing potentially suitable data were contacted with requests for further analyses, and a meta-analysis was performed. Twelve correlations between hemoglobin and erythropoietin levels from eleven papers were analyzed. None of these correlations were significantly positive, three, restricted to the normal range of hemoglobin, were significantly negative. All but one of the other correlations showed a negative trend. New analyses of previously published data sets resulted in similar findings. In particular a new analysis of large data sets of males (n = 2417) and females (n = 2592) with normal range hemoglobin levels, revealed significantly negative correlations. A meta-analysis of our results indicated that the data overall are not consistent with a positive relationship between hemoglobin and erythropoietin (P < 0.0001). Population data indicate that individuals do not have set point levels of hemoglobin.

Designing group dose-response studies in the presence of transmission.

Dose-response studies are used throughout pharmacology, toxicology and in clinical research to determine safe, effective, or hazardous doses of a substance. When involving animals, the subjects are often housed in groups; this is in fact mandatory in many countries for social animals, on ethical grounds. An issue that may consequently arise is that of unregulated between-subject dosing (transmission), where a subject may transmit the substance to another subject. Transmission will obviously impact the assessment of the dose-response relationship, and will lead to biases if not properly modelled. Here we present a method for determining the optimal design - pertaining to the size of groups, the doses, and the killing times - for such group dose-response experiments, in a Bayesian framework. Our results are of importance to minimising the number of animals required in order to accurately determine dose-response relationships. Furthermore, we additionally consider scenarios in which the estimation of the amount of transmission is also of interest. A particular motivating example is that of Campylobacter jejuni in chickens. Code is provided so that practitioners may determine the optimal design for their own studies.

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.

A method of decision analysis quantifying the effects of age and comorbidities on the probability of deriving significant benefit from medical treatments.

BACKGROUND: The external validity, or generalizability, of trials and guidelines has been considered poor in the context of multiple morbidity. How multiple morbidity might affect the magnitude of benefit of a given treatment, and thereby external validity, has had little study. OBJECTIVE: To provide a method of decision analysis to quantify the effects of age and comorbidity on the probability of deriving a given magnitude of treatment benefit. DESIGN: We developed a method to calculate probabilistically the effect of all of a patient's comorbidities on their underlying utility, or well-being, at a future time point. From this, we derived a distribution of possible magnitudes of treatment benefit at that future time point. We then expressed this distribution as the probability of deriving at least a given magnitude of treatment benefit. To demonstrate the applicability of this method of decision analysis, we applied it to the treatment of hypercholesterolaemia in a geriatric population of 50 individuals. We highlighted the results of four of these individuals. RESULTS: This method of analysis provided individualized quantifications of the effect of age and comorbidity on the probability of treatment benefit. The average probability of deriving a benefit, of at least 50% of the magnitude of benefit available to an individual without comorbidity, was only 0.8%. CONCLUSION: The effects of age and comorbidity on the probability of deriving significant treatment benefits can be quantified for any individual. Even without consideration of other factors affecting external validity, these effects may be sufficient to guide decision-making.

An analysis of the interactions between individual comorbidities and their treatments--implications for guidelines and polypharmacy.

BACKGROUND: With aging there is an increase in frailty and chronic disease leading to a potential increase in medication use. Most clinical trials have excluded old, frail individuals and have failed to take into account the effects of outcome interaction. METHODS AND RESULTS: In this article we provide a mathematical model demonstrating that comorbidities, including old age, interact with therapies, reducing their effectiveness. CONCLUSION: These findings question the validity of single disease guidelines in old persons or in persons with multiple chronic diseases.