| Literature DB >> 23365787 |
Johannes W Dietrich1, Gabi Landgrafe, Elisavet H Fotiadou.
Abstract
This paper provides the reader with an overview of our current knowledge of hypothalamic-pituitary-thyroid feedback from a cybernetic standpoint. Over the past decades we have gained a plethora of information from biochemical, clinical, and epidemiological investigation, especially on the role of TSH and other thyrotropic agonists as critical components of this complex relationship. Integrating these data into a systems perspective delivers new insights into static and dynamic behaviour of thyroid homeostasis. Explicit usage of this information with mathematical methods promises to deliver a better understanding of thyrotropic feedback control and new options for personalised diagnosis of thyroid dysfunction and targeted therapy, also by permitting a new perspective on the conundrum of the TSH reference range.Entities:
Year: 2012 PMID: 23365787 PMCID: PMC3544290 DOI: 10.1155/2012/351864
Source DB: PubMed Journal: J Thyroid Res
Overview of published models of thyrotropic feedback control. Applications for research refer to any scientific exploitation outside of the modelling context itself, for example, for reasoning in clinical trials or generation of hypotheses.
| Authors | Year | Transfer characteristics | Type of modelling approach | Applications for research | Clinical applications | Reference |
|---|---|---|---|---|---|---|
| Danziger and Elmergreen | 1956 | Linear | Phenomenological | − | − | [ |
| Roston | 1959 | Linear with basal secretion | Phenomenological | − | − | [ |
| Norwich and Reiter | 1965 | Linear | Phenomenological | − | − | [ |
| DiStefano and Stear | 1968 | Linear with basal secretion | Phenomenological, partly parametrically isomorphic | − | − | [ |
| DiStefano and Chang | 1969, 1971 | Linear with basal secretion | Phenomenological, partly parametrically isomorphic | − | − | [ |
| DiStefano et al. | 1975 | N/A | Parametrically isomorphic | − | − | [ |
| Sudova and Langer | 1975 | Exponential with compartment-analytical components | Phenomenological, partly parametrically isomorphic | − | − | [ |
| Saratchandran et al. | 1976 | Logarithmic and linear | Phenomenological, partly parametrically isomorphic | − | − | [ |
| Seif | 1977 | Logarithmic and linear | Phenomenological, partly parametrically isomorphic | − | − | [ |
| Wilkin et al. | 1977 | Limit elements | Phenomenological, partly parametrically isomorphic | − | − | [ |
| Hatakeyama and Yagi | 1985 | Linear with first order time constants | Phenomenological | − | − | [ |
| Cohen | 1990 | Logarithmic | Phenomenological | + | + | [ |
| Li et al. | 1995, 1994 | Complex polynoms | Phenomenological, partly parametrically isomorphic | − | − | [ |
| Dietrich et al. | 1997 | Linear and Michaelis-Menten kinetics | Phenomenological, partly parametrically isomorphic | − | − | [ |
| Dietrich et al. | 2002, 2004 | Michaelis-Menten kinetics, noncompetitive divisive inhibition, first order time constants | Parametrically isomorphic | + | + | [ |
| Falaschi et al. | 2004 | Linear | Phenomenological | − | − | [ |
| Degon et al. | 2008 | Based on compartment and flux analysis | Phenomenological, partly parametrically isomorphic | − | − | [ |
| Leow | 2007 | 2nd order Bernoulli differential equations, hysteresis, | Phenomenological, partly parametrically isomorphic | − | − | [ |
| Mclanahan et al. | 2008 | Michaelis-Menten kinetics, noncompetitive divisive inhibition, first order time constants | Parametrically isomorphic | − | − | [ |
| Eisenberg et al. | 2008, 2010 | Based on earlier models by DiSefano et al. | Phenomenological, partly parametrically isomorphic | + | − | [ |
Figure 1Information processing structure of the logarithmic standard model of thyroid homeostasis [105, 121].
Figure 2Information processing structure of a nonlinear parametrically isomorphic model based on Michaelis-Menten kinetics, noncompetitive divisive inhibition, and pharmacokinetic data [11]. Modified with permission from [49].
Figure 3SimThyr, a continuous simulation program for thyrotropic feedback control [11].
Figure 4Characteristic curves of pituitary and thyroid. The area shaded in green denotes univariate reference ranges for TSH and FT4. The dashed red line denotes the pituitary's response in form of TSH incretion to varying FT4 levels; the continuous blue line represents the thyroid's response to TSH. Note that for the response curve of the thyroid—contrary to convention—the ordinate (TSH) is the independent axis, while the dependent axis is the abscissa (FT4). This uncommon notation facilitates superposition of both characteristic curves. Marked is a normal equilibrium point (also referred to as setpoint) defined by the intersection of both 50% percentiles. Response curves were calculated from percentiles for secretory capacities of pituitary (G ) and thyroid (G ) using the mathematical model displayed in Figure 2. Structure parameters were derived from a subgroup of subjects included in the NOMOTHETICOS trial [153].
Figure 5Successive development of hypothyroidism as a consequence of decreasing G . Beginning with a hypothetical “sublatent” form defined by reduced G and still normal levels of TSH and FT4 (panel b), further steps are subclinical hypothyroidism with increased TSH levels and FT4 still in the lowest fraction of the reference region (panel c) and overt hypothyroidism where both parameters have left their reference region (panel d). See text for additional information.
Figure 6Partial and complete thyrotropic insufficiency as results of nonlinear interaction of pituitary and thyroid. TSH axis is logarithmically scaled in order to zoom small values. G values are given in percent from normal values. See text for additional information.
Figure 7Computer simulation of thyrotropic adaptation in critical illness. A gradual increase of central type 2 deiodinase activity over several days with subsequent restoration to normal values has been simulated with SimThyr using the mathematical model shown in Figure 2. Note the temporarily increased TSH values after day 17 that are occasionally observed also in vivo in patients recovering from nonthyroidal illness syndrome.
Constant parameters for diagnostic calculations.
| Symbol | Explanation | Value | Reference |
|---|---|---|---|
|
| Correction coefficient for log-linear model | −0.1345 | [ |
|
| Dilution factor for T4 (reciprocal of apparent volume of distribution) | 0,1 L−1 | [ |
|
| Clearance exponent for T4 | 1,1 ∗ 10−6 sec−1 | [ |
|
| EC50 for TSH | 2,75 mU/L | [ |
|
| Dissociation constant T4-TBG | 2 ∗ 1010 L/mol | [ |
|
| Dissociation constant T4-TBPA | 2 ∗ 108 L/mol | [ |
|
| Dilution factor for T3 | 0,026 L−1 | [ |
|
| Clearance exponent for T3 | 8 ∗ 10−6 sec−1 | [ |
|
| Dissociation constant of type 1 deiodinase | 5 ∗ 10−7 mol/L | [ |
|
| Dissociation constant T3-TBG | 2 ∗ 109 L/mol | [ |
Test-retest reliability measures of TSH, FT4, FT3, SPINA-GT, and SPINA-GD from repeated measurements with at least one month interval in 20 healthy volunteers from the SPINA network [11, 116]. e: repeatability = (interindividual variance)/(intraindividual variance + interindividual variance) [300]. Larger figures denote higher reliability.
| Parameter |
|
|
|---|---|---|
| TSH | 0.63 | 0.16 |
| FT4 | 0.71 | 0.35** |
| FT3 | 0.68 | 0.36** |
| SPINA-GT | 0.73 | 0.42** |
| SPINA-GD | 0.64 | 0.36** |
**P < 0.01.
Figure 8Interaction of TSH, thyrotropic agonists, and thyrotropic antagonists with TSH receptor. SMLs bind to a pocket within the heptahelical transmembrane domain, while TSH, HCG, and TRAbs bind primarily to the TSHr amino-terminal ectodomain.
Figure 9Comparison of conventional univariate reference ranges for TSH and FT4 (grey box) and a bihormonal reference region (green kite-like area) from nonlinear modelling of thyroid homeostasis. For more information see text and legend of Figure 4.