Your browser does not fully support modern features. Please upgrade for a smoother experience.
SPINA Thyr: History
Please note this is an old version of this entry, which may differ significantly from the current revision.
Contributor: Johannes W Dietrich

SPINA Thyr is a set of cybernetic methods for endotyping the hypothalamus-pituitary-thyroid feedback control system (HPT axis). The equations deliver calculated biomarkers (structure parameters) for the thyroid’s secretory capacity (SPINA-GT) and the sum activity of peripheral deiodinases (SPINA-GD).

  • thyroid
  • homeostasis
  • hypothyroidism
  • hyperthyroidism
  • thyrotoxicosis
  • deiodinase
  • SPINA-GT
  • SPINA-GD

1. Fundamentals

The structure parameters are calculated from serum concentrations of thyrotropin (TSH), free thyroxine (FT4), and free triiodothyronine (FT3)[1]. The equations are derived from a platform for nonlinear modelling of endocrine feedback loops (MiMe-NoCoDI approach)[2][3].

The calculations require simultaneous measurements of the hormones in steady-state conditions, i.e., if the patient receives treatment with thyroid hormones, the dosage should have been unchanged for at least four to six weeks. Calculating SPINA-GT is not meaningful under treatment with levothyroxine. Likewise, SPINA-GD is not informative under therapy with liothyronine.

SPINA-GT correlates positively with thyroid volume and the extent of perfusion in ultrasound investigations and negatively with the titres of autoantibodies directed to thyroid tissue. It has a higher retest reliability than determinations of TSH, FT4 or FT3[1].

SPINA-GD correlates with the conversion rate of T4 to T3 in slow tissue pools and is associated with the supply of selenium, an essential trace element for the formation of deiodinases[1].

Calculating SPINA-GT and SPINA-GD has helped to identify additional regulatory motifs of thyroid homeostasis[4]. The methods have been used in multiple clinical studies with more than 10,000 included patients.

2. Calculation

The parameters are calculated as follows[1]

[math]\displaystyle{SPINA\text{-}GT=\frac{\beta_T(D_T+[TSH])(1+K_{41}[TBG]+K_{42}[TTR])[FT4]}{\alpha_T[TSH]}}[/math]

[math]\displaystyle{SPINA\text{-}GD=\frac{\beta_{31}(K_{M1}+[FT4])(1+K_{30}[TBG])[FT3]}{\alpha_{31}[FT4]}}[/math]

[TSH]: Serum thyrotropin concentration (in mIU/L or μIU/mL)
[FT4]: Serum free T4 concentration (in pmol/L)
[FT3]: Serum free T3 concentration (in pmol/L)
αT: Dilution factor for T4 (reciprocal of apparent volume of distribution, 0.1 L−1)
βT: Clearance exponent for T4 (1.1e-6 sec−1), i.e., rate constant for degradation
α31: Dilution factor for T3 (reciprocal of apparent volume of distribution, 0.026 L−1)
β31: Clearance exponent for T3 (8e-6 sec−1) (i.e., rate constant for degradation)
K41: Binding constant T4-TBG (2e10 L/mol)
K42: Binding constant T4-TBPA (2e8 L/mol)
DT: EC50 for TSH (2.75 mU/L)
KM1: Binding constant of type-1-deiodinase (5e-7 mol/L)
K30: Binding constant T3-TBG (2e9 L/mol)

3. Interpretation

Reference ranges have been reported to be 1.41–8.47 for SPINA-GT and 20–40 for SPINA-GD[1]. SPINA-GT is an ultrasensitive (and specific) biomarker for primary disorders of the thyroid gland[5]. SPINA-GD provides an estimate for total deiodinase activity. The parameters have predictive value for the development of thyroid disorders even in the euthyroid range[6] and for all-cause mortality in large populations[3]. Their use is, therefore, a recommended supplementary tool for pediatric populations[6], for the assessment in the occupational health system[7] and the management of hypothyroidism[5].

References

  1. Johannes W. Dietrich; Gabi Landgrafe-Mende; Evelin Wiora; Apostolos Chatzitomaris; Harald H. Klein; John E. M. Midgley; Rudolf Hoermann; Calculated Parameters of Thyroid Homeostasis: Emerging Tools for Differential Diagnosis and Clinical Research. Front. Endocrinol. 2016, 7, 57, .
  2. Johannes W. Dietrich; Nina Siegmar; Jonas R. Hojjati; Oliver Gardt; Bernhard O. Boehm; CyberUnits Bricks: An Implementation Study of a Class Library for Simulating Nonlinear Biological Feedback Loops. ADCAIJ: Adv. Distrib. Comput. Artif. Intell. J. 2024, 13, e31762-e31762, .
  3. Dietrich, J.W.; P4-Endokrinologie – Kybernetische Perspektiven eines neuen Ansatzes. Leibniz Online 2024, 54, 1-23, .
  4. Rudolf Hoermann; John E.M. Midgley; Rolf Larisch; Johannes W. Dietrich; Relational Stability of Thyroid Hormones in Euthyroid Subjects and Patients with Autoimmune Thyroid Disease. Eur. Thyroid. J. 2016, 5, 171-179, .
  5. Rudolf Hoermann; Johannes W. Dietrich. Diagnosis of Hypothyroidism; Springer Nature: Dordrecht, GX, Netherlands, 2025; pp. 111-132.
  6. Aristeidis Giannakopoulos; Alexandra Efthymiadou; Dimitra Kritikou; Dionisios Chrysis; Usefulness of SPINA model in evaluation of the thyroid function in euthyroid pediatric patients children with subclinical hypothyroidism. Front. Endocrinol. 2025, 16, 1365354, .
  7. Johannes W. Dietrich; Ekkehard Schifferdecker; Helmut Schatz; Harald Klein. Endokrine und Stoffwechseldiagnostik; Springer Nature: Dordrecht, GX, Netherlands, 2025; pp. 1025-1036.
More
This entry is offline, you can click here to edit this entry!
Academic Video Service