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  • Title: Physiological states and functional relation between thyrotropin and free thyroxine in thyroid health and disease: in vivo and in silico data suggest a hierarchical model.
    Author: Midgley JE, Hoermann R, Larisch R, Dietrich JW.
    Journal: J Clin Pathol; 2013 Apr; 66(4):335-42. PubMed ID: 23423518.
    Abstract:
    AIMS: Understanding the exact relationship between serum thyrotropin/thyroid stimulating hormone (TSH) and free thyroxine (FT(4)) is a prerequisite for improving diagnostic reliability and clinical decision making. METHODS: We (1) retrospectively studied the relationship between TSH and FT(4) in a large unselected clinical sample (n=6641) of primary hypothyroid, euthyroid and hyperthyroid subjects, and (2) applied a mathematical model of thyroid hormone feedback control to assess the relation between structural parameters and TSH levels in the different functional states. RESULTS: When separately analysing total sample and untreated subjects, the correlation slope for logTSH versus FT(4) for hypothyroid subjects was significantly different from that of the euthyroid panel and hyperthyroid subjects (the latter being compromised by reaching the TSH assay's lower detection limit). As trends between functional states changed, each functional segment appeared to become differently regulated. Theoretical modelling and sensitivity analysis revealed that the influence of various structural parameters on TSH levels also depends on the overall function of the feedback loop. CONCLUSIONS: Our data suggest that the states of hypothyroidism, euthyroidism and hyperthyroidism can be regarded as differently regulated entities. The apparent complexity could be replicated by mathematical modelling suggesting a hierarchical type of feedback regulation involving patterns of operative mechanisms unique to each condition. For clinical purposes and assay evaluation, neither the standard model relating logTSH with FT(4), nor an alternative model based on non-competitive inhibition can be reliably represented by a single correlation comparing all samples for both hormones in one all-inclusive group.
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