Literature DB >> 29370954

How to disentangle psychobiological stress reactivity and recovery: A comparison of model-based and non-compartmental analyses of cortisol concentrations.

Robert Miller1, Jan-Georg Wojtyniak2, Lisa J Weckesser3, Nina C Alexander4, Veronika Engert5, Thorsten Lehr2.   

Abstract

This article seeks to address the prevailing issue of how to measure specific process components of psychobiological stress responses. Particularly the change of cortisol secretion due to stress exposure has been discussed as an endophenotype of many psychosomatic health outcomes. To assess its process components, a large variety of non-compartmental parameters (i.e., composite measures of substance concentrations at different points in time) like the area under the concentration-time curve (AUC) are commonly utilized. However, a systematic evaluation and validation of these parameters based on a physiologically plausible model of cortisol secretion has not been performed so far. Thus, a population pharmacokinetic (mixed-effects stochastic differential equation) model was developed and fitted to densely sampled salivary cortisol data of 10 males from Montreal, Canada, and sparsely sampled data of 200 mixed-sex participants from Dresden, Germany, who completed the Trier Social Stress Test (TSST). Besides the two major process components representing (1) stress-related cortisol secretion (reactivity) and (2) cortisol elimination (recovery), the model incorporates two additional, often disregarded components: (3) the secretory delay after stress onset, and (4) deviations from the projected steady-state concentration due to stress-unrelated fluctuations of cortisol secretion. The fitted model (R2 = 99%) was thereafter used to investigate the correlation structure of the four individually varying, and readily interpretable model parameters and eleven popular non-compartmental parameters. Based on these analyses, we recommend to use the minimum-maximum cortisol difference and the minimum concentration as proxy measures of reactivity and recovery, respectively. Finally, statistical power analyses of the reactivity-related sex effect illustrate the consequences of using impure non-compartmental measures of the different process components that underlie the cortisol stress response.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Cortisol; Differential equation model; Non-compartmental analyses; Population pharmacokinetics; Psychosocial stress; Statistical power

Mesh:

Substances:

Year:  2017        PMID: 29370954     DOI: 10.1016/j.psyneuen.2017.12.019

Source DB:  PubMed          Journal:  Psychoneuroendocrinology        ISSN: 0306-4530            Impact factor:   4.905


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