Meta-analysis reveals glucocorticoid levels reflect variation in metabolic rate, not 'stress'

Glucocorticoid (GC) variation has long been thought to reflect variation in organismal 'stress,' but associations between GCs and Darwinian fitness components are diverse in magnitude, direction, and highly context-dependent. This paradox reveals our poor understanding of the causes of GC variation, contrasting with the detailed knowledge of the functional consequences of GC variation. Amongst an array of effects in many physiological systems, GCs orchestrate energy availability to anticipate and recover from predictable and unpredictable environmental fluctuations and challenges. Although this is mechanistically well-known, the extent to which GC levels are quantitatively explained by energy metabolism is unresolved. We investigated this association through meta-analysis, selecting studies of endotherms in which (1) an experiment was performed that affected metabolic rate and (2) metabolic rate and GC levels were measured simultaneously. We found that an increase in metabolic rate was associated with an increase in GC levels in 20 out of 21 studies (32 out of 35 effect sizes). More importantly, there was a strong positive correlation between the increases in metabolic rate and GCs (p=0.003). This pattern was similar in birds and mammals, and independent of the nature of the experimental treatment. We conclude that metabolic rate is a major driver of GC variation within individuals. Stressors often affect metabolic rate, leading us to question whether GC levels provide information on 'stress' beyond the stressor's effect on metabolic rate.

Allostasis revisited: A perception, variation, and risk framework

The framework of allostasis, allostatic load and overload (i.e., stability through change) attempts to combine homeostasis processes in day-to-day responses of physiology and behavior. These include predictive changes in environment such as seasons, and facultative responses to perturbations. The latter can be severe, occur at any time, and may present considerable additional challenges to homeostasis. Hormonal cascades, such as the hypothalamo-pituitary-adrenal cortex (HPA) axis, play a key role in responses to perturbations across vertebrate taxa. Glucocorticoids have been implicated in these processes in relation to energy balance that plays a role in determining responses to energetic demand (allostatic load) and influencing subsequent physiology and behavior associated with coping. Circulating glucocorticoid levels are likely regulated in part based on an individual’s proximity to energetic crisis, identified as the perturbation resistance potential (PRP). In the model of allostatic load, PRP is quantified as the difference between available resources and all energetic costs of allostatic load such as daily routines, life history stages (breeding, migration, molt and so on), and the impact of environmental perturbations. PRP can change gradually or abruptly and may be reflected by spikes in blood hormone levels. The pattern of individual responsiveness to PRP may vary and has specific implications for the activation of mineralocorticoid vs glucocorticoid-type receptors, hormone metabolizing enzymes and other downstream factors in target tissues. However, PRP is a difficult metric to measure. Here, we examine the variety of cues that animals may use to inform them about the status of their PRP and probability of energetic crisis. We consider (1) elevation in glucocorticoids as an endocrine “decision,” and (2) error management strategies in evaluating responsiveness to cues that may reflect or predict an impending energetic crisis. The potential for differential receptor activation as well as further integrative “decisions” to determine the diverse and sometimes contradictory effects of receptor activation and its downstream actions are important to the consideration of error management. This perspective offers insight into the basis of intra- and inter-individual variability in responsiveness and opens an avenue toward improving compatibility of the allostasis model with more classical views on “stress”.