Profile repeatability: A new method for evaluating repeatability of individual hormone response profiles

Reed, J. Michael; Harris, David R.; Romero, L. Michael

doi:10.1016/j.ygcen.2018.09.015

Cited by 14 publications

(4 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Given the moderate repeatability of hormone levels, this sampling effort is likely to yield imprecise estimates of individual consistency (47). It would also be valuable for endocrinologists to have a discussion of the best approach for evaluating individual consistency, as there are a variety of different approaches, including several recent suggestions [e.g., reaction norm approach (40) and profile repeatability (34)]. Finally, to improve our understanding of consistent individual variation in endocrinology, it is critical that repeatability studies recognize the pleiotropic nature of hormones so that repeated measurements assess the same biological function of a hormone.…”

Section: R107mentioning

confidence: 99%

Meta-analytic insights into factors influencing the repeatability of hormone levels in agricultural, ecological, and medical fields

Fanson

Biro

2019

American Journal of Physiology-Regulatory, Integrative and Comp

View full text Add to dashboard Cite

Interest in individual variation in hormone concentrations is rapidly increasing, particularly with regard to the evolutionary and practical implications. A key aspect of studying individual variation in any labile trait is estimating the degree of within- versus among-individual variation, but at present, we do not have a broad consensus on the extent to which hormone levels are repeatable and what factors might influence repeatability. To address this knowledge gap, we conducted a comprehensive meta-analysis of hormone levels that included 1,132 estimates of repeatability from 368 studies across three fields of study: agriculture, ecology, and medicine. We assessed the influence of sex, age class, sample type, hormone family, type of hormone measure, assay type, number of subjects, number of samples per subject, and sampling interval on repeatability estimates. Overall mean repeatability was 0.58, but estimates differed substantially among study disciplines, being lowest in ecology (0.34), moderate in agriculture (0.52), and relatively high in medicine (0.68). In addition, repeatability decreased slightly as sampling interval increased, and also tended to be higher for peak hormone levels than baseline levels. Overall, hormone levels are moderately repeatable, suggesting that they can potentially be useful indicators of individual variation. However, estimates of repeatability are quite variable among fields, so caution should be used when relying on single samples to assess individual variation.

show abstract

Section: R107mentioning

confidence: 99%

Meta-analytic insights into factors influencing the repeatability of hormone levels in agricultural, ecological, and medical fields

Fanson

Biro

2019

American Journal of Physiology-Regulatory, Integrative and Comp

View full text Add to dashboard Cite

show abstract

“…negative feedback strength) are emerging as having greater value than single time point measurements (e.g. maximum titres) in predicting fitness [9], while establishing within-individual repeatability between acute stress responses is essential for determining response phenotypes [10].…”

Section: Introductionmentioning

confidence: 99%

Eye region surface temperature dynamics during acute stress relate to baseline glucocorticoids independently of environmental conditions

Jerem

Jenni-Eiermann

McKeegan

et al. 2019

Physiology & Behavior

View full text Add to dashboard Cite

Reactions to acute stressors are critical for survival. Yet, the challenges of assessing underlying physiological processes in the field limit our understanding of how variation in the acute stress response relates to fitness in free-living animals. Glucocorticoid secretion during acute stress can be measured from blood plasma concentrations, but each blood sample can only provide information for one point in time. Also, the number of samples that can be extracted from an individual in the field is usually limited to avoid compromising welfare. This restricts capacity for repeated assessment, and therefore temporal resolution of findings within- and between-acute stress responses - both of which are important for determining links between acute stress and fitness. Acute stress induces additional body surface temperature changes that can be measured non-invasively, and at high frequencies using thermal imaging, offering opportunities to overcome these limitations. But, this method's usefulness in the field depends on the extent that environmental conditions affect the body surface temperature response, which remains poorly understood. We assessed the relative importance of individual physiology (baseline glucocorticoid concentrations) and environmental conditions (air temperature and relative humidity) in determining the eye region surface temperature (Teye) response to acute stress, in wild blue tits (Cyanistes caeruleus) during trapping, handling and blood sampling. When controlling for between-individual baseline variation, Teye initially dropped rapidly below, and then recovered above baseline, before declining more slowly until the end of the test, 160 s after trap closure. One measure of the amplitude of this response – the size of the initial drop in Teye – was dependent on environmental conditions, but not baseline corticosterone. Whereas, two properties defining response dynamics – the timing of the initial drop, and the slope of the subsequent recovery – were related to baseline corticosterone concentrations, independently of environmental conditions. This suggests inferring the acute stress response using thermal imaging of Teye will be practical under fluctuating environmental conditions in the field.

show abstract

“…Finally, given recent interest in estimating the repeatability of glucocorticoid regulation ( Cockrem, 2013 ; Hau et al, 2016 ; Taff, Schoenle & Vitousek, 2018 ), I also included a function that takes input from cort_sim2 and calculates the observed repeatability of several measures using package rptR ( Stoffel, Nakagawa & Schielzeth, 2017 ). Full details are included in the package documentation, but this function returns repeatability for each individual time point specified in the down sampled data set, profile repeatability ( Reed, Harris & Romero, 2019 ), and repeatability for area under the curve (AUC) calculated as both increase (AUC I ) and ground (AUC G ) approaches ( Pruessner et al, 2003 ). For each AUC measure, the function returns repeatability for the full time course, for an estimate using only the observed values in the down sampled data set, and for the full data set constrained to the time period encompassing the observed data points.…”

Section: Methodsmentioning

confidence: 99%

Simulating physiological flexibility in the acute glucocorticoid response to stressors reveals limitations of current empirical approaches

Taff

2022

PeerJ

View full text Add to dashboard Cite

Wild animals often experience unpredictable challenges that demand rapid and flexible responses. The glucocorticoid mediated stress response is one of the major systems that allows vertebrates to rapidly adjust their physiology and behavior. Given its role in responding to challenges, evolutionary physiologists have focused on the consequences of between-individual and, more recently, within-individual variation in the acute glucocorticoid response. However, empirical studies of physiological flexibility are severely limited by the logistical challenges of measuring the same animal multiple times. Data simulation is a powerful approach when empirical data are limited, but has not been adopted to date in studies of physiological flexibility. In this article, I develop a simulation that can generate realistic acute glucocorticoid response data with user specified characteristics. Simulated animals can be sampled continuously through an acute response and across as many separate responses as desired, while varying key parameters. Using the simulation, I develop several scenarios that address key questions in physiological flexibility. These scenarios demonstrate the conditions under which a single glucocorticoid trait can be accurately assessed with typical experimental designs, the consequences of covariation between different components of the acute stress response, and the way that context specific differences in variability of acute responses can influence the power to detect relationships between the strength of the acute stress response and fitness. I also describe how to use the simulation tools to aid in the design and evaluation of empirical studies of physiological flexibility.

show abstract

Profile repeatability: A new method for evaluating repeatability of individual hormone response profiles

Cited by 14 publications

References 44 publications

Meta-analytic insights into factors influencing the repeatability of hormone levels in agricultural, ecological, and medical fields

Meta-analytic insights into factors influencing the repeatability of hormone levels in agricultural, ecological, and medical fields

Eye region surface temperature dynamics during acute stress relate to baseline glucocorticoids independently of environmental conditions

Simulating physiological flexibility in the acute glucocorticoid response to stressors reveals limitations of current empirical approaches

Contact Info

Product

Resources

About