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Quantifying Glucocorticoid Plasticity Using Reaction Norm Approaches: There Still is So Much to Discover!

Hormones are highly responsive internal signals that help organisms adjust their phenotype to fluctuations in environmental and internal conditions. Our knowledge of the causes and consequences of variation in circulating hormone concentrations has improved greatly in the past. However, this knowled...

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Autores principales: Malkoc, Kasja, Mentesana, Lucia, Casagrande, Stefania, Hau, Michaela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9375136/
https://www.ncbi.nlm.nih.gov/pubmed/34665256
http://dx.doi.org/10.1093/icb/icab196
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author Malkoc, Kasja
Mentesana, Lucia
Casagrande, Stefania
Hau, Michaela
author_facet Malkoc, Kasja
Mentesana, Lucia
Casagrande, Stefania
Hau, Michaela
author_sort Malkoc, Kasja
collection PubMed
description Hormones are highly responsive internal signals that help organisms adjust their phenotype to fluctuations in environmental and internal conditions. Our knowledge of the causes and consequences of variation in circulating hormone concentrations has improved greatly in the past. However, this knowledge often comes from population-level studies, which generally tend to make the flawed assumption that all individuals respond in the same way to environmental changes. Here, we advocate that we can vastly expand our understanding of the ecology and evolution of hormonal traits once we acknowledge the existence of individual differences by quantifying hormonal plasticity at the individual level, where selection acts. In this review, we use glucocorticoid (GC) hormones as examples of highly plastic endocrine traits that interact intimately with energy metabolism but also with other organismal traits like behavior and physiology. First, we highlight the insights gained by repeatedly assessing an individual's GC concentrations along a gradient of environmental or internal conditions using a “reaction norm approach.” This study design should be followed by a hierarchical statistical partitioning of the total endocrine variance into the among-individual component (individual differences in average hormone concentrations, i.e., in the intercept of the reaction norm) and the residual (within-individual) component. The latter is ideally further partitioned by estimating more precisely hormonal plasticity (i.e., the slope of the reaction norm), which allows to test whether individuals differ in the degree of hormonal change along the gradient. Second, we critically review the published evidence for GC variation, focusing mostly on among- and within-individual levels, finding only a good handful of studies that used repeated-measures designs and random regression statistics to investigate GC plasticity. These studies indicate that individuals can differ in both the intercept and the slope of their GC reaction norm to a known gradient. Third, we suggest rewarding avenues for future work on hormonal reaction norms, for example to uncover potential costs and trade-offs associated with GC plasticity, to test whether GC plasticity varies when an individual's reaction norm is repeatedly assessed along the same gradient, whether reaction norms in GCs covary with those in other traits like behavior and fitness (generating multivariate plasticity), or to quantify GC reaction norms along multiple external and internal gradients that act simultaneously (leading to multidimensional plasticity). Throughout this review, we emphasize the power that reaction norm approaches offer for resolving unanswered questions in ecological and evolutionary endocrinology.
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spelling pubmed-93751362022-08-15 Quantifying Glucocorticoid Plasticity Using Reaction Norm Approaches: There Still is So Much to Discover! Malkoc, Kasja Mentesana, Lucia Casagrande, Stefania Hau, Michaela Integr Comp Biol Invited Paper Hormones are highly responsive internal signals that help organisms adjust their phenotype to fluctuations in environmental and internal conditions. Our knowledge of the causes and consequences of variation in circulating hormone concentrations has improved greatly in the past. However, this knowledge often comes from population-level studies, which generally tend to make the flawed assumption that all individuals respond in the same way to environmental changes. Here, we advocate that we can vastly expand our understanding of the ecology and evolution of hormonal traits once we acknowledge the existence of individual differences by quantifying hormonal plasticity at the individual level, where selection acts. In this review, we use glucocorticoid (GC) hormones as examples of highly plastic endocrine traits that interact intimately with energy metabolism but also with other organismal traits like behavior and physiology. First, we highlight the insights gained by repeatedly assessing an individual's GC concentrations along a gradient of environmental or internal conditions using a “reaction norm approach.” This study design should be followed by a hierarchical statistical partitioning of the total endocrine variance into the among-individual component (individual differences in average hormone concentrations, i.e., in the intercept of the reaction norm) and the residual (within-individual) component. The latter is ideally further partitioned by estimating more precisely hormonal plasticity (i.e., the slope of the reaction norm), which allows to test whether individuals differ in the degree of hormonal change along the gradient. Second, we critically review the published evidence for GC variation, focusing mostly on among- and within-individual levels, finding only a good handful of studies that used repeated-measures designs and random regression statistics to investigate GC plasticity. These studies indicate that individuals can differ in both the intercept and the slope of their GC reaction norm to a known gradient. Third, we suggest rewarding avenues for future work on hormonal reaction norms, for example to uncover potential costs and trade-offs associated with GC plasticity, to test whether GC plasticity varies when an individual's reaction norm is repeatedly assessed along the same gradient, whether reaction norms in GCs covary with those in other traits like behavior and fitness (generating multivariate plasticity), or to quantify GC reaction norms along multiple external and internal gradients that act simultaneously (leading to multidimensional plasticity). Throughout this review, we emphasize the power that reaction norm approaches offer for resolving unanswered questions in ecological and evolutionary endocrinology. Oxford University Press 2021-10-19 /pmc/articles/PMC9375136/ /pubmed/34665256 http://dx.doi.org/10.1093/icb/icab196 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Invited Paper
Malkoc, Kasja
Mentesana, Lucia
Casagrande, Stefania
Hau, Michaela
Quantifying Glucocorticoid Plasticity Using Reaction Norm Approaches: There Still is So Much to Discover!
title Quantifying Glucocorticoid Plasticity Using Reaction Norm Approaches: There Still is So Much to Discover!
title_full Quantifying Glucocorticoid Plasticity Using Reaction Norm Approaches: There Still is So Much to Discover!
title_fullStr Quantifying Glucocorticoid Plasticity Using Reaction Norm Approaches: There Still is So Much to Discover!
title_full_unstemmed Quantifying Glucocorticoid Plasticity Using Reaction Norm Approaches: There Still is So Much to Discover!
title_short Quantifying Glucocorticoid Plasticity Using Reaction Norm Approaches: There Still is So Much to Discover!
title_sort quantifying glucocorticoid plasticity using reaction norm approaches: there still is so much to discover!
topic Invited Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9375136/
https://www.ncbi.nlm.nih.gov/pubmed/34665256
http://dx.doi.org/10.1093/icb/icab196
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