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Actigraphic sleep and cortisol in middle childhood: A multivariate behavioral genetics model

To date, behavioral genetic studies investigated either sleep or cortisol levels in middle childhood, but not both simultaneously. Therefore, a pertinent question is the degree to which genetic factors and environmental factor contribute to the correlation between sleep and cortisol levels. To addre...

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Autores principales: Runze, Jana, Euser, Saskia, Oosterman, Mirjam, Dolan, Conor V., Koopman-Verhoeff, M. Elisabeth, Bakermans-Kranenburg, Marian J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9216557/
https://www.ncbi.nlm.nih.gov/pubmed/35757668
http://dx.doi.org/10.1016/j.cpnec.2021.100094
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author Runze, Jana
Euser, Saskia
Oosterman, Mirjam
Dolan, Conor V.
Koopman-Verhoeff, M. Elisabeth
Bakermans-Kranenburg, Marian J.
author_facet Runze, Jana
Euser, Saskia
Oosterman, Mirjam
Dolan, Conor V.
Koopman-Verhoeff, M. Elisabeth
Bakermans-Kranenburg, Marian J.
author_sort Runze, Jana
collection PubMed
description To date, behavioral genetic studies investigated either sleep or cortisol levels in middle childhood, but not both simultaneously. Therefore, a pertinent question is the degree to which genetic factors and environmental factor contribute to the correlation between sleep and cortisol levels. To address this question, we employed the classical twin design. We measured sleep in 6-9-year-old twins (N = 436 twin pairs, “Together Unique” study) over four consecutive nights using actigraphy, and we measured morning cortisol on two consecutive days. Sleep duration, sleep efficiency, and wake episodes were used as indicators of sleep. Morning cortisol level was used as cortisol indicator. A structural equation model was fitted to estimate the contribution of additive genetic effects (A), shared (common) environmental effects, (C) and unique environmental effects (E) to phenotypic variances and covariances. Age, cohort, and sex were included as covariates. The heritability of sleep duration, sleep efficiency, and wake episodes were 52%, 45%, and 55%, respectively. Common environmental factors played no significant role. High genetic correlations between sleep duration and sleep efficiency and high genetic correlations between sleep efficiency and wake episodes were found. Shared environmental (29%) and unique environmental factors (53%) explained the variance in morning cortisol levels. Because the sleep and cortisol measures were found to be uncorrelated, we did not consider genetic and environmental contributions to the association between the sleep and cortisol measures. Our findings indicate that sleep duration, sleep efficiency, and wake episodes in children are mostly impacted by genetic factors and by unique environmental factors (including measurement error).
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spelling pubmed-92165572022-06-24 Actigraphic sleep and cortisol in middle childhood: A multivariate behavioral genetics model Runze, Jana Euser, Saskia Oosterman, Mirjam Dolan, Conor V. Koopman-Verhoeff, M. Elisabeth Bakermans-Kranenburg, Marian J. Compr Psychoneuroendocrinol Clinical Science To date, behavioral genetic studies investigated either sleep or cortisol levels in middle childhood, but not both simultaneously. Therefore, a pertinent question is the degree to which genetic factors and environmental factor contribute to the correlation between sleep and cortisol levels. To address this question, we employed the classical twin design. We measured sleep in 6-9-year-old twins (N = 436 twin pairs, “Together Unique” study) over four consecutive nights using actigraphy, and we measured morning cortisol on two consecutive days. Sleep duration, sleep efficiency, and wake episodes were used as indicators of sleep. Morning cortisol level was used as cortisol indicator. A structural equation model was fitted to estimate the contribution of additive genetic effects (A), shared (common) environmental effects, (C) and unique environmental effects (E) to phenotypic variances and covariances. Age, cohort, and sex were included as covariates. The heritability of sleep duration, sleep efficiency, and wake episodes were 52%, 45%, and 55%, respectively. Common environmental factors played no significant role. High genetic correlations between sleep duration and sleep efficiency and high genetic correlations between sleep efficiency and wake episodes were found. Shared environmental (29%) and unique environmental factors (53%) explained the variance in morning cortisol levels. Because the sleep and cortisol measures were found to be uncorrelated, we did not consider genetic and environmental contributions to the association between the sleep and cortisol measures. Our findings indicate that sleep duration, sleep efficiency, and wake episodes in children are mostly impacted by genetic factors and by unique environmental factors (including measurement error). Elsevier 2021-10-14 /pmc/articles/PMC9216557/ /pubmed/35757668 http://dx.doi.org/10.1016/j.cpnec.2021.100094 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Clinical Science
Runze, Jana
Euser, Saskia
Oosterman, Mirjam
Dolan, Conor V.
Koopman-Verhoeff, M. Elisabeth
Bakermans-Kranenburg, Marian J.
Actigraphic sleep and cortisol in middle childhood: A multivariate behavioral genetics model
title Actigraphic sleep and cortisol in middle childhood: A multivariate behavioral genetics model
title_full Actigraphic sleep and cortisol in middle childhood: A multivariate behavioral genetics model
title_fullStr Actigraphic sleep and cortisol in middle childhood: A multivariate behavioral genetics model
title_full_unstemmed Actigraphic sleep and cortisol in middle childhood: A multivariate behavioral genetics model
title_short Actigraphic sleep and cortisol in middle childhood: A multivariate behavioral genetics model
title_sort actigraphic sleep and cortisol in middle childhood: a multivariate behavioral genetics model
topic Clinical Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9216557/
https://www.ncbi.nlm.nih.gov/pubmed/35757668
http://dx.doi.org/10.1016/j.cpnec.2021.100094
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