Phenotypic, Genetic and Environmental Architecture of the Components of Sleep Quality.

Autor: Madrid-Valero JJ; Department of Health Psychology, Faculty of Health Sciences, University of Alicante, 03690, Alicante, Spain. juanjose.madrid@ua.es., Sánchez-Romera JF; Department of Human Anatomy and Psychobiology, University of Murcia, Campus de Espinardo, 30100, Murcia, Spain.; Murcia Institute of Biomedical Research, IMIB-Arrixaca, 30120, Murcia, Spain., Martínez-Selva JM; Department of Human Anatomy and Psychobiology, University of Murcia, Campus de Espinardo, 30100, Murcia, Spain.; Murcia Institute of Biomedical Research, IMIB-Arrixaca, 30120, Murcia, Spain., Ordoñana JR; Department of Human Anatomy and Psychobiology, University of Murcia, Campus de Espinardo, 30100, Murcia, Spain.; Murcia Institute of Biomedical Research, IMIB-Arrixaca, 30120, Murcia, Spain.
Jazyk: angličtina
Zdroj: Behavior genetics [Behav Genet] 2022 Sep; Vol. 52 (4-5), pp. 236-245. Date of Electronic Publication: 2022 Aug 25.
DOI: 10.1007/s10519-022-10111-0
Abstrakt: The genetic and environmental underpinnings of sleep quality have been widely investigated. However, less is known about the etiology of the different sleep quality components and their associations. Subjective sleep quality has been studied most commonly using the Pittsburgh Sleep Quality Index (PSQI). Therefore, this work aimed to study the structure of sleep quality dimensions in a population-based twin sample by examining the etiology of the associations among the PSQI components themselves and between them. The sample comprised 2129 participants from the Murcia Twin Registry. In order to study the phenotypic, genetic and environmental structure of the PSQI we used three alternative multivariate twin models including all seven sub-scales of the PSQI (subjective sleep quality, latency, duration, efficiency, disturbances, use of sleeping medication and daytime dysfunction): a multivariate model (with seven separate correlated factors), a common pathway model and an independent pathway model. The multivariate correlated factors model showed the best fit to the data. All twin models indicated significant genetic overlap among most of the PSQI components, except daytime dysfunction and use of sleep medication. Bivariate heritability explained between 25 and 50% of the covariance for most associations between dimensions. Furthermore, the common pathway model showed that around one third of the variance (0.32; CI 95% 0.18.0.43) of a latent factor common to all questionnaire dimensions is explained by genetic factors. Genetic influences on a latent factor common to all questionnaire dimensions produced the same heritability estimates as the PSQI global score. However, sleep quality dimensions showed considerable specificity regarding its genetic-environmental structure.
(© 2022. The Author(s).)
Databáze: MEDLINE
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