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Genetic and Environmental Influences on Sleep Quality: Quantitative and Molecular Genetic Approaches to an Understanding of Individual Differences

By Nicola L. Barclay


There are vast inter-individual differences in sleep quality in the general population – whilst some individuals sleep well with little or no sleep disturbance, others experience frequent sleep disturbances, problems which often manifest into chronic sleep disorders such as insomnia. The aim of this thesis is to explore factors accounting for these observed differences in sleep quality between individuals. Using data from a large-scale twin study this thesis uses behavioural genetic techniques to investigate genetic and environmental influences on sleep quality in a sample of 1,556 twins and siblings aged 18-27 years. The first four studies use quantitative genetic techniques to investigate 1) associations between components of sleep quality and the overlap in the genetic and environmental influences accounting for them; 2) specific non-shared environmental influences on global sleep quality; 3) the presence of gene-environment interplay between sleep quality and dependent negative life events; and 4) the association between sleep quality and diurnal preference, and the overlap in their aetiological influences. Most importantly, there was substantial genetic overlap between individual components of sleep quality (rA mostly ≥.50); sleep quality and diurnal preference (rD = .52[95% CI=.37-.70]); and sleep quality and dependent negative life events (rD = .63[.45-.83]) – the latter finding providing evidence of gene-environment correlation. In general, non-shared environmental overlap was small (rE mostly ≤.40). The final study used a candidate gene approach to investigate associations between sleep quality and diurnal preference with 5HTTLPR, PER3, and CLOCK 3111 – polymorphisms hypothesized to be implicated in sleep and/or the circadian system. An association was found between the ‘long’ allele of 5HTTLPR and poor sleep quality (β = -.34, p<.01). This thesis utilises the twin method in novel ways in the context of sleep research and advances knowledge of the genetic and environmental underpinnings of the variation in sleep quality in healthy young adults

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