Browsing by Author "MacKeith, Ada"

Sleep difficulties have been on the rise for the past decade. Insomnia and sleep difficulties have associations with an increased risk of overall mortality, as well as with a diverse array of complex diseases, such as coronary heart disease, major depressive disorder, fibromyalgia and Alzheimer’s disease. Epigenomics provides information on how environmental factors influence the genome via epigenetic mechanisms, such as DNA methylation. Thus far, epigenome-wide association studies looking at the effects of sleep disturbances on the methylome have provided evidence of distinctive methylation patterns in insufficient sleep, involving biological processes related to neuroplasticity and neurodegeneration. However, more knowledge is needed to determine how the severity of sleeping difficulties influence the methylome. This thesis investigates the effects of increasing sleep difficulties on DNA methylation with an epigenome-wide association study. The study sample is derived from the Health 2000 general population survey. Subjects were divided into three different groups by their self-reported level of sleeping difficulty, and methylation measurements performed from whole blood samples utilizing the Illumina Infinium MethylationEPIC kit, encompassing >850,000 CpG sites. To identify differentially methylated sites, a multivariable regression model was used with age, gender, smoking, alcohol use, cell type distribution and plate and array data as covariates. None of the differentially methylated CpG sites identified remained significant after multiple testing correction. To gain more information regarding which biological processes the methylated sites may be part of, those CpG sites with an uncorrected p-value of <0.0005 were subjected to pathway analysis. Notable significant pathways included oxytocin- and serotonin receptor-mediated signalling pathways and Alzheimer’s disease-amyloid secretase pathway. Altogether, six pathways remained significant after multiple testing correction, with a total of 12 different genes appearing in them. Furthermore, a post-hoc regression analysis was conducted between these 12 genes and their corresponding CpG sites, and health-related quality of life questionnaire responses. Significant results included associations between sleep, and discomfort and symptoms (including pain). As an additional analysis, a database search was conducted to learn more about the genes’ functionality at the level of phenotype. Results included some variant trait associations to sleep, Alzheimer’s disease and cognitive performance. The associations to Alzheimer’s disease and cognitive performance warrant further research with a similar additive model, perhaps with a larger sample.