How we sleep, and whether we are at risk of sleep disorders, is partly influenced by the genes we inherited from our parents. For example, during sleep, our brain produces repetitive patterns of activity that are not found during wake. These patterns can be measured using electroencephalography (EEG). Many of these distinct patterns, such as 'sleep-spindles' and 'k-complexes', can be described as an 'EEG fingerprint' that is unique to each individual and are highly heritable. The initial goal of this project is to better understand the function of one specific EEG pattern, sleep spindles, by identifying the genetic modifiers of sleep spindle characteristics. We will do this by developing and evaluating bioinformatic tools used to automatically identify spindles in the EEG signal. Once these tools are adapted to work in very large datasets, we can perform a genome-wide association study to identify the genes that are associated with changes in sleep spindle characteristics in the human population.
In addition, sleep disorders such as insomnia and somnambulism (sleepwalking) also have a strong heritable basis, but like sleep spindles, the identity of the genes involved are largely unknown. We plan to use DNA contributed by patients to the Sleep Research Biobank to identify genetic risk factors for these sleep disorders. In particular, we are interested in the shared genetic basis of insomnia and depression, where there is considerable overlap. The bioinformatic tools developed for the EEG will also be used to identify biomarkers of altered brain activity during sleep in these disorders, and their relationship to the genetic risk factors we find. Identifying the genetic basis of EEG traits and sleep disorders will help us understand the mysterious process of sleep. The genes identified may also serve as new drug targets for treatment of specific sleep and psychiatric disorders.