Circadian assays for abnormality detection in mental and physical health
This project is connected with the newly established Sleep, Circadian and Neuroscience Institute (SCNi) which is funded by the Wellcome Trust. As a collaboration between Neuroscience, Genetics, Psychiatry, and the Institute of Biomedical Engineering, week seek to establish pathways for circadian rhythm disorders from the genetic mechanisms up to the social behaviours which contribute to and result from such disorders. The project fits within the larger aim of providing the infrastructure to explore the relationship between sleep/circadian rhythm disruption and a sub-set of neuropsychiatric disorders and drive forward translation studies for the improvement of health. Although the initial focus will be on a sub-set of neuropsychiatric disorders, ultimately we hope that the expertise developed within the SCNi will be applied to additional psychiatric problems and encompass a broad range of neurodegenerative disease. This study outlines an integrated approach to define some of the specific mechanisms that give rise to sleep/circadian rhythm disruption in neuropsychiatric disorders and to use this information for the provision of evidence-based approaches for the improvement of health.
As sleep and circadian physiology are dependent upon all the major neurotransmitter systems, it should be no surprise that sleep complaints are reported in more than 80% of patients with either depression or schizophrenia and that sleep abnormalities are common in patients with chronic pain, Alzheimer's and Parkinson's disease. Interestingly, sleep and circadian rhythm disruption often precedes the symptoms associated with these conditions. Disruption of sleep/circadian control will in-turn have wide-spread effects, ranging across all aspects of neural and neuroendocrine function including impaired cognition, emotions, metabolic abnormalities, reduced immunity and elevated risks of cancer and coronary heart disease. This spectrum of pathologies, which frequently arise from sleep/circadian disruption, are also co-morbid with many brain disorders. Yet these co-morbid pathologies are rarely linked to the disruption of sleep. Furthermore, sleep/circadian rhythm disruption will lead to abnormal light exposure and atypical patterns of social behaviour that will feedback to further destabilize sleep/circadian physiology and exacerbate an abnormal pattern of neurotransmitter release within the brain.
Initial summer project work will explore sleep structure, actigraphy, and cardiovascular phase using several large databases (comprising 100’s of patients) of scored clinical data. Signal processing, feature selection and statistical machine learning techniques will be applied to extract clinically useful characteristics for assessing sleep structure and disease symptom severity. Clinical applications will include a variety of sleep related illnesses and behavioural abnormalities such as borderline mid disorder, attention deficit hyperactivity disorder (ADHD), and schizophrenia.
The long range research for a DPhil will involve analysis of social networking behaviour, actigraphy, geolocation, cardiovascular signal phase, and sleep structure. We also hope to connect the behaviours to gene expression and phenotypic categories.