Approved research

Understanding associations between sleep and circadian disruption and mental health

Lay summary

Growing evidence suggests disruption to sleep and daily circadian rhythms may increase risk of mood disorders, and the co-occurrence of mood disorders with cardiometabolic diseases like hypertension. However, most studies are limited using small samples, subjective measures of sleep/circadian rhythmicity (which are open to bias), and have not considered important potential mediating factors, like brain structure. This highly interdisciplinary project will form the largest, most comprehensive study to date of the role of sleep and circadian disruption in mental health, using data from the landmark UK Biobank cohort. UK Biobank comprises lifestyle, health and genetic data for over 500,000 individuals, and brain imaging data for over 30,000. Over 100,000 participants wore an accelerometer for 7 days: from this data, we will calculate objective measures of circadian rest-activity patterns, alongside sleep duration/quality measures. Using this wealth of high-quality data, we will examine which sleep and circadian rhythmicity factors are associated with mental health related outcomes; and determine what aspects of brain structure and function underpin these associations. We will use participants' anonymised health records to assess whether episodes of depression and bipolar disorder can be predicted by integrating circadian rhythmicity, sleep, neuroimaging, genetic, sociodemographic and lifestyle measures. We will also examine whether circadian/sleep disruption and mental health combine to influence risk of cardiometabolic conditions like hypertension and heart disease, and by using cutting-edge genetics methods, we will examine causal relationships between sleep/circadian factors, mental health, and cardiometabolic disease. Our findings will significantly improve our understanding of the role of sleep and circadian health in mental health, and the co-occurrence between disorders of mental health with cardiometabolic disease.

The research aims to further understanding of how sleep and circadian factors influence mental health (particularly mood disorders) and brain health, and the comorbidity between mental health disorders and physical disease. We will examine associations between measures of sleep and circadian function with depression and bipolar disorder, and with Magnetic Resonance Imaging (MRI) measures of brain structure and function. We will also assess the accuracy of predicting risk of mood disorders by integrating circadian, neuroimaging, sociodemographic, lifestyle and genetic data, including with machine learning models.

Scope extension:

The research aims to further understanding of how sleep and circadian factors influence mental health (particularly mood disorders) and brain health, and the comorbidity between mental health disorders and physical disease. We will examine associations between measures of sleep and circadian function with depression and bipolar disorder, and with Magnetic Resonance Imaging (MRI) measures of brain structure and function. We will also assess the accuracy of predicting risk of mood disorders by integrating circadian, neuroimaging, sociodemographic, lifestyle, genotype and whole exome sequencing data, including with machine learning models