Principal Investigator: Dr Martin Rutter
Department: Manchester Diabetes Centre
Institution: University of Manchester
Dr Simon Kyle – University of Oxford
Professor Deborah Lawlor – University of Bristol
Dr Nicole Tang – University of Warwick
Dr Jingyi Qian – Brigham and Womens Hospital
Dr Richa Saxena – Massachusetts General Hospital
Dr Richa Saxena – Broad Institute
Dr Max Little – Aston University
Dr Kai Spiegelhalder -University of Freiburg
Mr Angus Burns – Monash UniversityTags: 6818, cardiovascular, chronic inflammation, chronotype, metabolic, sleep
1a: It is uncertain how sleep patterns and chronotype (morning/evening preference) are associated with disease and therefore:
1. We will study relationships with common diseases such as diabetes.
2. We will investigate how sleep duration and chronotype from questionnaires relate to movement sensor information.
3. We will observe the temporal relationships of disease onset and change in sleep/chronotype to see if one develops/changes after the other.
4. Finally, we will identify genes linked to sleep patterns and chronotype, and use this information to understand whether sleep patterns and chronotype have a role in causing or worsening common diseases
PROJECT EXTENSION -APPROVED 21.12.2015
Characterising the association between sleep/chronotype with brain function, structure and mental health
“We are requesting to extend our application 6818 to look at the associations of sleep/chronotype with brain function, structure and mental health.
Justification: We have made this request because our preliminary analysis has suggested causal links between chronotype and educational attainment and we wish to further explore this and related hypotheses. It is relevant to our original application because educational attainment and other psychological and mental health parameters could mediate links between sleep/chronotype and cardiometabolic diseases.
Background: While the core function(s) of sleep remain to be fully elucidated, contemporary theories emphasise the central importance of sleep for brain function; playing a critical role in synaptic downscaling (Tononi & Cirelli, 2006), memory consolidation (Diekelmann & Born, 2010) and clearance of wake-accumulated neurotoxic metabolites (Xie et al., 2013). Correspondingly, chronic poor sleep has been linked to impairments in neurocognition, manifest in both performance-based measures of attention and memory and hypoactivation of task-related cortical regions during fMRI recordings (Fortier-Brochu et al., 2012). Moreover, several studies have shown altered brain morphometry in patients with insomnia relative to normal sleeping controls, across both grey and white matter indices, although findings have been mixed, possibly due to important design and methodological limitations (Spiegelhalder et al., 2015).
In general, studies investigating associations between insomnia and neuropsychological performance, brain activity and structure, have recruited small samples, assessed discrete variables in isolation, and have not interrogated different sleep phenotypes, stratified by important dimensions of sleep health such as chronotype and sleep duration. Given the high prevalence of disrupted sleep – up to 1/3 of the population experience problems with sleep initiation and maintenance – there is a clear need to better circumscribe linkage between sleep disturbance and brain function/ structure within the context of adequately-powered designs. The UK biobank affords such an exciting opportunity. Defining how dimensions of sleep co-vary with brain structure and function helps to 1) advance understanding and importance of sleep for brain health; but also 2) identifies important outcome variables for future causal tests of sleep improvement (within the context of prospective RCTs). Such work may have important implications for understanding the development and maintenance of psychiatric disorder and pathological ageing, where sleep alterations are common and impairing.
Aims and study design:
- a) i) To compare subgroups of poor sleepers (classified based on sleep duration, continuity and chronotype) with matched normal sleeping controls on the following dependent variables of interest:
– Neuropsychological performance (reasoning, simple reaction time, pairs matching, numeric memory, prospective memory)
– Brain morphometry
– Resting state and task-related fMRI activity
– Controlling for relevant confounding variables: e.g. neurological conditions, psychotropic medication use, depression, sleep disorders (sleep apnoea / narcolepsy), shiftwork, age, gender, years of education, socioeconomic status, BMI, physical activity.
- b) ii) To determine whether sleep parameters or chronotype predict deterioration of neuropsychological performance, anxiety or depression. These analyses will include the 20K individuals with four-year longitudinal UK Biobank data and the entire UK Biobank cohort using HES data and, when available, Primary Care data. The analysis will control for relevant confounding variables including baseline mental health status.
- c) To determine whether genetic factors for dimensions of sleep (continuity, duration and chronotype) associate with specific measures of neuropsychological performance, brain structure and activity or mental health outcomes. This aim seeks to provide deeper understanding of our novel observation in the UK Biobank that there is significant genetic sharing between chronotype and educational attainment, with evening chronotype being causally related to increased years of education and seeks to test for a causal role of sleep in brain health.
Potential benefits of this research:
– The research is expected to highlight the importance of sleep/chronotype for psychological performance/health which could have important implications for public health policy/guidance and could have important long-term societal benefits.
– The research will assess whether genetic factors related to sleep parameters have a role in influencing neuropsychological performance, brain structure/function and mental health. These findings could help identify novel targets for therapeutic intervention to improve psychological health and well-being.
1b: The aim of this research is to better understand the associations and potential causal pathways linking sleep and/or chronotype with several common metabolic and inflammatory diseases that have major health, economic and societal impacts such as heart disease, diabetes, asthma and arthritis.
The study also aims to discover genes associated with sleep patterns and chronotype. This new knowledge will be used to explore whether sleep patterns and chronotype have a role in causing these diseases.
This research may guide the development of new treatments targeting sleep or the biological clock to prevent or treat cardiometabolic and chronic inflammatory diseases.
1c: We will relate the presence and severity of cardiometabolic and chronic inflammatory diseases to:
1. Sleep duration
2. Sleep disturbance (insomnia/waking)
3. Chronotype (morning/evening person)
4. Sleep apnoea symptoms (snoring/daytime sleepiness)
5. Shift work
Each analysis will control/stratify for the other factors listed (1-5).
Prospective studies will assess the temporal relationships between disorders of sleep/chronotype, shift work and common diseases.
Genome-wide association studies will aim to identify genes linked to sleep duration, disturbance and chronotype and Mendelian randomisation studies will explore causal relationships between these factors and the development of common diseases.
1d: Whole cohort: a) cross-sectional studies; b) the prospective study assessing incident cardiometabolic and inflammatory diseases; c) genome-wide association studies; d) Mendelian randomisation studies.
Individuals with accelerometer data: to relate to shift work, prevalent/incident disease, sleep/chronotype (questionnaire) and genotype (if adequately powered).
20,000 people assessed on two occasions over 4 years (including those with accelerometer data): assessing incident sleep disturbance and change in chronotype.
GWAS and Mendelian Randomisation studies: Primary analyses will be done when genotype data on 170K individuals is released and updated when data on the whole cohort is available and when imputation is complete.
Scope extension – October 2019
Proposed new scope
Our previous focus was on the “downstream” health consequences of disturbed sleep. For this project we would like to look “upstream” of sleep to understand the aetiology of sleep disturbance. We propose to assess the following exposures: early and adult stress events and genetic risk for insomnia. Outcomes will be objectively (actigraphy) and subjectively assessed sleep traits focussing on insomnia.
1) describe how Adverse Childhood Experiences (ACEs) and Stressful Life Events (SLEs) are related to objective and subjective sleep traits with sex/gender as a moderator.
3) perform a mediation/moderation analysis on the effect of ACEs and SLEs together to understand whether ACEs operate through SLEs (mediation), there is effect-modification by ACEs (moderation), or both (mediated moderation).
4) perform a gene by environment analysis in which objectively determined sleep traits are regressed on polygenic risk scores for insomnia in interaction with SLEs to assess effect modification.
5) perform a gene by environment analysis in which objective sleep parameters associated with insomnia (e.g. wake after sleep onset) and self-reported insomnia complaints are regressed on polygenic risk scores for short sleep in interaction with SLEs to assess effect modification.
Last updated Nov 1, 2019