Sleep and chronotype and their causal links with cardiometabolic and chronic inflammatory diseases
Approved Research ID: 6818
Approval date: March 15th 2015
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. 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. 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. 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 done when genotype data on 170K individuals is released and updated when data on the whole cohort is available and when imputation is complete.
- We will study relationships with common diseases such as diabetes.
- We will investigate how sleep duration and chronotype from questionnaires relate to movement sensor information.
- We will observe the temporal relationships of disease onset and change in sleep/chronotype to see if one develops/changes after the other.
- 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.
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.
25th Sept 2020
Our original aims were to study relationships of sleep traits with cardiometabolic and chronic inflammatory disease outcomes. In our original application, we also specified using actigraphy data to define sleep traits and have published several papers using these data.1-4
Now, we would like to extend our application by using novel methods to derive sleep-rest-activity patterns from actigraphy data and then to assess relationships of these exposures with cardiometabolic and chronic inflammatory diseases.
The specific aims of the project will be to:
1) Derive sleep-rest-activity rhythm characteristics from actigraphy data using novel methods (extended cosine models, functional PCA, and Hidden Markov Models).
2) Examine cross-sectional and prospective associations with cardiometabolic and chronic inflammatory diseases outcomes and related biomarkers.
3) Use machine learning models to determine the predictive power of these exposures for cardiometabolic and chronic inflammatory outcomes.
4) Perform GWAS of these exposures and then Mendelian Randomisation studies exploring causal relationships with cardiometabolic and chronic inflammatory outcomes.
We hope that these additional aims will be seen as natural extensions to our original aims. If any of this is unclear please let me know.
Proposed new scope, aims and hypotheses:
Aim: to investigate possible mediators between disturbed sleep and depression.
Hypotheses (pre-registered at Open Science Framework):
1) At visit 1, the cross-sectional associations between depressive symptoms and sleep problems including insomnia are mediated by inflammation as assessed by C-reactive protein levels.
2) At visit 3 (first imaging visit), the cross-sectional association between depressive symptoms and sleep problems including insomnia is mediated by amygdala responses to emotional, negatively valanced faces in the Hariri task.
As part of this work, we would like to confirm that depressive symptoms are associated with amygdala brain activity in the functional imaging task (viewing of negative, emotional faces). Amygdala reactivity for emotional stimuli has long been considered to be a "biomarker" of depression, although these ideas are based on data from small studies.
3) Sleep problems at visit 1 will predict depression at visit 2, 3 and 4, and sleep problems at visit 3 will predict depression at visit 4, adjusting for depression at visit 1 and 3 respectively.
4) CRP levels at visit 1 will mediate the longitudinal association between sleep problems at visit 1 and depression at visits 2, 3 and 4.
5) Amygdala responses to emotional faces at visit 3 will mediate the longitudinal association between sleep problems at visit 3 and depression at visit 4.
27 March 21: Proposed new aim:
To assess relationships between sleep traits/chronotype/circadian misalignment with income, job type, and level of deprivation (aspects of employment/productivity) using traditional epidemiology and Mendelian randomisation.