Sleep and death : the relationship between REM sleep and mortality
Keywords: Epidemiology.

Sleep is a non-negotiable requirement for a happy, healthy life. In the last 70 years, our understanding of sleep has grown exponentially. However, in our busy society, sleep is often overlooked and undervalued. This is surprising given that sleep disorders and sleep dysregulation have been linked to multiple systemic and brain-based diseases, including cardiovascular disease, type 2 diabetes, dementia, and major depressive disorder. Additionally, sleep disorders and sleep characteristics (e.g. sleep duration) have been linked to higher rates of mortality. Despite the emerging evidence of a sleep-mortality association, the mechanisms underlying the relationship are not well understood. Little is known about how the proportion of time spent in each sleep stage relate to timing or cause of death. This dissertation is an in-depth investigation of the relationship between rapid eye movement (REM) sleep and risk of mortality. Specific aim one combines traditional and machine learning analytic approaches to evaluate whether lower levels of REM sleep would be associated with an increased rate of mortality. Sleep is comprised of multiple sleep stages that by nature are highly correlated. Therefore, it is necessary to tease apart whether another sleep stage could be a better predictor of mortality. Aim two used supervised machine learning to rank the four sleep stages from most to least predictive in context of one another. The hypotheses were increased mortality rates would be associated with lower quantities of REM sleep and that compared to other sleep stages, REM would be the best predictor of mortality. Specific aim three was to evaluate the validity, consistency, and generalizability of the findings. to do this, the final models were validated in two independent cohorts and the results from all three cohorts were combined in a meta-analysis. Materials and Methods Three longitudinal, population-based cohorts were used in this project. The Osteoporotic Fractures in Men (MrOS) sample included 2,675 older men (mean age 76.3 years ± 5.5 years) recruited from 2003 to 2005 and followed for a median of 12.1 years. The Wisconsin Sleep Cohort (WSC) started in 1988 and followed 1,386 participants (45.7% women, mean age 51.5 years ± 8.5) for a median of 20.8 years. The Sleep Heart Health Study (SHHS) was comprised of 5,550 participants (52.4% women, mean age 63.0 years ± 11.2) recruited between 1995 and 1998 and monitored for a median of 11.9 years. The exposure was percent of total sleep time spent in REM sleep and was evaluated at baseline using polysomnography. The main outcomes included all-cause and cause-specific (cardiovascular, cancer, other) mortality confirmed with death certificates. Cox proportional hazards regression models were used to evaluate the association between percent REM and mortality. The first model contained a core set of covariates selected a priori based on existing literature and clinical experience. Additional covariates commonly associated with sleep architecture were evaluated using 6-fold cross-validation with a forward step-wise feature selection algorithm to obtain the best candidates for the final multivariate regression models. A threshold effect was suspected based on Kaplan-Meier curves, so separate models were run with percent REM as a binary variable using 15% as the cut-point. Conditional inference survival tree and random survival forest analyses were conducted to identify which sleep stage(s) were driving the significance of the finding and to evaluate relevant cut-points. Several sensitivity analyses were completed to rule out alternative explanations for the findings. The findings were replicated using data from the Wisconsin Sleep Cohort (WSC) and Sleep Heart Health Study (SHHS). A meta-analysis pooled and weighted the results from all three studies to provide a global quantification of the hazard ratio. Results MrOS participants had a 13% higher mortality rate for every 5% reduction in REM sleep (percent REM standard deviation = 6.6%) after adjusting for multiple demographic, sleep, and health covariates including study site, age at sleep visit, race, education, medication use, smoking status, caffeine intake, respiratory disturbance index, and actigraphy measures (age-adjusted hazard ratio [HR] = 1.12, fully adjusted HR = 1.13, 95% CI, 1.08--1.19). The association was also present for cardiovascular disease-related mortality (CVD) (HR = 1.18, 95% CI, 1.09--1.28), cancer related mortality (HR = 1.14, 95% CI, 1.03--1.26), and non-cardiovascular, non-cancer related mortality (HR = 1.19, 95% CI, 1.10--1.28). Individuals with < 15% REM had a higher mortality rate relative to individuals with ≥15% for each mortality outcome with odds ratios ranging from 1.20 to 1.35. The random forest model identified REM as the most important sleep stage for predicting survival. In the WSC, the effect size for 5% reduction in REM on risk of all-cause mortality was similar despite the younger age, inclusion of women, and longer follow-up period (HR = 1.17, 95% CI, 1.03--1.34). When stratified by gender, lower percent REM was associated with all-cause mortality in women (HR = 1.34, 95% CI, 1.07--1.68) but was not statistically significant in men (HR = 1.09, 95% CI, 0.92--1.30). In the SHHS results were consistent with the other cohorts with a 13% increase in all-cause mortality rate for every 5% reduction in REM (HR = 1.13, 95% CI, 1.07--1.18) and a 7% increase in cardiovascular mortality rate (HR = 1.07, 95% CI, 0.97--1.17). Unlike WSC, when stratified by gender, the hazard ratio was higher in men (HR = 1.16, 95% CI, 1.08--1.17) than women (HR = 1.09, 95% CI, 1.02--1.17). Meta-analysis of the three cohorts yielded an overall hazard ratio of 1.13 (95% CI 1.10--1.17) for all-cause mortality and 1.10 (95% CI 1.03--1.16) for cardiovascular mortality. Conclusion and Relevance There was a robust association between lower levels of REM sleep and mortality in three independent cohorts, which persisted across different causes of death and multiple sensitivity analyses. Given the complex underlying biological functions, further studies are required to understand whether the relationship is causal. Accelerated brain aging may result in reduced REM sleep, making it a disease, frailty or biologic aging marker rather than a direct mortality risk factor. Mechanistic studies are needed and strategies to preserve REM may influence clinical therapies and reduce mortality risk, particularly for adults with < 15% REM