Polygenic score for sleep duration. Association with cognition

Associations of a multidimensional polygenic sleep health score and a sleep lifestyle index on health outcomes and their interaction in a clinical biobank

Sleep is a complex behavior regulated by genetic and environmental factors, and is known to influence health outcomes. However, the effect of multidimensional sleep encompassing several sleep dimensions on diseases has yet to be fully elucidated. Using the Mass General Brigham Biobank, we aimed to examine the association of multidimensional sleep with health outcomes and investigate whether sleep behaviors modulate genetic predisposition to unfavorable sleep on mental health outcomes. First, we generated a Polygenic Sleep Health Score using previously identified single nucleotide polymorphisms for sleep health and constructed a Sleep Lifestyle Index using data from self-reported sleep questions and electronic health records; second, we performed phenome-wide association analyses between these indexes and clinical phenotypes; and third, we analyzed the interaction between the indexes on prevalent mental health outcomes. Fifteen thousand eight hundred and eighty-four participants were included in the analysis (mean age 54.4; 58.6% female). The Polygenic Sleep Health Score was associated with the Sleep Lifestyle Index (β=0.050, 95%CI=0.032, 0.068) and with 114 disease outcomes spanning 12 disease groups, including obesity, sleep, and substance use disease outcomes (p<3.3×10-5). The Sleep Lifestyle Index was associated with 458 disease outcomes spanning 17 groups, including sleep, mood, and anxiety disease outcomes (p<5.1×10-5). No interactions were found between the indexes on prevalent mental health outcomes. These findings suggest that favorable sleep behaviors and genetic predisposition to healthy sleep may independently be protective of disease outcomes. This work provides novel insights into the role of multidimensional sleep on population health and highlights the need to develop prevention strategies focused on healthy sleep habits.

Genetic associations between sleep traits and cognitive ageing outcomes in the Hispanic Community Health Study/Study of Latinos

BACKGROUND

Sleep phenotypes have been reported to be associated with cognitive ageing outcomes. However, there is limited research using genetic variants as proxies for sleep traits to study their associations. We estimated associations between Polygenic Risk Scores (PRSs) for sleep duration, insomnia, daytime sleepiness, and obstructive sleep apnoea (OSA) and measures of cogntive ageing in Hispanic/Latino adults.

METHODS

We used summary statistics from published genome-wide association studies to construct PRSs representing the genetic basis of each sleep trait, then we studied the association of the PRSs of the sleep phenotypes with cognitive outcomes in the Hispanic Community Healthy Study/Study of Latinos. The primary model adjusted for age, sex, study centre, and measures of genetic ancestry. Associations are highlighted if their p-value <0.05.

FINDINGS

Higher PRS for insomnia was associated with lower global cognitive function and higher risk of mild cognitive impairment (MCI) (OR = 1.20, 95% CI [1.06, 1.36]). Higher PRS for daytime sleepiness was also associated with increased MCI risk (OR = 1.14, 95% CI [1.02, 1.28]). Sleep duration PRS was associated with reduced MCI risk among short and normal sleepers, while among long sleepers it was associated with reduced global cognitive function and with increased MCI risk (OR = 1.40, 95% CI [1.10, 1.78]). Furthermore, adjustment of analyses for the measured sleep phenotypes and APOE-ε4 allele had minor effects on the PRS associations with the cognitive outcomes.

INTERPRETATION

Genetic measures underlying insomnia, daytime sleepiness, and sleep duration are associated with MCI risk. Genetic and self-reported sleep duration interact in their effect on MCI.

FUNDING

Described in Acknowledgments.

Sleep disturbance is associated with mild cognitive impairment: a community population-based cross-sectional study

BACKGROUND

Sleep is conducive to the elimination of brain metabolites and the recovery of brain function. However, the relationship between sleep disturbance and Mild Cognitive Impairment is not fully been determined.

METHODS

This was a community population-based cross-sectional study. A total of 1,443 participants from a village in the suburbs of Xi'an, China were enrolled in 2017. Sleep quality was evaluated using the Pittsburgh sleep quality index (PSQI), and sleep disturbance was defined as a PSQI score > 5. Mini-Mental State Examination (MMSE) was used to assess cognitive function and Mild Cognitive Impairment(MCI) was defined as the MMSE score less than cutoff values and meets the diagnostic criteria. Univariate and multivariate analyses were used to analyze the relationships between sleep disturbance and MCI.

RESULTS

Among 1,443 subjects, 69(4.78%) had MCI, and 830 (57.52%) had sleep disturbance. In bivariate analysis, MCI was associated with sleep disturbance (ρ = 0.094, P<0.001). In the binary logistic regression, MCI was positively associated with the sleep disturbance (OR = 2.027, 95%CI = 1.112-3.698, P = 0.021). In the internal constitution of PSQI, MCI was negatively associated with the habitual sleep efficiency (OR = 0.447, 95%CI = 0.299-0.669, P < 0.001). Compared with waking up before or at 7 am, waking up after 7 am (OR = 0.555, 95%CI = 0.309-0.995, P = 0.048), or 8 am (OR = 0.296, 95%CI = 0.097-0.902, P = 0.032) was probably more likely to have normal cognition. However, people who slept more than 8 h a day might be more likely to suffer from MCI (OR = 5.560, 95%CI = 1.419-21.789, P = 0.014).

CONCLUSION

Sleep disturbance is associated with Mild Cognitive Impairment. However, the causal relationship between them is not clear. It needs to be further studied.

Sleep Polygenic Risk Score Is Associated with Cognitive Changes over Time

Sleep problems have been associated with cognition, both cross-sectionally and longitudinally. Specific genes have been also associated with both sleep regulation and cognition. In a large group of older non-demented adults, we aimed to (a) validate the association between Sleep Polygenic Risk Score (Sleep PRS) and self-reported sleep duration, and (b) examine the association between Sleep PRS and cognitive changes in a three-year follow-up. Participants were drawn from the Hellenic Longitudinal Investigation of Aging and Diet (HELIAD). A structured, in-person interview, consisting of a medical history report and physical examination, was conducted for each participant during each of the visits (baseline and first follow-up). In total, 1376 participants were included, having all demographic, genetic, and cognitive data, out of which, 688 had at least one follow-up visit. In addition, an extensive neuropsychological assessment examining five cognitive domains (memory, visuo-spatial ability, attention/speed of processing, executive function, and language) was administered. A PRS for sleep duration was created based on previously published, genome-wide association study meta-analysis results. In order to assess the relationship between the Sleep PRS and the rate of cognitive change, we used generalized estimating equations analyses. Age, sex, education, ApolipoproteinE-ε4 genotype status, and specific principal components were used as covariates. On a further analysis, sleep medication was used as a further covariate. Results validated the association between Sleep PRS and self-reported sleep duration (B = 1.173, E-6, p = 0.001). Further, in the longitudinal analyses, significant associations were indicated between increased Sleep PRS and decreased visuo-spatial ability trajectories, in both the unadjusted (B = -1305.220, p = 0.018) and the adjusted for the covariates model (B = -1273.59, p = 0.031). Similarly, after adding sleep medication as a covariate (B = -1372.46, p = 0.019), none of the associations between Sleep PRS and the remaining cognitive domains were significant. PRS indicating longer sleep duration was associated with differential rates of cognitive decline over time in a group of non-demented older adults. Common genetic variants may influence the association between sleep duration and healthy aging/cognitive health.