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As we age, we experience changes in our nighttime sleep and daytime wakefulness. Individuals afflicted with Alzheimer’s disease (AD) can develop sleep problems even before memory and other cognitive deficits are reported. As the disease progresses and cognitive changes ensue, sleep disturbances become even more debilitating. Thus, it is imperative to gain a better understanding of the relationship between sleep and AD pathogenesis. We postulate a bidirectional relationship between sleep and the neuropathological hallmarks of AD; in particular, the accumulation of amyloid-β (Aβ) and tau. Our research group has shown that extracellular levels of both Aβ and tau fluctuate during the normal sleep−wake cycle. Disturbed sleep and increased wakefulness acutely lead to increased Aβ production and decreased Aβ clearance, whereas Aβ aggregation and deposition is enhanced by chronic increased wakefulness in animal models. Once Aβ accumulates, there is evidence in both mice and humans that this results in disturbed sleep. New findings from our group reveal that acute sleep deprivation increases levels of tau in mouse brain interstitial fluid (ISF) and human cerebrospinal fluid (CSF) and chronic sleep deprivation accelerates the spread of tau protein aggregates in neural networks. Finally, recent evidence also suggests that accumulation of tau aggregates in the brain correlates with decreased nonrapid eye movement (NREM) sleep slow wave activity. In this review, we first provide a brief overview of the AD and sleep literature and then highlight recent advances in the understanding of the relationship between sleep and AD pathogenesis. Importantly, the effects of the bidirectional relationship between the sleep−wake cycle and tau have not been previously discussed in other reviews on this topic. Lastly, we provide possible directions for future studies on the role of sleep in AD.

Richa Saxena and colleagues report genome-wide association analyses of sleep disturbance traits in the UK Biobank cohort. They discover loci associated with insomnia symptoms and excessive daytime sleepiness and identify genetic correlations with several neuropsychiatric and metabolic traits. Chronic sleep disturbances, associated with cardiometabolic diseases, psychiatric disorders and all-cause mortality 1 , 2 , affect 25–30% of adults worldwide 3 . Although environmental factors contribute substantially to self-reported habitual sleep duration and disruption, these traits are heritable 4 , 5 , 6 , 7 , 8 , 9 and identification of the genes involved should improve understanding of sleep, mechanisms linking sleep to disease and development of new therapies. We report single- and multiple-trait genome-wide association analyses of self-reported sleep duration, insomnia symptoms and excessive daytime sleepiness in the UK Biobank ( n = 112,586). We discover loci associated with insomnia symptoms (near MEIS1 , TMEM132E , CYCL1 and TGFBI in females and WDR27 in males), excessive daytime sleepiness (near AR – OPHN1 ) and a composite sleep trait (near PATJ ( INADL ) and HCRTR2 ) and replicate a locus associated with sleep duration (at PAX8 ). We also observe genetic correlation between longer sleep duration and schizophrenia risk ( r g = 0.29, P = 1.90 × 10 −13 ) and between increased levels of excessive daytime sleepiness and increased measures for adiposity traits (body mass index (BMI): r g = 0.20, P = 3.12 × 10 −9 ; waist circumference: r g = 0.20, P = 2.12 × 10 −7 ).

In mammals, the circadian clocks network (central and peripheral oscillators) controls circadian rhythms and orchestrates the expression of a range of downstream genes, allowing the organism to anticipate and adapt to environmental changes. Beyond their role in circadian rhythms, several studies have highlighted that circadian clock genes may have a more widespread physiological effect on cognition, mood, and reward-related behaviors. Furthermore, single nucleotide polymorphisms in core circadian clock genes have been associated with psychiatric disorders (such as autism spectrum disorder, schizophrenia, anxiety disorders, major depressive disorder, bipolar disorder, and attention deficit hyperactivity disorder). However, the underlying mechanisms of these associations remain to be ascertained and the cause–effect relationships are not clearly established. The objective of this article is to clarify the role of clock genes and altered sleep–wake rhythms in the development of psychiatric disorders (sleep problems are often observed at early onset of psychiatric disorders). First, the molecular mechanisms of circadian rhythms are described. Then, the relationships between disrupted circadian rhythms, including sleep–wake rhythms, and psychiatric disorders are discussed. Further research may open interesting perspectives with promising avenues for early detection and therapeutic intervention in psychiatric disorders.

Timing and duration of sleep are controlled by the circadian system, which keeps an ~24-h internal rhythm that entrains to environmental stimuli, and the sleep homeostat, which rises as a function of time awake. There is a normal distribution across the population in how the circadian system aligns with typical day and night resulting in varying circadian preferences called chronotypes. A portion of the variation in the population is controlled by genetics as shown by the single-gene mutations that confer extreme early or late chronotypes. Similarly, there is a normal distribution across the population in sleep duration. Genetic variations have been identified that lead to a short sleep phenotype in which individuals sleep only 4–6.5 h nightly. Negative health consequences have been identified when individuals do not sleep at their ideal circadian timing or are sleep deprived relative to intrinsic sleep need. Whether familial natural short sleepers are at risk of the health consequences associated with a short sleep duration based on population data is not known. More work needs to be done to better assess for an individual’s chronotype and degree of sleep deprivation to answer these questions.

Sleep disturbance is an important factor in the pathophysiology and progression of psychiatric disorders, but whether it is a cause, or a downstream effect is still not clear. To investigate causal relationships between three sleep-associated traits and seven psychiatric diseases, we used genetic variants related to insomnia, chronotype and sleep duration to perform a two-sample bidirectional Mendelian randomisation analysis. Summary-level data on psychiatric disorders were extracted from the Psychiatric Genomics Consortium. Effect estimates were obtained by using the inverse-variance-weighted (IVW), weights modified IVW, weighted-median methods, MR-Egger regression, MR pleiotropy residual sum and outlier (MR-PRESSO) test and Robust Adjusted Profile Score (RAPS). The causal odds ratio (OR) estimate of genetically determined insomnia was 1.33 (95% confidence interval (CI) 1.22-1.45; p = 5.03 × 10-11) for attention-deficit/hyperactivity disorder (ADHD), 1.31 (95% CI 1.25-1.37; p = 6.88 × 10-31) for major depressive disorder (MDD) and 1.32 (95% CI 1.23-1.40; p = 1.42 × 10-16) for post-traumatic stress disorder (PTSD). There were suggestive inverse associations of morningness chronotype with risk of MDD and schizophrenia (SCZ). Genetically predicted sleep duration was also nominally associated with the risk of bipolar disorder (BD). Conversely, PTSD and MDD were associated with an increased risk of insomnia (OR = 1.06, 95% CI 1.03-1.10, p = 7.85 × 10-4 for PTSD; OR = 1.37, 95% CI 1.14-1.64; p = 0.001 for MDD). A suggestive inverse association of ADHD and MDD with sleep duration was also observed. Our findings provide evidence of potential causal relationships between sleep disturbance and psychiatric disorders. This suggests that abnormal sleep patterns may serve as markers for psychiatric disorders and offer opportunities for prevention and management in psychiatric disorders.

Patients with autism spectrum disorder (ASD) frequently experience sleep disturbance. Genetic mutations in the neuroligin 3 (NLG3) gene are highly correlative with ASD and sleep disturbance. However, the cellular and neural circuit bases of this correlation remain elusive. Here, we found that the conditional knockout of Nlg3 (Nlg3-CKO) in the medial septum (MS) impairs social memory and reduces sleep. Nlg3 CKO in the MS caused hyperactivity of MSGABA neurons during social avoidance and wakefulness. Activation of MSGABA neurons induced social memory deficits and sleep loss in C57BL/6J mice. In contrast, inactivation of these neurons ameliorated social memory deficits and sleep loss in Nlg3-CKO mice. Sleep deprivation led to social memory deficits, while social isolation caused sleep loss, both resulting in a reduction in NLG3 expression and an increase in activity of GABAergic neurons in the MS from C57BL/6J mice. Furthermore, MSGABA-innervated CA2 neurons specifically regulated social memory without impacting sleep, whereas MSGABA-innervating neurons in the preoptic area selectively controlled sleep without affecting social behavior. Together, these findings demonstrate that the hyperactive MSGABA neurons impair social memory and disrupt sleep resulting from Nlg3 CKO in the MS, and achieve the modality specificity through their divergent downstream targets.

Sleep is an essential human function but its regulation is poorly understood. Using accelerometer data from 85,670 UK Biobank participants, we perform a genome-wide association study of 8 derived sleep traits representing sleep quality, quantity and timing, and validate our findings in 5,819 individuals. We identify 47 genetic associations at P  < 5 × 10 −8 , of which 20 reach a stricter threshold of P  < 8 × 10 −10 . These include 26 novel associations with measures of sleep quality and 10 with nocturnal sleep duration. The majority of identified variants associate with a single sleep trait, except for variants previously associated with restless legs syndrome. For sleep duration we identify a missense variant (p.Tyr727Cys) in PDE11A as the likely causal variant. As a group, sleep quality loci are enriched for serotonin processing genes. Although accelerometer-derived measures of sleep are imperfect and may be affected by restless legs syndrome, these findings provide new biological insights into sleep compared to previous efforts based on self-report sleep measures. Quality, quantity and timing of sleep are important factors for overall human health. Here, the authors perform GWAS for sleep traits estimated using wearable accelerometers and identify 47 genetic associations, including 26 novel associations for measures of sleep quality and 10 for nocturnal sleep duration.

In idiopathic Parkinson disease (IPD) sleep disorders are common and may antedate the onset of parkinsonism. Based on the clinical similarities between IPD and Parkinson disease associated with LRRK2 gene mutations (LRRK2-PD), we aimed to characterize sleep in parkinsonian and nonmanifesting LRRK2 mutation carriers (NMC). A comprehensive interview conducted by sleep specialists, validated sleep scales and questionnaires, and video-polysomnography followed by multiple sleep latency test (MSLT) assessed sleep in 18 LRRK2-PD (17 carrying G2019S and one R1441G mutations), 17 NMC (11 G2019S, three R1441G, three R1441C), 14 non-manifesting non-carriers (NMNC) and 19 unrelated IPD. Sleep complaints were frequent in LRRK2-PD patients; 78% reported poor sleep quality, 33% sleep onset insomnia, 56% sleep fragmentation and 39% early awakening. Sleep onset insomnia correlated with depressive symptoms and poor sleep quality. In LRRK2-PD, excessive daytime sleepiness (EDS) was a complaint in 33% patients and short sleep latencies on the MSLT, which are indicative of objective EDS, were found in 71%. Sleep attacks occurred in three LRRK2-PD patients and a narcoleptic phenotype was not observed. REM sleep behavior disorder (RBD) was diagnosed in three LRRK2-PD. EDS and RBD were always reported to start after the onset of parkinsonism in LRRK2-PD. In NMC, EDS was rarely reported and RBD was absent. When compared to IPD, sleep onset insomnia was more significantly frequent, EDS was similar, and RBD was less significantly frequent and less severe in LRRK2-PD. In NMC, RBD was not detected and sleep complaints were much less frequent than in LRRK2-PD. No differences were observed in sleep between NMC and NMNC. Sleep complaints are frequent in LRRK2-PDand show a pattern that when compared to IPD is characterized by more frequent sleep onset insomnia, similar EDS and less prominent RBD. Unlike in IPD, RBD and EDS seem to be not markers of the prodromal stage of LRRK2-PD.

Sleep problems are common in psychotic disorders and are associated with worse quality of life and disease prognosis. Genome-wide association studies (GWAS) have revealed genetic influences for schizophrenia and sleep, but polygenic scores (PGSs) for sleep traits have not been evaluated systematically in patients with psychotic disorders. This study investigated the associations between PGSs for sleep traits (insomnia, PGS ; sleep duration, PGS ; short sleep duration, PGS ; long sleep duration; PGS ), diurnal preference (eveningness, PGS ), and schizophrenia (PGS ) with clinical features of psychotic disorders in the Finnish SUPER study comprising 8,232 patients with psychotic disorders. The measures included self-reported sleep and well-being, cognitive assessments, clozapine use, and functional outcomes. Using FinnGen data of 356,077 individuals, we analyzed the distributions of PGSs in psychotic and bipolar disorders and the general population. PGS associated with more sleep problems and worse well-being (e.g. worse health-related quality of life [β = -0.07, CI = -0.09, -0.05,  < .001]). High PGS is associated with better sleep quality, worse clinical outcomes, and performance in cognitive tests (e.g. more errors in paired-associated learning [β = 0.07, CI = 0.04, 0.09,  < .001]). PGS was higher in affective psychotic and bipolar disorders, while PGS and PGS were higher in schizophrenia as compared with individuals with no psychiatric disorders. Genetic risks for sleep and diurnal preference vary between non-affective psychosis, affective psychosis, and the general population. The findings in this study emphasize the heterogeneity in genetic etiology of the objective features of disease severity and the more subjective measures related to well-being and self-reported measures of sleep.

Bipolar disorder is highly heritable and therefore longitudinal observation of children of affected parents is important to mapping the early natural history. To model the developmental trajectory of bipolar disorder based on the latest findings from an ongoing prospective study of the offspring of parents with well-characterised bipolar disorder. A total of 229 offspring from families in which 1 parent had confirmed bipolar disorder and 86 control offspring were prospectively studied for up to 16 years. High-risk offspring were divided into subgroups based on the parental long-term response to lithium. Offspring were clinically assessed and DSM-IV diagnoses determined on masked consensus review using best estimate procedure. Adjusted survival analysis and generalised estimating equations were used to calculate differences in lifetime psychopathology. Multistate models were used to examine the progression through proposed clinical stages. High-risk offspring had an increased lifetime risk of a broad spectrum of disorders including bipolar disorder (hazard ratio (HR) = 20.89; P = 0.04), major depressive disorder (HR = 17.16; P = 0.004), anxiety (HR = 2.20; P = 0.03), sleep (HR = 28.21; P = 0.02) and substance use disorders (HR = 2.60; P = 0.05) compared with controls. However, only offspring from lithium non-responsive parents developed psychotic disorders. Childhood anxiety disorder predicted an increased risk of major mood disorder and evidence supported a progressive transition through clinical stages, from non-specific psychopathology to depressive and then manic or psychotic episodes. Findings underscore the importance of a developmental approach in conjunction with an appreciation of familial risk to facilitate earlier accurate diagnosis in symptomatic youth.