Genetic risk for insomnia is associated with objective sleep measures in young and healthy good sleepers.

Insomnia disorder (ID) is the second most common neuropsychiatric disorder. Its socioeconomic burden is enormous while diagnosis and treatment are difficult. A novel approach that reveals associations between insomnia genetic propensity and sleep phenotypes in youth may help understand the core of the disease isolated from comorbidities and pave the way for new treatments. We obtained quantitative nocturnal sleep electroencephalogram (EEG) features in 456 participants (18-31y, 49 women). Sleep EEG was recorded during a baseline night following at least 7 days of regular sleep times. We then assessed daytime sleep onset latency in a subsample of N = 359 men exposed to manipulations affecting sleep pressure. We sampled saliva or blood for polygenic risk score (PRS) determination. The PRS for ID was computed based on genome-wide common single nucleotide polymorphism assessments. Participants also completed a battery of behavioral and cognitive tests. The analyses revealed that the PRS for ID was negatively associated with cumulated EEG power in the delta (0.5-4 Hz) and theta (4-8 Hz) bands across rapid eye movement (REM) and non-REM sleep (p ≤ .0026; ß ≥ -0.13) controlling for age, sex and BMI. The PRS for ID was also negatively associated with daytime likelihood of falling asleep (ß = -0.19, p = .0009). Other explorations for associations with non-baseline-nights, cognitive measures, and mood did not yield significant results. These results propose that the need or the ability to fall asleep and to generate slow brain activity during sleep may constitute the core sleep-related risk factors for developing ID.

Variability of sleep stage scoring in late midlife and early old age.

Sleep stage scoring can lead to important inter-expert variability. Although likely, whether this issue is amplified in older populations, which show alterations of sleep electrophysiology, has not been thoroughly assessed. Algorithms for automatic sleep stage scoring may appear ideal to eliminate inter-expert variability. Yet, variability between human experts and algorithm sleep stage scoring in healthy older individuals has not been investigated. Here, we aimed to compare stage scoring of older individuals and hypothesized that variability, whether between experts or considering the algorithm, would be higher than usually reported in the literature. Twenty cognitively normal and healthy late midlife individuals' (61 ± 5 years; 10 women) night-time sleep recordings were scored by two experts from different research centres and one algorithm. We computed agreements for the entire night (percentage and Cohen's κ) and each sleep stage. Whole-night pairwise agreements were relatively low and ranged from 67% to 78% (κ, 0.54-0.67). Sensitivity across pairs of scorers proved lowest for stages N1 (8.2%-63.4%) and N3 (44.8%-99.3%). Significant differences between experts and/or algorithm were found for total sleep time, sleep efficiency, time spent in N1/N2/N3 and wake after sleep onset (p ≤ 0.005), but not for sleep onset latency, rapid eye movement (REM) and slow-wave sleep (SWS) duration (N2 + N3). Our results confirm high inter-expert variability in healthy aging. Consensus appears good for REM and SWS, considered as a whole. It seems more difficult for N3, potentially because human raters adapt their interpretation according to overall changes in sleep characteristics. Although the algorithm does not substantially reduce variability, it would favour time-efficient standardization.

Exploring scoring methods for research studies: Accuracy and variability of visual and automated sleep scoring.

Sleep studies face new challenges in terms of data, objectives and metrics. This requires reappraising the adequacy of existing analysis methods, including scoring methods. Visual and automatic sleep scoring of healthy individuals were compared in terms of reliability (i.e., accuracy and stability) to find a scoring method capable of giving access to the actual data variability without adding exogenous variability. A first dataset (DS1, four recordings) scored by six experts plus an autoscoring algorithm was used to characterize inter-scoring variability. A second dataset (DS2, 88 recordings) scored a few weeks later was used to explore intra-expert variability. Percentage agreements and Conger's kappa were derived from epoch-by-epoch comparisons on pairwise and consensus scorings. On DS1 the number of epochs of agreement decreased when the number of experts increased, ranging from 86% (pairwise) to 69% (all experts). Adding autoscoring to visual scorings changed the kappa value from 0.81 to 0.79. Agreement between expert consensus and autoscoring was 93%. On DS2 the hypothesis of intra-expert variability was supported by a systematic decrease in kappa scores between autoscoring used as reference and each single expert between datasets (.75-.70). Although visual scoring induces inter- and intra-expert variability, autoscoring methods can cope with intra-scorer variability, making them a sensible option to reduce exogenous variability and give access to the endogenous variability in the data.

Does Homeostatic Sleep Pressure Buildup Explain Objective Excessive Daytime Sleepiness in Adults With ADHD? An Exploratory Study.

Background: Excessive daytime sleepiness (EDS) is central in Attention deficit hyperactivity disorder (ADHD) but its causes remain unclear. The aim of this study was to explore objective EDS and homeostatic sleep pressure buildup, evaluated by power theta-alpha frequency (PTAF), in drug-free sleepy adults with ADHD and controls. Methods: Participants were placed during a 36-h period of extended wakefulness under constant routine protocol to strictly control sleep time, sleep duration, and circadian zeitgebers. Results: Eight drug-free sleepy patients with ADHD and 7 matched controls were included. The ADHD group had significantly shorter sleep latency on the Maintenance of Wakefulness Test (MWT) throughout extended wakefulness than the control group. There was no significant difference between the groups in PTAF evolution during extended wakefulness and in kinetic sleep pressure buildup, evaluated by the time constant of saturating exponential function. Limitations: The sample was small, so the findings cannot be generalized. Moreover, psychiatric comorbidities and circadian regulation should be taken into account in future studies. Conclusion: In very controlled conditions, mean sleep latency on the MWT during the whole extended wakefulness was significantly shorter in sleepy patients with ADHD than in control subjects. However, the difficulty to remain awake during soporific circumstances observed in these patients with ADHD cannot be explained by changes in the kinetic of sleep pressure buildup. Clinical Trials Registration: www.clinicaltrials.gov/, Identifier: NCT02217371.

Automatic analysis of single-channel sleep EEG in a large spectrum of sleep disorders.

STUDY OBJECTIVES: To assess the performance of the single-channel automatic sleep staging (AS) software ASEEGA in adult patients diagnosed with various sleep disorders. METHODS: Sleep recordings were included of 95 patients (38 women, 40.5 ± 13.7 years) diagnosed with insomnia (n = 23), idiopathic hypersomnia (n = 24), narcolepsy (n = 24), and obstructive sleep apnea (n = 24). Visual staging (VS) was performed by two experts (VS1 and VS2) according to the American Academy of Sleep Medicine rules. AS was based on the analysis of a single electroencephalogram channel (Cz-Pz), without any information from electro-oculography nor electromyography. The epoch-by-epoch agreement (concordance and Conger's coefficient [κ]) was compared pairwise (VS1-VS2, AS-VS1, AS-VS2) and between AS and consensual VS. Sleep parameters were also compared. RESULTS: The pairwise agreements were: between AS and VS1, 78.6% (κ = 0.70); AS and VS2, 75.0% (0.65); and VS1 and VS2, 79.5% (0.72). Agreement between AS and consensual VS was 85.6% (0.80), with the following distribution: insomnia 85.5% (0.80), narcolepsy 83.8% (0.78), idiopathic hypersomnia 86.1% (0.68), and obstructive sleep disorder 87.2% (0.82). A significant low-amplitude scorer effect was observed for most sleep parameters, not always driven by the same scorer. Hypnograms obtained with AS and VS exhibited very close sleep organization, except for 80% of rapid eye movement sleep onset in the group diagnosed with narcolepsy missed by AS. CONCLUSIONS: Agreement between AS and VS in sleep disorders is comparable to that reported in healthy individuals and to interexpert agreement in patients. ASEEGA could therefore be considered as a complementary sleep stage scoring tool in clinical practice, after improvement of rapid eye movement sleep onset detection.

Regular Caffeine Intake Delays REM Sleep Promotion and Attenuates Sleep Quality in Healthy Men.

Acute caffeine intake can attenuate homeostatic sleep pressure and worsen sleep quality. Caffeine intake-particularly in high doses and close to bedtime-may also affect circadian-regulated rapid eye movement (REM) sleep promotion, an important determinant of subjective sleep quality. However, it is not known whether such changes persist under chronic caffeine consumption during daytime. Twenty male caffeine consumers (26.4 ± 4 years old, habitual caffeine intake 478.1 ± 102.8 mg/day) participated in a double-blind crossover study. Each volunteer completed a caffeine (3 × 150 mg caffeine daily for 10 days), a withdrawal (3 × 150 mg caffeine for 8 days then placebo), and a placebo condition. After 10 days of controlled intake and a fixed sleep-wake cycle, we recorded electroencephalography for 8 h starting 5 h after habitual bedtime (i.e., start on average at 04:22 h which is around the peak of circadian REM sleep promotion). A 60-min evening nap preceded each sleep episode and reduced high sleep pressure levels. While total sleep time and sleep architecture did not significantly differ between the three conditions, REM sleep latency was longer after daily caffeine intake compared with both placebo and withdrawal. Moreover, the accumulation of REM sleep proportion was delayed, and volunteers reported more difficulties with awakening after sleep and feeling more tired upon wake-up in the caffeine condition compared with placebo. Our data indicate that besides acute intake, also regular daytime caffeine intake affects REM sleep regulation in men, such that it delays circadian REM sleep promotion when compared with placebo. Moreover, the observed caffeine-induced deterioration in the quality of awakening may suggest a potential motive to reinstate caffeine intake after sleep.

Heterogeneity in the links between sleep arousals, amyloid-ß, and cognition.

BACKGROUNDTight relationships between sleep quality, cognition, and amyloid-ß (Aß) accumulation, a hallmark of Alzheimer's disease (AD) neuropathology, have been shown. Sleep arousals become more prevalent with aging and are considered to reflect poorer sleep quality. However, heterogeneity in arousals has been suggested while their associations with Aß and cognition are not established.METHODSWe recorded undisturbed night-time sleep with EEG in 101 healthy individuals aged 50-70 years, devoid of cognitive and sleep disorders. We classified spontaneous arousals according to their association with muscular tone increase (M+/M-) and sleep stage transition (T+/T-). We assessed cortical Aß burden over earliest affected regions via PET imaging and assessed cognition via neuropsychological testing.RESULTSArousal types differed in their oscillatory composition in θ (4-8 Hz) and ß (16-30 Hz) EEG bands. Furthermore, T+M- arousals, interrupting sleep continuity, were positively linked to Aß burden (P = 0.0053, R²ß* = 0.08). By contrast, more prevalent T-M+ arousals, upholding sleep continuity, were associated with lower Aß burden (P = 0.0003, R²ß* = 0.13), and better cognition, particularly over the attentional domain (P < 0.05, R²ß* ≥ 0.04).CONCLUSIONContrasting with what is commonly accepted, we provide empirical evidence that arousals are diverse and differently associated with early AD-related neuropathology and cognition. This suggests that sleep arousals, and their coalescence with other brain oscillations during sleep, may actively contribute to the beneficial functions of sleep and constitute markers of favorable brain and cognitive health trajectories.TRIAL REGISTRATIONEudraCT 2016-001436-35.FUNDINGFRS-FNRS Belgium (FRSM 3.4516.11), Actions de Recherche Concertées Fédération Wallonie-Bruxelles (SLEEPDEM 17/27-09), ULiège, and European Regional Development Fund (Radiomed Project).

Alzheimer's disease genetic risk and sleep phenotypes in healthy young men: association with more slow waves and daytime sleepiness.

STUDY OBJECTIVES: Sleep disturbances and genetic variants have been identified as risk factors for Alzheimer's disease (AD). Our goal was to assess whether genome-wide polygenic risk scores (PRS) for AD associate with sleep phenotypes in young adults, decades before typical AD symptom onset. METHODS: We computed whole-genome PRS for AD and extensively phenotyped sleep under different sleep conditions, including baseline sleep, recovery sleep following sleep deprivation, and extended sleep opportunity, in a carefully selected homogenous sample of 363 healthy young men (22.1 years ± 2.7) devoid of sleep and cognitive disorders. RESULTS: AD PRS was associated with more slow-wave energy, that is, the cumulated power in the 0.5-4 Hz EEG band, a marker of sleep need, during habitual sleep and following sleep loss, and potentially with larger slow-wave sleep rebound following sleep deprivation. Furthermore, higher AD PRS was correlated with higher habitual daytime sleepiness. CONCLUSIONS: These results imply that sleep features may be associated with AD liability in young adults, when current AD biomarkers are typically negative, and support the notion that quantifying sleep alterations may be useful in assessing the risk for developing AD.

Non-REM Sleep Characteristics Predict Early Cognitive Impairment in an Aging Population.

Objective: Recent research suggests that sleep disorders or changes in sleep stages or EEG waveform precede over time the onset of the clinical signs of pathological cognitive impairment (e.g., Alzheimer's disease). The aim of this study was to identify biomarkers based on EEG power values and spindle characteristics during sleep that occur in the early stages of mild cognitive impairment (MCI) in older adults. Methods: This study was a case-control cross-sectional study with 1-year follow-up of cases. Patients with isolated subjective cognitive complaints (SCC) or MCI were recruited in the Bordeaux Memory Clinic (MEMENTO cohort). Cognitively normal controls were recruited. All participants were recorded with two successive polysomnography 1 year apart. Delta, theta, and sigma absolute spectral power and spindle characteristics (frequency, density, and amplitude) were analyzed from purified EEG during NREM and REM sleep periods during the entire second night. Results: Twenty-nine patients (8 males, age = 71 ± 7 years) and 29 controls were recruited at T0. Logistic regression analyses demonstrated that age-related cognitive impairment were associated with a reduced delta power (odds ratio (OR) 0.072, P < 0.05), theta power (OR 0.018, P < 0.01), sigma power (OR 0.033, P < 0.05), and spindle maximal amplitude (OR 0.002, P < 0.05) during NREM sleep. Variables were adjusted on age, gender, body mass index, educational level, and medication use. Seventeen patients were evaluated at 1-year follow-up. Correlations showed that changes in self-reported sleep complaints, sleep consolidation, and spindle characteristics (spectral power, maximal amplitude, duration, and frequency) were associated with cognitive impairment (P < 0.05). Conclusion: A reduction in slow-wave, theta and sigma activities, and a modification in spindle characteristics during NREM sleep are associated very early with a greater risk of the occurrence of cognitive impairment. Poor sleep consolidation, lower amplitude, and faster frequency of spindles may be early sleep biomarkers of worsening cognitive decline in older adults.

Sleep spindles may predict response to cognitive-behavioral therapy for chronic insomnia.

BACKGROUND: While cognitive-behavioral therapy for insomnia constitutes the first-line treatment for chronic insomnia, only few reports have investigated how sleep architecture relates to response to this treatment. In this pilot study, we aimed to determine whether pre-treatment sleep spindle density predicts treatment response to cognitive-behavioral therapy for insomnia. METHODS: Twenty-four participants with chronic primary insomnia participated in a 6-week cognitive-behavioral therapy for insomnia performed in groups of 4-6 participants. Treatment response was assessed using the Pittsburgh Sleep Quality Index and the Insomnia Severity Index measured at pre- and post-treatment, and at 3- and 12-months' follow-up assessments. Secondary outcome measures were extracted from sleep diaries over 7 days and overnight polysomnography, obtained at pre- and post-treatment. Spindle density during stage N2-N3 sleep was extracted from polysomnography at pre-treatment. Hierarchical linear modeling analysis assessed whether sleep spindle density predicted response to cognitive-behavioral therapy. RESULTS: After adjusting for age, sex, and education level, lower spindle density at pre-treatment predicted poorer response over the 12-month follow-up, as reflected by a smaller reduction in Pittsburgh Sleep Quality Index over time. Reduced spindle density also predicted lower improvements in sleep diary sleep efficiency and wake after sleep onset immediately after treatment. There were no significant associations between spindle density and changes in the Insomnia Severity Index or polysomnography variables over time. CONCLUSION: These preliminary results suggest that inter-individual differences in sleep spindle density in insomnia may represent an endogenous biomarker predicting responsiveness to cognitive-behavioral therapy. Insomnia with altered spindle activity might constitute an insomnia subtype characterized by a neurophysiological vulnerability to sleep disruption associated with impaired responsiveness to cognitive-behavioral therapy.

Sleep spindles predict stress-related increases in sleep disturbances.

BACKGROUND AND AIM: Predisposing factors place certain individuals at higher risk for insomnia, especially in the presence of precipitating conditions such as stressful life events. Sleep spindles have been shown to play an important role in the preservation of sleep continuity. Lower spindle density might thus constitute an objective predisposing factor for sleep reactivity to stress. The aim of this study was therefore to evaluate the relationship between baseline sleep spindle density and the prospective change in insomnia symptoms in response to a standardized academic stressor. METHODS: Twelve healthy students had a polysomnography recording during a period of lower stress at the beginning of the academic semester, along with an assessment of insomnia complaints using the insomnia severity index (ISI). They completed a second ISI assessment at the end of the semester, a period coinciding with the week prior to final examinations and thus higher stress. Spindle density, amplitude, duration, and frequency, as well as sigma power were computed from C4-O2 electroencephalography derivation during stages N2-N3 of non-rapid-eye-movement (NREM) sleep, across the whole night and for each NREM sleep period. To test for the relationship between spindle density and changes in insomnia symptoms in response to academic stress, spindle measurements at baseline were correlated with changes in ISI across the academic semester. RESULTS: Spindle density (as well as spindle amplitude and sigma power), particularly during the first NREM sleep period, negatively correlated with changes in ISI (p < 0.05). CONCLUSION: Lower spindle activity, especially at the beginning of the night, prospectively predicted larger increases in insomnia symptoms in response to stress. This result indicates that individual differences in sleep spindle activity contribute to the differential vulnerability to sleep disturbances in the face of precipitating factors.