Sleep

Study ObjectivesIdiopathic hypersomnia (IH) is a central nervous system hypersomnia frequently accompanied by autonomic symptoms, yet objective physiological data are limited. We sought to characterize autonomic nervous system (ANS) dysfunction in IH using nocturnal heart rate variability (HRV) and diurnal autonomic reflex testing (ART), compared to individuals with type 1 narcolepsy (NT1) and healthy controls (HCs). MethodsTwenty-four adults with IH, 10 with NT1, and 14 HCs underwent overnight video polysomnography with HRV analyses in time and frequency domains during stable slow-wave sleep and REM sleep. Comprehensive ART included sympathetic adrenergic (head-up tilt (HUT), Valsalva BP responses), parasympathetic cardiovagal (HRV to deep breathing, Valsalva ratio), and sudomotor (Q-Sweat) measures. ResultsIH participants were predominantly female, with over half reporting long sleep duration. Compared to NT1 and HC, participants with IH demonstrated a greater magnitude of orthostatic tachycardia on tilt ({Delta}HR 41.0 {+/-} 16.3 vs. 26.3 {+/-} 9.3 vs. 30.8 {+/-} 9.3 bpm, p = 0.0086), as well as frequent sudomotor dysfunction (64.3%). IH participants demonstrated greater nocturnal and REM HR with reduced parasympathetic indices during REM, indicating diminished vagal modulation compared with HCs ConclusionsIH is characterized by a distinct pattern of autonomic dysfunction, including pronounced orthostatic tachycardia, frequent sudomotor abnormalities, and reduced parasympathetic activity during sleep. These findings provide objective physiological evidence of ANS involvement in IH and delineate features that distinguish IH from NT1 and HCs.

Actigraphy is widely used for long-term sleep monitoring, but established sleep-wake scoring algorithms often require parameter tuning, which is commonly performed manually and can reduce reproducibility. In this study, a grid-search-based calibration framework is presented for established actigraphy algorithms and evaluate whether it can serve as a practical alternative to manual tuning. The method was evaluated using two datasets: a multi-subject polysomnography-validated actigraphy dataset and a self-collected dual-device dataset. In the polysomnography-validated dataset, grid-search optimization produced performance patterns similar to manual parameter selection, while slightly improving detection of sleep onset and sleep offset and yielding modest gains in wake-sensitive metrics. In the dual-device dataset, consensus and majority voting were useful for reducing the influence of brief wake episodes occurring within the main sleep period, including micro-awakenings that can fragment sleep predictions across individual algorithms. Overall, these findings show that grid-search can replace manual parameter tuning with a more explicit and reproducible procedure while providing small improvements in sleep timing estimation and benefiting ensemble-based handling of within-sleep wakefulness.

Excessive daytime sleepiness (EDS) is a heterogeneous phenotype with little known of its genetic basis. Large-scale genome-wide association studies (GWAS) have reported genomic loci associated with EDS, though since most of these are non-coding, the causal gene(s) underlying the association are not known. Additionally, the cell types in which these genes exert their effects on sleep have not been functionally explored in vivo. Here, we employed a chromatin-based variant-to-gene mapping approach to first implicate candidate effector genes at EDS GWAS loci in human-derived neural and glial cell lines. Subsequent cell type-specific RNAi knockdown of orthologous genes using neural and glial GAL4 drivers in Drosophila confirmed cell-specific regulation of sleep by these GWAS-implicated effector genes. Among these, ruby (ortholog to AP3B2), a component of the AP-3 vesicular trafficking complex emerged as a robust sleep regulator. Targeted knockdown in flies localized ruby function to astrocyte-like glia, where loss of ruby increased sleep duration. The conserved role of ruby/ ap3b2 was validated in zebrafish where CRISPR-mediated loss increased daytime sleep. Together, these findings show that physical variant-to-gene mapping predicted cell-type-specific gene function for complex sleep traits and revealed ruby/AP3B2 as a conserved glial regulator of sleep and arousal. This work provides a generalizable framework for connecting non-coding GWAS variants and their corresponding effector genes to identify novel and highly conserved regulators of sleep.

ObjectivesChronic insomnia (INS) is particularly prevalent in older adults and females. Sex-and age-related differences in neurophysiological markers of sleep quality (sleep spindles and slow-wave activity [SWA]) may underlie differential vulnerability to INS. This study investigated the effects of sex and insomnia on spindle and SWA beyond aging, to better understand the mechanistic differences contributing to the higher prevalence of INS in females. MethodsAfter a habituation night, one night of sleep assessed with polysomnography was analyzed in 222 adults (aged 18-82) including 119 INS (71% female) and 103 healthy sleepers (HS; 61% female). Spindle density, slow oscillation (SO) density, relative sigma power and SWA were derived during NREM sleep. Age, group, sex, and group-by-sex interactions were examined, with age as a covariate. ResultsAge, insomnia, and sex each contributed uniquely to NREM oscillatory activity. INS primarily reduced spindle and SO density, while sex accounted for differences in SWA. While SWA was higher in females overall, sex differences were not significant within the INS or HS groups. Female INS reported highest rates of insomnia severity as well as lower sigma power than males in the INS group. Spindle and SO density deficits were also present in female INS relative to female HS, as well as male INS relative to male HS. ConclusionsThe combination of reduced sigma power in females with insomnia relative to their male counterparts, as well as less spindle and SO density compared to female healthy sleepers may contribute to greater insomnia severity in females. Statement of SignificanceInsomnia is a growing public health concern that is more commonly reported in females, yet the neural mechanisms underlying this sex difference remain poorly understood. Our findings suggest that specific markers of sleep quality are disproportionately disrupted in females with insomnia, potentially contributing to greater vulnerability and symptom severity. These results provide new insight into how sex influences the neurophysiology of insomnia disorder and identify oscillatory markers that could serve as targets for personalized interventions. Future research should investigate whether these alterations represent persistent dysfunction or reversible changes, which could advance understanding of the biological basis of insomnia and inform strategies to improve sleep health in at-risk populations.

Background Narcolepsy is a rare, lifelong neurological disorder that often begins in childhood or adolescence. Diagnosis is frequently delayed because current diagnostic testing relies on specialist in-patient sleep investigations: overnight polysomnography (PSG) followed by a multiple sleep latency test (MSLT), interpreted according to International Classification of Sleep Disorders criteria (ICSD-3-TR). These investigations are expensive, labour intensive, and available in a limited number of centres, contributing to delays and inequity of access. Automated analysis of sleep-stage probabilities (hypnodensity) using neural networks has shown promising diagnostic performance in research cohorts but still requires hospital-based PSG acquisition. The Dreem 3 headband (DH) is a comfortable, dry-montage EEG device designed for home use. Combined with its proprietary machine learning classification of sleep stages, it may offer accurate ambulatory sleep physiology assessments and support clinical decision making. Methods This was a single-centre, prospective, observational study recruiting 60 participants aged 10 to 35 years undergoing investigation for hypersomnolence within GSTT sleep services and scheduled for PSG and MSLT as part of routine care. Exclusion criteria included physician-diagnosed medical or psychiatric disorder that could independently account for excessive daytime sleepiness; and/ or regular use of prescribed or recreational medication known to affect sleep architecture. Participants first wore the DH at home for five weeknights, followed by a continuous 48-hour weekend recording using two devices in rotation. They then underwent routine in-patient PSG and MSLT. PSG and MSLT were interpreted according to ICSD-3 by an experienced sleep physician and a final diagnosis determined by a sleep physiology consultant. The primary outcome is accuracy of ambulatory DH-based assessment of sleep physiology and subsequent diagnosis of sleep disorders. We evaluate proprietary and in-house developed machine learning methods to detect SOREM epochs and predict narcolepsy diagnosis from PSG, PSG+MSLT and DH data. All algorithmic outcomes will be compared to clinical outcomes derived from current clinical standard of care. Discussion This study will provide proof-of-concept evidence for a home-based wearable EEG approach to narcolepsy diagnosis. Patient and public involvement work with young people with confirmed narcolepsy indicates high acceptability of the DH protocol: in a survey of ten young people, eight reported they would be willing to wear a sleep headband nightly at home for five days (two were unsure), and seven reported they would be willing to wear it continuously for 48 hours over a weekend (two were unsure; one said no). These findings informed the decision to restrict continuous wear to the weekend, reflecting feedback that daytime wear during school or work hours would be unacceptable. If validated, this approach could reduce delays to diagnosis, improve equity of access, and support development of a subsequent multicentre study. Trial registration IRAS Project ID: 321547. Registered October 2022. Recruitment was completed on 30 January 2026.

Objective: The narcolepsy type 1 (NT1) phenotype severity is heterogeneous, and the disease course is largely unknown. The 2009-10 H1N1-(Pandemrix(R))-vaccinations were followed by increased numbers of possibly more severe post-H1N1 NT1 cases but long-term prospective data on large, vaccinated cohorts are missing. Methods: 130 consecutive post-H1N1 NT1 cases (113/130 Pandemrix(R) -vaccinated) were prospectively followed up after approximately 5.5 years. Epworth Sleepiness Scale (ESS), cataplexy, hypnagogic hallucinations, sleep paralysis, PSG, MSLT, and BMI were evaluated. Phenotype severity predictors (hypocretin-1 deficiency severity <40 vs. 40-150 pg/ml; Pandemrix(R)- vaccination; disease duration) were tested in age and sex-adjusted multivariable regressions. Results: From baseline to follow-up, phenotype severity overall improved (milder symptoms, higher mean MSLT sleep latency (SL) and fewer SOREMPs, all p<0.001). Follow-up phenotype severity was strongly predicted by the same baseline measures. Females had worse ESS and cataplexy, men had higher BMI, and young individuals had lower mean MSLT SL and more SOREMPs. Severe hypocretin deficiency (<40 pg/ml) predicted baseline PSG SOREMPs and lower MSLT SL. Vaccinated individuals had more severe baseline PSG/MSLT measures but greater long-term symptom improvement, and vaccination no longer predicted PSG/MSLT severity at follow-up. Conclusion: The best prognostic factor for long-term NT1 phenotype severity is the earlier phenotype severity. Hypocretin deficiency severity also predicts parts of short-term but not long-term phenotype severity. Pandemrix(R)-vaccination is associated with initially more severe phenotype but larger long-term improvement i.e. a different clinical course than in unvaccinated NT1, although medication effects cannot be excluded. Our findings underscore heterogeneity in NT1 phenotype and disease trajectories.

Chronic short sleep (CSS) is an emerging public health issue that frequently begins in adolescence and is common among healthcare professionals and others engaged in shift work. Epidemiological studies associate CSS and sleep disruption with metabolic disorders, cardiovascular disease, cognitive decline, and heightened Alzheimers disease risk. Building on our prior findings that sleep deprivation perturbs proteostasis and activates endoplasmic reticulum (ER) stress pathways, we investigated the long-term consequences of CSS in young adult wild-type mice over the course of one year. Mice exposed to CSS displayed impaired cognition in hippocampal dependent tasks by 28 weeks of age, indicating emerging memory deficits. At the molecular level, CSS disrupted hippocampal proteostasis--particularly protein folding processes--and triggered ER stress and activation of the unfolded protein response (UPR). Importantly, disrupted proteostasis preceded the behavioral decline, with diminution of the key chaperone and UPR regulator BiP occurring at 20-22 weeks of age. CSS also increased markers of cellular stress and neuroinflammation while reducing the expression of proteins associated with memory function. Age also seemed to be a cellular stressor, causing a longitudinal increase in UPR, ISR, and neuroinflammation markers. Together, these results indicate that both chronic short sleep and age compromise proteostasis and promote neuroinflammation, contributing to progressive cognitive dysfunction.

Cannabis use is an increasingly common therapeutic for a variety of chronic diseases. In addition, people with sleep problems may self-medicate using cannabis products. However, genetic architecture of cannabis use and its shared genetic predispositions with sleep traits has not been systematically examined. We performed a meta-analysis of cannabis use within the All of Us and UK Biobank cohorts, consisting of 152,807 cases and 220,272 controls. Our meta-analysis identified 39 independent loci, including the previously reported CADM2 locus associated with cannabis use and replicating previous work. Additionally our associations include neuronal and sleep-regulating genes such as HTR1A, RAI1, SLC39A8, and NCAM1. Moreover, tissue-specific analyses revealed that the genetic architecture of cannabis use is heavily enriched within the central nervous system and specific brain cell types. In addition, we observed significant positive genetic correlations with clinical insomnia, insomnia-related medication usage, and objectively measured nighttime physical activity, alongside negative correlations with morningness chronotype and daytime activity. Fine-mapping and colocalization analyses identified shared genetic signals between cannabis use and clinical insomnia including a near-perfect colocalization at SLC39A8 and CADM2. Together, these results highlight the shared genetic risk between cannabis use and sleep disorders. Additionally, our findings indicate the importance of investigating the genetic effects of cannabis use as its use becomes more widespread, both recreationally and medicinally.

Neuroligin-3 (NLGN3) was first identified as a risk gene associated with autism spectrum disorder (ASD). The initial variant, p.R451C, associating NLGN3 with ASD has been heavily investigated, yet little is known about the functional consequences of other NLGN3 variants. Furthermore, while most of the identified variants are present in males with maternally inherited variants from unaffected mothers, several de novo variants were observed in females, suggesting a possible functional difference between de novo and maternally inherited variants. To address the functional consequences of NLGN3 variants in vivo, we generated transgenic Drosophila models corresponding to one de novo variant (p.R175W) identified in one female proband, and two maternally inherited variants (p.R451C and p.R597W) identified in male probands. In Drosophila, loss of the fly homolog, Nlg3, altered sleep patterns, synaptic architecture, and vesicle dynamics, which were rescued by the expression of the human NLGN3Ref allele. When comparing the variants, the de novo p.R175W variant and the maternally inherited p.R451C variant altered synapse morphology and sleep patterns, with minimal effects on vesicle dynamics, and the p.R597W variant altered sleep and vesicle dynamics with minimal impact on synapse morphology. Using overexpression models, human NLGN3Ref altered sleep patterns and synaptic morphology. Moreover, the p.R175W variant exacerbated sleep phenotypes, and the p.R175W and p.R451C variants exacerbated synapse morphology phenotypes. Together, our findings suggest that de novo NLGN3 variants identified in females are likely gain-of-function, while maternally inherited variants have mixed loss-and gain-of-function effects. Moreover, the location of the variants may contribute to the distinct functional differences we observed. Some NLGN3 variants disrupt synaptic development, while other variants alter synaptic function, suggesting that NLGN3 variants have differential effects. These functional differences may provide insight into the heterogeneity of individuals with ASD. Author SummaryAutism spectrum disorder (ASD) is a common neurodevelopmental disorder. Mutations in the Neuroligin-3 (NLGN3) gene are associated with ASD but very few of these mutations have been characterized in animal models. Most of these mutations affect male individuals who maternally inherited their genetic mutation; however, more rarely female individuals may present with a genetic mutation that was not identified in either of the parents. Here, we utilized the fruit fly model to investigate how three different mutations, one mutation identified in a female and two mutations identified in males, affect the flys behavior and synapse development. We identified altered sleep patterns in some of our mutants which is consistent with sleep disturbances being highly comorbid with ASD. Additionally, we identified alterations in synapse development and function which is consistent with the role of NLGN3 in synapse formation and maturation. Together, our findings support that NLGN3 is important for regulating the synapse and mutations in this gene can alter its function. However, different mutations can have differential effects. This demonstrates the need to assess multiple variants simultaneously because each variant may have distinct functional significances.

Actigraphy is a non-invasive and cost-effective method for monitoring behavioral rhythms under real-world conditions by collecting time-resolved measurements of locomotor activity, light exposure, and temperature. Although several open-source packages support specific aspects of actigraphy analysis, aspects such as preprocessing, metric calculation, and mathematical modeling are often distributed across separate software packages, limiting interoperability and increasing programming overhead. Here we introduce circStudio, a Python package that unifies actigraphy data processing and mathematical modeling of circadian rhythms within a single framework. Built from the pyActigraphy codebase and integrating circadian models from the Arcascope circadian package, circStudio provides flexible preprocessing tools, support for multiple actigraphy file formats through adaptor classes, standalone functions for computing commonly used actigraphy metrics, and implementations of several mathematical models of circadian rhythms. The package enables users to move efficiently from raw wearable data to physiologically interpretable circadian outputs. Ultimately, circStudio aims to facilitate reproducible workflows and to provide a flexible foundation for research applications across circadian biology, sleep science, and digital health.

Abstract Background: While total physical activity is a recognized modifier of cancer risk, accelerometer-derived digital phenotyping enables high-resolution mapping of circadian behavior. Whether these multidimensional patterns comprising step counts, sleep, physical activity, circadian rhythmicity, and light exposure independently influence the risk of incident colorectal cancer (CRC) has not been comprehensively evaluated Methods: We performed an exposure-wide association study (ExWAS) of 224 accelerometer-derived metrics among 95,050 UK Biobank participants who were free of CRC at accelerometry. To comprehensively define circadian rhythm patterns, we systematically categorized these metrics into five core behavioral domains: step counts, sleep architecture, physical activity bouts, circadian rhythmicity, and light exposure. Hazard ratios (HRs) and 95% confidence intervals were estimated using Cox proportional hazards models with age as the underlying timescale. Results: During a median follow-up of 8.5 years, 775 participants developed CRC (503 colon; 269 rectal). In minimally adjusted models, 121 metrics showed nominal significance (31 for overall CRC, 89 for colon, and 1 for rectal cancer). Protective associations were predominantly observed for metrics characterizing activity intensity and bout structure; notably, higher mean acceleration during 5-10 minute bouts of moderate-to vigorous physical activity was associated with reduced CRC risk (HR 0.88 per SD). In contrast, no metrics within the defined sleep or light exposure domains reached nominal significance. These associations attenuated substantially following progressive adjustment for lifestyle and metabolic covariates, suggesting potential confounding or shared biological pathways. Conclusions: Our findings identified specific behavioral phenotypes within a multidimensional framework of circadian rhythm, including step counts, physical activity intensity, and bout structure, as being associated with CRC risk. However, the marked attenuation of signals after multivariable adjustment suggests these markers may not serve as independent predictors. These results underscore the complexity of multidimensional circadian digital biomarkers and necessitate independent replication to clarify their utility in cancer risk stratification.

Deep sleep is widely considered to be the most recuperative component of sleep restoration. Accordingly, a positive relationship between naturally occurring deep sleep and function (e.g., cognitive performance) is often assumed. However, this assumption warrants closer examination--particularly given the rise of sleep tracking that emphasizes traditional sleep metrics and their implied predictive value. We present evidence that while clinical deep sleep scoring provides no predictive value, slow-wave activity (SWA) exhibits a paradoxical association with both improved and worsened neurobehavioral fatigue following sleep deprivation. Specifically, we found that SWA-based models account for approximately 50-60% of the inter-individual variance in recovery from sleep deprivation. Remarkably, when regressed against recovery from sleep deprivation, SWA during the baseline sleep night showed a negative association (normalized {beta} = (-)0.5, p = 0.001) while in the same model SWA during the subsequent wakefulness period showed an opposite positive association (normalized {beta} = 0.5, p = 0.001). Furthermore, although the group-averaged SWA while behaviorally awake increased with impairment across the sleep deprivation period, individual-level data revealed an inverse relationship: individuals more resilient to sleep deprivation exhibited greater SWA in-between mental test sessions and less corresponding impairment during wakefulness suggestive of a protective effect. These findings identify a Deep Sleep Dual Indeterminacy Problem -- simultaneous measurement and causal indeterminacy -- that explains why clinical sleep staging fails as a functional biomarker across a wide range of outcomes, and provide a principled framework for next-generation sleep metrics grounded in continuous electrophysiology and temporal modeling.

An increasing number of epidemiological and experimental studies have demonstrated a bidirectional relationship between mood disorders and the circadian system, with disrupted circadian rhythms contributing to depressive states, and their restoration playing a key role in antidepressants effects. In this context, we sought to examine whether key molecular targets of antidepressants exhibit diurnal regulatory patterns. Naive adult male and female C57BL/6 mice were euthanized at 3-hour intervals beginning at Zeitgeber Time 0 (ZT0), and hippocampal (HC) and medial prefrontal cortex (mPFC) tissues were collected for RT-qPCR and western blot analyses. We observed statistically significant diurnal rhythmicity in all analyzed transcripts (cFos, Arc, Nr4a1, Dusp1, Dusp5, and Dusp6) in both HC and mPFC samples, with peak expression occurring during the dark (active) phase (ZT15-18). Phosphorylation levels of TrkBY816 (tropomyosin-related kinase) and GSK3{beta}S9 (glycogen synthase kinase 3{beta}) also showed periodic rhythmicity, peaking during the light (inactive) phase. Levels of p-ERK2T185/Y187 (extracellular-signal regulated kinase) did not display rhythmicity, but peaked during the light phase in the HC, especially in males. Collectively, these findings demonstrate that antidepressant targets are subject to diurnal regulation, highlighting the importance of integrating circadian biology and time-of-day as relevant variables in the development of translationally relevant antidepressant research. HighlightsO_LIKey molecular targets of antidepressants exhibit diurnal regulation in adult mice C_LIO_LIDiurnal patterns were conserved across targets, sexes, and brain regions (HC&PFC) C_LIO_LIcFos, Arc, Nr4a1, Dusp1,5,6 mRNAs display peak expression during the dark phase C_LIO_LITrkBY816 and GSK3{beta}S9 phosphorylation peak during the light (inactive) phase C_LIO_LIAntidepressant mechanisms may be linked with circadian and sleep-wake dynamics C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/716906v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1e65e60org.highwire.dtl.DTLVardef@13e302corg.highwire.dtl.DTLVardef@1ccc25forg.highwire.dtl.DTLVardef@1ed10d3_HPS_FORMAT_FIGEXP M_FIG C_FIG

Study objectives Consumer sleep technologies (CSTs) enable low-burden longitudinal sleep monitoring, and their output measures are often interpreted as equivalent to polysomnography (PSG) measures. We applied a measurement reliability-aware approach to determine whether CST-derived 'sleep' measures (1) are interchangeable or device-specific, (2) can reliably assess trait-like sleep characteristics of an individual, (3) can be reduced to latent principal components of sleep, and (4) can be used for classification and biomarker discovery. Methods Data from 74 older adults (20 people living with dementia [PLWD]) were collected at-home (upto 14 nights; Total=752nights) using four tools simultaneously: research-grade actigraphy (Axivity), a wearable (Withings Watch), a nearable (Withings Sleep Analyzer) and Sleep Diary, followed by one in-lab PSG assessment. We used repeated-measures correlation analyses, intraclass correlation coefficients (ICC), principal component analysis (PCA) and binary classification models to address our objectives. Results Single-night between-device correlations and correlations with PSG were moderate (0.3[&le;]r<0.7) for some duration- and timing-related measures, but other associations were weak (r<0.3). Seventy-one percent of sleep measures reached acceptable reliability (ICC[&ge;]0.7) within seven nights of aggregation, but the required aggregation window varied across measures, tools and between PLWD and Controls. Reliability-filtered PCA yielded stable and interpretable principal components, but Duration was the only component showing moderate between-device association. Principal components were successfully used to classify PLWD vs Controls but feature importance varied across devices. Conclusions Aggregation of CST derived measures across 7-14 nights, yielded reliable measures, most of which were device-specific, with duration being the only essential aspect transferable between devices.

BackgroundThe mechanisms underpinning associations between sleep and psychiatric conditions are poorly understood, partly due to challenges with longitudinal sleep studies outside the laboratory. Children and young people with rare genetic conditions caused by micro-deletions or -duplications (Copy Number Variants or CNVs) have increased risk of disrupted sleep and poorer neurodevelopmental (ND) outcomes. The Sleep Detectives study aims to investigate this by tracking behavioural and neurophysiological signatures of sleep health in young people with ND risk or ND-CNVs. To optimally achieve this, we have worked with families with ND-CNVs and charity partners to co-design our tools, methods, study protocol, and materials. MethodWe established a Lived Experience Advisory Group (LEAP) with nine parents and 13 children and young people with ND-CNVs, alongside representatives of UK charities Max Appeal and Unique. Together, the research team and LEAP co-designed two in-person family workshops in which we collected feedback on the acceptability of sleep monitoring devices, the design of bespoke cognitive tasks, and overall study protocol. Informal interviews and surveys were conducted with LEAP members and researchers, to enable the team to reflect and learn from their Patient/Public Involvement (PPI) experiences. ResultsKey outputs included pre-workshop invitation and briefing materials and insights that iteratively refined the main study design, including the need for flexibility to increase accessibility, selection of sleep devices, customisation of cognitive tasks, and choice of language in documents. The PPI process was highly valued by LEAP members, workshop attendees, and the research team. One investigator described the PPI work as "reinvigorating my love of research by helping me focus on science that matters". Participating families also established peer support networks. ConclusionsInvolving families affected by ND-CNVs in co-designing the Sleep Detectives study maximised opportunities for acceptability, accessibility and scalability. The research team gained inspiration and deeper understanding of the impact of ND-CNVs on families. Families gained awareness about research, established connections with each other and peer support, and were enthusiastic about future research involvement. This experience empowered families to engage more deeply with the research process and helped the PPI work to be more impactful and inclusive. Plain English summaryChildren and young people with rare genetic conditions caused by small deletion or duplication of genetic material are more likely to experience sleep difficulties such as insomnia, restless sleep, and tiredness. They also show an increased likelihood of neurodevelopmental conditions such as learning disability and autism, and mental health issues such as anxiety. The Sleep Detectives team wanted to explore how these genetic conditions affect childrens sleep, cognition and psychiatric health. To make sure that the project design was well suited to the children and young people that would be invited to participate, the team worked closely with families to design the study. Parents and caregivers of affected children and young people were invited to join a Lived Experience Advisory Panel (LEAP), together with charity representatives and Sleep Detective researchers, to co-design two hands-on workshops, and advise on study design. Children and young people and parents/caregivers attending the workshops tried out and provided feedback on tools and devices that the research team were developing. They also advised on the arrangements and support families might need whilst taking part, and on the study protocol. This collaborative approach helped ensure the study design was optimally suited for the recruitment and participation of children and young people and their families. This report documents our public involvement work for the Sleep Detectives study, illustrating the difference the partnership between researchers and families has made to the project, and the wider benefits for all concerned.

Background: Peri-lead edema (PLE) occurs in up to 15% of Deep Brain Stimulation (DBS) cases, can cause morbidity, and its etiology remains unknown. We hypothesized that PLE represents a secondary brain injury modulated by hypoxemia, and that patients with obstructive sleep apnea (OSA) are at elevated risk. Methods: We conducted a retrospective case-control study of 121 Parkinson's disease (PD) patients undergoing DBS at a single center (2019-2024). PLE severity was quantified by CT volumetric segmentation and Hounsfield unit (HU) measures. Perioperative SpO2 and PaO2 were recorded. Polysomnography (PSG) was available in 26 patients; and the REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ) was administered retrospectively. Results: Symptomatic PLE occurred in 12 patients (9.9%), with onset at 3.5 (2-9) days postoperatively. PLE patients had higher body mass index (p = 0.022) and higher OSA prevalence (75% vs. 30%; p = 0.002). Perioperative SpO2 was lower in the PLE group in both the operating room and post-anesthesia care unit (PACU; p < 0.05); PaO2 was lower in the PACU (p = 0.037). In the PSG subgroup, REM Sleep Behavior Disorder (RBD) incidence was lower in PLE patients (20% vs. 60%; unadjusted p = 0.048), and PLE severity correlated significantly with sleep-related hypoxemia and respiratory indices. RBDSQ scores were positively associated with edema density (normalized HU: rho = 0.86, p = 0.024). Conclusions: OSA and perioperative hypoxemia are associated with symptomatic PLE following DBS, while RBD appears protective. Preoperative sleep evaluation and optimized perioperative airway management warrant prospective investigation as PLE prevention strategies.

Abstract Background Insomnia is a major public health problem affecting an estimated 852 million adults worldwide. Current pharmacological treatments, including benzodiazepines and Z-drugs, carry serious risks of dependency, cognitive impairment, and adverse events. These limitations have driven growing interest in complementary and alternative therapies, particularly herbal sedatives, which are perceived as natural and safer. However, evidence on their safety and efficacy remains insufficient and patchy. Objective: This review evaluated the effectiveness of lesser known herbal sedatives for insomnia. Methods The protocol was registered with PROSPERO (CRD420251101795). Eligibility was defined using the PICO framework: Population: adults aged [&ge;]18 years with insomnia; Interventions: Passiflora incarnata, Hawthorn, Melissa officinalis, Chamomile, Viola odorata, Nelumbo nucifera, Rhodiola rosea, and Eschscholtzia californica. Comparators: placebo or usual care; Primary and Secondary Outcomes: sleep quality (Pittsburgh Sleep Quality Index, Insomnia Severity Index, Epworth Sleepiness Scale), sleep duration, and sleep latency. Databases and registers were searched from January 2005 to July 2025. Randomized controlled trials, nonrandomized controlled trials, clinical trials, and observational studies were included. Five reviewers independently screened studies. Data extraction used a structured Excel spreadsheet. Risk of bias was assessed using RoB 2.0 for randomized trials and ROBINS-I V2 for nonrandomized studies. Random-effects meta-analyses (DerSimonian and Laird) were conducted in RevMan. Narrative synthesis followed SWiM guidelines. Results From 1,294 records, 32 studies met eligibility criteria. Meta-analysis of 23 RCTs demonstrated a statistically significant pooled effect favouring herbal sedatives (SMD -0.77, 95% CI -1.14 to -0.40, p=0.0001), with substantial heterogeneity (I square=92%). Subgroup analysis showed larger effects for chamomile (SMD -1.06) and Melissa officinalis (SMD -0.66). Most RCTs had high overall risk of bias; nonrandomized studies predominantly had critical risk of bias. Conclusions This systematic review provides preliminary evidence that several herbal sedatives, particularly chamomile and Melissa officinalis, may improve insomnia-related outcomes. However, methodological weaknesses, high risk of bias, and substantial heterogeneity limit evidence strength. Future research requires standardized extracts, large multicentre RCTs, and extended follow-up.

BackgroundGrowing evidence suggests that sleep plays an important role in PTSD outcomes, potentially due to its influence on emotional memory consolidation, though these mechanisms remain unknown. This study sought to test the hypotheses that sleep neurophysiology, PTSD status, and sex moderates the degree to which the late positive potential (LPP) mediates memory accuracy for affective visual stimuli. MethodsN = 39 participants (18 female) viewed 75 negative and 75 neutral IAPS images while EEG was recorded. After viewing the images, participants took a two-hour long nap which was followed by a memory assessment. Memory accuracy was measured using d = Z(hit rate) - Z(false alarm rate), where hit rate refers to the proportion of images seen during the memory assessment that are correctly identified as being previously seen, false alarm rate refers to the proportion of images seen during the memory assessment that are incorrectly identified as being previously seen, and Z() is the inverse cumulative distribution function of the standard normal distribution function. ResultsThe early (300 - 1000 ms) and late (1000 - 1500 ms) LPP mediated enhanced discrimination accuracy for emotional compared to neural stimuli (d) (ps < 0.001). The association between the late LPP and d was moderated by sleep such that the association was stronger when participants spent proportionately more time in N3 and REM (p = 0.02). The differences in reactivity between emotional and neutral images for both the early and late LPP were attenuated in PTSD+ individuals vs. controls (ps < 0.001). Despite mediation results showing greater d for emotional compared to neutral stimuli, women showed overall worse memory accuracy for negative compared to neutral stimuli (p < 0.001) whereas men showed no difference (p = 0.64). ConclusionsN3 and REM sleep play a critical role for memory of stimuli that produce large and sustained neural responses. PTSD is marked by a diminished ability to distinguish between negative and neutral information. More research is critical to understand sex effects on emotional memory.

Importance: Sleep-wake disturbances in midlife are common and potentially modifiable contributors to long-term brain health, yet primary care lacks a brief, validated tool that reliably identifies adults with early cognitive vulnerability. Objective: To evaluate associations between commonly used sleep questionnaires and cognitive impairment among midlife primary care patients. Design, Setting, and Participants: Cross-sectional analysis of baseline data from the MidCog cohort, an observational study of English-speaking adults aged 35 to 64 years receiving primary care at academic practices or federally qualified health centers in the Chicagoland area. Exposures: Five validated sleep questionnaires were used to assess distinct sleep-wake disturbance phenotypes: (A) unsatisfactory sleep (PROMIS Sleep Disturbance T-score >55), (B) short sleep duration (<6 hours; Munich Chronotype Questionnaire), (C) obstructive sleep apnea (OSA) risk (STOP-Bang [&ge;]3), (D) insomnia symptoms (Insomnia Severity Index [&ge;]15), and (E) poor multidimensional sleep health (RU-SATED [&le;]6). Main Outcomes and Measures: The primary outcome was cognitive impairment defined as an age- and education-adjusted NIH Toolbox Cognition Battery (NIHTB-CB) Fluid Composite T-score <40 ( >1 SD below the population mean). Cognitive impairment defined by the Montreal Cognitive Assessment (MoCA) score <23 served as the secondary outcome. Logistic regression estimated adjusted odds ratios (aOR), controlling for age, sex, education, body mass index, hypertension, hypercholesterolemia, diabetes, smoking, depressive symptoms, and recruitment site. Results: Among 646 participants (mean [SD] age, 52.3 [8.1] years; 62.4% female; 38.0% non-Hispanic Black, 38.4% non-Hispanic White, 16.0% Hispanic), cognitive impairment was present in 18.7% by NIHTB-CB and 22.3% by MoCA. Among five sleep-wake disturbance phenotypes evaluated, only poor multidimensional sleep health was consistently associated with cognitive impairment after multivariable adjustment (NIHTB-CB: adjusted OR [95% CI] = 2.03 [1.25-3.26]; MoCA: 1.98 [1.20-3.26]). Conclusions and Relevance: Poor multidimensional sleep health was associated with cognitive impairment in midlife primary care patients. Brief multidimensional sleep health screening may identify individuals with early cognitive vulnerability and represent a potential strategy for targeting sleep-focused interventions to promote long-term brain health.

Loneliness--the perceived discrepancy between desired and actual social connection--is a common and aversive psychological state associated with a range of adverse health outcomes. Several theoretical models suggest that these associations may operate partly through health behaviors. In this preregistered study, we used data from the All of Us Research Program to evaluate associations of loneliness and functional rurality (FR), a study-specific contextual index of reduced neighborhood accessibility, with Fitbit-derived physical activity and sleep outcomes. Final samples included 16,912 participants for physical activity analyses and 13,937 for sleep analyses. In adjusted models, higher FR was associated with greater loneliness ({beta} = 0.061, 95% CI [0.045, 0.077], p = 9.63 x 10-14). FR and loneliness were independently associated with fewer daily steps and lower moderate-to-vigorous physical activity. Loneliness was also associated with shorter sleep duration, greater sleep duration variability, higher odds of short sleep, and higher odds of low sleep efficiency. FR was not associated with sleep duration or sleep duration variability but showed a small positive association with mean sleep efficiency and lower odds of low sleep efficiency. Interaction analyses provided little evidence that FR modified the associations of loneliness with most outcomes, although the FR x loneliness interaction was significant for sleep duration variability, indicating that loneliness was more strongly associated with irregular sleep duration in higher-FR contexts. Sensitivity analyses using stricter valid-day thresholds, winsorization, quartile-based exposure coding, and a backward 30-day window yielded directionally similar findings. These results suggest that FR and loneliness are independently associated with lower physical activity, whereas loneliness shows a more consistent relationship with adverse sleep patterns.