SLEEP

Isolated rapid eye movement (REM) sleep behaviour disorder (iRBD) is an early-stage synucleinopathy characterized by brainstem pathology. In rodents, the pontine tegmentum contains an REM sleep centre, the sublaterodorsal nucleus (SLD), which expresses corticotropin-releasing hormone binding protein (CRHBP). While the involvement of brainstem pathophysiology is thus implicated in iRBD, its solid evidence remains scarce in humans due to the difficulty in identifying small brainstem nuclei with conventional MRI technology alone. Here, we aimed to detect tegmental atrophy in iRBD with voxel-based morphometry (VBM) analysis combined with a novel human brainstem atlas. Structural MRIs from 98 patients with iRBD and 114 controls were analysed to investigate grey matter volume (GMV) using VBM. Our unique approach involved detailed assessments of the VBM results, guided by a high-resolution MRI-based atlas of the human brainstem. This brainstem atlas was founded on ex vivo MRI of 10 postmortem human specimens. We validated it with CRHBP immunostaining, which aided in identifying putative REM sleep-regulating nuclei in humans. We applied this brainstem atlas to identify atrophy in specific brainstem regions in iRBD and correlate their volumes with clinical measures, including autonomic functions. VBM revealed a focal cluster of grey matter atrophy in the dorsal pontine tegmentum of iRBD patients, including the laterodorsal tegmental nucleus, ventral part (LDTgV) and the pedunculopontine tegmental nucleus (PTg). Our atlas-based analysis confirmed the LDTgV as the site of most conspicuous atrophy, revealing a significant volume reduction in iRBD patients compared to controls with a moderate effect size (Cohens d = 0.46, Bonferroni-corrected p = 0.019). Furthermore, greater atrophy in the LDTgV and the PTg was associated with more severe autonomic dysfunction as measured by Scales for Outcomes in Parkinsons Disease-Autonomic dysfunction (SCOPA-AUT) scores (partial r = -0.237, p = 0.019 and partial r = -0.236, p = 0.019, respectively). Histological analysis confirmed that the LDTgV is selectively enriched with CRHBP-positive neurons, a putative marker for REM sleep-on neurons. We provided novel evidence for the involvement of LDTgV, the putative human homolog of the murine SLD, in iRBD. The present findings advance our understanding of the neuroanatomical basis of iRBD and will contribute to the development of early biomarkers for -synucleinopathies.

BackgroundBrain waves during sleep are involved in sensing and regulating peripheral glucose level. Whether brain waves in patients with diabetes differ from those of healthy subjects is unknown. We examined the hypothesis that patients with diabetes have reduced sleep spindle waves, a form of brain wave implicated in periphery glucose regulation during sleep. MethodsFrom a retrospective analysis of polysomnography (PSG) studies on patients who underwent sleep apnea evaluation, we identified 1,214 studies of patients with diabetes mellitus (>66% type 2) and included a sex- and age-matched control subject for each within the scope of our analysis. We similarly identified 376 patients with prediabetes and their matched controls. We extracted spindle characteristics from artifact-removed PSG electroencephalograms and other patient data from records. We used rank-based statistical methods to test hypotheses. We validated our finding on an external PSG dataset. ResultsPatients with diabetes mellitus exhibited on average about half the spindle density (median=0.38 spindles/min) during sleep as their matched control subjects (median=0.70 spindles/min) (P<2.2e-16). Compared to controls, spindle loss was more pronounced in female patients than in male patients in the frontal regions of the brain (P=0.04). Patients with prediabetes also exhibited signs of lower spindle density compared to matched controls (P=0.01-0.04). ConclusionsPatients with diabetes have fewer spindle waves that are implicated in glucose regulation than matched controls during sleep. Besides offering a possible explanation for neurological complications from diabetes, our findings open the possibility that reversing/reducing spindle loss could improve the overall health of patients with diabetes mellitus. FundingThis research was supported by the Intramural Research Program of the National Institutes of Health, National Institute of Environmental Health Sciences (ZIA ES101765).

Study objectivesSleep deficiency is associated with Alzheimers disease (AD) pathogenesis. We examined the association of sleep architecture with anatomical features observed in AD: (1) atrophy of hippocampus, entorhinal, inferior parietal, parahippocampal, precuneus, and cuneus regions ("AD-vulnerable regions") and (2) cerebral microbleeds. MethodsIn 271 participants of the Atherosclerosis Risk in the Communities Study, we examined the association of baseline sleep architecture with anatomical features identified on brain MRI 13[~]17 years later. Sleep architecture was quantified as the proportion of slow wave sleep (SWS), proportion of rapid eye-movement sleep (REM), and arousals index using polysomnography. Outcomes included (1) volumetric measurements of each AD-vulnerable region and (2) the presence of any cerebral microbleeds (CMBs) and that of lobar CMBs, which are more specifically associated with AD. We analyzed the association of each sleep predictor with each MRI outcome, adjusting for covariates. ResultsHaving less SWS was associated with smaller inferior parietal region ({beta}=-44.19 mm3 [95%CI=-76.63,-11.76]) and cuneus ({beta}=-11.99 mm3 [-20.93,-3.04]) after covariate adjustment. Having less REM was associated with smaller inferior parietal region ({beta}=-75.52 mm3 [-129.34, -21.70]) and precuneus ({beta}=-31.93 mm3 [-63.79,-0.07]). After FDR adjustments, lower SWS and REM, respectively, were associated with smaller inferior parietal region. Arousal index was not associated with the volumes of AD-vulnerable regions. None of the sleep architecture variables were associated with CMBs or lobar CMBs. ConclusionsSleep deficiency is associated with the atrophy of the inferior parietal region, which is observed in early AD. Sleep architecture may be a modifiable risk factor for AD. Brief summarya. Current Knowledge/Study Rationale: two sentences summarizing why the study was doneWhile impaired sleep architecture has been associated with Alzheimers disease [AD] diagnosis and cognitive decline. To better understand the impact of sleep on AD pathogenesis, this study examined the association of sleep architecture with anatomical features observed in AD, including the atrophy of AD-vulnerable regions and CMBs. b. Study Impact: two sentences summarizing how the study impacts the fieldOur study shows that lower slow wave sleep and rapid eye movement sleep may be precipitating factors of inferior parietal region atrophy, which is associated with AD risk. Importantly, the current studys findings can help characterize underlying mechanisms of how sleep deficiency, a prevalent disturbance among middle-aged and older adults, may facilitate AD pathogenesis and cognitive impairment.

Sex differences in sleep architecture are well-documented, with females experiencing longer total sleep time (TST), more slow wave sleep (SWS) and shorter Rapid Eye Movement (REM) sleep duration than males. Although studies imply that sex hormones could affect sleep, effects of exogenous sex hormones on sleep architecture remain unclear. This study examined sleep architecture changes in transgender individuals after 3 months of gender-affirming hormone therapy (GAHT). We assessed sleep architecture in 73 transgender individuals: 38 transmasculine participants who started using testosterone and 35 transfeminine participants who started using estrogens and anti-androgens. Sleep architecture was measured before GAHT and after 3 months of GAHT for 7 nights using an ambulatory single-electrode sleep EEG device. Changes in sleep architecture were analyzed using linear mixed models, and non-normally distributed outcomes were log-transformed and reported as percentages. In transmasculine participants, SWS decreased by 7 minutes (95% CI: -12; -3) and 1.7% (95% CI: -3%; - 0.5%), REM sleep latency decreased by 39% (95% CI: -52%; -22%) and REM sleep duration increased by 17 minutes (95% CI: 7; 26) after 3 months of GAHT. In transfeminine participants, sleep architecture showed no significant changes after 3 months of GAHT. Sleep architecture changes after three months of masculinizing GAHT in line with sleep in cisgender males, while it shows no changes after feminizing GAHT. The sex-specific nature of these changes raises new questions on sex hormones and sleep. Future research should focus on studying possible underlying neural mechanisms and clinical consequences of these changes. Statement of significanceSleep architecture shows differences between men and women, with women showing longer sleep, longer slow wave sleep and shorter REM sleep than men. Rodent research indicates that sex hormones can alter sleep architecture, but research on sex hormones and sleep architecture in humans is still lacking. This study examined effects of three months of gender-affirming hormone use in transgender individuals. Results show that testosterone use in persons assigned female at birth resulted in sleep architecture changes similar to cisgender males, whereas estradiol- and anti-androgen use by persons assigned male at birth did not change sleep architecture. These novel findings indicate that sex hormones could change sleep architecture in a sex-specific manner, warranting further studies into causal mechanisms underlying these changes.

ObjectiveSleep disturbances are increasingly recognized as early features of Alzheimers disease (AD) neuropathology. In that context, spontaneous arousals during sleep have been associated with the burden of Amyloid beta in the brain of healthy late middle-aged individuals. Whether the heterogeneity of arousals during sleep may be related to the genetic risk of developing AD in young adults is not established. Likewise, whether arousals may be associated with cognitive decline is not known. Here, we evaluated the association between arousals, the genetic risk for developing AD and cognitive performance and cognitive decline in healthy young and late-middle-aged individuals. MethodsWe classified spontaneous arousals using in-lab EEG recordings of sleep in 453 younger individuals (22+/-2.7y; 49 women) and 87 late middle-aged individuals (59.3+/-5.3y; 59 women) based on their association with sleep stage transitions and changes in muscle tone. We examined the associations between arousal types and the polygenic risk scores (PRS) for AD, cognitive performance at baseline and, in late middle-aged individuals, cognitive decline over 2 and 7 years. ResultsThe prevalence of arousals associated with sleep stage transition was higher in late middle-aged vs. younger individuals. Among these arousals, those with and without muscle tone increases were, respectively, associated with lower and higher PRS for AD in late middle-aged but not in younger individuals. In the late middle-aged individuals, transition arousals associated with and without muscle tone increases were, respectively, correlated with better and worse attentional performance at baseline, and lower and larger memory decline over 2 or 7 years. ConclusionThe heterogeneity in spontaneous arousals during sleep may reflect their physiological intensity or underlying neural activation, and may indicate vulnerability to AD in late middle-aged individuals. The findings may contribute to identifying early markers of neurodegenerative risk. Statement of SignificanceSleep arousals are typically regarded as disruptive events, yet their physiological diversity may reveal important insights into brain health. In this study, we report that distinct subtypes of spontaneous sleep arousals are differentially associated with genetic vulnerability to Alzheimers disease (AD) and with future cognitive decline in healthy late middle-aged adults. Specifically, sleep arousals linked to sleep stage transitions but lacking muscle activation were related to higher polygenic risk for AD and greater memory decline, while those accompanied by muscle tone increases showed the opposite pattern. These findings indicate that subtle variations in sleep microstructure can reflect neurobiological vulnerability to AD before clinical symptoms emerge. By identifying electrophysiological markers associated with genetic risk and cognitive trajectories, this work advances the potential for using sleep-based biomarkers to detect and monitor preclinical neurodegenerative processes.

Isolated REM Sleep Behaviour Disorder (iRBD) represents an early stage of -synucleinopathy, often preceding Parkinsons disease, dementia with Lewy bodies or Multiple System Atrophy. Growing evidence shows that iRBD patients are not only characterized by sleep disturbances but also dysautonomia. However, whether the brain-body coupling reflecting the interaction between neural and peripheral physiological activity is altered in iRBD remains unknown. Leveraging whole-night polysomnography data from thirty-six participants, we quantified heart-brain coupling via heartbeat evoked potentials (HEPs) across wakefulness, NREM, and REM sleep. HEPs were compared between individuals with isolated REM sleep behavior disorder (iRBD; n = 13) and healthy controls (HC; n = 23). In addition, heart rate variability (HRV) and other ECG-derived features were analyzed. During wakefulness, iRBD patients showed altered HEP compared to HC, between 230 and 445 ms after the R-peak. over frontal regions. The duration of RBD symptoms was positively associated with the magnitude of these HEP alterations. HEP alterations were specific to wakefulness, as no differences were observed during NREM or REM sleep. Additional analyses showed that HEP alterations in iRBD during wakefulness were not driven by ECG differences. We corroborate previous findings of altered heart rate variability (HRV) in iRBD patients during REM sleep. We demonstrate that brain-body coupling, as indexed by HEP, is altered during wakefulness in iRBD patients. These diurnal HEP may represent a novel quantitative biomarker of iRBD, and could, in the future, serve as a marker for the phenoconversion to -synucleinopathy.

Sleep bruxism (SB) is a sleep-related movement disorder characterized by grinding and clenching of the teeth during sleep. We previously found a significant association between SB and a single nucleotide polymorphism (SNP), rs6313, in the neuronal serotonin 2A receptor gene (HTR2A), and established human induced pluripotent stem cell (hiPSC)-derived neurons from SB patients with a genetic variant. To elucidate the electrophysiological characteristics of SB iPSC-derived neural cells bearing a SB-related genetic variant, we generated ventral hindbrain neurons from two SB patients and two unaffected controls and explored the intrinsic membrane properties of these neurons by patch-clamp technique. We found that the electrophysiological properties of the iPSC-derived neurons from the control line mature in a time-dependent manner in long-term cultures. In the early stage of neurogenesis, neurons from two SB lines tended to display shorter action potential (AP) half durations, which led to an increased cell capability of evoked firing. This is the first in vitro modelling of SB using disease-specific hiPSCs. The revealed electrophysiological characteristics may serve as a benchmark for further investigation of pathogenic mechanisms underlying SB. Summary StatementSleep bruxism patient-specific iPSC-derived neurons with the HTR2A variant show altered electrophysiological characteristics, providing the foremost narration of sleep bruxism neurological phenotypes in vitro from any species.

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.

Sleep-related problems (SRP) in childhood are common and clinically relevant yet their underlying neural mechanisms and links to future mental health outcomes remain poorly understood. Here, we investigated how distinct dimensions of SRP relate to multimodal brain structure and function in preadolescents, and whether these neural signatures predict trajectories of mental health difficulties. We employed multivariate mapping to investigate the relationship between structural and functional brain network patterns and various dimensions of SRP in the Adolescent Brain Cognitive Development (ABCD) dataset. Moreover, we explored whether and how the identified multimodal brain signatures could predict the trajectory of internalizing and externalizing behavior difficulties over a two-year follow-up. Our multivariate analysis revealed two robust dimensions of SRP: a general sleep disturbance dimension and a hypersomnolence and parasomnia dimension. Each was associated with partially distinct patterns of brain morphology and functional connectivity, consistent with their differential alignment along the hierarchical organization of cortical neurodevelopment maps. However, both dimensions shared common disruptions in the somatosensory, attention, and default mode networks. We further observed that only these neural patterns associated with the general sleep disturbance dimension predict the longitudinal trajectories of internalizing/externalizing symptoms. Our findings enhance the understanding of the neurobiological mechanisms underlying dimensions of SRP in preadolescence and could inform brain-based intervention and treatment programs to improve sleep-related and mental health-related outcomes across development.

ImportanceSleep electroencephalographic (EEG) microstructures are closely related to cognition and undergo age-dependent changes. However, their multidimensional nature makes them challenging to interpret using conventional approaches. Machine learning-computed EEG brain age index (BAI) represents the difference between the sleep EEG-based brain age and chronological age, quantifying deviations in sleep EEG microstructures from normative patterns. ObjectiveTo determine the association between sleep BAI and incident dementia in community-dwelling populations. DesignFive individual cohorts and random-effects meta-analysis. SettingThis study pooled data from five community-based, methodologically consistent, longitudinal cohorts: MESA, ARIC, FHS-OS, MrOS, and SOF. We used Fine-Gray models to assess the association between BAI and incident dementia within each cohort, accounting for death as a competing risk. Cohort-specific estimates were then pooled using random-effects meta-analyses. Participants7,071 participants (MESA 54-94 years old, ARIC 52-75, FHS-OS 40-81, MrOS 67-96, SOF 79-93) without dementia at the time of polysomnography were included. ExposureThe sleep EEG-based BAI was computed using interpretable machine learning, incorporating 13 age-dependent features extracted from central EEG channels in overnight, home-based sleep polysomnography. Main Outcomes and MeasuresIncident dementia or probable dementia was determined in each cohort, with death as a competing risk. ResultsAcross the five cohorts, dementia incidence ranged from 6.6% to 34.3% over a median follow-up of 3.5 to 17.0 years. Across cohorts, each 10-year increase in BAI was associated with a 39% increased risk of incident dementia (hazard ratio: 1.39 [95% confidence interval=1.21-1.59], p<0.001) after adjustment for age, sex, race, education, body mass index, current smoking, sleep medications, and physical activity level. The top feature underlying BAI was waveform kurtosis in N2 with a negative association with incident dementia (p<0.001). The associations remained after additional adjustment for multiple comorbidities, APOE e4 status, and apnea-hypopnea index, and were consistent across sex and age groups. Conclusions and RelevanceA higher sleep EEG-based BAI was associated with a higher risk of incident dementia across five community-based longitudinal cohorts. Future studies are warranted to evaluate the predictive value of BAI as a non-invasive digital biomarker for the early detection of dementia in community settings.

Study ObjectivesAutomated sleep staging underpins clinical sleep assessment and translational neuroscience, yet most data analyses work addresses human and animal data separately. We tested whether a seizure-oriented machine learning framework can be repurposed for three-state sleep staging in humans and rats, and whether models trained solely on rodent data can be applied directly to human recordings using an explicit cross-species montage. MethodsWe used the PySeizure, a standardised EEG preprocessing and seizure-detection framework, together with TinySleepNet as the core classifier. Models were trained and evaluated on the Sleep-EDF expanded Sleep Cassette subset (three classes: wake, non-rapid eye movement sleep, rapid eye movement sleep), then applied without fine-tuning to the Sleep Telemetry subset. The same pipeline was used on a SYNGAP1 rat dataset with analogous three-state labels. A novel human-rat electroencephalography montage mapped rat electrodes to putative human scalp homologues, enabling direct application of rat-trained models to Sleep Cassette. ResultsWithin Sleep Cassette, the accuracy in three-stage sleep classification was 0.95. Applying this model directly to Sleep Telemetry yielded an accuracy of 0.89. On the rodent dataset, accuracy was 0.78. When the rat-trained model was applied directly to Sleep Cassette, accuracy was 0.68. ConclusionsA single deep learning pipeline can support robust three-state sleep staging in humans and rodents and retains meaningful performance under both human cross-subset and rat-to-human transfer without any retraining or fine-tuning. The rat-trained models above-chance performance on human data, achieved without human training samples, shows that rodent-derived representations can contribute directly to human sleep staging when constrained by an anatomically informed montage, linking preclinical rodent recordings and clinical human sleep studies.

Study ObjectivesTo investigate associations between social jetlag and developing brain circuits and structures in adolescents. MethodsN = 3507 youth (median (IQR) age = 12.0 (1.1) years; 50.9% females) from the Adolescent Brain Cognitive Development (ABCD) cohort were studied. Social jetlag (adjusted for sleep debt (SJLSC) versus non-adjusted (SJL)), topological properties and intrinsic dynamics of resting-state networks, and morphometric characteristics were analyzed. ResultsOver 35% of participants had SJLSC [&ge;]2.0 h. Boys, Hispanic and Black non-Hispanic youth, and/or those at later pubertal stages had longer SJLSC ({beta}=0.06 to 0.68, CI=[0.02, 0.83], p[&le;]0.02), which was also associated with higher BMI ({beta}=0.13, CI=[0.08, 0.18], p<0.01). SJLSC and SJL were associated with weaker thalamic projections ({beta}=- 0.22, CI=[-0.39, -0.05], p=0.03), potentially reflecting a disrupted sleep-wake cycle. Longer SJLSC was also associated with less topologically resilient and weakly connected salience network ({beta}=-0.04, CI=[-0.08, -0.01], p=0.04), and lower thickness and/or volume of cortical and subcortical structures overlapping with this and other networks supporting emotional and reward processing and regulation, and social function ({beta}=- 0.08 to -0.05, CI=[-0.12, -0.01], p<0.05). SJLSC and SJL were associated with alterations in spontaneous brain activity and coordination that indicate disrupted neural maturation and plasticity. SJL was associated with lower information transfer between regions supporting sensorimotor integration, social function and emotion regulation ({beta}=-0.07 to-0.05, CI=[-0.12, -0.01], p<0.04). ConclusionsMisaligned sleep may have detrimental effects on adolescent brain circuit organization and dynamics, and structural characteristics of regions that play critical roles in cognitive function and regulation of fundamental biological processes.

Brain structural integrity has been suggested to contribute to the variability in human sleep quality and composition. The associations between sleep parameters and the regional integrity of subcortical structures implicated in sleep-wake regulation remain, however, largely unexplored. The present study aimed at assessing association between quantitative Magnetic Resonance Imaging (qMRI)-derived marker of the myelin content of the brainstem with the variability in the sleep electrophysiology in a large sample of healthy young men (N=321;[~]22y). Generalized Additive Model for Location, Scale and Shape (GAMLSS) was used to seek associations between sleep metrics and Magnetisation Transfer saturation (MTsat) qMRI values, proxy for myelin content. Separate GAMLSS revealed that sleep onset latency and slow wave sleep intensity were significantly associated with MTsat-derived myelin estimates in the brainstem (pcorrected[&le;].03), with overall higher MTsat value associated with values reflecting better sleep quality. The association changed with age, however (MTsat-by-age interaction - pcorrected[&le;].03), with higher MTsat value linked to better values in the two sleep metrics in the individuals of our sample aged [~]18 to 20y. Similar associations were detected across different parts of the brainstem (pcorrected[&le;].03), suggesting that the overall maturation and integrity of the brainstem was associated with both sleep metrics. Our results suggest that myelination of the many reticular nuclei of the brainstem essential to regulation of sleep is associated with inter-individual differences in sleep characteristics during early adulthood. They may have implications for sleep disorders or neurological diseases related to myelin.

BackgroundExcessive daytime sleepiness (EDS) is a disabling symptom of Lewy body disorders (LBD). The hypothalamus is a key sleep-wake regulator, but its contribution to EDS in LBD remains unclear. ObjectivesUse diffusion MRI to evaluate the relationship of hypothalamic microstructure to EDS symptoms in LBD. MethodsWe studied 102 patients with clinically-defined LBD (Parkinsons disease, n=93; Parkinsons disease dementia, n=4; and dementia with Lewy bodies, n=5) and Epworth Sleepiness Scale (ESS) within 2 years of MRI. Mean diffusivity (MD) was compared between EDS+ (ESS[&ge;]10, n=37) and EDS- (ESS<10, n=65) groups in the whole hypothalamus and three subregions, covarying for age and sex. Secondary analyses tested correlations between subregion MD and continuous ESS, global cognition, and motor scores; and between subregion volume and continuous ESS. ResultsMD was increased in EDS+ compared to EDS-only in the inferior tuberal subregion (Cohens d=0.43, p=0.043, {beta}=0.117{+/-}0.057), with trend level differences in the whole hypothalamus (Cohens d=0.39, p=0.064, {beta}=0.070{+/-}0.037) and superior tuberal subregion (Cohens d=0.38, p=0.073, {beta}=0.063{+/-}0.035). No difference was seen in the posterior subregion (Cohens d=0.1, p=0.628, {beta}=0.019{+/-}0.038). Significant correlations with continuous ESS were seen in MD of whole hypothalamus (r2=0.074, p=0.0057), superior tuberal (r2=0.081, p=0.0038), and inferior tuberal (r2=0.073, p=0.0059) subregions. There was no correlation of hypothalamic MD with global cognition or motor scores, and no correlation of whole/subregional hypothalamic volumes with ESS. ConclusionsDaytime sleepiness associates with increased MD in the inferior tuberal hypothalamus in an LBD cohort. This suggests degeneration within this region could contribute to EDS symptoms.

Sleep disturbances are prevalent in Alzheimers disease (AD) and Progressive Supranuclear Palsy (PSP), often exacerbating disease progression. Understanding the neuropathological basis of these disturbances is essential for identifying potential therapeutic targets. This study investigates the intermediate nucleus (IntN) of the human hypothalamus--a key sleep-regulating region analogous to the rodent ventrolateral preoptic area (VLPO)--to assess neuronal loss and tau pathology in AD and PSP. Using postmortem brain tissue, we applied unbiased stereology to quantify galanin-expressing neurons and phosphorylated tau (p-tau) accumulation. Among 26 cases analyzed, both AD and PSP exhibited significant neuronal loss in the IntN, with PSP showing the most pronounced reduction (84.9% fewer neurons than healthy controls [HC]). In AD, neuronal loss correlated with Braak staging, with late-stage AD cases (Braak 5-6) demonstrating a 76.9% reduction in galanin-expressing neurons compared to HC, while non-galanin neurons exhibited a more moderate decline (45.7%). In PSP, extensive neuronal loss precluded a clear assessment of p-tau burden. These findings suggest a differential neuronal vulnerability to tau pathology across diseases, aligning with distinct sleep disturbances observed in each condition. PSP, characterized by severe insomnia despite preserved wake-promoting neurons, may be explained by the near-total loss of NREM sleep-regulating neurons. In contrast, AD exhibits a progressive decline in both wake- and sleep-promoting neurons, contributing to excessive daytime sleepiness and sleep fragmentation. This study provides critical insights into the selective neuronal vulnerabilities underlying sleep dysfunction in tauopathies, emphasizing the need for targeted interventions to mitigate sleep disturbances in these disorders.

Background and ObjectivesNarcolepsy Type 1 (NT1) is a neurological disorder caused by hypocretin deficiency, leading to excessive daytime sleepiness and cataplexy. This study characterized dynamic functional connectivity (dFC) states in NT1 patients, acute sleep-deprived (SD) individuals, and healthy controls, and explored how these states relate to clinical measures of sleepiness and arousal. MethodsIn this study, resting-state co-fluctuation analysis was employed to identify recurring brain states and compare group differences in state dwell time, transition probabilities, and interaction strength. Associations between dFC properties and clinical metrics (Epworth Sleepiness Scale [ESS] scores, mean sleep latency from MSLT) were also investigated. ResultsFive distinct resting-state co-fluctuation states were identified. NT1 patients showed significantly longer mean dwell time and higher fraction rate in State 3, characterized by synchronized activity between the salience/ventral attention network (SN/VAN) and sensorimotor network (SMN) with antagonistic co-fluctuations to the visual network (VIS), compared to both SD and control groups. They also exhibited increased reciprocal transition probabilities between State 3 and State 5. Group-specific differences in co-fluctuation strength were observed across multiple states, with NT1 showing distinct alterations in interactions involving the striatum, limbic system, and attentional networks. Moreover, the fraction rate of State 5 negatively correlated with ESS scores, while the fraction rate of State 3 negatively correlated with mean sleep latency from MSLT in NT1 patients, indicating that increased occupancy of certain states was associated with less subjective sleepiness and greater arousal instability. ConclusionThese findings highlight the role of chronic hypocretin-mediated arousal failure versus acute homeostatic sleep pressure in shaping network co-fluctuation patterns, characterized by thalamocortical disconnection, cortical dysregulation, and enhanced striatal-limbic connectivity. This state might be specific to hypocretin deficiency and suggests that dFC states may serve as potential biomarkers for sleep-wake disorders.

Increasing evidence suggests that the sleep pathology associated with neurodegenerative diseases can in turn exacerbate both the cognitive deficits and underlying pathobiology of these conditions. Treating sleep may therefore bear significant, even disease-modifying, potential for these conditions, but how best and when to do so remains undetermined. Huntingtons Disease (HD), by virtue of being an autosomal-dominant neurodegenerative disease presenting in mid-life, presents a key model condition through which to advance this field. To date, however, there has been no clinical longitudinal study of sleep abnormalities in HD, and no robust interrogation of their association with disease onset, cognitive deficits and markers of disease activity. Here we present the first such study. HD gene carriers (n=28) and age- and sex-matched controls (n=21) were studied at baseline and 10- and 12-year follow up. All HD gene carriers were premanifest at baseline, and were stratified at follow up into prodromal/manifest and premanifest groups. Sleep abnormalities were assessed through two-night inpatient polysomnography (PSG) and two-week domiciliary actigraphy, and their association was explored against i)validated cognitive and affective outcomes (Montreal Cognitive Assessment, Trail A/B task, Symbol Digit Modalities Task [SDMT], Hopkins Verbal Learning Task [HVLT], Montgomery-Asberg Depression Rating Scale [MADRS]) and ii)serum neurofilament-light (NfL) levels. Statistical analysis incorporated cross-sectional ANCOVA, longitudinal repeated measures linear models and regressions adjusted for multiple confounders including disease stage. 15 HD gene carriers phenoconverted to prodromal/early manifest HD by study completion. At follow-up, these gene carriers showed more frequent sleep stage changes (p=<0.001,p2=0.62) and higher levels of sleep maintenance insomnia (p=0.002,p2=0.52). The latter finding was corroborated by nocturnal motor activity patterns on follow-up actigraphy (p=0.004,p2=0.32). Greater sleep maintenance insomnia was associated with greater cognitive deficits (Trail A p=<0.001,R{superscript 2}=0.78;SDMT p=0.008,R{superscript 2}=0.63;Trail B p=0.013,R{superscript 2}=0.60) and higher levels of NfL (p=0.015,R{superscript 2}=0.39). Longitudinal modelling suggested that sleep stage instability accrues from the early premanifest phase, whereas sleep maintenance insomnia emerges closer to phenoconversion. Baseline sleep stage instability was able to discriminate those who phenoconverted within the study period from those who remained premanifest (area under curve=0.81,p=0.024). These results demonstrate that the key sleep abnormalities of premanifest/early HD are sleep stage instability and sleep maintenance insomnia, and suggest that the former bears value in predicting disease onset, while the latter is associated with greater disease activity and cognitive deficits. Intervention studies to interrogate causation within this association could not only benefit patients with HD, but also help provide fundamental proof-of-concept findings for the wider sleep-neurodegeneration field.

INTRODUCTIONLocus coeruleus and glymphatic dysfunction are linked both to Alzheimers disease (AD) and, recently, to infraslow oscillation in sleep spindle (sigma) activity (ISO). Here we hypothesise ISO integrity is a critical link between sleep and AD. METHODSWe analyzed non-rapid eye movement sleep EEG from AD and controls, extracting ISO peak amplitude, intrinsic frequency, and bandwidth from the sigma-power time course. We assessed group differences and correlations with plasma biomarkers (A{beta}42/40, pTau181 and 217, NfL, GFAP). RESULTSISO peak amplitude was significantly reduced in AD, while intrinsic frequency and bandwidth were preserved. ISO peak amplitude positively correlated with A{beta}42/40 ratio, and ISO bandwidth correlated with GFAP and NfL levels, and with lower verbal memory retention. DISCUSSIONSuch selective weakening of ISO in AD is consistent with LC dysfunction and impaired glymphatic cycling. ISO may be a novel mechanism and electrophysiological marker linking sleep microarchitecture to AD pathology.

BackgroundIsolated rapid eye movement (REM) sleep behavior disorder (iRBD) cohorts have provided novel insights in the earliest neurodegenerative processes in -synucleinopathies. Even though polysomnography remains the gold standard for diagnosis, an accurate questionnaire-based algorithm to identify eligible subjects could facilitate efficient recruitment in research. ObjectivesThis study aimed to optimize the identification of subjects with iRBD from the general population. MethodsBetween June 2020 and July 2021, we placed newspaper advertisements including the single-question screen for RBD (RBD1Q). Participants evaluations included a structured telephone screening consisting of the RBD screening questionnaire (RBDSQ) and additional sleep-related questionnaires. We examined anamnestic information predicting polysomnography-proven iRBD using logistic regressions and receiver operating characteristic curves. Results543 participants answered the advertisements and 185 subjects fulfilling in- and exclusion criteria were screened. Of these, 124 received polysomnography after expert selection and 78 (62.9%) were diagnosed with iRBD. Selected items of the RBDSQ, the Pittsburgh Sleep Quality Index, the STOP-Bang questionnaire, and age predicted iRBD with high accuracy in a multiple logistic regression model (area under the curve >80%). Comparing the algorithm to the sleep expert decision, 77 instead of 124 polysomnographies (62.1%) would have been carried out, while 63 (80.8%) of iRBD patients would have been identified. 32 of 46 (69.6%) unnecessary polysomnography examinations could have been avoided. ConclusionsOur proposed algorithm displayed high diagnostic accuracy for polysomnography-proven iRBD in a cost-effective manner and may be a convenient tool for application in research and clinical settings. External validation sets are warranted to prove its reliability.

Isolated REM sleep behavior disorder (iRBD), a prodromal synucleinopathy, generally precedes Parkinsons disease (PD) or dementia with Lewy bodies (DLB). While disruptions in structural brain connectivity have been reported in these diseases, their presence in prodromal phases such as iRBD remains unclear. In this cross-sectional study, we analysed diffusion MRI in a large multicentric dataset (198 iRBD, 174 controls), mapping white matter pathways between 462 regions. Comparing groups, we found disrupted structural connectivity in iRBD. This included reduced density in multiple cortical areas alongside focal increases suggesting compensation in parietal, orbitofrontal and visual cortices. Global and local efficiency were altered in iRBD, notably in motor-related regions (putamen, thalamus, sensorimotor and parietal cortices), and was associated with emerging motor features. Importantly, increased local efficiency in the supramarginal gyrus predicted phenoconversion to DLB, but not PD. These findings highlight early structural connectivity disruptions in iRBD, offering a potential marker for progression to DLB.