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ABSTRACT Background and Purpose White matter hyperintensities (WMH) are a core neuroimaging marker of cerebral small vessel disease (CSVD). Sleep apnoea (SA) is a recognized vascular risk factor, but its associations with regional WMH burden, short‐interval WMH change and cognitive performance in population‐based cohorts remain incompletely defined. We examined these associations in the UK Biobank imaging cohort. Methods We conducted cross‐sectional analyses with an exploratory longitudinal subset in propensity score–matched cohorts excluding major neurologic and cerebrovascular disease before imaging. SA was identified from hospital records and self‐reports prior to brain magnetic resonance imaging (MRI). Head‐size–normalized WMH volumes were analysed on the log1p scale using multivariable linear regression with robust standard errors. Total WMH was the primary outcome; periventricular WMH (PWMH), deep WMH (DWMH) and cognitive measures were secondary outcomes. Mediation analyses evaluated WMH as a mediator of SA–cognition associations. Results In cross‐sectional analyses ( N = 12,890; mean age, 67.4 years; 27.2% women), SA was associated with greater WMH burden. Total WMH volume was 10.7% higher among participants with SA (95% CI, 5.0%–16.6%; p < 0.001). PWMH and DWMH volumes were 10.0% (95% CI, 4.7%–15.7%; q < 0.001) and 15.7% (95% CI, 7.1%–25.1%; q < 0.001) higher, respectively. SA was associated with modestly worse cognitive performance, with effect estimates attenuated after adjustment for WMH burden and cardiometabolic conditions. Mediation analyses indicated that WMH burden, particularly PWMH, mediated associations between SA and cognitive performance. In the longitudinal subset ( N = 698; median follow‐up, 2.26 years), no significant between‐group differences were observed in annualized WMH change. Conclusions In this large population‐based imaging cohort, SA was associated with higher WMH burden, a key neuroimaging marker of CSVD. Cognitive differences were modest, but WMH burden, particularly PWMH, consistently mediated associations between SA and cognitive performance. Longer term studies are needed to clarify temporal relationships and potential treatment effects.

Abstract Introduction Isolated REM sleep behavior disorder (iRBD) is characterized by loss of normal REM sleep atonia and dream enactment behavior. iRBD is strongly associated with α-synucleinopathies and risk for developing Parkinson’s disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA), yet phenoconversion risk for long-term outcomes of younger women and men remains undefined. We aimed to ascertain longitudinal outcomes and phenoconversion risk in the Mayo Clinic iRBD cohort. Methods Eighty-nine of 165 registry participants with at least one-year follow-up were included. Retrospective chart review attained baseline demographics, age at presentation, baseline Timed Up and Go (TUG) and Montreal Cognitive Assessment (MoCA) scores, and phenoconversion status (iRBD, PD, DLB, mild cognitive impairment [MCI], MSA, or other). Kaplan–Meier survival analysis and Cox proportional hazards modeling were analyzed with alpha at p &lt; 0.05. Results 68 men and 21 women had a mean age of 63 years at polysomnographic diagnosis. At follow-up, 64 (71.9%) remained iRBD; 7 (7.9%) developed PD, 11 (12.4%) developed DLB, 3 (3.4%) developed MCI, 1 (1.1%) developed MSA, and 3 (3.4%) developed another dementia. Abnormal TUG (&gt;12 seconds) occurred in 5.9% and abnormal MoCA (&lt; 24) in 23.3%. Phenoconversion rates were similar in women and men (p = 0.44). Older age at PSG predicted phenoconversion, corresponding to a two-fold increase in risk with each 10-year increase (HR 2.00, 95% CI 1.15–3.52). Neither abnormal TUG nor MoCA predicted conversion. Cumulative phenoconversion was approximately 1% at 1 year, 7% at 3 years, 10% at 5 years, 30% at 10 years, 34% at 12 years, and 49% at 15 years. Mean and median time to phenoconversion was 7 years (range, 1-18 years). Conclusion We found that iRBD phenoconversion rates were lower than historically reported. Only age at presentation predicted phenoconversion, with risk doubling per decade. At 12 years, cumulative phenoconversion rate was approximately 34%. Support (if any)

Abstract Introduction Observational studies have reported associations between hypnotic use and increased risk of cognitive decline. These findings may reflect confounding from insomnia severity, healthcare utilization, and comorbidity burden. We evaluated whether hypnotic exposure is independently associated with incident mild cognitive impairment (MCI) or dementia after rigorous adjustment, including a comprehensive propensity score (PS) and Apolipoprotein E (APOE) ε4 status. Methods We conducted a retrospective cohort study using a biobank sample with linked electronic health records and genetic data. Hypnotic exposure was derived from orders data and categorized as unexposed (n=27,055), single prescription (n=4243), shorter-term use (n=3999), long-term use (≥6 orders for ≥1 year; n=3214), and by drug class: benzodiazepines (n=376), Z-drugs (n=6222), trazodone (n=2395), and mixed exposure (≥2 classes; n=2435). Incident MCI/dementia diagnoses (ICD-9/10) occurring ≥12 months after initial prescription constituted outcomes. The PS modeled likelihood of receiving hypnotics based on demographics; sleep-related conditions; healthcare utilization (record length, visit frequency, diagnostic burden); psychiatric comorbidities; alcohol use and chronic pain. Hypnotic users were 1:2 matched to unexposed individuals on age, sex, healthcare utilization, and PS. Cox proportional hazards models with a 60-month lag tested associations of exposure category, duration, and class with outcomes. Models adjusted for all PS covariates, cardiovascular risk score, and APOE ε4 status. Results Matched but unadjusted analyses suggested slightly higher hazards of MCI/dementia among hypnotic users versus unexposed (HR=1.08; CI=0.99–1.18). However, after PS adjustment and APOE ε4 inclusion, hypnotic users showed significantly lower hazards (HR=0.81; CI=0.74–0.89). Class-specific analyses indicated reduced hazards for Z-drugs (HR=0.83; CI=0.74–0.93), trazodone (HR=0.71; CI=0.60–0.86), and mixed users (HR=0.79; CI=0.68–0.91), with all classes showing lower hazards than benzodiazepine-only users. Long-term hypnotic use was associated with lower hazards than no prescription (HR=0.69; CI=0.61–0.80), single prescription (HR=0.81; CI=0.68–0.97), or short-term use (HR=0.76; CI=0.65–0.90). Conclusion The elevated cognitive risk among hypnotic users appears largely attributable to underlying clinical/utilization factors rather than hypnotic exposure itself. After comprehensive confounding control, all hypnotic classes except benzodiazepines demonstrated lower risk of MCI/dementia. These findings underscore the need for rigorous adjustment in studies of insomnia pharmacotherapy and suggest potential protective effects of certain hypnotics that warrant further investigation. Support (if any) None

Abstract Introduction The relationship between sleep and brain metabolism remains unclear. This study aimed to examine whether overnight sleep features, using a home sleep apnea system based on peripheral arterial tonometry, are associated with regional FDG-PET changes in older adults. Methods We analyzed cognitively unimpaired adults (≥60 years) from the Mayo Clinic Study of Aging (MCSA) cohort who were not receiving sleep apnea treatment. Participants underwent overnight sleep assessment with the WatchPAT system, followed by FDG-PET imaging the next morning. FDG-PET data were co-registered to 3T MRI and automatically segmented into 122 anatomical regions. PET signal was referenced to the pons (SUVR). We computed voxel-weighted median FDG signal across 47 bilateral cortical and subcortical regions of interest (ROIs), excluding brainstem and cerebellum. Associations between sleep architecture and sleep apnea/hypoxemia burden and regional metabolism were assessed using partial Spearman’s rank correlation, adjusting for age. Results Thirty-seven participants were included (70.3% female; median [IQR] age: 72.0 [68.0–78.0] years). Wake after sleep onset (WASO) showed widespread negative associations with FDG uptake in cortical regions (p&lt; 0.05), particularly the ventromedial/ventrolateral (rs=–0.47 to –0.33) prefrontal cortex, lateral temporal (rs=–0.38 to –0.33), and occipital (rs=–0.47 to –0.37) cortices. Total sleep time (TST) was positively associated with medial structures (p&lt; 0.05), including the posterior cingulate (rs=0.39), retrosplenial cortex (rs=0.48), hippocampus/parahippocampal (rs=0.34 to 0.36), calcarine cortex (ρ=0.38), thalamus (rs=0.37), and caudate (rs=0.43). Hypoxic burden was positively associated with medial occipital regions (rs=0.35 to 0.39) and AHI-4% with cuneus (rs=0.33). Regional gray matter volume did not mediate these associations. WASO correlated with Insomnia Severity Index (rs=0.43, p=0.008) and self-reported refreshing sleep (rs=0.046). Conclusion Overnight sleep macrostructure features (WASO and TST) and hypoxic burden are significantly associated with brain metabolism, potentially underlying symptoms of sleep disturbance and cognitive aging. Support (if any) Mayo Clinic Alzheimer’s Disease Research Center Development Award (P30 AG062677), R01 AG056366, U01 AG006786, R01 AG056366, R01 AG034676, R37 AG011378, R01 AG041851, R01 NS097495, R01 AG068206, P30 AG062677, R01 HL065176. CLARA project work with funding from the European Union’s HORIZON EUROPE research and innovation programme (No 101136607).

Abstract Introduction Moyamoya is characterized by idiopathic, progressive, large intracranial arterial steno-occlusion, affecting the anterior circulation of the brain. Common presentations include strokes, seizures, and headaches, which have been associated with poor sleep quality and sleep disorders in the general population. However, to our knowledge, sleep quality has not been previously investigated in Moyamoya disease. The aim of this study was to characterize self-reported sleep quality, sleepiness, sleep disorder diagnoses in patients with Moyamoya syndrome, and to explore possible association between sleep disturbance and quality of life in these patients. Methods We analyzed consecutive patients with Moyamoya evaluated at our institution who completed the Pittsburgh Sleep Quality Index (PSQI) and the Epworth Sleepiness Scale (ESS). We also abstracted the Patient-Reported Outcomes Measurement Information System (PROMIS) to measure person-centered physical, mental and social wellbeing. Results We studied 23 patients with mean age 41.8 ± 12.1 years old having disease duration of 3 ± 4.4 years. 15 (65.2%) had ischemic strokes. Mean total PSQI score was 6.9 ± 2.9, and 17 (73.9%) had poor sleep quality (PSQI&gt;5). Mean sleep efficiency was reduced at 80 ± 17%. Although Median ESS was 6 (IQR 3.25 – 8), most patients (91.3%) reported at least mild daytime dysfunction (Component 7≥1). Mean PSQI component scores (0 – 3 severity, 3 is worse) were 1.29 ± 0.62 (subjective quality), 1.1 ± 0.73 (sleep latency), 1.04 ± 0.83 (sleep duration), 0.87 ± 1.01 (sleep efficiency), 1.22 ± 0.52 (sleep disturbances), 0.3 ± 0.88 (sleep medication), and 1.1 ± 0.52 (daytime dysfunction). The total PSQI score was positively correlated with PROMIS score (r=0.47, p=0.044). Only one patient was diagnosed with obstructive sleep apnea and three with chronic insomnia. Conclusion Poor sleep quality appears to be a frequent problem in patients with Moyamoya disease. Sleep disturbance severity was similar to previous findings in clinical stroke populations. The apparent mismatch between subjective sleep disturbance and sleep disorder diagnoses suggest that sleep disorders are likely underdiagnosed in Moyamoya patients. The relationship between PSQI and PROMIS scores suggests that sleep disturbance may significantly affect quality of life in these patients. Support (if any)

Abstract Obstructive sleep apnoea (OSA) is associated with an increased risk for cognitive impairment and dementia, which likely involves Alzheimer’s disease pathology. Non-rapid eye movement slow-wave activity (SWA) has been implicated in amyloid clearance, but it has not been studied in the context of longitudinal amyloid accumulation in OSA. This longitudinal retrospective study aims to investigate the relationship between polysomnographic and electrophysiological SWA features and amyloid accumulation. From the Mayo Clinic Study of Aging cohort, we identified 71 participants ≥60 years old with OSA (mean baseline age = 72.9 ± 7.5 years, 60.6% male, 93% cognitively unimpaired) who had at least 2 consecutive Amyloid Pittsburgh Compound B (PiB)-PET scans and a polysomnographic study within 5 years of the baseline scan and before the second scan. Annualized PiB-PET accumulation [global ΔPiB(log)/year] was estimated by the difference between the second and first log-transformed global PiB-PET uptake estimations divided by the interval between scans (years). Sixty-four participants were included in SWA analysis. SWA was characterized by the mean relative spectral power density (%) in slow oscillation (SO: 0.5–0.9 Hz) and delta (1–3.9 Hz) frequency bands and by their downslopes (SO-slope and delta-slope, respectively) during the diagnostic portion of polysomnography. We fit linear regression models to test for associations among global ΔPiB(log)/year, SWA features (mean SO% and delta% or mean SO-slope and delta-slope), and OSA severity markers, after adjusting for age at baseline PiB-PET, APOE ɛ4 and baseline amyloid positivity. For 1 SD increase in SO% and SO-slope, global ΔPiB(log)/year increased by 0.0033 (95% CI: 0.0001; 0.0064, P = 0.042) and 0.0069 (95% CI: 0.0009; 0.0129, P = 0.026), which were comparable to 32% and 59% of the effect size associated with baseline amyloid positivity, respectively. Delta-slope was associated with a reduction in global ΔPiB(log)/year by −0.0082 (95% CI: −0.0143; −0.0021, P = 0.009). Sleep apnoea severity was not associated with amyloid accumulation. Regional associations were stronger in the pre-frontal region. Both slow-wave slopes had more significant and widespread regional associations. Annualized PiB-PET accumulation was positively associated with SO and SO-slope, which may reflect altered sleep homeostasis due to increased homeostatic pressure in the setting of unmet sleep needs, increased synaptic strength, and/or hyper-excitability in OSA. Delta-slope was inversely associated with PiB-PET accumulation, suggesting it may represent residual physiological activity. Further investigation of SWA dynamics in the presence of sleep disorders before and after treatment is necessary for understanding the relationship between amyloid accumulation and SWA physiology.

Abstract Introduction Central sleep apnea (CSA) is associated with several medical conditions (e.g., heart failure, atrial fibrillation) and medications (e.g., opioids, ticagrelor, sodium oxybate and valproic acid). We report a case of a 31-year-old female with bipolar disorder treated with valproic acid diagnosed with central sleep apnea on polysomnography, which revealed an apnea-hypopnea index of 150/hour, central apnea index of 112/hour, nadir oxygen saturation of 78%, and 38.6 minutes with oxygen saturation ≤ 88%. Echocardiogram, electrocardiogram, brain magnetic resonance imaging, serum acylcarnitine and serum ammonia levels were unremarkable. Total and free serum valproic acid level was 33 and &lt; 3 mcg/mL, respectively. Two cases of central sleep apnea associated with valproic acid use, both of which improved upon discontinuation of valproic acid, have been reported in the literature. We started the patient on positive airway pressure and suggested she taper off valproic acid and then repeat polysomnography. Given the possible association between central sleep apnea and valproic acid use, we retrospectively analyzed patients receiving valproic acid at time of polysomnography. Methods We retrospectively identified patients between 2005-2017 who were prescribed valproic acid (n=6,169), and of these 72 received valproic acid within 90 days of polysomnography. After chart review, we were able to confirm that 29 received valproic acid at time of polysomnography via blood levels or clear chart documentation. Results Four patients (13.8 %) demonstrated a central apnea index ≥ 5 per hour (mean apnea-hypopnea index 39.2/hour +/- 32.2/ hour including a central apnea index 11.7 +/- 6.6/hour) during polysomnography. Although one patient (3.4 %), a 2-year-old child with Dravet syndrome and refractory/drug resistant generalized epilepsy, was diagnosed clinically with central sleep apnea, the other three patients were diagnosed with obstructive sleep apnea and had other potential reason(s) for the elevated central apnea index (e.g., opioid use as needed for migraines). Conclusion Our case describes a third report of central sleep apnea possibly associated with valproic acid, and our retrospective study indicates that this association is rare. Prospective sleep studies on patients before and after receiving valproic acid are warranted to determine if valproic acid causes central sleep apnea. Support (if any)