Carvalho, Diego Z.

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 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)

Abstract Introduction The ICSD-3-TR defines idiopathic hypersomnia in terms of objective sleep times as sleeping at least 11 hours using 24-hour polysomnography or wrist actigraphy averaged over at least 7 days. Published studies on sleep duration are generally limited by lower sleep duration cut-offs (e.g., ≥ 9 hours), so prevalence data on longer sleep durations are missing. This study used clinical questionnaire data from Mayo Clinic patients to characterize longer sleep times and excessive daytime sleepiness in this population. Methods We retrospectively identified patients who answered questions about subjective sleep times and excessive daytime sleepiness, using the Epworth Sleepiness Scale (ESS), as part of their evaluation in a sleep clinic across the Mayo Clinic Enterprise from 2017 to 2023. Demographic data and sleep disorder diagnoses were then analyzed. Results Patients (N=25,480) with subjective nocturnal sleep times of ≥ 9 (n=2721, 10.7%), ≥ 10 (n=1059, 4.2%), and ≥ 11 hours (n=349, 1.4%) had an ESS ≥ 10 in 33.5%, 41.0%, and 51.3% of the time, respectively. 3.6% (age 53.2±19.7; 58.9% female), 1.7% (age 53.1±20.4; 58.1% female), and 0.7% (age 49.8±19.9; 58.1% female) of the patients reported an ESS ≥ 10 and subjective nocturnal sleep times of ≥ 9, ≥ 10, and ≥ 11 hours per night, respectively. After adjusting for age and sex, patients with more than one diagnostic entry compared to those with one or fewer diagnostic entries for idiopathic hypersomnia with long sleep time (OR=12.75, 95% CI [6.09, 24.52], p&lt; 0.001) and narcolepsy with cataplexy (OR=5.53, 95% CI [1.31, 15.84], p=0.005) were significantly more likely to report ESS ≥ 10 and subjective nocturnal sleep times ≥ 11 hours per night. Conclusion Less than 1% of patients presenting to a Mayo Clinic sleep specialist have self-reported metrics (i.e., ESS ≥ 10 and subjective nocturnal sleep times ≥ 11 per night) consistent with basic clinical features of idiopathic hypersomnia with long sleep time. Additional data analyses (e.g., comorbid conditions, social history, and laboratory results) are underway. Support (if any)

Abstract Introduction Meta-analytic studies support that insomnia is a risk factor for cognitive decline and dementia, but limited accounting of confounders reduces their validity. Further, it is unclear whether these associations are driven by specific insomnia phenotypes. In this study, we aimed to assess the relationship between insomnia and longitudinal global cognitive decline in community-dwelling older adults after considering self-reported sleep duration changes and other important characteristics. Methods From the Mayo Clinic Study of Aging (MCSA) cohort, we identified all (age&gt;=50yo) cognitively unimpaired participants at baseline without comorbid neurological disease with at least two previous comprehensive neuropsychological evaluations. Participants with at least two occurrences of insomnia ICD diagnosis (by EMR and Rochester Epidemiological Project data) at least 30 days apart were classified as having insomnia, and those without any instance of diagnosis were considered negative for insomnia. Changes in sleep duration were assessed using the question #16 of BDI-2 and categorized in reduced sleep (yes/no). We fit mixed-effect regression models to assess whether insomnia was associated with standardized global cognitive scores, after adjusting for age, sex, education, APOEe4, composite cardiovascular and metabolic conditions scores, anxiety/depression, reduced sleep, OSA (ICD diagnosis), alcoholism (CAGE≥2), and pain (NSAIDs use). Number of cognitive assessments and time from baseline were included as both fixed and random effects. Multiple interactions (e.g. insomnia*reduced sleep) were included. A backward stepwise procedure maintaining the hierarchical principal for interactions was utilized to reach the most parsimonious models. Results 3063 participants (50.24% males, aged 70±9.73 at baseline) were included. Insomnia alone was not associated with a decrease in global cognition, but when combined with subjective reduction in sleep duration at baseline it was associated with a -0.19 (95% CI: -0.32, -0.07; interaction p=0.01) reduction in global cognitive scores. This was equivalent to approximately 3 additional years of age or 6 cardiometabolic comorbidities at baseline. The effect size was greater than those associated with baseline cognition for having any APOE e4 allele (-0.12) and alcoholism (-0.15). Conclusion Insomnia with reduced sleep duration phenotype is a potentially modifiable risk factor for cognitive decline in older adults. Further studies with objective sleep measures are necessary for objective confirmation. Support (if any) NIA/NIH

AbstractBackgroundQuantitative rapid eye movement (REM) sleep without atonia (RSWA) recorded during polysomnography (PSG) represents loss of normal REM sleep atonia. RSWA is the neurophysiologic signature of REM sleep behavior disorder (RBD). Visually scored RSWA is a candidate biomarker for synucleinopathies. However, visual RSWA scoring requires expert scoring, limiting widespread application. We comparatively analyzed RSWA in DLB and iRBD using the automated Ferri REM Atonia Index (RAI).MethodWe quantitatively analyzed the RAI in 12 DLB and 20 iRBD patients, compared to 20 controls using Hypnolab Software for Sleep Analysis (SWS Soft, Inc, Colognola ai Colli, Italy). PSG data were converted to European Data Format (.EDF), and the submentalis surface electromyogram (EMG) signal was notch‐filtered at 60 Hertz and rectified. Automatically calculated RAI scores were comparatively analyzed across groups (DLB, iRBD, controls) using Kruskal Wallis H tests for group comparisons, and regression analyses determined relationships between diagnosis, age, and sex. Logistic regression ROC determined optimal RAI for distinguishing iRBD from DLB. When interpreting RAI, lower values represent greater amounts of RSWA, and higher values represent more normal REM atonia.ResultMean age was older in DLB than in iRBD or controls (72.6 vs. 68.7 vs. 66.5 years). All 12 DLB participants were men, the iRBD group had 18 men and 2 women, and controls were comprised of 16 men and 4 women. Mean RAI was lowest in DLB (0.46), intermediate in iRBD (0.71) and highest in controls (0.96), indicating a gradient in RSWA amounts from DLB patients (highest) to controls (lowest) (Figure). Regression demonstrated diagnosis independently predicted RAI, controlling for age and sex (adjusted R2 = 0.49, p = 0.0001). The RAI that optimally distinguished iRBD from DLB was 0.46 (specificity 85%, sensitivity 58%, AUC = 0.75).ConclusionThe RAI demonstrated a clear gradient throughout the Lewy body spectrum; highest (indicating lowest RSWA amounts) in controls, intermediate in iRBD, and lowest (indicating greatest RSWA) in DLB. The RAI is a promising, time efficient and broadly applicable candidate biomarker for DLB and iRBD. Automated quantitative RSWA could be a valuable tool for deep phenotyping throughout the Lewy body disease spectrum.