Faculty Bibliography

There is emerging evidence that obstructive sleep apnea (OSA) is a risk factor for preclinical Alzheimer's disease (AD). An American Thoracic Society workshop was convened that included clinicians, basic scientists, and epidemiologists with expertise in OSA, cognition, and dementia, with the overall objectives of summarizing the state of knowledge in the field, identifying important research gaps, and identifying potential directions for future research. Although currently available cognitive screening tests may allow for identification of cognitive impairment in patients with OSA, they should be interpreted with caution. Neuroimaging in OSA can provide surrogate measures of disease chronicity, but it has methodological limitations. Most data on the impact of OSA treatment on cognition are for continuous positive airway pressure (CPAP), with limited data for other treatments. The cognitive domains improving with CPAP show considerable heterogeneity across studies. OSA can negatively influence risk, manifestations, and possibly progression of AD and other forms of dementia. Sleep-dependent memory tasks need greater incorporation into OSA testing, with better delineation of sleep fragmentation versus intermittent hypoxia effects. Plasma biomarkers may prove to be sensitive, feasible, and scalable biomarkers for use in clinical trials. There is strong biological plausibility, but insufficient data, to prove bidirectional causality of the associations between OSA and aging pathology. Engaging, recruiting, and retaining diverse populations in health care and research may help to decrease racial and ethnic disparities in OSA and AD. Key recommendations from the workshop include research aimed at underlying mechanisms; longer-term longitudinal studies with objective assessment of OSA, sensitive cognitive markers, and sleep-dependent cognitive tasks; and pragmatic study designs for interventional studies that control for other factors that may impact cognitive outcomes and use novel biomarkers.

BACKGROUND:Preclinical studies suggest body temperature (Tb) and consequently brain temperature has the potential to bidirectionally interact with tau pathology in Alzheimer's Disease (AD). Tau phosphorylation is substantially increased by small (<1 °C) decreases in temperature within the human physiological range, and thermoregulatory nuclei are affected by tau pathology early in the AD continuum. In this study we evaluated whether Tb (as a proxy for brain temperature) is cross-sectionally associated with clinically utilized markers of tau pathology in cognitively normal older adults. METHODS:Tb was continuously measured with ingestible telemetry sensors for 48-h. This period also included two nights of nocturnal polysomnography to delineate whether Tb during waking vs sleep is differentially associated with tau pathology. Tau phosphorylation was assessed with plasma and cerebrospinal fluid (CSF) tau phosphorylated at threonine 181 (P-tau), sampled the day following Tb measurement. In addition, neurofibrillary tangle (NFT) burden in early Braak stage regions was imaged with PET-MR using the [18F]MK-6240 radiotracer on average one month later. RESULTS:Lower Tb was associated with increased NFT burden, as well as increased plasma and CSF P-tau levels (p < 0.05). NFT burden was associated with lower Tb during waking (p < 0.05) but not during sleep intervals. Plasma and CSF Ptau levels were highly correlated with each other (p < 0.05), and both variables were correlated with tau tangle radiotracer uptake (p < 0.05). CONCLUSIONS:These results, the first available for human, suggest that lower Tb in older adults may be associated with increased soluble and aggregated tau pathology. Our findings add to the substantial preclinical literature associating lower body and brain temperature with tau hyperphosphorylation. CLINICAL TRIAL NUMBER/BACKGROUND:NCT03053908.

STUDY OBJECTIVES/OBJECTIVE:Determine if changes in K-complexes associated with sustained inspiratory airflow limitation (SIFL) during N2 sleep are associated with next-day vigilance and objective sleepiness. METHODS:Data from thirty subjects with moderate-to-severe OSA who completed three in-lab polysomnograms: diagnostic, on therapeutic continuous positive airway pressure (CPAP), and on suboptimal CPAP (4cmH20 below optimal titrated CPAP level) were analyzed. Four 20-min psychomotor vigilance tests (PVT) were performed after each PSG, every two hours. Changes in proportion of spontaneous K-complexes and spectral characteristics surrounding K-complexes were evaluated for K-complexes associated with both delta (∆SWAK), alpha (∆αK) frequencies. RESULTS:Suboptimal CPAP induced SIFL (14.7(20.9) vs. 2.9(9.2); %total sleep time, p<0.001) with a small increase in apnea hypopnea index (AHI3A: 6.5(7.7) vs. 1.9(2.3); p<0.01) versus optimal CPAP. K-complex density (num./min of stage N2) was higher on suboptimal CPAP (0.97±0.7 vs. 0.65±0.5, #/min, mean±SD, p<0.01) above and beyond the effect of age, sex, AHI3A, and duration of SIFL. A decrease in ∆SWAK with suboptimal CPAP was associated with increased PVT lapses and explained 17% of additional variance in PVT lapses. Within-night during suboptimal CPAP K-complexes appeared to alternate between promoting sleep and as arousal surrogates. EEG changes were not associated with objective sleepiness. CONCLUSIONS:Sustained inspiratory airflow limitation is associated with altered K-complex morphology including increased occurrence of K-complexes with bursts of alpha as arousal surrogates. These findings suggest that sustained inspiratory flow limitation may be associated with non-visible sleep fragmentation and contribute to increased lapses in vigilance.

OBJECTIVE:Sleep-dependent memory processing occurs in animals including humans, and disturbed sleep negatively affects memory. Sleep disturbance and memory dysfunction are common in multiple sclerosis (MS), but little is known about the contributions of sleep disturbance to memory in MS. We investigated whether subjective sleep disturbance is linked to worse memory in early MS independently of potential confounders. METHODS:Persons with early MS (n = 185; ≤5.0 years diagnosed) and demographically matched healthy controls (n = 50) completed four memory tests to derive a memory composite, and four speeded tests to derive a cognitive efficiency composite. Z-scores were calculated relative to healthy controls. Sleep disturbance was defined by the Insomnia Severity Index score ≥ 10. ANCOVAs examined differences in memory and cognitive efficiency between patients with and without sleep disturbance controlling for potential confounds (e.g., mood, fatigue, disability, T2 lesion volume, gray matter volume). Comparisons were made to healthy controls. RESULTS:Seventy-four (40%) patients reported sleep disturbance. Controlling for all covariates, patients with sleep disturbance had worse memory (z = -0.617; 95% CI: -0.886, -0.348) than patients without disturbance (z = -0.171, -0.425, 0.082, P = .003). Cognitive efficiency did not differ between groups. Relative to healthy controls, memory was worse among patients with sleep disturbance, but not among patients without sleep disturbance. INTERPRETATION/CONCLUSIONS:Sleep disturbance contributes to MS memory dysfunction, which may help explain differential risk for memory dysfunction in persons with MS, especially since sleep disturbance is common in MS. Potential mechanisms linking sleep disturbance and memory are discussed, as well as recommendations for further mechanistic and interventional research.

BACKGROUND:Recent advancement in deep learning provides a pivotal opportunity to potentially supplement or supplant the limiting step of manual sleep scoring. NEW METHOD/UNASSIGNED:In this paper, we characterize the WaveSleepNet (WSN), a deep convolutional neural network (CNN) that uses wavelet transformed images of mouse EEG/EMG signals to autoscore sleep and wake. RESULTS:WSN achieves an epoch by epoch mean accuracy of 0.86 and mean F1 score of 0.82 compared to manual scoring by a human expert. In mice experiencing mechanically induced sleep fragmentation, an overall epoch by epoch mean accuracy of 0.80 is achieved by WSN and classification of non-REM (NREM) sleep is not compromised, but the high level of sleep fragmentation results in WSN having greater difficulty differentiating REM from NREM sleep. We also find that WSN achieves similar levels of accuracy on an independent dataset of externally acquired EEG/EMG recordings with an overall epoch by epoch accuracy of 0.91. We also compared conventional summary sleep metrics in mice sleeping ad libitum. WSN systematically biases sleep fragmentation metrics of bout number and bout length leading to an overestimated degree of sleep fragmentation. COMPARISON WITH EXISTING METHODS/UNASSIGNED:In a cross-validation, WSN has a greater macro and stage-specific accuracy compared to a conventional random forest classifier. Examining the WSN, we find that it automatically learns spectral features consistent with manual scoring criteria that are used to define each class. CONCLUSION/CONCLUSIONS:These results suggest to us that WSN is capable of learning visually agreeable features and may be useful as a supplement to human manual scoring.

STUDY OBJECTIVES/OBJECTIVE:Obstructive sleep apnea (OSA) prevalence increases with age, but whether OSA-related sleep disruption could interrupt the processing of previously encoded wake information thought to normally occur during sleep in cognitively normal older adults remains unknown. METHODS:Fifty-two older (age = 66.9 ± 7.7 years, 56 % female), community-dwelling, cognitively normal adults explored a 3D maze environment and then performed 3 timed trials before (evening) and after (morning) sleep recorded with polysomnography (PSG) with a 20-minute morning psychomotor vigilance test (PVT). RESULTS:Twenty-two (22) subjects had untreated OSA (Apnea Hypopnea Index (AHI4%) ≥ 5/hour) where severity was mild on average [median (interquartile range (IQR))] AHI4% = 11.0 (20.7)/hour) and 30 subjects had an AHI4% < 5/hour. No significant differences were observed in overnight percent change in completion time or in the pattern of evening pre-sleep maze performance. However, during the morning post-sleep trials, there was a significant interaction between OSA group and morning trial number such that participants with OSA performed worse on average with each subsequent morning trial, whereas those without OSA showed improvements. There were no significant differences in morning PVT performance suggesting that vigilance is unlikely to account for this difference in morning maze performance. Increasing relative frontal slow wave activity (SWA) was associated with better overnight maze performance improvement in participants with OSA (r= 0.51, p = 0.02) but not in those without OSA, and no differences in slow wave activity were observed between groups. CONCLUSIONS:OSA alters morning performance in spatial navigation independent of a deleterious effect on morning vigilance or evening navigation performance. Relative frontal slow wave activity is associated with overnight performance change in older subjects with OSA, but not those without.