Faculty Bibliography

Narcolepsy is a sleep disorder marked by chronic, debilitating excessive daytime sleepiness and can be associated with cataplexy, sleep paralysis and sleep-related hallucinations. Pharmacological therapy for narcolepsy primarily aims to increase wakefulness and reduce cataplexy attacks. Pitolisant is a first-in-class agent utilizing histamine to improve wakefulness by acting as an antagonist/inverse agonist of the presynaptic histamine 3 receptor. This review summarizes the clinical efficacy, safety and tolerability of pitolisant in treating the symptoms of narcolepsy. Randomized and observational studies demonstrate pitolisant to be effective in treating both hypersomnolence and cataplexy while generally being well tolerated at prescribed doses. The most common adverse reactions include headache, insomnia and nausea.

Increasing evidence links cognitive-decline and Alzheimer's disease (AD) to various sleep disorders, including obstructive sleep apnea (OSA). With increasing age, there are substantial differences in OSA's prevalence, associated comorbidities and phenotypic presentation. An important question for sleep and AD researchers is whether OSA's heterogeneity results in varying cognitive-outcomes in older-adults compared to middle-aged adults. In this review, we systematically integrated research examining OSA and cognition, mild cognitive-impairment (MCI) and AD/AD biomarkers; including the effects of continuous positive airway pressure (CPAP) treatment, particularly focusing on characterizing the heterogeneity of OSA and its cognitive-outcomes. Broadly, in middle-aged adults, OSA is often associated with mild impairment in attention, memory and executive function. In older-adults, OSA is not associated with any particular pattern of cognitive-impairment at cross-section; however, OSA is associated with the development of MCI or AD with symptomatic patients who have a higher likelihood of associated disturbed sleep/cognitive-impairment driving these findings. CPAP treatment may be effective in improving cognition in OSA patients with AD. Recent trends demonstrate links between OSA and AD-biomarkers of neurodegeneration across all age-groups. These distinct patterns provide the foundation for envisioning better characterization of OSA and the need for more sensitive/novel sleep-dependent cognitive assessments to assess OSA-related cognitive-impairment.

Introduction: The phenomena of a 'first-night effect' (worse sleep) or the 'reverse first-night' effect (better sleep) has ensured that many sleep research protocols employ multiple nights' of in-lab polysomnography (PSG), at the cost of increased financial and participant burden. Although previous investigations in healthy and sleep disordered populations show high night-to-night variability of PSG macrostructure metrics, it is suggested that there is considerable stability in EEG microstructure and respiratory measures. Findings relating NREM EEG microstructure measures to Alzheimer's disease (AD) pathology (tau and beta-amyloid burden) make sleep a potential biomarker of AD risk. Given that variability is always a major concern, we assessed the night-to-night variability of sleep macro and microstructure, respiratory and psychomotor vigilance test (PVT) measures in a group of normal elderly participating in aging and memory studies.
Material(s) and Method(s): 39 participants (66+/- 6.4 years-old and 72% female) attended 2 consecutive nights PSG and completed a 20-minute morning time PVT. 78 PSGs were scored according to AASM guidelines for sleep staging and sleep disordered breathing (S

Sleep spindles have been implicated in motor learning in human subjects, but their occurrence, timing in relation to cortical slow oscillations, and relationship to offline gains in motor learning have not been examined in animal models. In this study, we recorded EEG over bilateral primary motor cortex in conjunction with EMG for 24 h following a period of either baseline handling or following rotarod motor learning to monitor sleep. We measured several biophysical properties of sleep spindles and their temporal coupling with cortical slow oscillations (SO, <1 Hz) and cortical delta waves (1-4 Hz). Following motor learning, we found an increase in spindles during an early period of NREM sleep (1-4 h) without changes to biophysical properties such as spindle power, peak frequency and coherence. In this same period of early NREM sleep, both SO and delta power increased after motor learning. Notably, a vast majority of spindles were associated with minimal SO power, but in the subset that were associated with significant SO power (>1 z-score above the population mean), spindle-associated SO power was greater in spindles following motor learning compared to baseline sleep. Also, we did not observe a group-level preferred phase in spindle-SO or spindle-delta coupling. While SO power alone was not predictive of motor performance in early NREM sleep, both spindle density and the difference in the magnitude of the mean resultant vector length of the phase angle for SO-associated spindles, a measure of its coupling precision, were positively correlated with offline change in motor performance. These findings support a role for sleep spindles and their coupling to slow oscillations in motor learning and establish a model in which spindle timing and the brain circuits that support offline plasticity can be mechanistically explored.

STUDY OBJECTIVES/OBJECTIVE:To determine the effect of self-reported clinical diagnosis of Obstructive Sleep Apnea (OSA) on longitudinal changes in brain amyloid-PET and CSF-biomarkers (Aβ42, T-tau and P-tau) in cognitively normal (NL), mild cognitive impairment (MCI) and Alzheimer's Disease (AD) elderly. METHODS:Longitudinal study with mean follow-up time of 2.52±0.51 years. Data was obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Participants included 516 NL, 798 MCI and 325 AD elderly. Main Outcomes were annual rate-of-change in brain amyloid-burden (i.e. longitudinal increases in florbetapir-PET uptake or decreases in CSF-Aβ42 levels); and tau-protein aggregation (i.e. longitudinal increases in CSF total-tau (T-tau) and phosphorylated-tau (P-tau)). Adjusted multi-level mixed effects linear regression models with randomly varying intercepts and slopes was used to test whether the rate-of-biomarker-change differed between participants with and without OSA. RESULTS:In NL and MCI groups, OSA+ subjects experienced faster annual increase in florbetapir uptake (B=.06, 95% CI .02, .11 and B=.08, 95% CI .05, .12 respectively) and decrease in CSF-Aβ42 levels (B=-2.71, 95% CI -3.11, -2.35 and B=-2.62, 95% CI -3.23, -2.03, respectively); as well as increases in CSF T-tau (B=3.68, 95% CI 3.31, 4.07 and B=2.21, 95% CI 1.58, 2.86, respectively) and P-tau (B=1.221, 95% CI, 1.02, 1.42 and, B=1.74, 95% CI 1.22, 2.27, respectively); compared to OSA- participants. No significant variations in the biomarker changes over time were seen in the AD group. CONCLUSIONS:In both NL and MCI, elderly, clinical interventions aimed to treat OSA are needed to test if OSA treatment may affect the progression of cognitive impairment due to AD.

Current sleep analyses have used electroencephalography (EEG) to establish sleep intensity through linear and nonlinear measures. Slow wave activity (SWA) and entropy are the most commonly used markers of sleep depth. The purpose of this study is to evaluate changes in brain EEG connectivity during sleep in healthy subjects and compare them with SWA and entropy. Four different connectivity metrics: coherence (MSC), synchronization likelihood (SL), cross mutual information function (CMIF), and phase locking value (PLV), were computed focusing on their correlation with sleep depth. These measures provide different information and perspectives about functional connectivity. All connectivity measures revealed to have functional changes between the different sleep stages. The averaged CMIF seemed to be a more robust connectivity metric to measure sleep depth (correlations of 0.78 and 0.84 with SWA and entropy, respectively), translating greater linear and nonlinear interdependences between brain regions especially during slow wave sleep. Potential changes of brain connectivity were also assessed throughout the night. Connectivity measures indicated a reduction of functional connectivity in N2 as sleep progresses. The validation of connectivity indexes is necessary because they can reveal the interaction between different brain regions in physiological and pathological conditions and help understand the different functions of deep sleep in humans.

Rapid eye movement (REM) sleep was discovered nearly 60 years ago. This stage of sleep accounts for approximately a quarter of total sleep time in healthy adults, and it is mostly concentrated in the second half of the sleep period. The majority of research on REM sleep has focused on neurocognition. More recently, however, there has been a growing interest in understanding whether obstructive sleep apnea (OSA) during the two main stages of sleep (REM and non-REM sleep) leads to different cardiometabolic and neurocognitive risk. In this review, we discuss the growing evidence indicating that OSA during REM sleep is a prevalent disorder that is independently associated with adverse cardiovascular, metabolic, and neurocognitive outcomes. From a therapeutic standpoint, we discuss limitations of continuous positive airway pressure (CPAP) therapy given that 3 or 4 h of CPAP use from the beginning of the sleep period would leave 75% or 60% of obstructive events during REM sleep untreated. We also review potential pharmacologic approaches to treating OSA during REM sleep. Undoubtedly, further research is needed to establish best treatment strategies in order to effectively treat REM OSA. Moreover, it is critical to understand whether treatment of REM OSA will translate into better patient outcomes.

Introduction: Obstructive sleep apnea (OSA) is a common sleep disorder associated with inconsistent cognitive consequences. Spatial disorientation increases with age and is an early sign of cognitive dysfunction in Alzheimer disease (AD). Sleep and related EEG oscillations, slow wave activity (SWA) and slow oscillations (SOs), are important for processing spatial memories, however it is not known if OSA-related sleep disruption effects spatial navigational memory processing in older adults.
Method(s): 42 older (age=66.5+/-7.9 years, 54.8% female) cognitively normal adults were recruited from the community. Participants performed timed trials on a 3D spatial maze navigational task and psychomotor vigilance test (PVT), before and after polysomnography (PSG). Maze completion time, PVT, sleep EEG macro and microstructure measures were compared between participants with and without OSA (AHI4%>=5.0/hour). Associations between sleep EEG microstructure (relative SWA (0.5-4Hz) & SOs (<1Hz) spectral power) and maze completion times were explored separately according to OSA diagnosis.
Result(s): Median AHI4% was 0.5/hour in those without OSA(n=30) and 10.7/hour in OSA(n=12). N1 sleep was significantly increased and N2 significantly decreased with OSA. No significant group differences in SWS, REM sleep or PVT performance were observed. There were no significant groups differences in pre-sleep maze completion time, whereas post-sleep maze performance was significantly different. On average participants without OSA continued to improve maze completion time across 3 morning trials whereas participants with OSA performed best on the first morning trial and performed worse on average with each subsequent trial (significant interaction between OSA group and morning trial number, p=0.016, Two Way Repeated Measures ANOVA). There were no significant differences in EEG microstructure observed between groups but in OSA, post-sleep maze performance showed a significant negative association with <1Hz spectral power at frontal (-0.78, p=0.007), central (-0.8, p=0.005) and occipital EEG (-0.71, p=0.02) during SWS.
Conclusion(s): Cognitively normal older adults with mild OSA demonstrated significantly worse morning spatial navigation performance compared to individuals without OSA after equivalent evening encoding. The associations between greater SOs and worse morning maze performance in OSA require replication

Introduction: We determined whether Obstructive Sleep Apnea (OSA) and beta-Amyloid Burden (Abeta) act additively or synergistically to promote conversion from cognitive normal (CN) to mild cognitive impairment (MCI) and from MCI to AD.
Method(s): In this longitudinal observational study, we examined CN (n=298) and MCI (n=418) older adults from the ADNI database (adni.loni.usc.edu). OSA was self-reported during a clinical interview. Brain Abeta was assessed using Florbetapir-PET imaging. The primary outcome of the analysis was conversion from CN to MCI (CN participants) and from MCI to AD (MCI participants). Participants were required to have a baseline and at least one follow-up clinical visit that identified their cognitive status. Logistic mixed-effects models with random intercept and slope were used to assess associations between OSA, Abeta, and risk of conversion from CN to MCI, and MCI to AD. All models included age at baseline, sex, APOE4 status, years of education, and their interactions with time.
Result(s): Of the 716 participants, 329 (46%) were women. The overall mean (SD) age was 74.7 (5.0) years, and the overall mean (SD) follow-up time was 5.5 (1.7) years (Range: 2.7 - 10.9 years). In CN participants at baseline, conversion to MCI was associated with both OSA (beta = 0.418; 95% CI, 0.133 to 0.703; P < .001) and higher Abeta-burden (beta = 0.554; 95% CI, 0.215 to 0.892; P < .001). The interaction of OSA and Abeta burden with time was significant (beta = 1.169, 95% CI, 0.776 to 1.562; P < .001), suggesting a synergistic effect. In MCI participants at baseline, conversion to AD was associated with both OSA (beta = 0.637; 95% CI, 0.291 to 0.982; P < .001) and higher Abeta-burden (beta = 1.061; 95% CI, 0.625 to 1.497; P < .001). The interaction of OSA and Abeta burden with time was significant (beta = 1.312, 95% CI, 0.952 to 1.671; P < .001), suggesting a synergistic effect.
Conclusion(s): In both CN and MCI elderly, Abeta modified the risk of progression to AD in OSA participants. OSA patients maybe more physiologically susceptible as Abeta load becomes increasingly abnormal