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.

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

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.

Blacks are at greater risk for lower sleep quality and higher risk for obstructive sleep apnea (OSA) than other racial groups. In this study, we summarize the development of a tailored website including visuals, key messages, and video narratives, to promote awareness about sleep apnea among community-dwelling blacks. We utilized mixed methods, including in-depth interviews, usability-testing procedures, and brief surveys (n = 9, 55% female, 100% black, average age 38.5 years). Themes from the qualitative analysis illuminated varied knowledge regarding OSA symptoms and prevalent self-reported experience with sleep disturbance and OSA symptoms (e.g., snoring). On a scale from 1 (not at all) to 5 (very high), participants provided favorable ratings of website usefulness (mean = 4.9), user friendliness (mean = 4.9) and attractiveness (mean = 4.3). Our findings suggest although tailored health communication has potential for serving as a tool for advancing health equity, usability-testing of health materials is critical to ensure that culturally and linguistically tailored messages are acceptable and actionable in the intended population.

Mobile technology has been designed to serve a number of functions relating to health, but we know little about individuals who use these tools to track sleep. This study utilized data from a cross-sectional, geographically diverse survey of adults in the USA (N = 934). Among the sample, 28.2% (n = 263) report current use of a mobile phone for sleep tracking. Income and gender were significant correlates of sleep tracking (p < 0.05). Compared to a poor diet, a reported "excellent" diet was associated with sleep tracking (p < 0.05). Interestingly, compared to individuals who never smoke, report of smoking "everyday" was associated with sleep tracking (p < 0.05). Finally, individuals who reported current use of their mobile device for other health functions (e.g., chat with their doctor or log symptoms) were more likely to report sleep tracking on their mobile device (p < 0.05). Results appear to suggest sleep tracking is common among individuals with good general health.

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

Introduction: We determined whether the co-occurrence of OSA and hypertension interact synergistically to promote beta-Amyloid burden and cognitive decline in clinically normal older adults Methods: Prospective longitudinal study utilizing NYU cohort of community-dwelling cognitively-normal elderly, with baseline and at least one follow-up of CSF-Abeta42 (measured using ELISA), and neuropsychological visits. OSA was defined using AHI4%. Hypertension diagnosis was according to AHA-guidelines. Cognitive variables assessed included Logic-2, Animal-Fluency [AF], Vegetable-Fluency [VF]), Boston-Naming-Test [BNT], Digit-Symbol-Substitution-Test [DSST], Trails Making Test-A and B [TMT-A and B]). Linear mixed-effects models with random intercept and slope were used to assess associations between OSA, hypertension, and longitudinal changes in CSF-Abeta and cognition, controlling for age-at-baseline, sex, APOE4-status, years-of-education, and their interactions with time.
Result(s): Of the 98 participants, 63 (64.3%) were women. The mean (SD) age was 69.6 (7.3) years and follow-up time was 2.46 (0.64) years. OSA and hypertension were each associated with faster rate-of-change in CSF-Abeta42 (beta = -3.11; 95%CI, -3.71, -2.51; and beta= -2.82, 95% CI -3.29, -2.35, P < .01 for both respectively). The interaction of OSA and hypertension with time was significant (beta= -1.28, 95% CI -1.78 to -0.78, P < .01) suggesting a synergistic effect. No significant associations were seen between annual-changes in CSF-Abeta42 and cognitive-decline. However, faster decline in VF, and DSST were associated with OSA (beta = -0.054; 95%CI, -0.094, -0.013; P = .02; beta = -0.058; 95%CI, -0.084, -0.033; P < .05 for both respectively), and with hypertension (beta = -0.048; 95%CI, -0.079, -0.017; P = .04; beta = -0.078; 95%CI, -0.098, -0.057; P = .002; respectively). The interaction of OSA and hypertension with time was significant for both VF and DSST (beta = -0.033, 95%CI, -0.048, -0.018; P < .001 and beta = -0.040, 95%CI, -0.064, -0.016; P < .001, respectively), suggesting a synergistic effect.
Conclusion(s): In cognitive-normal elderly OSA individuals, vascular risk may complement AD-biomarkers in assessing risk of prospective cognitive-decline in preclinical AD

Introduction: Assessment of habitual sleep duration and obstructive sleep apnea (OSA) severity and their relationships with subjective sleepiness and vigilance in cognitively normal older subjects is limited.
Method(s): Data are from subjects participating in an ongoing longitudinal study of sleep and Alzheimer's disease biomarkers in cognitively normal elderly subjects (CDR=0, MMSE>=24). Demographic data, comorbidities, medications and Apolipoprotein E4 (ApoE4) genotype were collected. Habitual nocturnal sleep duration was measured by 7-day actigraphy. OSA was evaluated from in-laboratory nocturnal polysomnography (NPSG) and/or 2-night home-sleep test (HST). Excessive daytime sleepiness (EDS) was determined from Epworth Sleep Scale (ESS), and vigilance by 20-min psychomotor vigilance test (PVT). OSA was defined by Apnea hypopnea Index 4 (AHI4)>=5 and/or respiratory disturbance index (RDI)>=15.
Result(s): Among 267 subjects (age 68.4+/-8.1 years, BMI 26.3+/-5 kg/ m2, 36.4% male), 185 underwent HST alone, 11 NPSG alone, and 71 both HST and NPSG. 58.7% of subjects had OSA. Of these, 67.3% had AHI4<15/hr and 32.7% had AHI4>=15/hr. Sleep duration was 7+/-1.1 hours. Median ESS was 5 (IQR 5), with 16.4% subjects having ESS>=10. Median PVT lapses was 3.2 (IQR 2.7). ESS and PVT showed no relationship (rho=0.093, p-value 0.14). There was a significant inverse correlation between actigraphy sleep duration and ESS (rho=-0.348, p-value<0.01), but not lapses. AHI4 (rho=0.188, p-value<0.01) and RDI (rho=0.166, p-value 0.01) from HST were correlated with ESS but not PVT. Sleep duration explained 12% of variance in ESS even after adjusting for AHI4. In 82 subjects with NPSG, we found no correlation between ESS or PVT and in-lab total sleep time, sleep stages or OSA severity. No differences in sleepiness were seen in ApoE4 carriers compared to others.
Conclusion(s): Our data confirm that OSA is highly prevalent in cognitively normal elderly subjects. We found limited subjective sleepiness, even in those with OSA. Typical sleep duration measured in the home was the main predictor of sleepiness. To date, conventional NPSG metrics do not explain the lack of EDS in OSA in this group