Faculty Bibliography

BACKGROUND:, P-tau, and T-tau with sleep spindle density and other biophysical properties of sleep spindles in a sample of cognitively normal elderly individuals. METHODS:, P-tau and T-tau. Seven days of actigraphy were collected to assess habitual total sleep time. RESULTS:, P-tau and T-tau. From the three, CSF T-tau was the most significantly associated with spindle density, after adjusting for age, sex and ApoE4. Spindle duration, count and fast spindle density were also negatively correlated with T-tau levels. Sleep duration and other measures of sleep quality were not correlated with spindle characteristics and did not modify the associations between sleep spindle characteristics and the CSF biomarkers of AD. CONCLUSIONS:Reduced spindles during N2 sleep may represent an early dysfunction related to tau, possibly reflecting axonal damage or altered neuronal tau secretion, rendering it a potentially novel biomarker for early neuronal dysfunction. Given their putative role in memory consolidation and neuroplasticity, sleep spindles may represent a mechanism by which tau impairs memory consolidation, as well as a possible target for therapeutic interventions in cognitive decline.

BACKGROUND:Many respiratory conditions have been attributed to toxic dust and fume exposure in World Trade Center (WTC) rescue and recovery workers, who frequently report symptoms of OSA. We examined the prevalence of new-onset OSA and tested if the prevalence and severity of OSA are related to the presence of chronic rhinosinusitis (CRS). METHODS:) enrolled in the WTC Health Program, excluding those with significant pre-September 11, 2001, snoring or prior CRS, underwent two nights of home sleep testing. OSA was defined as Apnea Hypopnea Index 4% ≥ 5 events/h or respiratory disturbance index of ≥ 15 events/h. CRS was assessed using nasal symptom questionnaires. RESULTS:The prevalence of OSA was 75% (25% no OSA, 46% mild OSA, 19% moderate OSA, and 10% severe OSA), and the prevalence of CRS was 43.5%. Compared with no CRS, new and worsening CRS was a significant risk factor for OSA with an OR of 1.80 (95% CI, 1.18-2.73; P = .006) unadjusted and 1.76 (95% CI, 1.08-2.88; P = .02) after adjustment for age, BMI, sex, gastroesophageal reflux disorder, and alcohol use. CONCLUSIONS:The high prevalence of OSA in WTC responders was not explained fully by obesity and sex. Possible mechanisms for the elevated risk of OSA in subjects with CRS include increased upper airway inflammation and/or elevated nasal/upper airway resistance, but these need confirmation.

RATIONALE/BACKGROUND:Obstructive Sleep Apnea (OSA) is associated with recurrent obstruction, sub-epithelial edema, and airway inflammation. The resultant inflammation may influence or be influenced by the nasal microbiome. OBJECTIVES/OBJECTIVE:To evaluate whether the composition of the nasal microbiota is associated with obstructive sleep apnea and inflammatory biomarkers. METHODS:Two large cohorts were utilized: 1) a discovery cohort of 472 subjects from the WTCSNORE cohort; and 2) a validation cohort of 93 subjects from the Zaragoza Sleep cohort. Sleep apnea was diagnosed using home sleep tests. Nasal lavages were obtained from cohort subjects to measure: 1) microbiome composition (based on 16S rRNA gene sequencing); 2) biomarkers for inflammation (inflammatory cells, IL-8, and IL-6). Longitudinal 3 months samples were obtained in the validation cohort including post-CPAP treatment when indicated. RESULTS:In both cohorts, we identified that: 1) severity of OSA correlated with differences in microbiome diversity and composition; 2) the nasal microbiome of subjects with severe OSA were enriched with Streptococcus, Prevotella, and Veillonella; 3) the nasal microbiome differences were associated with inflammatory biomarkers. Network analysis identified clusters of co-occurring microbes that defined communities. Several common oral commensals (e.g., Streptococcus, Rothia, Veillonella, and Fusobacterium) correlated with apnea-hypopnea index. Three months of treatment with CPAP did not change the composition of the nasal microbiota. CONCLUSIONS:We demonstrate that the presence of an altered microbiome in severe OSA is associated with inflammatory markers. Further experimental approaches to explore causal links are needed.

RATIONALE/BACKGROUND:Home sleep apnea testing (HSAT) typically does not include electroencephalogram (EEG) monitoring for sleep assessment. In patients with insomnia and low sleep efficiency, overestimation of the sleep period can result from absence of EEG, which will reduce sleep disordered breathing (SDB) indices and may lead to a false-negative result. OBJECTIVE:To validate a single channel frontal EEG for scoring sleep versus wake against full EEG during polysomnography, and then to examine the utility of adding this single channel EEG to standard HSAT to prevent false-negative results. METHODS:), to calculate AHI4 and RDI and the effect on OSA diagnosis and severity. Analyses were repeated in 69 patients with poor sleep suggesting insomnia plus Epworth Sleepiness Scale < 7 as well as in 38 patients ultimately shown to have sleep efficiency < 70% on HSAT with EEG. MEASUREMENTS AND MAIN RESULTS/RESULTS:Single channel and full EEG during polysomnography agreed on sleep versus wake in 92-95% of all epochs. HSAT without EEG overestimated the sleep period by 20% (VST = 440 ± 76 min vs TST = 356 ± 82 min), had a false-negative rate of 8% by AHI4 criteria, and underestimated disease severity in 11% of all patients. Sub-group analysis of patients with subjective poor sleep suggesting insomnia did not change the results. Patients later shown to have low sleep efficiency had lower SDB indices and a 20.8% false negative rate of sleep apnea diagnosis. CONCLUSIONS:were moderate, suggesting utility for ruling out OSA, there was a specific subgroup in whom there were significant missed diagnoses. However, we were unable to identify this subgroup a priori.

RATIONALE: Recent evidence suggests that Obstructive Sleep Apnea (OSA) may be a risk factor for developing Mild Cognitive Impairment and Alzheimer's disease. However, how sleep apnea affects longitudinal risk for Alzheimer's disease is less well understood. OBJECTIVE: To test the hypothesis that there is an association between severity of OSA and longitudinal increase in amyloid burden in cognitively normal elderly. METHODS: Data was derived from a 2-year prospective longitudinal study that sampled community-dwelling healthy cognitively normal elderly. Subjects were healthy volunteers between the ages of 55 to 90, were non-depressed and had a consensus clinical diagnosis of cognitively normal. CSF Amyloid beta was measured using ELISA. Subjects received Pittsburgh compound B Positron Emission Tomography scans following standardized procedures. Monitoring of OSA was completed using a home sleep recording device. MEASUREMENTS AND MAIN RESULTS: We found that severity of OSA indices (lnAHIall [F1,88=4.26, p<.05] and lnAHI4% [F1,87=4.36, p<.05]) were associated with annual rate of change of CSF Abeta42 using linear regression after adjusting for age, sex, BMI and ApoE4 status. LnAHIall and lnAHI4 were not associated with increases in ADPiB-mask most likely due to the small sample size although there was a trend for lnAHIall (F1,28=2.96, p=.09 and F1,28=2.32, n.s. respectively). CONCLUSION: In a sample of cognitively normal elderly, OSA was associated with markers of increased amyloid burden over the 2 year follow-up. Sleep fragmentation and/or intermittent hypoxia from OSA are likely candidate mechanisms. If confirmed, clinical interventions for OSA may be useful in preventing amyloid build-up in cognitively normal elderly.