A W Varga

Obstructive sleep apnea severity affects amyloid burden in cognitively normal elderly a longitudinal study

Rationale: Recent evidence suggests that obstructive sleep apnea (OSA) may be a risk factor for developing mild cognitive impairment and Alzheimers disease. However, how sleep apnea affects longitudinal risk for Alzheimers disease is less well understood. Objectives: 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 were 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 and 90, were nondepressed, and had a consensus clinical diagnosis of cognitively normal. Cerebrospinal fluid amyloid &bgr; 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 (AHIall [F1,88 = 4.26; P < 0.05] and AHI4% [F1,87 = 4.36; P < 0.05]) were associated with annual rate of change of cerebrospinal fluid amyloid &bgr;42 using linear regression after adjusting for age, sex, body mass index, and apolipoprotein E4 status. AHIall and AHI4% were not associated with increases in ADPiB‐mask (Alzheimers disease vulnerable regions of interest Pittsburg compound B positron emission tomography mask) most likely because of the small sample size, although there was a trend for AHIall (F1,28 = 2.96, P = 0.09; and F1,28 = 2.32, not significant, respectively). Conclusions: 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.

Multichannel sleep spindle detection using sparse low-rank optimization

BACKGROUNDnAutomated single-channel spindle detectors, for human sleep EEG, are blind to the presence of spindles in other recorded channels unlike visual annotation by a human expert.nnnNEW METHODnWe propose a multichannel spindle detection method that aims to detect global and local spindle activity in human sleep EEG. Using a non-linear signal model, which assumes the input EEG to be the sum of a transient and an oscillatory component, we propose a multichannel transient separation algorithm. Consecutive overlapping blocks of the multichannel oscillatory component are assumed to be low-rank whereas the transient component is assumed to be piecewise constant with a zero baseline. The estimated oscillatory component is used in conjunction with a bandpass filter and the Teager operator for detecting sleep spindles.nnnRESULTS AND COMPARISON WITH OTHER METHODSnThe proposed method is applied to two publicly available databases and compared with 7 existing single-channel automated detectors. F1 scores for the proposed spindle detection method averaged 0.66 (0.02) and 0.62 (0.06) for the two databases, respectively. For an overnight 6 channel EEG signal, the proposed algorithm takes about 4min to detect sleep spindles simultaneously across all channels with a single setting of corresponding algorithmic parameters.nnnCONCLUSIONSnThe proposed method attempts to mimic and utilize, for better spindle detection, a particular human expert behavior where the decision to mark a spindle event may be subconsciously influenced by the presence of a spindle in EEG channels other than the central channel visible on a digital screen.

REM obstructive sleep apnea: risk for adverse health outcomes and novel treatments

Rapid eye movement (REM) sleep was discovered nearly 60xa0years 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 4xa0h 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.