The nexus of Aβ, aging, and sleep

Exploring the local field potential signal from the subthalamic nucleus for phase-targeted auditory stimulation in Parkinson's disease

BACKGROUND

Enhancing slow waves, the electrophysiological (EEG) manifestation of non-rapid eye movement (NREM) sleep, could potentially benefit patients with Parkinson's disease (PD) by improving sleep quality and slowing disease progression. Phase-targeted auditory stimulation (PTAS) is an approach to enhance slow waves, which are detected in real-time in the surface EEG signal.

OBJECTIVE

We aimed to test whether the local-field potential of the subthalamic nucleus (STN-LFP) can be used to detect frontal slow waves and assess the electrophysiological changes related to PTAS.

METHODS

We recruited patients diagnosed with PD and undergoing Percept™ PC neurostimulator (Medtronic) implantation for deep brain stimulation of STN (STN-DBS) in a two-step surgery. Patients underwent three full-night recordings, including one between-surgeries recording and two during rehabilitation, one with DBS+ (on) and one with DBS- (off). Surface EEG and STN-LFP signals from Percept PC were recorded simultaneously, and PTAS was applied during sleep in all three recording sessions.

RESULTS

Our results show that during NREM sleep, slow waves of the cortex and STN are time-locked. PTAS application resulted in power and coherence changes, which can be detected in STN-LFP.

CONCLUSION

Our findings suggest the feasibility of implementing PTAS using solely STN-LFP signal for slow wave detection, thus without a need for an external EEG device alongside the implanted neurostimulator. Moreover, we propose options for more efficient STN-LFP signal preprocessing, including different referencing and filtering to enhance the reliability of cortical slow wave detection in STN-LFP recordings.

Memory rescue and learning in synaptic impaired neuronal circuits

Neuronal impairment is a characteristic of Alzheimer's disease (AD), but its effect on neural activity dynamics underlying memory deficits is unclear. Here, we studied the effects of synaptic impairment on neural activities associated with memory recall, memory rescue, and learning a new memory, in an integrate-and-fire neuronal network. Our results showed that reducing connectivity decreases the neuronal synchronization of memory neurons and impairs memory recall performance. Although, slow-gamma stimulation rescued memory recall and slow-gamma oscillations, the rescue caused a side effect of activating mixed memories. During the learning of a new memory, reducing connectivity caused impairment in storing the new memory, but did not affect previously stored memories. We also explored the effects of other types of impairments including neuronal loss and excitation-inhibition imbalance and the rescue by general increase of excitability. Our results reveal potential computational mechanisms underlying the memory deficits caused by impairment in AD.

A Dichotomous Role for FABP7 in Sleep and Alzheimer's Disease Pathogenesis: A Hypothesis

Fatty acid binding proteins (FABPs) are a family of intracellular lipid chaperone proteins known to play critical roles in the regulation of fatty acid uptake and transport as well as gene expression. Brain-type fatty acid binding protein (FABP7) is enriched in astrocytes and has been implicated in sleep/wake regulation and neurodegenerative diseases; however, the precise mechanisms underlying the role of FABP7 in these biological processes remain unclear. FABP7 binds to both arachidonic acid (AA) and docosahexaenoic acid (DHA), resulting in discrete physiological responses. Here, we propose a dichotomous role for FABP7 in which ligand type determines the subcellular translocation of fatty acids, either promoting wakefulness aligned with Alzheimer's pathogenesis or promoting sleep with concomitant activation of anti-inflammatory pathways and neuroprotection. We hypothesize that FABP7-mediated translocation of AA to the endoplasmic reticulum of astrocytes increases astrogliosis, impedes glutamatergic uptake, and enhances wakefulness and inflammatory pathways via COX-2 dependent generation of pro-inflammatory prostaglandins. Conversely, we propose that FABP7-mediated translocation of DHA to the nucleus stabilizes astrocyte-neuron lactate shuttle dynamics, preserves glutamatergic uptake, and promotes sleep by activating anti-inflammatory pathways through the peroxisome proliferator-activated receptor-γ transcriptional cascade. Importantly, this model generates several testable hypotheses applicable to other neurodegenerative diseases, including amyotrophic lateral sclerosis and Parkinson's disease.

Intermittent hypoxia and sleep disruption in obstructive sleep apnea increase serum tau and amyloid-beta levels

Obstructive sleep apnea is characterized by intermittent hypoxia and sleep disruption, leading to accelerated neurodegenerative changes and cognitive decline. Serum amyloid-beta and tau proteins, which are markers for Alzheimer's disease, have been reported to increase in patients with obstructive sleep apnea. This study compared the serum levels of amyloid-beta proteins and tau proteins in 46 cognitively normal obstructive sleep apnea patients and 30 healthy controls. Sleep parameters and severity of obstructive sleep apnea were determined using overnight polysomnography. Serum levels of Aβ40, Aβ42, total tau and phosphorylated-tau were determined by enzyme-linked immunosorbent assay. Patients with obstructive sleep apnea had significantly higher median serum levels of Aβ40 (121.0 versus 78.3 pg ml^-1 ), Aβ42 (105.6 versus 18.6 pg ml^-1 ) and total tau (168.5 versus 10.9 pg ml^-1 ) than controls. Serum levels of phosphorylated-tau did not differ significantly between the two groups. Serum levels of amyloid and tau proteins correlated with parameters of nocturnal oxygen saturation. Rapid eye movement sleep was negatively correlated with total amyloid-beta proteins. We conclude that serum levels of amyloid-beta and total tau are higher in patients with obstructive sleep apnea and hypoxia as well as changes in sleep architecture associated with their increased levels. Patients with obstructive sleep apnea should be closely monitored for the signs of cognitive impairment. Obstructive sleep apnea is a modifiable risk factor, and its treatment may reverse neurodegenerative changes and prevent cognitive impairment.

Alzheimer's disease: Neurotransmitters of the sleep-wake cycle

With aging, our sleeping pattern alters. Elderly often wake unrested because their sleep time and sleep efficacy is reduced. In Alzheimer's disease (AD) patients, these alterations are even more pronounced and may further aggravate cognitive decline. Therefore, sleep disturbances greatly impact self-care ability, caregiver exhaustion and institutionalization rate. Reestablishing an effective sleep-wake cycle in these patients still remains an unresolved challenge, partly because sleep physiology is quite complex and multiple neurotransmitter systems contribute to a single process. Gaining a better understanding of sleep physiology will be crucial for further research. Conjointly, animal models, along with a multidisciplinary approach, will be of great value to establish a common ground between AD and sleep disturbances and work towards a potential therapeutic application.

Alzheimer's Disease and Sleep-Wake Disturbances: Amyloid, Astrocytes, and Animal Models

Sleep-wake abnormalities are common in patients with Alzheimer's disease, and can be a major reason for institutionalization. However, an emerging concept is that these sleep-wake disturbances are part of the causal pathway accelerating the neurodegenerative process. Recently, new findings have provided intriguing evidence for a positive feedback loop between sleep-wake dysfunction and β-amyloid (Aβ) aggregation. Studies in both humans and animal models have shown that extended periods of wakefulness increase Aβ levels and aggregation, and accumulation of Aβ causes fragmentation of sleep. This perspective is aimed at presenting evidence supporting causal links between sleep-wake dysfunction and aggregation of Aβ peptide in Alzheimer's disease, and explores the role of astrocytes, a specialized type of glial cell, in this context underlying Alzheimer's disease pathology. The utility of current animal models and the unexplored potential of alternative animal models for testing mechanisms involved in the reciprocal relationship between sleep disruption and Aβ are also discussed.Dual Perspectives Companion Paper: Microglia-Mediated Synapse Loss in Alzheimer's Disease by Lawrence Rajendran and Rosa Paolicelli.

Microglia-Mediated Synapse Loss in Alzheimer's Disease

Microglia are emerging as key players in neurodegenerative diseases, such as Alzheimer's disease (AD). Thus far, microglia have rather been known as modulator of neurodegeneration with functions limited to neuroinflammation and release of neurotoxic molecules. However, several recent studies have demonstrated a direct role of microglia in "neuro" degeneration observed in AD by promoting phagocytosis of neuronal, in particular, synaptic structures. While some of the studies address the involvement of the β-amyloid peptides in the process, studies also indicate that this could occur independent of amyloid, further elevating the importance of microglia in AD. Here we review these recent studies and also speculate about the possible cellular mechanisms, and how they could be regulated by risk genes and sleep. Finally, we deliberate on possible avenues for targeting microglia-mediated synapse loss for therapy and prevention.Dual Perspectives Companion Paper: Alzheimer's Disease and Sleep-Wake Disturbances: Amyloid, Astrocytes, and Animal Models by William M. Vanderheyden, Miranda M. Lim, Erik S. Musiek, and Jason R. Gerstner.

Does sleep disturbance affect the amyloid clearance mechanisms in Alzheimer's disease?

Sleep is an important factor that plays a key role in Alzheimer's disease pathogenesis. However, it is still unclear whether poor-quality sleep may overlap with sleep disturbances in the underlying dysfunctional mechanisms of amyloid beta (Aβ) clearance metabolism. Here, we aimed to evaluate the current evidence on the role of sleep deprivation in Aβ clearance metabolism. To that end, we discuss possible mechanisms underlying the bidirectional interaction between the sleep deprivation and Aβ clearance pathways.

Amyloid-β induces sleep fragmentation that is rescued by fatty acid binding proteins in Drosophila

Disruption of sleep/wake activity in Alzheimer's disease (AD) patients significantly affects their quality of life and that of their caretakers and is a major contributing factor for institutionalization. Levels of amyloid-β (Aβ) have been shown to be regulated by neuronal activity and to correlate with the sleep/wake cycle. Whether consolidated sleep can be disrupted by Aβ alone is not well understood. We hypothesize that Aβ42 can increase wakefulness and disrupt consolidated sleep. Here we report that flies expressing the human Aβ42 transgene in neurons have significantly reduced consolidated sleep compared with control flies. Fatty acid binding proteins (Fabp) are small hydrophobic ligand carriers that have been clinically implicated in AD. Aβ42 flies that carry a transgene of either the Drosophila Fabp or the mammalian brain-type Fabp show a significant increase in nighttime sleep and long consolidated sleep bouts, rescuing the Aβ42-induced sleep disruption. These studies suggest that alterations in Fabp levels and/or activity may be associated with sleep disturbances in AD. Future work to determine the molecular mechanisms that contribute to Fabp-mediated rescue of Aβ42-induced sleep loss will be important for the development of therapeutics in the treatment of AD. © 2016 Wiley Periodicals, Inc.

The sleep-wake cycle and Alzheimer's disease: what do we know?

Sleep-wake disturbances are a highly prevalent and often disabling feature of Alzheimer's disease (AD). A cardinal feature of AD includes the formation of amyloid plaques, associated with the extracellular accumulation of the amyloid-β (Aβ) peptide. Evidence from animal and human studies suggests that Aβ pathology may disrupt the sleep-wake cycle, in that as Aβ accumulates, more sleep-wake fragmentation develops. Furthermore, recent research in animal and human studies suggests that the sleep-wake cycle itself may influence Alzheimer's disease onset and progression. Chronic sleep deprivation increases amyloid plaque deposition, and sleep extension results in fewer plaques in experimental models. In this review geared towards the practicing clinician, we discuss possible mechanisms underlying the reciprocal relationship between the sleep-wake cycle and AD pathology and behavior, and present current approaches to therapy for sleep disorders in AD.

Quasi-supervised scoring of human sleep in polysomnograms using augmented input variables

The limitations of manual sleep scoring make computerized methods highly desirable. Scoring errors can arise from human rater uncertainty or inter-rater variability. Sleep scoring algorithms either come as supervised classifiers that need scored samples of each state to be trained, or as unsupervised classifiers that use heuristics or structural clues in unscored data to define states. We propose a quasi-supervised classifier that models observations in an unsupervised manner but mimics a human rater wherever training scores are available. EEG, EMG, and EOG features were extracted in 30s epochs from human-scored polysomnograms recorded from 42 healthy human subjects (18-79 years) and archived in an anonymized, publicly accessible database. Hypnograms were modified so that: 1. Some states are scored but not others; 2. Samples of all states are scored but not for transitional epochs; and 3. Two raters with 67% agreement are simulated. A framework for quasi-supervised classification was devised in which unsupervised statistical models-specifically Gaussian mixtures and hidden Markov models--are estimated from unlabeled training data, but the training samples are augmented with variables whose values depend on available scores. Classifiers were fitted to signal features incorporating partial scores, and used to predict scores for complete recordings. Performance was assessed using Cohen's Κ statistic. The quasi-supervised classifier performed significantly better than an unsupervised model and sometimes as well as a completely supervised model despite receiving only partial scores. The quasi-supervised algorithm addresses the need for classifiers that mimic scoring patterns of human raters while compensating for their limitations.