Mapping sleep's oscillatory events as a biomarker of Alzheimer's disease

Progress on early diagnosing Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects both cognition and non-cognition functions. The disease follows a continuum, starting with preclinical stages, progressing to mild cognitive and behavioral impairment, ultimately leading to dementia. Early detection of AD is crucial for better diagnosis and more effective treatment. However, the current AD diagnostic tests of biomarkers using cerebrospinal fluid and/or brain imaging are invasive or expensive, and mostly are still not able to detect early disease state. Consequently, there is an urgent need to develop new diagnostic techniques with higher sensitivity and specificity during the preclinical stages of AD. Various non-cognitive manifestations, including behavioral abnormalities, sleep disturbances, sensory dysfunctions, and physical changes, have been observed in the preclinical AD stage before occurrence of notable cognitive decline. Recent research advances have identified several biofluid biomarkers as early indicators of AD. This review focuses on these non-cognitive changes and newly discovered biomarkers in AD, specifically addressing the preclinical stages of the disease. Furthermore, it is of importance to explore the potential for developing a predictive system or network to forecast disease onset and progression at the early stage of AD.

Remote Wearable Neuroimaging Devices for Health Monitoring and Neurophenotyping: A Scoping Review

Digital health tracking is a source of valuable insights for public health research and consumer health technology. The brain is the most complex organ, containing information about psychophysical and physiological biomarkers that correlate with health. Specifically, recent developments in electroencephalogram (EEG), functional near-infra-red spectroscopy (fNIRS), and photoplethysmography (PPG) technologies have allowed the development of devices that can remotely monitor changes in brain activity. The inclusion criteria for the papers in this review encompassed studies on self-applied, remote, non-invasive neuroimaging techniques (EEG, fNIRS, or PPG) within healthcare applications. A total of 23 papers were reviewed, comprising 17 on using EEGs for remote monitoring and 6 on neurofeedback interventions, while no papers were found related to fNIRS and PPG. This review reveals that previous studies have leveraged mobile EEG devices for remote monitoring across the mental health, neurological, and sleep domains, as well as for delivering neurofeedback interventions. With headsets and ear-EEG devices being the most common, studies found mobile devices feasible for implementation in study protocols while providing reliable signal quality. Moderate to substantial agreement overall between remote and clinical-grade EEGs was found using statistical tests. The results highlight the promise of portable brain-imaging devices with regard to continuously evaluating patients in natural settings, though further validation and usability enhancements are needed as this technology develops.

The effectiveness of exercise interventions targeting sleep in older adults with cognitive impairment or Alzheimer's disease and related dementias (AD/ADRD): A systematic review and meta-analysis

Sleep loss is associated with reduced health and quality of life, and increased risk of Alzheimer's disease and related dementias. Up to 66% of persons with Alzheimer's disease and related dementias experience poor sleep, which can predict or accelerate the progression of cognitive decline. Exercise is a widely accessible intervention for poor sleep that can protect against functional and cognitive decline. No previous systematic reviews have investigated the effectiveness of exercise for sleep in older adults with mild cognitive impairment or Alzheimer's disease and related dementias. We systematically reviewed controlled interventional studies of exercise targeting subjectively or objectively (polysomnography/actigraphy) assessed sleep in persons with mild cognitive impairment or Alzheimer's disease and related dementias. We conducted searches in PubMed, Embase, Scopus and Cochrane-Library (n = 6745). Nineteen randomised and one non-randomised controlled interventional trials were included, representing the experiences of 3278 persons with mild cognitive impairment or Alzheimer's disease and related dementias. Ten had low-risk, nine moderate-risk, and one high-risk of bias. Six studies with subjective and eight with objective sleep outcomes were meta-analysed (random-effects model). We found moderate- to high-quality evidence for the beneficial effects of exercise on self-reported and objectively-measured sleep outcomes in persons with mild cognitive impairment or Alzheimer's disease and related dementias. However, no studies examined key potential moderators of these effects, such as sex, napping or medication use. Our results have important implications for clinical practice. Sleep may be one of the most important modifiable risk factors for a range of health conditions, including cognitive decline and the progression of Alzheimer's disease and related dementias. Given our findings, clinicians may consider adding exercise as an effective intervention or adjuvant strategy for improving sleep in older persons with mild cognitive impairment or Alzheimer's disease and related dementias.

Which Are the Most Reliable Sleep Parameters that Predict Cognitive Decline and Alzheimer's Disease?

Sleep disorders can represent an independent risk factor for cognitive decline and Alzheimer's disease (AD). It remains to be clarified if specific sleep parameters could be considered biomarkers of AD-related neurodegeneration. Several studies solely investigated the results of cross-sectional research, without providing conclusive evidence. Few longitudinal studies showed some inconsistencies in macrostructural and microstructural sleep findings. Methodological heterogeneity among studies can explain the discrepancies in the results. Moreover, the polysomnographic findings are usually related to only one-night recording. The combination of actigraphic recordings with sleep EEG monitoring for some consecutive days should be considered in future research.