Wearables measuring sleep could provide Alzheimer’s opportunity

Science Translational Medicine: Reduced non-rapid eye movement sleep is associated with tau pathology in early Alzheimer’s disease

Scientists in the US have found that people who experience less deep sleep have higher levels of hallmark Alzheimer’s proteins in the brain. The findings are published today (Wednesday 9 January) in the journal, Science Translation Medicine.

Researchers at Washington University looked at 119 participants over the age of 60 and used a number of methods to measure their sleep and brain activity. This included asking study volunteers to wear watches to measure their sleep activity as well as using a portable, non-invasive method known as electroencephalography (EEG) to record the brain’s electrical activity.

Scientists also used state-of-the-art brain scans or spinal fluid samples to measure the levels of key proteins, amyloid and tau, that build up in the brain in Alzheimer’s disease.

The research team found that people who had less deep, slow-wave sleep, also had elevated levels of amyloid and tau in their brains.

Dr Laura Phipps of Alzheimer’s Research UK said:

“We know that there is a link between sleep problems and Alzheimer’s disease, but the reasons behind this relationship are complex.

“In this study scientists found that people who experience less deep sleep have more hallmark Alzheimer’s protein in their brains, but it doesn’t tell us whether these brain changes are caused by the sleep problems or vice versa.

“The researchers suggest that monitoring sleep patterns could help to assess Alzheimer’s risk or the progression of the disease, and wearable devices like those used in this study have the potential to generate vast amounts of data. While such digital data presents an opportunity to gain unprecedented insight into the factors that affect our health, we need to see this research repeated on a much larger scale to understand how the findings could be applied more widely.

“Alzheimer’s Research UK is now leading a major programme of work to harness the power of big data to revolutionise how we detect diseases like Alzheimer’s and wearable devices are likely to be key in understanding the subtle biological changes that could help us to diagnose people years earlier than we do today.”