How can wearables revolutionise the detection of dementia?
Today we’re announcing an ambitious project that will transform research efforts and revolutionise the way we spot the early stages of diseases like Alzheimer’s. The Early Detection of Neurodegenerative diseases (EDoN) initiative is spearheaded by Alzheimer’s Research UK and brings together 14 leading research and support organisations, working to develop innovative ways to pick up these diseases in the brain years before the symptoms of dementia start.
The importance of early detection
At the moment, we can’t trial potential Alzheimer’s medications in people until they are showing symptoms of the disease. But these symptoms only emerge after the disease has been underway in the brain for as long as twenty years.
Much like trying to tackle a late-stage cancer, this is much more difficult task and it is likely to be a big part of why experimental Alzheimer’s drugs, which show promising signs of being able to tackle key disease-processes, haven’t yet been successful in clinical trials.
Many researchers believe that we may have already developed effective Alzheimer’s treatments that can slow the progression of the disease. But because we can’t identify people with the disease early enough, they are languishing in a lab instead of changing people’s lives.
We urgently need to improve disease detection to unlock the potential of future treatments, both for Alzheimer’s disease and for other diseases that cause dementia. And advances in technology offer an important opportunity to do just that – just as we have already seen in other areas of science.
The weather forecast
Weather forecasting works by carefully measuring factors like temperature, air pressure, humidity and many other atmospheric conditions, and then using this information to predict what is likely to come next.
Meteorologists can see what set of conditions have preceded particular weather events in the past and use that data to help determine what is likely to happen in the future.
The days of people poring over charts to make these predictions are long gone. Today, sophisticated computer programmes are able to integrate and analyse weather data to give (although it doesn’t always seem like it) astonishingly accurate forecasts.
When it comes to predicting dementia, we don’t have such a sophisticated approach. In fact, despite brain changes that lead to dementia getting underway many years earlier, currently we can only identify that a person has a disease like Alzheimer’s when symptoms are already impacting their life. This is a bit like forecasting a blizzard when you’re already tramping through snow.
But, just as there are many measurements we can take to predict weather, there are aspects of our behaviour and physical health that we can monitor to detect diseases that will go on to cause dementia.
Changes to our speech patterns, how active we are, the way we move, even how often we contact our friends, can all provide vital clues about the health of our brains. And now, digital technology has the potential to detect these changes, even when they are so subtle that they could never be spotted by the human eye.
Devices like smart watches and fitness apps are already generating mountains of data relevant to our health. And advances in big data and machine learning are providing tools to combine and analyse this data so that we can make sense of the new digital health landscape.
This month we have launched a global initiative to develop digital data “fingerprints” to pick up very early signs of neurodegenerative diseases like Alzheimer’s, which can be detected using wearable technologies.
EDoN brings together world leading experts in data science, digital technology and dementia. They are mapping changes in digital health measures, such as sleep, gait, eye movement and speech patterns, onto clinical changes such as those we see in brain scans.
Specialist data teams can then identify the pattern of change in digital health measures that appears when a person has the earliest biological signs of a disease.
This pattern of change forms a signal. If people are wearing a digital device that could measure all of these changes, we would be able to see when this signal appears in the data and identify someone with a disease like Alzheimer’s even though they are not showing any obvious symptoms.
EDoN will refine these signals by testing them in different groups of people and making sure they are as relevant and reliable as possible.
EDoN aims to move disease detection 10 -15 years earlier than today. A breakthrough like this would represent a research revolution allowing us to study and understand more about the crucial early stages.
Ultimately, the EDoN initiative aims to develop a device that would be provided to people by their doctor, who would be able to interpret the data to help identify people with the early signs of a disease. This would empower people to make lifestyle changes that could delay the onset of the symptoms of dementia.
Thanks to your support EDoN will radically speed up the search for effective treatments and make life-changing breakthroughs possible.
Taking part in EDoN
In the first part of the project we will be working with people who are already involved in ongoing research studies. We expect that people will be able to take part in the testing once it starts to be rolled out to a wider population, but this will likely be a few years down the road
Anyone who is interested in taking part in other dementia research studies, including research into early detection, can do so by registering to Join Dementia Research.
Find out more about EDoN at www.edon-initiative.org
Donate today to help make breakthroughs possible.
About the author
Dr Carol Routledge
Carol was the Director of Research at Alzheimer’s Research UK up to 2020. Carol moved to Alzheimer's Research UK from the Dementia Discovery Fund, where she was a Venture Partner with a key focus on identifying and developing novel disease-modifying mechanisms for the treatment of all types of dementia, sourcing opportunities from academic research groups and small companies.