Smartwatches could help predict who is likely to develop Parkinson’s disease

New research by Cardiff University has found that smartwatches could help predict who is likely to develop Parkinson’s disease, up to seven years before clinical diagnosis.

Published in the journal Nature Medicine, the team from the University’s Neuroscience and Mental Health Innovation Institute (NMHII) and the UK Dementia Research Institute, found that wearable tech that tracks accelerometery – the acceleration of motion – could be vital in identifying individuals in the general population who are most likely to develop Parkinson’s disease.

While Parkinson’s is largely recognised for its motor symptoms, such as tremors and slowness of movement, non-motor changes in an earlier stage of the disease called the prodromal stage, can predate the onset of these symptoms by many years.

Dr Kathryn Peall, Clinical Senior Lecturer in the NMHII, said: “Parkinson’s disease is a progressive movement disorder caused by the loss of brain cells that use dopamine. However, by the time of clinical diagnosis approximately 50-70% of these brain cells will have been lost. This makes early diagnosis of the disease difficult.

Using data from over 500,000 individuals aged 40-69 years through the UK Biobank which dated back to 2006, the researchers compared data on accelerometery to models based on genetics, lifestyle, blood biochemistry, and prodromal symptoms data.

They found that computer programmes trained using the accelerometery data were able to distinguish both patients with clinically diagnosed Parkinson’s disease and prodromal Parkinson’s disease from the general population. No other date type in their research performed better than accelerometery.

Dr Cynthia Sandor, Cardiff University’s Dementia Research Institute, said: “To our knowledge, this is the first demonstration of the clinical value of accelerometery-based biomarkers for prodromal Parkinson’s disease in the general population. Our results showed a pre-diagnosis reduction in acceleration was unique to Parkinson’s disease and was not observed for any other disorder that we examined.

“It suggests that accelerometery could be used to identify those at elevated risk for Parkinson’s disease on an unprecedented scale.

“In a clinical setting, continuous or semi-continuous monitoring of individuals can’t be achieved because of time, cost, accessibility and sensitivity.

“But smart devices capable of collecting accelerometer data are worn daily by millions of people.

“While much more work will need to be done before this is put into clinical practice, our discovery marks a significant leap forward in the early diagnosis of Parkinson’s disease, and suggests that devices such as  activity trackers and smartwatches could play a key role in clinical monitoring.”

The paper ‘Wearable movement-tracking data identify Parkinson’s disease years before clinical diagnosis’ was published in Nature Medicine.

This study was supported by UK Dementia Research Institute, funded by the Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK and by the Ser Cymru II programme which is part-funded by Cardiff University and the European Regional Development Fund through the Welsh Government. Funding was also received from Health and Care Research Wales.

SOURCE: https://www.cardiff.ac.uk/