Parkinson’s disease is a degenerative neurological ailment that causes movement problems as well as other symptoms. There is presently no medication available to stop or slow the growth of this disease. Much research is now ongoing to uncover relevant biomarkers for the early detection of Parkinson’s disease by studying drugs that may prevent further brain damage during the illness’s early stages, according to an article in Nature Medicine. It is critical to detect Parkinson’s disease as soon as possible so that therapy can begin.
According to a study published in Nature Medicine, prodromal symptoms might last for a long period before Parkinson’s disease is diagnosed. Researchers are integrating these symptoms with data on genetics, lifestyle, and blood biochemistry to see whether they may be used to predict Parkinson’s disease. There is still more to be done, but the results thus far are encouraging.
Previous study has shown that PD symptoms, such as slowness of movement and difficulty with ordinary tasks, might appear years before a diagnosis. As a result of this discovery, researchers are examining the feasibility of using wearable digital sensors to track gait in order to detect persons with Parkinson’s disease. Accelerometers, which monitor how quickly an object moves, are already widespread in high-tech wristwatches. Researchers predicted that wrist-worn accelerometers might identify Parkinson’s illness as early as 2021. One of the study’s flaws is that it only looked at those who already had Parkinson’s disease.
Using this as a foundation, researchers from Cardiff’s Neuroscience and Mental Health Innovation Institute and the UK Dementia Research Institute investigated whether wrist-worn accelerometers might be used to detect Parkinson’s disease years before a clinical diagnosis. The study relied on data acquired by the UK Biobank program from people aged 40 to 69 during 2006.
Between 2013 and 2015, some participants in the UK Biobank project (n=103,712) wore accelerometers to measure their levels of physical activity. The goal of this study was to see if accelerometer data might be used as an early indication of Parkinson’s disease by comparing it to data from those with the disease, those without it, and those with other neurodegenerative or movement problems.
The accelerometer-based Parkinson’s disease model’s accuracy was compared to models trained on known medical symptoms, genetics, lifestyle, or blood biochemistry. These findings revealed that a steady decrease in movement speed, or “acceleration,” might be seen years before a Parkinson’s diagnosis. Parkinson’s disease was the only neurodegenerative or movement ailment that showed this decrease in acceleration.
Acceleration data also indicated that those with Parkinson’s disease or in the prodromal stage slept for shorter periods of time and had less peaceful sleep overall than healthy controls. The findings proved the viability of utilizing accelerometer data to detect Parkinson’s disease in its early stages, far before symptoms appear. Models trained using known medical symptoms, genetics, lifestyle, or blood biochemistry performed worse than those trained using accelerometer data.
Dr. Walter Maetzler, a full professor for neurogeriatrics and the deputy chairman of the neurology department at the University Hospital in Kiel, Germany, who was not involved in the study but expressed surprise at “the strong results of this study,” expressed surprise at “the strong results of this study.” The ramifications of this groundbreaking discovery for Parkinson’s disease diagnosis and therapy are exciting. The combination of wearable technology and movement pattern analysis may allow for the early identification of Parkinson’s disease when medicines are more likely to be effective.
