Doctor explaining results of MRI scan of brain to senior patient. Diagnosis of diseases for elderly people. Examination of brain, detecting stroke, dementia, head injures or neurological disorders.
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British investigators have harnessed artificial intelligence to create a groundbreaking blood test that can predict Parkinson’s disease up to seven years before symptoms emerge.

Researchers from University College London and University Medical Center Goettingen used machine learning to analyze a panel of eight blood-based biomarkers. The study involved examining blood samples from 72 patients with Rapid Eye Movement Behavior Disorder, a condition where individuals act out their dreams and which has a high likelihood of progressing to Parkinson’s.

Over a decade of follow-up, the AI tool’s predictions closely matched the clinical outcomes, correctly forecasting the development of Parkinson’s in 16 patients up to seven years before any symptoms were seen. This accuracy presents a promising horizon for early intervention strategies.

Professor Kevin Mills of UCL’s Great Ormond Street Institute of Child Health emphasized the necessity of early diagnosis for the effectiveness of emerging therapies. 

“As new therapies become available to treat Parkinson’s, we need to diagnose patients before they have developed symptoms,” said Mills. “We cannot regrow our brain cells and therefore we need to protect those that we have,” he said.

Dr. Michael Bartl of University Medical Center Goettingen and Paracelsus-Elena-Klinik Kassel, a co-first author of the study, highlighted the study’s broader implications. 

“By determining eight proteins in the blood, we can identify potential Parkinson’s patients several years in advance,” said Bartl. “This means that drug therapies could potentially be given at an earlier stage, which could slow down disease progression or even prevent it from occurring.”

For senior living operators, the results of this research could be profound. Early diagnosis can lead to better management of the condition, potentially reducing the overall burden of care and improving the quality of life for residents. Moreover, the  ability to identify at-risk individuals before symptoms arise could allow for proactive, personalized care plans and the integration of emerging therapies.

Professor Kailash Bhatia, co-author and part of the team from UCL Queen Square Institute of Neurology, is further validating the test’s accuracy in populations at high risk, such as those with genetic mutations linked to Parkinson’s. Additionally, efforts are underway to develop a simpler blood spot test, enabling easier and earlier diagnosis through a drop of blood mailed to a laboratory.

This pioneering blood test not only heralds a new era in the fight against Parkinson’s but also illustrates how cutting-edge technology can be harnessed to significantly improve senior care and health outcomes.

Parkinson’s disease, the fastest-growing neurodegenerative disorder globally, is a progressive condition caused by the death of dopamine-producing nerve cells in the substantia nigra region of the brain. 

The current treatment paradigm typically begins only after symptoms such as tremors, slow movement, and memory issues have appeared. 

Full study findings appear in Nature Communications.