Researchers from University College London (UCL) and University Medical Center Goettingen have introduced a novel blood test that utilizes artificial intelligence (AI) to detect Parkinson's disease up to seven years before the onset of symptoms.
This advance could transform the early diagnosis and treatment of Parkinson's, the fastest-growing neurological condition globally, which currently affects nearly 10 million people.
NES TSIONA, ISRAEL - JANUARY 22: A laboratory technician places human blood samples on an automated testing line at the Maccabi Health Services HMO central testing laboratory January 22, 2006 in Nes Tsiona which is located in central Israel. Photo by David Silverman/Getty Images
How Parkinson's Disease Impacts the Brain
Parkinson's disease, which usually occurs in older people, is a progressive disorder resulting from the death of nerve cells in the brain's substantia nigra, which controls movement.
These nerve cells either die or become impaired due to the buildup of a protein called alpha-synuclein, leading to the loss of the critical neurotransmitter dopamine.
Traditionally, diagnosis relies on observing movement-related symptoms such as tremors, stiffness, and slowness of movement. By this stage, significant brain damage has often already occurred, limiting treatment effectiveness.
AI Blood Test Offers 100% Accuracy in Detecting Parkinson's Disease
The new AI-powered blood test, developed by the UCL and University Medical Center Goettingen team, promises to revolutionize this process. It analyzes a panel of eight blood-based biomarkers known to be altered in Parkinson's patients.
"As new therapies become available, we need to diagnose patients before they develop symptoms. We cannot regrow brain cells, so protecting existing ones is crucial," Professor Kevin Mills, a senior author of the study explains the research in a press release.
The blood test's initial clinical trials demonstrated a remarkable 100% accuracy in diagnosing Parkinson's disease. To evaluate the test's predictive capabilities, researchers focused on patients with Rapid Eye Movement Sleep Behavior Disorder (iRBD), a condition where individuals physically act out their dreams. Approximately 75-80% of iRBD patients eventually develop synucleinopathies, a group of brain disorders that includes Parkinson's.
Using AI, the researchers analyzed blood samples from these patients and identified that 79% of the iRBD patients' blood profiles matched those of individuals with Parkinson's.
The team followed these patients for ten years, and the AI's predictions held, accurately identifying 16 individuals who developed Parkinson's, some as early as seven years before any symptoms emerged.
Early detection through this blood test could allow for timely medical intervention, potentially slowing or even halting the disease's progression.
Dr. Michael Bartl, co-first author of the study, emphasized that by determining 8 proteins in the blood, potential Parkinson's patients could be identified years in advance, allowing drug therapies to be given at an earlier stage.
The research team is actively refining the test and exploring simpler methods, such as a blood spot test that could allow for even earlier detection.
Speaking with Interesting Engineering, Professor Mills expressed optimism that with sufficient funding, this may be possible within two years. The timeline for the simpler test to become widely available is estimated to be between 18 months to five years, depending on financial support.
