AI Test For Parkinson’s

Researchers, led by scientists at UCL and University Medical Center Goettingen, Germany, have developed an AI-enhanced blood test that can predict Parkinson’s in at-risk patients up to seven years before the onset of symptoms. 

What Is Parkinson’s? 

Parkinson’s disease is a condition caused by the progressive breakdown of certain nerve cells in the brain, resulting in a deficiency of the neurotransmitter dopamine. This results in symptoms including slowness of movement, increased muscle tension and tremors, and non-motor symptoms like olfactory (sense of smell) loss, plus sleep disorders and even depression. 

In the UK, approximately 1 in 350 adults is diagnosed with Parkinson’s disease, which translates to around 153,000 people currently living with the condition. Parkinson’s is the second most common neurodegenerative disease and is becoming increasingly common in the population. For example, estimates suggest that the number of people diagnosed will rise by nearly a fifth by 2025, reaching about 168,000 (Parkinson’s UK). 

The Challenge 

Up until now, the diagnosis has mostly been based on motor symptoms, which only occur when more than 70 percent of the dopamine-containing nerve cells have already been degraded. Also, there are currently no clues (biomarkers), which can indicate the specific disease process simply, directly, and at an early stage.  

The New Research 

The new cooperation project research, however, which involved researchers from the University Medical Center Göttingen (UMG), the Paracelsus-Elena-Klinik Kassel and University College London (UC), appears to have found a simple AI-enhanced way to diagnose the disease early. 

How? 

In the first stage, the researchers analysed blood samples from Parkinson’s patients and healthy study participants. This enabled them to identify 23 proteins that showed differences between the diseased and healthy participants and could therefore be considered biomarkers for the disease. 

Secondly, the 23 proteins were examined in the blood samples of people with isolated rapid eye movement (REM) sleep behavior disorder because this represents a high risk for Parkinson’s disease.  

The researchers then used AI to identify eight of the 23 proteins that could be used to predict Parkinson’s disease for 79 per cent of these ‘high-risk’ patients up to seven years before the onset of symptoms. 

How Will This Help? 

Dr Michael Bartl (a member of the UMG’s Translational Biomarker Research in Neurodegenerative Diseases working group and one of the first authors of the study) highlighted how the research findings will help, saying: “By determining eight proteins in the blood, we can identify potential Parkinson’s patients several years in advance. Drug therapies could be given at an earlier stage, which could possibly slow down the progression of the disease or even prevent it from occurring”. Dr Barl also added “We have not only developed a test, but also make the diagnosis using eight marker proteins that are directly linked to processes such as inflammation and the breakdown of non-functional proteins. These markers also represent potential targets for drug treatments”. 

What Does This Mean For Your Business? 

The development of a simple but AI-enhanced blood test that can indicate Parkinson’s at an early stage (seven years before symptoms) signifies a groundbreaking advancement not only in medical diagnostics but also in the broader application of AI technology.  

For businesses, particularly those in the healthcare and biotech sectors, this research highlights the transformative potential of AI in tackling many complex health challenges. The ability to predict Parkinson’s disease so early could lead to earlier interventions, potentially slowing disease progression and improving patient outcomes. This breakthrough demonstrates the crucial role AI can play in early disease detection and personalised medicine, opening new avenues for innovation and investment in healthcare technologies. 

For companies operating outside the healthcare sector, the implications are equally important. The research highlights how AI could address significant challenges across various industries, from health and business to climate and environmental management. For example, AI’s capability to analyse vast datasets and identify critical patterns could be leveraged to optimise operations, improve decision-making, and enhance sustainability efforts. Businesses can, therefore, draw inspiration from this study to explore AI applications that could revolutionise their own processes, leading to increased efficiency and competitive advantage. 

Also, this development highlights the importance of collaboration between academic institutions and industry. The partnership between UCL and the University Medical Centre Goettingen showcases how interdisciplinary cooperation can lead to significant technological advancements. Businesses should consider fostering similar collaborations to drive innovation and stay at the forefront of technological progress.