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Eye scans detect signs of Parkinson’s disease up to seven years before symptoms emerge

Middle aged man undergoing an eye test with equipment

Research theme

Data, diagnostics and decision tools

People involved

Professor Alastair Denniston

Data, Diagnostics and Decision Tools Theme Lead

Markers showing the presence of Parkinson’s years before symptoms appear can be found in the eyes, new study proves.

A new collaborative study has identified markers indicating the presence of Parkinson’s disease in patients on average seven years before clinical presentation. This was the first time such markers were found several years before diagnosis, and these results were made possible by the largest study to date on retinal imaging in Parkinson’s disease. 

The study, which was published yesterday in Neurology and involved NIHR Birmingham Biomedical Research Centre (BRC) Professor Alastair Denniston, used artificial intelligence (AI) to identify markers of Parkinson’s in eye scans. To achieve this, the team analysed the AlzEye database and then repeated the analysis using the broader UK Biobank database of healthy volunteers, which confirmed the discoveries. Using these two extensive databases enabled the researchers to identify subtle markers of Parkinson’s disease, despite its relatively low prevalence in the population (0.1-0.2%). Generation of the AlzEye dataset was enabled by INSIGHT, the world’s largest database of retinal images and associated clinical data. 

“This work demonstrates the potential for eye data, harnessed by the technology to pick up signs and changes too subtle for humans to see. We can now detect very early signs of Parkinson’s, opening up new possibilities for treatment.”

– Professor Alastair Denniston 

The eye as a window to systemic disease 

This research builds on the emerging field of oculomics, where eye scans have previously revealed signs of other neurodegenerative conditions like Alzheimer’s, multiple sclerosis, and schizophrenia. Eye scans and eye data have also successfully indicated higher risks of high blood pressure, cardiovascular disease and strokes, and diabetes. 

Oculomics uses machine learning to efficiently analyse large numbers of high-resolution images of the retina obtained through techniques like optical coherence tomography (OCT), a type of 3D scan used routinely in eye care. In less than a minute, OCT provides a detailed cross-section of the retina, allowing researchers to examine layers of cells beneath the skin’s surface with incredible precision – down to a thousandth of a millimetre – in a non-invasive way. This allows not only to monitor eye health, but to also gain valuable insights into the overall health of the whole body. 

Leveraging the power of partnership 

This project was led by Siegfried Wagner and Pearse Keane of Moorfields Eye Hospital and UCL Institute of Ophthalmology. It was the result of a research collaboration between the NIHR (National Institute of Health and Social Care) Biomedical Research Centres at Moorfields Eye Hospital, University Hospital Birmingham, Great Ormond Street Hospital, Oxford University Hospitals and University College Hospital London.  

Study author Alastair Denniston, consultant ophthalmologist at University Hospitals Birmingham, Professor at the University of Birmingham’s Institute of Inflammation and Ageing, co-lead of the NIHR Birmingham BRC Data, Diagnostics and Decision Tools research theme, and part of the Biomedical Research Centre for Ophthalmology at Moorfields Eye Hospital/UCL said: “This work demonstrates the potential for eye data, harnessed by the technology to pick up signs and changes too subtle for humans to see. We can now detect very early signs of Parkinson’s, opening up new possibilities for treatment.”  

Siegfried Wagner, clinical research fellow at Moorfields Eye Hospital, UCL Institute of Ophthalmology researcher and principal investigator for this study, added: “I continue to be amazed by what we can discover through eye scans. While we are not yet ready to predict whether an individual will develop Parkinson’s, we hope that this method could soon become a pre-screening tool for people at risk of disease. Finding signs of a number of diseases before symptoms emerge means that, in the future, people could have the time to make lifestyle changes to prevent some conditions arising, and clinicians could delay the onset and impact of lifechanging neurodegenerative disorders.”