Can a Simple Eye Test Predict Parkinson’s Disease?

Parkinson’s disease is a progressive neurodegenerative disorder. It is marked by the gradual loss of nerve cells, especially those that produce dopamine. As the disease evolves, it presents as a movement disorder, with symptoms that significantly impact daily activities. Initially, individuals might experience tremors, difficulty moving, dizziness, and balance problems. With progression, symptoms include slow movements, diminished voluntary action, and issues like rigidity, tremors, and postural instability.

Elderly hands
Photo by Pixabay: https://www.pexels.com/photo/man-hands-waiting-senior-33786/

Globally, the disease affects over 10 million people. Although no cure exists, there are strategies to manage its symptoms. These include medications, surgeries, and lifestyle alterations, such as physical therapy and regular exercise. The origins of Parkinson’s are multifaceted, involving both genetics and environmental factors. Experts have associated certain genetic mutations with the disease, and around 15% of those diagnosed report a family history. Additionally, exposure to substances like pesticides, metals, and solvents might increase the risk.

Traditionally, diagnosis of Parkinson’s relies on observing a patient’s symptoms. This is because many other diagnostic tools are either in their experimental stages or are prohibitively expensive. This diagnostic challenge is exacerbated when early symptoms are subtle and easily overlooked.

However, a recent study in Neurobiology has shed light on the potential of retina imaging for early detection. Post-mortem analyses have indicated lower dopamine content in the retinas of Parkinson’s patients. Researchers, building on this observation, proposed that non-invasive retina scans might reveal abnormalities stemming from this deficiency.

The Study

The research team speculated that Parkinson’s onset could be tied to changes in retinal thickness. Using data from two retrospective cohorts, they examined retina scans concerning Parkinson’s diagnoses. Their analysis focused on the thickness of three distinct retina layers. They determined the presence of Parkinson’s using publicly accessible hospital admission records.

This post may interest those with a higher polygenic risk score for Parkinson’s disease.

The primary dataset included over 150,000 patients aged 40 and above. Among these, 700 were diagnosed with Parkinson’s. When compared to about 100,000 controls, two specific retinal layers – the ganglion cell-inner plexiform layer (GCIPL) and the inner nuclear layer (INL) – were noticeably thinner in Parkinson’s patients.

This observation remained consistent even after adjusting for factors such as age, gender, ethnicity, and other health conditions such as diabetes and hypertension. The study involved a secondary dataset comprising over 50,000 individuals. Of these, 53 were diagnosed with Parkinson’s after their initial retina scan. Statistical analysis highlighted a connection: individuals with thinner GCIPL and INL layers exhibited a heightened risk of developing Parkinson’s, typically around seven years after their scan.

Summary

Prior studies had already suggested a link between GCIPL thinning and Parkinson’s. However, this research is significant in its identification of the role of the INL. The potential to detect these changes in the retina well before the disease manifests offers a promising avenue for early detection. This could pave the way for timely interventions through simple eye exams and better patient outcomes.

Retina
Retina. Pexels.com
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Citation

Wagner SK, Romero-Bascones D, Cortina-Borja M, Williamson DJ, Struyven RR, Zhou Y, Patel S, Weil RS, Antoniades CA, Topol EJ, Korot E, Foster PJ, Balaskas K, Ayala U, Barrenechea M, Gabilondo I, Schapira AH, Khawaja AP, Patel PJ, Rahi JS, Denniston AK, Petzold A, Keane PA; for UK Biobank Eye & Vision Consortium. Retinal Optical Coherence Tomography Features Associated With Incident and Prevalent Parkinson Disease. Neurology. 2023 Aug 21:10.1212/WNL.0000000000207727. doi: 10.1212/WNL.0000000000207727. Epub ahead of print. PMID: 37604659.

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