A groundbreaking study led by the Walter and Eliza Hall Institute of Medical Research (WEHI) has revealed new insights into retinal thickness, highlighting its potential as an early diagnostic marker for diseases such as type 2 diabetes, dementia, and multiple sclerosis.
Utilizing advanced artificial intelligence (AI) technology, researchers analyzed retinal images from over 50,000 individuals, creating the most detailed maps of the retina to date. These findings could transform routine eye examinations into powerful screening tools for early disease detection, similar to how mammograms help in diagnosing breast cancer.
Retinal Imaging: A Window Into Systemic Health
The retina, an integral part of the central nervous system, shares connections with the brain and spinal cord. Many neurological and metabolic diseases, including dementia and diabetes, are associated with disruptions in this system. With over 3 billion people worldwide affected by brain-related conditions, researchers believe retinal imaging could serve as a critical non-invasive diagnostic tool.
Dr. Vicki Jackson, a lead researcher at WEHI, emphasized the significance of the findings, stating that retinal thickness could serve as a diagnostic biomarker to detect and track disease progression. The study also uncovered genetic factors that influence retinal thickness, potentially impacting retinal development and disease susceptibility.
“We can now pinpoint specific locations in the retina that exhibit key changes in various diseases, offering new possibilities for early diagnosis and management,” Dr. Jackson said.
AI Technology Accelerating Disease Detection
Led by bioinformatician Professor Melanie Bahlo AM, the research team leveraged AI technology to analyze large-scale population data, comparing retinal imaging with genetic and health information. This approach enabled researchers to identify 294 genes associated with retinal thinning, linking them to disease processes.
“AI is revolutionizing medical discovery, allowing us to interpret vast amounts of data with unprecedented accuracy,” said Prof. Bahlo. “This fusion of technology, big data, and human expertise is unlocking insights that were previously unattainable.”
Advancing the Field of Oculomics
The study contributes to the expanding field of oculomics, which explores how eye-related data can be used to diagnose and predict systemic diseases. By identifying specific retinal changes linked to various conditions, researchers hope to integrate retinal imaging into routine healthcare practices for early intervention and improved patient outcomes.
The international study involved collaborations with leading institutions, including the UK Biobank (retinal imaging), University of Washington (AI processing), Lowy Medical Research Institute (disease association analysis), Moorfields Eye Hospital, and University College London. The research was funded by the Lowy Medical Research Institute.
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