A major global study on eye health has uncovered important new information about retinal thickness, which may help in the early detection of conditions such as type 2 diabetes, dementia, and multiple sclerosis.
Conducted by researchers at WEHI, this study employed advanced artificial intelligence to analyze over 50,000 eyes, generating detailed maps of the retina. This approach allows for a deeper understanding of how variations in retinal structure are linked to different diseases.
The results of this research suggest that routine eye imaging could serve as an effective tool for screening and managing various health issues, similar to the role of mammograms in breast cancer detection.
Key Points
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Utilizing innovative AI technology has resulted in the creation of the most detailed retina maps ever.
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Researchers at WEHI have connected retinal thinning to a variety of diseases while also discovering new genetic factors affecting retinal thickness.
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This research may set the foundation for implementing routine eye imaging as a screening method for diseases.
A Gateway to Understanding the Brain
The retina is an integral part of the central nervous system, which includes the brain and spinal cord. Many illnesses stem from the degeneration or disruption of this essential system, encompassing neurodegenerative diseases like dementia and metabolic disorders such as diabetes.
Globally, neurological conditions rank among the top causes of disability and health issues, affecting over 3 billion individuals, or 43% of the world’s population, with brain-related ailments.
Dr. Vicki Jackson, the lead researcher at WEHI, expressed that these findings expand the potential for utilizing retinal imaging as a means to understand and manage central nervous system conditions.
“Our research showcases that retinal imaging can provide insights into the brain by identifying associations with neurological disorders like multiple sclerosis and other conditions,” stated Dr. Jackson, who specializes in statistics and genetics.
“The detailed measurements from our maps reveal essential new connections between retinal thinning and a variety of common diseases.”
The study also unveiled new genetic influences on retinal thickness, which likely contribute to how an individual’s retina grows and develops.
“This research highlights the potential for retinal thickness to serve as a diagnostic indicator, aiding in the detection and monitoring of multiple diseases. We can now identify specific areas of the retina that exhibit critical changes linked to certain conditions.”
The international research team, under the direction of WEHI, applied AI techniques to large population data of retinal imaging, comparing it with genetic and health information to discover unprecedented disease links.
The findings resulted in 50,000 detailed retina maps with measurements taken at over 29,000 distinct locations, identifying retinal thinning associated with 294 significant disease-related genes.
Accelerating the Diagnostic Future with AI
Professor Melanie Bahlo AM, who led the study and is a bioinformatician, mentioned that while previous research indicated relationships between retinal thickness and diseases, her team’s findings, powered by AI, offer deeper insights into the complex spatial structure of the retina and its implications for health.
“Technological advancements like AI spark new discoveries. When paired with talented researchers, there’s a remarkable ability to translate vast population data into significant insights,” noted Professor Bahlo, who runs a lab at WEHI.
“We are living in a unique time where the synergy of technology, big data, and exceptional talent is leading to advancements in human health.”
The study further supports the emerging field of oculomics, which focuses on using eye examinations to diagnose health conditions as a powerful and non-invasive method for predicting and diagnosing diseases.
Numerous collaborators participated in this research, including the UK Biobank (for retinal imaging), the University of Washington (for AI processing of imaging data), the Lowy Medical Research Institute (for disease association analysis), as well as Moorfields Eye Hospital and University College London (for clinical expertise).
This research has received generous funding from the Lowy Medical Research Institute.
