Eye2Gene

A Web Tool For Genetic Prediction Of Inherited Retinal Disease Using Machine Learning

The Eye2Gene web interface.

Over 300 gene mutations are known to cause inherited retinal dystrophy and a genetic diagnosis is a significant step towards managing, and possibly treating, people's sight-loss. Eye2Gene makes genetic diagnosis faster and accessible to more IRD-affected families. Eye2Gene has been trained using the data of thousands of patients and has learned to distinguish between the different genetic causes using retinal images. You can try out a demo of Eye2Gene here by uploading a retinal scan. Please bear in mind however that this is a demo version of a research project prototype and not a clinically validated algorithm. We are currently seeking funding to achieve this.

Background

Early onset inherited retinal diseases, such as Stargardt disease and retinitis pigmentosa , can lead to permanent vision loss over a period of 10 to 30 years and are cumulatively the leading cause of blindness in the working-age population in the UK. Moorfields Eye Hospital, Europe's largest eye hospital (2M patients), has the largest and best characterised, genetically and phenotypically, cohort of IRD patients in the world (>9000), which includes 800 Stargardt and 600 retinitis pigmentosa patients. Discovering the causal genetic mutations in inherited retinal diseases is a prerequisite to determining prognosis and inclusion in any gene-directed clinical trials, such as gene therapy. Inherited retinal diseases often have characteristic patterns of progression due to gene expression timing and distribution in the different types of retinal cells. Experienced clinicians learn to diagnose these, using various imaging modalities, longitudinal information on the patient's symptoms, and genetic screening. However, the process is time-consuming and expensive, as it requires access to specialist centres, expensive clinical and genetic tests, and specialist training in electrophysiology, image interpretation and bioinformatics. Moreover, the spectrum of disease-causing mutations, which may be non-coding, and the genetic heterogeneity of similar clinical phenotypes is still poorly understood. Consequently, 40% of inherited retinal disease patients do not have a diagnosis because of lack of data or insight.

Leads

Nikolas Pontikos

Principal Investigator

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William Woof

Postdoc Medical Imaging and AI

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Advaith Yoga Veturi

Honorary Research Assistant Medical Imaging and AI

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We are always eager for hard-working & motivated people to come and work with us.

If you're interested in joining us, please send Nikolas Pontikos a quick email with a CV and personal statement