Improving predictions for glaucoma risk using genetics and machine learning
Official title: Enhancing Glaucoma Risk Prediction through Advanced Genomics and Machine Learning
Funded at Massachusetts Eye and Ear Infirmary · NIH-10944600 · Data updated 2026-11-12
This study is looking at how we can better predict who might be at risk for glaucoma by using advanced technology and genetic information from over 68,000 patients, so that you can get a more personalized assessment and potentially catch the condition earlier for better treatment.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Massachusetts Eye and Ear Infirmary NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | September 1, 2024 |
| Project end | June 30, 2029 |
| Funding year | 2024 |
| Award (this year) | $715,098 |
| NIH project number | 1R01EY036518-01 |
| Project ID | NIH-10944600 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals with a family history of glaucoma or those who have been diagnosed with early-stage glaucoma.
✕Less likely to help
Patients with advanced glaucoma or those who do not have any genetic predisposition to the disease may not benefit from this research.
What this research studies
This research focuses on enhancing the prediction of glaucoma risk through advanced genomic techniques and machine learning. By analyzing genetic data and electronic health records from over 68,000 patients, the study aims to develop more accurate risk scores for glaucoma. The approach includes using natural language processing to refine disease phenotyping and leveraging large-scale genetic data from biobanks. Patients will benefit from improved individualized assessments that could lead to earlier diagnosis and better management of glaucoma.
Why it matters
Potential benefit: If successful, this research could lead to more accurate predictions of glaucoma risk, allowing for earlier intervention and potentially preventing vision loss.
How similar studies have gone: Previous research has shown promise in using genetic risk scores and machine learning for other conditions, indicating potential success for this novel approach in glaucoma.
Where this research is happening
-
Massachusetts Eye and Ear Infirmary
Boston, United States Active
Researchers
- Principal investigator: Zebardast, Nazlee — Massachusetts Eye and Ear Infirmary
- Study coordinator: Zebardast, Nazlee
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.