Predicting risk for macular degeneration and glaucoma using blood fats and machine learning
Official title: Developing blood fatty acid-based algorithms as early predictors of macular degeneration and glaucoma: Applying machine learning to harmonized data from prospective cohort studies
Funded at Omegaquant Analytics, LLC · NIH-11313903 · Data updated 2026-11-12
A study will use blood fatty acids and machine learning to identify early signals of eye diseases like age-related macular degeneration and glaucoma using data from long-term health studies.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Omegaquant Analytics, LLC NIH-funded |
| Lab location | 1 site (Sioux Falls, United States) |
| Project start | August 1, 2026 |
| Project end | July 31, 2027 |
| Funding year | 2026 |
| Award (this year) | $320,864 |
| NIH project number | 1R41EY038578-01 |
| Project ID | NIH-11313903 on NIH RePORTER |
Who could benefit from this research
✓Could help
Adults at risk for AMD or glaucoma who consent to blood testing and the use of their health data for research.
✕Less likely to help
Individuals without risk factors or those unwilling to share blood samples and health data may not benefit.
What this research studies
This project aims to harness wearable-style data from blood tests and existing cohort information to build an algorithm that predicts who is at higher risk for AMD and glaucoma. Researchers will harmonize data from prospective studies and apply machine learning to uncover fatty acid patterns that may flag future eye disease before symptoms appear. The goal is to improve early intervention by identifying high-risk individuals so they can receive targeted monitoring and care. Participation would primarily involve providing blood samples and securely sharing health data from consenting individuals.
Why it matters
Potential benefit: If successful, the approach could enable earlier detection and personalized monitoring for AMD and glaucoma, potentially slowing or preventing vision loss.
How similar studies have gone: Prior studies suggest fatty acids can reflect eye health risk and machine learning can integrate complex data; this work builds on that by combining biomarkers with cohort data in a unified model.
Where this research is happening
-
Omegaquant Analytics, LLC
Sioux Falls, United States Active
Researchers
- Principal investigator: Harris, Bill — Omegaquant Analytics, LLC
- Study coordinator: Harris, Bill
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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.