Using AI to analyze retina images for genetic insights into eye diseases

Deep-Learning-Derived Endophenotypes from Retina Images

NIH-funded research University of Texas Hlth Sci Ctr Houston · NIH-10877005

This study is looking at eye images to find out how our genes might be linked to common eye problems like diabetic retinopathy, using advanced computer technology to help improve how we understand and treat these conditions.

Quick facts

Grant typeR01 grant
Study typeNIH-funded research
Funding institutionUniversity of Texas Hlth Sci Ctr Houston NIH-funded
Lab location1 site (Houston, United States)
Project IDNIH-10877005 on NIH RePORTER

What this research studies

This research aims to develop an innovative artificial intelligence approach to genome-wide association studies (GWAS) by analyzing retina images to identify genetic factors linked to common eye disorders, particularly diabetic retinopathy. By utilizing deep learning algorithms, the study will extract detailed quantitative data from optical coherence tomography scans and fundus images, which will help uncover new genetic loci associated with these conditions. This method seeks to enhance the understanding of the genetic basis of eye diseases and improve diagnostic and therapeutic strategies. Patients' retina images will be crucial in this process, allowing for a more objective analysis of genetic influences on eye health.

Who could benefit from this research

Good fit: Ideal candidates for this research include individuals with diabetic retinopathy or those undergoing routine eye examinations who can provide retina images for analysis.

Not a fit: Patients without any eye diseases or those who do not have retina images available for analysis may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to improved diagnostic tools and targeted therapies for patients with eye diseases, particularly those affected by diabetic retinopathy.

How similar studies have performed: Previous research has shown promise in using AI and imaging data for genetic studies, indicating that this approach could yield significant insights into eye diseases.

Where this research is happening

Houston, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Conditions Candidate Disease Gene
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.