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Approved Research

Development of a comprehensive predictive model for glaucoma occurrence

Principal Investigator: Dr Jin A Choi
Approved Research ID: 90981
Approval date: September 8th 2022

Lay summary


Glaucoma is the second-leading cause of blindness and the most common cause of irreversible blindness worldwide. A growing body of literature indicates that glaucoma is associated with many systemic vascular comorbidities, particularly in the aged. It is important to identify risk factors for the development of glaucoma in consideration of the polygenic risk scores and lifestyle behavioral factors. To this end, we will endeavor to construct a comprehensive predictive model for glaucoma development using multidimensional approach.

Project contents and scientific rationale:

The pathogenesis of glaucoma involves a composite of many contributing genetic, clinical, and environmental factors. For better understanding of these aspects, we will perform the following analyses using data from the UK Biobank:

First, we will develop a polygenic risk score describing the genetic component of risk for glaucoma occurrence. Because the genetic variants that are both known to contribute to glaucoma and common in the population have only modest effects on any individual patient's disease, we will use a polygenic risk score that incorporates multiple contributing genes in a single metric. We expect this score to be very helpful in classifying patients according to their degree of risk.

Second, we will develop a predictive model for glaucoma occurrence using systemic and local factors for better understanding of the nature of disease. The polygenic risk score generated will be integrated into the better classification of the patients for the occurrence of glaucoma.

Third, we plan to construct a comprehensive predictive model that combines all available data including lifestyle behavioral factors from the UK Biobank. This final model will build upon the first two and consider multidimensional risks for glaucoma occurrence - genetic, clinical, and environmental factors.

Project duration: We expect this project will take about three years to complete.

Public health impact: It is expected that utilizing the genomic, clinical, behavioral, and socio-economic data in the UK Biobank will help us to set an accurate predictive model that can precisely classify those at high risk for glaucoma occurrence, enabling for earlier preventive measure. In addition, we expect our comprehensive predictive model will provide new insights into the better understanding of glaucoma, a disease with heterogenous origin.