Enhancing glaucoma prediction across ancestries: integrating functional annotation into multi-trait polygenic risk...

Area of Science:

• Ophthalmology
• Genetics
• Bioinformatics

Background:

• Primary open-angle glaucoma (POAG) is a major cause of irreversible blindness globally.
• Early detection of POAG is critical for preventing vision loss.
• Current polygenic risk scores (PRS) for POAG have limited predictive accuracy.

Purpose of the Study:

• To develop and evaluate a multi-trait polygenic probability risk score (PPRS) for enhanced POAG prediction.
• To integrate polygenic risk scores (PRS) for multiple glaucoma-related traits.
• To leverage functional genomic annotations and extensive genomic coverage for improved prediction across diverse ancestries.

Main Methods:

• Developed a multi-trait PRS (PPRS) integrating POAG, intraocular pressure (IOP), vertical cup-to-disc ratio (VCDR), and retinal nerve fiber layer thickness PRSs.
• Incorporated functional genomic annotations and >7 million variants for comprehensive genomic coverage.
• Validated the PPRS in UK Biobank (European ancestry) and the Mexican American Glaucoma Genetic Study (MAGGS, Latino ancestry).

Main Results:

• PPRS significantly improved POAG prediction compared to baseline models (AUC 0.814 Europeans, 0.802 Latinos vs. 0.721-0.753).
• Genetic contributions varied by ancestry, with IOP PRS strongest in Europeans and VCDR PRS in Latinos.
• The highest PPRS decile indicated substantially elevated POAG risk (74.4-fold in Europeans, 49.3-fold in Latinos) compared to the lowest decile.

Conclusions:

• Integrating multiple disease-relevant PRSs and functional annotations substantially enhances POAG genetic prediction.
• The PPRS approach demonstrates improved predictive power across diverse populations.
• Findings support the use of PPRS for targeted POAG screening and early intervention strategies.