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Editors Selection IGR 26-1

Basic Science: Do your genes predict your visual field loss pattern?

Comment by Mahantesh Biradar & Anthony Khawaja on:

125211 Genetic Risk for Open-Angle Glaucoma Subtypes Is Associated with Specific Visual Field Defect Classes, Sekimitsu S; Selvan K; Zhao Y et al., Ophthalmology, 2025; 132: 980-987

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Understanding the genetic risk for glaucoma has advanced rapidly, yet there remains limited knowledge regarding how specific genetic profiles may influence different clinical patterns of glaucoma. In particular, the connections between the genetic architecture of high-tension glaucoma (HTG) and normal-tension glaucoma (NTG) and their distinct clinical manifestations are not fully defined. Sekimitsu et al. (Ophthalmology, 2025) directly address this gap by examining associations between polygenic risk scores (PRSs) for glaucoma subtypes and specific visual field (VF) defect patterns.

The authors applied unsupervised machine learning algorithms—previously validated for classifying VF loss¹—to a large dataset of 79,357 VF results from 11,572 patients with primary open-angle glaucoma (POAG). They identified nine archetypal VF patterns and evaluated their association with PRSs for POAG, NTG, and HTG. Notably, higher POAG and NTG PRSs were most strongly associated with paracentral VF loss, while higher HTG genetic risk correlated with total VF loss but not paracentral defects. These findings suggest that the genetic underpinnings of HTG and NTG may not only affect disease susceptibility but also influence the spatial distribution of functional damage.

This work stands out due to its large sample size and its linkage of genetic risk profiles with detailed functional phenotypes. Previous research has shown that PRSs can stratify POAG and NTG risk at the population level^{2, 3}, but their relevance to functional outcomes has been less clear. By demonstrating associations between PRSs and specific VF archetypes, Sekimitsu et al. advance our understanding of the heterogeneity of glaucoma and move toward more nuanced risk stratification. The definition of NTG varied across cohorts, particularly as untreated intraocular pressure data were unavailable in some datasets and ICD codes were used instead of IOP-based criteria. Generalizability may be limited by the underrepresentation of non-European ancestries and the lack of adjustment for environmental factors, gene–environment interactions, and social determinants of health.

While this work may not immediately impact clinical care, it supports the concept that POAG is multiple distinct diseases with different genetic underpinnings. This provides hope that, in the future, we may be able to use genetic prediction models to identify clinically meaningful subtypes of POAG. This may include distinguishing slow vs fast progressors or identifying subtypes that will respond especially well to certain treatments.

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