Multimodal Prediction of Primary Open-Angle Glaucoma Using Genetic Risk Scores and Clinical Features in a High-Risk African Ancestry Cohort

We developed four polygenic risk scores (PGS) for primary open-angle glaucoma (POAG), which is the leading cause of irreversible blindness worldwide and remains undiagnosed in over half of patients. We constructed two genome-wide PGS using genome wide association study from African ancestry subjects: 1) the Primary Open-Angle African Ancestry Glaucoma Genetics (POAAGG) study (N = 7,031; POAAGG PGS) and an African ancestry GWAS (N = 11,275; MEGA PGS). We also derived two selected loci PGS from six multi-ancestry glaucoma GWAS and weighted these scores using African ancestry effect sizes (PGS616 and PGS526). In an independent training cohort (N = 271), the curated loci-based score PGS526 demonstrated the strongest standalone performance (mean AUC = 0.668), outperforming the genome-wide PGS constructed using PRS-CS. Integration with baseline demographic features (age and gender) further improved prediction, with the base + PGS616 model achieving a peak AUC of 0.806 with support vector machine model. Clinical enrichment in an independent suspect cohort (N = 1,013) showed that higher predicted genetic risk was significantly associated with elevated intraocular pressure, larger cup-to-disc ratio, and thinner retinal nerve fiber layer, which are all POAG diagnostic features. Leveraging inter-eye asymmetry, PGS further enhanced early disease discrimination, improving AUC from 0.823 to 0.862 for {Delta}IOP, from 0.769 to 0.817 for {Delta}CDR, and from 0.790 to 0.831 for {Delta}RNFL. These results demonstrate that PGS enhances prediction in phenotype-rich settings and enables accurate risk stratification in deep phenotype-limited cohorts, supporting earlier glaucoma detection. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=197 SRC="FIGDIR/small/25336797v3_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@1be6b71org.highwire.dtl.DTLVardef@7ff2aaorg.highwire.dtl.DTLVardef@14b5baorg.highwire.dtl.DTLVardef@1a6fab1_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LIAncestry-matched polygenic scores improve POAG risk prediction in African ancestry populations C_LIO_LICurated loci-based PGS outperform genome-wide scores in machine learning models C_LIO_LIGenetic risk integrates with minimal demographics to achieve AUC up to 0.806 C_LIO_LIPredicted risk aligns with optic nerve damage and inter-eye asymmetry in suspects C_LI