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Meta-Analysis
. 2024 Nov 17;15(1):9959.
doi: 10.1038/s41467-024-54301-2.

Genome-wide meta-analysis identifies 22 loci for normal tension glaucoma with significant overlap with high tension glaucoma

Collaborators, Affiliations
Meta-Analysis

Genome-wide meta-analysis identifies 22 loci for normal tension glaucoma with significant overlap with high tension glaucoma

Santiago Diaz-Torres et al. Nat Commun. .

Abstract

Primary open-angle glaucoma typically presents as two subtypes. This study aimed to elucidate the shared and distinct genetic architectures of normal-tension (NTG) and high-tension glaucoma (HTG), motivated by the need to develop intraocular pressure (IOP)-independent drug targets for the disease. We conducted a comprehensive multi-ethnic meta-analysis, prioritized variants based on functional annotation, and explored drug-gene interactions. We further assessed the genetic overlap between NTG and HTG using pairwise GWAS analysis. We identified 22 risk loci associated with NTG, 17 of which have not previously been reported for NTG. Two loci, BMP4 and TBKBP1, have not previously been associated with glaucoma at the genome-wide significance level. Our results indicate that while there is a significant overlap in risk loci between tension subtypes, the magnitude of the effect tends to be lower in NTG compared to HTG, particularly for IOP-related loci. Additionally, we identified a potential role for biologic immunomodulatory treatments as neuroprotective agents.

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Conflict of interest statement

Competing interests A.P.K. has acted as a paid consultant or lecturer to Abbvie, Aerie, Allergan, Google Health, Heidelberg Engineering, Novartis, Reichert, Santen and Thea. J.H.K. has received research funding from Pfizer, Inc. S.M., J.E.C. and A.W.H. are co-founders of and hold stock in Seonix Pty Ltd. The remaining authors report no other competing interests.

Figures

Fig. 1
Fig. 1. Manhattan plot based on the meta-analysis of normal tension glaucoma (NTG).
Each dot (N = 22) represents a single nucleotide polymorphism (SNP), and the red line represents the threshold for multiple testing correction (p < 5 × 10−8) and blue line p < 5 × 10−6; p-values derived from logistic regression models are two-sided. Previously unidentified loci are highlighted in purple and represented in the plot as red dots, while known loci are in black.
Fig. 2
Fig. 2. Correlation of the allele effect estimates using a two-sided linear model between multitrait analysis of European ancestry (EUR) and two independent cohorts, FinnGen and the Asians in the International Genetics of Glaucoma Consortium (IGGC).
Effects estimate (Beta) are presented as center points and black crosses represent 95% confidence intervals. A Correlation of the effect estimates between the NTG of EUR and IGGC Asians (N = 8), B NTG of EUR and FinnGen (N = 11) and C NTG of EUR and POAG (N = 11).
Fig. 3
Fig. 3. Inverse weighted variance (IVW) correlation between the effect sizes (N = 22), estimated in the log(OR), of normal tension glaucoma (NTG) and high tension glaucoma (HTG).
The slope for IOP loci (P < 0.05 for IOP; red line) shows that the effect sizes on average are 1.9 times higher in HTG compared to NTG whereas the slope for non-IOP loci (P > 0.05 for IOP; blue line), shows that the effect sizes on average are more similar (only 1.2 times higher in HTG); P-values derived from IVW are two-sided. Effects estimate (Beta) are presented as center points and black crosses represent 95% confidence intervals.

References

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