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Meta-Analysis
. 2024 Oct 23;15(1):9116.
doi: 10.1038/s41467-024-53212-6.

Uncovering genetic loci and biological pathways associated with age-related cataracts through GWAS meta-analysis

Santiago Diaz-Torres  1   2 , Samantha Sze-Yee Lee  3 , Luis M García-Marín  4   5 , Adrian I Campos  4   5   6 , Garreth Lingham  3 , Jue-Sheng Ong  4 , David A Mackey  3 , Kathryn P Burdon  7 , Michael Hunter  8 , Xianjun Dong  9   10 , Stuart MacGregor  4   5 , Puya Gharahkhani #  4   5   11 , Miguel E Rentería #  4   5
Affiliations
Meta-Analysis

Uncovering genetic loci and biological pathways associated with age-related cataracts through GWAS meta-analysis

Santiago Diaz-Torres et al. Nat Commun. .

Abstract

Age-related cataracts is a highly prevalent eye disorder that results in the clouding of the crystalline lens and is one of the leading causes of visual impairment and blindness. The disease is influenced by multiple factors including genetics, prolonged exposure to ultraviolet radiation, and a history of diabetes. However, the extent to which each of these factors contributes to the development of cataracts remains unclear. Our study identified 101 independent genome-wide significant loci, 57 of which are novel. We identified multiple genes and biological pathways associated with the cataracts, including four drug-gene interactions. Our results suggest a causal association between type 1 diabetes and cataracts. Also, we highlighted a surrogate measure of UV light exposure as a marker of cataract risk in adults.

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Conflict of interest statement

A.I.C. is currently employed by the Regeneron Genetics Center, a wholly-owned subsidiary of Regeneron Pharmaceuticals, Inc., and may own Regeneron stock or stock options. A.I.C. contributed to this work during his tenure at QIMR Berghofer Medical Research Institute and The University of Queensland. The other authors report no competing interests.

Figures

Fig. 1
Fig. 1. Manhattan plot showing results for the GWAS meta-analysis of cataracts; p values derived from logistic regression models are two-sided.
Each dot represents a single nucleotide polymorphism (SNP) and the red line represents the threshold for multiple testing correction (p < 5 × 10−8) and the blue line (p < 5 × 10−6). Novel loci are represented in the plot as red dots and are highlighted in purple, whereas previously known loci are presented in black.
Fig. 2
Fig. 2. Correlation of allele effect estimates (log(OR)) using a two-sided linear model between the meta-analysis and previous cataract GWAS, based on independent and genome-wide significant loci (N = 101).
Effects estimates (center points) are presented as logarithms of odd ratios (log(OR)) and black crosses represent a 95% confidence interval. The studies included are (A) The previous meta-analysis for cataracts (Choquet et al.; p < 2.2 × 10−16), (B) FinnGen (p < 2.2 × 10−16), and (C) The Mass General Brigham Biobank (MGBB; p = 2.3 x 10−5).
Fig. 3
Fig. 3. MR results of the putative causal association between cataracts and type 1 diabetes (N = 33).
A Forest plot based on different MR methods. Estimated effects (center point), odd ratios (OR), are presented as per unit change of the exposure with a 95% confidence interval. B Effect of variants associated with Cataracts (Outcome) and type 1 Diabetes (Exposure). Effects estimates (center points) are presented as logarithms of odd ratios (log(OR)) and gray crosses represent a 95% confidence interval. The dashed blue line shows the inverse variance weighted (IVW) fit and the red dashed line shows the MR-Egger-fit; p values derived from IVW and MR-Egger are two-sided.
Fig. 4
Fig. 4
Distribution of Polygenic Risk Scores for Cataracts in Cases and Controls. Standardized PRS for cataracts are based on 389 cases and 4416 controls from the BHAS cohort (p = 0.01). The PRS distribution for cases is shown in blue, while the distribution for controls is shown in yellow.
Fig. 5
Fig. 5. Cohorts included in the cataract meta-analysis and polygenic risk score (PRS) analysis.
UK biobank (UKB), Adult Health and Aging (GERA), Mass General Brigham Biobank (MGBB).
See this image and copyright information in PMC

References

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