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C. A. McCarty, S. Turner, L. Rasmussen, C. Waudby, R. Berg, J. Linneman, P. Peissig, L. Chen, J. Starren, M. Ritchie; Genome-Wide Association Study of Cataract in the Emerge Consortium. Invest. Ophthalmol. Vis. Sci. 2010;51(13):2512.
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© ARVO (1962-2015); The Authors (2016-present)
Heritability of cortical and nuclear cataract has been calculated to be 58% and 48% respectively, with as many as 40 genes estimated to be involved. The purpose of this study was to identify genetic predictors of age-related cataract through a genome-wide association study (GWAS), as part of eMERGE, a consortium funded by NHGRI to conduct GWAS in the context of biobanks attached to electronic medical records.
Cases and controls were identified through electronic chart extraction of adults aged 50 years and older enrolled in the population-based Personalized Medicine Research Project biobank. Natural language processing and optical character recognition were used to identify cataract type from the ophthalmic notes and ink-over forms. Manual chart abstraction was performed to validate and improve the electronic case/control finding algorithms until predictive values of that least 95% had been achieved. The DNA samples were genotyped at the Center for Inherited Diseases at Johns Hopkins University using the Illumina 660W-Quad platform. Additive logistic regression models were used and the p-values of all SNPs on the platform were ranked for potential association.
1323 surgical cases, 1323 diagnosis only and 1323 controls were genotyped. There were 743 cases of mixed cataract type, 883 nuclear only and 122 cortical only. The analysis set comprised 2333 females and 1635 males; 98.5% were Caucasian by self-report. Using only unrelated individuals, 8 markers in three genes on chromosome 2, 2 markers each on chromosomes 5 and 14 and one marker each on chromosomes 8, 15 and 17 reached statistical significance at a p<10-5. The top hits were found to be very similar, regardless of cataract type. These results are currently being replicated at Vanderbilt University, one of the five eMERGE sites.
We believe that we have identified the first SNPs associated with age-related cataracts. It was striking to find that the most significant markers varied little by cataract type. The next step will be to conduct gene-environment analyses that could inform potential interventions to decrease the prevalence of cataract in those at increased risk genetically.
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