Electronic medical records and genomics (eMERGE) network exploration in cataract: Several new potential susceptibility loci

Marylyn D. Ritchie, Shefali S. Verma, Molly A. Hall, Robert J. Goodloe, Richard L. Berg, Dave S. Carrell, Christopher S. Carlson, Lin Chen, David R. Crosslin, Joshua C. Denny, Gail Jarvik, Rongling Li, James G. Linneman, Jyoti Pathak, Peggy Peissig, Luke V. Rasmussen, Andrea H. Ramirez, Xiaoming Wang, Russell A. Wilke, Wendy A. WolfEric S. Torstenson, Stephen D. Turner, Catherine A. McCarty

Research output: Contribution to journalArticlepeer-review

30 Scopus citations


Purpose: Cataract is the leading cause of blindness in the world, and in the United States accounts for approximately 60% of Medicare costs related to vision. The purpose of this study was to identify genetic markers for age-related cataract through a genome-wide association study (GWAS).

Methods: In the electronic medical records and genomics (eMERGE) network, we ran an electronic phenotyping algorithm on individuals in each of five sites with electronic medical records linked to DNA biobanks. We performed a GWAS using 530,101 SNPs from the Illumine 660W-Quad in a total of 7,397 individuals (5,503 cases and 1,894 controls). We also performed an age-at-diagnosis case-only analysis.

Results: We identified several statistically significant associations with age-related cataract (45 SNPs) as well as age at diagnosis (44 SNPs). The 45 SNPs associated with cataract at p<1×10-5 are in several interesting genes, including ALDOB, MAP3K1, and MEF2C. All have potential biologic relationships with cataracts.

Conclusions: This is the first genome-wide association study of age-related cataract, and several regions of interest have been identified. The eMERGE network has pioneered the exploration of genomic associations in biobanks linked to electronic health records, and this study is another example of the utility of such resources. Explorations of age-related cataract including validation and replication of the association results identified herein are needed in future studies.

Original languageEnglish (US)
Pages (from-to)1281-1295
Number of pages15
JournalMolecular vision
StatePublished - Sep 19 2014

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© 2014 Molecular Vision.


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