The primary goals of this project are first to develop and validate electronic algorithms, to accurately identify cases and controls for each ophthalmic phenotype, and to conduct genome wide association studies that advance our understanding of these disease states and their treatment. The next goal will be to translate clinically meaningful results into clinical practice. The Marshfield Clinic is an ideal setting for translational research, in part because an internally-developed electronic health record facilitates timely incorporation of research results with necessary decision support tools for health care providers.
Specific aims i nclude: 1. Develop and validate electronic algorithms for ophthalmic conditions and efficacy of medical therapy for ophthalmic conditions and implement other phenotype algorithms developed across the eMERGE network.
Aim 1 a. Develop and validate electronic algorithms for ocular hypertension/glaucoma, intraocular pressure (lOP) response to lOP lowering medications, AMD, response to AMD treatment, tear film insufficiency, response to artificial tears used to treat tear film insufficiency Aim lb. Implement electronic algorithms for phenotypes developed at the other eMERGE sites and share data with the other sites. 2. Leverage GWAS data available for nearly 5000 research subjects aged 50 years and older in Marshfield and an additional 20-25,000 subjects throughout the eMERGE network to undertake genetic discoveries for ophthalmic conditions and ophthalmic pharmacogenetics. Statistical analyses will include traditional GWAS using the SNP data, analysis of copy number variant (CNV) data, and gene/environment analyses. 3. Undertake consultation activities with the general community and clinicians related to the incorporation of GWAS results into electronic health records to inform health care decisions.
Aim 3 a. Conduct focus group discussion with ophthalmologists related to genetic-based prescribing Aim 3b. Meet with the PMRP Community Advisory Group to discuss potential reconsent of study subjects to allow the sharing of genetic data Aim 3c. Communicate with the entire PMRP cohort about return of results and study progress Aim 3d. Contact all subjects with GWAS data to obtain consent to share their GWAS data with themselves and/or their health care providers, based on the results of the consultation efforts Aim 3e. Incorporate clinically relevant GWAS data in the EMRs for ophthalmologists and optometrists
With the ageing of the population, vision disorders are becoming more common, impacting quality of life and health care costs. The proposed project will identify gene/environment predictors of glaucoma/ocular hypertension (the second leading cause of blindness), age-related macular degeneration (the leading cause of blindness in the elderly) and dry eye, as well as genetic predictors of response to medical therapy for these conditions. Use of clinically meaningful GWAS data could save sight and health care costs.
|Peissig, Peggy; Schwei, Kelsey M; Kadolph, Christopher et al. (2017) Prototype Development: Context-Driven Dynamic XML Ophthalmologic Data Capture Application. JMIR Med Inform 5:e27|
|Rasmussen-Torvik, Laura J; Almoguera, Berta; Doheny, Kimberly F et al. (2017) Concordance between Research Sequencing and Clinical Pharmacogenetic Genotyping in the eMERGE-PGx Study. J Mol Diagn 19:561-566|
|Kim, TaeWon; Havighurst, Thomas; Kim, KyungMann et al. (2017) RNA-Binding Protein IGF2BP1 in Cutaneous Squamous Cell Carcinoma. J Invest Dermatol 137:772-775|
|Nadkarni, Girish N; Galarneau, Geneviève; Ellis, Stephen B et al. (2017) Apolipoprotein L1 Variants and Blood Pressure Traits in African Americans. J Am Coll Cardiol 69:1564-1574|
|Liu, Jixia; Zhao, Ran; Ye, Zhan et al. (2017) Relationship of SULT1A1 copy number variation with estrogen metabolism and human health. J Steroid Biochem Mol Biol 174:169-175|
|Hall, Molly A; Wallace, John; Lucas, Anastasia et al. (2017) PLATO software provides analytic framework for investigating complexity beyond genome-wide association studies. Nat Commun 8:1167|
|Holzinger, Emily R; Verma, Shefali S; Moore, Carrie B et al. (2017) Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. BioData Min 10:25|
|Karnes, Jason H; Bastarache, Lisa; Shaffer, Christian M et al. (2017) Phenome-wide scanning identifies multiple diseases and disease severity phenotypes associated with HLA variants. Sci Transl Med 9:|
|Bailey, Jessica N Cooke; Loomis, Stephanie J; Kang, Jae H et al. (2016) Genome-wide association analysis identifies TXNRD2, ATXN2 and FOXC1 as susceptibility loci for primary open-angle glaucoma. Nat Genet 48:189-94|
|Brilliant, Murray H; Vaziri, Kamyar; Connor Jr, Thomas B et al. (2016) Mining Retrospective Data for Virtual Prospective Drug Repurposing: L-DOPA and Age-related Macular Degeneration. Am J Med 129:292-8|
Showing the most recent 10 out of 89 publications