The Seattle eMERGE project aims to bring personal genomics to practice settings by taking advantage of the extensive electronic medical record (EMR) and biorepository of Group Health Cooperative (GH), including a 33-year pharmacy database and longitudinal data on an aging population. Algorithms developed in eMERGE I will be used to combine genome-wide association studies with phenotypes mined from EMRs to discover new polymorphism-phenotype relationships. Target phenotypes are infectious disease susceptibility, specifically to Clostridium difficile diarrhea, shingles from varicella zoster virus, and fungal nail infection, responses to antihypertensive drugs, serotonin-specific reuptake inhibitors, and statins, including adverse events. A new algorithm will follow longitudinal glycemia and hematocrit trajectories, and a novel automated method will detect karyotype abnormalities for assessing correlation to myelodysplasia and leukemia. Data will also support phenotypes investigated at other eMERGE sites. To create a model for introducing genomics into clinical practice, successful needs assessment methods from eMERGE I will engage stakeholders in guiding development of prototype EMR user interfaces in a clinical decision support format. The test case will be human leukocyte antigen-typing for an adverse drug reaction and the setting will be the patient-centered medical home care model developed at GH. This proposal provides the eMERGE network and its collaborators with the Seattle team's unique expertise in using natural language processing (NLP) to extract information from EMRs, and assisting in adoption of NLP methods. To disseminate eMERGE results and foster collaborations, it takes advantage of leadership positions of the investigators, including partners within eMERGE, other consortia and the HMO Research network, especially the potential for developments supported by the NIH Director's Common Fund in biobanking and megaepidemiology. Completion of the aims will reveal new, medically useful markers, improve the linking of high-throughput genomic methods to EMR data, and develop policies and practices for bringing individualized evidence-based medicine to communities.

Public Health Relevance

To advance personalized medicine-treatment and preventive care based on individual traits;this project matches small differences in DNA to infectious disease susceptibility and response to statins, serotonin- specific reuptake inhibitors (SSRIs) and blood pressure medications. Methods to use these results in clinical care will be guided by focus groups of patients and caregivers in the patient-centered Group Health system.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01HG006375-03
Application #
8517791
Study Section
Special Emphasis Panel (ZHG1-HGR-N (M1))
Program Officer
Li, Rongling
Project Start
2011-08-15
Project End
2015-07-31
Budget Start
2013-08-01
Budget End
2014-07-31
Support Year
3
Fiscal Year
2013
Total Cost
$935,039
Indirect Cost
$147,968
Name
Group Health Cooperative
Department
Type
DUNS #
078198520
City
Seattle
State
WA
Country
United States
Zip Code
98101
Katsumata, Yuriko; Nelson, Peter T; Ellingson, Sally R et al. (2017) Gene-based association study of genes linked to hippocampal sclerosis of aging neuropathology: GRN, TMEM106B, ABCC9, and KCNMB2. Neurobiol Aging 53:193.e17-193.e25
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
Sanderson, Saskia C; Brothers, Kyle B; Mercaldo, Nathaniel D et al. (2017) Public Attitudes toward Consent and Data Sharing in Biobank Research: A Large Multi-site Experimental Survey in the US. Am J Hum Genet 100:414-427
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
Sims, Rebecca (see original citation for additional authors) (2017) Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease. Nat Genet 49:1373-1384
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
Jun, Gyungah R; Chung, Jaeyoon; Mez, Jesse et al. (2017) Transethnic genome-wide scan identifies novel Alzheimer's disease loci. Alzheimers Dement 13:727-738
Himes, Patricia; Kauffman, Tia L; Muessig, Kristin R et al. (2017) Genome sequencing and carrier testing: decisions on categorization and whether to disclose results of carrier testing. Genet Med 19:803-808
Chouraki, Vincent; Reitz, Christiane; Maury, Fleur et al. (2016) Evaluation of a Genetic Risk Score to Improve Risk Prediction for Alzheimer's Disease. J Alzheimers Dis 53:921-32
Rasmussen, Luke V; Overby, Casey L; Connolly, John et al. (2016) Practical considerations for implementing genomic information resources. Experiences from eMERGE and CSER. Appl Clin Inform 7:870-82

Showing the most recent 10 out of 126 publications