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.
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.
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