Linking biorepositories of patients in healthcare delivery systems with electronic medical records (EMRs) is an efficient strategy for high-throughput genome wide association (GWA) studies, as phenotype, covariable and exposure data of public health importance can be economically abstracted and pooled across delivery systems to facilitate the large numbers of subjects needed for GWA studies of each phenotype. Key obstacles to the success of this strategy remain. In this project, which will use population-based genomic and phenotype data from a well characterized population served by a delivery system which captures virtually all health care encounters in its data bases. Researchers from Group Health Cooperative's Center for Health Studies, the University of Washington, and the Fred Hutchinson Cancer Research Center will address these obstacles by pursuing the following specific aims: 1. Informed by results from targeted focus groups, implement a consensus process with key stakeholders to develop recommendations concerning consent, data sharing, and return of research results to subjects. 2. Work together with other network sites to develop a virtual data warehouse (VDW) analogous to that used in the Cancer Research Network, and extend natural language processing (NLP) to pathology, radiology, and clinical chart notes. 3. Develop and test strategies to determine whether each candidate EMR-based phenotype is sufficiently valid to pursue analyses of GWA data, and develop statistical methods that explicitly account for heterogeneous phenotype validity within and between sites. 4. Perform a series of GWA analyses in the GHC biorepository and linked biorepositories. 4a: Alzheimer's disease (AD). 4b: Carotid artery atherosclerotic disease (CAAD). 4c: Complications of statin use, including elevations of CPK and muscle pain. Through cooperation with other investigators and the NHGRI, this work will facilitate development of policies and procedures to realize the incredible potential of EMR-linked biorepositories for GWA studies to improve understanding, prevention and treatment of chronic diseases and illnesses. Specific GWA research will allow us to explore both etiologic research (AD and CAAD progression) and pharmacogenetics (statin therapy). The implications of this portfolio of research extend far beyond the specific phenotypes we have chosen to emphasize;we expect this work represents the beginning of a large and productive enterprise.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01HG004610-03
Application #
7684273
Study Section
Special Emphasis Panel (ZHG1-HGR-N (O2))
Program Officer
Li, Rongling
Project Start
2007-09-27
Project End
2011-07-31
Budget Start
2009-08-01
Budget End
2010-07-31
Support Year
3
Fiscal Year
2009
Total Cost
$1,039,667
Indirect Cost
Name
Group Health Cooperative
Department
Type
DUNS #
078198520
City
Seattle
State
WA
Country
United States
Zip Code
98101
El Rouby, Nihal; McDonough, Caitrin W; Gong, Yan et al. (2018) Genome-wide association analysis of common genetic variants of resistant hypertension. Pharmacogenomics J :
Deming, Yuetiva; Dumitrescu, Logan; Barnes, Lisa L et al. (2018) Sex-specific genetic predictors of Alzheimer's disease biomarkers. Acta Neuropathol 136:857-872
Mosley, Jonathan D; Shoemaker, M Benjamin; Wells, Quinn S et al. (2017) Investigating the Genetic Architecture of the PR Interval Using Clinical Phenotypes. Circ Cardiovasc Genet 10:
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
Mosley, Jonathan D; van Driest, Sara L; Wells, Quinn S et al. (2016) Defining a Contemporary Ischemic Heart Disease Genetic Risk Profile Using Historical Data. Circ Cardiovasc Genet 9:521-530
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
Karch, Celeste M; Ezerskiy, Lubov A; Bertelsen, Sarah et al. (2016) Alzheimer's Disease Risk Polymorphisms Regulate Gene Expression in the ZCWPW1 and the CELF1 Loci. PLoS One 11:e0148717
Mez, Jesse; Mukherjee, Shubhabrata; Thornton, Timothy et al. (2016) The executive prominent/memory prominent spectrum in Alzheimer's disease is highly heritable. Neurobiol Aging 41:115-121

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