One promise of the human genome project was to enable genome-informed personalized medicine. During the past four years Northwestern has been a site in the eMERGE network. This consortium of biobanks linked to electronic health records (EHR) has developed portable algorithms to identify cases and controls from EHR data and then performed genome-wide association studies (GWAS) to correlate genetic variation with disease and normal physiological variation in widely measured laboratory values. In response to RFA-HG-10-009, we propose to contribute to the network development of additional phenotype algorithms and the analysis of the genotype data from the Northwestern eMERGE cohort supplemented by approximately 3,000 additional EHR-linked samples, each associated with 660k GWAS genotypes. We will develop a range of phenotypes that will allow us to assess patient and physician attitudes to the utility of genetic information in predicting disease susceptibility, drug response and therapeutic outcomes. Based on these consultations, we propose to develop a modified quality improvement model for determining, in a pilot study, which genotypes might be most valuable to present in a clinical care setting. We will develop a consent model and associated educational methods in support of providing experimental subjects with genotype information in a clinical encounter, including CLIA certified re-genotyping of participants who were previously genotyped for research purposes. At Northwestern, we utilize a widely-deployed, commercial EHR, EPIC, and propose to develop technical approaches for integrating genetic variation data into the health record and to effectively present these results using point-of-care, decision support tools to physicians. A goal of this effort is to develop best practices collaboratively within the network, for reporting of genetic variation data and developing local practice guidelines for using genetic data in primary care clinical encounters. Finally, we propose a rigorous assessment of the impact of these approaches on primary care physicians and their patients, defining the regulatory issues and then disseminating lessons learned and best practice recommendations. Together, the work proposed should provide an assessment of key elements of genome-informed personalized medicine.

Public Health Relevance

This project begins to answer questions about using genomic analysis and applying it to real world clinical situations. We propose to study the clinical and personal utility of genomic variation in a diverse primary care patient and physician population.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01HG006388-03
Application #
8523193
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
$958,491
Indirect Cost
$331,927
Name
Northwestern University at Chicago
Department
Anatomy/Cell Biology
Type
Schools of Medicine
DUNS #
005436803
City
Chicago
State
IL
Country
United States
Zip Code
60611
Rasmussen, Luke V; Thompson, Will K; Pacheco, Jennifer A et al. (2014) Design patterns for the development of electronic health record-driven phenotype extraction algorithms. J Biomed Inform 51:280-6
Jeff, Janina M; Armstrong, Loren L; Ritchie, Marylyn D et al. (2014) Admixture mapping and subsequent fine-mapping suggests a biologically relevant and novel association on chromosome 11 for type 2 diabetes in African Americans. PLoS One 9:e86931
Muthalagu, A; Pacheco, J A; Aufox, S et al. (2014) A rigorous algorithm to detect and clean inaccurate adult height records within EHR systems. Appl Clin Inform 5:118-26
Brothers, Kyle B; Lynch, John A; Aufox, Sharon A et al. (2014) Practical guidance on informed consent for pediatric participants in a biorepository. Mayo Clin Proc 89:1471-80
Hsu, Joy; Pacheco, Jennifer A; Stevens, Whitney W et al. (2014) Accuracy of phenotyping chronic rhinosinusitis in the electronic health record. Am J Rhinol Allergy 28:140-4
Ramos, Erin M; Din-Lovinescu, Corina; Berg, Jonathan S et al. (2014) Characterizing genetic variants for clinical action. Am J Med Genet C Semin Med Genet 166C:93-104
Rasmussen, Luke V (2014) The electronic health record for translational research. J Cardiovasc Transl Res 7:607-14
Rasmussen-Torvik, L J; Stallings, S C; Gordon, A S et al. (2014) Design and anticipated outcomes of the eMERGE-PGx project: a multicenter pilot for preemptive pharmacogenomics in electronic health record systems. Clin Pharmacol Ther 96:482-9
Gottesman, Omri; Kuivaniemi, Helena; Tromp, Gerard et al. (2013) The Electronic Medical Records and Genomics (eMERGE) Network: past, present, and future. Genet Med 15:761-71
Smith, Maureen E; Aufox, Sharon (2013) Biobanking: The Melding of Research with Clinical Care. Curr Genet Med Rep 1:122-128

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