Northwestern University Feinberg School of Medicine
Center for Genetic Medicine
Skip to main content

Electronic Medical Records and Genomics (eMERGE) Network

The national Electronic Medical Records and Genomics (eMERGE) Network launched in 2007 with funding from the National Institutes of Health to incorporate DNA biorepository data with electronic medical record (EMR) systems for large-scale, high-throughput genetic research. Northwestern was one of five sites originally funded for this project and continues as a funded site for eMERGE through 2025. See below for summaries of eMERGE I, II, III and IV.

emerge-4-map-1024x571.png

Current Goals

eMERGE Phase IV

For some common diseases, polygenetic risk scores (PRS) identify individuals with risk comparable to carriers of highly penetrant rare variants. This has created excitement about the potential to tailor risk management strategies for common diseases and ultimately reduce morbidity and mortality.

Now in Phase IV (July 2020 - April 2025), or eMERGE 4 (e4), the Northwestern eMERGE project will address three major scientific questions related to clinical PRS use:

  • Does use of PRS contribute to improved adherence to risk management strategies and improved clinical outcomes?
  • Does a high risk PRS presented with culturally sensitive and tailored risk communication improve adherence and outcomes across diverse racial and ethnic groups?
  • Can we develop and test information technology that stores PRS in the electronic health record (EHR) and delivers clinical decision support (CDS) to aid providers in PRS use clinically?

To answer these questions and achieve e4 goals, we will also create and deploy a smartphone application (app) to facilitate recruitment, retention and outcome monitoring.

As participants in the e4 consortium, we will implement a program called ENDORSED (eMERGE Northwestern Develops Optimized Risk Scores for Everyone’s DNA). ENDORSED will:

  1. Calculate and validate common disease PRS selected for actionable outcomes. With all eMERGE 4 network partners, we will select 20 PRS for common diseases to calculate and validate across the network. We propose 20 common disorders with published evidence supporting the PRS. These 20 conditions were selected due to the likelihood that a high PRS will change health care management.
  2. Recruit and genotype a diverse population of 2,500 for return of 15 PRS. Building on our successful recruitment in eMERGE 2 and 3 (e2 and e3), we will recruit at least 2,500 participants, at least 35 percent of whom will be racial and ethnic minorities, for clinical return of genomic risk estimation. Northwestern’s extensive health system allows recruitment from our primary medical center as well as a vast network of community hospitals and clinics.
  3. Place genomic risk information in the EHR testing alternative communication tools. We will use behavioral theory to create culturally sensitive communication strategies that promote understanding of and trust in PRS among a diverse patient and provider population. PRS will be deposited into the EHR and integrated with clinical decision support and patient education materials tailored by the results of the proposed ethical legal and social implications (ELSI) project.
  4. Assess impact by monitoring intervention uptake and outcomes after PRS return. Using our expertise in EHR data ascertainment, we will analyze outcomes after PRS return by monitoring pre-specified diagnoses, symptoms and activities. We selected these downstream behaviors with the expectation that at least 50 percent intervention uptake will be achieved in those at highest genomic risk. Successfully accomplishing these goals will provide evidence supporting genomic medicine implementation in real world clinical settings and provide a robust test of the clinical utility of PRS.

Join the Study

Interested in participating in or learning more about eMERGE?  

Learn More

History

 eMERGE Phase I

In eMERGE Phase I (September 2007 to July 2011), each participating institution led studies of the relationship between genetic variation and at least two common human traits among the network participants. Sites also explored the ethical and social issues associated with large-scale genomic research.

The Northwestern eMERGE team led the implementation of diabetes, asthma, lipids and several other phenotype algorithms. During Phase I, investigators successfully analyzed genome-wide association study data to discover new and validate known genetic associations with type II diabetes and height in African Americans. The NUgene Project biobank, Northwestern’s hospital-based biorepository, served as the source of DNA samples and data used for the eMERGE studies. The Northwestern team also led studies on the public perception of participation in genetic research and data sharing of genomic research results and the understanding of Institutional Review Board professionals of data sharing for genomic research.  

In Phase I, the eMERGE consortium validated the hypothesis that clinical data derived from electronic medical records can be used successfully for complex genomic analysis of disease susceptibility across diverse patient populations. In addition, the network showed the efficiency that can result from the use of electronic health record data. For instance, genotypes for type II diabetes patients have also contributed to research of cardiac QRS duration, hypothyroidism and a dozen other phenotypes.

 eMERGE Phase II

The aim of eMERGE Phase II (August 2011 to July 2015) was to provide a meaningful assessment of key elements necessary for the implementation of genome-informed personalized medicine via the tracking of patient and physician actions and responses to genetic information through electronic medical records.

In eMERGE 2 (e2), the Northwestern team led the development of phenotyping algorithms for diverticulosis and diverticulitis, colon polyps, caMRSA and the sub-phenotype for asthma exacerbations, as well as implemented adult and pediatric phenotype algorithms led by other e2 sites. 

In addition, Northwestern furthered progress on a pilot project of genome-informed clinical care. Scientists identified and validated the association between genetic variation and clinically relevant conditions (hemochromatosis, Factor V Leiden, prothrombin and pharmacogenetic variants). The Northwestern e2 team has also begun to define what makes a genetic variation clinically actionable, to develop technical and regulatory solutions to integrate genomic information into the EHR, to assess physician and patient attitudes toward the value of these data and to develop strategies to educate physicians and patients in the use of genomic data.

 eMERGE Phase III

In eMERGE Phase III (September 2015 – May 2020), the Northwestern eMERGE team was focused on the following goals:

  • Perform electronic phenotyping and genomic analysis on at least four novel phenotypes of medical, scientific and public health importance.
  • Consent 3,000 ethnically diverse participants who agree to receive results about clinically actionable variants found in their genotyped genes and return appropriate information to them.
  • Expand our ancillary genomics system to incorporate sequence data, including whole genome and exome sequence and develop strategies for transferring actionable variants into EHR to enable clinical decision support.
  • Develop and share best practices, expertise and experience for:
    1. creating tools and methods for rapid and accurate phenotyping;
    2. assisting patients and families in making choices about genomic testing/results;
    3. sharing of clinical and family history data with families;
    4. storing and representing genomic data in the EHR; and
    5. understanding downstream effects of genomic sequencing results on the healthcare system, patient and family.

The eMERGE 1 and 2 project outcomes demonstrated the value of longitudinal clinical care data captured in electronic health records, namely the identification of new genetic variant disease associations. The eMERGE 3 consortium continued this progress through the development of novel algorithms and the use of the large eMERGE dataset to identify novel variant-disease associations and move into the domain of rare genetic variants.

Learn More

Follow Center for Genetic Medicine on Flickr