The mapping of the human genome has enabled new exploration of how genetic variations contribute to health and disease. To better realize this promise, researchers must now determine ways in which genetic make-up gives some individuals a greater chance of becoming sick with chronic conditions such as diabetes, Alzheimer’s, or heart disease. The goal of gaining this knowledge is to translate it to bedside practice and ultimately improve patient care.
The Electronic Medical Records and Genomics (eMERGE) Network is a national consortium organized by NHGRI to develop, disseminate, and apply approaches to research. It combines DNA biorepositories with electronic medical record (EMR) systems for large-scale, high-throughput genetic research with the ultimate goal of returning genomic testing results to patients in a clinical care setting. The Network is currently exploring more than a dozen phenotypes (with 13 additional electronic algorithms having already been published). Various models of returning clinical results have been implemented or planned for pilot at sites across the Network. Themes of bioinformatics, genomic medicine, privacy and community engagement are of particular relevance to eMERGE.
What makes eMERGE unique?
Each center participating in the Network is studying the relationship between genome-wide genetic variation and a common human trait. Such studies commonly involve testing hundreds of thousands of genetic variants called single nucleotide polymorphisms (SNPs) throughout the genome in people with and without the trait. A number of such studies are routinely conducted to uncover the association between disease and a person’s genetic make-up, but those studies are typically costly and take a long time to complete.
The eMERGE model is exploring use of data from the EMR – clinical systems that represent actual health care events - as an alternative methodology. Electronic medical records are one of the most exciting potential resources for research data. Each member site has EMR data linked to genetic samples obtained in the course of existing cohort studies, biorepositories, or from residual tissue or blood samples. In the eMERGE model, there is no need to actively recruit and gather samples from a study population. Cases and controls are quickly and consistently identified from the EMR, and the genetic samples are all readily available. This approach is both cost-effective and time-efficient. More detailed information about the chosen phenotypes being explored in eMERGE can be found on PheKB, and other freely downloadable files can be found on the Resources page.
Lastly, the eMERGE Network is highly collaborative, and cross-site projects are the standard. A list of current eMERGE manuscripts, toolkits, and software is available, as are eMERGE phenotype algorithms and other documents. To ensure that the maximum scientific benefit is derived from NHGRI's generous public investment, this Network emphasizes sharing of data with the broad scientific community for research use, primarily through community resource databases such as dbGaP. Through researching new methodologies and disseminating the information, this consortium will improve the use of biorepositories for genomic research.