Electronic Medical Records and Genomics Network

Electronic Medical Records and Genomics Network
Name	Electronic Medical Records and Genomics Network
Formation	2007
Purpose	To conduct genome-wide association studies using electronic health record-linked biobanks
Headquarters	Bethesda, Maryland
Region served	United States
Parent organization	National Human Genome Research Institute

Electronic Medical Records and Genomics Network. It is a national consortium established to pioneer the use of electronic health record systems linked to DNA biorepositories for large-scale genetic research. Funded by the National Human Genome Research Institute, the network aims to discover genetic variants influencing disease by leveraging the vast clinical data within healthcare systems. Its work has been instrumental in advancing the field of biomedical informatics and precision medicine.

Overview

The network was created to address the need for large, diverse cohorts in genome-wide association studies. It integrates clinical phenotype data extracted from Epic and Cerner electronic health record platforms with genotype data from participating biobanks. This infrastructure enables researchers to investigate the genetic architecture of a wide array of medical conditions, from cardiovascular disease to psychiatric disorders. The initiative represents a major collaboration between academic medical centers, pharmaceutical industry partners, and the National Institutes of Health.

History and development

The network was launched in 2007 with an initial grant from the National Human Genome Research Institute, part of a broader strategic plan to translate genomic discoveries into clinical care. Its development was influenced by earlier projects like the Pharmacogenomics Research Network and the Framingham Heart Study, which demonstrated the value of longitudinal data. A significant milestone was its role in the Human Genome Project's successor initiatives, focusing on genomic medicine. The consortium's design was also shaped by evolving policies like the Health Information Technology for Economic and Clinical Health Act, which promoted health information technology adoption.

Research objectives and design

A primary objective is to identify single-nucleotide polymorphism associations with diseases and drug response phenotypes derived from International Classification of Diseases codes and clinical notes. The study design employs a case-control methodology across multiple ancestry groups to ensure findings are broadly applicable. Key methodological innovations include the development of phenotype algorithms using the Observational Medical Outcomes Partnership common data model and advanced statistical genetics techniques. The network also prioritizes research into Mendelian randomization and the construction of polygenic risk scores for common diseases.

Key studies and findings

Notable publications have identified novel loci for conditions such as type 2 diabetes, cataracts, and venous thromboembolism. A landmark study in Nature Genetics detailed the genetic basis of Ehlers-Danlos syndrome using electronic health record phenotypes. The consortium contributed significantly to the All of Us Research Program and the UK Biobank in validating genetic associations for inflammatory bowel disease. Other findings have explored the genetics of laboratory test values and their correlation with clinical trial outcomes, published in journals like The New England Journal of Medicine and Cell.

Participating institutions and consortia

Core clinical sites have included the Geisinger Health System with its MyCode Community Health Initiative, the Mayo Clinic, Massachusetts General Hospital, and Vanderbilt University Medical Center through its BioVU biobank. The network collaborates with the eMERGE consortium and the Genomics England initiative. Key principal investigators have been affiliated with the Broad Institute, Icahn School of Medicine at Mount Sinai, and the University of Washington. Industry partnerships have involved Regeneron Pharmaceuticals and the Personal Genome Project.

Impact and future directions

The network has profoundly impacted clinical genomics by demonstrating the feasibility of using real-world data for discovery research. Its phenotype algorithms and data sharing protocols have become models for subsequent initiatives like the Precision Medicine Initiative. Future directions include integrating whole-genome sequencing data, expanding diversity through partnerships with the Hispanic Community Health Study, and applying artificial intelligence to radiology reports. The consortium continues to address ethical challenges related to incidental findings and informed consent in the era of big data.

Category:Medical research organizations Category:Genomics organizations Category:Research networks