Leveraging Electronic Health Records for Phenotyping - Translational Informatics: Realizing the Promise of Knowledge-Driven Healthcare - page 63

support. Since the clinical data needed to apply the rule (e.g., the prescribing of
warfarin and patient demographics) were already used in the discovery of the
correlation, its application is simplifi ed.

4.3.4 Projects Leveraging EHRs for Genotype-Phenotype

Studies

Based on the early results and promise of using EHRs for extracting phenotype
information for genetics research, the National Human Genome Research Institute
(NHGRI) funded the Electronic Medical Records and Genomics Network, or
eMERGE. The NHGRI began working with the International Human Genome
Project, and continues to support genome research as one of the National Institutes
of Health. eMERGE was created to specifi cally develop methods and practices for
using EHRs for genomic research [ 15 , 34 ]. It began as a network of fi ve institutions,
each with a biobank and an electronic health record. The size of the biorepositories
at each site ranged from about 4,000 to 75,000. Each eMERGE site was focused on
a particular primary and secondary phenotypic outcome with its subject population.
eMERGE later expanded to include nine main research groups or institutions, and
additional affi liate institutions.
eMERGE has been signifi cant in advancing the understanding of capabilities and
issues of using EHR data for phenotyping. They have published results of GWAS
using phenotypes from EHRs in each of the primary conditions studied: cataract
and HDL, dementia, electrocardiographic QRS duration, peripheral arterial disease,
and type 2 diabetes. Their successes have furthered the interest in using EHRs for
GWAS. They also were able to successfully validate and deploy phenotypes devel-
oped at one institution using one EHR to other institutions and EHRs across the
network [ 35 ].
eMERGE has also increased understanding of issues related to using EHRs for
phenotypes, that has extended beyond the goals of GWAS. They published results
of studies demonstrating how privacy could be both breached and protected when
performing research with data from EHRs for GWAS and other studies [ 36 - 38 ].
The timing of these analyses and results was signifi cant - with breach penalties
incurred from the HITECH act, many institutions had diffi culty in navigating the
new rules of privacy and confi dentiality, while still sharing data. eMERGE research-
ers were also able to demonstrate how phenotypes from EHRs could be used for a
new type of study beyond GWAS. Rather than scanning genotypes for associations
with a defi ned phenotype, as is done with GWAS, they demonstrated scanning a
large set of phenotypes for associations among various genotypes. This new
approach created phenome-wide association studies, or PheWAS.
Another product of eMERGE has been resources for other researchers to use in
GWAS or PheWAS research. Software to perform PheWAS was made available and
distributed to researchers. eMERGE researchers created over 21 different pheno-
types, that are made publically available in the Phenotype KnowledgeBase. These