Cardiovascular Biomarkers - Iftikhar J. Kullo

EMR-based Genetic Studies: The eMERGE Network

The Electronic Medical Records and Genomics (eMERGE) Network is funded by the National Human Genome Research Institute (NHGRI) to develop and implement approaches for leveraging biorepositories with electronic medical record (EMR) systems for large-scale genomic research, including genome-wide association studies (GWAS), sequencing and structural variation.

The five participating sites are Group Health Cooperative (with the University of Washington), Marshfield Clinic, Mayo Clinic, Northwestern University and Vanderbilt University. Each site is conducting a GWAS of a primary and supplementary phenotype.

The Mayo Clinic proposal aims to identify genetic loci associated with peripheral arterial disease and red blood cell traits, including hemoglobin, hematocrit, red blood cell count, mean corpuscular volume, mean corpuscular hemoglobin and mean corpuscular hemoglobin concentration.

Phenotype characteristics and covariates relevant to statistical genetic analyses are derived using EMR-based algorithms, including diagnosis and procedure codes, laboratory data, medication use, and natural language processing of unstructured text. An ethical, legal and social issues (ELSI) component is included, which focuses in particular on community interaction and return of results.

Mayo eMERGE phase II project

As part of eMERGE-I, EMR-based algorithms were used to enable GWAS of several primary and network-wide phenotypes. In phase II of eMERGE (July 2011 to June 2015), the research infrastructure established in eMERGE-I is being leveraged to identify common genetic variants that influence medically important phenotypes.

The Mayo eMERGE-II cohort (6,916 people) includes the 3,769 eMERGE-I patients and an additional 3,147 individuals, the majority (90 percent) of whom were genotyped on the same Illumina 660W platform.

Mayo Clinic is working with other eMERGE-II sites to expand and validate the library of electronic phenotyping algorithms to enable GWAS of multiple phenotypes of interest. A major focus in phase II is to translate recent GWAS findings into clinical practice.

Specific aims are to:

• Conduct EMR-based GWAS to identify common genetic variants that influence 1) interindividual variation in cardiorespiratory fitness and response to statin medications, and 2) susceptibility to venous thromboembolism and heart failure.
• Quantify genetic risk of a common "complex" disease — coronary heart disease — and adverse drug reactions. Risk communication tools are being developed that convey the clinical and genetic components of risk to both patients and health care providers.
• Develop informatics approaches to incorporate genomic data into the EMR, including links to clinical decision support.
• Conduct a randomized clinical trial to investigate how patients respond to genetically informed coronary heart disease risk. Investigators will reconsent 150 eMERGE-I patients without coronary heart disease, have a genetic counselor communicate the results and discuss in detail the implications of the testing relevant to disease risk. The effectiveness of the communication and patients' comprehension of risk, as well as their hopes, concerns and planned changes in lifestyle, will be assessed by surveys and interviews after the patient-counselor encounter. As part of ongoing efforts in community consultation, a community advisory group specific to this project will be established.