The eMERGE III study is an exciting collaboration between Mayo Clinic and Mountain Park Health Center in Arizona that's funded by the NHGRI and the Mayo Clinic Center for Individualized Medicine. Ethical, legal, and social implications of incorporating genomic information into electronic health records. Hazin R, Brothers KB, Malin BA, Koenig BA, Sanderson SC, Rothstein MA, Williams MS, Clayton EW, Kullo IJ.Return of results in the genomic medicine projects of the eMERGE network. Kullo IJ, Haddad R, Prows CA, Holm I, Sanderson SC, Garrison NA, Sharp RR, Smith ME, Kuivaniemi H, Bottinger EP, Connolly JJ, Keating BJ, McCarty CA, Williams MS, Jarvik GP.Return of genomic results to research participants: the floor, the ceiling, and the choices in between. Jarvik GP, Amendola LM, Berg JS, Brothers K, Clayton EW, Chung W, Evans BJ, Evans JP, Fullerton SM, Gallego CJ, Garrison NA, Gray SW, Holm IA, Kullo IJ, Lehmann LS, McCarty C, Prows CA, Rehm HL, Sharp RR, Salama J, Sanderson S, Van Driest SL, Williams MS, Wolf SM, Wolf WA eMERGE Act-ROR Committee and CERC Committee CSER Act-ROR Working Group, Burke W.

A major focus in phase II was to translate recent GWAS findings into clinical practice. The Mayo eMERGE-II cohort (6,916 people) includes the 3,769 eMERGE-I patients and an additional 3,147 people, the majority (90 percent) of whom were genotyped on the same Illumina 660W platform. In phase II of eMERGE (July 2011 to June 2015), the research infrastructure established in eMERGE-I was leveraged to identify common genetic variants that influence medically important phenotypes. An ethical, legal and social issues (ELSI) component was included and focused in particular on community interaction and return of results. Phenotype characteristics and covariates relevant to statistical genetic analyses were derived using EHR-based algorithms, including diagnosis and procedure codes, laboratory data, medication use, and natural language processing of unstructured text. The Mayo Clinic eMERGE I project aimed to identify genetic loci associated with peripheral artery disease and red blood cell traits, including hemoglobin, hematocrit, red blood cell count, mean corpuscular volume, mean corpuscular hemoglobin and mean corpuscular hemoglobin concentration. Leveraging informatics for genetic studies: use of the electronic medical record to enable a genome-wide association study of peripheral arterial disease. Kullo IJ, Fan J, Pathak J, Savova GK, Ali Z, Chute CG.A genome-wide association study of red blood cell traits using the electronic medical record. Kullo IJ, Ding K, Jouni H, Smith CY, Chute CG.

Group Health Cooperative (with the University of Washington).

The network is funded by the National Human Genome Research Institute (NHGRI) to develop and implement approaches for leveraging biorepositories with EHR systems for large-scale genomic research, including genome-wide association studies (GWAS), sequencing and structural variation. Kullo's Atherosclerosis and Lipid Genomics Laboratory is conducting electronic health record (EHR)-based genetic studies. As part of the Electronic Medical Records and Genomics (eMERGE) Network, the research team in Dr.

Andres kullo