Electronic Medical Records and Genomics (eMERGE) Phase III (eMERGE)

• ClinicalTrials.gov Identifier: NCT03394859
• Recruitment Status: Completed
• First Posted: January 9, 2018
• Last Update Posted: May 28, 2020
• Sponsor: Vanderbilt University Medical Center
• Information provided by (Responsible Party): Josh Peterson, Vanderbilt University Medical Center

Study Description

Brief Summary:

The Electronic Medical Records and Genomics (eMERGE) Network is in its third phase and during this time is enrolling and sequencing 25,000 individuals on a custom sequencing panel of clinically relevant, actionable genes. The genetic results will be returned to participants and outcomes tracked through the electronic health records.

Condition or disease
Cardiac Disease; Cancer; Hypercholesterolemia; Diabetes; Kidney Diseases; Neuromuscular Diseases

Detailed Description:

The Electronic Medical Records and Genomics (eMERGE) Network is a National Human Genome Research Institute (NHGRI)-funded consortium tasked with developing methods and best practices for utilization of the electronic medical record (EMR) as a tool for genomic research. Phase III is focused on returning actionable gene variants to patients and measuring clinical outcomes. Ultimately, eMERGE hopes its efforts will result in improvements in health care, through safer and more effective prescription methodology, augmentation of primary and secondary prevention strategies, and enhanced understanding of the biology of disease.

eMERGE is composed of 10 clinical sites [ Childrens Hospital of Pennsylvania (CHOP); Cincinnati Children's Medical Center (CCHMC); Columbia University; Geisinger; Kaiser Permanente Washington with Washington University and the Fred Hutchinson Cancer Research Center; Harvard University; Mayo Clinic; Meharry Medical College; Northwestern University; Vanderbilt University Medical center (VUMC)], one non clinical site: Marshfield Clinic, two sequencing centers [Baylor college of Medicine; Partners Healthcare with Broad Institute], a Coordinating Center (VUMC), and the NHGRI. More information on the eMERGE Network can be found at www.gwas.org.

Each sites' research study is tailored to their specific interests. An eMERGE specific sequencing panel was designed and ran on participants covering 109 genes and 1551 Single Nucleotide Variants (SNVs), of which 68 genes and 14 SNVs are clinically actionable and are being returned to patients.

Study Design

• Study Type: Observational
• Actual Enrollment: 25380 participants
• Observational Model: Cohort
• Time Perspective: Prospective
• Official Title: Electronic Medical Records and Genomics (eMERGE) Phase III
• Actual Study Start Date: September 1, 2015
• Actual Primary Completion Date: April 1, 2020
• Actual Study Completion Date: April 1, 2020

Groups and Cohorts

Outcome Measures

Primary Outcome Measures :

1. Impact of return of clinically actionable results on patient treatment [ Time Frame: Six months post return of results ]
   The network will abstract data from patient electronic health records (EHR) six months after clinically actionable results have been returned to the patients and providers. The Network will determine changes in medication or treatments after return of the sequencing results. Outcome measures on patients receiving both positive and negative results will be analyzed.

Biospecimen Retention:   Samples With DNA

Blood samples are drawn from patients after consent in a CLIA certified manner. These samples are processed, DNA is extracted and sent to one of two sequencing centers (Baylor College of Medicine or Partners Healthcare with Broad Institute). DNA is then sequenced and clinical reports along with sequencing results returned to sites.

Eligibility Criteria

• Ages Eligible for Study: up to 120 Years (Child, Adult, Older Adult)
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: Yes
• Sampling Method: Probability Sample

Study Population

Approximately 2500 to 3000 participants are enrolled at each site. Two sites (CCHMC and CHOP) are primarily enrolling pediatric patients while the rest focus on adult populations. Each site has unique specific aims and due to this cohorts differ slightly at each site. After sequencing is complete the data from all sites will be pooled into one large data set to allow for cross site analysis.

Criteria

Inclusion Criteria:

• Age: 1 day old
• Vital status: Alive

Exclusion Criteria:

-None

Contacts and Locations

Sponsors and Collaborators

Vanderbilt University Medical Center

Investigators

• Principal Investigator: Teri Manolio, MD, PhD; National Human Genome Research Institute (NHGRI)
• Principal Investigator: John Harley, MD, PhD; Children's Hospital Medical Center, Cincinnati
• Principal Investigator: Hakon Hakonarson, MD, PhD; Children's Hospital of Philadelphia
• Principal Investigator: Chunhua Weng, PhD; Columbia University
• Principal Investigator: Marc Williams, MD; Geisinger Clinic
• Principal Investigator: Elizabeth Karlson, MD; Harvard University
• Principal Investigator: Scott Hebbring, PhD; Marshfield Clinic
• Principal Investigator: Iftikhar Kullo, MD; Mayo Clinic
• Principal Investigator: Samuel Adunyah, PhD; Meharry Medical College
• Principal Investigator: Rex Chisholm, PhD; Northwestern University
• Principal Investigator: Gail Jarvik, MD, PhD; Kaiser Permanente Washington with the University of Washington and the Fred Hutchinson Cancer Research Center
• Principal Investigator: Dan Roden, MD; Vanderbilt University Medical Center
• Principal Investigator: Heidi Rehm, PhD; Partners Healthcare with Broad Institute
• Principal Investigator: Richard Gibbs, PhD; Baylor College Medicine

More Information

Publications:

Dumitrescu L, Ritchie MD, Denny JC, El Rouby NM, McDonough CW, Bradford Y, Ramirez AH, Bielinski SJ, Basford MA, Chai HS, Peissig P, Carrell D, Pathak J, Rasmussen LV, Wang X, Pacheco JA, Kho AN, Hayes MG, Matsumoto M, Smith ME, Li R, Cooper-DeHoff RM, Kullo IJ, Chute CG, Chisholm RL, Jarvik GP, Larson EB, Carey D, McCarty CA, Williams MS, Roden DM, Bottinger E, Johnson JA, de Andrade M, Crawford DC. Genome-wide study of resistant hypertension identified from electronic health records. PLoS One. 2017 Feb 21;12(2):e0171745. doi: 10.1371/journal.pone.0171745. eCollection 2017.

Heit JA, Armasu SM, McCauley BM, Kullo IJ, Sicotte H, Pathak J, Chute CG, Gottesman O, Bottinger EP, Denny JC, Roden DM, Li R, Ritchie MD, de Andrade M. Identification of unique venous thromboembolism-susceptibility variants in African-Americans. Thromb Haemost. 2017 Apr 3;117(4):758-768. doi: 10.1160/TH16-08-0652. Epub 2017 Feb 16.

Sanderson SC, Brothers KB, Mercaldo ND, Clayton EW, Antommaria AHM, Aufox SA, Brilliant MH, Campos D, Carrell DS, Connolly J, Conway P, Fullerton SM, Garrison NA, Horowitz CR, Jarvik GP, Kaufman D, Kitchner TE, Li R, Ludman EJ, McCarty CA, McCormick JB, McManus VD, Myers MF, Scrol A, Williams JL, Shrubsole MJ, Schildcrout JS, Smith ME, Holm IA. Public Attitudes toward Consent and Data Sharing in Biobank Research: A Large Multi-site Experimental Survey in the US. Am J Hum Genet. 2017 Mar 2;100(3):414-427. doi: 10.1016/j.ajhg.2017.01.021. Epub 2017 Feb 9.

Wan Z, Vorobeychik Y, Xia W, Clayton EW, Kantarcioglu M, Malin B. Expanding Access to Large-Scale Genomic Data While Promoting Privacy: A Game Theoretic Approach. Am J Hum Genet. 2017 Feb 2;100(2):316-322. doi: 10.1016/j.ajhg.2016.12.002. Epub 2017 Jan 5.

Schmidt AF, Swerdlow DI, Holmes MV, Patel RS, Fairhurst-Hunter Z, Lyall DM, Hartwig FP, Horta BL, Hyppönen E, Power C, Moldovan M, van Iperen E, Hovingh GK, Demuth I, Norman K, Steinhagen-Thiessen E, Demuth J, Bertram L, Liu T, Coassin S, Willeit J, Kiechl S, Willeit K, Mason D, Wright J, Morris R, Wanamethee G, Whincup P, Ben-Shlomo Y, McLachlan S, Price JF, Kivimaki M, Welch C, Sanchez-Galvez A, Marques-Vidal P, Nicolaides A, Panayiotou AG, Onland-Moret NC, van der Schouw YT, Matullo G, Fiorito G, Guarrera S, Sacerdote C, Wareham NJ, Langenberg C, Scott R, Luan J, Bobak M, Malyutina S, Pająk A, Kubinova R, Tamosiunas A, Pikhart H, Husemoen LL, Grarup N, Pedersen O, Hansen T, Linneberg A, Simonsen KS, Cooper J, Humphries SE, Brilliant M, Kitchner T, Hakonarson H, Carrell DS, McCarty CA, Kirchner HL, Larson EB, Crosslin DR, de Andrade M, Roden DM, Denny JC, Carty C, Hancock S, Attia J, Holliday E, O'Donnell M, Yusuf S, Chong M, Pare G, van der Harst P, Said MA, Eppinga RN, Verweij N, Snieder H; LifeLines Cohort study group, Christen T, Mook-Kanamori DO, Gustafsson S, Lind L, Ingelsson E, Pazoki R, Franco O, Hofman A, Uitterlinden A, Dehghan A, Teumer A, Baumeister S, Dörr M, Lerch MM, Völker U, Völzke H, Ward J, Pell JP, Smith DJ, Meade T, Maitland-van der Zee AH, Baranova EV, Young R, Ford I, Campbell A, Padmanabhan S, Bots ML, Grobbee DE, Froguel P, Thuillier D, Balkau B, Bonnefond A, Cariou B, Smart M, Bao Y, Kumari M, Mahajan A, Ridker PM, Chasman DI, Reiner AP, Lange LA, Ritchie MD, Asselbergs FW, Casas JP, Keating BJ, Preiss D, Hingorani AD; UCLEB consortium, Sattar N. PCSK9 genetic variants and risk of type 2 diabetes: a mendelian randomisation study. Lancet Diabetes Endocrinol. 2017 Feb;5(2):97-105. doi: 10.1016/S2213-8587(16)30396-5. Epub 2016 Nov 29.

Smith ME, Sanderson SC, Brothers KB, Myers MF, McCormick J, Aufox S, Shrubsole MJ, Garrison NA, Mercaldo ND, Schildcrout JS, Clayton EW, Antommaria AH, Basford M, Brilliant M, Connolly JJ, Fullerton SM, Horowitz CR, Jarvik GP, Kaufman D, Kitchner T, Li R, Ludman EJ, McCarty C, McManus V, Stallings S, Williams JL, Holm IA. Conducting a large, multi-site survey about patients' views on broad consent: challenges and solutions. BMC Med Res Methodol. 2016 Nov 24;16(1):162.

Jackson KL, Mbagwu M, Pacheco JA, Baldridge AS, Viox DJ, Linneman JG, Shukla SK, Peissig PL, Borthwick KM, Carrell DA, Bielinski SJ, Kirby JC, Denny JC, Mentch FD, Vazquez LM, Rasmussen-Torvik LJ, Kho AN. Performance of an electronic health record-based phenotype algorithm to identify community associated methicillin-resistant Staphylococcus aureus cases and controls for genetic association studies. BMC Infect Dis. 2016 Nov 17;16(1):684.

Mosley JD, van Driest SL, Wells QS, Shaffer CM, Edwards TL, Bastarache L, McCarty CA, Thompson W, Chute CG, Jarvik GP, Crosslin DR, Larson EB, Kullo IJ, Pacheco JA, Peissig PL, Brilliant MH, Linneman JG, Denny JC, Roden DM. Defining a Contemporary Ischemic Heart Disease Genetic Risk Profile Using Historical Data. Circ Cardiovasc Genet. 2016 Dec;9(6):521-530. doi: 10.1161/CIRCGENETICS.116.001530. Epub 2016 Oct 25.

Verma SS, Cooke Bailey JN, Lucas A, Bradford Y, Linneman JG, Hauser MA, Pasquale LR, Peissig PL, Brilliant MH, McCarty CA, Haines JL, Wiggs JL, Vrabec TR, Tromp G, Ritchie MD; eMERGE Network; NEIGHBOR Consortium. Epistatic Gene-Based Interaction Analyses for Glaucoma in eMERGE and NEIGHBOR Consortium. PLoS Genet. 2016 Sep 13;12(9):e1006186. doi: 10.1371/journal.pgen.1006186. eCollection 2016 Sep.

Verma A, Verma SS, Pendergrass SA, Crawford DC, Crosslin DR, Kuivaniemi H, Bush WS, Bradford Y, Kullo I, Bielinski SJ, Li R, Denny JC, Peissig P, Hebbring S, De Andrade M, Ritchie MD, Tromp G. eMERGE Phenome-Wide Association Study (PheWAS) identifies clinical associations and pleiotropy for stop-gain variants. BMC Med Genomics. 2016 Aug 12;9 Suppl 1:32. doi: 10.1186/s12920-016-0191-8.

Lingren T, Chen P, Bochenek J, Doshi-Velez F, Manning-Courtney P, Bickel J, Wildenger Welchons L, Reinhold J, Bing N, Ni Y, Barbaresi W, Mentch F, Basford M, Denny J, Vazquez L, Perry C, Namjou B, Qiu H, Connolly J, Abrams D, Holm IA, Cobb BA, Lingren N, Solti I, Hakonarson H, Kohane IS, Harley J, Savova G. Electronic Health Record Based Algorithm to Identify Patients with Autism Spectrum Disorder. PLoS One. 2016 Jul 29;11(7):e0159621. doi: 10.1371/journal.pone.0159621. eCollection 2016.

• Responsible Party: Josh Peterson, Associate Professor of Biomedical Informatics, Vanderbilt University Medical Center
• ClinicalTrials.gov Identifier: NCT03394859
• Other Study ID Numbers: eMERGEIII
• First Posted: January 9, 2018
• Last Update Posted: May 28, 2020
• Last Verified: May 2020

Individual Participant Data (IPD) Sharing Statement:

• Plan to Share IPD: No

• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No

Additional relevant MeSH terms:

Neuromuscular Diseases; Kidney Diseases; Heart Diseases; Hypercholesterolemia; Urologic Diseases; Hyperlipidemias; Dyslipidemias; Lipid Metabolism Disorders; Metabolic Diseases; Nervous System Diseases; Cardiovascular Diseases