Electronic Medical Records and Genomics (eMERGE) Phase III

Cancer Clinical Trial

— eMERGE  

Official title:

Electronic Medical Records and Genomics (eMERGE) Phase III

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT03394859
• Other study ID #: eMERGEIII
• Status: Completed
• Start date: September 1, 2015
• Est. completion date: April 1, 2020

Study information

• Verified date: May 2020
• Source: Vanderbilt University Medical Center
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial 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.

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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 25380
• Est. completion date: April 1, 2020
• Est. primary completion date: April 1, 2020
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: N/A to 120 Years

Eligibility

Inclusion Criteria:

• Age: 1 day old

• Vital status: Alive

Exclusion Criteria:

-None

Related Conditions & MeSH terms

• Cancer
• Cardiac Disease
• Diabetes
• Heart Diseases
• Hypercholesterolemia
• Kidney Diseases
• Neuromuscular Diseases

Locations

Country	Name	City	State
n/a

Sponsors (1)

Lead Sponsor	Collaborator
Vanderbilt University Medical Center

References & Publications (11)

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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, Pajak 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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

* Note: There are 11 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Impact of return of clinically actionable results on patient treatment	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.	Six months post return of results