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Study Description

The Electronic Medical Records and Genomics (eMERGE) Network is a National Institutes of Health (NIH)-organized and funded consortium of U.S. medical research institutions. The primary goal of the eMERGE Network is to develop, disseminate, and apply approaches to research that combine biorepositories with electronic medical record (EMR) systems for genomic discovery and genomic medicine implementation research. eMERGE was announced in June 2007 and began its third phase in September 2015. eMERGE Phase III (June 2015 - June 2020) consists of 10 study sites, two central sequencing and genotyping facilities, and a coordinating center.

Included in this study are:

  • Human Reference Consortium (HRC) single nucleotide variants and 1000 Genomes structural variants imputed array data of 105,108 eMERGE participants from nine Phase III study sites and three Phase II study site collaborators.
  • Corresponding demographics, body mass index measurements.
  • Case/control status for the following phenotypes: Abdominal aortic aneurysm; Ace-Inhibitor/Cough; Attention Deficit Hyperactivity Disorder; Age-related macular disease; Appendicitis; Asthma; Atopic Dermatitis; Autism; Benign Prostatic Hyperplasia; Carotid artery disease as a Quantitative Measure; caMRSA; Cataract; Clostridium difficile colitis; Extreme Obesity; Chronic Kidney Disease; Chronic Kidney Disease and Type 2 Diabetes; Chronic Kidney Disease, Type 2 Diabetes and Hypertension; Colon Polyps; Cardiorespiratory Fitness; Dementia; Diverticulosis; Diabetic retinopathy; Gastroesophageal Reflux Disease; Glaucoma; Height; Heart failure; Hypothyroidism; Lipids; Ocular hypertension; Peripheral Arterial Disease; QRS duration; Red blood cell indices; Remission of Diabetes after ROUX-EN-Y gastric bypass surgery; Resistant hypertension; MACE while on Statins; Type 2 Diabetes; Venous Thromboembolism; White blood cell indices; and Zoster virus infection.

Study sites and participants include:

Boston Children's Hospital: The Gene Partnership (TGP) is a prospective longitudinal registry at Boston Children's Hospital (BCH) to study the genetic and environmental contributions to childhood health and disease, collect genetic information on a large number of children who have been phenotyped, and implement the Informed Cohort and the Informed Cohort Oversight Board (ICOB). The term "The Gene Partnership" reflects a partnership between researchers and participants. Children seen at BCH are offered enrollment, as are their parents and siblings. DNA is collected on all enrollees. BCH has a comprehensive EMR system, and virtually all inpatient and outpatient data are captured electronically. Clinical data in the BCH EMR is loaded in the i2b2 data warehouse which is available to investigators. Cases, phenotypes, and covariates are ascertained using the i2b2 database. Participants at BCH in TGP have consented to receive any research result and/or incidental finding that arises from studies using TGP that is approved by the Informed Cohort Oversight Board (ICOB) and is in accordance with the participants'preferences;results are returned through the Personally Controlled Health Record (PCHR). BCH and Cincinnati Children's Hospital Medical Center (CCHMC) have partnered as the Pediatric Alliance for Genomic and Electronic Medical Record (EMR) Research (PAGER) site for the eMERGE Phase II network for pediatric institutions, and the cohort for eMERGE at BCH is TGP.

Children's Hospital of Pennsylvania (CHOP): The Center for Applied Genomics (CAG) at the Children's Hospital of Philadelphia (CHOP) is a high-throughput, highly automated genotyping and sequencing facility equipped with state-of-the-art genotyping and sequencing platforms. Children who are treated at the Children's Hospital Healthcare Network and their parents may be eligible to take part in a major initiative to collect more than 100,000 blood samples, covering a wide range of pediatric diseases. A large majority of participants consenting to prospective genomic analyses also consent to analysis of their de-identified electronic health records (EHRs). EHRs are longitudinal, with a mean duration of 6.5 years.

Cincinnati Children's Hospital Medical Center/Boston's Children's Hospital (CCHMC/BCH): Cincinnati Children's Hospital Medical Center (CCHMC) is a pediatric institution dedicated to improving health and welfare of children and to the discovery and practical application of new genomic information to the ordinary care of children. CCHMC brings an extraordinary faculty to eMERGE III who are committed to gain a better understanding of the genesis of disease and to elucidate the mechanisms of diseases that afflict children, specifically pediatric disease phenotypes that will leverage the available eMERGE adult genomic data and electronic medical records (EMRs) to discover meaningful use results. Generation of EMR phenotype algorithms, informed by natural language processing, using heuristic and machine learning methods is ongoing. CCHMC has developed tools to evaluate adolescent return of results preferences, examined the ethical and legal obligations and potential to reanalyze results, and developed clinical decision support for phenotyping, test ordering, and returning sequencing results. The success of these eMERGE III studies is enhanced by the ongoing institutional investment made in the CCHMC Biobank, the comprehensive EMR (EPIC), the i2b2 de-identified medical record data warehouse, and hundreds of faculty and senior staff who make genomics or informatics an active focus of their research.

Columbia University: Columbia University Medical Center/New York Presbyterian (CUMC/NYP) Hospital system is one of the nation's largest and most comprehensive hospital systems with over 2 million inpatient and outpatient yearly visits that serves a racially and ethnically diverse urban patient population. The Columbia University GENomic Integration with EHR (GENIE) research study contributed and shared phenotype and genotype data for individuals who were recruited as part of a diverse array of initiatives within the hospital, including Northern Manhattan Study (NOMAS), Pediatric Cardiac Genomic Consortium (PCGC), Caribbean Hispanics with Familial and Sporadic Late Onset Alzheimer's disease (AD), Alzheimer's Disease Sequencing Project (ADSP), and Genetics of Chronic Kidney Disease study. Some of these individuals had kidney or neurological problems, some were healthy adult volunteers with self-reported health status information from the medically underserved Northern Manhattan community, and others were pediatric patients with cardiac conditions. For the kidney disease cohort, patients with the diagnosis of Chronic Kidney Disease (CKD) and healthy controls were recruited to the Columbia University CKD biobank. For the NOMAS cohort, eligible participants were stroke-free, were 40 years old, and resided for at least 3 months in a Northern Manhattan household with a telephone. The PCGC study recruited parent-offspring trios with pediatric probands diagnosed with congenital heart defects (CHD). For the Caribbean Hispanics with Alzheimer's disease project, individuals from families affected by AD and with sporadic AD were recruited, along with unrelated controls. Samples for the ADSP study have been selected from well-characterized cohorts of individuals with AD diagnosis.

Geisinger Health System: A research cohort of adult Geisinger Clinic patients was enrolled from community-based primary care clinics of the Geisinger Health System. Patients were eligible for enrollment if they were a primary care patient of a Geisinger Clinic physician and were scheduled for a non-emergent clinic visit. All participants provided written informed consent and HIPAA authorization. Consenting patients agreed to provide blood samples for broad biomedical research use, and permission to access data in their Geisinger electronic medical record for research. The enrollment rate was 90% of patients approached. The demographics of the cohort approximate those of the Geisinger Clinic outpatient population. Research blood samples were collected during an outpatient clinical phlebotomy encounter. Research blood samples are coded and stored in a central biorepository. Samples are linkable to clinical data in a de-identified manner for research via an IRB-approved data broker process. For genomic analysis, DNA is extracted from EDTA-anticoagulated whole blood.

Partners Health Care (Harvard): The Partners HealthCare Biobank is a large research program designed to help researchers understand how people's health is affected by their genes, lifestyle, and environment. This large research data and sample repository provides access to high-quality, consented blood samples to help foster research, advance our understanding of the causes of common diseases, and advance the practice of medicine. For the Partners research community (Massachusetts General Hospital and Brigham and Women's Hospital), the Biobank provides:

  1. Banked samples (plasma, serum, and DNA) collected from consented patients
  2. Blood samples that were discarded after clinical testing in the Crimson Cores maintained in the Brigham and Women's Hospital and Massachusetts General Hospital Pathology Departments
  3. Sample handling and preparation services
  4. Link to the biobank data to the Partners Research Patient Data Registry (RPDR) a research instance of our electronic clinical chart
  5. Data access through our research portal.

To date, over 60,000 Partners patients have given their consent to enroll, give a blood sample, receive research results and agreed to be re-contacted for additional research studies. The Biobank has enabled Partners investigators to compete for nationally recognized grants in personalized medicine such as a clinical electronic Medical Records and Genomics network (eMERGE) site and the national All of US program. The Biobank currently supports over 120 Partners investigators and over 100 million dollars in NIH research.

Kaiser Permanente Washington with the University of Washington and the Fred Hutchinson Cancer Research Center: KPWA participants were enrolled in the eMERGE Network through the Northwest Institute of Genetic Medicine (NWIGM) biorepository, and provided the appropriate consent to receive clinically relevant genetic results (N~8,073.) NWIGM is based at the University of Washington and co-managed by the University of Washington and KPWA. The purpose of the NWIGM biorepository is to build infrastructure and resources to carry out a broad range of future genetic research. KPWA members enrolled in the biorepository are asked to provide informed consent to providing a DNA sample for storage in the NWIGM biorepository. The consent is purposefully broad to serve the dual purpose of reducing the burden on researchers who wish to use this biorepository and the IRB committees who will be responsible for reviewing these requests in the future. Participants were eligible if aged 50 - 65 years old at the time of their enrollment into the NWIGM repository, living, enrolled in KPWA's integrated group practice, and had completed an online Health Risk Appraisal. The selection algorithm was based on several data sources from the EHR at KPWA. 1) Demographics - participants with self-reported race as Asian ancestry were prioritized and selected to enrich for non-European ancestry. The KPWA eMERGE cohort includes n=1,245 members of Asian ancestry. 2) Participants were also selected for a history of colorectal cancer (n=1,002), in order to allow us to enrich germline pathogenic variants.

Essentia Institute of Rural Health, Marshfield Clinic, Pennsylvania State University (Marshfield): The Marshfield Clinic Personalized Medicine Research Project is a population-based biobank in central Wisconsin with more than 20,000 adult subjects who provided written, informed consent to access their medical records and provided a blood sample from which DNA was extracted and plasma and serum stored. In addition to an average of 30 years of medical history data, a questionnaire about environmental exposures, including a detailed food frequency questionnaire, is available to facilitate gene/environment studies.

Mayo Clinic: The Mayo Vascular Disease Biorepository is a disease-specific biobank for vascular diseases including peripheral arterial disease (PAD). PAD patients were identified from individuals referred to the non-invasive vascular laboratory for lower extremity arterial evaluation. Since 1997, laboratory findings have been recorded into an electronic database employing an in-house software package for data archiving and retrieval;this data becomes part of the Mayo EMR. Patients referred to the center with suspected PAD undergo a comprehensive non-invasive evaluation including the ankle-brachial index (ABI) - the ratio of blood pressure measured in the upper arms divided by blood pressure measured at the ankles. Controls subjects are identified from patients referred to the Cardiovascular Health Clinic for stress ECG. The prevalence of PAD in patients with normal exercise capacity who do not have inducible ischemia on the stress ECG , was <1%. Data regarding risk factors for atherosclerosis such as diabetes, dyslipidemia, hypertension, and smoking are ascertained from the EMR. Case control study of venous thromboembolism (PI John Heit) Controls from a case control study of pancreatic cancer (PI Gloria Petersen) Mayo Clinic Biobank.

Icahn School of Medicine at Mount Sinai School (Mt. Sinai): The Institute for Personalized Medicine (IPM) Biobank Project is a consented, EMR-linked medical care setting biorepository of the Mount Sinai Medical Center (MSMC) drawing from a population of over 70,000 inpatients and 800,000 outpatient visits annually. MSMC serves diverse local communities of upper Manhattan, including Central Harlem (86% African American), East Harlem (88% Hispanic Latino), and Upper East Side (88% Caucasian/white) with broad health disparities. IPM Biobank populations include 28% African American (AA), 38% Hispanic Latino (HL) predominantly of Caribbean origin, 23% Caucasian/White (CW). IPM Biobank disease burden is reflective of health disparities with broad public health impact: average body mass index of 28.9 and frequencies of hypertension (55%), hypercholesterolemia (32%), diabetes (30%), coronary artery disease (25%), chronic kidney disease (23%), among others. Biobank operations are fully integrated in clinical care processes, including direct recruitment from clinical sites, waiting areas and phlebotomy stations by dedicated Biobank recruiters independent of clinical care providers, prior to or following a clinician standard of care visit. Recruitment currently occurs at a broad spectrum of over 30 clinical care sites.

Northwestern University: The NUgene Project is a repository with longitudinal medical information from participating patients at affiliated hospitals and outpatient clinics from the Northwestern University Medical Center. Participants'DNA samples are coupled with data from a self-reported questionnaire and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 2 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators.

Vanderbilt University Medical Center: BioVU, Vanderbilt's DNA databank, was designed as an enabling resource for exploration of the relationships among genetic variation, disease susceptibility, and variable drug responses. BioVU acquires DNA from discarded blood samples collected from routine patient care. The biobank is linked to de-identified clinical data extracted from Vanderbilt's EMR, which forms the basis for phenotype definitions used in genotype-phenotype correlations. BioVU is currently the largest single site DNA collection world-wide, at >235,000 samples as of spring 2017.

Authorized Access
Publicly Available Data
  Link to other NCBI resources related to this study
Study Inclusion/Exclusion Criteria

Eligible subjects were determined using electronic algorithms applied to existing EMRs:

  1. FOR Abdominal aortic aneurysm (Please see additional document AAA definition)
  2. FOR Ace-I Cough (Please see additional document ACE definition)
  3. FOR Attention Deficit Hyperactivity Disorder (Please see additional document ADHD definition)
  4. FOR Age-related macular disease (Please see additional document AMD definition)
  5. FOR Appendicitis (Please see additional document Appendicitis definition)
  6. FOR Asthma (Please see additional document Asthma definition)
  7. FOR Atopic Dermatitis (Please see additional document Atopic dermatitis definition)
  8. FOR Autism (Please see additional document Autism definition)
  9. FOR Benign Prostatic Hyperplasia (Please see additional document BPH definition)
  10. FOR Carotid artery disease as a Quantitative Measure (Please see additional document CAAD definition)
  11. FOR caMRSA (Please see additional document caMRSA definition)
  12. FOR Cataract (Please see additional document Cataract definition)
  13. FOR Clostridium difficile colitis (Please see additional document Clostridium difficile definition)
  14. FOR Childhood Obesity (Please see additional document Childhood obesity definition)
  15. FOR Chronic Kidney Disease (Please see additional document Chronic kidney disease definition)
  16. FOR Chronic Kidney Disease and Type 2 Diabetes (Please see additional document Chronic kidney disease definition)
  17. FOR Chronic Kidney Disease, Type 2 Diabetes and Hypertension (Please see additional document Chronic kidney disease definition)
  18. FOR Colon Polyps (Please see additional document Colon polyps definition)
  19. FOR Cardiorespiratory Fitness (Please see additional document Cardiorespiratory fitness definition)
  20. FOR Dementia (Please see additional document Dementia definition)
  21. FOR Diverticulosis (Please see additional document Diverticulosis definition)
  22. FOR Diabetic retinopathy (Please see additional document Diabetic retinopathy definition)
  23. FOR Extreme Obesity (Please see additional document Extreme obesity definition)
  24. FOR Gastroesophageal Reflux Disease (Please see additional document (Please see additional document GERD definition)
  25. FOR Glaucoma (Please see additional document Glaucoma definition)
  26. FOR Height (Please see additional document Height definition)
  27. FOR Heart Failure (Please see additional document Heart failure definition)
  28. FOR Hypothyroidism (Please see additional document Hypothyroidism definition)
  29. FOR Lipids (Please see additional document Lipids definition)
  30. FOR Ocular Hypertension (Please see additional document Ocular hypertension definition)
  31. FOR Peripheral Arterial Disease (Please see additional document PAD definition)
  32. FOR QRS duration(Please see additional document (Please see additional document QRS definition)
  33. FOR Red blood cell indices (Please see additional document Red blood cell indices definition)
  34. FOR Remission of Diabetes after ROUX-EN-Y (Please see additional document Diabetes remission following Roux-en-Y gastric bypass definition)
  35. FOR Resistant hypertension (Please see additional document Resistant hypertension definition)
  36. FOR Major Adverse Cardiac Events (MACE) while on Statins (Please see additional document MACE on Statins definition)
  37. FOR Type 2 Diabetes (Please see additional document Type 2 Diabetes definition)
  38. FOR Venous Thromboembolism (Please see additional document Venous thromboembolism definition)
  39. FOR White blood cell indices (Please see additional document White blood cell indices definition)
  40. FOR Herpes zoster infection (Please see additional document Herpes zoster infection definition)

Molecular Data
TypeSourcePlatformNumber of Oligos/SNPsSNP Batch IdComment
Imputation Roche NimbleGen Nimblegen Custom SeqCap N/A N/A Michigan Imputation Server; 1000 Genomes Project
Selected Publications
Diseases/Traits Related to Study (MeSH terms)
Authorized Data Access Requests
See articles in PMC citing this study accession
Study Attribution
  • Principal Investigators
    • Hakon Hakonarson, MD, PhD. Children's Hospital of Philadelphia, Philadelphia, PA, USA.
    • John Harley, MD, PhD. Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
    • Chunhua Weng, PhD, MS. Columbia University Medical Center and New York Presbyterian Hospital, New York, NY, USA.
    • Ali Gharavi, MD. Columbia University Medical Center and New York Presbyterian Hospital, New York, NY, USA.
    • George Hripcsak, MD, MS. Columbia University Medical Center/New York Presbyterian Hospital, New York, NY, USA.
    • Marc Williams, MD. Geisinger Health, Danville, PA, USA.
    • Marylyn Ritchie, PhD. Geisinger Health, Danville, PA, USA.
    • Elizabeth Karlson, MD. Harvard Medical School, Brigham and Women's Hospital, Massachusetts General Hospital, Partners HealthCare Personalized Medicine, Cambridge, MA, USA.
    • Shawn Murphy, MD, PhD. Harvard Medical School, Brigham and Women's Hospital, Massachusetts General Hospital, Partners HealthCare Personalized Medicine, Cambridge, MA, USA.
    • Jordan Smoller, MD, ScD. Harvard Medical School, Brigham and Women's Hospital, Massachusetts General Hospital, Partners HealthCare Personalized Medicine, Cambridge, MA, USA.
    • Scott Weiss, MD, MS. Harvard Medical School, Brigham and Women's Hospital, Massachusetts General Hospital, Partners HealthCare Personalized Medicine, Cambridge, MA, USA.
    • Eric Larson, MD, MPH. Kaiser Permanente Washington with the University of Washington and the Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
    • Gail Jarvik, MD, PhD. Kaiser Permanente Washington with the University of Washington and the Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
    • Iftikhar Kullo, MD. Mayo Clinic, Rochester, MN, USA.
    • Stephen Thibodeau, PhD. Mayo Clinic, Rochester, MN, USA.
    • Rex Chisholm, PhD. Northwestern University, Chicago, IL, USA.
    • Maureen Smith, MS. Northwestern University, Chicago, IL, USA.
    • Dan Roden, MD. Vanderbilt University Medical Center, Nashville, TN, USA.
    • Josh Denny, MD, MS. Vanderbilt University Medical Center, Nashville, TN, USA.
    • Richard Sharp, PhD. Mayo Clinic, Rochester, MN, USA.
    • Josh Peterson, MD, MPH. Vanderbilt University Medical Center, Nashville, TN, USA.
    • Murray Brilliant, PhD. Marshfield Clinic Research Institute, Marshfield, WI, USA.
    • Cathy McCarty, PhD, MPH. Essentia Rural Health, Duluth, MN, USA.
    • Isaac Kohane, MD, PhD. Boston Children's Hospital, Boston, MA, USA.
    • Erwin Bottinger, MD. Icahn School of Medicine at Mount Sinai, New York, NY, USA.
    • David Carey, PhD. Geisinger Health System, Danville, PA, USA.
  • Funding Sources
    • U01HG8684. Children's Hospital of Philadelphia, Philadelphia, PA, USA.
    • U01HG8666. Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
    • U01HG8680. Columbia University Medical Center and New York Presbyterian Hospital, New York, NY, USA.
    • U01HG8679. Geisinger Health, Danville, PA, USA.
    • U01HG8685. Harvard Medical School, Brigham and Women's Hospital, Massachusetts General Hospital, Partners HealthCare Personalized Medicine, Cambridge, MA, USA.
    • U01HG8657. Kaiser Permanente Washington with the University of Washington and the Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
    • U01HG6379. Mayo Clinic, Rochester, MN, USA.
    • U01HG8673. Northwestern University, Chicago, IL, USA.
    • U01HG8672. Vanderbilt University Medical Center, Nashville, TN, USA.
    • U01HG8701. Vanderbilt University Medical Center, Nashville, TN, USA.
    • U01HG006389. Essentia Institute of Rural Health, Duluth, MN; Marshfield Clinic Research Foundation, Marshfield, WI; Pennsylvania State University, University Park, PA, USA.
    • U01HG006828. Cincinnati Children's Hospital Medical Center, Cincinnati, OH; Boston Children's Hospital, Boston, MA, USA.
    • U01HG006380. Icahn School of Medicine at Mount Sinai, New York, NY, USA.