The eMERGE III Clinical Center proposal from Partners HealthCare leverages a large biobank, clinical data in the electronic medical records (EMR) for >4 million participants from the largest integrated health care provider in New England, advanced bioinformatics expertise and state-of-the-art genetic analysis. We propose three aims. (1) Aim 1. Discovery. We will test the hypothesis that common and rare variants from a custom chip including 50,000 loss of function (LoF) alleles will be associated with cardiovascular, neuropsychiatric and immune-mediated phenotypes derived from the EMR. We are currently genotyping 25,000 Partners HealthCare Biobank subjects with a custom chip that includes LoF alleles from 63,000 exomes that we have analyzed. (2) Aim 2. Penetrance and Pleiotropy. We will test the hypothesis that sequencing a set of established genes or loci will allow us to discover additional variation, and define penetrance and pleiotropy using EMR phenotypes. Rare variants in genes selected by the eMERGE network will be studied for penetrance and pleiotropic outcomes by PheWAS and chart review. In addition, we are poised to perform recall-by-genotype studies because all Biobank participants have provided consent for such callback. (3) Aim 3. Implementation. We will test the hypothesis that physicians will alter their surveillance and treatment of patients based upon voluntary return of actionable variants to provide safe and cost-effective benefits to patients. We will screen our entire Biobank population of 25,000 individuals for pathogenic variants in the LDLR gene, the leading genetic cause of premature coronary artery disease, and conduct an exploratory trial in disclosing this information. Biobank participants with pathogenic variants in LDLR will be offered enrollment into a randomized trial, in which their finding will be CLIA-confirmed, and in one arm, this result will be communicated to their physicians through the EMR. Over one year, we will collect the following outcomes through participant surveys and EMR queries: physician visits, laboratory testing, changes in medication prescriptions, LDL levels, medical costs and the number of family members screened and treated as a result of the intervention. We will collaborate with the entire eMERGE III Network to incorporate what we learn from this pilot trial into large-scale implementation protocols for the genes selected by the Network for sequencing. Finally, we will participate in all Network activities to enhance the movement of genetics into clinical practice.

Public Health Relevance

The discovery and clinical use of genetic variants associated with both rare Mendelian and more common complex diseases promises to dramatically change the practice of medicine. Our eMERGE III project will leverage a large Biobank and a rich electronic medical record to define the phenotypic impact of mutations emerging from sequencing and then return results on selected variants to Biobank participants using a clinical trial.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project--Cooperative Agreements (U01)
Project #
1U01HG008685-01
Application #
8968123
Study Section
Special Emphasis Panel (ZHG1-HGR-N (M1))
Program Officer
Li, Rongling
Project Start
2015-09-01
Project End
2019-05-31
Budget Start
2015-09-01
Budget End
2016-05-31
Support Year
1
Fiscal Year
2015
Total Cost
$972,425
Indirect Cost
$320,768
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
02115
Yu, Zhi; Kim, Seoyoung C; Vanni, Kathleen et al. (2018) Association between inflammation and systolic blood pressure in RA compared to patients without RA. Arthritis Res Ther 20:107
Can, Anil; Castro, Victor M; Dligach, Dmitriy et al. (2018) Lipid-Lowering Agents and High HDL (High-Density Lipoprotein) Are Inversely Associated With Intracranial Aneurysm Rupture. Stroke 49:1148-1154
Mosley, Jonathan D; Feng, QiPing; Wells, Quinn S et al. (2018) A study paradigm integrating prospective epidemiologic cohorts and electronic health records to identify disease biomarkers. Nat Commun 9:3522
Chen, Chia-Yen; Lee, Phil H; Castro, Victor M et al. (2018) Genetic validation of bipolar disorder identified by automated phenotyping using electronic health records. Transl Psychiatry 8:86
Fossey, Robyn; Kochan, David; Winkler, Erin et al. (2018) Ethical Considerations Related to Return of Results from Genomic Medicine Projects: The eMERGE Network (Phase III) Experience. J Pers Med 8:
Prado, Maria G; Iversen, Maura D; Yu, Zhi et al. (2018) Effectiveness of a Web-Based Personalized Rheumatoid Arthritis Risk Tool With or Without a Health Educator for Knowledge of Rheumatoid Arthritis Risk Factors. Arthritis Care Res (Hoboken) 70:1421-1430
Sparks, Jeffrey A; Iversen, Maura D; Yu, Zhi et al. (2018) Disclosure of Personalized Rheumatoid Arthritis Risk Using Genetics, Biomarkers, and Lifestyle Factors to Motivate Health Behavior Improvements: A Randomized Controlled Trial. Arthritis Care Res (Hoboken) 70:823-833
Wei, Wei-Qi; Li, Xiaohui; Feng, Qiping et al. (2018) LPA Variants Are Associated With Residual Cardiovascular Risk in Patients Receiving Statins. Circulation 138:1839-1849
Can, Anil; Castro, Victor M; Dligach, Dmitriy et al. (2018) Elevated International Normalized Ratio Is Associated With Ruptured Aneurysms. Stroke 49:2046-2052
Can, Anil; Rudy, Robert F; Castro, Victor M et al. (2018) Low Serum Calcium and Magnesium Levels and Rupture of Intracranial Aneurysms. Stroke 49:1747-1750

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