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The Electronic Medical Records and Genomics (eMERGE) Network Phase III - Coordinating Center (U01)

电子病历和基因组学 (eMERGE) 网络第三期 - 协调中心 (U01)

基本信息

批准号：
10164633
负责人：
Joseph F. Peterson
金额：
$ 90.04万
依托单位：
VANDERBILT UNIVERSITY MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-06-01 至 2021-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10164633
关键词：
2019-nCoV Address Algorithms Bioinformatics Breathing COVID-19 COVID-19 pandemic Candidate Disease Gene Cardiovascular system Characteristics Clinical Clinical Data Clinical Research Communities Computerized Medical Record Data Development Disease Disease Outcome Disease susceptibility Electronic Health Record Electronic Medical Records and Genomics Network Environment Fibrinogen Foundations Funding Future Genes Genetic Genome Genomic medicine Genomics Goals Health Hospitalization Individual Infection Intervention Investigation Longevity Lung Medical Genetics Mining Outcome Parents Participant Patient Care Patients Phase Phenotype Population Positioning Attribute Predisposition Preventive treatment Prophylactic treatment Protocols documentation Recording of previous events Records Reporting Research Research Activity Research Institute Resources Risk Assessment Risk Management Science Severities Severity of illness Shapes Signs and Symptoms Site Socioeconomic Factors Structure Symptoms System Telefacsimile Telephone To specify Translational Research Universities Vaccination Vaccines Validation Virus Washington base biobank cerebrovascular clinical practice clinical risk comorbidity coronavirus disease data warehouse design disorder risk electronic data electronic structure experience genetic analysis genetic epidemiology genetic risk factor genomic data global health improved infection risk interest novel organizational structure outcome forecast pandemic disease personalized care phenome polygenic risk score recruit screening support network treatment strategy

项目摘要

As the COVID-19 pandemic emerged in early 2020 and rapidly spread across the US, an urgent need developed to improve our current understanding of what factors increase infection risk, likelihood of severe illness, or poor outcomes. Early reports suggest genetics, personal health history, socioeconomic factors, and one's environment increases risk of infection or differences in outcomes, but little is known with high confidence. As there are currently no vaccinations or other preventative treatment, understanding clinical and genetic risk factors would immediately improve our ability to manage the pandemic across populations and deliver precision care at the bedside. The Electronic Medical Records and Genomics (eMERGE) Network has the expertise and resources to investigate the factors leading to increased COVID disease susceptibility by rapidly compiling data from electronic health records (EHRs) and mining records for gene and disease associations. To perform this task well, the features of COVID disease course and characteristics of patients with COVID-19 and those who serve as controls must be precisely defined (“ePhenotyped”) across different record system. Our experience with phenotyping and imputing genomic and EHR data across large populations will enable us to quickly merge a large number of COVID-19 patients for future genome and phenome wide association studies, polygenic risk assessments, and candidate gene studies. Our specific aims include first to create and deploy ePhenotypes for immediate research use establishing a COVID case definition, severity scale, and comorbidities with relation to outcomes. Secondly, we propose to collect COVID EHR and genomic data centrally for future translational research. These resources will be beneficial to the scientific community, necessary to predict comprehensive risk of disease across the lifespan, and have the potential to impact downstream patient care.

随着2019冠状病毒病大流行于2020年初出现并迅速在美国蔓延，迫切需要