The centralization of human genomic variation data is a critical step in accelerating genomic medicine. The creation of a single, unified database of genome-wide structural and sequence-level variation will not only enable more efficient approaches to data analysis, but will also ensure the use of a uniform set of standards across clinical and research applications. The success of such a database has already been demonstrated for structural variation with this group's ongoing effort, the International Standards for Cytogenomic Arrays (ISCA) Consortium, which has made major advances in establishing resources for data analysis and interpretation. To address the critical need to expand this effort to genome-wide sequence-level variation and to unite variation data within a single resource, the following Specific Aims are proposed;1) Develop a standardized infrastructure for data acquisition, submission and public access for a clinical genomic variation database. 2) Coordinate the submission of variant and phenotypic data into ClinVar, a unified database at the National Center for Biotechnology Information (NCBI). 3) Implement sustainable expert clinical level curation systems for human genomic variants. Recognizing that their ability to standardize the clinical interpretation of variants will be much improved if larger bodies of data are availabl, many clinical laboratories in the US have already agreed to provide access to their data for this project. Access to all data and evidence on human genomic variants will be maintained within the ClinVar database, and the state of variant understanding will be graded, allowing components of the centralized database to be used for different applications, from clinical decision support to basic science research. A centralized database will also allow us to harness the collective experience of multiple laboratories to support evidence-based curation of structural and sequence-level variants leading to a clinical grade database of genome-wide variation. This innovative project will create a resource that can be used for a variety of applications, providing valuable data for the day-to-day interpretation of clinical laboratory results, for research investigations, and for the development of guidelines surrounding the use of genetic information in clinical care.

Public Health Relevance

Hundreds of thousands of disease-causing variants have been identified in patients with disease, yet only a small fraction of that data, and the interpretation of it, is accessible to researchers and clinicians. This project will serve to collect and organize genomic data from many sources into a free and publically accessible environment and enable expert curation of that data for use in improving healthcare and biomedical research.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Biotechnology Resource Cooperative Agreements (U41)
Project #
1U41HG006834-01A1
Application #
8503747
Study Section
Special Emphasis Panel (ZHG1-HGR-M (J2))
Program Officer
Brooks, Lisa
Project Start
2013-09-23
Project End
2016-07-31
Budget Start
2013-09-23
Budget End
2014-07-31
Support Year
1
Fiscal Year
2013
Total Cost
$2,986,850
Indirect Cost
$602,186
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
02115
Henrie, Alex; Hemphill, Sarah E; Ruiz-Schultz, Nicole et al. (2018) ClinVar Miner: Demonstrating utility of a Web-based tool for viewing and filtering ClinVar data. Hum Mutat 39:1051-1060
Shen, Lishuang; Attimonelli, Marcella; Bai, Renkui et al. (2018) MSeqDR mvTool: A mitochondrial DNA Web and API resource for comprehensive variant annotation, universal nomenclature collation, and reference genome conversion. Hum Mutat 39:806-810
Wain, Karen (2018) A Commentary on Opportunities for the Genetic Counseling Profession through Genomic Variant Interpretation: Reflections from an Ex-Lab Rat. J Genet Couns 27:747-750
Oza, Andrea M; DiStefano, Marina T; Hemphill, Sarah E et al. (2018) Expert specification of the ACMG/AMP variant interpretation guidelines for genetic hearing loss. Hum Mutat 39:1593-1613
Ghosh, Rajarshi; Harrison, Steven M; Rehm, Heidi L et al. (2018) Updated recommendation for the benign stand-alone ACMG/AMP criterion. Hum Mutat 39:1525-1530
Ormond, Kelly E; Hallquist, Miranda L G; Buchanan, Adam H et al. (2018) Developing a conceptual, reproducible, rubric-based approach to consent and result disclosure for genetic testing by clinicians with minimal genetics background. Genet Med :
Bush, Lynn W; Beck, Anita E; Biesecker, Leslie G et al. (2018) Professional responsibilities regarding the provision, publication, and dissemination of patient phenotypes in the context of clinical genetic and genomic testing: points to consider-a statement of the American College of Medical Genetics and Genomics (AC Genet Med 20:169-171
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
Tavtigian, Sean V; Greenblatt, Marc S; Harrison, Steven M et al. (2018) Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework. Genet Med 20:1054-1060
Sanghvi, Rashesh V; Buhay, Christian J; Powell, Bradford C et al. (2018) Characterizing reduced coverage regions through comparison of exome and genome sequencing data across 10 centers. Genet Med 20:855-866

Showing the most recent 10 out of 78 publications