Advancing Scientific Progress through Genomic Data Sharing and Access
The National Institutes of Health (NIH) is interested in advancing genomic studies to identify common genetic factors that influence health and disease. The NIH Policy for Sharing of Data Obtained in NIH Supported or Conducted Genome-Wide Association Studies (NOT-OD-07-088) facilitates broad and consistent access to NIH-supported genomic data to speed the translation of basic genetic research into therapies, products, and procedures that benefit the public health.
NIH believes that the full value of genomic studies to the public can be realized only if the resulting genotype and phenotype data sets are made available as rapidly as possible to a wide range of scientific investigators. Such studies generally require significant resources, present challenges in the analysis of large data sets, and provide extraordinary opportunities for making comparisons across multiple studies.
On January 24, 2011, the Epidemiology and Genetics Research Program (EGRP) and the Division of Cancer Epidemiology and Genetics (DCEG) sponsored a Workshop on “Advancing Scientific Progress through Genomic Data Sharing and Access” to showcase the wealth of research generated by the NIH data sharing policy and discuss ways to improve the data access process. This 1-day event brought together NIH staff and researchers who have used publicly available genome-wide association study (GWAS) data. The Workshop agenda featured scientific presentations by approved users of NCI-sponsored genomic data sets and a town hall discussion on the expansion of the policy to genomic data sharing.
Conclusions drawn from this meeting will inform changes to the NIH GWAS data sharing policy and improvements to the dbGaP data access process.
Workshop Planning Committee and Participants
The Workshop Planning Committee included the following EGRP and DCEG staff members:
- Camilla Benedicto, M.P.H., Public Health Advisor, Office of the Associate Director, EGRP
- Laura Buccini, Dr.P.H., M.P.H., Program Director, Host Susceptibility Factors Branch (HSFB), EGRP
- Stephen Chanock, M.D., Chief, Laboratory of Translational Genomics, DCEG
- Elizabeth Gillanders, Ph.D., Chief, GEB, EGRP
- Geoffrey Tobias, Program Analyst, Human Genetics Program (HGP), DCEG
- Margaret Tucker, M.D., Director, HGP, DCEG
Other NCI participants included DCEG’s Patricia Hartge, Sc.D., Neil Caporaso, M.D., and Nilanjan Chatterjee, Ph.D., who moderated the scientific presentations by approved users of the NIH Database on Genotypes and Phenotypes (dbGaP) data sets, and members of the Cancer Genetic Markers of Susceptibility (CGEMS) and Extramural NCI Data Access Committees (DACs). Several extramural investigators spoke about the ways in which they have used genomic data available publicly through dbGaP, including: Nancy Cox, Ph.D., University of Chicago; Carolyn Hutter, Ph.D., Fred Hutchinson Cancer Research Center; Jianfeng Xu, M.D., Dr.P.H., Wake Forest University School of Medicine; Christopher Amos, Ph.D., University of Texas MD Anderson Cancer Center; Struan Grant, Ph.D., The Children’s Hospital of Philadelphia; Robert Martin Plenge, M.D., Ph.D., Harvard Medical School and Brigham and Women’s Hospital; Dezheng Huo, M.D., M.S., Ph.D., University of Chicago; and Itsik Pe’er, Ph.D., M.S., Columbia University. Workshop presenters and participants also included staff from the National Human Genome Research Institute (NHGRI), National Center for Biotechnology Information (NCBI), and Nature Genetics.
Related Funding Opportunities
NCI currently is participating in a trans-NIH Ethical, Legal, and Social Implications (ELSI) Request for Applications (RFA-HG-11-003) led by the NHGRI. The focus of this RFA is to stimulate empirical research to develop a preliminary evidence base to inform decision-making about whether, when, and how to offer to return individual research results to participants in genomic research studies (especially whole-exome or whole-genome sequencing studies) or to individuals who have provided samples or data for genomic repositories (such as biobanks or databases such as dbGaP).
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