Title: A ROAD MAP FOR EFFICIENT AND RELIABLE HUMAN GENOME EPIDEMIOLOGY Authors
|Ioannidis, John - UNIV OF IOANNINA, GREECE|
|Gwinn, Marta - CENTER DIS CONTROL PREV|
|Little, Julian - UNIV OF OTTAWA CANADA|
|Higgins, Julian - UNIV OF CAMBRIDGE UK|
|Bernstein, Jonine - MEMORIAL SLOAN-KETTERING|
|Boffeta, Paolo - INT AGENCY RES CA, FRANCE|
|Bondy, Melissa - MD ANDERSON CANCER CENTER|
|Brenchley, Paul - MANCHEDTER INST NEPH TRAN|
|Buffler, Patricia - UNIV OF CALIFORNIA|
Submitted to: Nature Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: October 15, 2005
Publication Date: January 15, 2006
Citation: Ioannidis, J.P., Gwinn, M., Little, J., Higgins, J.P.T., Bernstein, J.L., Boffeta, P., Bondy, M., Bray, M.S., Brenchley, P.E., Buffler, P.A. 2006. A road map for efficient and reliable human genome epidemiology. Nature Genetics. 38(1):3-5. Interpretive Summary: Many genetic studies have been performed with a great deal of conflicting results. These conflicting results occur because many studies only have a small number and/or specialized groups of individuals to study, and their results may not be representative of all people. Thus, many groups have begun to form networks of research teams who can share study samples and information and perform studies that cover a wider range of individuals. In order to provide some support and guidance for the formation of these networks, a "Network of Investigator Networks" has been set up, sponsored by the Human Genome Epidemiology (HuGE) Network. This paper summarizes the various types of guidance (organization, publications, etc.) that the Network of Networks will provide.
Technical Abstract: Network of investigators have begun sharing best practices, tools, and methods for analysis of associations between genetic variation and common diseases. A Network of Investigator Networks has been set up to drive the process, sponsored by the Human Genome Epidemiology Network. A workshop is planned to develop consensus guidelines for reporting results of genetic association studies. Published literature databases will be integrated, and unpublished data, including 'negative' studies, will be captured by online journals and through investigator network. Systematic reviews will be expanded to include more mete-analyses of individual-level data and prospective mata-analyses. Field synopses will offer regularly updated overviews.