Journal Article

A Network of Investigator Networks in Human Genome Epidemiology

John P. A. Ioannidis, Jonine Bernstein, Paolo Boffetta, John Danesh, Siobhan Dolan, Patricia Hartge, David Hunter, Peter Inskip, Marjo-Riitta Jarvelin, Julian Little, Demetrius M. Maraganore, Julia A.Newton Bishop, Thomas R. O'Brien, Gloria Petersen, Elio Riboli, Daniela Seminara, Emanuela Taioli, André G. Uitterlinden, Paolo Vineis, Deborah M. Winn, Georgia Salanti, Julian P. T. Higgins and Muin J. Khoury

in American Journal of Epidemiology

Published on behalf of Johns Hopkins Bloomberg School of Public Health

Volume 162, issue 4, pages 302-304
Published in print August 2005 | ISSN: 0002-9262
Published online August 2005 | e-ISSN: 1476-6256 | DOI: http://dx.doi.org/10.1093/aje/kwi201
A Network of Investigator Networks in Human Genome Epidemiology

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The task of identifying genetic determinants for complex, multigenetic diseases is hampered by small studies, publication and reporting biases, and lack of common standards worldwide. The authors propose the creation of a network of networks that include groups of investigators collecting data for human genome epidemiology research. Twenty-three networks of investigators addressing specific diseases or research topics and representing several hundreds of teams have already joined this initiative. For each field, the authors are currently creating a core registry of teams already participating in the respective network. A wider international registry will include all other teams also working in the same field. Independent investigators are invited to join the registries and existing networks and to join forces in creating additional ones as needed. The network of networks aims to register these networks, teams, and investigators; be a resource for information about or connections to the many networks; offer methodological support; promote sound design and standardization of analytical practices; generate inclusive overviews of fields at large; facilitate rapid confirmation of findings; and avoid duplication of effort.

Keywords: epidemiology; genome; meta-analysis; multicenter studies

Journal Article.  1374 words. 

Subjects: Public Health and Epidemiology

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