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American Journal of Epidemiology Advance Access originally published online on July 13, 2005
American Journal of Epidemiology 2005 162(4):302-304; doi:10.1093/aje/kwi201
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American Journal of Epidemiology Copyright © 2005 by the Johns Hopkins Bloomberg School of Public Health All rights reserved

HUMAN GENOME EPIDEMIOLOGY (HuGE) COMMENTARIES

A Network of Investigator Networks in Human Genome Epidemiology

John P. A. Ioannidis1,2, Jonine Bernstein3, Paolo Boffetta4, John Danesh5, Siobhan Dolan6, Patricia Hartge7, David Hunter8, Peter Inskip7, Marjo-Riitta Jarvelin9,10, Julian Little11, Demetrius M. Maraganore12, Julia A.Newton Bishop13, Thomas R. O'Brien7, Gloria Petersen14, Elio Riboli15, Daniela Seminara16, Emanuela Taioli17, André G. Uitterlinden18, Paolo Vineis9,19, Deborah M. Winn7, Georgia Salanti20, Julian P. T. Higgins20,21 and Muin J. Khoury22

1 Clinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
2 Department of Medicine, Tufts University School of Medicine, Boston, MA
3 Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY
4 Gene-Environment Epidemiology Group, International Agency for Research on Cancer, Lyon, France
5 Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
6 March of Dimes, White Plains, NY
7 Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD
8 Department of Epidemiology, Harvard School of Public Health, Boston, MA
9 Department of Epidemiology and Public Health, Imperial College, London, United Kingdom
10 Department of Public Health Science and General Practice, University of Oulu, Oulu, Finland
11 Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, Canada
12 Department of Neurology, Mayo Clinic, Rochester, MN
13 Genetic Epidemiology Division, CR-UK Clinical Centre, Leeds, United Kingdom
14 Department of Health Sciences Research, Mayo Clinic, Rochester, MN
15 Unit of Nutrition and Cancer, International Agency for Research on Cancer, Lyon, France
16 Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD
17 Molecular and Genetic Epidemiology Unit, Ospedale Policlinico IRCCS, Milan, Italy
18 Departments of Internal Medicine and of Epidemiology and Biostatistics, Erasmus MC, Rotterdam, the Netherlands
19 ISI Foundation, Torino, Italy
20 MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
21 Public Health Genetics Unit, Strangeways Research Laboratory, Cambridge, United Kingdom
22 Office of Genomics and Disease Prevention, Centers for Disease Control and Prevention, Atlanta, GA

Correspondence to Dr. John P. A. Ioannidis, Clinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina 45110, Greece (e-mail: jioannid{at}cc.uoi.gr).

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.

epidemiology; genome; meta-analysis; multicenter studies


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