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IJE Advance Access originally published online on September 26, 2007
International Journal of Epidemiology 2008 37(1):120-132; doi:10.1093/ije/dym159
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Published by Oxford University Press on behalf of the International Epidemiological Association © The Author 2007; all rights reserved.

Assessment of cumulative evidence on genetic associations: interim guidelines

John PA Ioannidis1–3,*, Paolo Boffetta4, Julian Little5, Thomas R O’Brien6, Andre G Uitterlinden7, Paolo Vineis8, David J Balding8, Anand Chokkalingam9, Siobhan M Dolan10, W Dana Flanders11, Julian PT Higgins12, Mark I McCarthy13,14, David H McDermott15, Grier P Page16, Timothy R Rebbeck17, Daniela Seminara18 and Muin J Khoury19

1Clinical and Molecular Epidemiology Unit, University of Ioannina School of Medicine, Ioannina 45110, Greece.
2Biomedical Research Institute, Foundation for Research and Technology – Hellas, Ioannina 45110, Greece.
3Department of Medicine, Tufts University School of Medicine, Boston MA 02111, USA.
4International Agency for Research on Cancer, Lyon 69008, France.
5Department of Epidemiology and Community Medicine, Canada Research Chair in Human Genome Epidemiology, University of Ottawa, Ottawa, Ontario K1H 8M5, Canada.
6Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Rockville MD 02982, USA.
7Departments of Internal Medicine and Epidemiology & Biostatistics, Erasmus MC, Rotterdam 3000 CA, The Netherlands.
8Department of Epidemiology and Public Health, Imperial College, St Mary's Campus, London, W2 1PG London, UK.
9School of Public Health, University of California, Berkeley, CA 94707, USA.
10Department of Obstetrics and Gynecology and Women's Health, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY 10461, USA.
11Emory University, Rollins School of Public Health, Department of Epidemiology, 1518 Clifton Rd, Atlanta, GA 30327, USA.
12MRC Biostatistics Unit, Institute of Public Health, University Forvie Site, Robinson Way, Cambridge CB2 0SR, UK.
13Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Headington, Oxford, OX3 7LJ, UK.
14Wellcome Trust Centre for Human Genetics, University of Oxford, Headington, Oxford, OX3 7BM, UK.
15Laboratory of Molecular Immunology, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD 20892, USA.
16Department of Biostatistics, University of Alabama at Birmingham School of Public Health, Birmingham, AL 35294, USA.
17Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104-6021, USA.
18Epidemiology and Genetics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Rockville, MD 20892, USA.
19National Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA, USA.

*Corresponding author. Professor J Ioannidis, Clinical and Molecular Epidemiology Unit, University of Ioannina School of Medicine, Ioannina 45110, Greece. E-mail: jioannid{at}cc.uoi.gr


  Abstract

Established guidelines for causal inference in epidemiological studies may be inappropriate for genetic associations. A consensus process was used to develop guidance criteria for assessing cumulative epidemiologic evidence in genetic associations. A proposed semi-quantitative index assigns three levels for the amount of evidence, extent of replication, and protection from bias, and also generates a composite assessment of ‘strong’, ‘moderate’ or ‘weak’ epidemiological credibility. In addition, we discuss how additional input and guidance can be derived from biological data. Future empirical research and consensus development are needed to develop an integrated model for combining epidemiological and biological evidence in the rapidly evolving field of investigation of genetic factors.

Keywords Epidemiologic methods, genetics, genomics, causality, evidence

Accepted 9 July 2007


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