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IJE Advance Access originally published online on December 20, 2006
International Journal of Epidemiology 2007 36(2):439-445; doi:10.1093/ije/dyl253
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Published by Oxford University Press on behalf of the International Epidemiological Association 2006
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org

On the synthesis and interpretation of consistent but weak gene–disease associations in the era of genome-wide association studies

Muin J Khoury1,*, Julian Little2, Marta Gwinn1 and John PA Ioannidis3

1National Office of Public Health Genomics, Coordinating Center for Health Promotion, Centers for Disease Control and Prevention.
2Canada Research Chair in Human Genome Epidemiology, Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Canada.
3Department of Hygiene and Epidemiology University of Ioannina School of Medicine, Ioannina, Greece and Department of Medicine, Tufts University School of Medicine, Boston, USA.

* Corresponding author. National Office of Public Health Genomics, Centers for Disease Control and Prevention, 4770 Buford Hwy, Atlanta GA 30341 USA (mailstop K89). E-mail: mkhoury{at}cdc.gov


  Abstract

Emerging technologies are allowing researchers to study hundreds of thousands of genetic variants simultaneously as risk factors for common complex diseases. Both theoretical considerations and empirical evidence suggest that specific genetic variants causally associated with common diseases will have small effects (risk ratios mostly <2.0). However, the combination of even a few small effects (e.g. effects of fewer than 20 common genetic variants) could account for a sizeable population attributable fraction of common diseases and shed important light on disease pathogenesis and environmental determinants. Nevertheless, the inauguration of genome-wide association studies only magnifies the challenge of differentiating between the expected, true weak associations from the numerous spurious effects caused by misclassification, confounding and significance-chasing biases. Standards are urgently needed for presenting and interpreting cumulative evidence on gene–disease associations, especially for consistent but weak associations. Criteria for synthesis of the evidence should include sound methods for study conduct and analysis, biological plausibility, experimental evidence and adequate replication in large-scale, collaborative studies. Efforts by the Human Genome Epidemiology Network (HuGENet) are currently ongoing to streamline and operationalize these criteria for data on genetic associations with common diseases.

Keywords Epidemiological methods, genomics, risk ratios, genome-wide analysis

Accepted 21 October 2006


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