Journal Article

Sample Size Needed to Detect Gene-Gene Interactions using Association Designs

Shuang Wang and Hongyu Zhao

in American Journal of Epidemiology

Published on behalf of Johns Hopkins Bloomberg School of Public Health

Volume 158, issue 9, pages 899-914
Published in print November 2003 | ISSN: 0002-9262
Published online November 2003 | e-ISSN: 1476-6256 | DOI: http://dx.doi.org/10.1093/aje/kwg233
Sample Size Needed to Detect Gene-Gene Interactions using Association Designs

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It is likely that many complex diseases result from interactions among several genes, as well as environmental factors. The presence of such interactions poses challenges to investigators in identifying susceptibility genes, understanding biologic pathways, and predicting and controlling disease risks. Recently, Gauderman (Am J Epidemiol 2002;155:478–84) reported results from the first systematic analysis of the statistical power needed to detect gene-gene interactions in association studies. However, Gauderman used different statistical models to model disease risks for different study designs, and he assumed a very low disease prevalence to make different models more comparable. In this article, assuming a logistic model for disease risk for different study designs, the authors investigate the power of population-based and family-based association designs to detect gene-gene interactions for common diseases. The results indicate that population-based designs are more powerful than family-based designs for detecting gene-gene interactions when disease prevalence in the study population is moderate.

Keywords: genetic predisposition to disease; genetics; interaction; research design; sample size

Journal Article.  7359 words.  Illustrated.

Subjects: Public Health and Epidemiology

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