False Appearance of Gene–Environment Interactions in Genetic Association Studies
Autor: | Wen-Chung Lee, Yi-Shan Su |
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Rok vydání: | 2016 |
Předmět: |
Confounding Factors (Epidemiology)
Observational Study 01 natural sciences Macular Degeneration 010104 statistics & probability 03 medical and health sciences 0302 clinical medicine Bias Statistics Odds Ratio Humans Medicine Computer Simulation 030212 general & internal medicine 0101 mathematics Gene–environment interaction Genetic Association Studies Genetic association Genetic heterogeneity business.industry Null (mathematics) Confounding Factors Epidemiologic General Medicine Odds ratio Environmental exposure Complement Factor H Relative risk ComputingMethodologies_DOCUMENTANDTEXTPROCESSING Gene-Environment Interaction business Research Article |
Zdroj: | Medicine |
ISSN: | 0025-7974 |
DOI: | 10.1097/md.0000000000002743 |
Popis: | Supplemental Digital Content is available in the text Under the assumption of gene–environment independence, unknown/unmeasured environmental factors, irrespective of what they may be, cannot confound the genetic effects. This may lead many people to believe that genetic heterogeneity across different levels of the studied environmental exposure should only mean gene–environment interaction—even though other environmental factors are not adjusted for. However, this is not true if the odds ratio is the effect measure used for quantifying genetic effects. This is because the odds ratio is a “noncollapsible” measure—a marginal odds ratio is not a weighted average of the conditional odds ratios, but instead has a tendency toward the null. In this study, the authors derive formulae for gene–environment interaction bias due to noncollapsibility. They use computer simulation and real data example to show that the bias can be substantial for common diseases. For genetic association study of nonrare diseases, researchers are advised to use collapsible measures, such as risk ratio or peril ratio. |
Databáze: | OpenAIRE |
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