Medical Journal of The Islamic Republic of Iran (MJIRI)
Iran University of Medical Sciences
Thu, Jul 11, 2024
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Volume 38, Issue 1 (1-2024)
Med J Islam Repub Iran 2024 |
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Eybpoosh S, Ahmadi S A Y. Pleiotropic Bias and Study Design Considerations in Genetic Association Studies. Med J Islam Repub Iran 2024; 38 (1) :336-339
URL: http://mjiri.iums.ac.ir/article-1-8708-en.html
URL: http://mjiri.iums.ac.ir/article-1-8708-en.html
Research Centre for emerging and reemerging infectious diseases, Department of Epidemiology and Biostatistics, Pasteur institute of Iran, Tehran, Iran , s_eybpoosh@pasteur.ac.ir
Abstract: (61 Views)
Background: Case-control studies are efficient designs for investigating gene-disease associations. A discovery of genome-wide association studies (GWAS) is that many genetic variants are associated with multiple health outcomes and diseases, a phenomenon known as pleiotropy. We aimed to discuss about pleiotropic bias in genetic association studies.
Methods: The opinions of the researchers on the basis of the literature were presented as a critical review.
Results: Pleiotropic effect can bias the results of gene-disease association studies if they use individuals with pre-existing diseases as the control group, while the disease in cases and controls have shared genetic markers. The idea supports the conclusion that when the exposure of interest in a case-control study is a genetic marker, the use of controls from diseased cases that share similar genetic markers may increase the risk of pleiotropic effect. However, not manifesting the disease symptoms among controls at the time of recruitment does not guarantee that the individual will not develop the disease of interest in the future. Age-matched disease-free controls may be a better solution in similar situations. Different analytical techniques are also available that can be used to identify pleiotropic effects. Known pleiotropic effects can be searched from various online databases.
Conclusion: Pleiotropic effects may result in bias in genetic association studies. Suggestions consist of selecting healthy yet age-matched controls and considering diseases with independent genetic architecture. Checking the related databases is recommended before designing a study.
Methods: The opinions of the researchers on the basis of the literature were presented as a critical review.
Results: Pleiotropic effect can bias the results of gene-disease association studies if they use individuals with pre-existing diseases as the control group, while the disease in cases and controls have shared genetic markers. The idea supports the conclusion that when the exposure of interest in a case-control study is a genetic marker, the use of controls from diseased cases that share similar genetic markers may increase the risk of pleiotropic effect. However, not manifesting the disease symptoms among controls at the time of recruitment does not guarantee that the individual will not develop the disease of interest in the future. Age-matched disease-free controls may be a better solution in similar situations. Different analytical techniques are also available that can be used to identify pleiotropic effects. Known pleiotropic effects can be searched from various online databases.
Conclusion: Pleiotropic effects may result in bias in genetic association studies. Suggestions consist of selecting healthy yet age-matched controls and considering diseases with independent genetic architecture. Checking the related databases is recommended before designing a study.
Keywords: Pleiotropy, Research Design, Observational Study, Genetic Epidemiology, Case-Control Studies, Genetic Association Studies
Type of Study: Review Article |
Subject:
Epidemiology
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