Combining information from related meta-analyses of genetic association studies
When synthesizing data from genetic association studies researchers frequently perform several related meta-analyses, perhaps on different polymorphisms of the same gene, or on different outcomes, or they might define subgroups of studies by factors such as ethnicity, gender or study design. Current...
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| Main Authors: | , , , , |
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| Format: | Article |
| Published: |
2018
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| Subjects: | |
| Online Access: | https://repository.li.mahidol.ac.th/handle/123456789/19153 |
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| Institution: | Mahidol University |
| Summary: | When synthesizing data from genetic association studies researchers frequently perform several related meta-analyses, perhaps on different polymorphisms of the same gene, or on different outcomes, or they might define subgroups of studies by factors such as ethnicity, gender or study design. Current practice is to perform a totally separate meta-analysis of each set of studies; however, when the meta-analyses investigate related questions, it is possible that the estimates in one meta-analysis could be improved by using information from another. The meta-analytic model for a genetic association study can be parameterized in terms of four meaningful parameters: the size of the genetic effect, the genetic model, the allele frequency in controls and the degree of departure from Hardy-Weinberg equilibrium in controls. Even when the size of the genetic effect differs across meta-analyses, it may be possible to assume that some of the other parameters are common. The models are applied to a meta-analysis of the same gene-disease relationship in three different ethnic groups. © 2008 Royal Statistical Society. |
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