| Meta-analysis of genetic association studies under heterogeneity. | |
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MedLine Citation:
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PMID: 22643179 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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In multi-cohort genetic association studies or meta-analysis, associations of genetic variants with complex traits across cohorts may be heterogeneous because of genuine genetic diversity or differential biases or errors. To detect the associations of genes with heterogeneous associations across cohorts, new global fixed-effect (FE) and random-effects (RE) meta-analytic methods have been recently proposed. These global methods had improved power over both traditional FE and RE methods under heterogeneity in limited simulation scenarios and data application, but their usefulness in a wide range of practical situations is not clear. We assessed the performance of these methods for both binary and quantitative traits in extensive simulations and applied them to a multi-cohort association study. We found that these new approaches have higher power to detect mostly the very small to small associations of common genetic variants when associations are highly heterogeneous across cohorts. They worked well when both the underlying and assumed genetic models are either multiplicative or dominant. But, they offered no clear advantage for less common variants unless heterogeneity was substantial. In conclusion, these new meta-analytic methods can be used to detect the association of genetic variants with high heterogeneity, which can then be subjected to further exploration, in multi-cohort association studies and meta-analyses. |
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Authors:
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Binod Neupane; Mark Loeb; Sonia S Anand; Joseph Beyene |
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Publication Detail:
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Type: Journal Article; Meta-Analysis; Research Support, Non-U.S. Gov't Date: 2012-05-30 |
Journal Detail:
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Title: European journal of human genetics : EJHG Volume: 20 ISSN: 1476-5438 ISO Abbreviation: Eur. J. Hum. Genet. Publication Date: 2012 Nov |
Date Detail:
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Created Date: 2012-10-18 Completed Date: 2013-03-19 Revised Date: 2013-04-16 |
Medline Journal Info:
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Nlm Unique ID: 9302235 Medline TA: Eur J Hum Genet Country: England |
Other Details:
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Languages: eng Pagination: 1174-81 Citation Subset: IM |
Affiliation:
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Population Genomics Program, Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada. |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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Genetic Heterogeneity* Genome, Human Genome-Wide Association Study* Humans Models, Theoretical Polymorphism, Single Nucleotide |
| Grant Support | |
ID/Acronym/Agency:
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84392//Canadian Institutes of Health Research |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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