Abstract
Objective
The aim of the study was to consider statistical and methodological issues affecting
the results of meta-analysis of genetic association studies for pertinent gene–disease
associations. Although the basic statistical issues for performing meta-analysis are
well described in the literature, there are remaining methodological issues.
Study Design and Setting
An analysis of our database and a literature review were performed to assess issues
such as departure of Hardy–Weinberg equilibrium, genetic contrasts, sources of bias
(replication validity, early extreme contradictory results, differential magnitude
of effect in large versus small studies, and “racial” diversity), utility of cumulative
and recursive cumulative meta-analyses. Gene–gene–environment interactions and methodological
challenges of genome-wide association studies are discussed.
Results
Departures from Hardy–Weinberg equilibrium can be handled using sensitivity analysis
or correction procedures. A spectrum of genetic models should be investigated in the
absence of biological justification. Cumulative and recursive cumulative meta-analyses
are useful to explore heterogeneity in risk effect in time. Exploration of bias leading
to heterogeneity provides insight to postulated genetic effects. In the presence of
bias, results should be interpreted with caution.
Conclusions
Meta-analysis provides a robust tool to investigate contradictory results in genetic
association studies by estimating population-wide effects of genetic risk factors
in diseases and explaining sources of bias and heterogeneity.
Keywords
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Article info
Publication history
Accepted:
December 19,
2007
Identification
Copyright
© 2008 Elsevier Inc. Published by Elsevier Inc. All rights reserved.
