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There has been a steep increase in the number of meta-analyses of genome-wide association (GWA) studies aimed at identifying genetic variants with increasingly smaller effects, but pressure to publish findings of new genetic associations has limited the time available for careful consideration of all of their methodological aspects. The authors surveyed the literature (2007-2010) to provide empirical evidence on the methods used in GWA meta-analyses, including their organization, requirements about the uniformity of methods used in primary studies, methods for data pooling, investigation of between-study heterogeneity, and quality of reporting. This review showed that a great variety of methods are being used, but the rationale for their choice is often unclear. It also highlights how important methodological aspects have received insufficient attention, potentially leading to missed opportunities for improving gene discovery and characterization. Evaluation of power to replicate findings was inadequate, and the number of variants selected for replication was not associated with replication sample size. A low proportion of GWA meta-analyses investigated the presence and magnitude of heterogeneity, even when there was little uniformity in methods used in primary studies. More methodological work is required before clear guidance can be offered as to optimal methods or tradeoffs between alternative methods. However, there is a clear need for guidelines for reporting the results of GWA meta-analyses.

Although there has been a rapid rise in the publication of meta-analyses of genetic association studies, little is known about their methodological quality. The authors reviewed the quality of 120 randomly selected genetic meta-analyses published between 2005 and 2007. Data extracted included issues of general relevance and other issues specific to genetic epidemiology. Quality was markedly poorer in the 26% of the meta-analyses that accompanied a report on a primary study. Such meta-analyses were predominantly published in specialist journals, and their quality was positively associated with the impact factor of the journal. Among the meta-analyses that did not accompany a primary study, Human Genome Epidemiology reviews tended to score better than the others, although the comparison was limited by relatively small numbers. Comparison of the overall quality with that of genetic meta-analyses published before 2000 showed improvement in both conduct and reporting. However, the quality of the handling of specific genetic issues remains disappointingly low. For a few key general quality issues, the authors compared their findings with findings in other fields of medicine and found that general quality was similar. On the basis of this review, the authors provide practical recommendations for the conduct and reporting of genetic meta-analyses.

A number of studies have investigated two common polymorphisms in the beta(2)-adrenoceptor gene, Arg/Gly16 and Gln/Glu27, in relation to asthma susceptibility. The authors performed a meta-analysis of each polymorphism, as well as haplotype analysis, for adult and pediatric populations separately, using published data, supplemented by additional data requested from the original authors. Individual analysis detected no effect of Arg/Gly16 in adults but did suggest a recessive protective effect of Gly16 for children, with an odds ratio of 0.71 (95% confidence interval (CI): 0.53, 0.96) compared with the other genotypes. Results for Gln/Glu27 in adults seem to indicate that heterozygotes are at decreased risk of asthma than either homozygote (odds ratio = 0.73, 95% CI: 0.62, 0.87), although the studies are heterogeneous; in children, the Glu/Glu genotype has a decreased risk of asthma (odds ratio = 0.60, 95% CI: 0.35, 0.99) compared with the other genotypes. Despite the proximity of these two polymorphic sites, the linkage disequilibrium coefficient of 0.41 was not high (p < 0.001). Haplotype analysis suggests that there may be an interaction between the two sites, with a lower risk of asthma associated with the Glu27 allele (compared with Gln27), and that this risk is modified by the allele at position 16.