Trends in meta-analysis of genetic association studies.
The number of published genetic association studies (GASs) is increasing tremendously due to the availability of mapped single-nucleotide polymorphisms (SNPs) and advances in genotyping technologies. A search in HuGENet illustrates the rapid accumulation of evidence for major diseases. Recently, there has been a lot of activity regarding genome-wide association studies (GWASs), and a growing number of forthcoming studies is expected. GASs and GWASs are usually underpowered to detect significant associations, and the varying quality of reporting publications befuddles researchers. A meta-analysis can increase power and provide standards of reporting results. However, the conduct of a meta-analysis of GASs faces a major obstacle, which is the structure and diversity of stored information in databases. Similar problems are expected for GWASs, though the data are not yet publicly available. The development of a Web-based system for the detailed and structured recording of GAS or GWAS data, accompanied by an estimation of the overall genetic risk effects, would enable scientists to keep track of evidence for gene-disease associations.
Zintzaras
Elias
E
Department of Biomathematics, University of Thessaly School of Medicine, Papakyriazi 22, Larissa, 41222, Greece. zintza@med.uth.gr.|Center for Clinical Evidence Synthesis, Institute for Clinical Research and Health Policy Studies, Tufts-New England Medical Center, Tufts University School of Medicine, Boston, MA, USA. zintza@med.uth.gr.
Lau
Joseph
J
Center for Clinical Evidence Synthesis, Institute for Clinical Research and Health Policy Studies, Tufts-New England Medical Center, Tufts University School of Medicine, Boston, MA, USA.
D030541:Databases, Genetic; D016021:Epidemiologic Studies; D020022:Genetic Predisposition to Disease; D015894:Genome, Human; D005838:Genotype; D006801:Humans; D015201:Meta-Analysis as Topic; D010641:Phenotype; D011110:Polymorphism, Genetic