There is already a huge interest and even commercial pressure for marketing prognostic services based on common genetic variants [51]. However, this would require explicit knowledge of the exact identity and magnitude of the effect sizes associated with causal variants, an expansion of the list of associated variants and even more extensive replication across diverse populations and settings [52], with accumulation of evidence that can be confidently graded as having high credibility [53]. The extent to which genetic risk may lie in rare variants and may need to be approached and/or complemented with other high-throughput platforms (e.g. copy number variation) remains unquantified. Meta-analysis methods for such variants are likely to pose new challenges and would require careful interpretation. At the same time, the blossoming of human genome epidemiology research means that large numbers of teams may have access to high throughput facilities and that many GWA teams, consortia, replication studies, and isolated efforts may continue to perform research in parallel. The synthesis and synopsis [54] of all these data in what might be called conglomerate meta-analyses and the updating of
