studies in schizophrenia. Some have argued6,7,18 that common variants play little role in the etiology of schizophrenia and that the GWA approach for schizophrenia has been misconceived. Our results refute this conjecture that common variants play little role in the etiology of schizophrenia and that the GWA approach for schizophrenia has been misconceived by demonstrating that at least one quarter of variation in liability to schizophrenia is tagged by SNPs and that common causal variants must be responsible for most of this signal. Therefore, larger sample sizes are likely to achieve the statistical power necessary to detect additional effects (over those detected to date) with genome-wide significance. For example, a GWA for height17, considered as a model complex trait, identified 180 robustly associated loci in a total sample size of 180,000 individuals and the identified variants were concentrated in pathways biologically associated with growth. Sample sizes of ~50,000 schizophrenia cases and 50,000 controls are needed to afford the same power to detect variants that explain the same proportion of phenotypic variance and gain insight into biological pathways achieved in the height study11,12,22. Our results imply that the GWA approach applied to larger case-control samples will deliver important results for schizophrenia.
