Schizophrenia genetics: Building the foundations of the future

In recent years, our understanding of the genetic architecture of schizophrenia, a phrase which denotes the numbers of risk variants, their frequencies and effect sizes, has been transformed. This has come about through advances in technology that have allowed almost the entire human genome to be simultaneously interrogated for the presence of disease-associated genetic variation and allows this to be performed in sample sizes powered for a realistic possibility of success. Another development has been the emergence of international consortia willing to share raw data and their coalescence into super-consortia to achieve sample sizes and bodies of clinical and analytic expertise that was unimaginable a decade ago. These innovations have driven the emergence of statistically robust and replicable genetic findings in schizophrenia, and a rapid escalation in the number of those findings over the last 5 years. The latest example comes from the Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC-SCZ) which, at the time of publication, included contributions from around 37 000 individuals with schizophrenia, 302 investigators, 35 countries, and 4 continents.1 In their recent paper, published in Nature in July 2014, the PGC-SCZ group report 128 statistically independent genetic associations, implicating a minimum of 108 conservatively defined schizophrenia-associated genetic loci.1 Of the identified loci, 83 have not been previously robustly supported as playing a role in schizophrenia, but it is also important to note the findings are consistent with previous literature; 25 loci that had previously been reported as associated with schizophrenia in large samples were again supported in this much larger analysis, confirming that the use of large samples and stringent statistical cut-offs results in reproducible findings. The availability of so many robustly supported findings offers immense opportunities for investigating and advancing our understanding of etiology