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Psychiatric diseases are characterized by affective, behavioral, and cognitive abnormalities. The majority of psychiatric diseases share a common feature, namely that family history of disease is a major risk factor, which is suggestive of a strong genetic component to the underlying disease risk. Epidemiological studies have estimated high heritability values of up to 80% for many common psychiatric diseases, such as schizophrenia and bipolar disorder. Psychiatric research to date has uncovered little about the underlying biology of disease. Commonly used tools in biomedical research, such as suitable in vitro and in vivo model systems, are essentially absent.

This makes GWAS the perfect tool for gaining more fundamental insight into the etiology of psychiatric diseases. Moreover, large-scale genotyping has become more affordable by today’s standards. Indeed it is now feasible to analyze tens of thousands of individuals. This is a crucial requirement because large data sets are necessary for a successful GWAS of complex diseases as the apparent effect sizes are small.

In this presentation I will described current results from GWAS for a range of psychiatric diseases. We have identified here which components have been critical for its success and discuss how we learned from both failures and successes. By far, it has become clear that the most important step to scientific progress in human genetics of complex traits is collaboration and exchange of data. In a world where data (in this case genotype data) becomes available in enormous amounts, and where computer power increases significantly via computer clusters and cloud computing, it has been essential to bring everybody together to produce robust findings.

The most recent GWAS for schizophrenia, builds the central piece of this presentation. Here we obtained genome-wide genotype data from which we constructed 49 ancestry matched, non-overlapping case-control samples (34,241 cases and 45,604 controls) and 3 family-based samples of European ancestry (1,235 parent affected-offspring trios). Also we obtained replication data from deCODE genetics for two independent samples of European ancestry (1,513 cases and 66,236 controls) for our top findings.

We identify 128 independent associations spanning 108 conservatively defined physically distinct loci that meet genome-wide significance. Most of the associated loci are novel (N=84). The localization of associations to DRD2, multiple voltage-gated calcium channels, and genes involved in glutamatergic transmission, support leading aetiological hypotheses as well as highlight molecules of known and potential therapeutic relevance to schizophrenia.

In summary the analyses of common variants in psychiatric genetics is the main contributor to a huge scientific success that is in the process of changing the field with many robust genetic findings. It will continue to be a valuable source of information to the biology in psychiatry for the decades to come.