New technologies provide insights into genetic basis of psychiatric disorders and explain their co-morbidity.

The completion of Human Genome Project and the "HapMap" project was followed by translational activities from companies within the private sector. This led to the introduction of genome-wide scans based on hundreds of thousands of single nucleotide polymorphysms (SNP). These scans were based on common genetic variants in human populations. This new and powerful technology was then applied to the existing DNA-based datasets with information on psychiatric disorders. As a result, an unprecedented amount of novel scientific insights related to the underlying biology and genetics of psychiatric disorders was obtained. The dominant design of these studies, so called "genome-wide association studies" (GWAS), used statistical methods which minimized the risk of false positive reports and provided much greater power to detect genotype-phenotype associations. All findings were entirely data-driven rather than hypothesis-driven, which often made it difficult for researchers to understand or interpret the findings. Interestingly, this work in genetics is indicating how non-specific some genes are for psychiatric disorders, having associations in common for schizophrenia, bipolar disorder and autism. This suggests that the earlier stages of psychiatric disorders may be multi-valent and that early detection, coupled with a clearer understanding of the environmental factors, may allow prevention. At the present time, the rich "harvest" from GWAS still has very limited power to predict the variation in psychiatric disease status at individual level, typically explaining less than 5% of the total risk variance. The most recent studies of common genetic variation implicated the role of major histocompatibility complex in schizophrenia and other disorders. They also provided molecular evidence for a substantial polygenic component to the risk of psychiatric diseases, involving thousands of common alleles of very small effect. The studies of structural genetic variation, such as copy number variants (CNV), coupled with the efforts targeting rare genetic variation (using the emerging whole-genome "deep" sequencing technologies) will become the area of the greatest interest in the field of genetic epidemiology. This will be complemented by the studies of epigenetic phoenomena, changes of expression at a large scale and understanding gene-gene interactions in complex networks using systems biology approaches. A deeper understanding of the underlying biology of psychiatric disorders is essential to improve diagnoses and therapies of these diseases. New technologies - genome-wide association studies, imaging and the optical manipulation of neural circuits - are promising to provide novel insights and lead to new treatments.