The first GWASs of schizophrenia and bipolar disorder have recently been published, and many more are in progress. Large international collaborations have been initiated to combine GWAS data sets in order to increase statistical power, the largest being the Psychiatric GWAS Consortium, which is expected to publish its first results in 2010 (The Psychiatric GWAS Consortium Steering Committee 2009). Currently available research findings suggest that the variants identified through GWASs confer only small individual risks. The major limitation of GWASs is that they are only able to investigate common variants. If a large fraction of the genetic contribution is conferred by rare variants, other approaches will be necessary to identify them. A successful first step in this direction has been the identification of associations between rare CNVs and psychiatric diseases, in particular schizophrenia. However, due to methodological constraints, this approach remains restricted to the investigation of aberrations of at least several thousand base pairs. Continuing technological developments will provide future studies with increasing resolution, and the availability of low-cost whole genome sequencing technology will ultimately make it possible to obtain the complete genomic sequences of large patient samples for comparison with controls. In principle, this will allow the systematic identification of rare variants that are associated with disease risk, although the existence of a myriad of rare variants in the human genome will render this a complex task. It is hoped that some rare variants confer a larger disease risk, as this will facilitate the detection of association in large case-control samples. Rare variants with small disease risk may be extremely difficult to detect, since prohibitively large sample sizes may be required to demonstrate any significant association.
It is likely, however, that even after the identification of all common and rare risk variants a substantial fraction of the familial clustering will remain unexplained. This “missing heritability” in complex diseases is the subject of intense debate and several potential explanations have been proposed, including epistasis and epigenetic mechanisms.62-64
It will be necessary to apply specific research strategies to further investigate this issue, although these may require prohibitively large sample sizes or tissue samples that are difficult to access in human subjects.
It is not yet clear whether any of the association findings identified by GWASs represent causal variants. Systematic resequencing of the associated genomic regions will provide a comprehensive overview of such variants. In cases where association findings are due to linkage disequilibrium, it is possible that the causal variants have a stronger genetic effect than has been previously suspected. It is also theoretically possible that a given association finding is not attributable to a common causal variant. A simulation study has shown that the “synthetic” effect of multiple rare variants may be responsible for signals detected for common variants. It has also been shown that the location of these variants may be relatively far (up to 2 megabases) from the site identified in GWASs.65
If this were the case for an associated locus, resequencing over large genomic distances in large samples would be required to identify the true causative variants. Ultimately, it is necessary to identify a direct functional effect for each potential causal variant, such as an effect on the function or expression of a gene.
GWASs performed to date have indicated that certain genes contribute to a susceptibility to both schizophrenia and bipolar disorder. It is clear that some of these genes convey a rather nonspecific susceptibility that overlaps diagnostic boundaries, and it is highly probable that this also overlaps with other psychiatric disorders. Other genes, however, convey specific effects. Future studies of the phenotypic dimensions that are most strongly associated with a specific gene will include analysis of clinical symptoms and endophenotypes. The latter may be particularly suited to guiding researchers in the selection of the most promising phenotypes for animal studies.66
The identification of disease-associated genes is likely to increase our knowledge of the underlying pathophysiology of psychiatric disorders in an as-yet unforeseen manner. The identification of biological pathways has the potential to revolutionize diagnostics and treatment.?