Genome-wide studies of copy number variation (CNV) have given rise to a new understanding of schizophrenia etiology, bringing rare variants to the forefront: rare variant-common disease (RDCV) model. Earlier, we conducted low resolution CNV screening using affimetrix 5.0 array in order to catalog CNVs that may increase the schizophrenia susceptibility in the Japanese population. In our current study, we are using high resolution comparative genomic hybridization array for the CNV detection. Besides the known large CNVs that are previously reported to be associated with schizophrenia we found hundreds of small to medium size novel, exon disrupting sequence variations in more than 10 % of patients with schizophrenia. These findings point to the number of genomic variants that may be relevant to the pathoetiology of schizophrenia were below the detection threshold of last generation CNV typing technologies.
In conclusion, our results showed that in case of schizophrenia, the 'rare high risk variant' vs the 'common variant with low effect' hypotheses should not be viewed as exclusive hypotheses, but more as a continuum. That is why direct resequencing of candidate genes, as well as CNV on the one side, and GWAS on the other side, could be viewed as complementary approaches to dissect the genetic susceptibilities