The first successful application of polygenic score analysis to GWAS data was in schizophrenia [3], in which few individual markers were significant and the common disease common variant hypothesis remained in question. It was shown that a large mass, up to half, of all markers in one GWAS could be jointly associated with disease in a second sample, implying a polygenic component to disease risk that justified larger study sizes [4]. Furthermore, markers from schizophrenia GWAS could together be associated with bipolar disorder, and vice versa, establishing a common polygenic basis to those conditions, whereas such cross-prediction was not achieved with clinically distinct conditions such as cardiovascular disease. This common basis has further been exploited to discriminate sub-types of bipolar disorder [5].
