In a post-hoc analysis, we specified the p-factor in the context of a bifactor model5,6 in which the p-factor and four domain-specific factors are orthogonal to one another and directly predict the 11 disorders (Fig. 1d). In contrast to the hierarchical model, the bifactor model allows for direct associations between p and the 11 disorders. We identified 66 independent hits on the bifactor p-factor, including the two hits for the hierarchical p-factor (Supplementary Table 29). Among these 66 hits, 38 were in LD with hits from the correlated factors model, eight were novel relative to univariate hits, and seven were novel relative to both univariate and correlated factors hits. We identified 76 QSNP hits, 50 of which were in LD with hierarchical p, QSNP hits (Supplementary Table 31). Although the bifactor specification of p produced more factor hits than did the hierarchical specification, the pattern of results with respect to the large number of QSNP hits and high overall mean χ2 of QSNP was similar, and the LDSC genetic correlation across these two specifications of p was > 0.99. Collectively, these results indicate low utility of either specification of the p-factor at the level of individual genetic variants.
