The factor structure described above is based on average effects across the genome, but does not address more fine-grained cross-disorder effects at the level of genomic regions or individual loci. To identify genetic loci with shared risk, we performed a meta-analysis of the eight neuropsychiatric disorders using a fixed-effects-based method (Bhattacharjee et al., 2012) that accounts for the differences in sample sizes, existence of subset-specific effects, and overlapping subjects across datasets (Online Methods). The standardized genomic inflation factor was close to one, suggesting no inflation of test statistics due to confounding (λ1000 = 1.005; Fig. 2a). We identified 136 LD-independent regions with genome-wide significant association (Pmeta ≤ 5×10−8). Due to the extensive LD at the major histocompatibility complex (MHC) region (chromosome 6 region at 25–35 Mb), we considered multiple signals present there as one locus. 101 of the 136 (74.3%) significantly associated regions overlapped with previously reported genome-wide significant regions from at least one individual disorder, while 35 loci (25.7%) represented novel genome-wide significant associations. Simulation analyses confirmed that the number of pleiotropic loci we identified exceeds chance expectation given
