Once SNPs with genome-wide significant association were identified, we identified LD-independent genomic regions using PLINK clumping (--clump-r2=0.4, --clump-kb=500, --clump-p1=5e-08, --clump-p2=5e-02). Genomic regions were merged if they physically overlap using bedtools. Due to extensive LD, the MHC region was considered as one region (chr6:25–35Mb). To detect secondary signals independent of index SNP in each of the candidate cross-disorder loci, conditional analysis was performed with GCTA-COJO (Yang et al., 2012) using meta-analysis summary statistics from ASSET. 1KG EUR population was used as the reference panel for estimating LD. For each genomic region harboring a cross-disorder signal, we tested the presence of any additional associated SNPs using a stepwise procedure (--cojo-slct), conditioning on the primary significant SNP for model initiation. A conditional p-value for each variant was reported, adjusted for genomic control and collinearity. In each region, additional SNPs were selected as a distinct association signal if having a conditional p-value < 1e-06.
