We applied the HEIDI-outlier approach to remove SNPs that showed pleiotropic effects on both risk factor and disease, significantly deviated from a causal model (Methods). The LD correlations between pairwise SNPs were estimated from the Atherosclerosis Risk in Communities (ARIC) data33 (n = 7703 unrelated individuals) imputed to 1000 Genomes (1000G)34. Using the large data sets described above, we identified from GSMR analyses 45 significant causative associations between risk factors and diseases (Supplementary Data 1; Fig. 2). We controlled the family-wise error rate (FWER) at 0.05 by Bonferroni correction for 231 tests (PGSMR threshold = 2.2 × 10−4). For method comparison, we have also performed the analyses with MR-Egger13 and the methods in Pickrell et al.16 (Supplementary Data 2).
