Four methods, weighted median [28], inverse-variance weighted (IVW, random-effects model) [27], and MR-Egger [29], implemented in the R package “MendelianRandomization v0.3.0” [68], MR-PRESSO [30], and GSMR [31] were used for MR inference. Evidence of average pleiotropic effects was examined by the MR-Egger intercept test, where a non-zero intercept indicates horizontal pleiotropy [29]. Individual variants with horizontal pleiotropy were detected by MR-PRESSO, and an outlier test was applied to correct horizontal pleiotropy via outlier removal. Pleiotropic variants were also detected by the HEIDI test in GSMR, and removed from causal inference. Instrumental variants that are associated with outcome (p < 5 × 10−8) were removed. For instrumental variants missing in the outcome summary data, we used the results of the best-proxy variant with the highest LD (r2 > 0.8) with the missing variant. If the MAF of the missing variant was < 0.01, or none of the variants within 200 kb had LD r2 > 0.8, we removed the instrumental variant from the analysis. Palindromic SNPs (A/T or G/C alleles) with MAF [0.4, 0.5], which can introduce ambiguity into the identity of the effect allele, were also removed.
