the SMR analysis21 (see below) to identify genes associated with brain-related phenotypes and disorders. If we had selected the top-associated cis-eQTLs in blood and compared their effects with those in brain, we would likely suffer a form of winner’s curse. To avoid the potential ascertainment bias, we selected the top cis-eQTLs in a reference tissue, i.e., GTEx-muscle (n = 361) or CMC (n = 467; independent of GTEx), using a stringent P-value threshold that is required for the SMR analysis21 (see below), and estimated rb between brain and blood using these SNPs (Supplementary Fig. 3). Although this strategy uses only a quarter of all genes, the estimates of rb should be valid (see below). Note that the estimates of local and distal rg at all SNPs14 would be more informative for other gene-trait association methods such as TWAS22 and MetaXcan23 that use all SNPs in a prediction analysis framework. We chose SMR (URLs) because of one of its features (i.e., the HEIDI test) to filter out associations due to linkage21.
