With the Brain-eMeta eQTL data (neff = 1194) obtained from the meta-analysis above, we applied the SMR approach21,46 to test for associations of gene expression levels with four brain-related phenotypes, i.e., ever-smoked (smoking), fluid intelligence score (IQ), years of education (EduYears), and schizophrenia (SCZ). GWAS data were from published meta-analyses for EduYears and SCZ47,48, and from analyses of the full release of the UK Biobank data for smoking and IQ (Methods and Supplementary Table 6). LD data required for the HEIDI test21 were estimated from genotyped/imputed data of the Health and Retirement Study (HRS)49. LD r2 from HRS were strongly correlated with those from CMC (Supplementary Fig. 22), consistent with the observation from previous studies26. For power comparison, we included in the SMR analysis an additional set of blood eQTL data from a sample of 14,115 individuals from the eQTLGen Consortium. Only the genes with at least one cis-eQTL at PeQTL < 5 × 10−8 (one of the basic assumptions of SMR) in both Brain-eMeta and eQTLGen were included. We further excluded genes in the major histocompatibility complex (MHC) region
