To generate a more comprehensive database of mQTLs in the fetal brain and identify more examples where the same SNP is associated with both DNA methylation and disease, we imputed our genotype data using the most recent panel downloaded from the 1000 Genome Project (see Online Methods). Using an imputed set of 5,177,320 variants we identified an additional 256,040 mQTLs, which reflected the non-imputed dataset in terms of genomic distribution and observed effect sizes (Supplementary Table 2 and Supplementary Fig. 12). The full list of fetal brain mQTLs after imputation can be downloaded from: http://epigenetics.essex.ac.uk/mQTL//All_Imputed_BonfSignificant_mQTLs.csv.gz. Our imputed data enabled us to identify 1,067 instances where the same SNP is associated with both DNA methylation and schizophrenia, with a comprehensive list available for download from: http://epigenetics.essex.ac.uk/mQTL//PGC_IndexSNPs_QTLs_Inc2PCs_AllTissues_MatchS NPPosition.csv). Because they could be biased by the LD structure at associated loci the imputed mQTL data were not used for subsequent enrichment analyses, but they enabled us to further refine schizophrenia candidate regions and undertake co-localization analyses in order to identify variants associated with both DNA methylation and schizophrenia. We performed a Bayesian co-localization
