The majority of the disease risk variants identified by genome wide association studies (GWAS) fall inside of non-coding regions, leading to the conclusion that their effects are likely to be mediated by regulation of gene expression or other molecular phenotypes. This highlights the value of utilizing multiple molecular phenotype QTLs (collectively, xQTLs) to establish the link between the regulatory genetic variant (risk allele) and various traits and diseases. In this study we will employ DNA methylation QTL, expression QTL, histone QTL, protein QTL and metabolite QTL data from peripheral blood to map shared genetic influences on multiple intermediate molecular traits in GWAS and EWAS associated loci and investigate the molecular pathways in which they play a role.