In this study we generated two large eQTL databases for LCLs that identify robust local and distant eQTLs for more than 14,000 genes. This is more than six times larger than our previous eQTL database (Dixon et al. 2007), which has been used to identify association with expression for SNPs associated with asthma (Moffatt et al. 2007), Crohn's disease (Libioulle et al. 2007), and type 1 diabetes (Plagnol et al. 2009). Even before publication, our two newly developed eQTL databases have been used to interpret findings from large-scale GWAS, including human height (Lango Allen et al. 2010), body mass index (Speliotes et al. 2010), waist–hip ratio (Heid et al. 2010), osteoporosis-related traits (Hsu et al. 2010), Graves' disease (Chu et al. 2011), pancreatic cancer (Wu et al. 2012), and pathways associated with basal cell skin carcinoma (Zhang et al. 2012). Our systematic investigation of the GWAS database presented in Supplemental Table 3 suggests that eQTL analyses may add to the understanding of many other loci mapped for complex genetic diseases.
