Identification of loci of functional relevance to Barrett's esophagus and esophageal adenocarcinoma: Cross-referencing of expression quantitative trait loci data from disease-relevant tissues with genetic association data

Esophageal adenocarcinoma (EA) and its precancerous condition Barrett's esophagus (BE) are multifactorial diseases with rising prevalence rates in Western populations. A recent meta -analysis of genome-wide association studies (GWAS) data identified 14 BE/EA risk loci located in non-coding genomic regions. Knowledge about the impact of non-coding variation on disease pathology is incomplete and needs further investigation. The aim of the present study was (i) to identify candidate genes of functional relevance to BE/EA at known risk loci and (ii) to find novel risk loci among the suggestively associated variants through the integration of expression quantitative trait loci (eQTL) and genetic association data. eQTL data from two BE/EA-relevant tissues (esophageal mucosa and gastroesophageal junction) generated within the context of the GTEx project were cross-referenced with the GWAS meta-analysis data. Variants representing an eQTL in at least one of the two tissues were categorized into genome-wide significant loci (P < 5x10(-8)) and novel candidate loci (5x10(-8) <= P <= 5x10(-5)). To follow up these novel candidate loci, a genetic association study was performed in a replication cohort comprising 1,993 cases and 967 controls followed by a combined analysis with the GWAS meta-analysis data. The cross-referencing of eQTL and genetic data yielded 2,180 variants that represented 25 loci. Among the previously reported genome-wide significant loci, 22 eQTLs were identified in esophageal mucosa and/or gastroesophageal junction tissue. The regulated genes, most of which have not been linked to BE/EA etiology so far, included C2orf43/LDAH, ZFP57, and SLC9A3. Among the novel candidate loci, replication was achieved for two variants (rs7754014, P-combined = 3.16x10(-7) and rs1540, P-combined = 4.16x10(-6)) which represent eQTLs for CFDP1 and SLC22A3, respectively. In summary, the present approach identified candidate genes whose expression was regulated by risk variants in