Inherited genetics represents an important contributor to risk of esophageal adenocarcinoma (EAC), and its precursor Barrett's esophagus (BE). Genome-wide association studies have identified ∼30 susceptibility variants for BE/EAC, yet genetic interactions remain unexamined. To address challenges in large-scale G×G scans, we combined knowledge-guided filtering and machine learning approaches, focusing on genes with (A) known/plausible links to BE/EAC pathogenesis (n=493) or (B) prior evidence of biological interactions (n=4,196). ∼75 x 106 SNP×SNP interactions were screened via hierarchical group lasso (glinternet) using BEACON GWAS data. The top ∼2000 interactions retained in each scan were prioritized using P values from single logistic models. Identical scans were repeated among males only (78%), with two independent GWAS datasets used for replication. In overall and male-specific primary replications, 11 of 187 and 20 of 191 interactions satisfied P<0.05, respectively. The strongest evidence for secondary replication was for rs17744726×rs3217992 among males, with consistent directionality across all cohorts (Pmeta=2.19×10-8); rs3217992 "T" was associated with reduced risk only in individuals homozygous for rs17744726 "G". Rs3217992 maps to the CDKN2B 3'UTR and reportedly disrupts microRNA-mediated repression. Rs17744726 maps to an intronic enhancer region in BLK. Through in-silico prioritization and experimental validation, we identified a nearby proxy variant (rs4841556) as a functional modulator of enhancer activity. Enhancer-gene mapping and eQTLs implicated BLK and FAM167A as targets. The first systematic G×G investigation in BE/EAC, this study uncovers differential risk associations for CDKN2B variation by BLK genotype, suggesting novel biological dependency between two risk loci encoding key mediators of tumor suppression and inflammation.
Read full abstract