eQTL set-based association analysis identifies novel susceptibility loci for Barrett's esophagus and esophageal adenocarcinoma
Abstract
Background: Over 20 susceptibility single-nucleotide polymorphisms (SNPs) have been identified for esophageal adenocarcinoma (EAC) and its precursor, Barrett's esophagus (BE), explaining a small portion of heritability.
Methods: Using genetic data from 4,323 BE and 4,116 EAC patients aggregated by international consortia including the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON), we conducted a comprehensive transcriptome-wide association study (TWAS) for BE/EAC, leveraging Genotype Tissue Expression (GTEx) gene expression data from six tissue types of plausible relevance to EAC etiology: mucosa and muscularis from the esophagus, gastroesophageal (GE) junction, stomach, whole blood, and visceral adipose. Two analytical approaches were taken: standard TWAS using the predicted gene expression from local expression quantitative trait loci (eQTLs), and set-based SKAT association using selected eQTLs that predict the gene expression.
Results: While the standard approach did not identify significant signals, the eQTL set-based approach identified eight novel associations, three of which were validated in independent external data (eQTL SNP sets for EXOC3, ZNF641 and HSP90AA1).
Conclusions: This study identified novel genetic susceptibility loci for EAC and BE using an eQTL set based genetic association approach.
Impact: This study expanded the pool of genetic susceptibility loci for EAC and BE, suggesting the potential of the eQTL set based genetic association approach as an alternative method for TWAS analysis.
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Esophageal adenocarcinoma, Esophagus, eQTLs
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Wang, X. et al. (2022) ‘eQTL set-based association analysis identifies novel susceptibility loci for Barrett’s esophagus and esophageal adenocarcinoma’, Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology [Preprint].
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Cancer Epidemiology, Biomarkers & Prevention