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American Association for Cancer Research, Cancer Epidemiology, Biomarkers & Prevention, 9(31), p. 1735-1745, 2022

DOI: 10.1158/1055-9965.epi-22-0096

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eQTL Set–Based Association Analysis Identifies Novel Susceptibility Loci for Barrett Esophagus and Esophageal Adenocarcinoma

Journal article published in 2022 by Xiaoyu Wang ORCID, Puya Gharahkhani ORCID, David M. Levine ORCID, Rebecca C. Fitzgerald ORCID, Ines Gockel ORCID, Douglas A. Corley ORCID, Harvey A. Risch ORCID, Leslie Bernstein ORCID, Wong-Ho Chow ORCID, Lynn Onstad ORCID, Nicholas J. Shaheen ORCID, Jesper Lagergren ORCID, Laura J. Hardie ORCID, Anna H. Wu ORCID, Paul D. P. Pharoah ORCID and other authors.
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Data provided by SHERPA/RoMEO

Abstract

Abstract Background: Over 20 susceptibility single-nucleotide polymorphisms (SNP) have been identified for esophageal adenocarcinoma (EAC) and its precursor, Barrett 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 (eQTL), and set-based SKAT association using selected eQTLs that predict the gene expression. Results: Although 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.