GWAS meta-analysis of 16 790 patients with Barrett's oesophagus and oesophageal adenocarcinoma identifies 16 novel genetic risk loci and provides insights into disease aetiology beyond the single marker level

Julia Schröder, Laura Chegwidden, Carlo Maj, Jan Gehlen, Jan Speller, Anne C. Böhmer, Oleg Borisov, Timo Hess, Nicole Kreuser, Marino Venerito, Hakan Alakus, Andrea May, Christian Gerges, Thomas Schmidt, Rene Thieme, Dominik Heider, Axel M. Hillmer, Julian Reingruber, Orestis Lyros, Arne DietrichAlbrecht Hoffmeister, Matthias Mehdorn, Florian Lordick, Gertraud Stocker, Michael Hohaus, Daniel Reim, Jennis Kandler, Michaela Müller, Alanna Ebigbo, Claudia Fuchs, Christiane J. Bruns, Arnulf H. Hölscher, Hauke Lang, Peter P. Grimminger, Dani Dakkak, Yogesh Vashist, Sandra May, Siegfried Görg, Andre Franke, David Ellinghaus, Sara Galavotti, Lothar Veits, Josef Weismüller, Jens Dommermuth, Udo Benner, Thomas Rösch, Helmut Messmann, Brigitte Schumacher, Horst Neuhaus, Carsten Schmidt, Thaddäus T. Wissinowski, Markus M. Nöthen, Jing Dong, Jue Sheng Ong, Matthew F. Buas, Aaron P. Thrift, Thomas L. Vaughan, Ian Tomlinson, David C. Whiteman, Rebecca Claire Fitzgerald, Janusz Jankowski, Michael Vieth, Andreas Mayr, Puya Gharahkhani, Stuart MacGregor, Ines Gockel, Claire Palles, Johannes Schumacher*

*Corresponding author for this work
2 Citations (Scopus)


Objective Oesophageal cancer (EC) is the sixth leading cause of cancer-related deaths. Oesophageal adenocarcinoma (EA), with Barrett's oesophagus (BE) as a precursor lesion, is the most prevalent EC subtype in the Western world. This study aims to contribute to better understand the genetic causes of BE/EA by leveraging genome wide association studies (GWAS), genetic correlation analyses and polygenic risk modelling. Design We combined data from previous GWAS with new cohorts, increasing the sample size to 16 790 BE/EA cases and 32 476 controls. We also carried out a transcriptome wide association study (TWAS) using expression data from disease-relevant tissues to identify BE/EA candidate genes. To investigate the relationship with reported BE/EA risk factors, a linkage disequilibrium score regression (LDSR) analysis was performed. BE/EA risk models were developed combining clinical/lifestyle risk factors with polygenic risk scores (PRS) derived from the GWAS meta-analysis. Results The GWAS meta-analysis identified 27 BE and/or EA risk loci, 11 of which were novel. The TWAS identified promising BE/EA candidate genes at seven GWAS loci and at five additional risk loci. The LDSR analysis led to the identification of novel genetic correlations and pointed to differences in BE and EA aetiology. Gastro-oesophageal reflux disease appeared to contribute stronger to the metaplastic BE transformation than to EA development. Finally, combining PRS with BE/EA risk factors improved the performance of the risk models. Conclusion Our findings provide further insights into BE/EA aetiology and its relationship to risk factors. The results lay the foundation for future follow-up studies to identify underlying disease mechanisms and improving risk prediction.

Original languageEnglish
Issue number4
Pages (from-to)612-623
Number of pages12
Publication statusPublished - 04.2023

Research Areas and Centers

  • Research Area: Medical Genetics
  • Research Area: Luebeck Integrated Oncology Network (LION)
  • Centers: University Cancer Center Schleswig-Holstein (UCCSH)

DFG Research Classification Scheme

  • 205-14 Haematology, Oncology

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