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Polymorphisms in transcription factor binding sites and enhancer regions and pancreatic ductal adenocarcinoma risk. 2024
Pelin Ünal, and
Ye Lu, and
Bas Bueno-de-Mesquita, and
Casper H J van Eijck, and
Renata Talar-Wojnarowska, and
Andrea Szentesi, and
Maria Gazouli, and
Edita Kreivenaite, and
Francesca Tavano, and
Ewa Małecka-Wojciesko, and
Bálint Erőss, and
Martin Oliverius, and
Stefania Bunduc, and
Mateus Nóbrega Aoki, and
Ludmila Vodickova, and
Ugo Boggi, and
Matteo Giaccherini, and
Jurate Kondrackiene, and
Roger Chammas, and
Orazio Palmieri, and
George E Theodoropoulos, and
Maarten F Bijlsma, and
Daniela Basso, and
Beatrice Mohelnikova-Duchonova, and
Pavel Soucek, and
Jakob R Izbicki, and
Vytautas Kiudelis, and
Giuseppe Vanella, and
Paolo Giorgio Arcidiacono, and
Barbara Włodarczyk, and
Thilo Hackert, and
Ben Schöttker, and
Faik G Uzunoglu, and
Franco Bambi, and
Mara Goetz, and
Viktor Hlavac, and
Hermann Brenner, and
Francesco Perri, and
Silvia Carrara, and
Stefano Landi, and
Péter Hegyi, and
Frederike Dijk, and
Evaristo Maiello, and
Giovanni Capretti, and
Sabrina Gloria Giulia Testoni, and
Maria Chiara Petrone, and
Hannah Stocker, and
Stefano Ermini, and
Livia Archibugi, and
Manuel Gentiluomo, and
Giulia Martina Cavestro, and
Raffaele Pezzilli, and
Gregorio Di Franco, and
Anna Caterina Milanetto, and
Cosimo Sperti, and
John P Neoptolemos, and
Luca Morelli, and
Klara Vokacova, and
Claudio Pasquali, and
Rita T Lawlor, and
Francesca Bazzocchi, and
Juozas Kupcinskas, and
Gabriele Capurso, and
Daniele Campa, and
Federico Canzian
Genomic Epidemiology Group, German Cancer Research Center, In Neuenheimer Feld 280, 69120, Heidelberg, Germany.
Genome-wide association studies (GWAS) are a powerful tool for detecting variants associated with complex traits and can help risk stratification and prevention strategies against pancreatic ductal adenocarcinoma (PDAC). However, the strict significance threshold commonly used makes it likely that many true risk loci are missed. Functional annotation of GWAS polymorphisms is a proven strategy to identify additional risk loci. We aimed to investigate single-nucleotide polymorphisms (SNP) in regulatory regions [transcription factor binding sites (TFBSs) and enhancers] that could change the expression profile of multiple genes they act upon and thereby modify PDAC risk. We analyzed a total of 12,636 PDAC cases and 43,443 controls from PanScan/PanC4 and the East Asian GWAS (discovery populations), and the PANDoRA consortium (replication population). We identified four associations that reached study-wide statistical significance in the overall meta-analysis: rs2472632(A) (enhancer variant, OR 1.10, 95%CI 1.06,1.13, p = 5.5 × 10-8), rs17358295(G) (enhancer variant, OR 1.16, 95%CI 1.10,1.22, p = 6.1 × 10-7), rs2232079(T) (TFBS variant, OR 0.88, 95%CI 0.83,0.93, p = 6.4 × 10-6) and rs10025845(A) (TFBS variant, OR 1.88, 95%CI 1.50,1.12, p = 1.32 × 10-5). The SNP with the most significant association, rs2472632, is located in an enhancer predicted to target the coiled-coil domain containing 34 oncogene. Our results provide new insights into genetic risk factors for PDAC by a focused analysis of polymorphisms in regulatory regions and demonstrating the usefulness of functional prioritization to identify loci associated with PDAC risk.
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