학술논문
A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer
Document Type
article
Author
Evangelina López de Maturana; Juan Antonio Rodríguez; Lola Alonso; Oscar Lao; Esther Molina-Montes; Isabel Adoración Martín-Antoniano; Paulina Gómez-Rubio; Rita Lawlor; Alfredo Carrato; Manuel Hidalgo; Mar Iglesias; Xavier Molero; Matthias Löhr; Christopher Michalski; José Perea; Michael O’Rorke; Victor Manuel Barberà; Adonina Tardón; Antoni Farré; Luís Muñoz-Bellvís; Tanja Crnogorac-Jurcevic; Enrique Domínguez-Muñoz; Thomas Gress; William Greenhalf; Linda Sharp; Luís Arnes; Lluís Cecchini; Joaquim Balsells; Eithne Costello; Lucas Ilzarbe; Jörg Kleeff; Bo Kong; Mirari Márquez; Josefina Mora; Damian O’Driscoll; Aldo Scarpa; Weimin Ye; Jingru Yu; PanGenEU Investigators; Montserrat García-Closas; Manolis Kogevinas; Nathaniel Rothman; Debra T Silverman; SBC/EPICURO Investigators; Demetrius Albanes; Alan A Arslan; Laura Beane-Freeman; Paige M Bracci; Paul Brennan; Bas Bueno-de-Mesquita; Julie Buring; Federico Canzian; Margaret Du; Steve Gallinger; J Michael Gaziano; Phyllis J Goodman; Marc Gunter; Loic LeMarchand; Donghui Li; Rachael E Neale; Ulrika Peters; Gloria M Petersen; Harvey A Risch; Maria José Sánchez; Xiao-Ou Shu; Mark D Thornquist; Kala Visvanathan; Wei Zheng; Stephen J Chanock; Douglas Easton; Brian M Wolpin; Rachael Z Stolzenberg-Solomon; Alison P Klein; Laufey T Amundadottir; Marc A Marti-Renom; Francisco X Real; Núria Malats
Source
Genome Medicine, Vol 13, Iss 1, Pp 1-18 (2021)
Subject
Language
English
ISSN
1756-994X
Abstract
Abstract Background Pancreatic cancer (PC) is a complex disease in which both non-genetic and genetic factors interplay. To date, 40 GWAS hits have been associated with PC risk in individuals of European descent, explaining 4.1% of the phenotypic variance. Methods We complemented a new conventional PC GWAS (1D) with genome spatial autocorrelation analysis (2D) permitting to prioritize low frequency variants not detected by GWAS. These were further expanded via Hi-C map (3D) interactions to gain additional insight into the inherited basis of PC. In silico functional analysis of public genomic information allowed prioritization of potentially relevant candidate variants. Results We identified several new variants located in genes for which there is experimental evidence of their implication in the biology and function of pancreatic acinar cells. Among them is a novel independent variant in NR5A2 (rs3790840) with a meta-analysis p value = 5.91E−06 in 1D approach and a Local Moran’s Index (LMI) = 7.76 in 2D approach. We also identified a multi-hit region in CASC8—a lncRNA associated with pancreatic carcinogenesis—with a lowest p value = 6.91E−05. Importantly, two new PC loci were identified both by 2D and 3D approaches: SIAH3 (LMI = 18.24), CTRB2/BCAR1 (LMI = 6.03), in addition to a chromatin interacting region in XBP1—a major regulator of the ER stress and unfolded protein responses in acinar cells—identified by 3D; all of them with a strong in silico functional support. Conclusions This multi-step strategy, combined with an in-depth in silico functional analysis, offers a comprehensive approach to advance the study of PC genetic susceptibility and could be applied to other diseases.