López de Maturana, EvangelinaRodríguez, Juan AntonioAlonso, LolaLao, OscarMolina-Montes, EstherMartín-Antoniano, Isabel AdoraciónGómez-Rubio, PaulinaLawlor, RitaCarrato, AlfredoHidalgo, ManuelIglesias, MarMolero, XavierLöhr, MatthiasMichalski, ChristopherPerea, JoséO'Rorke, MichaelBarberà, Victor ManuelTardón, AdoninaFarré, AntoniMuñoz-Bellvís, LuísCrnogorac-Jurcevic, TanjaDomínguez-Muñoz, EnriqueGress, ThomasGreenhalf, WilliamSharp, LindaArnes, LuísCecchini, LluísBalsells, JoaquimCostello, EithneIlzarbe, LucasKleeff, JörgKong, BoMárquez, MirariMora, JosefinaO'Driscoll, DamianScarpa, AldoYe, WeiminYu, JingruGarcía-Closas, MontserratKogevinas, ManolisRothman, NathanielSilverman, Debra TAlbanes, DemetriusArslan, Alan ABeane-Freeman, LauraBracci, Paige MBrennan, PaulBueno-de-Mesquita, BasBuring, JulieCanzian, FedericoDu, MargaretGallinger, SteveGaziano, J MichaelGoodman, Phyllis JGunter, MarcLeMarchand, LoicLi, DonghuiNeale, Rachael EPeters, UlrikaPetersen, Gloria MRisch, Harvey ASánchez, María-JoséShu, Xiao-OuThornquist, Mark DVisvanathan, KalaZheng, WeiChanock, Stephen JEaston, DouglasWolpin, Brian MStolzenberg-Solomon, Rachael ZKlein, Alison PAmundadottir, Laufey TMarti-Renom, Marc AReal Arribas, FranciscoMalats, Nuria2024-02-192024-02-192021-02-01Genome Med . 2021 ;13(1):15http://hdl.handle.net/20.500.12105/18218BACKGROUND: 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.engVoRhttp://creativecommons.org/licenses/by-nc-nd/4.0/Genetic Predisposition to DiseaseGenome-Wide Association StudyBiomarkers, TumorCell Line, TumorComputer SimulationGene Regulatory NetworksGenome, HumanHumansLinkage DisequilibriumPancreatic NeoplasmsReproducibility of ResultsSignal TransductionAttribution-NonCommercial-NoDerivatives 4.0 Internacional335178871311510.1186/s13073-020-00816-41756-994XGenome medicineopen access