Lopez de Maturana, EvangelinaRodriguez, Juan AntonioAlonso, LolaLao, OscarMolina-Montes, EstherMartin-Antoniano, Isabel AdoracionGomez-Rubio, PaulinaLawlor, RitaCarrato, AlfredoHidalgo, ManuelIglesias, MarMolero, XavierLöhr, MatthiasMichalski, ChristopherPerea, JoseO'Rorke, MichaelBarbera, Victor ManuelTardon, AdoninaFarre, AntoniMuñoz-Bellvis, LuisCrnogorac-Jurcevic, TanjaDominguez-Muñoz, EnriqueGress, ThomasGreenhalf, WilliamSharp, LindaArnes, LuisCecchini, LluisBalsells, JoaquimCostello, EithneIlzarbe, LucasKleeff, JörgKong, BoMárquez, MirariMora, JosefinaO'Driscoll, DamianScarpa, AldoYe, WeiminYu, JingruGarcia-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 ASanchez-Perez, Maria-JoseShu, Xiao-OuThornquist, Mark DVisvanathan, KalaZheng, WeiChanock, Stephen JEaston, DouglasWolpin, Brian MStolzenberg-Solomon, Rachael ZKlein, Alison PAmundadottir, Laufey TMarti-Renom, Marc AReal, Francisco XMalats, Nuria2023-02-092023-02-092020-12-03López de Maturana E, Rodríguez JA, Alonso L, Lao O, Molina-Montes E, Martín-Antoniano IA, et al. A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer. Genome Med. 2021 Feb 1;13(1):15.http://hdl.handle.net/10668/17074Pancreatic 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. 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. 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. 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.enAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/3D genomic structureGenetic susceptibilityGenome-wide association analysisLocal indices of genome spatial autocorrelationPancreatic cancer riskBiomarkers, TumorCell Line, TumorComputer SimulationGene Regulatory NetworksGenetic Predisposition to DiseaseGenome, HumanGenome-Wide Association StudyHumansLinkage DisequilibriumPancreatic NeoplasmsReproducibility of ResultsSignal Transductionresearch article33517887open accessBiomarcadores de tumorDesequilibrio de ligamientoEstudio de asociación del genoma completoGenoma humanoHumanosLínea celular tumoralNeoplasias pancreáticasPredisposición genética a la enfermedadRedes reguladoras de genesReproducibilidad de los resultadosSimulación por computadorTransducción de señal10.1186/s13073-020-00816-41756-994XPMC7849104https://doi.org/10.1186/s13073-020-00816-4https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7849104/pdf