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000178220 1001_ $$0P:(DE-He78)ebb819874e9553d89bd480e6811dc0f3$$aLu, Ye$$b0$$eFirst author$$udkfz
000178220 245__ $$aIdentification of Recessively Inherited Genetic Variants Potentially Linked to Pancreatic Cancer Risk.
000178220 260__ $$aLausanne$$bFrontiers Media$$c2021
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000178220 520__ $$aAlthough 21 pancreatic cancer susceptibility loci have been identified in individuals of European ancestry through genome-wide association studies (GWASs), much of the heritability of pancreatic cancer risk remains unidentified. A recessive genetic model could be a powerful tool for identifying additional risk variants. To discover recessively inherited pancreatic cancer risk loci, we performed a re-analysis of the largest pancreatic cancer GWAS, the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), including 8,769 cases and 7,055 controls of European ancestry. Six single nucleotide polymorphisms (SNPs) showed associations with pancreatic cancer risk according to a recessive model of inheritance. We replicated these variants in 3,212 cases and 3,470 controls collected from the PANcreatic Disease ReseArch (PANDoRA) consortium. The results of the meta-analyses confirmed that rs4626538 (7q32.2), rs7008921 (8p23.2) and rs147904962 (17q21.31) showed specific recessive effects (p<10-5) compared with the additive effects (p>10-3), although none of the six SNPs reached the conventional threshold for genome-wide significance (p < 5×10-8). Additional bioinformatic analysis explored the functional annotations of the SNPs and indicated a possible relationship between rs36018702 and expression of the BCL2L11 and BUB1 genes, which are known to be involved in pancreatic biology. Our findings, while not conclusive, indicate the importance of considering non-additive genetic models when performing GWAS analysis. The SNPs associated with pancreatic cancer in this study could be used for further meta-analysis for recessive association of SNPs and pancreatic cancer risk and might be a useful addiction to improve the performance of polygenic risk scores.
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000178220 650_7 $$2Other$$agenetic polymorphisms
000178220 650_7 $$2Other$$agenome-wide association study
000178220 650_7 $$2Other$$apancreatic cancer
000178220 650_7 $$2Other$$arecessive model
000178220 650_7 $$2Other$$asusceptibility
000178220 7001_ $$aGentiluomo, Manuel$$b1
000178220 7001_ $$0P:(DE-He78)b791a47b92809f7c54501331f72e0243$$aMacauda, Angelica$$b2$$udkfz
000178220 7001_ $$aGioffreda, Domenica$$b3
000178220 7001_ $$aGazouli, Maria$$b4
000178220 7001_ $$aPetrone, Maria C$$b5
000178220 7001_ $$aKelemen, Dezső$$b6
000178220 7001_ $$aGinocchi, Laura$$b7
000178220 7001_ $$aMorelli, Luca$$b8
000178220 7001_ $$aPapiris, Konstantinos$$b9
000178220 7001_ $$aGreenhalf, William$$b10
000178220 7001_ $$aIzbicki, Jakob R$$b11
000178220 7001_ $$aKiudelis, Vytautas$$b12
000178220 7001_ $$aMohelníková-Duchoňová, Beatrice$$b13
000178220 7001_ $$aBueno-de-Mesquita, Bas$$b14
000178220 7001_ $$aVodicka, Pavel$$b15
000178220 7001_ $$0P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2$$aBrenner, Hermann$$b16$$udkfz
000178220 7001_ $$aDiener, Markus K$$b17
000178220 7001_ $$aPezzilli, Raffaele$$b18
000178220 7001_ $$aIvanauskas, Audrius$$b19
000178220 7001_ $$aSalvia, Roberto$$b20
000178220 7001_ $$aSzentesi, Andrea$$b21
000178220 7001_ $$aAoki, Mateus Nóbrega$$b22
000178220 7001_ $$aNémeth, Balázs C$$b23
000178220 7001_ $$aSperti, Cosimo$$b24
000178220 7001_ $$aJamroziak, Krzysztof$$b25
000178220 7001_ $$aChammas, Roger$$b26
000178220 7001_ $$aOliverius, Martin$$b27
000178220 7001_ $$aArchibugi, Livia$$b28
000178220 7001_ $$aErmini, Stefano$$b29
000178220 7001_ $$aNovák, János$$b30
000178220 7001_ $$aKupcinskas, Juozas$$b31
000178220 7001_ $$aStrouhal, Ondřej$$b32
000178220 7001_ $$aSouček, Pavel$$b33
000178220 7001_ $$aCavestro, Giulia M$$b34
000178220 7001_ $$aMilanetto, Anna C$$b35
000178220 7001_ $$aVanella, Giuseppe$$b36
000178220 7001_ $$aNeoptolemos, John P$$b37
000178220 7001_ $$aTheodoropoulos, George E$$b38
000178220 7001_ $$avan Laarhoven, Hanneke W M$$b39
000178220 7001_ $$aMambrini, Andrea$$b40
000178220 7001_ $$aMoz, Stefania$$b41
000178220 7001_ $$aKala, Zdenek$$b42
000178220 7001_ $$aLoveček, Martin$$b43
000178220 7001_ $$aBasso, Daniela$$b44
000178220 7001_ $$aUzunoglu, Faik G$$b45
000178220 7001_ $$aHackert, Thilo$$b46
000178220 7001_ $$aTestoni, Sabrina G G$$b47
000178220 7001_ $$aHlaváč, Viktor$$b48
000178220 7001_ $$aAndriulli, Angelo$$b49
000178220 7001_ $$aLucchesi, Maurizio$$b50
000178220 7001_ $$aTavano, Francesca$$b51
000178220 7001_ $$aCarrara, Silvia$$b52
000178220 7001_ $$aHegyi, Péter$$b53
000178220 7001_ $$aArcidiacono, Paolo G$$b54
000178220 7001_ $$aBusch, Olivier R$$b55
000178220 7001_ $$aLawlor, Rita T$$b56
000178220 7001_ $$aPuzzono, Marta$$b57
000178220 7001_ $$aBoggi, Ugo$$b58
000178220 7001_ $$0P:(DE-He78)0311ebf3415e41860b4e2c56fbae6919$$aGuo, Feng$$b59$$udkfz
000178220 7001_ $$aMałecka-Panas, Ewa$$b60
000178220 7001_ $$aCapurso, Gabriele$$b61
000178220 7001_ $$aLandi, Stefano$$b62
000178220 7001_ $$aTalar-Wojnarowska, Renata$$b63
000178220 7001_ $$aStrobel, Oliver$$b64
000178220 7001_ $$0P:(DE-He78)8218df9f6f41792399cd3a29b587e4e7$$aGao, Xin$$b65$$udkfz
000178220 7001_ $$aVashist, Yogesh$$b66
000178220 7001_ $$aCampa, Daniele$$b67
000178220 7001_ $$0P:(DE-He78)5323704270b6393dcea70186ffd86bca$$aCanzian, Federico$$b68$$eLast author$$udkfz
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